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Chemical Engineering Faculty Publication Series Chemical Engineering

2017

Microfluidics: From Crystallization to Serial Time-Resolved CrystallographyShuo SuiUniversity of Massachusetts Amherst

Sarah L. PerryUniversity of Massachusetts Amherst

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Recommended CitationSui, Shuo and Perry, Sarah L., "Microfluidics: From Crystallization to Serial Time-Resolved Crystallography" (2017). StructuralDynamics. 840.https://doi.org/http://dx.doi.org/10.1063/1.4979640

Microfluidics: From crystallization to serial time-resolved crystallographyShuo Sui and Sarah L. Perry

Citation: Structural Dynamics 4, 032202 (2017); doi: 10.1063/1.4979640View online: http://dx.doi.org/10.1063/1.4979640View Table of Contents: http://aca.scitation.org/toc/sdy/4/3Published by the American Institute of Physics

Microfluidics: From crystallization to serial time-resolvedcrystallography

Shuo Sui and Sarah L. Perrya)

Department of Chemical Engineering, University of Massachusetts Amherst, Amherst,Massachusetts 01003, USA

(Received 30 November 2016; accepted 17 March 2017; published online 7 April 2017)

Capturing protein structural dynamics in real-time has tremendous potential in

elucidating biological functions and providing information for structure-based

drug design. While time-resolved structure determination has long been consid-

ered inaccessible for a vast majority of protein targets, serial methods for crystal-

lography have remarkable potential in facilitating such analyses. Here, we

review the impact of microfluidic technologies on protein crystal growth and

X-ray diffraction analysis. In particular, we focus on applications of microflui-

dics for use in serial crystallography experiments for the time-resolved determi-

nation of protein structural dynamics. VC 2017 Author(s). All article content,except where otherwise noted, is licensed under a Creative Commons Attribution(CC BY) license (http://creativecommons.org/licenses/by/4.0/).[http://dx.doi.org/10.1063/1.4979640]

I. INTRODUCTION AND BACKGROUND

The development of increasingly bright and micro-focused synchrotron X-ray beams, as

well as the advent of X-ray free-electron lasers (XFELs), has enabled structure determination

using ever-smaller crystals and more challenging targets.1,2 However, the direct observation of

functional motions within proteins and other biomolecules remains an ultimate goal. The chal-

lenge of obtaining dynamic structural information stems from (i) the large X-ray dose required

for the collection of data at multiple time points during a reaction, (ii) sample handling strate-

gies for multi-crystal experiments, and (iii) difficulties associated with synchronizing structural

dynamics within protein crystals and matching X-ray exposure times to the timescale of the rel-

evant structural dynamics.

Many of these challenges have been addressed through serial data collection strategies,3,4

which extend the concept of combining data from multiple crystals5–13 with the limit of a single

frame of data per crystal. This type of single-frame-per-crystal data collection has been critical

for structural biology efforts at X-ray free-electron laser (XFEL) sources where radiation dam-

age may require a “diffraction before destruction” approach3,14 and has subsequently been

extended for use at synchrotron sources.15–18 Furthermore, these approaches have enabled time-

resolved structural determination for a much broader range of targets than had previously been

accessible.19–30

However, these large-scale serial methods suffer from the need to manipulate crystals and/

or from inefficient sample utilization.3,31–36 The material-intensive nature of these experiments

extends the long-standing challenge of growing a well-diffracting crystal to reproducibly gener-

ating a large number of high quality, isomorphous crystals. These issues are then further com-

pounded by the need to deliver those samples efficiently to the X-ray beam.5,7–11,18,37–42

Microfluidic and microscale technologies have played a critical role in facilitating both protein

crystallization and structure determination, with the breadth and variety of reported solutions

demonstrating the challenging nature of the field.

a)Author to whom correspondence should be addressed. Electronic mail: perrys@engin.umass.edu

2329-7778/2017/4(3)/032202/29 VC Author(s) 2017.4, 032202-1

STRUCTURAL DYNAMICS 4, 032202 (2017)

In this review, we discuss the utility of microfluidic technologies for addressing the chal-

lenges of crystal growth and sample manipulation for applications in serial crystallography and

time-resolved structure determination. We begin by considering the benefits of working at the

microscale and how these advantages facilitated the development of a wide range of microflui-

dic platforms for protein crystallization. We then examine the evolution of these crystallization-

centric technologies for in situ X-ray analysis and contrast such devices with a range of

platforms developed to facilitate the efficient, high-throughput delivery of crystals for both

static and time-resolved structure determination. Finally, we discuss the potential for these vari-

ous microfluidic strategies to address future challenges related to the study of protein structures

and dynamics. As this review is focused on the technologies surrounding crystal growth and

delivery, and not on the larger aspects of serial43–46 or time-resolved X-ray methods,46–48 we

refer the reader to other excellent reviews on these topics.

II. MICROFLUIDICS FOR PROTEIN CRYSTALLIZATION, AN HISTORICAL PERSPECTIVE

A. The benefits of working at the microscale

Undoubtedly, the most obvious benefit of transitioning from the laboratory-scale to micro-

scale experiments is the potential for dramatically decreasing the quantity of a sample needed

for a given experiment. Decreasing the physical size (i.e., the length, L) of a sample results in a

decrease in the volume that scales as L3 (Table I). Thus, for a cubic geometry, decreasing the

size of the cube from 1 mm to 0.1 mm results in a 1000� volume change, from 1 ll to 1 nl.

However, the benefits of working at the microscale extend far beyond sample conservation.

Microfluidic technologies are able to take advantage of small geometries by enabling large

surface-area to volume ratios (SA/V, Table I), eliminating convective effects to create a purely

diffusive environment, generating extremely sharp and controllable gradients in concentration

and temperature and harnessing interfacial tension effects.49,50

B. Capillary-based counter-diffusion methods

Much of the motivation and inspiration for early microfluidic efforts in protein crystalliza-

tion were connected with experiments performed in microgravity.51–53 The excitement regarding

these experiments was fueled by the production of higher quality diffraction for nearly 35% of

the targets investigated in space, as compared to ground-based methods. The advantage con-

ferred by microgravity was a tremendous reduction in buoyancy-driven convection and sedi-

mentation effects and the subsequent dominance of diffusive mixing. These microgravity

experiments were typically performed in a counter-diffusion style geometry, where protein and

precipitant solutions are placed into contact in a capillary and allowed to slowly intermix

(Figure 1(a)). The resulting diffusional profile continuously samples a wide range of supersatu-

ration conditions. While high levels of supersaturation close to the initial point of contact will

TABLE I. Surface area and volume benefits at the microscale.

Length (L) Volume (V) SA/Va

mm lm mm3 l m�1

10 10 000 103 10�3 (1 ml) 6 � 102

1 1000 1 10�6 (1 ll) 6 � 103

0.1 100 10�3 10�6 (1 nl) 6 � 104

0.01 10 10�6 10�9 (1 pl) 6 � 105

0.001 (1 lm) 1 10�9 10�12 (1 fl) 6 � 106

0.0001 0.1 10�12 10�15 (1 al) 6 � 107

aSA/V is the surface area to volume ratio specified based on the geometry of a cube.

032202-2 S. Sui and S. L. Perry Struct. Dyn. 4, 032202 (2017)

tend to result in amorphous precipitates, lower levels of supersaturation allow for continuous

sampling and the identification of optimal rates of nucleation and growth.52

In translating counter-diffusion style experiments for use in earth-bound laboratories, it is

necessary to utilize a strategy to minimize the effects of convection. While smaller capillaries

and microfluidic channels can achieve this condition directly as a consequence of their geome-

try,49,55–63 larger capillaries typically utilize a gel matrix to eliminate convection.64–69 These

techniques have been applied to a range of proteins and can be compatible with in situ X-ray

analyses, depending on the thickness of the surrounding material.55,56,58,60–62,65–68,70

C. Integrated microfluidic devices

While simple channel and capillary-based approaches are effective strategies for protein

crystallization, more integrated microfluidic devices have been used to enable higher-

throughput screening of a broad range of conditions and have the potential to enable the repro-

ducible growth of a large number of isomorphous crystals for serial crystallography efforts.

Advances in the microfabrication techniques known as soft lithography and replica molding71–74

facilitated the straightforward manufacture of microscale features from poly(dimethylsiloxane)

(PDMS), an optically transparent elastomer. Furthermore, the elastomeric nature of PDMS

FIG. 1. (a) Schematic depiction of a counter-diffusion experiment. Protein (blue) and precipitant (pink) solutions are loaded

into a capillary and separated due to an isolation valve. Upon opening of the valve, the two solutions counter-diffuse, as

indicated by the color gradient. Typically, the precipitant solution will diffuse more quickly than the protein because of the

difference in the molecular weight. The resulting concentration gradient will sample a range of supersaturation levels,

resulting in a range of outcomes including precipitation at very high supersaturation levels and the growth of crystals at

more optimal conditions. (b) Optical micrograph of a microfluidic chip for free-interface diffusion experiments. Three pairs

of wells with different volumetric ratios are connected by a microfluidic channel. Pneumatic valves (orange) control fluid

flow and allow for filling and isolation of the chambers. (c) Photograph of an array chip with 144 parallel crystallization

chambers. (d) 3D exploded view showing the different materials and layers used in a single well of an X-ray compatible

array chip. (e) Schematic design of a 96-well array chip. Protein and precipitant solutions are filled into the black channels.

Each chip screens 12 different precipitant conditions over 8 different protein-to-precipitant ratios, varying from 4:1 to 1:4

along a single column. Three sets of valves (blue, green, and pink) are used to control all fluid flow on the entire chip.

Embossed window structures (yellow) are present to minimize contributions to the X-ray background from the device. (b)

and (c) Adapted with permission from Hansen et al., Proc. Natl. Acad. Sci. U. S. A. 99(6), 16531–16536 (2002). Copyright

2002 National Academy of Sciences.54 (d) and (e) Adapted with permission from Perry et al., Lab Chip 13(16), 3183–3187

(2013). Copyright 2013 Royal Society of Chemistry.40

032202-3 S. Sui and S. L. Perry Struct. Dyn. 4, 032202 (2017)

enabled the development of a range of multi-layer microfluidic device structures such as inte-

grated valves and pumps based on the deflection of a thin PDMS membrane.75–78

Probably, the most well-known microfluidic device for protein crystallization was devel-

oped by Quake et al., where pairs of fluidic chambers were used to screen for crystallization

conditions via free-interface diffusion (FID).54,79–85 For a single crystallization experiment,

three different volumetric ratios of protein and precipitant were tested, as defined by the size of

the molded chamber. Control of fluid flow and isolation of the chambers were achieved with

integrated pneumatic valves (Figure 1(b)). By scaling out, the components of an individual

crystallization experiment were replicated across a larger area to create an integrated array chip

(Figure 1(c)). This device architecture was commercialized by Fluidigm Corp., along with the

necessary ancillary equipment for valve control as the Topaz System, one of the first commer-

cially available microfluidic platforms for protein crystallization.86 Recognizing the challenge

of harvesting crystals from such a device, a thinner X-ray compatible version was also

fabricated.84

One of the limitations of many first-generation integrated microfluidic devices, including

the initial FID chip, was the use of valves that required the application of pressure in order to

remain sealed. The subsequent development of vacuum actuate-to-open valves enabled the

design of array-style counter-diffusion chips that could be set up and then allowed to incubate

without the need for ancillary pressure sources (Figures 1(d) and 1(e)).18,19,39,40 Furthermore,

this new generation of devices was designed specifically with in situ X-ray analysis in mind.

These chips retained only the thin layer of PDMS necessary for valve actuation, replacing the

remaining device layers with thin films of cyclic olefin copolymers (COCs) to alleviate the

potential for sample dehydration during incubation and/or data collection (Figure 1(d)).18,19,39,40

Similar device architectures have also been applied to microfluidic platforms to facilitate the

lipidic cubic phase (LCP) method for crystallizing membrane proteins.87–89 A wide range of

other integrated microfluidic devices have also been developed to help survey crystallization

phase space and protein solubility behavior.54,79,89

D. SlipChip devices

However, it should not be supposed that multi-layer architectures are the limit of integrated

microfluidics. Ismagilov et al. developed an elegant platform for sample formulation termed

SlipChip.57,90–92 SlipChip-based devices consist of channel and well features fabricated into the

top and bottom layers of a device. A lubricating layer of a fluorocarbon oil is used to facilitate

slipping of the two plates relative to one another, allowing for the alignment of fluidic channels

with microfluidic wells for filling and subsequent “slipping” of the two plates to align features

containing, for instance, protein solution and precipitant solution (Figure 2). A variety of device

designs have been reported, including geometries for both microbatch and FID.57 While X-ray

compatible SlipChips have not been reported, such devices could serve as interesting platforms

to create dense sample arrays for serial crystallography experiments.

E. Capillary valves and centrifugal devices

The small length scales of microfluidic geometries also allow for the use of surface

tension-based or capillary pressure-based valving. In these types of devices, the ability of a liq-

uid to flow past either a hydrophobic surface patch or a constriction in the channel is deter-

mined by the applied pressure.93 While this pressure can be applied by any source, it is conve-

nient to utilize a CD-based form factor and use centrifugal force to drive fluid flow (Figure 3).

Thus, the force needed to “open” such a capillary valve is determined by the spin rate of the

device and the radial location of the valve. Lower-force valves can be used to facilitate initial

metering applications while higher-force valves can be used to control subsequent mixing

events. These types of centrifugal devices have been reported in both microbatch94,95 and vapor

diffusion configurations96 and can be made X-ray compatible.95,97

032202-4 S. Sui and S. L. Perry Struct. Dyn. 4, 032202 (2017)

F. Droplet microfluidics

The last major class of microfluidics is based on the formation of droplets in two-phase

flow (Figure 4). A tremendous advantage of droplet-based microfluidics over the types of pre-

fabricated chips described previously is their ability to change experimental parameters such as

the protein-to-precipitant ratio or the total sample volume by simply adjusting the flowrates of

FIG. 2. A SlipChip (well-based) system. Schematics showing (i) loading of protein into a SlipChip that has already been

preloaded with precipitants and (ii) slipping to combine protein and precipitants to form trials. (iii) Optical micrograph

showing the loading of a green food dye (mimicking the protein) into a SlipChip that has already been preloaded with col-

ored dyes (mimicking precipitants). (iv) Optical micrograph of the SlipChip after slipping to combine the solutions. (v)

Crystals of the photosynthetic reaction center from Blastochloris viridis obtained using this device. Adapted with permis-

sion from Du et al., Lab Chip 9(16), 2286–2292 (2009). Copyright 2009 Royal Society of Chemistry.90

FIG. 3. Schematic depiction of a vapor diffusion-style centrifugal microfluidic device, showing (a) the top view and (b) the

vapor diffusion chamber. Reprinted with permission from Wang et al., Sens. Actuators, B 219, 105–111 (2015). Copyright

2015 Elsevier.96

032202-5 S. Sui and S. L. Perry Struct. Dyn. 4, 032202 (2017)

the various component streams during device operation. Furthermore, such trials can be formu-

lated either as microbatch or pseudo-vapor diffusion trials, based on the permeability of the oil

phase and/or the container used to house the final droplets.15,98–118 Additionally, the two-phase

nature of this method ensures that the formation of precipitants and/or crystals will not result in

clogging of the device. This flexibility has been extended to the formulation of LCP trials for

membrane proteins.119–121 Beyond formulation, storage of the resulting droplets can be per-

formed either in two-dimensional arrays in a chip-like structure or in flexible tubing. Thus, it is

straightforward to formulate crystallization trials into X-ray compatible capillaries, tubing, or

planar arrays for subsequent in situ analysis.15,99,101,103,104,106,109–111,120–122

For all these various microfluidic crystallization platforms, the obvious benefits are the

small sample volumes and high-throughput formulation. However, the true utility of these devi-

ces is the exquisite control that is afforded over local gradients, concentrations, and mixing.

This reproducibility in terms of sample formulation has been suggested as a possible explana-

tion for the high degree of isomorphism observed in crystals grown on-chip,18,40 as compared

to more traditional, larger-scale methods.5,37,38,41,42 This observation could have tremendous

utility in terms of sample preparation for large-scale serial crystallography experiments.

III. DESIGN CONSIDERATIONS FOR X-RAY COMPATIBILITY

The design and optimization of any X-ray experiment relies on finding a balance between

the observed signal and contributions to background noise. For protein crystallography

FIG. 4. (a) Schematic depiction of a droplet microfluidics setup. Oil and various aqueous solutions are metered by a bank

of syringe pumps to a microfluidic junction. The resulting droplets are then quickly mixed as they pass through a curved

channel region, before passing into an external capillary for storage. (b) Optical micrograph of the injection and mixing

regions on a microfluidic chip. (c) Optical micrographs of crystallization trials for the photosynthetic reaction center from

Rhodopseudomonas viridis. The concentration of an ammonium sulfate precipitate solution is increased from left to right,

and a transition is observed from an amorphous precipitate to a large single crystal and to small microcrystals. Scale bar:

100 lm. (a) and (b) Adapted with permission from Yadav et al., J. Appl. Crystallogr. 38(6), 900–905 (2005). Copyright

2005 International Union of Crystallography.104 (c) Adapted with permission from Li et al., Proc. Natl. Acad. Sci. U. S. A.

103(51), 19243–19248 (2006). Copyright 2006 National Academy of Sciences.111

032202-6 S. Sui and S. L. Perry Struct. Dyn. 4, 032202 (2017)

experiments, this translates to balancing the strength of the diffraction from the crystal with the

attenuation of both the incident and diffracted beam and contributions to background noise.

These background effects can come from the direct beam itself, if the beam size is not matched

to the sample size, or can be the result of X-ray scattering due to the presence of air, liquid

around or within the crystal, and/or the materials used to mount the crystal. Thus, the design of

an X-ray compatible microfluidic device for the delivery of crystals to the X-ray beam can

have a tremendous impact on the quality of the resulting data.

While many of the early microfluidic devices for protein crystallization were focused solely

on crystallization screening and optimization, the need for X-ray compatible microfluidics was

quickly recognized because of the challenge in translating crystallization results obtained on-

chip to more traditional, larger-scale platforms. However, at the time, most traditional micro-

fluidic chips were manufactured from millimeter-thick layers of PDMS and/or glass that were

incompatible with the requirements for X-ray diffraction experiments, requiring a reexamination

of the materials and fabrication strategies for such devices.

A. Design considerations

From a design perspective, X-ray compatibility must address the attenuation of both the

incident and the diffracted X-ray beam and scattering resulting from the material of the device

itself. Attenuation results from the absorption of photons into the material, thereby decreasing

the intensity of both the incident X-ray beam and the resultant signal. Scattering is an elastic

redirection of photons based on the internal structure of the material that scales with the thick-

ness of the material and can increase the observed background. The strength of the diffraction

signal from a crystal is related to not only the degree of order within the crystal but also the

packing density and the size of the crystal.1,2,39,46,123

Attenuation can be calculated for a particular energy based on the exponential decay in

intensity of a narrow beam of monochromatic photons from an incident intensity I0 as it passes

through a material of thickness x and density q with a mass attenuation coefficient of the mate-

rial l,124

I ¼ I0 exp ð�l=qÞx½ �: (1)

Thus, decreasing the thickness of any material interacting with the X-rays can mitigate both the

attenuation and scattering effects. Eq. (1) also demonstrates the reason why X-ray experiments

are frequently done in a vacuum, enabling a decrease in the density of air present between the

sample and the detector.

Attenuation coefficients have been well studied and documented for elemental materials.124

The mass attenuation coefficient for a compound or a mixture can be calculated based on the

sum of the contribution to attenuation from each of the individual elements i, weighted based

on their mass fraction wi,

l ¼X

liwi: (2)

It should be noted that the attenuation coefficient varies significantly as a function of photon

energy, with stronger attenuation observed for soft X-rays compared to hard X-rays.

Thus, from Eqs. (1) and (2), the transmission factor I/I0 can be calculated as a function of

thickness for any material. Analysis of a plot of transmission vs. thickness (Figure 5) highlights

the importance of both the material composition and the density in signal attenuation. The low

density of gases such as air and helium facilitates a much higher level of transmission than

solid materials; however, the lower atomic number of helium dramatically decreases attenuation

effects. Similarly, thin films of organic polymers such as cyclic olefin copolymer (COC) and

poly(methyl methacrylate) (PMMA) show significantly lower attenuation compared to silicon-

based elastomers like poly(dimethylsiloxane) (PDMS) or hard materials such as quartz (SiO2),

silicon, or silicon nitride (Si3N4), while atomically thin films such as graphene mitigate

032202-7 S. Sui and S. L. Perry Struct. Dyn. 4, 032202 (2017)

attenuation purely by thickness. It is interesting to note that water, the presence of which is

practically inescapable in protein crystallography, attenuates the X-ray signal to an equal or

greater degree than most organic polymers. Table II summarizes the results shown in Figure 5,

listing both the density and the absorption coefficient for each material and quantifying the

thickness associated with varying levels of X-ray transmission.

Thus, the solution to creating X-ray compatible microfluidics typically involves decreasing

the thickness of the various device layers and possibly substituting dense or high atomic num-

ber materials (such as silicon-containing PDMS) for lighter organic polymers. Indeed, Quake

et al. were able to transform their approximately �1 cm thick FID chip54 to a device where a

�250 lm thick section of the device could be easily removed and mounted for X-ray analy-

sis.80,84 Similar strategies were adopted by Kenis et al., Perry et al., and later Fraden et al.,keeping a minimal amount of elastomeric PDMS in the device to facilitate microfluidic valving

and capping the device on top and bottom with a more X-ray compatible film of optically trans-

parent COC to minimize the potential for sample dehydration due to water loss through the thin

PDMS layers.15,18,19,39,40,88,89,122,125 The quality of diffraction observed from these chips has

been sufficient to solve the structures of novel proteins,40,80 including via single-wavelength

anomalous diffraction methods40 and time-resolved Laue diffraction studies.19

B. Device materials for microcrystallography

Thin polymeric materials have proven to be a successful solution for the challenge of

in situ crystallography. In particular, COC has seen widespread adoption as the polymer film

of choice for X-ray compatible devices,46 including simple channel structures for counter-

diffusion,56,58,60,61,126 droplet-based devices,108,109,118 and larger-scale X-ray compatible well-

plates.127–140 However, further decreasing the device thickness to achieve the signal-to-noise

levels required for microcrystallography is a significant materials’ challenge. Typical reports

of X-ray compatible microfluidics describe results where the path length of the device materi-

als is nearly twice that of the crystal of interest.18,19,40,128,129,141 Thus, the analysis of micron-

scale or smaller crystals would suggest the need to shrink device materials to a total thickness

of 1–10 lm. Unfortunately, although ultra-thin polymeric films are available, such materials

tend to suffer from poor mechanical stability and more critically show poor barrier perfor-

mance against sample dehydration.

While the popularity of polymeric materials has stemmed from their low cost and ease

of use, micromachining of hard materials has been demonstrated as a viable solution for the

creation of stable, X-ray compatible devices for the in situ analysis of microcrystals. Various

deposition, photolithography, and etching strategies have been utilized to fabricate a range

FIG. 5. A comparison of the transmission factors I/I0 for varying thicknesses of helium, air, COC, graphene, PMMA, water,

PDMS, quartz, silicon nitride, and silicon at an X-ray energy of 12.4 keV or a wavelength of 1 A.

032202-8 S. Sui and S. L. Perry Struct. Dyn. 4, 032202 (2017)

TABLE II. Calculated values of the material thickness (in lm) corresponding to the transmission of 99.9%, 99%, and 90% of the incident X-ray beam at an energy of 12.4 keV or a wavelength of 1 A.

Transmission

factor

Helium

(He) Air N79O21 COC C9H14

PMMA

C5H8O

Water

(H2O)

Graphene

(C)

PDMS

Si61O60C124H368

Quartz

(SiO2)

Silicon nitride

(Si3N4)

Silicon

(Si)

99.9% 26 701 345 0.88 0.68 0.62 0.15 0.136 0.107 0.093 0.060

99% 268 223 3468 8.9 6.8 6.3 1.5 1.37 1.08 0.93 0.60

90% 2 811 861 36 356 93 72 66 16 14.4 11.3 9.8 6.3

Density q (g/cm3) 1.66� 10�4 1.23� 10�3 1.02 0.94 1.00 1.8 0.92 2.65 3.2 2.3

l/q at 1 A (cm�1) 3.747� 10�5 2.898� 10�3 1.13 1.47 1.607 6.51 7.33 9.33 10.8 16.6

032202-9

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S.L.P

erry

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of microstructures out of silicon or other hard materials. The resulting devices can then

be sealed with �50 to 500 nm-thick silicon nitride windows.34,46,141–144 This approach

allows for the creation of extremely small features, such as wells to capture individual

microcrystals. However, the devices are relatively time and labor intensive and expensive

to produce.

Recently, Perry et al. reported the use of large-area graphene films as both ultra-thin

X-ray transparent windows and vapor diffusion barriers.123 This proof-of-concept work,

inspired by earlier reports on the stability of graphene-wrapped crystals,145,146 utilized win-

dows of single-layer graphene backed by a 500 nm-thick layer of PMMA for structural stabil-

ity, surrounding a microfluidic channel cut into 100 lm-thick COC. The resulting microfluidic

chambers were shown to be stable against dehydration for at least two weeks and were robust

enough to survive overnight shipping to the synchrotron. Using lysozyme as a model system,

albeit with relatively large crystals, the authors then analyzed the resulting levels of back-

ground scattering and the observed signal-to-noise in their diffraction data, comparing diffrac-

tion through graphene/PMMA-only windows with the observed signal obtained through gra-

phene/PMMA and a 100 lm COC layer (Figure 6). Both the two-dimensional diffraction

images and the corresponding one-dimensional integrated intensity plots showed a tremendous

enhancement in the observed signal-to-noise, particularly at high resolution and in the regions

where a significant scattering signal from COC was observed. This initial work shows tremen-

dous promise for the use of graphene-based windows in other areas of X-ray compatible

microfluidics.43

IV. PLATFORMS FOR SERIAL CRYSTALLOGRAPHY

Thus far, this review has discussed the general use of microfluidics in the context of pro-

tein crystallization and the potential for adapting such technologies to facilitate the growth of a

large number of isomorphous crystals. However, for serial crystallography, much of the techno-

logical focus has been less on crystal growth and more on the efficient delivery of crystals into

the X-ray beam. This discontinuity in the use of microfluidic technology for structural biology

represents an opportunity to couple exquisitely controlled microfluidic methods for crystalliza-

tion with high-throughput strategies for sample analysis. While most of the microfluidic crystal-

lization platforms were originally designed for more traditional-scale experiments on the order

of 1–100 crystals, strategies for “scaling out” could be used to facilitate the controlled, large-

scale preparation of crystals at the scale necessary for serial or even time-resolved serial crys-

tallography experiments.

Looking beyond crystal growth, the priorities of a serial crystallography experiment and/or

a sample delivery technology include (i) maximization of diffraction data quality, (ii) maximi-

zation of data collected per quantity of the sample, and (iii) maximization of experimental

capacity by enabling efficient data collection and minimization of down time.141 Although these

priorities might appear somewhat obvious and represent a common sense approach to experi-

mental design, the challenge lies in actualizing such goals in the context of the high repetition

rates of current and planned X-ray sources. For instance, while fast readout detectors enable

data collection on the order of 10 Hz at synchrotron sources, X-ray pulses are currently deliv-

ered at a rate of 120 Hz for the LCLS and are anticipated in the MHz regime at the European

XFEL and the LCLS II.

Successful sample delivery methods for serial crystallography at both XFEL and synchro-

tron sources have utilized both fixed-target and injector technologies, nearly all of which qual-

ify as microfluidic or microscale in nature. As with the X-ray compatible microfluidic devices

discussed earlier, the thickness of any material surrounding the crystals and the stability of the

crystals in the resulting environment must be carefully addressed, particularly for weakly dif-

fracting microcrystals. Here, we will briefly summarize the various technologies that have been

used to date. We also refer the reader to other recent review articles on sample delivery

techniques.141,147

032202-10 S. Sui and S. L. Perry Struct. Dyn. 4, 032202 (2017)

A. Injectors

1. Gas dynamic virtual nozzle (GDVN)

The most common delivery device for serial crystallography experiments at XFELS has

been the gas dynamic virtual nozzle (GDVN, Figure 7(a)).3,20–24,141,147–156 The original GDVN

design consisted of two relatively large-diameter concentric capillaries. The slurry of crystals

flows through the inner capillary, while a sheath gas such as helium or nitrogen flows through

the outer one. More recently, soft lithographic and 3D printing methods for the robust manufac-

ture of nozzles have been reported.157,158 For all these various GDVN designs, the pressure of

the flowing sheath gas is used to focus the liquid stream into a narrower jet that could be

achieved by the features of the nozzle alone. This gas-driven focusing also allows for the use

of larger capillaries or injector features, relative to the size of the crystals, to decrease the

FIG. 6. (a) One-dimensional integrated X-ray intensity profiles showing the relative strength of the observed (Laue) diffrac-

tion signal from a lysozyme crystal compared to the noise resulting from background scattering due to the presence of

device materials as a function of resolution. The corresponding two-dimensional diffraction images for a crystal (b) located

between two 500 nm-thick PMMA/graphene windows and a 100 lm-thick COC layer (orange) and (c) a crystal located

between two 500 nm-thick PMMA/graphene windows (magenta). Adapted with permission from Sui et al., Lab Chip 16,

3082–3096 (2016). Copyright 2016 Royal Society of Chemistry.123

032202-11 S. Sui and S. L. Perry Struct. Dyn. 4, 032202 (2017)

potential for clogging and allow for the modulation of the jet size, relative to the crystal size.

Furthermore, the presence of the sheath helps to delay ice formation during data collection per-

formed in a vacuum.159 Typical jet sizes are 1–5 lm in diameter,141 facilitating minimization of

signal attenuation and background noise from the carrier fluid itself. The tunability and low

background of GDVN-based systems have even enabled the analysis of sub-micron crystals at

XFEL sources.4 Despite these benefits, the most significant disadvantage of GDVN injectors is

poor efficiency in terms of sample utilization. The current data acquisition rate at the LCLS is

typically 120 Hz, resulting in estimated crystal hit rates on the order of 0.01%–0.1%.147,160,161

Thus, sample utilization at synchrotron sources would be prohibitive. However, for the higher

MHz-level data acquisition rates anticipated at the European XFEL and the LCLS II, more opti-

mal sample utilization should be achievable.

2. Electrokinetic injectors

To increase the efficiency of data collection at currently available sources, a major goal

has thus been to decrease the rate of sample delivery. One potential solution to this chal-

lenge has been the use of electrospinning or electrokinetic injection of the crystal slurry

(Figure 7(b)).141,161,162,164–168 In this method, an applied voltage is used to extend the liquid

emerging from a capillary into a fine Taylor cone. The addition of viscosity modifiers such

as glycerol or poly(ethylene glycol) (PEG) can facilitate the formation of a liquid jet, rather

than a spray of droplets. While electrospinning can be performed directly on the crystal

slurry,162 data collection performed in a vacuum can result in freezing of the jet. Similar to

the GDVN, coaxial flow where an outer “sister liquor” can be used to mitigate freezing

FIG. 7. An overview of injector technology for serial crystallography. (a) GDVN liquid injector schematic for use at the

LCLS, including images of the observed diffraction data. (b) Electrospinning jet schematic depicting the injection of a crys-

tal suspension and the resulting powder diffraction pattern. (c) Acoustic injector for on-demand drop injection. The setup

can be operated either vertically (purple) or inverted (red). (d1) Schematic depiction of the LCP injector. Cross-polarized

micrographs of the extruded LCP with (d2a) helium as the co-flowing gas, resulting in the dessication and formation of the

birefringent crystalline lipid, and (d2b) nitrogen as the co-flowing gas, showing no visible birefringence. Scale bar: 100 lm.

The corresponding diffraction images showing (d3a) diffraction spots from A2A adenosine receptor microcrystals and

strong powder rings from crystalline lipid and (d3b) diffraction from serotonin receptor 5-HT2B with no visible powder dif-

fraction. (a) Adapted with permission from Chapman et al., Nature 469, 73–77 (2011). Copyright 2011 Royal Society of

Chemistry.3 (b) Adapted with permission from Sierra et al., Acta Crystallogr., Sect. D: Biol. Crystallogr. 68, 1584–1587

(2012). Copyright 2012 International Union of Crystallography.162 (c) Adapted with permission from Roessler et al.,Structure 24, 631–640 (2006). Copyright 2016 Elsevier.32 (d) Adapted with permission from Weierstall et al., Nat.

Commun. 5, 3309 (2014). Copyright 2016 Royal Society of Chemistry.163

032202-12 S. Sui and S. L. Perry Struct. Dyn. 4, 032202 (2017)

effects and to facilitate focusing of the jet.164 This electrokinetic method of sample injection

allows for a 10-fold decrease in the overall flowrate, helping to improve sample utilization

to around 5%.164

3. On-demand droplet delivery

With both the GDVN and electrokinetic injection methods, a slurry of crystals is delivered

to the X-ray beam as a continuous jet. The potential for inefficient sample utilization is strongly

coupled to the continuous nature of such a delivery method. An alternative delivery strategy is

the on-demand delivery of discrete liquid droplets (Figure 7(c)). This approach has been dem-

onstrated using both acoustic32,167,169 and piezoelectric36 droplet injectors, resulting in a hit rate

of close to 90%. However, the diameter of the delivered droplets has typically been at least an

order of magnitude larger than for the GDVN or electrokinetic methods, representing a signifi-

cant increase in the background. Thus, on-demand droplet delivery could be used for serial

analysis of larger-scale crystals but would be extremely challenging for the analysis of weakly

diffracting or submicron crystals.32

4. Aerosol injection

Sample nebulization has also been proposed as a sample delivery strategy for serial crystal-

lography. The advantage of working with an aerosolized sample is the absolute minimization of

background scattering and signal attenuation effects from the carrier solvent.170 This type of

approach could be used to enable analysis of nanocrystals; however, the speed of sample deliv-

ery would most likely be the fastest of all the methods discussed heretofore and would result in

the lowest hit rates. Additionally, the effect of nebulization on protein crystal quality and hydra-

tion has not yet been fully explored161 although the injector shows promise for single particle

diffractive imaging experiments.170

5. Viscous media extrusion

Stepping aside from advanced injector technologies, one of the simplest ways to improve sam-

ple efficiency is to slow down the overall flowrate by increasing the viscosity of the stream. Using

positive displacement extrusion, a variety of high viscosity materials including the lipidic cubic

phase (LCP) matrix used in membrane protein crystallization (Figure 7(d)),27,141,147,161,163,171–174 a

grease matrix,175–177 agarose,178 and hyaluronic acid have been used as carrier materials for serial

crystallography.179 In these methods, the aqueous slurry of crystals is mixed with the higher vis-

cosity component. One reason why a variety of high viscosity matrices have been explored is the

challenge of finding a carrier material that is compatible with each particular protein system and

crystallization condition. Transfer of crystals into a viscous medium has the potential to cause

osmotic stress and potentially alter protein solubility.179 Additionally, the LCP method in particular

can be sensitive to crystallization conditions. For instance, the LCP is not compatible with ammo-

nium sulfate,171,176,180,181 while agarose requires gentle heating of the sample.178

With respect to signal-to-noise, as with any method, the diameter of the extruded material

will directly affect the level of background scattering. One drawback of this approach is the dif-

ficulty in extruding small columns of viscous materials. For instance, pressures of several thou-

sand psi are required to extrude the LCP through a capillary of diameter 10–50 lm.147,163 Thus,

while viscous jets have the potential to enable structure determination of small and weakly dif-

fracting crystals, a significant loss in signal-to-noise is expected because of the larger diameter

of the carrier material. The level of background noise resulting from the carrier material is fur-

ther exacerbated by the fact that nearly all the materials used to date have characteristic molec-

ular length scales that result in an observable background scattering signal. For instance, the

LCP shows characteristic diffuse scattering signals at approximately 4.5 A,172,178 grease at

around 5 A, agarose at 3.2 A,178 and hyaluronic acid at 3.3 A.179 Depending on the expected res-

olution of the protein crystals, this scattering ring could dramatically affect the quality of the

observed diffraction. Preliminary comparison work has suggested that the scattering intensity of

032202-13 S. Sui and S. L. Perry Struct. Dyn. 4, 032202 (2017)

agarose is lower than that of the LCP178 and that hyaluronic acid showed weaker scattering

than grease-based matrices.179

B. Fixed-target approaches

While a degree of uncertainty regarding the crystal location exists with the majority of

injector technologies, the most sample-efficient delivery strategy would involve preparing an

ordered array of crystals onto a fixed-target type of mount and then rapidly rastering through

the various sample locations (Figure 8(a)).161 However, three potential challenges must be con-

sidered. Firstly, such an approach requires the development of a method for creating such an

array of crystals. Secondly, the batch nature of this kind of fixed-target device could necessitate

frequent exchange, thereby increasing the dead time during an experiment. Thirdly, while these

types of mounts are typically robust in the context of synchrotron radiation, the intensity of the

unattenuated X-ray pulses generated at XFEL sources is likely to destroy any sort of window

material, which has the potential to compromise the entire array of samples.

FIG. 8. An overview of fixed-target mounting strategies for serial crystallography. (a) Schematic depiction of a crystal

slurry embedded in a micro-manufactured silicon mesh with silicon nitride windows being rapidly translated relative to

the beam path for data collection at the LCLS. (b) A droplet-microfluidics based X-ray compatible array chip mounted

on the goniometer inside the Cornell CHESS F1 beamline. The inset shows an optical micrograph of glucose isomerase

crystals inside the microfluidic device. (c) X-CHIP with 24 crystallization drops mounted on a goniometer. (d) Optical

micrograph of a plastic grid fabricated from SU-8. (e) A sample-mounting grid affixed to a standard magnetic base. For

comparison, a Hampton Research-style copper magnetic sample pin is also shown. Samples fit into a Uni-Puck enclosure.

The optical microscopy image shows lysozyme crystals growing in sitting-drops mounted on a grid. (a) Adapted with

permission from Hunter et al., Sci. Rep. 4, 6026 (2014). Copyright 2014 Royal Society of Chemistry.34 (b) Adapted with

permission from Heymann et al., IUCrJ 1, 349–360 (2014). Copyright 2014 International Union of Crystallography.15 (c)

Adapted with permission from Kisselman et al., Acta Crystallogr., Sect. D: Biol. Crystallogr. 67, 533–539 (2011).

Copyright 2011 International Union of Crystallography.186 (d) Adapted with permission from Feld et al., J. Appl.

Crystallogr. 48, 1072–1079 (2015). Copyright 2015 International Union of Crystallography.191 (e) Adapted with permis-

sion from Baxter et al., Acta Crystallogr., Sect. D: Biol. Crystallogr. 72, 2–11 (2016). Copyright 2016 International

Union of Crystallography.195

032202-14 S. Sui and S. L. Perry Struct. Dyn. 4, 032202 (2017)

Interestingly, nearly all the fixed target solutions for serial crystallography have been devel-

oped independent of previous X-ray transparent microfluidic array chips for protein crystalliza-

tion. This is most likely a consequence of the emphasis on sample preparation for use at

XFELs, where large-scale methods have been used to grow the millions of crystals needed for

such high-throughput experiments. However, a consequence of this type of ex situ crystal

growth is the need to transfer crystals into an injector or sample array, which can cause damage

and/or sample loss.18,19,40,123,133,171,176 Thus, depending on the injection or mounting strategy, it

may also be necessary to pre-prepare and/or sort crystals by size for subsequent use.182,183

Finally, as in any protein crystallography experiment, samples must be protected against dehy-

dration or degradation during data collection, all while addressing experimental priorities

related to data quality and signal-to-noise.159

1. Goniometer-based approaches

One of the simplest approaches to mounting a large number of crystals is the use of tradi-

tional loops,17,184 micromounts,185 or capillaries16 to mount a slurry of crystals.169 It is also

possible to mount crystals grown directly on the mount, as in the case of the X-CHIP, where

pinned droplets are protected against dehydration by a thin coating of oil (Figure 8(c))186,187 or

the aforementioned graphene-based microfluidic devices.123 Such samples can be cryocooled,

protected by a capillary sheath or other materials, or analyzed directly using a traditional goni-

ometer setup for sample manipulation. Again, the presence of extra material and/or solvent will

increase background noise and decrease the resultant data quality. Thus far, these types of

smaller-scale mounting approaches have been favored more at synchrotron-based sources

because of the lower rates of data acquisition and the higher availability of beam time. Serial

approaches have also been reported for larger loop-mounted crystals, where a fresh crystal vol-

ume is sampled each time.188–190

2. Sample arrays

To increase the number of crystals available for analysis, a variety of mesh and array-

based approaches have been developed.25,31,33,34,37,143,185,191–195 The simplest mounting strategy

involves the deposition of a crystal slurry between two thin silicon nitride wafers.143 However,

most approaches have utilized microfabricated mesh-type structures. One advantage of a mesh-

type structure is the potential to localize individual crystals within each small micro-well. This

process, along with the removal of excess mother liquor to reduce the background, can be facil-

itated by the application of vacuum to the mesh structure.37 Mesh structures have been fabri-

cated out of silicon25,31,37,192,193 and polymers such as SU-8 (Figure 8(d))191 and polycarbonate

(Figure 8(e)).185,195 The material of the mesh itself should not affect the quality of the observed

diffraction, provided that the crystal is well located within the center of the well. However,

care must be taken when crystalline materials such as silicon or metal are used, as intense dif-

fraction from the mesh structure can potentially damage the detector.37,191,193 One particular

advantage of this type of mesh, or well-based approach, is its ability to insulate crystals in one

region of the device from the destructive aspects of the intense XFEL beam when applied to a

neighboring well. Such isolation strategies would be critical in adapting any of the aforemen-

tioned protein crystallization devices for use as fixed-target XFEL delivery platforms.

Once mounted, a variety of approaches have been utilized to stabilize the slurry of crystals

during analysis. From a signal-to-noise perspective, the use of either cryocooling37 or a humidi-

fied stream of air193 circumvents the need to seal the device, helping to minimize the back-

ground. However, it is more common to provide some layer of protection, particularly, as data

collection at XFEL sources is often performed under vacuum. Examples have been reported for

crystals embedded in oil;34 however, most reports have sealed the device using thin films of

plastic, such as polyimide,31 mylar,25 PMMA,192 or polycarbonate.195 These films have the

advantage of being relatively cheap and easy to use. However, the physical strength and barrier

properties of most polymer films decrease significantly as a function of film thickness, sugges-

ting the possibility of a lower limit on the crystal size for mounting and stabilization strategies

032202-15 S. Sui and S. L. Perry Struct. Dyn. 4, 032202 (2017)

that rely on the use of polymer films. Alternatively, micromachining can be used to fabricate

ultra-thin (e.g., 20–50 nm-thick) silicon nitride windows, which provide rigidity, sample stabil-

ity, and excellent X-ray transmission.34,191,194 These hard materials have the potential to facili-

tate the analysis of nanocrystals but are more expensive and labor-intensive to manufacture

than polymer films. Ultimately, it should be possible to use atomically thin barrier materials

such as graphene for this purpose.43,123 While proof-of-concept results have been reported for

the in situ analysis of crystals grown on a microfluidic chip at a synchrotron source,123

graphene-based materials have not yet been extended for use in high-throughput serial crystal-

lography experiments at XFELs.

Generally, mesh structures represent a passive strategy for the creation of an ordered array

of samples. Disadvantages of this approach are the potential for either clustering and overlap-

ping of crystals at high concentrations or empty wells and less efficient data collection at lower

concentrations. Active strategies for the arrangement of single crystals have also been reported.

Brunger et al. reported a microfluidic trap array which utilized hydrodynamic forces to arrange

microcrystals grown off-chip into an ordered array (Figure 9).33 In contrast, Fraden et al.reported that kinetic optimization of droplet-microfluidics was used to ensure the growth of

only a single in each droplet.15 The droplets were then arranged into a microfluidic array for

subsequent analysis (Figure 8(b)). Both of these approaches have tremendous promise as fixed-

target delivery strategies. However, a key advantage of the droplet-based approach described by

Fraden et al. is its ability to both grow and then analyze protein crystals in place, without the

need for sample manipulation. Further studies would be needed to explore the limits of the

crystal size and signal-to-noise levels achievable using this droplet-based approach, as well as

an examination of whether such arrays of droplets would be stable in the destructive context of

ultra-brilliant XFEL pulses.

Ultimately, a combination of factors must be considered in terms of experimental design

and the development of a sample delivery strategy. The physical robustness, size, and available

quantity of a particular protein target will dictate, in part, an optimal sample delivery strategy

FIG. 9. A microfluidic trap array for protein microcrystals. (a) Schematic representation of the overall crystal-capturing

device design. (b) Close-up of the general scheme for trap-and-bypass hydrodynamic crystal capture. (c) Schematic of a

single hydrodynamic trap (labeled in (b); WT is the width of the trap channel and LT is the length of the trap channel). (d)

Optical micrograph of a representative section of a fabricated crystal-capture chip. (e) Optical micrograph series showing

single and multiple lysozyme microcrystals immobilized in hydrodynamic traps. Adapted with permission from Lyubimov

et al., Acta Crystallogr., Sect. D: Biol. Crystallogr. 71, 928–940 (2015). Copyright 2015 International Union of

Crystallography.33

032202-16 S. Sui and S. L. Perry Struct. Dyn. 4, 032202 (2017)

for serial analysis. However, for hard-to-handle samples, there is tremendous opportunity to

integrate microfluidic platforms for protein crystallization using in situ, high-throughput serial

crystallography at both synchrotrons and XFELs. Furthermore, there is also tremendous poten-

tial to harness the complex fluid handling capabilities of microfluidic devices for more challeng-

ing time-resolved crystallography experiments.

V. TIME-RESOLVED STRUCTURE DETERMINATION

In addition to the aforementioned experimental design challenges for serial crystallography,

experiments geared towards the elucidation of protein structural dynamics must also address the

need for reaction initiation for time-resolved measurements. The detection of transient structural

intermediates in time-resolved crystallography requires a rapid triggering event or pump (e.g., a

laser pulse, temperature jump, or substrate addition) to synchronize reaction events within a

crystal. This process must then be repeated to facilitate data collection at the various time

points of interest, as well as at different crystal orientations. Prior to the development of serial

methods for crystallography, these types of experiments were only feasible on very large, stable

crystals where the structural change or enzymatic reaction was reversible and would naturally

reset to the initial state, allowing for a large number of repetitions of this pump-probe

cycle.19,196–203 The advent of serial crystallography has opened up the potential for time-

resolved experiments to smaller crystals and targets that are highly sensitive to radiation

damage, as well as reaction pathways that are irreversible within the limitations of the crystal

lattice.177,201,204–206 Furthermore, the development of next-generation X-ray sources has

expanded the range of available timescales from femtoseconds to seconds or longer.

A. Laser triggering

The challenge associated with reaction triggering is the necessity for the triggering event

to occur at a faster rate than the kinetics of the structural changes in question. Because of

this experimental requirement, a vast majority of time-resolved crystallography experiments

have been performed on targets where a fast laser pulse can be used to trigger the reaction.

Examples include photolysis-induced dissociation of CO from myoglobin207,208 and the

photocycles of photoactive yellow protein (PYP),19,199,200,209–215 photosystem II,22,165–167 and

bacteriorhodopsin.174 It is also possible to use laser triggering to initiate a reaction through the

photorelease of a caged compound.202,216 However, many caged compounds suffer from poor

solubility, and the resulting rate of initiation is limited by the rate of diffusion.

Serial approaches to time-resolved crystallography have recently been demonstrated using

laser photoinitiation at XFELs (Figure 10). Initial studies on photosystem II,20,22 myoglobin,151

and photoactive yellow protein (PYP)23,24 took advantage of a GDVN injector. Photoactivation

was achieved by laser pumping of the sample jet at a distance upstream of the X-ray pulse cor-

responding to the delay time of interest. The fast flowrates of GDVN injectors are such that

time delays longer than �100 ls would require sample illumination within the jet itself22,141 or

the use of a different sample delivery method. For example, the LCP injector has been used to

facilitate the time-resolved analysis of the light sensitive membrane protein bacteriorhodop-

sin,27,174 and a fixed-target approach utilizing a silicon mesh with mylar windows was used to

study CO dissociation from myoglobin.25 More recently, a combination of electrokinetic injec-

tion164 and an on-demand droplet injector with a conveyor-belt system169 was used with multi-

ple laser pulses to drive the activation of varying states of photosystem II at delay times rang-

ing from 0.5 s to 1 s.166,167

B. Chemical triggering

While light is the fastest and simplest method for initiating a reaction, the vast majority of

protein targets require a chemical trigger, such as the addition of a substrate, a pH jump, or a

change in ionic strength. Experimentally, it is much more difficult to affect such a change,

requiring mounting of crystals within a flow-cell to facilitate the fast delivery of the triggering

032202-17 S. Sui and S. L. Perry Struct. Dyn. 4, 032202 (2017)

molecules.217 However, even under ideal conditions, the accessible experimental timescales are

much slower for chemical triggering than for light-initiated reactions.

The rate at which reaction initiation can be carried out limits the accessible range of struc-

tural information. For chemical reaction initiation, the limiting rate is the timescale for the trig-

gering molecules to penetrate the crystal. Thus, only structural changes that are slower than the

diffusion time will be observable. If typical enzyme cycle times are on the order of microsec-

onds to milliseconds, one can then calculate the timescale for the diffusion of the triggering

molecule and determine the size of protein crystals, which will avoid diffusional limitations.

Calculations by Schmidt, based on the diffusivity of glucose and assuming no significant bar-

riers to diffusion within the crystal, suggest that the size of microcrystals is critical for the suc-

cess of chemically triggered time-resolved experiments (Table III).201,218 Furthermore, the use

of high concentrations of triggering molecules is important to facilitate diffusion and achieve

effective reaction initiation.219 With these experimental requirements in mind, many of the

injection strategies for serial crystallography are uniquely posed to usher in a new era of

dynamic protein structural studies.

Preliminary reports have described the use of GDVN injectors to facilitate chemical trig-

gering.29,30,35,220 By including an additional capillary into the GDVN architecture, diffusive

mixing between the crystal slurry and an outer sheath of triggering solution can be achieved.

The time for mixing can then be altered by adjusting the location of the mixing point within

the larger GDVN structure.141 This approach has been used to study the reaction of ß-lactamase

microcrystals from M. tuberculosis with an antibiotic solution of ceftriaxone29 and the binding

of ligands to the adenine riboswitch adaptor domain.30 For both these reports, crystals on the

order of 1–10 lm in size were analyzed at time-delays on the order of 2–10 s. The use of the

GDVN facilitated matching of the jet diameter to that of the crystals. While the mixing injector

FIG. 10. Schematic depiction of an experimental setup for the collection of time-resolved X-ray diffraction data. Crystals

are delivered in a serial fashion using a GDVN injector. Triggering of the reaction is achieved by a laser illumination of the

crystal at a specified location upstream of the X-ray focal spot to achieve the desired time delay. Adapted with permission

from Aquila et al., Opt. Express. 20(3), 2706–2716 (2012). Copyright 2012 Optical Society of America.20

032202-18 S. Sui and S. L. Perry Struct. Dyn. 4, 032202 (2017)

used in these studies is expected to enable the study of kinetics as fast as 500 ls,29 significantly

smaller crystals and a commensurate decrease in the jet diameter would be needed to maintain

signal-to-noise quality.

A similar approach could be applied to the other injector architectures. However, for the

high viscosity jets, diffusion through the highly viscous matrix material is expected to limit the

range of accessible timescales to only very slow reactions. Similarly, the relatively large droplet

size for on-demand droplet injectors may represent significant limitations in terms of the small-

est possible crystals that can be analyzed and the timescales for chemical triggering. However,

the potential exists to probe faster enzyme kinetics if fast mixing strategies can be coupled with

electrokinetic or aerosol injectors that are compatible with nanocrystals.

To date, there have been no reports of fixed-target strategies for chemical triggering. The

use of individually addressable sample locations within an integrated microfluidic platform has

the potential to enable extremely precise and potentially automated control.18,19,123

Unfortunately, there are currently no reports of microfluidic integration within the types of

ultra-thin devices that would be necessary for the study of typical enzyme kinetics. Thus, it is

difficult to estimate the potential rate of data collection using such a platform.

VI. SUMMARY AND OUTLOOK

We have discussed the impact and potential of microfluidic technologies related to protein

structure determination. The small scale of these devices, coupled with exquisite control over

flow patterns and local concentrations, has been instrumental in the development of technolo-

gies for both protein crystallization and serial crystallography. Looking forward, the push to

enable structure determination on even more challenging targets will require additional innova-

tion regarding the design and fabrication of such devices. In particular, new strategies are

needed to enable the use of chemical reaction initiation for time-resolved experiments in fixed-

target devices, while ultra-thin materials such as silicon nitride membranes and large-area gra-

phene sheets are critical to enable the analysis of ever smaller and more weakly diffracting

targets. Strategies that couple in situ crystallization and analysis may also prove to be critical

for targets where either physical handling and/or environmental exposure are a challenge. It is

also exciting to consider the potential application of these materials in related experiments cou-

pled to protein structural dynamics, including X-ray scattering and continuous diffusion/diffuse

scattering, where the signal-to-noise and low background are critical.

To date, the majority of serial crystallography efforts have been directed towards XFEL

sources because of the requirements of such “diffraction before destruction” experiments.

However, there are growing efforts to extend these types of data collection strategies to syn-

chrotron sources. Beyond static structure determination, the even more intense, microfocused

third generation synchrotron sources also have the potential to enable time-resolved experiments

using both monochromatic and polychromatic Laue diffraction strategies over timescales

TABLE III. Diffusion times sD for various crystal sizes from the calculation, simulation, and experiment. Adapted with

permission from Schmidt, Adv. Condens. Matter Phys. 5, 167276 (2013). Copyright 2013 Marius Schmidt.218

Crystal size sDa

300� 400� 500 lm3 9.5 s

10� 20� 30 lm3 15 ms

3� 4� 5 lm3 1 msb1� 2� 3 lm3 150 ls

0.5� 0.5� 0.5 lm3 17 ls

0.1� 0.2� 0.3 lm3 1.5 ls

aBased on the diffusivity of a typical substrate, such as glucose (5 � 10�6 cm2/s) assuming no barriers to diffusion within

the crystal lattice. Tortuosity and/or hindered diffusion may result in increased diffusion times. Variations in diffusivity

scale inversely with the effective radius and/or molecular weight of the molecule.bWith much smaller crystals, mixing times might be slower than diffusion times.

032202-19 S. Sui and S. L. Perry Struct. Dyn. 4, 032202 (2017)

ranging from the sub-nanosecond-scale and longer. Technological and software developments

in the field are rapidly advancing to the point where the automated collection of dynamic struc-

tural information has the potential to become as accessible as cryocrystallographic structure

determination is today.

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