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The Lipophorin Receptor of Drosophila melanogaster
By
Richard Dunbar‐Yaffe
A thesis submitted in conformity with the requirements for the degree of Master of Science
Graduate Department of Ecology & Evolutionary Biology
University of Toronto School of Graduate Studies
© Copyright by Richard Dunbar‐Yaffe, 2008
Abstract Title: The Lipophorin Receptor of Drosophila melanogaster
By Richard Dunbar‐Yaffe
Degree: M.Sc.
Department: Ecology and Evolutionary Biology
University of Toronto
Year: 2008
Animals carry lipids such as hydrocarbons, fats, and sterols throughout their circulatory systems bound
to a carrier protein known as lipophorin. The lipophorin receptor has been characterized in locusts,
mosquitoes and cockroaches yet little is known about it in Drosophila melanogaster. To this end, an
antibody against the eleven variants of the lipophorin receptor was developed and tested. Although this
was the main feature of the work, several preliminary experiments using RNA interference were
conducted to determine the effects of lipophorin receptor. Flies whose lipophorin receptor proteins
were knocked down were found to have no major differences in locomotor activity in total darkness
suggesting that their circadian rhythms are unaffected. The same flies were found to have extensive
differences in their cuticular hydrocarbon profiles as compared with wild‐type flies. Whole‐mount tissue
staining of Drosophila adult brains revealed that several cells in the central nervous system are
immunoreactive with the anti‐Lipophorin receptor antibody.
ii
Contents
Chapter 1 – Mechanics of Insect Lipid Synthesis and Transport ............................................................ 1
Introduction .............................................................................................................................................. 1
Functions of Insect Hydrocarbons ............................................................................................................ 2
Metabolism of Insect Lipids ...................................................................................................................... 3
Transport of Insect Hydrocarbons ............................................................................................................ 6
Lipophorin – The Insect Lipid Transporter ............................................................................................... 7
The Lipophorin Receptor ........................................................................................................................ 11
Conclusion .............................................................................................................................................. 18
Chapter 2 – Characterization of the Drosophila Lipophorin Receptor ................................................. 20
Introduction ............................................................................................................................................ 20
Methods ................................................................................................................................................. 24
Fly Food and Rearing Conditions ........................................................................................................ 24
Creating Homozygous UAS‐DCR2; LpR1/2 RNA Interference Lines ................................................... 24
Molecular Cloning and Microbiology ................................................................................................. 25
Polyacrylamide Gel Electrophoresis and Western Blotting ................................................................ 26
Haemolymph Collection and Purification ........................................................................................... 27
Ligand Blotting .................................................................................................................................... 28
Antibody Conditions ........................................................................................................................... 28
Collection and Gas Chromatography of Cuticular Hydrocarbons ...................................................... 28
Activity Monitoring ............................................................................................................................. 29
Tissue Staining and Confocal Microscopy .......................................................................................... 29
Results .................................................................................................................................................... 30
Subcloning LpR2 into an Expression Vector ....................................................................................... 30
Verifying Correct Insertion of LpR2 into pET21B ................................................................................ 35
Generation of anti‐LpR Serum ............................................................................................................ 38
Western Blot Testing of LpRv1 ........................................................................................................... 40
Ligand Blotting Assay .......................................................................................................................... 45
Effects of Lipophorin Receptor RNAi .................................................................................................. 49
iii
iv
Whole‐Mount Tissue Staining Using LpRv1 ........................................................................................ 71
Discussion ............................................................................................................................................... 75
LpRv1 Recognizes the Lipophorin Receptor ....................................................................................... 75
The Lipophorin Receptor Binds Lipophorin ........................................................................................ 77
Circadian Rhythms are not Affected by the Lipophorin Receptor ..................................................... 79
Cuticular Hydrocarbons are Affected by the Lipophorin Receptor .................................................... 80
The Lipophorin Receptor is Present in the Brain ................................................................................ 83
Conclusions and Future Directions ..................................................................................................... 84
Appendix ........................................................................................................................................... 86
Subcloning of desat1 .......................................................................................................................... 86
Overexpression of desat(3), esat(2) and per(2) for Immunization .................................................. 88 d
Testing of desat(3) and perSv1 ........................................................................................................... 90
Cited References ................................................................................................................................ 93
Chapter 1 – Mechanics of Insect Lipid Synthesis and Transport
Introduction
The importance of lipids is evidenced by the host of research that has been conducted in an attempt to
learn about their metabolism, transport, function, and regulation in a variety of organisms. Lipids are
essential macromolecules; phospholipid compounds create the membranes that separate cellular and
organellar contents from the outside world. Lipid precursors are biosynthesized into fat‐soluble
hormones involved in the regulation of gene expression. Lipid waxes on the cuticles of insects protect
them from desiccation, have functions in their immune systems, and act as signaling and communication
devices. Finally, lipids serve as a source of long‐term energy to be used in periods of starvation as well
as to sustain strenuous activities such as flight in insects. Lipids are not soluble in water; the necessity of
their movement throughout an animal’s aqueous circulatory system is therefore a unique problem.
Though a number of rewarding applications to studying lipids relate to humans, primary research
requires model organisms. Insects are studied for several reasons (Soulages and Wells, 1994). Insects
have a short life cycle and fast generational time allowing scientists to perform a variety of
manipulations in a short period of time. In addition, insects are extremely diverse; it is likely that with
such diversity various biologically adapted solutions to the common problem of lipid transport are
present (Soulages and Wells, 1994). Also, many insects have sequenced genomes with available
mutants at almost any genetic locus. Such genetic manipulation allows researchers to validate their
claims and place them in both physiological and genetic contexts. Despite their diversity, insects seem
to retain a number of the evolutionary pathways employed by higher organisms with respect to a
number of their physiological activities (Soulages and Wells, 1994), making them doubly useful as study
organisms.
The focus of this chapter will be to review lipid and hydrocarbon transport in insects. Because it places
the concepts of this chapter in a more familiar context, mammalian lipid transport will also be discussed.
A cursory overview of lipid synthesis focused on hydrocarbons will be given. Lipophorin, the protein
molecule used to transport lipids in insects will be discussed with a focus on hydrocarbon transport.
While the roles of lipophorin have received attention over the past few decades, its receptor has been
1
largely ignored. This receptor forms the basis of this thesis and work related to it will hence be given a
large proportion of this chapter. This material should serve as an introduction to the scope of this
thesis: lipid and hydrocarbon transport in Drosophila and its implications on the behavioural,
communicatory and physiological aspects of hydrocarbons in Drosophila melanogater. Work in this area
comprises a fascinating scientific conquest because it exemplifies the diversity with which both insects
and mammals approach the fundamentally similar problem of lipid transport.
Functions of Insect Hydrocarbons
Insects produce a layer of cuticular wax on their cuticles that would be most analogous to the oils on
human skin or the wax in animal ears. A wealth of information is contained in these waxes as they vary
among individuals (Howard and Blomquist, 2005). Function‐wise, they can be broken into two specific
subgroups of roles: metabolic and communication. The term “communication” encompasses a broad
set of roles for the hydrocarbons. Firstly, they are involved in species recognition and mate recognition
(Howard and Blomquist, 2005). Species recognition is effected by a number of volatile or non‐volatile
hydrocarbons on the surface of the animal. These hydrocarbons often differ in small ways between the
sexes of one species allowing potential mate recognition (Howard and Blomquist, 2005). Secondly,
hydrocarbons convey information in social contexts about task‐specific cues (such as those of an ant in
its colony), cues as to the dominance or fertility of a mate, and cues about dangerous predators that
some species have evolved to mimic (Howard and Blomquist, 2005; Sevala et al., 2000).
In the fruit fly Drosophila melanogaster much work has been done related to hydrocarbons and mating
cues. When a male fly detects the presence of a female through her hydrocarbon cues, a series of
courtship behaviours begins (Jallon, 1984; Jallon and Hotta, 1979). The male orients himself toward the
female after following her for some time. He then extends his wings to ‘sing’ a courtship song that is
species specific and is thought to convey information about his fertility and dominance (O'Dell, 2003).
The male may then lick the female’s genitals and copulate (O'Dell, 2003); the female may display a series
of behaviours most likely understood to be rejecting the male (Jallon, 1984). If the female is receptive,
however, she may deposit a volatile mixture of hydrocarbons from her ovipositor that increase the
excitement of the male and induce copulation (Ferveur, 2005).
Due to their relevance in studies of courthship behaviour, hydrocarbons on the fly have been the subject
of intense analysis. This is made feasible with the use of gas chromatography. Many researchers have
employed this method to identify and quantify hydrocarbons on the cuticle of the insect (Ferveur, 2005;
2
Jallon, 1984; Jallon and Hotta, 1979). Hydrocarbons are easily collected by washing the cuticle of the fly
in an organic solvent such as hexane; this hexane can then be subjected to gas chromatography. In
general, a single fly of the Drosophila species will have between one and twenty micrograms of total
cuticular hydrocarbon on its cuticle (Ferveur, 2005). Work on chemical cues in Drosophila has revealed
that, while saturated alkanes do not usually induce behaviours, unsaturated hydrocarbons do (Jallon,
1984). It has been demonstrated that the attractiveness of one fly to another is heavily dependent on
its hydrocarbon possession (Jallon and Hotta, 1979). The sensing of hydrocarbons to signal the presence
of a good mate seems to trump other mating cues; Drosophila males will actively court one another in
the presence of volatile hydrocarbons isolated from virgin Drosophila females (Tompkins et al., 1980).
Hydrocarbon sensing seems to occur either through contact with the gustatory organs of the legs or the
olfactory organs of the antennae (Stocker, 1994). Specific to Drosophila melanogaster, male
hydrocarbons appear to be monounsaturates while female hydrocarbons can be doubly unsaturated,
yielding a specific sexual cue to males (Jallon, 1984).
Metabolism of Insect Lipids
Mammals use a battery of
lipid transport techniques
(Fredrickson and Gordon,
1958); upon ingestion, lipids
(in the form of large, low
density particles called
chylomicrons) are taken in
through lacteals within the
small intestine and
transported through the
lymphatic system until they
reach the blood‐borne
circulatory system at the
thoracic duct. They are then
degraded by tissues which
require energy to form
Figure 1 represents a schematic of mammalian lipid transport (Rodenburg and Van derHorst, 2005). Mammals use a battery of different lipid transport molecules. Dietarylipids are packaged by the intestine into chylomicrons which can then be absorbedand stored by adipose; remnants are endocytosed into the liver. The liver repackageslipids into lipoproteins of very low, low, or intermediate density (VLDL, LDL, IDL).When these lipoproteins are endocytosed by tissues they lose fat content and theirdensity increases upon resecretion, forming high density lipoproteins or HDL.
3
Figure 2 A schematic of insect lipid transport (Rodenburg and Van der Horst, 2005). Liverand adipose tissue are functionally replaced by the fat body which synthesizes lipophorinparticles. Lipids absorbed through the gut are passed directly to lipophorin particlesthrough an unknown mechanism. Lipophorin transports lipids to the fat body for storageand processing or to using tissues for energy. Note the simplicity of the insect system oflipid transport and the efficient reusability of the shuttle‐like lipophorin which is notendocytosed and reprocessed at each stage of transport.
chylomicron remnants which are processed in the liver into very low density lipoproteins (VLDL) (see
figure 1). VLDL is secreted from the liver as a cholesterol‐rich and lipid rich carrier molecule; during its
time in the circulatory system
it can be degraded by using
tissues into lipoproteins
which range in density and
are named as such (low
density lipoproteins,
intermediate density
lipoproteins, high density
lipoproteins and very high
density lipoproteins). As
lipids are consumed from
these lipoprotein particles
their densities rise due to
the increased protein to lipid
ratio. At each stage of
consumption, the
lipoproteins are
endocytosed, processed, and then released back into the circulatory system with more or less lipid.
Much of the reloading of lipids takes place in the liver. High density lipoprotein (HDL) has a scavenging
role in picking up excess cholesterol and lipid; it is able to do this as a result of its high density and
relatively low fat and cholesterol content. HDL also serves as a source of apolipoproteins during
exchanges with lipoproteins of lower densities.
The insects which have been studied, by contrast, rely on a single, more versatile transport component
called lipophorin (see figure 2). Upon ingestion of dietary lipid, cells within the midgut of the animal
process the lipids into diacylglycerols (DAG; glycerol esterified to two fatty acid chains) (Shapiro et al.,
1988). In contrast to mammals who transport almost exclusively triacylglycerols (TAG), insects
exclusively transport dietary lipids in the form of DAG (Shapiro et al., 1988). Despite this, 98% of stored
lipid appears to be in the form of TAG (Chino and Gilbert, 1964). No reason for this discrepancy is
apparent. Once the DAG is synthesized by the cells of the midgut, it is released into haemolymph (insect
blood) at which point it binds with the transport particle lipophorin (Chino and Downer, 1982). In
4
contrast to mammalian lipid transport, exogenous (ingested) and endogenous (synthesized) lipids are
transported through the circulatory system by lipophorin. The fat body (the insect equivalent to the
mammalian liver and adipose tissue) synthesizes the nascent particles of lipophorin whose structure
will be discussed further (Shapiro et al., 1988).
The release of lipids, either from dietary sources or stored sources, is regulated. Over 40 years ago it
was demonstrated that a factor within haemolymph (now understood to be lipophorin) elicited the
release of lipids from the fat body into the haemolymph where they could partner with lipophorin
(Chino and Gilbert, 1964). In addition, these studies demonstrated that the release is an active process
(Chino and Gilbert, 1964). It was also shown that insect lipophorins are closely related and structurally
similar because, at least in the cases of the insects studied, lipophorins were able to elicit release of
lipids from cultured fat bodies of a different species. Lipids do not leak into the haemolymph; cultured
fat bodies released almost no lipids in the presence of biological buffers but very large amounts in the
presence of haemolymph (Chino and Gilbert, 1964).
The hydrocarbons of insects comprise an important group of communicatory and defensive lipids.
Rudimentary evidence led to the original hypothesis that large, cuticle or fat body associated cells called
oenocytes (sometimes spelled “enocytes”) synthesize the hydrocarbons that form cuticular wax (Piek,
1964). Modern evidence now supports the role of oenocytes as hydrocarbon producers (Diehl, 1975;
Fan et al., 2003). Most communicatory hydrocarbons are desaturated at a position nine carbons from
the carbonyl group (Chertemps et al., 2006; Dallerac et al., 2000; Wicker‐Thomas et al., 1997). The
desaturation reaction is important both empirically, due to the observation that saturated hydrocarbons
usually have little behavioural effect (Jallon, 1984), and experimentally as its ablation can result in a
variety of social problems (Coyne and Elwyn, 2006a, b; Fang et al., 2002). Desaturation reactions (at
least in Drosophila melanogaster and sechellia) appear to be sexually dimorphic; female flies display a
large amount of doubly unsaturated hydrocarbons (dienes) while they are absent on male flies (Jallon,
1984; Wicker‐Thomas et al., 1997). Both sexes desaturate hydrocarbons at the 9‐position with the
enzyme desat1 (Dallerac et al., 2000; Wicker‐Thomas et al., 1997) but a genetic discrepancy between
the two sexes causes females to desaturate some hydrocarbons a second time (Chertemps et al., 2006).
Because newly‐emerged flies of both sexes display similar hydrocarbon profiles (Jallon et al., 1980),
there has been speculation that sex‐specific hormonal control of hydrocarbon desaturation may be
responsible for the extra double bond, possibly by enabling expression of the female‐specific desaturase
5
desatF in female flies of D. melanogaster and sechellia (Chertemps et al., 2006; Wicker and Jallon,
1995a, b).
Transport of Insect Hydrocarbons
After the work of Piek, the function of oenocytes was
reinvestigated in the desert locust S. gregaria (Diehl,
1975). It was noted that oenocytes (found associated
with the fat body in this animal) contain large amounts of
smooth endoplasmic reticulum which is consistent with a
role in producing lipid‐soluble compounds (Diehl, 1975).
Cultured oenocytes also interact with labeled acetate to
produce labeled hydrocarbons common to cuticular wax
(Diehl, 1975). Finally, it was shown that labeled
hydrocarbons did not leak into the incubation medium
unless it contained haemolymph (Diehl, 1975). This study
suggests an in vivo role for the rapid release of
hydrocarbons from the oenocytes where they are
synthesized into the haemolymph though it is unlikely
that hydrocarbons serve any direct function in the
circulatory system. More likely instead is that the
haemolymph serves to transport hydrocarbons within
the animal.
Oe
LpR
Tr
?
Lp
Figure 3 Possible schemes for hydrocarbon transportbetween the oenocytes (open white circles) and thecuticle (dark curved lines). Black lines representexperimentally verified pathways while dashed linesrepresent possible pathways for hydrocarbon delivery.Hydrocarbons are produced in the oenocytes and loadedonto lipophorin (gradient‐filled hexagon). They may bethen loaded to the cuticle through interaction with alipophorin receptor (gradient rounded rectangles) or thetrachea of the animal (gradient cylinders). They may alsoload passively to the cuticle.
The advent of a rapid method for the purification of insect lipophorin (Chino et al., 1981b; Chino and
Kitazawa, 1981) led to a number of conclusions about the transport of hydrocarbons from their site of
synthesis (oenocytes) to their site of deposition (the cuticle of the insect). Lipophorin purified from both
the American cockroach and the locust was associated with large amounts of hydrocarbons in addition
to other lipids (Chino et al., 1981b). Of importance, however, was the continuity between the
hydrocarbons bound to lipophorin within the circulatory system and the hydrocarbons found on the
surface of the insects; such continuity was later observed in Drosophila preparations (Pho et al., 1996).
Because the hydrocarbons of the cuticular wax so strongly resembled those being transported in the
haemolymph, a model for transport in which lipophorin serves to “load” hydrocarbons from the
6
oenocytes and then “unload” them at the cuticle was formed (Chino and Downer, 1982). This was
confirmed during a number of experiments in which labeled hydrocarbons from dissected integuments
were found to flow into a medium containing purified lipophorin while they did not flow at all in a
medium devoid of it but otherwise physiologically acceptable (Fan et al., 2003; Katase and Chino, 1982).
In addition, the rate of hydrocarbon release (measured by radioactivity recovered in the medium) was
proportional to the concentration of lipophorin in the medium (Katase and Chino, 1982). Studies in
Drosophila have given further support to this model by demonstrating that the haemolymph pool of
hydrocarbons decreases in quantity with a concomitant increase in cuticular hydrocarbons (Pho et al.,
1996). Much in the same way that respiratory poisons inhibit the release of diacylglycerides (Chino and
Gilbert, 1964), they hamper the release of hydrocarbons into the haemolymph suggesting a mutual
mechanism of lipid transport (Katase and Chino, 1982). These combined observations suggest a
mechanism of haemolymph transport of hydrocarbons from oenocyte to cuticle; there is a possibility,
however, that hydrocarbons are transported in some other fashion from lipophorin to the cuticle that is
not reliant on the circulatory system, though it is unlikely due to the observation that injected labeled
hydrocarbon in the haemocoel of cockroaches produces label on the cuticle of the animal (Katase and
Chino, 1982).
Though the above experiments support the assertion that hydrocarbons are loaded at their site of
synthesis and then deposited at the cuticle (Chino and Downer, 1982; Katase and Chino, 1982), they do
not explain the specificity with which hydrocarbons are exclusively unloaded (Katase and Chino, 1982).
This question is further complicated by the fact that the loading mechanism at the oenocytes appears to
be an active process similar in nature to the loading of diacylglycerides from the fat body. This does not
rule out the possibility that two separate loading mechanisms exist or that the relative quantities of
hydrocarbons in the oenocytes or diacylglycerols in the fat body encourage specific loading from one
mechanism. It should be noted that little is known about the direct mechanisms that allow loading of
hydrocarbons or lipids onto lipophorin at source points (oenocytes, fat body) or unloading at sinks
(cuticle, metabolic tissues).
Lipophorin – The Insect Lipid Transporter
In addition to its role as a lipid carrier, lipophorin is also the major Drosophila circulatory protein as
albumin is in mammals. Lipophorin allows the transport of various types of lipids (sterols, hydrocarbons,
fats) throughout the insect body via the haemolymph (Chino, 1985; Katase and Chino, 1982; Ryan and
7
van der Horst, 2000; Soulages and Wells, 1994). Its name was coined decades after its discovery from
the greek roots lipos (fat) and phoros (bearing) to reflect its multi‐use distinction from mammalian
lipoproteins which are degraded during function (Katase and Chino, 1982). Because the density of
lipophorin is close to that of high density lipoprotein in mammals, it is often referred to as HDLp or high
density lipophorin. Though studies on lipophorin structure, functionality, and lipid content have been
performed in multiple model species, the implications have been similar with many insect species so
there is no reason to suspect any difference in the Drosophila model system (Soulages and Wells, 1994).
Lipophorins of insects studied to date contain two subunits: ApoLpI and ApoLpII (Shapiro et al., 1984).
ApoLpI is the larger of the two proteins with an approximate molecular mass of 250 kDa in the studied
insects while ApoLpII is much smaller having an approximate mass of 75 kDa (Shapiro et al., 1984).
Stoichiometrically, there appear to be one of each of these apolipoprotein units in each lipophorin
particle (Pattnaik et al., 1979); this stands in contrast to mammalian lipoproteins which are composed of
many apoprotein subunits in a less regimented stoichiometric ratio (Shapiro et al., 1984). Despite
differences, lipophorins of insects are likely related to lipoproteins in mammals (Kashiwazaki and Ikai,
1985).
Recent cDNA cloning of the tobacco hornworm M. sexta suggests that both apolipoproteins are made
from the same precursor polypeptide that is cleaved to yield ApoLpI and ApoLpII (Sundermeyer et al.,
1996). The mechanism was later discovered to involve the serine protease furin in Locusta migratoria
(Smolenaars et al., 2005). In both physiological and ectopic expression experiments, however, it was
also discovered that nascent lipophorin particles with a molecular mass and density identical to wild‐
type lipophorin which behaves as wild‐type lipophorin can still be created in the absence of furin
(Smolenaars et al., 2005); this suggests either an alternate cleavage mechanism or an alternate and
equally effective tertiary structure of ApoLpI/II when uncleaved. Structural and functional information
about these liporproteins would be extremely valuable in characterizing binding properties with a
potential receptor; direct evidence of the structural roles of either ApoLpI or ApoLpII is lacking. Because
proteolytic sensitivity studies on native lipophorin indicate that the larger ApoLpI is more sensitive to
cleavage than its smaller counterpart, ApoLpII may be somehow buried within the lipophorin particle
structure and hence protected from proteolysis (Kashiwazaki and Ikai, 1985). If ApoLpII is sequestered
within the protein, a picture is painted in which ApoLpII and perhaps the neutral lipids being carried by
the lipophorin particle are surrounded by the much larger ApoLpI whose interaction with the aqueous
environment is more stable. Additionally, lipid binding may take place during translation (as is
suspected to occur with the mammalian homolog apoB) prior to cleavage; this would explain the
8
observation that uncleaved apoLpI/II precursor is able to bind lipids (Smolenaars et al., 2005). It should
be noted that the lack of protease sensitivity in ApoLpII could also be a reflection of the stability of its
tertiary structure and may not reveal positioning information at all (Soulages and Wells, 1994).
Information about the Drosophila versions of ApoLpI/II is less available; this is partially due to the
reduced popularity of Drosophila as a model organism for lipid transport, and partially due to cloning
and sequencing problems with the abnormally large mRNA thought to produce the proapolipoprotein
which forms ApoLpI and ApoLpII. The apolipophorin candidate gene was eventually located in
Drosophila in the 102F region of the fourth chromosome (Kutty et al., 1996). Because of its high affinity
for retinoid compounds and fatty acids, it was named RFABG (Retinoid and Fatty Acid Binding
Glycoprotein). The gene product is a 3351 amino acid precursor with a putative localization sequence in
the first 25 amino acids. Uncharacterized post‐translational mechanisms, similar to those of the furin
pathway in L. migratoria, are likely to cleave at the single consensus sequence in the proapolipoprotein
RXRR (Kutty et al., 1996; Smolenaars et al., 2005); such cleavage would yield the predicted 70kDa
protein as well as a >200kDa protein. A furin candidate gene has indeed been found in Drosophila and is
likely to participate in this cleavage (Smolenaars et al., 2005). Finally, the processed apolipoproteins
produced in Drosophila strongly resemble ApoLpI/II counterparts in other insects further supporting
their candidacy as lipophorin homologs (Kutty et al., 1996).
Due to the complex nature of the interaction between ApoLpI/II and carried lipids, neither
apolipoprotein leaves the lipophorin particle in solution. In some species, a third apolipoprotein,
ApoLpIII, exists and is exchangeable (Soulages and Wells, 1994). This protein appears to be found only
in insects which use lipids to fuel flight (Soulages and Wells, 1994) and may act as a molecular switch
depending on the lipid saturation of haemolymph‐borne lipid carriers (Weers and Ryan, 2003). Its
structure has been revealed through X‐ray crystallography at a resolution of 2.5 angstroms (Breiter et
al., 1991). This information is less valuable in understanding the mechanics of Drosophila lipid transport
because ApoLpIII has yet to be found in flies, bees, or roaches (Soulages and Wells, 1994) although
preliminary evidence of a new apolipophorin may correspond to ApoLpIII in Drosophila (Pho et al.,
1996).
A model (see figure 3) for the structure of L. migratoria ApoLpI/II has been produced through
comparisons with a solved X‐ray crystal structure of the lipovitellin protein of the silver lamprey as well
as human apolipoprotein B (Smolenaars et al., 2005). The structure is not entirely independent; it is
based on two existing structures linked together through sequence homology. Additionally, the
9
determined structure is only partially useful because in vivo the two apolipoproteins would be cleaved
and operating with an altered structure. Notwithstanding this, the predicted structure of L. migratoria
ApoLpI/II is useful because it has been demonstrated that uncleaved ApoLpI/II precursors assemble to a
structure similar to that of native lipophorin (Smolenaars et al., 2005). The predicted lipophorin
structure also shows similarity to mammalian apolipoprotein B suggesting that differences in circulatory
lipid transport between insects and mammals may be caused more by lipoprotein receptors than
lipoproteins themselves (Rodenburg and Van der Horst, 2005).
Figure 4 The insect apoLpI/II complex (left) and the mammalian apolipoprotein B (apoB) comlex (right) has been reproduced (Rodenburg and Van der Horst, 2005). These structures were generated using a modeling technique relying on sequence homology between apoLpI/II and a previously solved crystal structure. Homologous beta‐sheets are denoted by βA, βB and βC. Black arrows are directed towards unmodelled areas containing the furin sites which allow cleavage to create mature lipoprotein particles. Note the similarity between the two lipid transport proteins.
10
The Lipophorin Receptor
Animals have a great degree of control over the circulatory transport of their lipids. Specific types of
lipids, be they sterol, hydrocarbon or fat, can be unloaded at tissues as required. These tissues can vary
with time, developmental stage, metabolic need or function. It is no surprise, therefore, that something
more sophisticated than simple diffusion permits the entry of lipids from the circulatory system into
using tissues. In mammals, this function is performed by a variety of receptor molecules on cell surfaces
which internalize and degrade lipoproteins (Fredrickson and Gordon, 1958). In Drosophila and several
insect species, however, the function of lipoprotein reception is accomplished by a single protein family:
the lipophorin receptor.
Although mammalian lipoprotein receptors have been studied for a long time, the insect lipophorin
receptor is a new addition to this area of research. Its existence was first experimentally suggested in
the early 1980’s when lipophorin affinity was measured in homogenized fat body and muscle tissue of L.
migratoria (Hayakawa and Chino, 1984). That study found that both tissues had a high affinity for
purified lipophorin, confirming the existence of a receptor protein at the loading site for lipid transport
(the fat body) as well as the unloading site (the muscle). Additionally, injection of adipokinetic hormone
(AKH) had the effect of augmenting the receptivity of the tissues to lipophorin (Hayakawa and Chino,
1984); this augmentation was more apparent in the homogenized muscle tissue which seems
reasonable given that AKH is used to mobilize fat stores in insects who use lipids to fuel flight muscles
(Robinson and Goldsworthy, 1976). A later study using 14C‐lipophorin incubated with homogenized
flight muscle demonstrated an increase in radioactivity uptake relative to controls that was dependent
on lipophorin concentration (Hayakawa, 1987). This binding was drastically reduced by the addition of
excess unlabeled lipohporin which competed for binding sites. In addition, the specific binding analysis
suggested the existence of only one type of lipophorin binding site (Hayakawa, 1987). Prior to any
molecular or genetic characterization, these data present several important findings: binding of
lipophorin to its receptor in flight muscle tissue is specific and reversible with a Kd of approximately
40μg/mL. Additionally, there is either only one type of lipophorin receptor, or multiple types with
virtually identical binding affinities. This study also demonstrated that, at least in the case of the
receptor variant present on flight muscle, lipophorin is not internalized. 14C‐radioactivity inside the cell
membranes was found to remain at background levels when homogenates were incubated with 14C‐
lipophorin. These levels were found to increase, however, when homogenates were incubated with 14C‐
diacylglycerol‐lipophorin (Hayakawa, 1987).
11
Further studies were carried out in M. sexta. Radioactive experiments demonstrated that M. sexta
contains a saturable, single type of lipophorin receptor that did not internalize lipophorin as had been
surmised previously (Tsuchida and Wells, 1990). Ligand blotting experiments were also performed
wherein radioactively labeled lipophorin was incubated with SDS‐PAGE separated protein fractions of M.
sexta; the fractions which bound lipophorin had an apparent molecular mass of 120 kDa (Tsuchida and
Wells, 1990). The receptor was then purified using DEAE‐cellulose chromatography (Chino and Downer,
1982). Interestingly, the purified lipophorin receptor was able to distinguish between lipophorin in lipid‐
rich and lipid‐depleted states (Tsuchida and Wells, 1990). Although the details of the mechanism by
which the receptor may do this are unknown, Tsuchida and Wells speculate that the depleted lipophorin
could have a nominal size difference from the lipid‐rich lipophorin. In any case it seems reasonable that
such discrimination could exist because the Kd values, at least in M. sexta, suggest that the receptor is
permanently saturated with lipophorin; therefore, its preference for lipid‐rich lipophorin would increase
the turnover of lipid‐depleted lipophorin from the receptor and overall efficiency of lipid transport. Of
further interest is the possibility that the lipophorin receptor may be able to distinguish among all types
of lipophorin simply based on differences in density or particle size. It has been noted that lipophorin is
able to deposit a variety of lipids at different tissues despite few receptor variants in some species.
Perhaps a lipophorin particle carrying hydrocarbon destined for the cuticle has a different radius from
one carrying diacylglycerol destined for energy‐using tissues. If such a difference were to exist, it could
explain the method by which insects achieve a very deliberate degree of lipid transport specificity
through a very genetically compact method. Unfortunately, lipophorin preparation methods are still
underdeveloped with respect to this level of specificity; any current method of purifying lipophorin
yields a heterogeneous mixture of particle sizes; in addition there is not yet a standard method for
determination of the sizes of lipophorin particles and the various methods available produce conflicting
results (Soulages and Wells, 1994).
Despite the archetypal role for lipophorin as a reusable lipid shuttle, certain insect tissues have the
ability to internalize it (Dantuma et al., 1999). The first cloned lipophorin receptor of the locust was of
this type; it was found to be expressed largely in oocytes and young adult fat body with the purpose of
internalizing lipophorin as both a fat and protein source (Dantuma et al., 1999). The authors also
investigated the genetic regulation of the transcript of the newly cloned lipophorin receptor and
discovered it to decrease with age; this was not surprising because lipophorin endocytosis in the fat
body shows a similar decrease (Dantuma et al., 1999). This did not explain the affinity that older adult
12
fat bodies retain for lipophorin and suggests the existence of a different lipophorin receptor that does
not internalize lipophorin (Dantuma et al., 1999).
The receptor cloned by Dantuma et al was found to share homology with a class of mammalian
lipoprotein receptors. Mammalian lipoprotein receptors and the lipophorin receptor share conserved
domains. Usually, there is a signal peptide directing membrane insertion followed by a ligand‐binding
domain that is often rich in cysteine, followed by an EGF precursor domain, a linker, a single
transmembrane domain and a cytosolic domain (Yamamoto et al., 1984). The cytosolic domain often
contains the amino acid sequence FDNPVY which recruits clathrin to the receptor and aid in
internalization (Dantuma et al., 1999). The classic mammalian LDL receptor as well as the VLDL receptor
seem to fall into this group along with the newly‐cloned insect member (Dantuma et al., 1999;
Yamamoto et al., 1984).
Not long after the cloning of the first insect lipophorin receptor from the locust, a second endocytic
lipophorin receptor variant was cloned from the mosquito Aedes aegypti (Cheon et al., 2001). This
receptor was deemed AaLpRov and owes the final part of its name to the fact that it is expressed chiefly
in ovarian tissue. Its region‐specific expression in addition to its ability to internalize lipophorin suggest
a role in the endocytosis of both the lipid and protein content of lipophorin in order to furnish the yolk
of the developing oocytes with nutrients (Cheon et al., 2001). The predicted protein structure of
AaLpRov is extremely similar to that of the LmLpR and the vertebrate VLDL receptor. It comes from a
gene of approximately 3.5 kb producing an 1156 amino acid protein structure with a molecular mass of
128.9 kDa (Cheon et al., 2001).
The fat body lipophorin receptor of the wax moth, Galleria mellonella was identified through a
technique known as ligand blotting (Lee et al., 2003). Ligand blotting allows for the detection of a
receptor by first incubating electrophoresed whole or purified protein lysates with the ligand, then
detecting the ligand through the use of a specific antibody (Lee et al., 2003). In this case, Lee et al were
able to identify a 97 kDa protein whose binding with lipophorin was both rapid and saturable (Lee et al.,
2003). In addition, the binding kinetics were shown to be sensitive to the concentration of divalent
calcium ions in the medium; chelating agents such as EDTA abolished the binding ability of lipophorin to
its putative G. mellonella receptor further elucidating the mechanics of lipophorin‐receptor interactions
(Lee et al., 2003). Given that at least two types of lipophorin receptor exist (an endocytic form found
chiefly in oocytes and fat body and a non‐endocytic form found in using tissues) it was surprising that
the ligand blotting assay revealed a clear, single band at 97 kDa and not at least one additional band.
13
Perhaps the electrophoresis conditions destroyed the binding ability of only one receptor variant or
perhaps both receptor variants have similar molecular masses that are not distinguishable on the
polyacrylamide gels that were used. It was also found in this study that the developmental stage of the
animal had an effect on the quantity of the G. mellonella lipophorin receptor (Lee et al., 2003).
The appearance of multiple lipophorin receptor polypeptides may result from splice variants of few
genes. Evidence for this has already been shown in the mosquito where, shortly after the discovery of
the ovarian lipophorin receptor (Cheon et al., 2001) a fat body variant was cloned (Seo et al., 2003). The
fat body variant AaLpRfb has a predicted molecular mass of 99.3 kDa, around 30 kDa smaller than the
ovarian version (Cheon et al., 2001; Seo et al., 2003). Southern blot analysis was used to verify that the
transcripts for both receptor variants arose from the same genetic locus (Seo et al., 2003). Slight
differences were found to exist between the ovarian and fat body variants of the A. aegypti lipophorin
receptor. Though both versions contained the same five domains, the ovarian version had an additional
cysteine‐rich repeat in its ligand binding domain to give a total of eight repeats (Seo et al., 2003). The
seven repeats of the fat body lipophorin receptor match perfectly with repeats two through eight of the
ovarian variant (Seo et al., 2003). As with the G. mellonella lipophorin receptor (Lee et al., 2003), both
temporal and spatial expression patterns were observed (Seo et al., 2003).
Ovarian lipophorin receptor mRNA was found to peak just after the blood meal of the mosquito
presumably in order to rapidly store fats and proteins in developing oocytes during vitellogenesis (Seo et
al., 2003). Expression of the fat body lipophorin receptor was found to increase steadily post‐blood
Figure 5 Conserved domain orientations of various VLDL receptor homologs among insect species (Cheon et al., 2001). Note the relative similarity in the organization of the domains even among species only distantly related.
14
meal and to remain at high levels once the ovarian receptor mRNA levels subsided. It has been
suggested that the onset of fat body lipophorin receptor expression signals a change in the animal’s
physiology from that of vitellogenic needs (producing yolk protein and mobilizing fat for vitellogenesis)
to that of post‐vitellogenic needs which usually consist of fat storage in the fat body (Seo et al., 2003).
The notion that up or down‐regulation of the expression of the lipophorin receptor can be mediated by
physiological and/or temporal constraints is validated by work performed on the locust lipophorin
receptor (Van Hoof et al., 2003). Although the endocytic lipophorin receptor is downregulated in this
animal four days after ecydsis, its presence can be maintained by starving the animal (Van Hoof et al.,
2003); perhaps endocrine signals verifying adequate storage of required lipids in the fat body are
necessary for the downregulation of the receptor.
Currently, several lipophorin receptors have been cloned in many prominent insect species. These
include L. migratoria (Dantuma et al., 1999; Van Hoof et al., 2003), A. aegypti (Cheon et al., 2001; Seo et
al., 2003) and G. mellonella (Lee et al., 2003). In contrast to earlier work that suggested that the
lipophorin receptor does not internalize lipophorin and that lipophorin is a reusable shuttle (Hayakawa,
1987; Soulages and Wells, 1994; Tsuchida and Wells, 1990) each of the cloned receptors appears to be
endocytic. The question of whether or not the lipophorin receptor is endocytic was investigated in
cultured cell lines (Van Hoof et al., 2005). Fluroescence microscopy was used to track fluorescent labels
on lipophorin molecules during their incubation with Drosophila Schneider 2 (S2) cells. When these cells
had been transfected with L. migratoria LpR cDNA, internalization of the fluorescent signal was
observed; in addition the signal was stored in vesicles resembling the fate of internalized low‐density
lipoprotein in mammalian cells (Van Hoof et al., 2005). In addition, the researchers used L. migratoria
fat bodies that were known to express an LpR variant endogenously and observed the opposite
phenomenon: recycling of the lipophorin particles (Van Hoof et al., 2005). This suggests that the cell
type and physiological environment are contributing factors to whether or not lipophorin particles are
endocytosed by their receptor (Van Hoof et al., 2005). This seems reasonable because, as mentioned
with respect to A. aegypti LpR variants, different life stages as well as different conditions of energy
storage are likely to dictate the advantage of lipophorin internalization. This explanation ignores the
fact that there are likely to be several variants of the lipophorin receptor which has been demonstrated
more recently (Gopalapillai et al., 2006). It is therefore possible that, rather than (or perhaps in addition
to) physiological cues, the receptor variant expressed on the cell surface dictates whether or not the
lipophorin molecule will be internalized once it has docked at the receptor. An additional possibility is
15
that, despite the endocytic ability of some lipophorin receptor variants, the lipid payload carried by the
lipophorin determines endocytosis.
Given the observation that the lipophorin receptor could function differently depending on the cell type
on which it resides or which particular transcript variant created it, the location of lipophorin receptors
in the insect body is very important. More specifically, the spatial and temporal distributions of the
lipophorin receptor variants in each of the insect model systems studied would be a crucial revelation
for dissecting the pathways of insect lipid transport. A partial characterization of these isoforms was
recently published in the silkworm Bombyx mori which appears to have four LpR isoforms, all of which
arise from alternative splicing of a single genetic locus (Gopalapillai et al., 2006). The most notable facet
of this work is that the four isoforms whose cDNA were cloned (BmLpR1, BmLpR2, BmLpR3, and
BmLpR4) appeared to have quite restrictive expression patterns in the animal (Gopalapillai et al., 2006).
BmLpR1 seemed to be relatively ubiquitous throughout the animal with the highest expression levels
occurring in the adult and pupal ovaries; interestingly this transcript was also found prominently in the
brain. LpR1 is distinguished from the other receptor transcripts by an 81 base pair in‐frame insertion
resulting in 27 additional amino acids in the O‐linked oligosaccharide domain with unknown function.
LpR2 transcript levels were also high in pupal and adult ovaries, pupal malphigian tubules, and pupal fat
body and were moderate in other larval tissues. LpR3 expression was restricted to the fat body and
ovary with minor amounts appearing elsewhere. LpR4, interestingly, seemed to be exclusive to the
brain and central nervous system of the silkworm (Gopalapillai et al., 2006). In terms of its predicted
protein sequence, BmLpR4 is unique compared to those obtained for the rest of the silkworm isoforms
as well as those obtained for the locust and mosquito (Cheon et al., 2001; Dantuma et al., 1999;
Gopalapillai et al., 2006; Seo et al., 2003; Van Hoof et al., 2003). BmLpR4 contains an 18 amino acid
terminal sequence (within its cytosolic domain) that is almost completely unrelated to the five
sequences against which it was compared (Gopalapillai et al., 2006). In a similar manner to BmLpR4,
human apolipoprotein E receptor 2 is predominantly expressed in the brain and contains an additional
59 amino acids on its cytoplasmic tail as compared with all other members of the VLDL receptor family
(Li et al., 2001). It should be noted that both B. mori LpR variants expressed predominantly in neural
tissue (BmLpR1 and BmLpR4) contain a highly conserved internalization sequence FDNPVY and probably
possess some endocytic ability although it may depend on the type of cell expressing it or the
physiological conditions of the cell (Gopalapillai et al., 2006). Although it has been demonstrated that
these receptors both bind to lipophorin using the ligand binding assays described earlier, internalization
of lipophorin in this species has not been verified (Gopalapillai et al., 2006). It is also unclear why there
16
is a separate receptor variant expressed almost entirely in the brain of the silk moth. Recent evidence
procured in mammals suggests that lipoprotein receptors in neural tissue may have a role in the
signaling cascades required for proper central nervous system development (Herz and Bock, 2002).
The most recent lipophorin receptor characterization was that of the German cockroach Blattella
germanica (Ciudad et al., 2007). Two isoforms were cloned using cDNA. Both sequences were similar in
length (around 3.1 kilobases) and had predicted protein molecular masses of 96.6 and 99.2 kDa; the
larger protein was deemed BgLpR‐L while the shorter was BgLpR‐S (Ciudad et al., 2007). Reminiscent of
the difference between BmLpR1 and the other three B. mori LpRs, BgLpR‐L differs from BgLpR‐S only in
the presence of a 24 amino acid insertion in its O‐linked oligosaccharide domain (Ciudad et al., 2007).
The two B. germanica variants exhibit the internalization sequence FDNPVY in their cytoplasmic
domains (Ciudad et al., 2007). In contrast to the work of Gopalapillai, the two BgLpRs were found
ubiquitously throughout the tissues tested (Ciudad et al., 2007). Temporally there was a distribution
reminiscent of the mosquito lipophorin receptor whereby BgLpR‐L peaked in ovarian tissue during
vitellogenesis but both isoforms were approximately equally expressed in the fat body peaking after 4
days of age (Ciudad et al., 2007). It is also noteworthy that only a single band was observed when an
antibody raised against BgLpR was used in western blotting; the authors note that only a single
transcript may be translated (Ciudad et al., 2007). Another possibility however is that the resolution of
the western blotting technique was insufficient to distinguish proteins differing in molecular mass by
only 3 kDa. This seems reasonable because the band detected by the antibody has a higher apparent
molecular weight than its predicted molecular weight; post‐translational modifications, therefore, may
have more of an influence on protein migration than molecular mass alone and could cause the lighter
BgLpR‐S to slow its migration to equal that of BgLpR‐L. Furthermore, the authors looked for expression
of BgLpR only in ovarian and fat body tissue and concede that the missing protein product could be
translated in other tissues they had not explored (Ciudad et al., 2007). The authors were also the first to
use RNA interference (RNAi) to reduce levels of both BgLpR isoforms; knockdown of LpR RNA in the
ovary resulted in a reduced level of lipophorin in the same tissue compared with controls (Ciudad et al.,
2007). Similar treatment in the fat body, however, produced paradoxical results; mRNA levels dropped
dramatically as one would expect but lipophorin levels remained constant until the effects of the
interfering RNA diminished after three days (Ciudad et al., 2007).
17
Conclusion
By comparison with the vast amount of literature relating to mammalian lipid synthesis, function and
transport, the insect counterparts appear to be young areas of research. In terms of insect
hydrocarbons, nearly thirty years of work have gone into understanding their functions but much work
remains. At present, only certain behavioural effects of hydrocarbon pheromones have been well
documented. Recent work, however, introduces an entirely new circadian aspect to the synthesis of
hydrocarbons whereby the animal’s subjective time of day plays a critical role in the production and
display of cuticular hydrocarbons (Levine, unpublished).
Our understanding of the mechanisms of lipid transport in insects, despite many recent advances, is
basic. While there is a relative wealth of data supporting the theory that energetic lipids are loaded
from the fat body to lipophorin particles in the circulatory system, the details of this process are poorly
understood. In addition, once loaded into lipophorin particles, little is known about the unloading
process at, for example, using tissues or other sites. It should be noted that despite a concrete role for
lipophorin in the transport of hydrocarbon pheromones, even less is understood about the loading and
unloading of hydrocarbons at the oenocytes following synthesis or the cuticle preceding display.
Crystallographic studies of lipophorin in lipid‐rich or lipid‐depleted states as well as loaded with a variety
of lipids would be extremely useful in determining structure‐function relationships. Though there do
not appear to be multiple subtypes of lipophorin particles, one can only speculate that the degree of
lipid transport specificity achieved in insects precludes the absence of some recognition mechanism;
research into the methods through which lipophorin particles are recognized for unloading at one tissue
and not at another could provide insight into this conjecture.
The complex transport specificity could also be achieved through interactions between lipophorin and
its receptor and could possibly be mediated by the cellular environment of the receiving tissue. Some
insects have as many as four cloned lipophorin receptor sequences (Gopalapillai et al., 2006) but
databases for sequenced organisms, such as Drosophila melanogaster show eleven possible transcripts.
Once more, these sequences must be characterized through experimentation. The many lipophorin
receptor isoforms could be providing the degree of circulatory transport specificity observed. The other
pressing issue related to lipophorin receptors seems to be the question of whether or not they are
endocytic like their mammalian VLDL‐related receptor counterparts. Each cloned lipophorin receptor
appears endocytic while earlier experiments have demonstrated a lack of lipophorin uptake in various
tissues. Once more, lipophorin receptor subtypes or even the cellular environment could be causing the
18
discrepancy. Perhaps one of the more intriguing questions about VLDL‐related receptors in general
relates to why there appears to be (at least in mammals and insects) a brain and central nervous system
specific variant. An understanding of the physiological roles and anatomical placement of these and
other lipophorin receptor variants is undoubtedly underway and will most likely provide fascinating
insight into the lipid transport of insects.
The study of lipid transport in insects remains in its infancy especially when compared to the advances
made in the mammalian counterpart. In the case of Drosophila melanogaster, one of the most popular
genetic model organisms in use today, even less is known about lipid transport. This has created a
fundamental problem for researchers interested in hormones, pheromones and hydrocarbons, or lipid
metabolism in such a ubiquitous organism. In this work, the use of a polyclonal antibody against the
Drosophila lipophorin receptor sheds a small amount of light on a relatively unknown research topic. A
specific antibody has been developed which recognizes the lipophorin receptor and reacts with this
receptor on specific cells of the brain. In addition, a genetic knock‐down of this receptor using RNA
interference demonstrates that it may be involved in the mechanisms of the cuticular display of
Drosophila hydrocarbons. Hopefully this research will open the door to a more complete functional and
spatial description of the lipophorin receptor as well as the downstream physiological consequences
that may result from its ablation.
19
Chapter 2 – Characterization of the Drosophila Lipophorin Receptor
Introduction The passage of lipid compounds (fats, sterols, hydrocarbons, free fatty acids) throughout an organism
has been an extensive area of research. Most of this research, however, has been directed towards the
understanding of the mammalian mechanisms of lipid transport while comparatively little work has
focused on their insect counterparts. The mechanisms involved in lipid transport differ between insects
and mammals. Certain aspects of transport, however, such as the need to transport fatty acids, sterols
and lipids in conjunction with a protein carrier, are shared. Insects have a one‐size‐fits‐all transport
molecule called lipophorin that is responsible for the carriage of energetic lipids, hydrocarbons and
sterols of varying density (Chino, 1985; Chino and Downer, 1982; Chino et al., 1981a; Chino and Gilbert,
1965; Soulages and Wells, 1994). In addition to its functions in lipid transport, lipophorin is also the
major protein constituent of insect blood, or haemolymph (Chino et al., 1981a). In contrast to
mammalian lipoproteins which are composed of several small (approximately 40kDa) protein subunits
which vary considerably in their stoichiometric contribution to the lipoprotein particle, lipophorin is
composed of two protein subunits or apolipophorins: ApoLpI (250kDa) and ApoLpII (75kDa). These two
protein subunits are constant in the lipophorin structure and, in addition to the lipid payload carried by
the lipophorin, constititute its entire structure (Pattnaik et al., 1979; Shapiro et al., 1984). Despite their
differences, it is strongly evident that lipophorin is related evolutionaily to mammalian apolipoprotein B
(Kashiwazaki and Ikai, 1985). Firstly, both proteins are rich in β‐sheet secondary structure. Although
this may be a necessary component for lipid transport and would therefore represent convergent
evolution, the amino acid content of apolipoprotein B strongly resembles that of lipophorin
(Kashiwazaki and Ikai, 1985). Preliminary, structural studies seem to indicate a similar tertiary structure
of the two proteins (Rodenburg and Van der Horst, 2005). Finally, while it is well known that
mammalian lipoproteins are endocytosed by tissues and degraded intracellularly, lipophorin has been
shown to sometimes act as a reusable shuttle in accordance with the cell type to which it delivers its
payload and the physiological state of the insect (Hayakawa, 1987; Soulages and Wells, 1994; Tsuchida
and Wells, 1990; Van Hoof et al., 2005).
20
As in mammals, insects have a receptor for this transport molecule – the lipophorin receptor – which, in
contrast to mammalian lipoprotein receptors, is relatively versatile (Soulages and Wells, 1994). The
insect lipophorin receptor replaces the host of density‐specific receptors found in mammals (Fredrickson
and Gordon, 1958). Receptors of lipophorin have been studied in several insect species including the
locust (Dantuma et al., 1999; Dantuma et al., 1996; Hayakawa, 1987; Van Hoof et al., 2003), tobacco
hornworm (Tsuchida and Wells, 1990), mosquito (Cheon et al., 2001; Sappington et al., 1996; Seo et al.,
2003), german cockroach ([Anon], 2004; Ciudad et al., 2007) and silkworm (Gopalapillai et al., 2006).
The lipophorin receptor shares several features with the mammalian very low density lipoprotein (VLDL)
receptor. It contains a ligand binding domain which is comprised of a varying number of cysteine‐rich
repeats, an EGF‐precursor domain, an O‐linked oligosaccharide domain, a single transmembrane
spanning domain as well as a small cytosolic domain (Cheon et al., 2001). The cytosolic receptor
domains of several insect species retain variants of the well‐conserved internalization sequence FDNPVY
which is thought to recruit clathrin to the cell surface and facilitate endocytosis (Dantuma et al., 1999).
It remains unclear why these internalization sequences appear to promote lipophorin endocytosis in
only some cases.
In Drosophila there are two variants of the lipophorin receptor: LpR1 (Accession No. CG31092,
Chromosome 3R 96F1‐96F2) and LpR2 (Accession No. CG31095, Chromosome 3R 96E10‐96F1). At least
six predicted LpR1 splice variants are thought to exist, each producing peptides with a distinct molecular
weight (LpR1‐PA, 98.3kDa; LpR1‐PB, 114kDa; LpR1‐PC, 102.7kDa; LpR1‐PD, 92.3kDa; LpR1‐PE, 109.5kDa;
LpR1‐PF, 118.4kDa). The final seven exons of the gene are constantly expressed except in the case of
LpR1‐PD which is missing exon 4. LpR2 is also thought to produce several peptides of varying molecular
weight (LpR2‐PA, 113.2kDa; LpR2‐PB, 91.6kDa; LpR2‐PC, 113.2; LpR2‐PD, 41.1kDa; LpR2‐PE, 117kDa;
LpR2‐PF, 95.4kDa; LpR2‐PG, 116.9kDa). Several exons at the 3’ end of the transcript are constant in all
variants but variability in splicing seems higher than that of LpR1.
There is evidence that insect hydrocarbons, in addition to fats, sterols and free fatty acids, are
transported throughout the haemolymph by lipophorin, presumably docking at lipophorin receptor sites
(Chino et al., 1981b; Diehl, 1975; Pho et al., 1996). Insect hydrocarbons serve a variety of functions:
they comprise a cuticular wax that is thought to prevent dessication, they function in conjunction with
the insect immune system to prevent infection and their volatility allows them to function as chemical
messengers to convey social messages between animals. Insect hydrocarbons are synthesized by large,
cuticle‐associated cells called oenocytes which can vary in position depending on the species of insect
21
(Piek, 1964). An insect cuticule may contain many hydrocarbons ranging in chain length from 18
carbons to around 30 carbons; behavioural assays have been used to elucidate the communicatory
function in only a few of these hydrocarbons. Cuticular hydrocarbons are found in three varieties: those
which are saturated (straight hydrocarbons of variable length), unsaturated (containing at least one
double bond) and methylated (those with branches in the hydrocarbon chain). While the functions of
many hydrocarbons are unknown, those thought to have communicatory functions are desaturated,
having at least one double bond in their structure (Chertemps et al., 2006; Dallerac et al., 2000; Jallon,
1984; Wicker‐Thomas et al., 1997). This desaturation is sex‐specific in the case of Drosophila
melanogaster and is carried out in the oenocytes by sex‐specific variants of desaturase genes
(Chertemps et al., 2006; Dallerac et al., 2000; Wicker‐Thomas et al., 1997; Wicker and Jallon, 1995a).
Though the method by which cuticular hydrocarbons are delivered from their site of synthesis to their
site of deposition is unknown, it has been proposed that hydrocarbons are haemolymph‐borne during at
least some of this process (Chino and Downer, 1982). Evidence has also accumulated to indicate that
the synthesis of insect hydrocarbon is likely to be under the influence of a circadian clock (Levine,
unpublished). In addition, it has also been demonstrated that the circadian clock of insects can be
‘reset’ using cues obtained from other insects or social experience (Levine et al., 2002). If these cues are
indeed the cuticular hydrocarbons likely to be under circadian control, then agitation of the lipophorin
transport dynamics of the animal could lead to both circadian and hydrocarbon effects.
What is currently known about the Drosophila branch of lipophorin receptors results from sequencing
evidence and experiments in other insect species. To improve this, we hoped to learn about the
Drosophila lipophorin receptor primarily using two techniques. The first was to create a polyclonal
antibody against the lipophorin receptor. This would allow us to have insight into the levels and spatial
localization of protein expression in various Drosophila tissues. Antibodies enable researchers to do this
by binding specifically to the target protein, or antigen, of interest. The position of the antigen is then
inferred indirectly by detecting the position of the antibody against it using a secondary antibody with a
detection tag that could be fluorescent or have some enzymatic activity. Antibodies are used in two
ways in this work: primarily they can detect proteins immobilized and blotted onto membranes after
electrophoresis through western blotting. Secondly, they can detect the spatial properties of target
antigens by staining fixed tissues with the antibody and then visualizing them with a confocal
microscope. Because we were interested in the link between the central circadian clock and the
lipophorin receptor, we imaged Drosophila brains stained with our generated anti‐LpR antibody in an
attempt to localize neural lipophorin receptor. Because mammalian lipoprotein receptors have been
22
identified as neural specific (Herz and Bock, 2002) we expected to find a variant of the lipophorin
receptor expressed in the Drosophila brain. Due to a partially verified link between circadian rhythm
and cuticular hydrocarbons (Levine, unpublished), and the potential that cuticular hydrocarbons are
linked to lipophorin and its receptor, we were particularly interested in whether the neural localization
of the lipophorin receptor is coincident with that of circadian clock function markers.
The second technique used to learn about the Drosophila lipophorin receptor employed powerful RNA
interference (RNAi) lines driven by the GAL4‐UAS system to specifically knock down expression of one or
both of the two main variants of the predicted Drosophila lipophorin receptor. In short, RNA
interference is a gene‐silencing pathway dependent upon exogenously supplied or ectopically expressed
double‐stranded RNA; its purpose is often gene silencing or translational repression (Hammond, 2005).
Because of the versatility associated with using the GAL4‐UAS system in Drosophila, knockdowns at
specific tissues and stages can be easily achieved. A variety of Drosophila lines containing transgenic
GAL4 constructs exist; this construct originally isolated from yeast is a transcriptional activator that
binds to an upstream activation sequence (UAS) causing the transcription of a target gene. Placed under
the control of the correct promoter, the GAL4 protein will only be found in desired tissues. Because the
GAL4 transcriptional activator has no known activity on endogenous Drosophila genes, flies containing
this transgene exhibit no direct phenotypic effect. When a line containing the GAL4 transcriptional
activator is crossed to a line containing a UAS construct upstream of a gene of interest, (such as an RNA
interference sequence,) the end result is that the gene of interest is expressed only in the tissues under
the control of the GAL4 promoter. RNAi lines obtained against LpR1 and LpR2 (directed against
sequences common to all transcriptional variants at each locus) were used to attempt tissue‐specific
translational repression of the lipophorin receptor.
Given the short time since its discovery, the extent of the characterization of the Drosophila RNAi
pathway is surprising. Several genes are involved in the RNA silencing pathway that is central to the
functioning of RNAi; mutants in these genes are defective in translational and transcriptional repression
(Grishok et al., 2001; Hammond, 2005). In the same manner, overexpression of the same genes under
the control of the GAL4‐UAS system may improve the translational repression of RNAi systems (Dietzl et
al., 2007; Lee et al., 2004). Dicer‐2 is one of the main genes responsible for the formation of the RNA
interference gene silencing complex; for this reason, UAS‐Dicer‐2 (UAS‐DCR2) was incorporated into all
UAS‐RNAi constructs used herein in an effort to bolster the tissue‐specific translational repression
desired. RNAi function is impaired in neuronal tissue for unknown reasons (Dietzl et al., 2007). This
23
impairment is reduced when Dicer‐2 is incorporated in neuron‐specific RNAi experiments (Dietzl et al.,
2007). Because these RNAi lines were used in several neuron‐specific GAL4 driver lines, and because the
effects of lipophorin receptor knockdown in neural tissue was of particular interest, incorporation of
Dicer‐2 was particularly important.
We attempted reduction of LpR1 and LpR2 under the control of several GAL4 lines: embryonic lethal
abnormal vision (elav), pigment dispersing factor (pdf), R32 (clock‐cell specific), and heat shock. The
expression pattern of elav‐GAL4 has been described as panneuronal; R32 is known to be expressed in all
clock cells of the Drosophila brain while pdf is expressed in a subset of these. The heat shock promoter,
though primarily activated at 37°C is thought to be constitutively active at temperatures of 25°C which
were used in fly rearing. Because circadian clock function and hydrocarbons appear to be linked, we
measured the effect of these tissue‐specific LpR knock‐downs on the cuticular hydrocarbons of
Drosophila males. We expected that, in accordance with the seemingly integral role of LpR for
hydrocarbon transport, we would identify a reduction in the cuticular quantities of several, if not all,
hydrocarbons. Additionally, RNAi lines were tested in activity monitors to try to identify an effect of LpR
knock down on circadian rhythms.
Methods
Fly Food and Rearing Conditions All Drosophila melanogaster stock lines were maintained on standard yeast‐sucrose‐agar medium. Food
was created by mixing all ingredients (12 g/L agar, 15 g/L sucrose, 30 g/L glucose monohydrage, 35 g/L
active dry yeast, 15 g/L cornmeal, 10 g/L wheat germ, 10 g/L soy flour and 30 g/L molasses) in hot tap
water and then heating and stirring the resulting mixture on a 395°C element until its temperature
reached 85°C. The heat was then lowered to 120°C for ten minutes, after which the food mixture was
removed to a fume hood and allowed to cool 47°C while stirring constantly. 5 mL of propionic acid and
10 mL of 10% w/v Tegosept in 95% ethanol were added to each litre of cooled food. The food was then
poured using blunt cannula‐tipped syringes in the amount of 8 mL per vial. Food was allowed to dry
overnight and was kept refrigerated at 4°C prior to use. Drosophila stocks were kept in prepared vials at
24°C with a 12‐12 light dark cycle changing vials every 14‐20 days.
Creating Homozygous UASDCR2; LpR1/2 RNA Interference Lines RNAi lines were obtained from the Vienna Drosophila RNAi Centre (VDRC) for both LpR1 (stock #14756;
CG31095) and LpR2 (stock # 25684; CG31092). Both lines contained insertions on the second
24
chromosome; LpR2‐RNAi lines were viable as homozygotes while LpR1‐RNAi lines were lethal and thus
balanced with the second‐chromosome balancer CyO which conferred curly wings on its bearer. UAS‐
DCR2 lines obtained from Paul Taghert contained a homozygous‐viable insertion on the first
chromosome. Males of the DCR2 line were crossed to females of genotype FM7/FM7;
Sp(Sternoplural)/CyO. A sibling cross between the resultant genotypes UAS‐DCR2/Y; Sp/+ and UAS‐
DCR2/FM7; CyO/+ resulted in the stable line UAS‐DCR2/UAS‐DCR2; Sp/CyO. Males of the LpR RNAi lines
were crossed to FM7/FM7; Sp/CyO. A sibling cross between the resultant genotypes FM7/+; UAS‐LpR
RNAi/CyO and FM7/Y; UAS‐LpR/CyO produced the two stable lines FM7/FM7; UAS‐LpR1 RNAi/CyO and
FM7/FM7; UAS‐LpR2 RNAi/UAS‐LpR2 RNAi. Males of each of these LpR RNAi stable lines were crossed
with UAS‐DCR2/UAS‐DCR2; Sp/CyO. A sibling cross between the resulting offspring UAS‐DCR2/Y; UAS‐
LpR RNAi/CyO and UAS‐DCR2/FM7; UAS‐LpR RNAi/CyO produced the two stable lines UAS‐DCR2/UAS‐
DCR2; UAS‐LpR1 RNAi/CyO and UAS‐DCR2/UAS‐DCR2; UAS‐LpR2 RNAi/UAS‐LpR2 RNAi.
Molecular Cloning and Microbiology All E. coli strains used for the subcloning and isolation of LpR2 (TOP10F and DH5α) were grown at 37°C
in Luria‐Bertani (LB) medium (solid or liquid) supplemented with 100 μg/mL ampicillin. The E. coli BL21
strain used specifically for the overexpression of T7‐tagged fusion proteins were grown in Terrific Broth
rather than LB medium. Protein inductions took place between 30 and 37°C depending on optimal
conditions. Expression of foreign constructs in E. coli pET21 vectors (EMD Biosciences Catalog No.
69741‐3) was accomplished through induction using Isopropyl β‐D‐1‐thiogalactopyranoside (IPTG;
Sigma‐Aldrich Product No. I5502). Polymerase Chain Reaction (PCR) was performed using the forward
primer LPR2A‐F (5’‐GGGTCGACAACATGGGACCAATA‐3’) and reverse primer LPR2A‐R (5’‐
GGCTCGAGCCGCTAAACTGGCAA‐3’) or LPR2B‐F (5’‐GGGTCGACAACATGGGACCAATA‐3’) and reverse
primer LPR2B‐R (5’‐GGCTCGAGCCGCTAAACTGGCAA‐3’) ordered from Sigma‐Genosys. Agarose gel
electrophoresis was performed using 1% agarose in standard Tris‐Acetate EDTA buffer. Electrophoresis
was monitored using the GeneRuler® marker (Fermentas Catalog No. SM0311) diluted appropriately in
6X DNA electrophoresis loading buffer. Agarose DNA gels were stained for 30 minutes after
electrophoresis in an ethidium bromide (10μg/mL) bath and destained in aqueous 1mM magnesium
sulfate prior to visualization under ultraviolet light. Plasmid minipreparations were performed using the
Sigma Genelute Plasmid Miniprep kit (Sigma Lot No. 074K6160) according to the manufacturer’s
instructions. Agarose gel extractions were performed using the QIAquick Gel Extraction Kit (Qiagen
Catalog No. 28706). Restriction digests were performed using enzymes purchased from New England
Biolabs in the recommended digestion buffers. Ligations were performed using T4 DNA Ligase (New
25
England Biolabs Catalog No. M0202) in the appropriate buffers according to the manufacturer’s
instructions. Cloning of PCR products into the pCR® 2.1 TOPO vector was accomplished using the
pCR®2.1 TOPO TA Cloning Kit (Invitrogen Catalog No. K2020‐20) according to the manufacturer’s
instructions. Rapid disruption plasmid minipreps were performed according to the standard protocol
(Sambrook and Russell, 2001). Electroporation of electrically competent E. coli was performed using
electroporator tubes with a 2 mm gap at a potential of 2.5 kV. Electroporated cells were quickly placed
in SOC medium without antibiotic (Sambrook and Russell, 2001) for one hour to recover and then
spread over LB plates supplemented with ampicillin.
Polyacrylamide Gel Electrophoresis and Western Blotting Polyacrylamide gels varying in concentration between 6% and 12% were cast using 30%
Acrylamide/Bisacrylamide 37.5:1 with 2.6% C (BioRad Catalog No. 161‐0158) according to standard
protocols (Sambrook and Russell, 2001). Proteins were electrophoresed at 150V for approximately 1‐1.5
hours in the BioRad Mini‐PROTEAN 3 electrophoresis system (Biorad). Electrophoresis was monitored
using SDS‐PAGE Standards (BioRad Broad Range Catalog No. 161‐0317) or Prestained Standards (BioRad
Broad Range Kaleidoscope Prestained Marker Catalog No. 161‐0324). Membrane transfer also took
place in the BioRad Mini‐PROTEAN 3 western blotting system for 2‐4 hours with stirring and on ice at
100V. Proteins were either transferred to Pure Nitrocellulose (Pall Corporation Biotrace NT Product No.
66485) or polyvinylidene fluoride (PVDF; BioRad Immun‐Blot PVDF Membrane 0.2 μm Catalog No. 162‐
0176). Electrophoresis buffer was diluted from a 5X stock (15.1g/L TRIS, 72.0g/L glycine, 5.0g/L SDS).
Protein transfers took place in a western blotting buffer (3g/L TRIS, 14.4g/L glycine, 20% methanol).
PVDF membranes were wetted in 99% methanol prior to and after electrophoretic transfer.
Membranes were blocked with gentle rocking overnight at 4°C in Tris‐buffered Saline with Tween (TBST;
2.42g/L Tris, 8g/L sodium chloride, 0.1% Tween, pH 7.6) supplemented with 5% w/v Carnation Non‐Fat
Powdered Milk. All other steps took place at room temperature. Primary antibodies were added
directly to this solution at a concentration of 1:2000 for approximately 1 hour. Membranes were
washed in TBST two to four times for 5 to 15 minutes each. Secondary antibodies were added at a
concentration of 1:5000 for 45 minutes and then washed two to four times for 5 to 15 minutes each
with TBST. Colorimetric development of alkaline‐phosphatase secondary antibodies (Jackson
Immunoresearch laboratories Goat‐anti‐Rabbit Alkaline Phosphatase Conjugated Antibody Catalog No.
63581; BioRad Goat‐anti‐Rabbit Alkaline Phosphatase Conjugated Antibody Catalog No. 170‐6518) took
place by washing the membrane twice in alkaline phosphatase buffer (12.1g/L Tris, 5.84g/L sodium
chloride, 1.02g/L magnesium chloride hexahydrate, pH 9.5) and adding, to the second wash, 165 μg/mL
26
5‐Bromo‐4‐Chloro‐3‐Indoyl Phosphate Toluidine Salt (BCIP; BioShop Lot No. 24524) and 220 μg/mL Nitro
Blue Tetrazolium (NBT; BioShop Lot No. 7A2742). Colorimetric development was monitored and rarely
exceeded five minutes. Membranes were then washed using distilled water. Fluorescent development
of horse‐radish peroxidase‐conjugated secondary antibodies (Jackson Immunoresearch Laboratories
Goat‐anti‐rabbit peroxidase conjugated secondary antibody Catalog No. 61797) was performed using
the Amersham ECL Plus Western Blotting Detection System (GE Healthcare RPN2132) according to the
manufacturer’s instructions. Polyacrylamide gels whose proteins were not electrophoretically
transferred to membranes were stained for several hours using Coomassie Blue R250 and destained
overnight in an aqueous solution of 5% v/v methanol and 7% v/v glacial acetic acid. These gels were
then dried overnight using the GelAir cellophane support (BioRad Catalog No. 165‐1779EDU and 165‐
1775EDU). E. coli protein lysates for PAGE were prepared by harvesting cells with benchtop
centrifugation then resuspending them in appropriately diluted 6X SDS Sample Buffer (0.35M Tris
hydrochloride at pH 6.8, 0.128g/mL SDS, 0.38g/mL glycerol, 0.093g/mL dithiothreitol, 0.12mg/mL
bromophenol blue). Lysates were then boiled for 5 minutes and stored at ‐20°C until use. Drosophila
protein lysates were prepared by grinding whole flies or separated fly heads and the remainder of the
flies in a chilled protease‐resistant sample buffer (100mM potassium chloride, 20mM HEPES (4‐(2‐
hydroxyethyl)‐1‐piperazineethanesulfonic acid), 5% glycerol, 10mM EDTA (ethylene diamine tetraacetic
acid), 0.1% Triton‐X 100, 1mM dithiothreitol, 10μg/mL aprotinin, 5μg/mL leupeptin). The mixture was
then centrigued at room temperature at 20 000 x g for 5 minutes and the supernatant decanted to a
separate container. To the supernatant was added the appropriate dilution of 6X SDS Sample Buffer
after which the sample was boiled for five minutes and stored at ‐20°C until use.
Haemolymph Collection and Purification
27
Collection of Drosophila haemolymph was performed using a modification of a procedure described
elsewhere (Lucas et al., 2004). Bottles with 0.15‐0.16g of flies which were 4‐6 days old were frozen by
placing a 50mL conical tube containing the flies within liquid nitrogen. The sample was then vortexed at
high speed to detach fly heads from bodies to allow for insect bleeding. Frozen flies were placed inside a
3mL VectaSpin tube which contained 1mL of aqueous buffer. The aqueous buffer solution was used in
order to retrieve small molecules and soluble proteins. The buffer was composed of: monosodium
phosphate (7.8g/L), sodium chloride (8.77g/L), ethylenediaminetetraacetic acid (EDTA) (1.86g/L), sodium
azide (0.10g/L), leupeptine (10μL/mL), benzamidine (10μL/mL), and aprotinine (10μL/mL). These agents
aid in preventing protein degradation and clotting. VectaSpin tubes were lightly vortexed for two
minutes to encourage bleeding. Then the sample was centrifuged at 2000 x g for two minutes at 4°C to
pull large body parts from the crude extract. Supernatant was collected and transferred into a 1.5mL
polypropylene SuperSpin Eppendorf tube. Eppendorf tubes were centrifuged for 30 minutes at 30 000 x
g at 4°C. Supernatant was kept on ice to inhibit remaining protease activity. The supernatant was then
loaded onto a pre‐wetted column (BioRad Biospin chromatography columns Catalog No. 732‐6008)
prepared with DEAE‐cellulose (Sigma‐Aldrich Product No. D3764‐100G). The column was then eluted
with phosphate buffer (0.2M sodium phosphate, pH 6.8) and 10 1mL fractions were collected into 1.5mL
tubes. Fractions were assayed separately for lipophorin content and purity.
Ligand Blotting SDS‐PAGE and western blotting techniques were performed as noted. SDS and dithiothreitol were
omitted from sample buffers for native protein products. Membranes were blocked overnight in TBST
supplemented with 5% Carnation Non‐Fat Powdered Milk. All other steps took place at room
temperature. DEAE‐cellulose purified haemolymph was added directly to the blocking solution at a
dilution of 1:500 for a period of one hour. The membrane was then washed in TBST three times for 15
minutes each time and replaced in blocking solution. Anti‐apoLpI or anti‐apoLpII was then added at a
dilution of 1:2000 for one hour. The membrane was then washed in TBST three times for 15 minutes
each time and the appropriate alkaline‐phosphatase conjugated secondary antibody was added for 45
minutes. The membrane was washed three times for 15 minutes each time in TBST and then washed
twice in alkaline phosphatase buffer. Colorimetric development took place as noted above.
Antibody Conditions Peptide and antibody production was performed by Pacific Immunology Inc. Ramona, CA. Antibodies
were generated by using solid phase peptide synthesis to produce immunogen‐grade peptides which
were then conjugated to Keyhole Limpet Haemocyanin (KLH) prior to injection into New Zealand White
Rabbits. Rabbits were maintained on a standard 13 week protocol prior to exsanguinations. Sera from
each rabbit were stored at ‐80°C in the absence of sodium azide, or at 4°C with 1mM sodium azide.
Collection and Gas Chromatography of Cuticular Hydrocarbons Extraction of cuticular hydrocarbons has been previously described (Ferveur, 1991). Flies 3‐6 days after
eclosion were anaesthetized in diethyl ether. Each fly was placed in a 1.5 mL glass conical vial with a 200
μL insert. The inserts contained 50μL of a standard mixture (10 μg/mL of octadecane and 10 μg/mL in
hexane solvent). Flies were then shaken at low speed for 2 minutes and removed from the standard
mix. Samples were analyzed using a gas chromatograph joined to a flame‐ionization detector (Varian CP‐
28
3800 with autosampler CP‐8400). The column employed was a DB‐1 custom capillary column with a 5m
X 0.25mm guard column (J&W Scientific; length 20m, diameter 0.18mm and film 0.18 μm; model 100‐
2000). Chromatograms were processed with Varian GC Workstation (Version 6.30) software. Peaks
were identified by comparing retention times to n‐alkane standards (10μL/mL) and using strains whose
main hydrocarbons had been identified by mass spectroscopy. All peaks were normalized with
hexacosane from the standard solution. All chemicals were purchased from Aldrich Chemical Company
Inc.
Activity Monitoring Flies were sorted on carbon dioxide pads and allowed to recover for at least 24 hours following
anesthesia prior to any behavioural testing (Greenspan, 2004). Males of each genotype were between 3
and 6 days old and were loaded into activity tubes containing a small amount of agar‐sucrose for
hydration and feeding after which point the other end of the activity tube was closed gently with cotton.
Activity tubes were fastened to Drosophila Activity Monitoring (DAM2) systems (Trikinetics, inc.
Waltham, MA). Flies were maintained in the appropriate lighting cycle (either 12‐12 light dark or total
darkness) without interruption. Data was acquired through DAM System Software for Windows version
3.02 and was analysed using MatLab R2006b (Mathworks inc. Natwick, MA) with previously described
algorithms for analysis of circadian rhythms (Levine et al., 2002).
Tissue Staining and Confocal Microscopy Male flies of each genotype were dissected in PBS (0.1M Phosphate Buffered Saline, pH 7.4) and tissues
of interest were fixed for 45 minutes in 4% paraformaldehyde. Tissues were washed in 0.2M phosphate
buffer, blocked in 4% normal goat serum with 0.5% Triton‐X for 3 hours, and incubated with the
appropriate dilution of primary antibody for 24‐48 hours. Tissues were washed once more and
incubated with the appropriate dilution of secondary antibody in 2% normal goat serum with 0.5%
Triton‐X for approximately 24 hours at 4°C. Tissues were kept in the dark to avoid photo‐bleaching of
the fluorophores on the secondary antibodies. Tissues were then cleared for at least 24 hours in
glycerol. Tissues were loaded onto glass slides in Vectashield® Mounting Medium (Vector Laboratories
Product No. H‐1000) and visualized using the Zeiss 510 Laser Scanning Confocal Microscope. The Zeiss
510 is controlled by Zeiss LSM software for Microsoft Windows NT. The Ar/HeNe lasers of the LSM 510
29
can excite fluorochromes with the following wavelengths in the visible spectrum: 458 nm, 476 nm, 488
nm, 514 nm, 543 nm and 633 nm. Tissue staining and microscopy were performed by Olga Sizova.
Results
Subcloning LpR2 into an Expression Vector In order to obtained the full‐length cDNA sequence of the gene, an E. coli clone containing LpR2 cDNA
was ordered from the Canadian Drosophila Microarray Centre (CDMC). The curated gene from the
Drosophila genome project for LpR2 is CG31092. Two variants of this gene were available from the
CDMC and both were ordered. These were named LD11117 (96 well plate reference UG74G6) and
GH26833 (96 well plate reference (CH14BE6) and were expected to contain 3.3kb and 2.3kb cDNAs,
respectively. LD11117 is available in pBS SK‐ which confers ampicillin resistance and was hence streaked
onto LB plates supplemented with ampicillin. GH26833 is available in p0T2 which conferred resistance
to chloramphenicol; these clones were therefore grown on LB plates supplemented with
chloramphenicol at the appropriate concentration (Sambrook and Russell, 2001). Plates were incubated
at 37°C overnight and well‐isolated colonies were used to inoculate 3mL of liquid LB medium
supplemented with the appropriate antibiotic. Liquid cultures were allowed to grow overnight (~16
hours) prior to harvesting. Plasmid minipreparations were performed to isolate the plasmids containing
the two genes of interest. PCR was performed using primer pairs LPR2A‐F/LPR2A‐R for the LD11117
clone and LPR2B‐F/LPR2B‐R for the GH26833 clone.
Optimized PCR conditions were required for the two separate clones due to differences in the G/C
content and melting temperatures of the two primers, as well as the difference in the size of the two
amplicons. Several template concentrations were used when amplifying GH26833 (1:100, 1:200, 1:500
and 1:1000 template:solution). Thermal cycling conditions were 95°C (40s), 67°C (40s) and 72°C (70s)
for 35 cycles. A 2.3kb amplicon was generated in each of the template concentrations (figure 6). PCR of
Figure 6 Agarose gel electrophoresis of amplicons resulting from PCR reactions using templates LD1117 (lanes 1‐8) and GH26833 (lanes 9‐12). White triangles indicate expected amplicon size (3.3kb lanes 1‐8 and 2.3kb lanes 9‐12). PCR reactions in lanes 1‐4 were performed with an annealing temperature of 63°C while all other PCR reactions were performed at 67°C. Lanes 1‐4, 5‐8, and 9‐12 comprise three sets of decreasing template concentrations (1:100, 1:200, 1:500, 1:1000). Lane M represents the marker.
30
LD11117 was attempted in the aforementioned concentrations and at two annealing temperatures;
thermal cycling conditions were 95°C (40s), 63°C/67°C (40s) and 72°C (80s) for 35 cycles. Only the lower
annealing temperature produced products with the expected 3.3kb amplicon size.
Lanes 1‐4 and 9‐12 of the above figure were excised from the gel under ultraviolet light keeping care to
minimize exposure times and damage to the DNA. DNA was purified from the agarose for use with the
Invitrogen TOPO TA cloning kit. A 6μL ligation reaction was created (4.2μL purified PCR product, 0.6μL
10X PCR buffer, 0.6μL 10X dNTP mix, 0.6μL pCR 2.1 TOPO vector). This ligation mixture was left at room
temperature for 30 minutes. 1μL of this mixture was mixture was used in the electroporation of
TOP10F’ E. coli. This mixture was spread over LB plates containing the appropriate concentrations of
ampicillin and X‐gal (Sambrook and Russell, 2001). Ampicillin was used to identify cells that had been
transformed successfully while X‐gal was used to verify that the vectors had not undergone self‐ligation;
thus, dark blue colonies were avoided. Colonies were selected and used to grow lawns on LB plates
containing ampicillin. A rapid disruption minipreparation was performed (Sambrook and Russell, 2001)
and the results are shown in the figure below. Lane 10 of both clone types represents a dark blue
colony selected as a negative control. Colonies with motilities retarded compared to those of negative
controls were selected for further analysis.
Figure 7 Rapid disruption minipreparation of LD11117 and GH26833 pCR2.1 TOPO clones. Lanes 1‐9 of both clones represent positive (white) colonies while lane 10 of both clones represents a negative (blue) colony used as a control. White triangles show plasmids containing the insert which retards their mobility as compared with that of the two negative clones in lane 10. As expected, the mobility of the LD11117‐containing plasmids is reduced compared to that of the GH26833 plasmids as a result of its their larger size.
31
In order to use the SalI and NotI restriction sites provided by the pCR2.1 TOPO vector to subclone the
two cDNA sequences into pET21B, the orientation of the cloned inserts needed to be determined.
Because the pCR2.1 TOPO cloning system relies only on TA cloning of the overhangs remaining on PCR
products, either insertion orientation was equally likely.
Thus, to determine the orientation of the inserted PCR product, restriction sites engineered into the PCR
primers LPR2A/B‐F and LPR2A/B‐R were used. The primer pair used to amplify the LD11117 fragment
contained a SalI restriction site on the forward primer and a HindIII site on its reverse primer. In the
correct orientation (figure 8) HindIII digestion of the pCR2.1 TOPO vector containing the LD11117 insert
would yield a large fragment approximately corresponding to the size of the LD11117 insert (3.3kb) .
Likewise, the primer pair used to amplify the GH26833 fragment contained a SalI restriction site on the
forward primer and an XhoIII site on its reverse primer. Therefore in the correct orientation in the TOPO
vector, an XhoI digestion of the plasmid would not produce a fragment corresponding to the size of the
insert but instead would produce a single linear fragment corresponding to the linearized plasmid
(figure 8). Positive TOPO clones 1‐5 for both LD11117 and GH26833 (figure 7) were grown overnight in
LB medium supplemented with ampicillin. Cells were harvested and minipreparations of plasmid DNA
were performed. 2μL of plasmid DNA was subjected to a 15μL digestion in 1.5μL 10X NEB restriction
buffer, 0.5μL of either HindIII or XhoI and 11μL of deionized water. Restriction digests demonstrated
that TOPO clones 2, 3 and 4 generated with the LD11117 PCR product were suitably oriented for
SalI/NotI subcloning while none of the clones of the GH26833 PCR product were suitable. Given that the
likelihood of insertion in either orientation is 50%, the results of GH26833 TOPO cloning are extremely
rare. More of the white TOPO clones were examined using XhoI digests (data not shown) and all gave
the result observed. The plausible explanation for this is that, when in the orientation desired for
SalI/NotI cloning, the GH26833 insert does not interfere with the functioning of the LacZ component of
the TOPO vector; therefore colonies with the insert in the correct orientation would not be
distinguishable from colonies with no insert. It was decided therefore to abandon the attempt to clone
GH26833 and focus solely on LD11117.
32
Figure 8 Determination of possible orientations of LD11117 and GH26833 PCR fragments in pCR2.1 TOPO vector. A) Map of thepCR2.1 TOPO cloning site with black labeled insert; desired orientation of SalI/HindIII restriction sites are shown coloured andgray arrows indicate that the orientation of these sites is random. B) Same as above; desired orientation of SalI/XhoI restrictionsites are shown coloured. C) Restriction digest of LD11117 and GH26833 TOPO clones 1‐5 with HindIII (left) and XhoI (right).3.3kb and 2.3kb bands are liberated LD11117 and GH26833 cDNA while 4kb bands are linearized TOPO plasmid.
33
Since directional insertion into pET21B was desired, (figure 8,) an LD11117 TOPO clone was doubly
digested with SalI and NotI in the NEB recommended buffer. Two 40μL reactions (34μL TOPO clone
minipreparation or pET21B minipreparation, 4μL 10X NEB digest buffer, 1μL SalI, 1μL NotI) were
incubated at 37°C for two hours. The products were electrophoresed and visualized (figure 9). Bands
were excised from the gel and then purified. A 10μL ligation reaction (7.5μL digested LD11117 TOPO,
1μL digested pET21B, 1μL NEB ligation
buffer, 0.5μL T4 DNA ligase) was
incubated at room temperature for 4
hours. 1μL of this mixture was then
transformed into DH5α E. coli. The
transformation mixture was spread over
LB plates and allowed to grow overnight.
The resulting colonies were examined
using a rapid disruption minipreparation
to ensure tranformation with the vector
containing the insert (figure 9). 7 clones
that were examined exhibited a mobility
shift corresponding to the presence of an
insert. The DH5α strain of E. coli was
selected for transformation due to
reduced transformation efficiencies
when trying to transform ligated
pET21B+LD11117 directly into the
protein expression strain BL21. Thus,
transformed DH5α E. coli were used to
inoculate 3mL of liquid medium and grown
overnight. Their plasmids were harvested
and then used to transform E. coli of the
less efficient BL21 strain for protein
expression purposes. DH5α clones
number 2 and 3 were arbitrarily chosen for
this purpose (figure 9).
Figure 9 a) Restriction digest of LD11117 TOPO insert as well as pET21Bvector in preparation for ligation. Digest was performed using SalI andNotI incubated at 37°C for 2 hours. Indicated 3.3kb band (LD11117insert) and 6.0kb band (linearized pET21B) were excised from the geland purified. b) Electrophoresed products from gel extraction andpurification technique. The 6kb and 3.3kb bands of high purity indicatea successful gel extraction. c) Verification of insertion based on linearand circularized plasmid mobility shift. d) Rapid disruptionminipreparation of positive DH5α E. coli clones; clones 2, 3, 5, 6, 7, 9and 10 contain an insert and exhibit retarded mobility compared to thecontrol pET21B lane.
34
Verifying Correct Insertion of LpR2 into pET21B
LpR2 (LD11117) was cloned into E. coli of the BL21 strain in order to allow inducible ectopic expression.
Therefore, determination of the correct insertion orientation and functioning of the engineered plasmid
was ultimately determined through expression studies. Several BL21 expression clones which were able
to grow on LB medium supplemented with ampicillin following transformation with pET21B+LD11117
were chosen for expression studies. The LD11117 predicted protein sequence would yield a protein of
1064 amino acids with a molecular weight of 117kDa. Because the pET21B vector adds a T7‐tag
recognition sequence upstream of the inserted protein sequence, molecular weight numbers are
approximately accurate. Single, well‐isolated colonies of 20 BL21 clones of LD11117 inserted in pET21B
were each used to inoculate 1mL of LB medium supplemented with ampicillin. These cells were then
incubated at 37°C for approximately 3 hours until reaching an optical density at 595nm of around 0.5.
Cells were then induced with 1‐2mM IPTG for 3 hours. Cells were harvested and resuspended in 50μL of
2X SDS‐Sample buffer and homogenized. Cells were then placed in a 100°C water bath for 5 minutes
and electrophoresed on an 8% polyacrylamide gel which was then stained in Coomassie brilliant blue
and dried (figure 10). Despite the ability to see the overexpression of glutathioine‐S tranferase (GST;
~30kDa) within the positive control BL21 strains containing pGEX, no overexpression of LpR2 was
apparent.
Figure 10 SDS‐PAGE expression of LD11117 (LpR2) BL21 E. coli clones after 3 hours induction in LB‐ampicillin. The expected sizeof this expression variant of LpR2 is 117kDa and no band is apparent; positive control lanes (pGEX) exhibit obviousoverexpression of glutathione‐S transferase (GST) with a visible band at 30kDa. M represents marker lanes (Bio‐rad BroadRange, unstained) with molecular weights noted in to the left of the figure.
Empirical evidence has suggested that changing the expression medium can sometimes facilitate the
expression of difficult proteins. In addition, changing the concentration of IPTG can also have an effect.
Therefore, to attempt to attain a suitable level of LpR2 overexpression from the BL21 clone, the above
35
procedure was repeated with two variations: rather than standard LB medium, terrific broth (TB)
medium was used (Sambrook and Russell, 2001). Also, rather than 1‐2mM IPTG, 8mM IPTG was used to
induce the clones for 3 hours. The pET21 vector series provides an additional mechanism for
determining whether the correct gene is inserted in the correct reading frame and orientation; the N‐
terminal T7‐tag is an 11 amino acid sequence that is not found elsewhere in the bacterial proteome and
is therefore likely to only be found in the expressed tag on the ectopic protein. A western blot was
therefore included (figure 11) to verify not only the size of the expressed protein attached to the T7‐tag,
but also the correct orientation (improperly inserted genes are likely to introduce premature stop
Figure 11 Western blot and Coomassie stained SDS‐PAGE gels to verify the presence and overexpression of LD11117(LpR2) in pET21B. Left two lanes: monoclonal mouse anti‐T7 tag antibody detects the presence of a 117kDa peptide inLD11117 E. coli but not in control pGEX lines expressing ectopic glutathione‐S transferase (GST). Right two lanes:Coomassie blue staining detects an overexpressed 30kDa band in pGEX control cells and a 117kDa band in LD11117 cellswhich is not present in control lines. M: Bio‐rad Broad Range SDS protein standards.
36
codons into the coding sequence and hence produce a smaller protein). The results demonstrated that,
under the correct induction conditions, ectopic expression of LpR2 was possible in LD11117 E. coli BL21
clones. Additionally, the overexpressed T7‐LpR2 was correctly identified by the monoclonal anti‐T7 tag
antibody indicating that the overexpressed protein with a size of 117kDa was not artifactual. While
these data indicate that the BL21 clones are likely to contain the correct insert, sequencing was also
performed. The sequences yielded (figure 12) demonstrate clearly that the LD11117 PCR product was
inserted in the correct orientation into the pET21B vector. Sequencing accuracy was low in the centre of
the gene (as each sequence read is only effective to around 700 base pairs) but the accuracy at the 5’
and 3’ ends of the inserted gene was sufficient to confirm insertion.
Figure 12 Sequences of LD11117 clones in pET21B vector minipreparations from E. coli BL21 strain. a) Multiple cloning site orientation and sequence from pET21 vectors. The T7 promoter and terminator primers indicated here were used in sequencing and flank the inserted sequence. d) Abridged sequence alignment showing only the 5’ and 3’ ends of the sequence indicating a correct insertion. Cap_LD203F indicates the sequence resulting from the T7 forward primer; cap_203R indicates the reverse compliment of the sequence resulting from the T7 terminator primer; cap_LpR2A represents the known sequence of the LD11117 Drosophila genome project clone; contig‐0 represents the consensus generated. Shaded areas represent identity between the 5’ and 3’ ends of the known sequence and the 5’ and 3’ sequences of the LD11117 pET clone.
37
Generation of antiLpR Serum The design of the antigen used to create the antiserum against the lipophorin receptor was of critical
importance. Rather than designing at least four different antigens, (against each of the predicted
lipophorin receptor sequences,) a more efficient approach of developing a single antiserum targeted
against all four predicted receptor sequences was chosen. This was done for two reasons; designing
multiple antisera would be costly and time‐consuming. Also, because this work is an initial
characterization of the Drosophila lipophorin receptor, promiscuous antisera could be used to identify
probable areas of expression which could later lead to the design of more specific antisera. Four
Drosophila polypeptides were chosen as templates of the lipophorin receptor; these were based on the
four sequences (named BmLpR1, BmLpR2, BmLpR3 and BmLpR4) of the silk worm Bombyx mori
(Gopalapillai et al., 2006). Using a BLAST (basic local alignment search tool) search (Altschul et al., 1990),
it was determined that these sequences corresponded to four variants of two different drosophila genes
(DmLpR1 and DmLpR2).
The design of the ideal antigen (herein referred to as LpRv1) would encompass several characteristics: it
would share minimal sequence similarity with other proteins of the study organism, its counterpart on
the protein of interest would be exposed to the aqueous solution and not buried within the hydrophobic
core, and it would maximize the immune response of the injected animal. Of paramount importance is
the lack of sequence similarity with other proteins in the study organism; should there be any sequence
similarity, the antigen injected into the immunizing animal could produce antibodies with promiscuous
affinities. In the case of the design of the antibody used in this work, cross‐reactivity was desired but
only among the four proteins mentioned. Several other receptor molecules share sequence homology
with DmLpR1/2 so antigenic areas had to be chosen carefully. The antigenic region used to inject the
immunizing animals had to be exposed on the protein rather than buried in the hydrophobic core. This
was especially pertinent for a membrane‐bound receptor such as LpR; should an antigenic region be
chosen that is buried in the native conformation of the protein, the immunized animal may produce
antibodies specific to it, but they may be ineffective in tissue preparations in which the protein
conformation protects the antigen. Hydrophobic portions of the protein are likely to be buried in its
core or, in the case of a membrane‐bound receptor, part of the transmembrane region that is unlikely to
be exposed to the surrounding medium. To ensure that only exposed regions of the protein were used
as antigens, hydropathy indices (the extent to which peptide sequences are hydrophobic) were
38
Figure 13 a) Adapted (Gopalapillai et al., 2006). Schematic representation of the domains in the B. mori lipophorin receptor; cysteine‐rich repeats of the ligand binding domains (I‐VIII), cysteine‐rich repeats of the EGF precursor homology domain (A‐C), O‐linked oligosaccharide domain (O), transmembrane domain (T) and cytosolic domain (CY). b) ClustalW alignment of the top four sequences matching the B. mori LpR sequences. Poor regions for antigen choice in developing anti‐LpR are indicated in red (transmembrane) or blue (cytoplasmic). Acceptable regions are shown in green. Stars beneath each peptide indicate identity among all four sequences.
considered in the design process. This consideration also maximizes the ability of the antigen to elicit an
immune response in the host animal (figure 13).
The region ultimately chosen as an antigen was NH2‐TQSIYKAPIDEGN‐C‐COOH. The NH2 and COOH
represent the amino and carboxy termini of the peptide. A cysteine residue had to be added to the
sequence in order to allow sulfur‐based conjugation between the peptide and KLH. This region had the
least cross‐reactivity potential with other Drosophila proteins. In addition, it was present in all four
isoforms of the Drosophila lipophorin receptor and had a negative hydropathy index, indicating
hydrophilicity. The sequence was sent to Pacific Immunlogy inc. (Ramona, CA). Peptide chemists used
39
solid‐phase peptide synthesis to produce the 15 amino acid peptide and then conjugated it to the carrier
protein prior to injecting it into rabbits. Rabbits were maintained on a 13 week protocol during which
they received four injections of immunogen. During this time, a single pre‐immune serum as well as
four production bleeds and one final exsanguination from each rabbit was received. The LpRv1 antigen
was injected into two New Zealand white rabbits to maximize the potential for developing high affinity
antibodies.
Western Blot Testing of LpRv1 Several avenues were explored to test the specificity, quantity and affinity of the LpRv1 antisera. The
cloned LD11117 peptide proved useful because it allowed testing of the antisera in a medium that was
likely to contain high levels of cross‐reactivity; this is logical considering that the immune system of each
rabbit is likely to contain at least some antibodies against E. coli peptides. In addition, by ensuring that
the commercially available anti‐T7 monoclonal antibody recognized the same peptide as the LpRv1
antiserum, we were able to verify its relative specificity. More important, however, is the performance
of the antiserum in lysates collected from Drosophila. Thus, each serum collection (production bleeds,
pre‐immunization bleeds and final bleeds) was tested in a Canton‐S and yellow‐white per0 Drosophila
background using separated heads and bodies of the animals. The yellow‐white per0 control simply
served in this case as an additional background strain and could hence confirm results obtained in a
Canton‐S background. In all cases of the LpRv1 antisera, production bleed 1 was virtually identical to
production bleed 2 and was hence omitted. Alkaline phosphatase development was used for the first
set of blots (figure 14) because of its relatively inexpensive development reagents as compared with
chemiluminescent development. For the same reason, pure nitrocellulose was used rather than PVDF
membranes.
Pre‐immune sera collected from both rabbits repeatedly showed little or no western blot reactivity
(figure 14). Because colorimetric development was used, pre‐immune blots were allowed to develop for
a greater length of time (around 15 to 20 minutes) than blots incubated with production sera. This
allowed us to ensure that there was no reactivity of the rabbit serum prior to injection with the
immunogen. In both rabbits, relative background detection levels seem to decrease between the
second production bleed and the final bleed with the least relative background on the fourth or final
bleeds. Interestingly, the two rabbits seem to have generated isoform‐specific antibodies. Because the
same immunogen was used to immunize both rabbits, such specificity is purely an artifact of the
unpredictability of the mammalian immune system. The first immunized rabbit (rabbit 1) seems to have
40
an affinity for an approximately 100 kDa peptide; several variants of the Drosophila lipophorin receptor
1 and 2 (CG31095 and CG31092, respectively) are of this approximate size. Thus, it appears that the
immune sera of this rabbit recognize the correct peptide. The second immunized rabbit (rabbit 2)
produced antisera with an affinity towards a larger peptide between 100 and 150 kDa (approximately
115 kDa). Several variants of the gene products at the aforementioned loci correspond to this
approximate size and it is therefore likely that the immune sera of this rabbit also recognize a lipophorin
receptor variant.
Figure 14 Immune serum testing for LpRv1 (anti‐DmLpR). Canton‐S and per0 fly lysates were electroblotted onto pure nitrocellulose membranes and the antisera from two different rabbits (Rabbit 1 and Rabbit 2) were used at a dilution of 1:2000 on ten replicate blots. Bio‐rad Goat anti‐rabbit secondary antibodies were used at a dilution of 1:5000. Lanes are labeled as follows: m (Bio‐Rad Kaleidoscope® prestained marker; visible bands are 250kDa, 150kDa, 100kDa, 75kDa) h (heads) b (bodies). Heads and bodies were collected and electrophoresed for both Drosophila genotypes. Black arrows represent probable lipophorin receptor immunoreactivity and are situated at molecular weights of ~100kDa (Rabbit 1) and ~115kDa (Rabbit 2).
41
Another interesting observation is the fact that the first rabbit almost exclusively recognizes peptides in
the body of the fly, while the second rabbit almost exclusively recognizes peptides in the head (figure
14). This could suggest that the variant to which the serum of each rabbit has more affinity is present in
larger quantities in the two tissues. In any case, both sera are useful and their differences on western
blots will be useful in determining which peptides are most likely to be expressed in different tissues.
The observation that LpRv1 sera recognize a peptide at approximately the correct molecular weight is
not sufficient to claim that it recognizes the Drosophila lipophorin receptor. In order to verify this, we
used the cloned T7‐LpR (LD11117 in pET21) lysates from E. coli. Verification that the peptide recognized
by the anti‐T7 tag antibody is the same peptide recognized by the LpRv1 serum is more concrete
evidence demonstrating the specificity of the polyclonal antibody. Samples of heads and bodies from
Canton‐S flies as well as lysates from E. coli containing the LD11117 PCR product in pET21 as well as E.
coli containing a control peptide unrelated to LpR2 were electroblotted onto PVDF membranes and
visualized using ECL.
Figure 15 Western Blots of Canton‐S heads and bodies, E. coli lysates containing LD11117 (Lpr2) in pET21 or control peptide in pET21. Lane labels are as follows: m (marker, Bio‐rad Kaleidoscope® prestained marker) h (heads) b (bodies) T7‐LpR (LD11117 PCR product in pET21B) T7‐Control (Drosophila peptide unrelated to LpR in pET21). Relevant marker bands are marked at 150kDa and 100kDa. Three anti‐sera were used: LpRv1 Rabbit 1 bleed 4 (left), LpRv1 Rabbit 2 bleed 4 (middle) and monoclonal anti‐T7 (right). Black arrows represent peptides of interest.
It is clear from the above figure (figure 15) that the peptides recognized by LpRv1 from each rabbit are
indeed related to the LD11117 sequence of LpR2 cloned into E. coli. As with the tests featured earlier,
the first immunized rabbit seems to retain immuno‐specificity for a lower molecular weight version of
42
the lipophorin receptor. Once again, the second rabbit seems to be immunoreactive against a higher
molecular weight (~115kDa) peptide as with test bleeds. Since this peptide more closesly matches the
molecular weight of the cloned LD11117 sequence, they appear as nearly equal molecular weights on
western blots. In both cases, the T7‐LpR peptide is clearly illuminated by the antibody and provides a
much clearer signal than either fly lysate. Additionally, the T7‐control lane only contains background
immunoreactivity that is obvious in either E. coli lysate. The monoclonal anti‐T7 antibody recognizes
the T7‐LpR sequence demonstrating a clear and precise band at approximately 115 kDa. As expected, it
recognizes fragments of the control peptide in the lane to the right as well.
As a final test of the immunospecificity of the LpRv1 antibody, the sera were tested in preparations of
Drosophila who were deficient in their production of LpR2. To accomplish this, stocks were ordered
from the Exelixis Drosophila Stock Center at Harvard Medical School. These stocks contained piggyback
insertions which, though uncharacterized, were expected to disrupt the gene of interest. Each of these
stocks as well as the gene notation of their insertions is shown in table 1.
Table 1 A list of the gene disrupting insertions ordered from the Exelixis Drosophila Stock Center at Harvard Medical School. Contained in the list are the stock code, insertion notation and rack location for ordering. Stocks contained piggy back or p‐elements and were thought to disrupt LpR2 expression.
Stock Code Insertion Rack Location C02771 PBac[PB]LpR2c02771 XC161‐0338‐D11 E00374 PBac[RB]LpR2e00374 XC162‐4148‐A12 E01190 PBac[RB]LpR2e01190 SP102‐1714‐C04 E03380 PBac[RB]LpR2e03380 SP167‐3181‐B02 F03030 PBac[WH]LpR2f03030 STOUT‐2966‐B09 D04404 P[XP]LpR2d04404 SP332‐1789‐C04
43
Figure 16 Western blot analyses of stocks obtained from the Exelixis Drosophila Stock Center at Harvard Medical School. Flies were separated into heads (h) and bodies (b) for each genotype. Control flies of the yellow‐ white‐ genotype (yw) were employed. Markers were omitted for clarity as only relevant portions of the blot are shown. Black arrows represent the band of interest; as before rabbit 1 recognizes a band of approximately 100kDa while rabbit 2 recognizes an approximately 115kDa band. The immunoreactive product in rabbit 1 appears to be at a higher relative concentration than that of some of the mutants. The immunoreactive product from rabbit 2 does not change appreciably between yellow‐ white‐ controls and mutants.
Western blot data resulting from the mutant stocks is difficult to interpret. In samples from rabbit 1 in
the figure 16, yellow‐ white‐ (yw) controls appear to have a higher level of the peptide of interest than
some of the other fly genotypes. This is not absolute, however, given that at least equal quantity of
immunoreactivity seen with this antiserum in stocks of E01190 and E03380. In all stocks and genotypes,
as expected, Rabbit 1 recognized a peptide in the head of approximately 100kDa while rabbit 2
recognizes a peptide in predominantly body preparations of approximately 115kDa. All Exelixis stocks
obtained disrupt the gene LpR2 which should be immunoreactive with the antibody. We were unable to
find stocks containing deletions or disruptions from any of the public stock centres for LpR1. However,
given the observation that the antiserum from rabbit 1 shows some decline in immunoreactivity with
some preparations of the LpR2‐disrupted stocks and rabbit 2 does not, it seems that rabbit 1 has
produced an antibody more suited to LpR2 while Rabbit 2 has produced an antibody more suited to
LpR1. From these data we might also assume that LpR1 is the variant expressed predominantly in the
body of the fly while LpR2 is expressed predominantly in the head. This conjecture is, of course, only
partially substantiated by our results.
44
Ligand Blotting Assay Information about the Drosophila lipophorin receptor results mainly from comparisons with other
species. Transcript and protein product information is based on predicted sequences and therefore
requires substantiation through experimental evidence. Therefore, while the predicted sequences of
DmLpR1 and DmLpR2 and their numerous transcripts suggest that they have ligand binding domains
specific to lipophorin, this has yet to be determined experimentally. In order to do this, we used a ligand
blotting assay (figure 17). Also called a far western blot, this type of assay relies on an additional
hybridization partner in the ligand identification process. A western blot is prepared in the usual fashion
with the exception that at least one lane of the animal lysate is not subjected to the denaturing effects
of dithiothreitol, β‐mercaptoethanol, or extensive heating. The blot is incubated with the ligand of
interest (in this case lipophorin) prior to antibody incubation. The blot is then developed using anti‐
lipophorin antibodies and the appropriate secondary antibody. As mentioned in chapter 1, lipophorin is
composed of two molecular components deemed ApoLpI and ApoLpII. The larger component ApoLpI is
250kDa while the smaller is 75kDa. Neither of these sizes is similar to the 100‐115kDa lipophorin
receptor and hence a band on the ligand blot corresponding to this size range is indicative of a positive
result (the anti‐lipophorin antibody detecting lipophorin bound to its receptor). We would expect that,
since the lipophorin ligand is added to the solution and not electroblotted, it will be washed off unless
specifically bound to its receptor. Bands are 250kDa and 75kDa corresponding to one of the native
apolipophorin molecules are also expected since they constitute a portion of the Drosophila lysate used.
Figure 17 A schematic representation of the ligand blot assay used to determine whether or not the predicted Drosophila lipophorin receptor is able to bind lipophorin. Lipophorin (as well as many other proteins) are electroblotted onto nitrocellulose and then incubated with lipophorin, followed by anti‐LpI or anti‐LpII and then the appropriate alkaline phosphatase‐conjugated secondary antibody. The results of this blot indicate the position of lipophorin bound to the membrane through an interaction with the lipophorin receptor.
45
Prior to the ligand blot, lipophorin needed to be isolated (see materials and methods for procedure). In
vitro or ectopic expression methods such as cloned lipophorin components would not have sufficed for
this procedure; the lipophorin must be in its approximate native conformation in order to retain the
ability to bind to its receptor. In order to verify the lipophorin content of the collected haemolymph
DEAE‐cellulose eluents, a western blot was performed using both rat and‐LpI and rabbit anti‐LpII (figure
18).
Figure 18 Western blots to determine the specificity of the anti‐ApoLpI and anti‐ApoLpII antibodies as well as to determine the titer of native lipophorin within haemolymph extracts. Black arrows represent the expected band size of each apolipoprotein (250kDa for ApoLpI and 75kDa for ApoLpII). In each case, eluent 2 appears to contain the maximum immunoreactivity with the sera. Specificity of the anti‐ApoLpI antibody is questionable (left) but specificity of anti‐ApoLpII is acceptable (right).
Each of the three eluates from the DEAE‐cellulose chromatography performed on native haemolymph
extracts were used in the western blot. Rat anti‐ApoLpI antibodies detected a band at approximately
46
250kDa in each eluate but displayed the maximum immunoreactivity in the case of the second eluate.
Unfortunately, despite the large immunoreactivitiy, specificity was questionable as a result of the
numerous extra bands in the second lane. Although these bands could represent background noise of
the western blot, their absence in the other lanes is suggestive of a non‐specific antibody. The rabbit
anti‐ApoLpII, conversely, displayed remarkable specificity in all three eluates also with strong
immunoreactivity in the second eluate. Therefore, each of the eluates contains at least a small amount
of relatively pure native lipophorin; in addition, each of the antisera against the two apolipoproteins is
relatively specific but the anti‐ApoLpII seems to have very clean immunoreactivity.
The ligand blot was performed as indicated in the materials and methods (figure 19). It was expected
that only blot incubated with one of the haemolymph DEAE‐cellulose eluates would produce a signal
and this was confirmed by the absence of immunoreactivity on blots incubated with control solution
instead. No eluates in the absence of denaturing conditions produced any bands at the approximate
molecular weight of the lipophorin receptor when detection was performed with the rat anti‐ApoLpI
antibody. In fact, smears in each of these lanes suggest improper electrophoresis and potential ligand
binding given that these smears are absent under the control incubation condition. Under denaturing
conditions, a 250kDa band was visible in all three eluate incubations suggesting that it was ApoLpI
derived from the fly lysates. The absence of such a band in the control incubation with 0.2M phosphate
buffer is surprising and not readily explicable.
Under denaturing conditions in all four treatments performed with the rabbit anti‐ApoLpII antibody, a
75kDa band is visible (figure 19). This likely corresponds to the denatured ApoLpII from the fly lysates
electroblotted onto the nitrocellulose. The lanes with fly lysate prepared under non‐denaturing
conditions show remnants of a 75kDa band suggesting only partial denaturing as well as, in the case of
incubation with haemolymph eluate 2, a band at approximately 100kDa. Because several variants of the
predicted Drosophila lipophorin receptor are of approximately this size, this band likely results from an
interation between haemolymph‐borne lipophorin and its receptor immobilized on the western blot.
47
Figure 19 Ligand blot analysis of whole Canton‐S lysates. Lysates were prepared under denaturing (95°C, dithiothreitol) or non‐denaturing conditions and electrophoresed on polyacrylamide gels. Proteins were electroblotted onto nitrocellulose wherein they were incubated with a 1:500 dilution of one of the substances listed below each blot (0.2M phosphate buffer, one of three DEAE‐cellulose haemolymph eluates). Blots were then incubated with one of two primary antibodies at a dilution of 1:2000. a) Rat anti‐apoLpI, b) Rabbit anti‐ApoLpII. Development using the appropriate secondary antibody reveals the position of both lectroblotted and incubated lipophorin components. Black arrows at 250kDa, 75kDa, and 100kDa represent immunoreactivity ith apoLpI, ApoLpII and lipophorin receptor‐bound apoLpII, respectively.
ew
48
Effects of Lipophorin Receptor RNAi Two Drosophila lines containing antisense RNA directed against DmLpR1 and DmLpR2 were obtained
from the Vienna Drosophila RNAi Centre (Dietzl et al., 2007). Antisense RNA (RNAi) was placed under
the control of the yeast upstream activating sequence (UAS) which can be conditionally activated by the
presence of the yeast transcriptional activator GAL4. Both the RNAi line against LpR2 (CG31092, VDRC
No. 25684) and LpR1 (CG31095, VDRC No. 14756) were crossed into lines containing the UAS‐DCR2
construct (see materials and methods). Information about the sequence and lethality of both RNAi lines
is provided (Dietzl et al., 2007).
These UAS‐RNAi; UAS‐DCR2 lines were crossed to several GAL4 lines: embryonic lethal abnormal vision
(elav), pigment dispersing factor (pdf), R32 (clock‐cell specific), and heat shock. The expression pattern
of elav‐GAL4 has been described as panneuronal; R32 is known to be expressed in all clock cells of the
Drosophila brain while pdf is expressed in a subset of these. Finally, the heat shock promoter is known
to be approximately constitutively active but more strongly activated at temperatures of 37°C. Thus, for
two days prior to any testing, lines containing the heat‐shock GAL4 construct were heat shocked at 37°C
for one hour at the same circadian time each day. To determine if any of these GAL4 lines in
combination with the two RNAi‐DCR2 lines had an effect on the behavior of male Drosophila, flies were
placed in activity monitors. Flies were allowed to entrain to a 12:12h light‐dark cycle for at least 3 days
and were then placed in total darkness to monitor the free‐running rhythm. Flies were monitored by
summing the activity of beam breaks which occur each time the fly traverses its activity tube in one
minute intervals and performing analyses on the data (see materials and methods, figures 20‐24). Flies
whose activity patterns indicated that they had not survived the entire duration of the testing period or
had only survived some part thereof were removed from the analysis in all cases. Certain flies which
appeared to be arrhythmic were examined and removed where indicated.
49
Figure 20 Activity statistics generated for the following lines in approximately 10 days of total darkness: UAS‐LpR1 RNAi/heatshock‐GAL4 (top, n=16), UAS‐LpR2 RNAi/heatshock‐GAL4 (middle, n=16), w1118/heatshock‐GAL4 (bottom, n=16). Having no RNAi construct to interfere with gene expression, the third line should act as a control line. Shown are actograms of summed activity (left), corrected and averaged activity data (middle) and an autocorrelation plot containing estimates of the period as well as its significance (RS>1.0 indicates significance, RI indicates the vertical value of the * on the plot) (right).
50
Figure 21 Activity statistics generated for the following lines in approximately 10 days of total darkness: UAS‐LpR1 RNAi/pdf‐GAL4 (top, n=16), UAS‐LpR2 RNAi/pdf‐GAL4 (middle, n=15), w1118/pdf‐GAL4 (bottom, n=16). Having no RNAi construct to interfere with gene expression, the third line should act as a control line. Shown are actograms of summed activity (left), corrected and averaged activity data (middle) and an autocorrelation plot containing estimates of the period as well as its significance (RS>1.0 indicates significance, RI indicates the vertical value of the * on the plot) (right).
51
Figure 22 Activity statistics generated for the following lines in approximately 10 days of total darkness: UAS‐LpR1 RNAi/R32‐GAL4 (top, n=16), UAS‐LpR2 RNAi/R32‐GAL4 (middle, n=15), w1118/R32‐GAL4 (bottom, n=16). Having no RNAi construct to interfere with gene expression, the third line should act as a control line. Shown are actograms of summed activity (left), corrected and averaged activity data (middle) and an autocorrelation plot containing estimates of the period as well as its significance (RS>1.0 indicates significance, RI indicates the vertical value of the * on the plot) (right).
52
Figure 23 Activity statistics generated for the following lines in approximately 10 days of total darkness: UAS‐LpR1 RNAi/ELAV‐GAL4 (top, n=16), UAS‐LpR2 RNAi/ELAV‐GAL4 (middle, n=12), w1118/ELAV‐GAL4 (bottom, n=5). Having no RNAi construct to interfere with gene expression, the third line should act as a control line. Shown are actograms of summed activity (left), corrected and averaged activity data (middle) and an autocorrelation plot containing estimates of the period as well as its significance (RS>1.0 indicates significance, RI indicates the vertical value of the * on the plot) (right).
53
Figure 24 Activity statistics generated for the following lines in approximately 10 days of total darkness: UAS‐LpR1 RNAi/w1118 (top, n=15), UAS‐LpR2 RNAi/w1118 (bottom, n=15). Both lines were used as heterozygotes to test and control for the amount of leaky expression of the RNAi construct that could occur independent from GAL4 activation. Shown are actograms of summed activity (left), corrected and averaged activity data (middle) and an autocorrelation plot containing estimates of the period as well as its significance (RS>1.0 indicates significance, RI indicates the vertical value of the * on the plot) (right).
54
Figure 25 Bar graphs representing the average periods obtained for each of the 14 genotypic combinations placed in activity tubes. Genotypes are shown on the lower axis, mean period on the y axis. Error bars represent 95% confidence intervals for period estimates. In each graph, from left to right, genotypes are UAS‐LpR1 RNAi/GAL4, UAS‐LpR1 RNAi/w1118, UAS‐LpR2 RNAi/GAL4, UAS‐LpR2 RNAi/w1118, w1118/GAL4. Letters above each bar represent statistically homogenous subgroups based on Tukey’s HSD post‐hoc comparisons of means. a) One‐way ANOVA; F[4,73]=10.4, p<1.0x10
‐6. b) One‐way ANOVA; F[4,72]=3.2, p= 0.017. c) One‐way ANOVA; F[4,72]=5.5, p= 0.0006. d) One‐way ANOVA; F[4,58]=0.94, p= 0.45. Because the difference in mean period was not statistically significant in the case of the elav‐GAL4 driver line comparison, Tukey’s HSD post‐hoc test was not performed.
55
Figure 26 Bar graphs representing the average periods obtained for each of the 14 genotypic combinations placed in activity tubes once flies determined to be arrhythmic had been removed. Genotypes are shown on the lower axis, mean period on the y axis. In each graph, from left to right, genotypes are UAS‐LpR1 RNAi/GAL4, UAS‐LpR1 RNAi/w1118, UAS‐LpR2 RNAi/GAL4, UAS‐LpR2 RNAi/w1118, w1118/GAL4. Error bars represent 95% confidence intervals for period estimates. Letters above each bar represent statistically homogenous subgroups based on Tukey’s HSD post‐hoc comparisons of means. a) One‐way ANOVA; F[4,73]=10.4, p<1.0x10
‐6. b) One‐way ANOVA; F[4,71]=2.6, p= 0.043. c) One‐way ANOVA; F[4,69]=5.9, p= 0.0003. d) One‐way ANOVA; F[4,54]=1.03, p= 0.40. Because the difference in mean period was not statistically significant in the case of the elav‐GAL4 driver line comparison, Tukey’s HSD post‐hoc test was not performed.
56
Figure 27 Selected representative actograms from individual flies. Genotypes are indicated in the top left corner of each of the eight actograms. The top left actogram of genotype elav‐GAL4/w1118 is representative of a rhythmic fly while the other seven actograms are representative of the arrhythmic flies removed during some of the analyses. At the left side of each actogram are labels for each day; the day indicated as well as the next day are shown on a single line. Each day is therefore represented twice in an actogram. The notches at the bottom of each actogram represent the hours within a single day; because there are two days, a total of 48 hours are represented in each line. Black triangles indicate the last time a 12:12 light‐dark cycle was used to entrain the fly. Driven rhythms (those occurring as a result of a light‐dark cycle) occurred on days 1 through 3 and their activity has been omitted from this figure.
Table 2 Average period (hours) and percent arrhythmicity by genotype as judged by actograms collected on individual 4‐6 day old males of each genotype. Arrhythmic actograms are shown in figure 27. Period calculations are shown in figures 20‐24.
Genotype Total Arrhythmic % Arrhythmic Period (h)
UAS‐LpR1 RNAi / hs‐GAL4 16 0 0% 24.4 UAS‐LpR2 RNAi / hs‐GAL4 16 0 0% 24.1 w1118 / hs‐GAL4 16 0 0% 23.9 UAS‐LpR1 RNAi / R32‐GAL4 16 2 13% 24.5 UAS‐LpR2 RNAi / R32‐GAL4 15 0 0% 24.4 w1118 / R32‐GAL4 16 0 0% 24.3 UAS‐LpR1 RNAi / pdf‐GAL4 16 1 6% 24.1 UAS‐LpR2 RNAi / pdf‐GAL4 15 0 0% 23.8 w1118 / pdf‐GAL4 16 0 0% 24.1
57
UAS‐LpR1 RNAi / elav‐GAL4 16 2 13% 24.0 UAS‐LpR2 RNAi / elav‐GAL4 12 2 17% 23.8 w1118 / elav‐GAL4 5 0 0% 24.0 UAS‐LpR1 RNAi / w1118 15 0 0% 24.5 UAS‐LpR2 RNAi / w1118 15 0 0% 24.2
Figures 20 through 24 demonstrate averaged activity analysis plots for each genotype used in the
LpR1/LpR2 RNAi experiment. A period was yielded for each genotype and is shown in table 2.
Periods for individual flies were calculated through generation of individual actograms similar to those
found in figures 20‐24 (not shown). The three genotypes produced for each GAL4 driver line (UAS‐LpR1
RNAi, UAS‐LpR2 RNAi and w1118) along with the two control lines UAS‐LpR1/w1118 and UAS‐
LpR2/w1118 were compared in four one‐way ANOVA statistical tests. Tests of heat shock‐GAL4
(F[4,73]=10.4, p<1.0x10‐6), R32‐GAL4 (F[4,72]=5.5, p= 0.0006) and pdf‐GAL4 (F[4,72]=3.2, p= 0.017) were found
to be statistically significant while a test of elav‐GAL4 lines revealed no statistically significant difference
in period (F[4,58]=0.94, p= 0.45). On statistically significant differences in period, a Tukey’s HSD post‐hoc
comparison of means was performed. In the case of the heat shock‐GAL4 lines, it was found that UAS‐
LpR1 RNAi/ hs‐GAL4 as well as UAS‐LpR1 RNAi/w1118 produced statistically homogenous period which
were also statistically distinct from that of the w1118/hs‐GAL4 control line. While the pdf‐GAL4
statistical test revealed an effect of genotype on period, the Tukey’s HSD comparison revealed that both
LpR RNAi lines had statistically homogenous period with the control line w1118/pdf‐GAL4. Finally, while
both UAS‐LpR2 RNAi/w1118 and UAS‐LpR2 RNAi/R32‐GAL4 lines had statistically equal periods to the
control line w1118/R32‐GAL4, UAS‐LpR1 RNAi/w1118 and UAS‐LpR1 RNAi/R32‐GAL4 had statistically
longer periods.
Because the effect of arrhythmic flies present in the analysis (see figure 27, table 2) could mask the
potential results of period comparisons, they were removed and the above analyses were repeated.
Once more, tests of heat shock‐GAL4 (F[4,73]=10.4, p<1.0x10‐6), R32‐GAL4 (F[4,69]=5.9, p= 0.0003) and pdf‐
GAL4 (F[4,71]=2.6, p= 0.043) were found to be statistically significant while a test of elav‐GAL4 lines
revealed no statistically significant difference in period (F[4,54]=1.03, p= 0.40). Because no flies in the
heat shock‐GAL4 set of experiments were determined to be arrhythmic, this adjustment did not alter
significance. Significance was doubled by the removal of several arrhythmic flies in the case of the R32‐
GAL4 experiment, while it was nearly abolished in the case of pdf‐GAL4. As before, elav‐GAL4
experiments did not reveal a significant difference in period. As before, a Tukey’s HSD post‐hoc analysis
58
was carried out. The analysis did not change in the case of the heat shock‐GAL4 and pdf‐GAL4
experiments. In the case of the R32‐GAL4 experiment, however, UAS‐LpR2 RNAi/R32‐GAL4 had a
statistically distinct and shorter period from all other lines considered.
It was also noted that several of the LpR RNAi constructs in trans with GAL4 driver lines produced
arrhythmic flies. While these flies were excluded from some analyses with regard to period, they are
intriguing mainly because no arrhythmic flies of any control genotype (including UAS‐LpR1 RNAi/w1118
or UAS‐LpR2 RNAi/w1118) were observed (see table 2). Percent arrhythmicity was minimal; the
maximum proportion of arrhythmic flies within one genotype was 17% (2 out of 12 flies) in the case of
UAS‐LpR2 RNAi / elav‐GAL4. This is surprising given that the genotypes of this particular GAL4 line did
not yield statistically different periods. Most crosses did not produce arrhythmic flies.
In addition to the behavior of the files resulting from the GAL4/UAS‐RNAi crosses, their cuticular
hydrocarbons were also considered. Given the tangible relationship between lipophorin and cuticular
wax in other species, we wanted to determine the effects, if any, which might result from disruption of
one of the two lipophorin receptor classes in Drosophila melanogaster on cuticular hydrocarbons. Thus,
5 male flies from each genotype that were 4‐6 days old were placed individual in hexane to removed
their cuticular wax and the resultant solution was subjected to gas chromatgrophy and analysis (see
materials and methods). In the case of progeny bearing the heat shock‐GAL4 contruct, they were heat
shocked at least twice at 37°C at the same circadian time of day prior to hydrocarbon extraction. For all
genotypes, hydrocarbons were extracted at the same circadian time. Cuticular hydrocarbons from the
three genotypes produced for each GAL4 driver line (UAS‐LpR1 RNAi, UAS‐LpR2 RNAi and w1118) along
with the two control lines UAS‐LpR1/w1118 and UAS‐LpR2/w1118 were compared in a one‐way ANOVA
statistical test for each hydrocarbon compound. P‐values are shown in the table 3 below. Values of all
hydrocarbon species have been normalized to the added standard, nC26.
59
Table 3 Comparison of statistical significance by GAL4 driver line and cuticular hydrocarbon. One‐way ANOVA statistical analyses were performed on the cuticular hydrocarbons from the three genotypes produced for each GAL4 driver line (UAS‐LpR1 RNAi, UAS‐LpR2 RNAi and w1118) along with the two control lines UAS‐LpR1/w1118 and UAS‐LpR2/w1118. These GAL4 driver lines comprise the columns of the table. Each hydrocarbon was analyzed separately and the results are shown in each row. Non‐significant differences in hydrocarbon quantity among genotypes in each experiment are filled in green; moderately significant differences (0.001<p<0.05) are shaded in orange while strongly significant differences (p<0.001) are not filled. Hydrocarbons denoted nCXX comprise saturated hydrocarbons of chain length XX. Hydrocarbons denoted by CXX:1(A) comprise monounsaturated hydrocarbons of length XX with unsaturation at position A. Hydrocarbons denoted by 2MeCXX comprise methylated compounds with a methyl group at position 2 and length XX. cVA represents cis‐vaccenyl acetate.
GAL4 Driver/ Hydrocarbon elav‐GAL4 pdf‐GAL4 R32‐GAL4 hs‐GAL4
nC18 0.20849 0.001337 0.003043 0.007703
nC21 1.15E‐06 3.95E‐06 0.003371 0.000989
C22:1(7) 0.075592 1.37E‐07 0.037567 0.019352
cVA 0.00494 0.003361 0.262018 0.226506
nC22 5.46E‐09 6.51E‐07 2.23E‐05 2.68E‐07
C23:1(9) 0.000259 0.000533 0.010348 0.149218
C23:1(7) 4.49E‐06 0.004836 0.055439 0.003452
C23:1(5) 1.26E‐05 0.000657 0.000891 0.000241
nC23 3.28E‐09 6.12E‐06 8.41E‐06 0.000546
C24:1(9) 7.03E‐05 2.59E‐05 9.99E‐06 0.006622
C24:1(7) 2.6E‐08 0.042364 0.00497 0.017697
C24:1(5) 0.001706 4.42E‐05 1.19E‐05 0.001834
nC24 7.04E‐07 3.61E‐05 2.47E‐07 4.81E‐05
2MeC24 1.66E‐06 0.000179 0.000122 6.85E‐05
C25:1(9) 0.003508 0.842919 0.165333 0.075484
C25:1(7) 4.95E‐09 0.053826 1.29E‐07 0.003231
C25:1(5) 2.65E‐09 0.993703 0.00128 0.800813
nC25 6.14E‐05 0.000101 1.48E‐06 0.00068
nC26 . . . .
2MeC26 1.69E‐09 1.8E‐08 2.56E‐07 9.28E‐11
C27:1(7) 5.88E‐06 0.003818 0.015854 0.016842
nC27 1.19E‐06 0.00079 4.49E‐09 4.53E‐08
nC28 0.000493 0.011524 0.000156 0.000764
2MeC28 0.00121 0.004114 0.000245 8.07E‐08
nC29 5.3E‐05 0.001337 2.82E‐05 4.3E‐07
2MeC30 0.004343 3.95E‐06 0.001205 3.66E‐05
Several hydrocarbon species appeared to be undisturbed by the perturbation of the lipophorin receptor
in these experiments. Because nC18 is not found within the repertoire of hydrocarbons produced on
the fly, it was expected to be non‐ (or marginally) significant for each of the driver lines. Because nC26 is
the standard to which all other hydrocarbon values are normalized, its value was static and hence not
60
considered in statistical analyses. Cis‐vaccenyl acetate (cVA) was noted to have little statistical
significance throughout these analyses. Most other hydrocarbon species were at least moderately
affected by perturbations in lipophorin receptor RNA. Several species were strongly affected by all
driver lines used.
Because hydrocarbons may tend to behave in classes rather than as individual and distinct compounds,
they were also compared in this respect. Thus, the same comparison as above was carried out with the
exception that, rather than individual compounds, groups of compounds were used as multivariate
response variables. MANOVA was thus carried out on three separate classes of hydrocarbons
(saturated, unsaturated and methylated). The p‐values from Pillai’s trace were the most conservative
and are hence reported for this analysis. The MANOVA demonstrated that, when considered as classes
rather than individuals, all GAL4 driver line experiments produced strong effects in the cuticular
hydrocarbons of the individual flies.
Table 4 Table of p‐values of Pillai’s trace results from a Multivariate ANOVA (MANOVA) comparing the effects of genotype (three genotypes produced for each GAL4 driver line (UAS‐LpR1 RNAi, UAS‐LpR2 RNAi and w1118) along with the two control lines UAS‐LpR1/w1118 and UAS‐LpR2/w1118) on hydrocarbon class (multivariate).
Hydrocarbon Class / GAL4 Driver
Saturated Unsaturated Methylated
elav‐GAL4 <0.001 <0.001 <0.001 pdf‐GAL4 0.002 <0.001 0.002 R32‐GAL4 <0.001 0.002 <0.001 hs‐GAL4 <0.001 <0.001 <0.001
61
Figure 28 Individual comparison of hydrocarbon quantities in each genotype. Hydrocarbon identity is indicated as the y‐axis title. Bars on the x‐axis represent means from each genotype. Shorthand notations are used: LpR1 (UAS‐LpR1 RNAi), LpR2 (UAS‐LpR2 RNAi), w (w1118), hs (heat shock‐GAL4), pdf (pdf‐GAL4), elav (elav‐GAL4), r32 (R32‐GAL4). Error bars represent the standard error of the mean. Within each group of a single GAL4 experiment, the three treatments were compared with a one‐way ANOVA and Tukey’s HSD post‐hoc comparison of means (if applicable). Groups whose means were statistically different from the control group (w1118/GAL4) are indicated by black lines; * represents 0.001<p<0.05, ** represents p<0.001.
62
Figure 29 Individual comparison of hydrocarbon quantities in each genotype. Hydrocarbon identity is indicated as the y‐axis title. Bars on the x‐axis represent means from each genotype. Shorthand notations are used: LpR1 (UAS‐LpR1 RNAi), LpR2 (UAS‐LpR2 RNAi), w (w1118), hs (heat shock‐GAL4), pdf (pdf‐GAL4), elav (elav‐GAL4), r32 (R32‐GAL4). Error bars represent the standard error of the mean. Within each group of a single GAL4 experiment, the three treatments were compared with a one‐way ANOVA and Tukey’s HSD post‐hoc comparison of means (if applicable). Groups whose means were statistically different from the control group (w1118/GAL4) are indicated by black lines; * represents 0.001<p<0.05, ** represents p<0.001.
63
Figure 30 Individual comparison of hydrocarbon quantities in each genotype. Hydrocarbon identity is indicated as the y‐axis title. Bars on the x‐axis represent means from each genotype. Shorthand notations are used: LpR1 (UAS‐LpR1 RNAi), LpR2 (UAS‐LpR2 RNAi), w (w1118), hs (heat shock‐GAL4), pdf (pdf‐GAL4), elav (elav‐GAL4), r32 (R32‐GAL4). Error bars represent the standard error of the mean. Within each group of a single GAL4 experiment, the three treatments were compared with a one‐way ANOVA and Tukey’s HSD post‐hoc comparison of means (if applicable). Groups whose means were statistically different from the control group (w1118/GAL4) are indicated by black lines; * represents 0.001<p<0.05, ** represents p<0.001.
64
Figure 31 Individual comparison of hydrocarbon quantities in each genotype. Hydrocarbon identity is indicated as the y‐axis title. Bars on the x‐axis represent means from each genotype. Shorthand notations are used: LpR1 (UAS‐LpR1 RNAi), LpR2 (UAS‐LpR2 RNAi), w (w1118), hs (heat shock‐GAL4), pdf (pdf‐GAL4), elav (elav‐GAL4), r32 (R32‐GAL4). Error bars represent the standard error of the mean. Within each group of a single GAL4 experiment, the three treatments were compared with a one‐way ANOVA and Tukey’s HSD post‐hoc comparison of means (if applicable). Groups whose means were statistically different from the control group (w1118/GAL4) are indicated by black lines; * represents 0.001<p<0.05, ** represents p<0.001.
65
The 22‐carbon aliphatic hydrocarbon nC22 was found to be multiply affected by specific perturbations in
the lipophorin receptor (figure 28). Under ubiquitous knock down of the receptor, with the UAS‐RNAi
constructs under the promotional control of the heat shock promoter, nC22 was found to be
significantly less abundant than the control condition of hs‐GAL4/w1118. Additionally, under panneuronal
knock down as driven by the elav‐GAL4 line, a similar reduction in the abundance of nC22 was observed
in the case of UAS‐LpR2 RNAi while an equally significant increase in nC22 was observed when elav‐
GAL4 was used to drive UAS‐LpR1 RNAi. Although mean levels of nC22 under the control condition of
pdf‐GAL4/w1118 were elevated in comparison with other control flies, pdf driven knockdown of either
LpR reduced nC22 abundance. Finally, despite a tendency visible in figure 28, R32‐driven knock‐down of
either LpR did not provide statistically different abundances of nC22 as compared with R32‐GAL4/w1118.
The unsaturated pheromone C23:1(5) was also strongly affected by some of the knock‐down conditions
(figure 28). Panneuronal knock down of either LpR proved to reduce its abundance several fold; it
appeared, however, that the control condition elav‐GAL4/w1118 produced abnormally high levels of this
hydrocarbon. This pattern was apparent in several other hydrocarbon species and, though
extraordinary, represents the mean of five male flies and is hence unlikely to have resulted from
measurement error. Ubiquitous knock‐down of LpR1 produced statistically lower levels of C23:1(5) than
controls but no effect was observed when LpR2 was knocked down under the same promotional
control. Knock‐down of both LpRs under the control of R32‐GAL4 reduced C23:1(5) abundance
significantly but no significant difference in its abundance was detected under the control of the pdf
promoter. It should be noted that the control condition UAS‐LpR2 RNAi/w1118 seemed quite variable
and produced a high standard error of the mean.
nC23 was found to be reduced compared to controls only when LpR2 was knocked down panneuronally;
UAS‐LpR1 RNAi/elav‐GAL4 and elav‐GAL4/w1118 produced homogenous levels of nC23. Ubiquitous
knock‐down of LpR1 under the heat shock promoter, conversely, produced statistically reduced levels of
nC23 while similar knock‐down of LpR2 had no effect. The results of both R32 and pdf‐controlled
knockdown of either LpR are the same; abundance of nC23 was reduced in both cases (figure 29).
nC24 was found to behave strangely when LpR1 or LpR2 was knocked down under the control of elav‐
GAL4 (figure 29). LpR1 knock‐down produced statistically higher levels of nC24 while LpR2 knock‐down
had the opposite effect. In the case of heat shock‐GAL4 and R32‐GAL4, knock‐down of either LpR
reduced the levels of nC24 in a strongly significant manner. Under the control of pdf‐GAL4, however,
only knock‐down of LpR2 produced statistically lower levels of nC24 than controls.
66
Levels of 2MeC24 were among the most labile in these experiments as compared with other methylated
hydrocarbons. Statistically, however, only under the control of elav‐GAL4 were levels of 2MeC24
different from controls. Knockdown of either receptor under the control of elav‐GAL4 reduced levels of
2MeC24. All other treatment groups were relatively homogenous (figure 30). 2MeC26 (figure 31)
behaved in a nearly identical fashion to 2MeC24 further demonstrating that hydrocarbons are more
likely to behave in groups than as individuals. As with 2MeC24, 2MeC26 was knocked down when either
RNAi construct was placed under the control of elav‐GAL4 compared to elav‐GAL4/w1118 control flies.
The alphatic hydrocarbon nC25 (figure 30) was strongly affected under several experimental conditions.
The two clock‐cell promoters R32‐GAL4 and pdf‐GAL4 affected this hydrocarbon equally; levels were
strongly reduced compared to controls when either LpR was knocked down. In the case of the more
ubiquitous knock‐downs such as elav (panneuronal) and heat shock (ubiquitous), levels of nC25 were
reduced only when LpR2 was knocked down while levels remained homogenous with those of controls
when LpR1 was knocked down.
The longest aliphatic hydrocarbon to be strongly affected in most cases was nC27 (figure 31). Oddly,
while elav‐GAL4/UAS‐LpR2 RNAi produced levels of nC27 that were statistically homogenous with
controls, elav‐GAL4/UAS‐LpR1 RNAi flies exhibited close to a three‐fold increase in nC27. Under the
control of the heat shock promoter and the pdf promoter, only knock‐down of LpR2 produced
statistically lower levels of nC27. Under the control of the R32 promoter, however, knock down of
either LpR strongly reduced levels of nC27.
67
Figure 32 Comparison of total hydrocarbon quantities in each genotype obtained from adding the normalized values of each hydrocarbon compound for each fly. Bars on the x‐axis represent means from each genotype. Shorthand notations are used: LpR1 (UAS‐LpR1 RNAi), LpR2 (UAS‐LpR2 RNAi), w (w1118), hs (heat shock‐GAL4), pdf (pdf‐GAL4), elav (elav‐GAL4), r32 (R32‐GAL4). Error bars represent the standard error of the mean. Within each group of a single GAL4 experiment, the three treatments were compared with a one‐way ANOVA and Tukey’s HSD post‐hoc comparison of means (if applicable). Groups whose means were statistically different from the control group (w1118/GAL4) are indicated by black lines; * represents 0.001<p<0.05, ** represents p<0.001.
In addition to individual hydrocarbons, total hydrocarbon quantities on the cuticles of the males used in
the RNAi experiments were also compared (figure 32). Total levels of hydrocarbon were obtained for
each male considered by adding the quantities of the individual hydrocarbons which were originally
normalized to the standard nC26. Because nC26 is present in a fixed amount, adding the normalized
values together provides a valid, if not absolute, measure of total hydrocarbon content. Within each
group of a GAL4 experiment (GAL4/w1118, GAL4/UAS‐LpR1 RNAi, GAL4/UAS‐Lpr2 RNAi) the three
genotypes were compared via one‐way ANOVA and, if found to be significant, were divided into
homogenous subgroups through a Tukey’s HSD post‐hoc comparison of means. Groups whose means
68
were statistically distinct from the GAL4/w1118 control line were considered to have different
hydrocarbon quantities.
elav‐GAL4 driven knock‐down of LpR1 and LpR2 produced statistically lower total hydrocarbon quantity
on the cuticle. This difference was substantial (nearly three‐fold) in the case of elav‐GAL4/UAS‐LpR2
RNAi. When ubiquitously driven by the heat shock promoter, both RNAi lines produced lower levels of
total hydrocarbon but only the difference between controls and UAS‐LpR1 RNAi was found to be
statistically significant. A similar case was observed in the case of pdf‐driven knock‐down of LpRs. Only
in the case of UAS‐LpR2 RNAi were total hydrocarbon levels statistically lower than those of controls.
Finally, as with elav‐GAL4, R32‐GAL4 driven reduction of either LpR RNAi strongly reduced hydrocarbon
quantities. The hydrocarbon quantities of the control lines UAS‐LpR1 RNAi/w1118 and UAS‐LpR2
RNAi/w1118 were generally lower than each set of GAL4/w1118 lines. This could represent potential
leakiness of the UAS‐RNAi constructs.
To confirm that the effects observed in both activity and hydrocarbon experiments are the result of a
reduction in the abundance of one of the lipophorin receptor peptides, a western blot was performed
using LpRv1 serum harvested from both rabbits 1 and 2 (figure 33).
69
Figure 33 Western blot analysis of elav‐GAL4, pdf‐GAL4, R32‐Gal4 or heat shock‐GAL4 placed in trans with either UAS‐LpR1 RNAi or UAS‐LpR2 RNAi in male flies. Heads were separated and electrophoresed separately from the remainder of the fly (lanes h and b). LpRv1 antiserum from rabbit 1 was used in (a) and that from rabbit 2 was used in (b). Main bands recognized by the antisera in previous tests are indicated with black arrows (100kDa for rabbit 1 (a) and 115kDa for rabbit 2 (b)) although other bands may be apparent.
70
Despite relatively strong phenotypic data resulting from the UAS‐RNAi constructs, there is no strong
indication of a knock‐down of the protein product of either LpR1 or LpR2 from western blot data (figure
33). Antisera from rabbit 1, as discovered during the testing phase, recognize several potential peptides
in fly body lysates and one particular peptide (~90kDa) in the fly head. Neither of these appears to
change appreciably between GAL4/w1118 lines and GAL4/UAS‐RNAi lines. One exception may be the two
lower molecular weight bands in the fly body lysates of hs‐GAL4/w1118 as compared with UAS‐LpR2
RNAi/hs‐GAL4 which appears noticeably lighter. An interesting result obtained from the serum of this
rabbit is the lack of a band in the head lysates of elav‐GAL4/w1118 as comapared with elav‐GAL4 in trans
with either UAS‐RNAi line. This is indeed opposite of our expectations and may be an experimental
artifact.
Antisera from rabbit 1, as before, recognize a peptide relatively strongly at approximately 115kDa with
dominant immunoreactivity in head lysates. Very little variability in immunoreactivity is apparent when
using this antiserum. In accordance with the unexpected results obtained in the elav‐GAL4 experimental
lines when LpRv1 serum from rabbit 1 was used, UAS‐LpR1 RNAi/elav‐GAL4 appears to have much
higher immunoreactivity in the head lysates as compared with elav‐GAL4/w1118.
WholeMount Tissue Staining Using LpRv1 LpRv1 anti‐serum provided reliable results using western blotting techniques to identify the extent to
which tissues or genotypes express variants of the lipophorin receptor. To identify the areas of
localization of the protein confocal microscopy was used. The brains of female flies aged 5‐8 days were
dissected and fixed prior to staining with LpRv1 alone or in combination with other antibodies and then
staining with secondary antibody (see materials and methods). As with western blotting, it was
apparent that the sera from the two different immunized rabbits recognized different areas of the
Drosophila brain (figures 34 and 35). LpRv1 rabbit 1 appeared to recognize cells at the anterior of the
Drosophila brain near the point at which the optic lobe meets the rest of the brain. At least two (and
sometimes three) cells were strongly labeled in each preparation; results were repeated to confirm that
these cells were not being labeled as artifacts. Pre‐immune sera from this particular rabbit do not
strongly label any cells in the vicinity of those labeled by LpRv1 Rabbit 1 bleed 4 (figure 34, panel c).
These results were confirmed in multiple specimens.
71
Figure 34 Whole mount tissue staining of adult female Drosophila brains of age 5‐8 days using LpRv1 antiserum from rabbit 1, bleed 4. a) and b) represent different depths of the same brain stained with LpRv1 rabbit 1, bleed 4 using the 20X objective. c) shows a representative brain stained with the pre‐immune serum from the same rabbit and was generated with the 20X objective. e) represents the the portion of a) enclosed by a white box and was created with the 40X objective. f) represents the portion of b) enclosed by a white box and was created with the 40X objective. Strongly labeled cells are indicated by white arrows in panels a, b, d and e. Alexafluor® 568‐conjugated goat anti‐rabbit IgG was used as a secondary antibody.
72
Figure 35 Whole mount tissue staining of adult female Drosophila brains of age 5‐8 days using LpRv1 antiserum from rabbit 2, bleed 4. Both images were taken using the 20X objective. a) represents the pre‐immune serum of LpRv1 rabbit 2 while b) represents LpRv1 rabbit 2 bleed 4. Strongly labeled cells are indicated by white arrows. Alexafluor® 568‐conjugated goat anti‐rabbit IgG was used as a secondary antibody.
73
Figure 36 Whole‐mount tissue staining of adult female Drosophila brains of age 5‐8 days using LpRv1 antiserum from rabbit 2, bleed 4 as well as anti‐PDF serum produced in guinea pig. Secondary antibodies were Alexafluor® 488‐goat anti‐rabbit IgG and Cy5‐goat anti‐guinea pig IgG. A 40X objective was used in a) while a 20X objective was used in b). Conditions were identical in a) and b) except that pre‐immune serum, rather than production bleed, was used as anti‐LpR.
LpRv1 rabbit 2 appeared to recognize cells near the posterior (bottom) of the Drosophila brain near the
point at which the optic lobe meets the rest of the brain. One, or potential two cells were strongly
labeled in each preparation; results were repeated to confirm that these cells were not staining
artifacts. Pre‐immune sera from this particular rabbit confirm that these results have not been obtained
in err; staining of the whole brain using LpRv1 rabbit 2 pre‐immune serum produces brains lacking
strongly labeled cells (figure 34, panel a).
To determine if LpR is found in clock neurons, we used whole‐mount tissue staining with two antibodies;
the first was directed against pigment dispersing factor (pdf), which is known to label a subset of clock
cells in the Drosophila brain. The second was LpRv1 rabbit 2 bleed 4. It was found that, while LpRv1 and
74
anti‐PDF label the same set of approximately four distinct cells (figure 36, panel a), this labeling was
shared when LpRv1 was exchanged for pre‐immune serum from LpRv1 rabbit 2 (figure 36, panel b). The
labeling is not identical in both experiments, but in each case the anti‐PDF labels the same neurons as
LpRv1 as well as its control; these results were repeatable. This suggests that staining of the clock cells
by LpRv1 during these experiments may have been artifactual.
Discussion
LpRv1 Recognizes the Lipophorin Receptor The specificity of LpRv1 as well as its affinity for the lipophorin receptor was tested in multiple ways.
The first method used was ectopic overexpression of an LpR variant in E. coli. This was accomplished by
sub‐cloning LpR2 transcript E (CG31092) into the Novagen® pET21 expression vector. Despite our
inability to clone both of the lipophorin receptor variants (CG31095) into a suitable expression vector,
the cloned LpR2 should be sufficient to demonstrate the efficacy of the antibody. Primarily, the
antibody was raised against a sequence that was common to the variants of the lipophorin receptor.
Thus, despite a lack of variety in the E. coli expression controls, LD11117 in pET21 should suffice. Also,
there are least 10 transcripts predicted for the Drosophila lipophorin receptor and each has a differing
coding sequence. The inability to obtain all of these transcriptional variants in Drosophila Genome
Project clones would make verification that LpRv1 recognizes all LpR variants with equal specificity
impossible. It is, however, reasonable to clone more LpR transcript variants for further verification of
LpRv1 as each variant may have different folding patterns which may obscure or enhance antibody
reactivity. This is unlikely to affect SDS‐PAGE western blots as they depend on the denaturation of the
antigen prior to its electrophoresis; it may, however, be useful in experiments using native‐PAGE.
LpRv1 antiserum from both rabbits was able to recognize the cloned LpR (figure 15). In addition, the
same band was identified by a monoclonal anti‐T7 antibody. Because the T7‐tag epitope is absent in E.
coli, this is acceptable verification that LpRv1 recognizes the same peptide as anti‐T7; hence, LpRv1
recognizes T7‐LpR2. E. coli controls are a useful and convenient method for testing an antibody but are
ultimately foreign to the model organism of interest. Because they ectopically express a foreign protein,
there is a possibility that it will not be synthesized properly due to the physiological conditions within
the bacterium. There is also a possibility that the overexpression of LpR in E. coli does not reflect is
proportions in fly tissues; thus a specific antibody with weak affinity may recognize overexpressed LpR2
75
but fail to recognize a peptide in Drosophila lysates. It was for these reasons that LpRv1 bleeds were
tested in western blots of fly lysates (figure 14).
Strangely, given that the rabbits used for immunization were injected with the same peptide sequence,
each rabbit produced a serum that seemed to be preferentially reactive with a different variant of the
lipophorin receptor. Because both LpR1 and LpR2 produce variants with molecular weights ranging
from 90 to 120kDa, it is impossible to judge the contributing LpR variant from the simple size difference
between the immunoreactive peptides. The western blots indicate not only a size difference between
the immunoreactive peptides, but a potentially interesting tissue distribution. Flies in these experiments
were separated into head and body preparations. It was found that antisera from rabbit 1 recognized a
100kDa band in fly body lysates with relatively little reactivity in heads. By contrast, serum from rabbit 2
exhibited a different phenomenon in which a slightly larger band (~115kDa) was recognized almost
exclusively in the head of the fly while a much lighter band of this size was detected in the body. If the
100kDa band represents one or several variants of the lipophorin receptor, its size at least rules out
several variants. The band could represent multiple similarly sized peptides, and its level of reactivity
could represent either differential immunoreactivity of LpRv1 with variants of the receptor or different
expression levels of LpR variants. The 100kDa band is likely to be LpR1‐PA, LpR1‐PC, LpR2‐PF, or a
combination of those. The 115kDa band has a greater number of possibilities: LpR1‐PB, LpR1‐PF, LpR2‐
PA, LpR2‐PC, LpR2‐PE or LpR2‐PG. Once more, some combination of these is equally possible. The band
or bands reacting with LpRv1 could be identified if more precise western blotting tools were used.
Other bands exist in the western blots performed to date but their presence is deemed background.
The presence of high molecular weight bands with dense immunoreactivity could also be glycolylsated
lipophorin receptor. Without a Drosophila control line in which all forms of LpR have been removed,
such as a null mutant, the confounding bands found using LpRv1 cannot be completely considered
background and could represent degradation products of LpR. Because LpR is ectopic to E. coli,
however, and because E. coli overexpressing ectopic proteins not related to LpR show little
immunoreactivity on western blots with LpRv1, we judge the antibody to be relatively specific.
What could cause the two different rabbits to develop antisera with varying degrees of specificity is
unclear. The only reasonable explanation is that the antibodies produced, assuming that the local
amino acid environment influences their interaction with LpR, were somehow unable to reach the
epitope in some versions of the lipophorin receptor.
76
While a lipophorin receptor null mutant would have been the most useful fly genotype in characterizing
LpRv1, a sufficient reduction in LpR protein content would serve the purpose equally well.
Unfortunately no experimental evidence has verified any mutant stock which exhibits reduced LpR
expression. We ordered several stocks from the Exelixis stock collection at Harvard Medical School
(table 1) each containing a p‐element mediated insertion that was thought to disrupt the LpR2 gene. It
was clear that LpRv1 Rabbit 2 Bleed 4 did not recognize any difference among the genotypes indicating
that either this antiserum is ineffective or it recognizes more specifically some variant of LpR1. The
second possibility is more likely given the affinity of production bleeds of rabbit 2 for ectopically
overexpressed T7‐LpR. LpRv1 Rabbit 1 Bleed 4 showed some difference in the 100kDa band among the
genotypes considered. The 100kDa band appears to be reduced in most of the stock genotypes
compared to yellow‐ white‐ except in the case of E01190. Since characterization of these lines has not
been performed, it is impossible to determine whether or not this result is spurious. Western blots
were repeated many times with these lines, each generating a similar result. At the very least, it does
not rule out the efficacy of LpRv1.
The Lipophorin Receptor Binds Lipophorin We performed a ligand blotting assay (figures 17 and 19) to determine whether or not a peptide the size
of the lipophorin receptor identified by LpRv1 binds to lipophorin itself. In order to perform the ligand
blotting assay we collected Drosophila haemolymph using a modified procedure which has been
described (Lucas et al., 2004). While ectopic overexpression of lipophorin may have been a more
suitable method to obtain purified lipophorin, the two apolipoproteins that constitute mature
lipophorin are known to require post‐translational processing and are hence unlikely to be correctly
translated in E. coli (Kutty et al., 1996; Smolenaars et al., 2005). Three 1mL eluates of DEAE‐cellulose‐
purified haemolymph exhibited strong immunoreactivity with the anti‐ApoLpI and anti‐ApoLpII
antibodies (figure 18). From figure 18, it appeared that the second haemolymph eluate contained the
most ApoLpI and ApoLpII (and, by inference, the most native lipophorin before being subjected to SDS‐
PAGE). The second eluate, also appeared to have the least refined immunoreactivity in the case of anti‐
ApoLpI; it showed multiple bands of lower molecular weight than the predicted 250kDa suggesting
potential degradation of the antigen or cross‐reactivity of the antibody. Anti‐ApoLpII, conversely,
showed strong immunoreactivity against the second eluate which was well‐localized to the 75kDa range
of the expected band. Thus, it was expected that the anti‐ApoLpII antibody would yield clearer results in
the ligand blot.
77
The Anti‐LpI antibody, while giving a clear signal at 250kDa in the denatured lane, produced a cryptically
strong signal in the native lane of the gel (figure 19). The denatured lane acts as an internal control for
the antibody and confirms its affinity for ApoLpI; the extensive reactivity throughout the native lane is
difficult to interpret. The structure of ApoLpI has not been well studied; it is therefore possible that
under non‐denaturing electrophoresis conditions, its movement within a polyacrylamide gel is
unpredictable and does not correspond with its size. This would explain the relatively widespread
reactivity in the native lane. It is also unclear why the control gel for ApoLpI showed no
immunoreactivity; because fly lysates were used rather than in vitro transcribed LpR as in other studies
(Lee et al., 2003) we would expect to identify a band at the approximate size of ApoLpI in all cases.
The experimental ligand blots using the anti‐ApoLpII antibody suggest that the lipophorin receptor does
bind lipophorin or, more specifically, a compound containing ApoLpII that is believed to be lipophorin.
As in the case of anti‐ApoLpI, there is a dearth of immunoreactivity in the control blot in which no
lipophorin was used; in the denatured lane there is a trace of immunoreactivity at approximately 75kDa.
This band is apparent in both lanes of the other three blots (figure 19). When haemolymph eluate 2 was
used, however, a band of approximately 100kDa is observed in the native lane but not the denatured
lane. This result supports the proposition that the 100kDa band identified by LpRv1 is indeed a variant
of the Drosophila lipophorin receptor. Several problems exist, however. Because there are multiple
variants of the lipophorin receptor in Drosophila containing the ligand binding sequence, we would
expect much more diverse immunoreactivity in the native lane than was observed. Immunoreactivity
would be expected for sizes ranging from 90 to 120kDa. One possibility is that the 100kDa lipophorin
receptor band (which may be composed of multiple similarly‐sized variants) simply contains more
protein than other lipophorin receptors and was more visible with the development techniques used in
the ligand blotting. This would also explain the preferential affinity for the 100kDa band seen using
LpRv1 Rabbit 1 antisera. It is also surprising, given the immunoblots in figure 18, that only eluate 2
produced immunoreactivity at the expected apparent molecular weight; eluates 1 and 3 contained
proteins with relatively high immunoreactivity towards anti‐ApoLpII. It is thus unclear why only one
eluate produced a signal at 100kDa during ligand blotting. It is possible that the conformational
condition of the lipophorin is dependent on concentration; in this case eluate 2, having the highest
apparent concentration of ApoLpII would retain more lipophorin in its native conformation. In either
case this result should be repeated for verification of the lipophorin receptor immunoreactivity. It
would also be beneficial to use ECL chemiluminescent development techniques on PVDF membranes in
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order to enhance the detection sensitivity of the method as compared with alkaline‐phosphatase
development on nitrocellulose membranes.
Circadian Rhythms are not Affected by the Lipophorin Receptor Using LpR1 and LpR2 RNA interference lines obtained from the Vienna Drosophila RNAi Centre (VDRC)
we attempted tissue‐specific reduction in the levels of LpR1 and LpR2. Figures 20‐24 demonstrate that
circadian rhythm is certainly not abolished by the tissue‐specific activation of UAS‐LpR1/2 RNAi. What
was interesting to note was that several flies containing RNAi constructs transcriptionally activated by
several of the GAL4 constructs were arrhythmic. This finding suggests that there may be a genotypic
effect on circadian rhythm in these experiments that may have reduced penetrance in the test
population.
While period averages were computed for each genotype and are shown in figures 20‐24, individual
rhythms were also computed (data not shown) and used to calculate variability in circadian rhythms
among each genotype. These data were then used to determine statistically (using ANOVA) whether the
period was significantly different among the gentoypes. In each case, UAS‐LpR1/2 RNAi in trans with
each GAL4 line as well as w1118 were compared (figure 25). Control lines were considered to be
GAL4/w1118 and therefore only genotypes whose periods differed from the control lines were likely to be
biologically significant in addition to their statistical significance.
Heat‐shock driven knockdown of LpR1 produced a statistically higher rhythm than that of controls.
While each experiment with the exception of that using pdf‐GAL4 as an expression driver had an overall
significance, the control groups were statistically homogenous with UAS‐LpR1/2 RNAi/GAL4 suggesting
that a statistical type one error had been made. Flies which demonstrated a lack of circadian rhythm
were removed from the data and it was re‐analyzed using the statistical measures previously
mentioned. Because no flies were arrhythmic in the heat‐shock experiment, this did affect heat shock
results. Results using R32‐GAL4, however, were altered. In this case, only R32‐GAL4/UAS‐LpR2 RNAi
produced a statistically reduced rhythm with respect to controls.
The effects observed here are cryptic. While there is much statistical significance, the minor changes in
period that have produced it are far smaller than what the field of circadian rhythms usually accepts as a
significant difference. The statistical relevance of the experiment, however, is not lost. By comparison
to some experiments, small numbers of flies were used in this experiment (n=16, maximum). When
small numbers are used, however, there is generally a greater variability in means and hence a taller
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statistical barrier to significance; when large numbers of tests subjects are used, statistical parameters
relax to the point where false positives are commonplace. This would therefore suggest that the results
of our RNAi experiment are the opposite of what might be expected; using small numbers of flies and
obtaining the levels of significance we obtained certainly demands further experimentation with larger
numbers of test subjects to verify repeatability.
Although we observe effects of the lipophorin receptor RNAi in this case, it is necessary to
experimentally verify the knockdown of the lipophorin receptor protein through western blotting (figure
33). The results in figure 33 do not demonstrate a knockdown of the receptor. This does not necessarily
indicate a spurious or artifactual result for RNAi experiments. One possible explanation relies on the
localized expression drivers used. Both pdf‐GAL4 and R32‐GAL4, assuming that they are only activated
in the cells in which we would expect them to be active, are expressed in an extremely small number of
neurons. Therefore, unless a substantially large proportion of the total lipophorin receptor protein pool
is expressed in these cells, western blotting would be unlikely to detect a reduction in protein quantity.
The reason that little knockdown was observed using elav‐GAL4 driver lines is also unclear. Assuming
that elav‐GAL4 is expressed exclusively in neurons, we would expect to observe a substantial knockdown
of LpR in the head preparations. This either suggests that the RNAi lines are ineffective or that the
lipophorin receptor, while expressed in the heads of the flies, is not expressed extensively in the brain.
The lipophorin receptor could instead be expressed in cuticular, fat body or antennal region of the head.
In heat shock‐GAL4 lines, there appears to be an experimental difference; two low molecular weight
bands (approximately 85‐90kDa) appear to have a higher level of immunoreactivity in w1118/hs‐GAL4
controls than UAS‐LpR2 RNAi/hs‐GAL4 flies when LpRv1 Rabbit 1 Bleed 4 was used. Because the heat
shock promoter exists ubiquitously throughout Drosophila cells, we expect the knockdown to be
strongest and most apparent in this particular set of GAL4/UAS lines. The fact that the aforementioned
difference is the only observable difference among all gentoypes is disquieting and merits further
experimentation, perhaps using RNA techniques to verify the knockdown of the lipophorin receptor.
Cuticular Hydrocarbons are Affected by the Lipophorin Receptor Many cuticular hydrocarbons of male Drosophila melanogaster appear to be strongly affected by the
genotypes used in the RNAi experiments (table 3). Due to the fact that nC18, an internal standard
added to the hexane mixture prior to gas chromatography, appeared to change significantly in several
experiments, the acceptable level of type one error was adjusted to reduce false positives; differences
were deemed strongly significant if their p‐values were below 0.001.
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Graphs of the levels of strongly affected hydrocarbons are shown for each genotype in figures 28‐31
while a comparison of the total hydrocarbon quantity on the cuticle is shown in figure 32. Because
lipophorin is thought to ‘carry’ hydrocarbons to their site of deposition (the cuticle), we expected that
knocking down the lipophorin receptor, at least in the more ubiquitous GAL4 driver lines such as heat
shock and elav‐GAL4 would reduce hydrocarbon content. This was observed for total hydrocarbon
quantity in which most combinations of GAL4/UAS RNAi resulted in statistically lower hydrocarbon
quantities as compared with the appropriate GAL4/w1118 control line. Notable exceptions are UAS‐LpR2
RNAi/heat shock GAL4 and UAS‐LpR1 RNAi/pdf‐GAL4. While reducing the levels of LpR1 in a countable
number of cells such as those expressing pdf may not be expected to reduce total hydrocarbon
quantities, ubiquitous LpR reduction as in the case of UAS‐LpR2 RNAi/heat shock‐GAL4 would be
expected to reduce total hydrocarbon. The reason for this discrepancy is unclear, especially considering
that, in both non‐significant cases the other UAS‐LpR RNAi genotype did produce a reduced total
cuticular hydrocarbon quantity.
Individual hydrocarbons varied considerably as compared with their total. Some, such as cVA and most
monoenes 25 carbons in length, were generally not affected by these experiments. This is not surprising
in the case of cVA as this particular hydrocarbon is synthesized in the ejaculatory bulb and is thought to
be transferred to the female in the ejaculate during copulation to deter further copulation with other
males (Butterwo.Fm, 1969). It is, however, surprising in the case of the 25 carbon monoenes as these
have been one of the few hydrocarbons whose behavioural effects have been studied to date. Large
quantities of these 25 carbon monoenes have been shown to induce wing vibration in males suggesting
that they have a role in courtship (Jallon, 1984; Jallon et al., 1980). The observation that they are largely
unaffected by GAL4‐driven repression of the lipophorin receptor in ubiquitous instances such as heat
shock‐GAL4 is surprising and may suggest that these communicatory pheromones reach the cuticule
through an alternative route. These compounds were strongly affected only using the elav‐GAL4 driver
to knock down LpR expression; though cells containing elav‐GAL4 should also have contained hs‐GAL4
this result suggests that knock‐down of the lipophorin receptor in non‐clock neurons may affect
hydrocarbon output. Because it does not seem to occur when knockdown is ubiquitous, the effect may
represent an element of neuronal control of hydrocarbon output rather than the mechanical inability to
display hydrocarbons.
In several cases, UAS‐LpR1 RNAi/elav‐GAL4 was found to have a higher level of certain cuticular
hydrocarbons than the appropriate GAL4 control line. This was observed especially in nC22, nC24 and
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nC27. The fact that the three hydrocarbons most strongly affected are of the same class suggests a
biologically significant effect. Also, the observation that neural‐specific knockdown of LpR1 repeatedly
produces this effect suggests that it is unlikely to be experimentally artifactual.
The most strongly affected monoene hydrocarbon was C23:1(5) or 5‐Tricosene. The effects of this
hydrocarbon have been studied in a preliminary fashion in several Drosophila strains and have been
inconclusive (Hedlund et al., 1996). One study found that 5‐tricosene had a strong inhibitory effect on
copulation and significantly delayed in the onset of male courtship behavior (Ferveur and Sureau, 1996).
We find a strong reduction in the levels of 5‐Tricosene on male flies when UAS‐LpR1 RNAi is driven by all
GAL4 drivers used except pdf‐GAL4. The situation is similar for the case of UAS‐LpR2 RNAi with the
exception that heat shock‐GAL4 driven expression does not produce a significant effect on 5‐Tricosene.
Without fully understanding the behavioural effects of this hydrocarbon, assigning meaning to its
reduction is challenging other than to identify that its actions are related to the lipophorin receptor in
some way.
Methylated, or branched hydrocarbons are a distinct class with little known effect in Drosophila.
Evidence from the wasp model system indicates that the quantity of these hydrocarbons may be
involved in nestmate recognition; wasps perfumed with excess methylated hydrocarbons have been
shown to be rejected by their nestmates (Howard and Blomquist, 2005). Here we show the most
significant RNAi effects on 2‐methyl‐tetracosane (figure 30) and 2‐methyl‐hexacosane (figure 31). Both
hydrocarbons only show a significant reduction from controls under the promotion of elav‐GAL4; both
UAS‐LpR1 and UAS‐LpR2 RNAi demonstrate significant reduction. Examining the means of the other
control and experimental genotypes found in the same graphs, however, suggests that it may be the
unusually high level of both these compounds in elav‐GAL4/w1118 causing the significance. The reason
for the high levels associated with this control genotype are unclear; they are repeated in at least these
two cases yet may represent experimental artifacts. Only further experimentation can determine
whether or not this control genotype is producing the observed effect.
They effects shown for hydrocarbons in these RNAi experiments are unclear. While it seems logical to
assume that down regulation of the lipophorin receptor in numerous tissues would be likely to equally
down regulate cuticular hydrocarbon expression, this is not always the case. In fact, several
hydrocarbons appear to undergo a concomitant increase with lipophorin receptor reduction. The
results shown here are preliminary; experiments of this nature are usually performed in triplicate at a
minimum to verify that the observed effects are not spurious. It is for this reason that this experiment
82
must be repeated to verify the observed effects. Our failure to demonstrate a strong knock down of the
lipophorin receptor, as previously mentioned, confounds the results obtained here as well. In
ubiquitous cases such as under the control of the heat shock‐GAL4 driver, we would expect the UAS‐
RNAi constructs, assuming that they work correctly, to significantly reduce the protein quantity of the
lipophorin receptor. Instead, in most cases, we observe little or no difference. Repetition of the
western blots shown in figure 33 is a necessity prior to drawing any experimental conclusion.
Additionally, the use of reverse‐transcriptase quantitative PCR could be used to determine LpR
transcript levels in response to these knock down experiments; this, or more sensitive western blotting
techniques, could demonstrate a knock down.
An additional possibility is that there are confounding effects caused by the inclusion of UAS‐Dicer‐2
with each RNAi line. Ideally, Dicer‐2 or any gene upstream of the yeast upstream activating sequence
would only be active in the presence of GAL4; additionally, GAL4 would only be present under the
desired promotional control. Unfortunately these ideals are rarely true and leaky UAS expression as
well as promiscuous GAL4 activity are experimental realities. In addition, because Dicer‐2 is an
endogenous gene involved in the natural RNAi‐like pathways of Drosophila, its upregulation may cause
additional effects in addition to enhancing the effects of RNAi. For this reason, future experiments of
this nature should contain the omitted controls involving UAS‐Dicer‐2 expression driven by each of the
GAL4 lines used.
The Lipophorin Receptor is Present in the Brain Although it was demonstrated through western blotting that the heads of flies contain peptides which
are immunoreactive with LpRv1, this does not conclusively implicate the central nervous system or brain
as expressing the lipophorin receptor. Several tissues of non‐neuronal nature exist in the head and
could express LpR. For this reason, the LpRv1 antisera were used in whole‐mount tissue staining
applications of the Drosophila brain (see materials and methods). Although pre‐immune sera
demonstrated little or no immunoreactivity on western blots and identification of LpR has been
demonstrated, the differing envioronment of whole‐mount tissue staining necessitated additional
controls. Under whole‐mount conditions, as opposed to western blots, proteins are in their native
conformation with the exception that they have been fixed using organic reagents. Proteins in whole‐
mount tissue would therefore be in a different conformation than the same proteins encountered on a
western blot in their denatured, partially linear conformation. Thus, immunoreactivity could be
increased in tissues, possibly due to epitpopes on proteins which occur only when part of the peptide
83
backbone folds to come in contact with another area. Similarly, immunoreactivity could be reduced
because epitopes are obscured by the tertiary structure of the protein.
Pre‐immune sera from LpRv1 rabbit 1 and rabbit 2 were tested in Drosophila brains (figures 34, panel c
and 35, panel a). It is clear from each of these results that there is little or no immunoreactivity beyond
what may be considered background levels. Thus, the fourth production bleed of each antiserum was
tested in the same tissue. Antisera from rabbit 1 recognize approximately four cells at the anterior
portion of the brain near the border between the optic lobe and the midbrain. These cells are shown in
figure 34 panels a, b, d and e). Our understanding of the position and potential identity of these cells is
incomplete. These cells are close to the area in which we would expect pdf‐containing neurons to
reside; for this reason we plan to test them using LpRv1 antiserum in conjungtion with an anti‐pdf
antibody to examine colocalization.
Antisera from the second rabbit recognize a set of cells in the same region as those from rabbit 1 but,
additionally, strongly recognize cells at the posterior portion of the brain also along the border between
the midbrain and optic lobe. Although we are unable to identify the cells at the posterior portion of the
brain, we suspect that the anteriorly labeled cells are clock neurons. For this reason we tested LpRv1
antiserum together with anti‐PDF antiserum in a colocalization experiment (figure 36). While we did
observe colocalization when LpRv1 rabbit 2 bleed 4 was paired with guinea pig anti‐PDF, similar
colocalization was observed in the case of the pre‐immune serum from the same rabbit. For this reason
we must consider the immunoreactivity of the anterior cells spurious. The posterior cells which were
strongly labeled, however, were completely absent when using pre‐immune sera suggesting that they
are indeed viable results.
Conclusions and Future Directions While the main feature of this work was the production, testing and potential future use of the
antiserum against the lipophorin receptor of Drosophila, several experiments of a preliminary nature
were carried out. We can be relatively confident, given the number of subjects used in the experiment,
that the lipophorin receptor RNAi, when activated by any of the GAL4 lines used, is unlikely to have a
major effect on circadian rhythm in locomotor activity. This is because, although significant, the
differences between control lines and experimental lines were often small and not of the caliber which
generally denotes significance in this field. We infer reliability of these data as a result of their relative
cleanliness and the strength of the rhythms observed.
84
It is clear that there is an effect on cuticular hydrocarbons using lipophorin receptor RNAi. Several GAL4
driver lines have already been employed in these pilot experiments but these represent a small portion
of those which may have an effect. Because of their role in hydrocarbon production, a fruitful future
experiment may involve an oenocyte‐specific GAL4 line which has been generated by our lab; in
addition, a ubiquitous GAL4 driver such as actin‐GAL4 may be more suitable to demonstrate the
widespread effects of the lipophorin receptor. Finally, cuticular hydrocarbons have their most
interesting effects on behaviour. Therefore, it would be beneficial, if a substantial knock down in
lipophorin receptor content could be demonstrated, to use GAL4/UAS‐LpR RNAi flies in behavioural
courtship experiments. In this manner, courtship anomalies could be detected and related to
subsequent reduction or increase in the quantity of certain hydrocarbons. To validate these and other
experiments, however, the effectiveness of the two RNAi lines employed must be verified at the
transcript or protein level.
We have only begun to identify the tissues in which the lipophorin receptor is expressed. In this work
we demonstrated that at least two LpR variants are present in the head of the fly through western
blotting and whole‐mount tissue staining. Dissection of other tissues for use in western blotting and
tissue staining could demonstrate additional locations of the lipophorin receptor. Specifically, dissected
oenocytes would be of primary interest given their role in hydrocarbon production. Also, LpRv1 is only
capable of identifying lipophorin receptors in general. A more specific method for identifying each
variant of the lipophorin receptor would involve production of isoform‐specific antibodies. This venture
would be costly and time consuming; an alternative would be the use of fluorescence in situ
hybridization (FISH) techniques that depend on nucleotide base‐pairing rather than antibody‐antigen
interactions. These have the added advantage of variant specificity and reduced background. In this
manner, variants in different tissues such as the head, antenna, or cuticle could be detected using
dissection followed by northern blotting techniques. In addition, the specific variants in the brain (or
other tissues) could be identified using FISH techniques and confocal microscopy.
Performance of these and similar experiments in Drosophila melanogaster represent an exciting new
area of research which combines the current interest in lipid metabolism and biochemistry with that of
social and chemical communication in a genetically manipulable species. While Drosophila is not a
traditional model species for lipid research, it is clear that benefits such as a sequenced genome,
countless genetic tools, as well as social and hydrocarbon research could be well applied to this area.
85
Appendix Subcloning of desat1 Using the primers desatF (5’‐AAGGATCCAACATGCCGCCCA‐3’) and desatR (5’‐
GGGAATTCCTAAACCCTCCCATGATTGG‐3’) desat1 (CG5887) cDNA clones from the Canadian Drsophila
Microarray Centre GH23546 and RH21245 were subjected to PCR. These 1.1 kb PCR products were both
cloned into pCR 2.1 TOPO vectors which were transformed into TOP10F’ E. coli strains, and then
subcloned into E. coli pET21 vectors in the BL21 strain for overexpression. Both were successfully
cloned but only GH23546 produced a protein product of the correct length (43 kDa) while RH21245
appeared to have a truncated product (21 kDa). SDS‐PAGE expression assays were not sensitive enough
to display the ectopic expression of desat1. Western blots using anti‐T7 monoclonal antibodies reveal
the protein products of cloned GH23546 and RH21245 (figure 37).
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Figure 37 Subcloning of desat1 (CG5887) from Canadian Drosophila Microarray Centre clones GH23546 and RH21245. a) PCR results carried out using plasmid template concentrations of 1:100, 1:200, 1:500, 1:1000 (left to right) for each CDMC clone. c) Rapid disruption minipreparation of TOPO clones; clone 7 is the control. b) determination of directional insertion orientation in TOPO clones using a NotI digest; those with a single band are of desired orientation. d) Restriction digest of TOPO clones with desired orientation as well as pET 21A vector. e) Rapid disruption minipreparation of E. coli BL21 clones of both CDMC desat1 constructs. f) SDS‐PAGE expression of T7‐desat1 shows no difference between controls and T7‐desat1 clones. g) anti‐T7 western blot shows that the proteins are expressed and that RH21245 produces a truncated product of an unexpected size.
87
Overexpression of desat(3), desat(2) and per(2) for Immunization desat(3), desat(2) and per(2), were antigens generated by Dr. Tony So for overexpression in a GST‐fusion
vector and immunization in rabbits. SDS‐PAGE expression assays were carried out to verify the
overexpression of the GST fusion construct in each case and it was then purified using a glutathione‐
sepharose column and eluted with glutathione. 2‐5mg of these eluates were combined, frozen, and
sent to Pacific Immunology Inc. (Ramona, CA) for the purpose of injection into New Zealand white
rabbits. Rabbits were maintained on a standard 13‐week protocol during which pre‐immune sera, four
production bleeds and a final exsanguinations from each of two rabbits per immunogen were generated
for testing (figure 38).
88
Figure 38 Overexpression and purification of desat(3), desat(2), and per(2) antigens generated by Dr. Tony So. Gels represent SDS‐PAGE expression assays of each construct in native E. coli lysates (above, left) with desat(2) in lane 1, desat(3) in lane 2 and per(2) in lane 3. Once purified, eluates 1, 3, 5, 7 and 9 were run on SDS‐PAGE gels and are shown under the heading of the appropriate overexpressed antigen.
89
Testing of desat(3) and perSv1 PerSv1 was generated using a previously described peptide sequence which produced viable antibodies
(Siwicki et al., 1992). This antigen was generated and immunized using the same procedures as LpRv1.
Preliminary tests indicated that desat(2) and per(2) seemed to be nonfunctional. This could be because
desat(2) was generated using C‐terminus of the RH21245 clone which produces an apparently truncated
protein. There has traditionally been difficulty in creating anti‐period antibodies. Desat3v1 and perSv1
antibodies were examined on western blots to verify their accuracy. Desat3 appeared to be relatively
accurate in the case of rabbit 2, identifying a band at the approximate molecular weigh to desat in
whole Drosophila lysates. Anti‐T7 antibodies and desat3v1 revealed a band of the same molecular
weight using cloned GH23546 overexpression constructs (figure 39).
PerSv1 antibodies do not appear to recognize a peptide of the approximately correct molecular weight
in Drosophila lysates (160kDa). PerSv1 sera from rabbit 1, though, recognize a series of peptides which
may represent degradation products of period in the T7‐per lanes of western blots but not in the T7‐
control lanes (figure 40).
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Figure 39 Testing of desat3v1 in Drosophila and E. coli. The antisera from rabbit 1 (panel a, top row) do not recognize the correct band while those from rabbit 2 (panel a, lower row) recognize a band at 45kDa, the approximate molecular weigh of desat. T7‐monoclonal antibodies and desat3v1 both recognize T7‐desat from GH23546 overexpression constructs while they fail to recognize anything in control lanes (panel b).
91
Figure 40 Testing of perSv1 in Drosophila and E. coli. The antisera from rabbit 1 (panel a, top row) do not recognize the correct band. Those from rabbit 2 (panel a, lower row) also fail to recognize a band at approximately 160kDa. T7‐per appears to be recognized by perSv1 while the T7‐control lane appears relatively empty of label.
92
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Acknowledgements I would like to express my sincere gratitude to those who have helped me in this work; surely without their contribution this work would not have been possible. Specific thanks go to Farheen Mohammed for tremendous help with all areas of the research shown here, Adrienne Chu for help with cuticular hydrocarbon extraction and analysis, Jade Atallah for help with activity monitoring and analysis, Olga Sizova and Julia Schnonfeld for dissections, Jonathan Schneider and Tony So for help with cloning and molecular methods, Joshua Krupp, Jean‐Christophe Billeter, Hania Pavlou, and Scott Douglas for extremely helpful and education discussions.