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21st Century Directions in Biology
Since the first recognition of microorganisms,scientists have devised classification schemes with thegoal of systematically identifying species in an evolutionary
or phylogenetic context (Clarke 1985). This has consistently
proved more challenging for bacteria than for macroorgan-isms. Bacteria are asexual, so the classic definition of a speciesas a group of organisms that can interbreed and produce
fertile offspring is difficult to apply. Furthermore, because of
their small size, bacteria have a limited range of morpholog-
ical attributes. They do exhibit enormous biochemical diversity in both their metabolism and cell structure; this has proved
to be a useful cue for the taxonomy of some groups, but by
no means all of them. It is important, then, that the molec-
ular revolution that has transformed all of biology has had asgreat an impact on the taxonomy and systematics of bacteria
as in any other area of biology. In the 1970s, on the basis of
molecular comparisons of evolutionarily conserved riboso-
mal genes, Carl Woese proposed the then-heretical notion thatthe bacteria actually made up two separate domains, theBacteria and the Archaea, each as distinct from one another
as they are from the Eukaryotes, the third domain that com-
prises all “higher forms” of life (Woese 1987). This classifi-
cation, supported by reams of additional molecular data, isnow the standard view among microbiologists. This is not to
say that bacterial systematics is now fully standardized; indeed,
there is a vigorous ongoing debate about what constitutes a
bacterial species (Gevers et al. 2005, Achtman and Wagner2008). Nonetheless, molecular systematics has provided the
crucial framework for building bacterial classification schemes.
Despite the lack of a coherent species definition, the timely
classification, characterization, and identification of bacteriacontinue to be critical in many areas, including public health,
clinical diagnosis, environmental monitoring, food safety
monitoring, and identification of biological threat agents.In particular, the recent advances of modern molecular tech-niques in genomics and proteomics have offered attractive
alternatives to conventional microbiological procedures for
characterizing and identifying microorganisms. These new
methods can provide a rapid, multidimensional data outputwith taxonomically relevant molecular information on both
individual strains and whole populations.
This article is primarily concerned with the identification
of individual strains of bacteria that can be grown as axenic
David Emerson is a senior research scientist at Bigelow Laboratory for Ocean
Sciences, West Boothby Harbor, Maine. He is an environmental microbiologist
who has worked on developing methods for the rapid identification of a
variety of environmentally important bacteria and archaea. Liane Agulto
is a biologist at the American Type Culture Collection (ATCC) in Manassas,
Virginia; her major interest is identifying disease-related biomarkers using
proteomics technology. Henry Liu, a graduate student at Georgetown University
School of Medicine in Washington, DC, interned at the ATCC, where he
worked on developing a diagnostic kit for rapid antimicrobial susceptibility
testing. Liping Liu (e-mail: [email protected]) was the head of proteomics at the
ATCC and is now the director of research and development at Stealth Peptides,
Inc., in Rockville, Maryland. Her major expertise is in identifying biomarkers
using proteomics technologies and in developing biotherapeutics. © 2008
American Institute of Biological Sciences.
Identifying and Characterizing
Bacteria in an Era of Genomics
and Proteomics
DAVID EMERSON, LIANE AGULTO, HENRY LIU, AND LIPING LIU
The advent of new molecular technologies in genomics and proteomics is shifting traditional techniques for bacterial classification, identification,and characterization in the 21st century toward methods based on the elucidation of specific gene sequences or molecular components of a cell. Wediscuss current genotypic and proteomics technologies for bacterial identification and characterization, and present an overview of how these new
technologies complement conventional approaches. The new methods can be rapid, offer high throughput, and produce unprecedented levels of discrimination among strains of bacteria and archaea. Remaining challenges include developing appropriate standards and methods for thesetechniques’ routine application and establishing integrated databases that can handle the large amounts of data that they generate. We conclude by discussing the impacts of rapid bacterial identification on the environment and public health, as well as directions for future development in this
field.
Keywords: bacterial identification, bacterial characterization, genotype, proteomics, bioinformatics
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cultures in the laboratory. The discrimination and identifi-cation of bacteria within mixed natural populations is also a
rapidly developing field that utilizes some of the same tech-
niques, but it is an entirely separate subject (Liu and Stahl 2007,
Logue et al. 2008). Methods of bacterial identification can bebroadly delimited into genotypic techniques based on profiling
an organism’s genetic material (primarily its DNA) and phe-notypic techniques based on profiling either an organism’s
metabolic attributes or some aspect of its chemical compo-sition. Genotypic techniques have the advantage over pheno-
typic methods that they are independent of the physiological
state of an organism; they are not influenced by the com-
position of the growth medium or by the organism’s phaseof growth. Phenotypic techniques, however, can yield more
direct functional information that reveals what metabolic
activities are taking place to aid the survival, growth, and
development of the organism. These may be embodied, forexample, in a microbe’s adaptive ability to grow on a certain
substrate, or in the degree to which it is resistant to a cohort
of antibiotics. Because genotypic and phenotypic approaches
are complementary and use different techniques, this review is divided into two parts. However, this division is historical;
we predict that as molecular-based identification matures,
there will be more and more overlap in the information
obtained using different methodologies.
Genotypic methodsGenotypic microbial identification methods can be broken
into two broad categories: (1) pattern- or fingerprint-basedtechniques and (2) sequence-based techniques. Pattern-based
techniques typically use a systematic method to produce a
series of fragments from an organism’s chromosomal DNA.These fragments are then separated by size to generate a pro-file, or fingerprint, that is unique to that organism and its very
close relatives. With enough of this information, researchers
can create a library, or database, of fingerprints from known
organisms, to which test organisms can be compared. Whenthe profiles of two organisms match, they can be considered
very closely related, usually at the strain or species level.
Sequence-based techniques rely on determining the
sequence of a specific stretch of DNA, usually, but not always,associated with a specific gene. In general, the approach is the
same as for genotyping: a database of specific DNA sequences
is generated, and then a test sequence is compared with it.
The degree of similarity, or match, between the two sequencesis a measurement of how closely related the two organismsare to one another. A number of computer algorithms have
been created that can compare multiple sequences to one
another and build a phylogenetic tree based on the results
(Ludwig and Klenk 2001). The example cited above of usingsequence comparisons of the ribosomal RNA (rRNA) gene
to distinguish bacteria and archaea demonstrates how this
information can be applied to identify relationships among
microorganisms.Both fingerprinting techniques and sequence-based meth-
ods have strengths and weaknesses. Traditionally, sequence-
based methods, such as analysis of the 16S rRNA gene, haveproved effective in establishing broader phylogenetic rela-
tionships among bacteria at the genus, family, order, and
phylum levels, whereas fingerprinting-based methods are
good at distinguishing strain- or species-level relationships butare less reliable for establishing relatedness above the species
or genus level (Vandamme et al. 1996). When these methodsare coupled with other phenotypic tests, this creates a polypha-
sic approach that is the standard for describing new bacter-ial species (Gillis et al. 2001).
Specific genotyping methodologiesCurrent protocols for the identification of bacteria may uti-lize a variety of different fingerprinting- or sequence-based
methods, either alone or, more often, in combination. These
techniques are constantly evolving to embrace new method-
ologies that provide both greater accuracy for identificationand higher sample throughput. Examples of some of the
most widely used techniques are provided below.
Fingerprinting-based methodologies. At present, fingerprintingtechniques are the most commonly used genotypic methods
for bacterial identification. The most widely used of these
methods are shown in table 1. Repetitive element PCR (rep-
PCR), amplified fragment length polymorphism (AFLP),and random amplification of polymorphic DNA all utilize
PCR to amplify multiple copies of short DNA fragments
using defined sets of primers (Versalovic et al. 1994, Coccon-
celli et al. 1995, Vos et al. 1995, Lin et al. 1996). These meth-ods are designed to take advantage of DNA polymorphisms
in related organisms that may accrue as a result of a variety
of evolutionary mechanisms. Figure 1 provides an illustrationof the type of data obtained using rep-PCR. Multiplex PCR uses unique PCR primer sets for more than one organism;
these sets can be separated on the basis of amplicon size as a
way of rapidly identifying more than one microbe at a time
in a mixed sample (Settanni and Corsetti 2007).Riboprinting does not use PCR, but instead utilizes a sen-
sitive probing method to detect differences in gene patterns
between strains and species (Bruce 1996). DuPont’s Ribo-
Printer system (www2.dupont.com/Qualicon/en_US/ ) andthe DiversiLab system for rep-PCR (http://biomerieux-usa.
com/diversilab) have both been developed as commercial
products for bacterial identification. All of the methods de-
scribed here have been used to identify bacteria in a multitudeof different ways, many of which can be found in the scien-tific literature. These applications include source tracking
(Meays et al. 2004), authentication of isolates for archival
purposes (Cleland et al. 2008), taxonomy and systematics
(Vandamme et al. 1996, Gevers et al. 2005), and determina-tion of microbial population structures and community
studies (Savenlkoul et al. 1999), to name but a few.
Sequence-based methodologies. The most widely usedsequence-based methods are also shown in table 1. Multilocus
sequencing is one of the newest and, to date, one of the most
21st Century Directions in Biology
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powerful methods developed to identify microbial species. In
principle, this technique is akin to 16S rRNA gene sequence
comparisons, except that, instead of one gene, the fragments
of multiple “housekeeping” genes are each sequenced, andthe combined sequences are put together, or concatenated,
into one long sequence that can be compared with other se-
quences. Housekeeping genes are generally defined as en-
coding for proteins that carry out essential cellular processes.A few examples include the gyrase B subunit ( gyrB); the
alpha and beta subunits of RNA polymerase (rpoA and rpoB);
and recA, a gene encoding for an enzyme important in DNA
repair; there are a host of others (Zeigler 2003). Housekeep-ing-gene loci are present in most cells and tend to be conservedamong different organisms. As a result, general-purpose
primers can be designed that will work using PCR to amplify
the same genes across multiple genera.
In practice, the story is a bit more complicated; in mostcases, truly universal primer sets are not possible, so primers
need to be designed for specific families or orders of bacteria.
Two multilocus sequencing strategies are currently used:
multilocus sequence typing (MLST) and multilocus sequenceanalysis (MLSA). MLST is a well-defined approach that uses
a suite of 6 to 10 genetic loci, with appropriate primers for each
locus to allow PCR amplification and sequencing of the
products (usually 400 to 600 base pairs) (Maiden et al. 1998).
The resulting concatenated sequences can then be compared
with a curated database of sequences for the same organism.The result provides a high-resolution identification of an in-
dividual strain that may reveal close evolutionary relationships
among individual strains. This technique has proved useful
in epidemiological studies, making it possible to track the out-break of virulent bacterial pathogens (Cooper and Feil 2004).
Thus far, MLST, and the robust databases that have been
created for it, has been applied only to a relatively small num-
ber of common pathogens, using highly prescribed conditionsfor each organism, both for PCR primers and for databaseanalysis.
MLSA also involves sequencing of multiple fragments of
conserved protein encoding genes, but it uses a more ad hoc
approach to choosing the genes for comparative analysis. Asmaller subset (≤ 6) of genes or loci is typically used in MLSA
than is used in MLST (Gevers et al. 2005). MLSA is typically
used to identify organisms in the broader context of probing
species relationships within genera of families, rather thantracking the history of individual strains. As typically ap-
plied, it does not have the analytical capacity to detect the very
21st Century Directions in Biology
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21st Century Directions in Biology
Table 1. Genotypic methods used in identifying bacteria.
Method Technology Application Database
Common fingerprinting methods
Repetitive element polymerase Polymerase chain reaction (PCR) Identification at the species and User created; commercial individualchain reaction (rep-PCR) primers target specific repetitive strain levels database available
elements randomly distributed inthe chromosomes of bacteria andarchaea
Amplified fragment length Restriction digestion of chromosomal Identification at the species and User createdpolymorphism DNA is followed by PCR using adapters strain levels; can be used for both
coupled to the restriction sites bacteria and archaea
Riboprinting Restriction digest of chromosomal DNA Identification at the species and User created; commercial universalis followed by probing for ribosomal strain levels; often used in quality database availablegenes control and assurance
Random amplification of A set of arbitrary short primers are Comparison of strains of known User createdpolymorphic DNA used to randomly amplify short species
stretches of chromosomal DNA
Pulsed-field gel electrophoresis Chromosomal DNA is cut into large Typing of pathogenic bacteria Public universal database adminis-fragments with rare-cutting restriction tered by the Centers for Diseaseenzymes, and fragment is determined Control and Prevention (www.cdc.gov/
pulsenet)
Multiplex PCR Multiple PCR primers are used for Identif ication of multiple species in User created
diagnostic genes mixed samples such as food andclinical specimens
Common DNA sequencing methods
Small-subunit ribosomal gene Conserved primers are used to amplify The current gold standard in bacterial Public universal databases available,sequencing (SSU rDNA) and then sequence the SSU rDNA identification and determination of including the Ribosomal Database
gene; sequences are then compared evolutionary relationships; may not Project (http://rdp.cme.msu.edu) andwith a database distinguish strains or species within greengenes (http://greengenes.lbl.gov )
a genus
Multilocus sequence typing DNA sequencing of a specific subset Typing of pathogenic bacteria; Public universal database available(MLST) of conserved and semiconserved epidemiology (administered by www.mlst.net)
genes for a given species is followedby a comparison of concatenatedsequences
Multilocus sequence analysis DNA sequencing of a specific subset Provides more robust identification User created; based on BLAST (Basicof conserved genes is followed by at the species level than traditional Local Alignment Search Tool) searchesa comparison of concatenated SSU rRNA gene sequencing against GenBanksequences; this method typicallyuses fewer genes than MLST does(only two or three)
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minor changes in sequence patterns that are useful in epi-
demiologic studies. At present, MLSA is limited by a lack of standardization, and no central databases are available. For ex-ample, an analysis of eight recent papers that used MLSA to
identify a wide range of bacterial phyla found that anywhere
from two to six genes were used in the different individual
studies (Devulder et al. 2005, Lodders et al. 2005, Naser et al.2005, Paradis et al. 2005, Thompson et al. 2005, Richter et al.
2006, Chelo et al. 2007, Richert et al. 2007). Furthermore, no
single gene was common to all studies, and most studies
used completely different sets of genes. Although the techniqueproved useful for each individual study, the lack of cohesive-
ness makes comprehensive comparative analyses impossible.
The genomic future. The genomes of approximately 2000
strains of bacteria and archaea have now been sequenced orare in the process of being sequenced. This has led to theadvent of using whole-genome comparisons between related
species to determine the average nucleotide identity between
two genomes (Goris et al. 2007). This technique currently de-
fines a species at the genomic level as having 95% averagenucleotide identity between two strains. This corresponds to
an estimate of at least 70% reassociation for DNA-DNA
hybridization, which has been the traditional standard for
defining bacterial species (Vandamme et al. 1996). Completegenome comparisons have proved to be more accurate than
DNA-DNA hybridization, which requires very stringent
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21st Century Directions in Biology
Figure 1. An example of genotyping archaea from extreme environments using repetitive element poly-
merase chain reaction. The dendrogram compares the barcodes derived from four genera of extremely thermophilic archaea ( Methanocaldococcus, Methanotorris, Sulfolobus , and Thermococcus ) associ-
ated with high-temperature environments like the hydrothermal vent shown in the photograph on the
left, and four genera of halophilic archaea ( Halobacterium, Haloferax, Haloarcula,and Halorubrum )
associated with high-salt environments like the solar saltern shown on the right. This analysis providesa highly specific method for strain identification of these unique organisms, but it does not provide in-
formation regarding their phylogenetic relatedness. Photographs: David Clelann.
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protocols and is often difficult to reproduce precisely be-
tween laboratories. The rapid advent of the next generation
of sequencing technologies is likely to make sequence-based
methods more cost-effective and more readily available for use
at all levels of bacterial classification and identification.
This raises the question of whether it will soon be possi-
ble to simply sequence the genome of an isolate to determinewhat it is and what it does. Can this be done for roughly the
same cost as a standard battery of biochemical identification
tests and a genotype analysis? Can it be done with the same
or better speed and efficiency as current methods? These are
the challenges faced by researchers who are developing and
using genomics-based identification methods. It is difficult to
predict how soon, if ever, whole-genome sequencing will be
used as a routine means of bacterial identification; however,
it is certain that the multilocus sequencing approaches de-
scribed above will expand and mature rapidly. While we ap-
preciate the technological challenges of DNA sequencing per
se, perhaps an even greater challenge will be the establishmentof large, integrated databases that allow for the rapid assem-
bly of sequence data to help researchers make robust com-
parisons among sequences and predict identifications between
bacteria with a high degree of confidence. The lack of stan-
dardization for MLSA analysis needs to be addressed so that
standards can be developed for comparisons of multiple
taxa. Once these are in place, it will become progressively
easier to develop MLSA- or MLST-type sequence-based
strategies that accurately target multiple genes and can be used
to provide a full range of genotypic information for all
bacteria and archaea.
Microarrays are another technology that shows promise asa means of simultaneously identifying specific microbes and
providing ecological context for the population structure
and functional structure of a given microbial community. Mi-
croarrays work on the general principle of spotting probes for
hundreds or thousands of genes onto a substrate (e.g., a glass
slide) and then hybridizing sample DNA or RNA to it. The
sample DNA or RNA is labeled with a fluorescent reporter
molecule so that samples that hybridize with probes on the
microarray can be detected rapidly. In terms of bacterial
identification, several iterations of a “phylochip” that utilizes
the small-subunit ribosomal gene as a target have been de-
veloped, both for specific and for very broad groups of envi-ronmental bacteria (Liu et al. 2001, Wilson et al. 2002).
Another example is the geochip, which has been developed
to identify microbes involved in essential biogeochemical
processes such as metal transformations, contaminant degra-
dation, and primary carbon cycling (He et al. 2007). In the clin-
ical realm, the use of microarrays is moving forward rapidly,
both for diagnostic purposes and for understanding the fun-
damentals of disease pathology (Frye et al. 2006, Richter et al.
2006). However, because of their inherent complexity and rel-
ative expense, microarrays have yet to be used as standard
methods in microbial identification.
Proteomics technologies in bacterialidentification and characterizationAlthough genotypic information is valuable in identifying an
organism and determining how it is related to others, meth-
ods that probe an organism’s phenotypic properties remaincritical for understanding the physiological and functional
activities of an organism at the protein level. Phenotypicmethods that determine the activity of specific enzymes,
such as catalase or oxidase, or metabolic functions, such as theability to degrade lactose, have long been a mainstay of bac-
terial identification. The advent of new proteomics tools that
are based primarily on mass spectrometry and allow rapid in-
terrogation of biomolecules produced by an organism offersan excellent complement to classical microbiological and
genomics-based techniques for bacterial classification, iden-
tification, and phenotypic characterization. What is also in-
teresting is that some of these techniques are integratinggenotypic and proteomic data to provide more complete
information. The predominant proteomic technologies that
have been explored for bacterial identification and charac-
terization include matrix-assisted laser desorption/ionizationtime-of-flight mass spectrometry (MALDI-TOF-MS); elec-
trospray ionization mass spectrometry (ESI-MS); surface-
enhanced laser desorption/ionization (SELDI) mass
spectrometry; one- or two-dimensional sodium dodecylsulfate–polyacrylamide gel electrophoresis (SDS-PAGE); or
the combination of mass spectrometry, gel electrophoresis, and
bioinformatics. (See figure 2 for a general integrated proteo-
mics flowchart.) In addition to the above-mentioned classi-cal proteomics approaches, Fourier-transform infrared
spectroscopy (FT-IR) has been used to classify and identify
bacterial samples (see, e.g., Al-Qadiri et al. 2006).
Mass spectrometry–based bacterial characterization and
identification. Mass spectrometry is a powerful analytical
technique that has been used to identify unknown com-
pounds, quantify known compounds, and elucidate the struc-ture and chemical properties of molecules. The development
of mass spectrometry can be traced back to the late 19th
century, when it was first used by J. J. Thomson (1899) to
measure the mass-to-charge ratio of electrons. With the re-finement of this technology throughout the 20th century,
mass-spectrometry applications have been expanded to
include physical measurement, chemical characterization,
and biological identification.One of the major breakthroughs in mass spectrometry
for the analysis of biological molecules was the soft ionization
method (i.e., MALDI-TOF-MS and ESI-MS; see figure 3 for
a simplified schematic representation). Until the develop-
ment of the soft ionization method, the application of massspectrometry to biological materials was limited by the re-
quirement that the sample be in vapor phase before ioniza-
tion. Soft ionization has made it possible to study larger
biological molecules and perform analyte sampling and ion-ization directly from native samples, including whole cells,
using mass spectrometry (Fenn et al. 1989). Since its initial
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MALDI-TOF-MS is rapidly becoming an accepted tech-
nology for bacterial identification, so we will cite only one
example of its use. Staphylococcus aureus, a bacterium com-
monly found on human skin, causes infection during timesof uncontrolled growth. Improper use of antibiotics has
rendered S. aureus resistant to the methicillin class of anti-
biotics. The first outbreak of methicillin-resistant S. aureus(MRSA) was recorded in a European hospital in the early 1960s. Since then, the threat of MRSA has spread from
hospitals and clinical settings to schools and public commu-
nities, thus necessitating the use of techniques that can rapidly
identify and discriminate MRSA from methicillin-sensitive S.aureus (MSSA). Edward-Jones and colleagues (2000) developeda MALDI-TOF-MS method for the identification, typing,
and discrimination of MRSA and MSSA. In this method, a
sample is taken from a single bacterial colony and smeared
onto a sample slide. The appropriate matrix is applied to thesample, which is then analyzed using MALDI-TOF-MS.
MALDI-TOF-MS analysis shows that MRSA and MSSA yield
distinct spectral peaks that allow for rapid distinction between
the two and therefore, hypothetically, for appropriate treat-ment of S. aureus infections with respect to their resistance
to antibiotics.
To serve market needs, severalinstrument systems based on
MALDI-TOF-MS have been
developed for bacterial identi-
fication and characterization.For instance, Bruker Daltonics’
MALDI BioTyper is a systembased on the measurement of
high-abundance proteins, includ-ing many ribosomal proteins in
a microorganism (Mellmann et
al. 2008). The system is equipped
with bioinformatics tools (clus-tering and phylogenetic dendro-
gram construction) that allow
for the rapid identification and
characterization of a known orunknown bacterial culture on the
basis of proteomics signatures.
Electrospray ionization mass
spectrometry. ESI-MS also has
the potential to play an impor-
tant role in bacterial character-
ization, especially for the analysisof cellular components. Proteins
expressed by the bacteria can be
extracted from the lysed cells
and analyzed using ESI-MS.This technique allows for the
analysis of both intracellular and
extracellular proteins, carbo-hydrates, and lipids. A major ad-
vantage of ESI-MS is its ability to perform tandem mass
spectrometry, in which the protein of interest can be frag-
mented for a second mass analysis that provides protein frag-
ment sequence information, or a peptide fragmentationfingerprint, that can then be applied to a database search to
identify that specific protein. This has significantly increased
the accuracy of protein identification compared with identi-
fication using only molecular weight information from asingle MALDI-TOF-MS analysis. A study by Krishnamurthy
and Ross (1996) reported that the total analysis time leading
to unambiguous bacterial identification in samples is less
than 10 minutes, with reproducible results. A system recently developed by Ibis Biosciences (the T5000 Biosensor System)can identify and characterize bacterial strains rapidly and
effectively using a combination of PCR and ESI-MS tech-
nology (Sampath et al. 2007). Another example of the use of
mass spectrometry to analyze nucleic acids for bacterial iden-tification is the combination of MALDI-TOF-MS with MLST
analysis using Neisseria meningitidis (Honisch et al. 2007).
These efforts exemplify how the integrated genotypic and pro-
teomics technologies provide an even more powerful tool forbacterial identification. Additional descriptions of the ESI-MS
technique and its applications for bacterial characterization
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21st Century Directions in Biology
Figure 3. Schematic representation of soft ionization techniques used in mass spectrome-
try. (a) Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass
spectrometry. The sample to be analyzed (the analyte) is mixed with organic matrices
and deposited on the sample plate in the form of a small spot. The mixture is ionizedby the laser beam. The resulting ions move toward the mass analyzer, and the mass is
detected to obtain the mass spectrum. (b) Electrospray ionization mass spectrometry
(ESI-MS). The analyte is mixed with a solvent and sprayed from a narrow tube.
Positively charged droplets in the spray move toward the mass-spectrometersampling orifice under the influence of electrostatic forces and pressure differentials.
As the droplets move to the orifice, the solvent evaporates, causing the analyte
ions to move toward the analyzer for mass analysis.
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may be found in a review article by Bons and colleagues(2005).
Another advantage of ESI-MS is its ability to identify
target bacteria in mixed samples. The resolution of ESI-MS
is such that specific intracellular biomarkers for individual mi-croorganisms can be distinguished with enough confidence
that they can be identified in unknown samples. For the pro-tein analysis, comparing the experimentally obtained protein
profile of an unknown bacterial species with the profile in-formation found in a proteomics database will allow for the
identification and characterization of the unknown species.
Identifying the virulence factors of pathogenic bacteria is
one of the major applications of liquid chromatography withtandem mass spectrometry (LC/MS/MS) (Chao et al. 2007).
Once the putative virulence factors are identified, their func-
tions and mechanism can be further characterized by pheno-
typic analyses such as mutagenesis, conventional biochemicalmethods, and structural biology.
Surface-enhanced laser desorption/ionization. SELDI is a
relatively new technology, designed to perform mass spec-trometric analysis of protein mixtures retained on chemically
(e.g., cationic, ionic, hydrophobic) or biologically (e.g.,
antibody, ligand) modified chromatographic chip surfaces.
These varied chemical and biochemical surfaces allow dif-ferential capture of proteins based on the intrinsic properties
of the proteins themselves. The SELDI mass spectrometer
produces spectra of complex protein mixtures based on the
mass-to-charge ratio of the proteins in the mixture and theirbinding affinity to the chip surface. Differentially expressed
proteins may then be determined from these protein profilesby comparing peak intensity. Figure 4 illustrates the general
procedure.
SELDI technology has been applied extensively to bio-
marker and protein profiling studies in the field of oncology (Yip and Lomas 2002). By contrast, only a limited number of
reports have investigated the applicability of SELDI for de-tecting and identifying bacterial pathogens (Seo et al. 2004)
and virulence factors. However, these limited study resultsdemonstrate that SELDI technology offers an alternative
approach to the other techniques for exploring bacterial pro-
teomes, ultimately permitting bacterial identification based
on a comparison of protein profiles and patterns. An exam-ple of how SELDI technology has been applied is its use in dis-
tinguishing between four subspecies of Francisella tularensis,the causative agent of tularemia in humans. Of the four sub-
species of F. tularensis, tularensis is the most infectious andthe only subspecies found in North America. Lundquist and
colleagues (2005) showed that SELDI time-of-flight mass
spectrometry is capable of generating unique and repro-
ducible protein profiles for each subspecies, allowing thesubspecies to be distinguished from one another.
Although the use of mass spectrometry has great potential
for identifying bacteria by their spectral profile, many factors
affect the reproducibility of bacterial spectra. Sample pre-paration, matrix selection, and differences in instrument
quality and performance can all have an impact on the re-
producibility of protein profiles (Wunschel et al. 2005). Just
as important, the physiological state of the cell may also in-fluence the results of mass spectral analysis, and thus both the
growth medium and the growth
stage of the cells must be takeninto account. Using MALDI-TOF-MS technology to analyze
and discriminate foodborne mi-
croorganisms, Mazzeo and col-
leagues (2006) concluded thatthe growth time did not affect
the bacterial protein profile, but
that different growth media did
affect the mass spectra of Es-
cherichia coli. Similarly, Walker
and associates (2002) showed
that culture medium—especially
with the addition of blood, as inColumbia blood agar—will causevariation in mass spectra profiles.
With so many variables, many
scientists have introduced stan-
dardized techniques for MALDI-TOF-MS of whole cells. Liu and
colleagues (2007) developed a
universal sample preparation
method for characterizing gram-positive and gram-negative bac-
teria using MALDI-TOF-MS.
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21st Century Directions in Biology
Figure 4. Schematic representation of the surface-enhanced laser desorption/ionization
technique. This technique utilizes aluminum-based chips, engineered with chemically
or biologically modified surfaces. These varied surfaces allow the differential captureof proteins based on the intrinsic properties of the proteins themselves. Bacterial lysates
are applied directly to the surfaces, where proteins with affinities to the surface will bind.
Following a series of washes to remove nonspecifically bound proteins, the bound proteins
are profiled using the integrated mass analyzer to generate a mass spectrum for further analysis. Abbreviations: MS, mass spectrometry; m/z, mass-to-charge ratio.
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These results emphasize the need to develop standardized tech-
niques for preparing samples to use in the creation of mass
spectra databases for bacterial identification.
Gel-based bacterial characterization and identification. Bac-
teria may also be differentiated on the basis of their cellular
protein contents. The most established technique for exam-ining cellular protein content is to lyse cells and separate
their entire protein complement using SDS-PAGE. This results
in a migration pattern of the protein bands that is character-
istic for a given bacterial strain (Vandamme et al. 1996). Re-
searchers can identify bacteria by comparing their migration
patterns with reference gel patterns in an established database.
However, because SDS-PAGE analysis is slow and labor-
intensive, and because the application necessitates precise
culture conditions that yield fairly large amounts of sample
material, it is not particularly useful for rapid identification
of bacteria, particularly for field and point-of-care applications.
Two-dimensional gel electrophoresis (2DE)—the combi-nation of isoelectric focusing (IEF) and SDS-PAGE—affords
a high-resolution separation of up to several thousand
spots in a single gel analysis. In 1975, O’Farrell (1975) intro-
duced 2DE as a method for separating complex mixtures of
cellular proteins. In 2DE, proteins are separated by IEF elec-
trophoresis in a pH gradient according to each protein’s
isoelectric point in the first dimension, followed by the
second-dimension SDS-PAGE separation according to the
relative molecular weight of each protein. After the second-
dimension separation, the gel can be stained with standard or
sensitive staining solutions so that protein spots can be visu-
alized and analyzed. Protein gel patterns or 2DE maps from
known bacteria can be further scanned, analyzed, and stored
in a reference database. To identify an unknown species, a 2DE
map from the unknown sample is generated by running a 2DE
gel and then comparing it with 2DE maps in the reference
database for identification.
When used as a stand-alone technique, 2DE is most often
used for analyzing protein mixtures, isolating proteins of in-
terest for identification, and comparing differential expression
patterns of different types of samples. For more complex
proteomics analysis, 2DE is greatly enhanced when com-
bined with mass spectrometry. For example, Redmond and
associates (2004) analyzed the exosporium of Bacillus anthracis
spores by isolating the proteins from the outer casing of thespore using SDS-PAGE and analyzing the isolated protein
using delayed-extraction MALDI-TOF-MS. The team iden-
tified several proteins associated with the exosporium of
B. anthracis. Using these same methods, the whole proteome
or subproteome (or both) has also been made available for
many other bacteria, including E. coli, Bacillus subtilis, S.
aureus, Pseudomonas aeruginosa, and Helicobacter pylori
(Nouwens et al. 2000, Hecker et al. 2003, Peng et al. 2005,
Pieper et al. 2006). A collective proteomics database with
complete 2DE maps and mass spectra of known bacteria
will allow investigators to compare and identify unknown bac-
teria with great efficiency. However, building such a database
will not be an easy undertaking.
The database challenge. One thing modern genomic and pro-
teomic approaches share is the generation of large data sets
for any individual sample that is analyzed. These present a real
challenge in terms of archiving the data, processing and in-tegrating data from many samples so that it can be used
for comparative purposes in the broadest way possible, and
developing robust quality control and quality assurance
practices. All this should be done in an environment that isaccessible and easy to use for a broad group of scientists,
many of whom may have little experience with a particular
method of analysis. At present there are no comprehensive ge-
nomic or proteomic databases for bacterial identification.There are, however, a great number of databases and tools
available for both genomic and proteomic analysis that are
essential for providing integrated data for specific types of
analysis. Two examples of databases that provide excellentanalysis for identification based on 16S rRNA gene sequence
analysis are the Ribosomal Database Project (Cole et al. 2007)
and greengenes (DeSantis et al. 2006). On the proteomics side,
LC/MS/MS data analysis has improved by several means andcontinues to complement 2DE gel analysis, which is still
limited by the inability of the pattern recognition software to
resolve overlapping protein spots (Palagi et al. 2006). Protein
identification and characterization has been carried out withmore depth since the development of predictive tools such as
GlycoMod and databases such as PhosphoSite, which can
reveal possible posttranslational modifications not other-
wise accounted for in databases consisting simply of theoretical
spectra (Barrett et al. 2005, Witze et al. 2007).More important, algorithms are evolving to adapt to actual
experimental occurrences and parameters. One example of
such adaptation is the development of a recent algorithm thatpredicts missed cleavage sites as they typically occur during
protein digests, in order to ease the return of, and render
greater confidence to, mass spectra probability matches
(Siepen et al. 2007). The goal of the ProDB platform proposedby Wilke and colleagues (2003) is not only to integrate data
derived from various databases to enrich a protein profile but
also to archive experimental conditions and parameters, such
as growth and culture conditions as they might apply to bac-teria, to account for the subsequent effects on mass-spectra
profile generation. Archiving and integrating specific exper-imental conditions as part of the proteomic bioinformatics
may alleviate the need for stringent culturing standards whenattempting to identify proteins that aid the characterization
and identification of clinically important bacteria. For a more
comprehensive review on proteomic data analysis, see Lisacek
and colleagues (2006).
ConclusionsAdvanced genomics and proteomics technologies will continueto play a critical role in bacterial identification and charac-
terization in the 21st century. Bacterial characterization has
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a number of practical applications, aside from being funda-
mental to questions of bacterial systematics, taxonomy,
and evolution. Rapid identification and discrimination of
pathogenic microbes has a major impact on public health in
terms of correct diagnosis and timely disease treatment.
The ability to identify specific indicator organisms is also
important for determining water quality, and an enhancedunderstanding of the population structure of these organisms
can allow researchers to identify the source of a particular
contaminant. For example, methods are being developed
to determine whether fecal bacteria found in public water
supplies are from humans, mammals, or birds. This kind of
information has a significant impact for treatment options.
As researchers learn more about the community fabric of
microbial ecosystems, it is likely that we will come to recog-
nize sentinel microbes that will tell us, by their presence (or
absence) and abundance, important information about
the state of that ecosystem. For example, the identification of
microbes that carry out specific transformations of nitrogenor phosphorus might indicate the status of these important
nutrients in aquatic or soil ecosystems. Likewise, the presence
of microorganisms with certain biodegradative capacities
could be an indicator of specific pollutants in an environment.
The ability to rapidly identify these individual organisms
within populations of thousands of different species is
essential for understanding how they will affect our eco-
systems. Bacterial characterization will also assist in elucidating
the mechanisms that govern microbial pathogenesis, and
allow for the discovery of important protein targets essential
to the development of vaccines, diagnostic kits, and thera-
peutics for infectious diseases. It is these kinds of applicationsthat make the continued development of techniques for bac-
terial identification important both for basic science and for
the maintenance of human and environmental health.
Acknowledgments
The authors would like to thank Raymond Cypess (chief
executive officer, American Type Culture Collection [ATCC])
and Cohava Gelber (chief scientific and technology officer,
ATCC) for their unconditional support in preparing this
manuscript. We thank Scott Jenkins for his help in editing
the manuscript and David Cleland for his help in preparing
figure 1. We also acknowledge that many excellent papers,
particularly those providing examples of the use of the tech-
nologies described herein, could not be cited because of space
limitations.
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