Sequence, structure prediction, and epitope analysis of the polymorphic membrane protein family in Chlamydia trachomatis.

The polymorphic membrane proteins (Pmps) are a family of autotransporters that play an important role in infection, adhesion and immunity in Chlamydia trachomatis. Here we show that the characteristic GGA(I,L,V) and FxxN tetrapeptide repeats fit into a larger repeat sequence, which correspond to the coils of a large beta-helical domain in high quality structure predictions. Analysis of the protein using structure prediction algorithms provided novel insight to the chlamydial Pmp family of proteins. While the tetrapeptide motifs themselves are predicted to play a structural role in folding and close stacking of the beta-helical backbone of the passenger domain, we found many of the interesting features of Pmps are localized to the side loops jutting out from the beta helix including protease cleavage, host cell adhesion, and B-cell epitopes; while T-cell epitopes are predominantly found in the beta-helix itself. This analysis more accurately defines the Pmp family of Chlamydia and may better inform rational vaccine design and functional studies.

Computationally restoring the potency of a clinical antibody against Omicron.

The COVID-19 pandemic underscored the promise of monoclonal antibody-based prophylactic and therapeutic drugs1-3 and revealed how quickly viral escape can curtail effective options4,5. When the SARS-CoV-2 Omicron variant emerged in 2021, many antibody drug products lost potency, including Evusheld and its constituent, cilgavimab4-6. Cilgavimab, like its progenitor COV2-2130, is a class 3 antibody that is compatible with other antibodies in combination4 and is challenging to replace with existing approaches. Rapidly modifying such high-value antibodies to restore efficacy against emerging variants is a compelling mitigation strategy. We sought to redesign and renew the efficacy of COV2-2130 against Omicron BA.1 and BA.1.1 strains while maintaining efficacy against the dominant Delta variant. Here we show that our computationally redesigned antibody, 2130-1-0114-112, achieves this objective, simultaneously increases neutralization potency against Delta and subsequent variants of concern, and provides protection in vivo against the strains tested: WA1/2020, BA.1.1 and BA.5. Deep mutational scanning of tens of thousands of pseudovirus variants reveals that 2130-1-0114-112 improves broad potency without increasing escape liabilities. Our results suggest that computational approaches can optimize an antibody to target multiple escape variants, while simultaneously enriching potency. Our computational approach does not require experimental iterations or pre-existing binding data, thus enabling rapid response strategies to address escape variants or lessen escape vulnerabilities.

Differential laboratory passaging of SARS-CoV-2 viral stocks impacts the in vitro assessment of neutralizing antibodies.

Viral populations in natural infections can have a high degree of sequence diversity, which can directly impact immune escape. However, antibody potency is often tested in vitro with a relatively clonal viral populations, such as laboratory virus or pseudotyped virus stocks, which may not accurately represent the genetic diversity of circulating viral genotypes. This can affect the validity of viral phenotype assays, such as antibody neutralization assays. To address this issue, we tested whether recombinant virus carrying SARS-CoV-2 spike (VSV-SARS-CoV-2-S) stocks could be made more genetically diverse by passage, and if a stock passaged under selective pressure was more capable of escaping monoclonal antibody (mAb) neutralization than unpassaged stock or than viral stock passaged without selective pressures. We passaged VSV-SARS-CoV-2-S four times concurrently in three cell lines and then six times with or without polyclonal antiserum selection pressure. All three of the monoclonal antibodies tested neutralized the viral population present in the unpassaged stock. The viral inoculum derived from serial passage without antiserum selection pressure was neutralized by two of the three mAbs. However, the viral inoculum derived from serial passage under antiserum selection pressure escaped neutralization by all three mAbs. Deep sequencing revealed the rapid acquisition of multiple mutations associated with antibody escape in the VSV-SARS-CoV-2-S that had been passaged in the presence of antiserum, including key mutations present in currently circulating Omicron subvariants. These data indicate that viral stock that was generated under polyclonal antiserum selection pressure better reflects the natural environment of the circulating virus and may yield more biologically relevant outcomes in phenotypic assays. Thus, mAb assessment assays that utilize a more genetically diverse, biologically relevant, virus stock may yield data that are relevant for prediction of mAb efficacy and for enhancing biosurveillance.

Computationally restoring the potency of a clinical antibody against SARS-CoV-2 Omicron subvariants.

The COVID-19 pandemic underscored the promise of monoclonal antibody-based prophylactic and therapeutic drugs1-3, but also revealed how quickly viral escape can curtail effective options4,5. With the emergence of the SARS-CoV-2 Omicron variant in late 2021, many clinically used antibody drug products lost potency, including Evusheld™ and its constituent, cilgavimab4,6. Cilgavimab, like its progenitor COV2-2130, is a class 3 antibody that is compatible with other antibodies in combination4 and is challenging to replace with existing approaches. Rapidly modifying such high-value antibodies with a known clinical profile to restore efficacy against emerging variants is a compelling mitigation strategy. We sought to redesign COV2-2130 to rescue in vivo efficacy against Omicron BA.1 and BA.1.1 strains while maintaining efficacy against the contemporaneously dominant Delta variant. Here we show that our computationally redesigned antibody, 2130-1-0114-112, achieves this objective, simultaneously increases neutralization potency against Delta and many variants of concern that subsequently emerged, and provides protection in vivo against the strains tested, WA1/2020, BA.1.1, and BA.5. Deep mutational scanning of tens of thousands pseudovirus variants reveals 2130-1-0114-112 improves broad potency without incurring additional escape liabilities. Our results suggest that computational approaches can optimize an antibody to target multiple escape variants, while simultaneously enriching potency. Because our approach is computationally driven, not requiring experimental iterations or pre-existing binding data, it could enable rapid response strategies to address escape variants or pre-emptively mitigate escape vulnerabilities.

Tailored approach to study Legionella infection using a lattice light sheet microscope (LLSM).

Legionella is a genus of ubiquitous environmental pathogens found in freshwater systems, moist soil, and composted materials. More than four decades of Legionella research has provided important insights into Legionella pathogenesis. Although standard commercial microscopes have led to significant advances in understanding Legionella pathogenesis, great potential exists in the deployment of more advanced imaging techniques to provide additional insights. The lattice light sheet microscope (LLSM) is a recently developed microscope for 4D live cell imaging with high resolution and minimum photo-damage. We built a LLSM with an improved version for the optical layout with two path-stretching mirror sets and a novel reconfigurable galvanometer scanner (RGS) module to improve the reproducibility and reliability of the alignment and maintenance of the LLSM. We commissioned this LLSM to study Legionella pneumophila infection with a tailored workflow designed over instrumentation, experiments, and data processing methods. Our results indicate that Legionella pneumophila infection is correlated with a series of morphological signatures such as smoothness, migration pattern and polarity both statistically and dynamically. Our work demonstrates the benefits of using LLSM for studying long-term questions in bacterial infection. Our free-for-use modifications and workflow designs on the use of LLSM system contributes to the adoption and promotion of the state-of-the-art LLSM technology for both academic and commercial applications.

Large-scale application of free energy perturbation calculations for antibody design.

Alchemical free energy perturbation (FEP) is a rigorous and powerful technique to calculate the free energy difference between distinct chemical systems. Here we report our implementation of automated large-scale FEP calculations, using the Amber software package, to facilitate antibody design and evaluation. In combination with Hamiltonian replica exchange, our FEP simulations aim to predict the effect of mutations on both the binding affinity and the structural stability. Importantly, we incorporate multiple strategies to faithfully estimate the statistical uncertainties in the FEP results. As a case study, we apply our protocols to systematically evaluate variants of the m396 antibody for their conformational stability and their binding affinity to the spike proteins of SARS-CoV-1 and SARS-CoV-2. By properly adjusting relevant parameters, the particle collapse problems in the FEP simulations are avoided. Furthermore, large statistical errors in a small fraction of the FEP calculations are effectively reduced by extending the sampling, such that acceptable statistical uncertainties are achieved for the vast majority of the cases with a modest total computational cost. Finally, our predicted conformational stability for the m396 variants is qualitatively consistent with the experimentally measured melting temperatures. Our work thus demonstrates the applicability of FEP in computational antibody design.

Functional Annotation from Structural Homology.

With the nexus of super computing and the biotech revolution, it seems an era of predictive biology through systems biology may be at hand. Modern omics capabilities enable examination of the state of biological system in exquisite detail. The genome, transcriptome, proteome, and metabolome may all be largely knowable, at least for some model systems, providing a basis for modeling and simulation of molecular mechanisms, or pathways, that could capture a biological system's emergent properties. However, there are significant challenges remaining that impede the realization of this vision, perhaps the most significant being the missing functional annotation of genes and gene products. For even the most well-studied organisms as much as a third of called genes for a given genome are not annotated and more than half may be tenuous. Homology inferred from sequence similarity is the basis for much of genome annotation. Homology inferred from structural similarity could be a powerful complement to sequence-based annotation methods. Structural biology or structural informatics can be used to assign molecular function and may have increasing utility with the rapid growth of gene sequence databases and emerging methods for structure determination, like structure prediction based on coevolution. Here we describe tools and provide example cases using structural similarity at the level of quaternary structure, domain content, domain topology, and small 3D motifs to infer homology and posit function. Ultimately annotation by similarity, be it 3D structure homology or more classically primary sequence homology, must be founded by accurate annotation of one ortholog in the group-understanding every function encoded by a genome remains a major challenge to life science.

Shotgun Immunoproteomic Approach for the Discovery of Linear B-Cell Epitopes in Biothreat Agents Francisella tularensis and Burkholderia pseudomallei.

Peptide-based subunit vaccines are coming to the forefront of current vaccine approaches, with safety and cost-effective production among their top advantages. Peptide vaccine formulations consist of multiple synthetic linear epitopes that together trigger desired immune responses that can result in robust immune memory. The advantages of linear compared to conformational epitopes are their simple structure, ease of synthesis, and ability to stimulate immune responses by means that do not require complex 3D conformation. Prediction of linear epitopes through use of computational tools is fast and cost-effective, but typically of low accuracy, necessitating extensive experimentation to verify results. On the other hand, identification of linear epitopes through experimental screening has been an inefficient process that requires thorough characterization of previously identified full-length protein antigens, or laborious techniques involving genetic manipulation of organisms. In this study, we apply a newly developed generalizable screening method that enables efficient identification of B-cell epitopes in the proteomes of pathogenic bacteria. As a test case, we used this method to identify epitopes in the proteome of Francisella tularensis (Ft), a Select Agent with a well-characterized immunoproteome. Our screen identified many peptides that map to known antigens, including verified and predicted outer membrane proteins and extracellular proteins, validating the utility of this approach. We then used the method to identify seroreactive peptides in the less characterized immunoproteome of Select Agent Burkholderia pseudomallei (Bp). This screen revealed known Bp antigens as well as proteins that have not been previously identified as antigens. Although B-cell epitope prediction tools Bepipred 2.0 and iBCE-EL classified many of our seroreactive peptides as epitopes, they did not score them significantly higher than the non-reactive tryptic peptides in our study, nor did they assign higher scores to seroreactive peptides from known Ft or Bp antigens, highlighting the need for experimental data instead of relying on computational epitope predictions alone. The present workflow is easily adaptable to detecting peptide targets relevant to the immune systems of other mammalian species, including humans (depending upon the availability of convalescent sera from patients), and could aid in accelerating the discovery of B-cell epitopes and development of vaccines to counter emerging biological threats.

Proteomic Profiling of Burkholderia thailandensis During Host Infection Using Bio-Orthogonal Noncanonical Amino Acid Tagging (BONCAT).

Burkholderia pseudomallei and B. mallei are the causative agents of melioidosis and glanders, respectively, and are often fatal to humans and animals. Owing to the high fatality rate, potential for spread by aerosolization, and the lack of efficacious therapeutics, B. pseudomallei and B. mallei are considered biothreat agents of concern. In this study, we investigate the proteome of Burkholderia thailandensis, a closely related surrogate for the two more virulent Burkholderia species, during infection of host cells, and compare to that of B. thailandensis in culture. Studying the proteome of Burkholderia spp. during infection is expected to reveal molecular mechanisms of intracellular survival and host immune evasion; but proteomic profiling of Burkholderia during host infection is challenging. Proteomic analyses of host-associated bacteria are typically hindered by the overwhelming host protein content recovered from infected cultures. To address this problem, we have applied bio-orthogonal noncanonical amino acid tagging (BONCAT) to B. thailandensis, enabling the enrichment of newly expressed bacterial proteins from virtually any growth condition, including host cell infection. In this study, we show that B. thailandensis proteins were selectively labeled and efficiently enriched from infected host cells using BONCAT. We also demonstrate that this method can be used to label bacteria in situ by fluorescent tagging. Finally, we present a global proteomic profile of B. thailandensis as it infects host cells and a list of proteins that are differentially regulated in infection conditions as compared to bacterial monoculture. Among the identified proteins are quorum sensing regulated genes as well as homologs to previously identified virulence factors. This method provides a powerful tool to study the molecular processes during Burkholderia infection, a much-needed addition to the Burkholderia molecular toolbox.

Structure and function of REP34 implicates carboxypeptidase activity in Francisella tularensis host cell invasion.

Francisella tularensis is the etiological agent of tularemia, or rabbit fever. Although F. tularensis is a recognized biothreat agent with broad and expanding geographical range, its mechanism of infection and environmental persistence remain poorly understood. Previously, we identified seven F. tularensis proteins that induce a rapid encystment phenotype (REP) in the free-living amoeba, Acanthamoeba castellanii. Encystment is essential to the pathogen's long term intracellular survival in the amoeba. Here, we characterize the cellular and molecular function of REP34, a REP protein with a mass of 34 kDa. A REP34 knock-out strain of F. tularensis has a reduced ability to both induce encystment in A. castellanii and invade human macrophages. We determined the crystal structure of REP34 to 2.05-Å resolution and demonstrate robust carboxypeptidase B-like activity for the enzyme. REP34 is a zinc-containing monomeric protein with close structural homology to the metallocarboxypeptidase family of peptidases. REP34 possesses a novel topology and substrate binding pocket that deviates from the canonical funnelin structure of carboxypeptidases, putatively resulting in a catalytic role for a conserved tyrosine and distinct S1' recognition site. Taken together, these results identify REP34 as an active carboxypeptidase, implicate the enzyme as a potential key F. tularensis effector protein, and may help elucidate a mechanistic understanding of F. tularensis infection of phagocytic cells.

Practical applications of structural genomics technologies for mutagen research.

Here we present a perspective on a range of practical uses of structural genomics for mutagen research. Structural genomics is an overloaded term and requires some definition to bound the discussion; we give a brief description of public and private structural genomics endeavors, along with some of their objectives, their activities, their capabilities, and their limitations. We discuss how structural genomics might impact mutagen research in three different scenarios: at a structural genomics center, at a lab with modest resources that also conducts structural biology research, and at a lab that is conducting mutagen research without in-house experimental structural biology. Applications span functional annotation of single genes or SNP, to constructing gene networks and pathways, to an integrated systems biology approach. Structural genomics centers can take advantage of systems biology models to target high value targets for structure determination and in turn extend systems models to better understand systems biology diseases or phenomenon. Individual investigator run structural biology laboratories can collaborate with structural genomics centers, but can also take advantage of technical advances and tools developed by structural genomics centers and can employ a structural genomics approach to advancing biological understanding. Individual investigator-run non-structural biology laboratories can also collaborate with structural genomics centers, possibly influencing targeting decisions, but can also use structure based annotation tools enabled by the growing coverage of protein fold space provided by structural genomics. Better functional annotation can inform pathway and systems biology models.

Isolation, characterization, and stability of discretely-sized nanolipoprotein particles assembled with apolipophorin-III.

BACKGROUND: Nanolipoprotein particles (NLPs) are discoidal, nanometer-sized particles comprised of self-assembled phospholipid membranes and apolipoproteins. NLPs assembled with human apolipoproteins have been used for myriad biotechnology applications, including membrane protein solubilization, drug delivery, and diagnostic imaging. To expand the repertoire of lipoproteins for these applications, insect apolipophorin-III (apoLp-III) was evaluated for the ability to form discretely-sized, homogeneous, and stable NLPs. METHODOLOGY: Four NLP populations distinct with regards to particle diameters (ranging in size from 10 nm to >25 nm) and lipid-to-apoLp-III ratios were readily isolated to high purity by size exclusion chromatography. Remodeling of the purified NLP species over time at 4 degrees C was monitored by native gel electrophoresis, size exclusion chromatography, and atomic force microscopy. Purified 20 nm NLPs displayed no remodeling and remained stable for over 1 year. Purified NLPs with 10 nm and 15 nm diameters ultimately remodeled into 20 nm NLPs over a period of months. Intra-particle chemical cross-linking of apoLp-III stabilized NLPs of all sizes. CONCLUSIONS: ApoLp-III-based NLPs can be readily prepared, purified, characterized, and stabilized, suggesting their utility for biotechnological applications.

Structure of Rv1848 (UreA), the Mycobacterium tuberculosis urease gamma subunit.

The crystal structure of the urease gamma subunit (UreA) from Mycobacterium tuberculosis, Rv1848, has been determined at 1.8 A resolution. The asymmetric unit contains three copies of Rv1848 arranged into a homotrimer that is similar to the UreA trimer in the structure of urease from Klebsiella aerogenes. Small-angle X-ray scattering experiments indicate that the Rv1848 protein also forms trimers in solution. The observed homotrimer and the organization of urease genes within the M. tuberculosis genome suggest that M. tuberculosis urease has the (alphabetagamma)(3) composition observed for other bacterial ureases. The gamma subunit may be of primary importance for the formation of the urease quaternary structure.

Amino acid and structural variability of Yersinia pestis LcrV protein.

The LcrV protein is a multifunctional virulence factor and protective antigen of the plague bacterium and is generally conserved between the epidemic strains of Yersinia pestis. We investigated the diversity in the LcrV sequences among non-epidemic Y. pestis strains which have a limited virulence in selected animal models and for humans. Sequencing of lcrV genes from 19 Y. pestis strains belonging to different phylogenetic groups (subspecies) showed that the LcrV proteins possess four major variable hotspots at positions 18, 72, 273, and 324-326. These major variations, together with other minor substitutions in amino acid sequences, allowed us to classify the LcrV alleles into five sequence types (A-E). We observed that the strains of different Y. pestis "subspecies" can have the same type of LcrV, including that conserved in epidemic strains, and different types of LcrV can exist within the same natural plague focus. Therefore, the phenomenon of "selective virulence" characteristic of the strains of the microtus biovar is unlikely to be the result of polymorphism of the V antigen. The LcrV polymorphisms were structurally analyzed by comparing the modeled structures of LcrV from all available strains. All changes except one occurred either in flexible regions or on the surface of the protein, but local chemical properties (i.e. those of a hydrophobic, hydrophilic, amphipathic, or charged nature) were conserved across all of the strains. Polymorphisms in flexible and surface regions are likely subject to less selective pressure, and have a limited impact on the structure. In contrast, the substitution of tryptophan at position 113 with either glutamic acid or glycine likely has a serious influence on the regional structure of the protein, and these mutations might have an effect on the function of LcrV. The polymorphisms at positions 18, 72 and 273 were accountable for differences in the oligomerization of LcrV.

Characterization and purification of polydisperse reconstituted lipoproteins and nanolipoprotein particles.

Heterogeneity is a fact that plagues the characterization and application of many self-assembled biological constructs. The importance of obtaining particle homogeneity in biological assemblies is a critical goal, as bulk analysis tools often require identical species for reliable interpretation of the results-indeed, important tools of analysis such as x-ray diffraction typically require over 90% purity for effectiveness. This issue bears particular importance in the case of lipoproteins. Lipid-binding proteins known as apolipoproteins can self assemble with liposomes to form reconstituted high density lipoproteins (rHDLs) or nanolipoprotein particles (NLPs) when used for biotechnology applications such as the solubilization of membrane proteins. Typically, the apolipoprotein and phospholipids reactants are self assembled and even with careful assembly protocols the product often contains heterogeneous particles. In fact, size polydispersity in rHDLs and NLPs published in the literature are frequently observed, which may confound the accurate use of analytical methods. In this article, we demonstrate a procedure for producing a pure, monodisperse NLP subpopulation from a polydisperse self-assembly using size exclusion chromatography (SEC) coupled with high resolution particle imaging by atomic force microscopy (AFM). In addition, NLPs have been shown to self assemble both in the presence and absence of detergents such as cholate, yet the effects of cholate on NLP polydispersity and separation has not been systematically examined. Therefore, we examined the separation properties of NLPs assembled in both the absence and presence of cholate using SEC and native gel electrophoresis. From this analysis, NLPs prepared with and without cholate showed particles with well defined diameters spanning a similar size range. However, cholate was shown to have a dramatic affect on NLP separation by SEC and native gel electrophoresis. Furthermore, under conditions where different sized NLPs were not sufficiently separated or purified by SEC, AFM was used to deconvolute the elution pattern of different sized NLPs. From this analysis we were able to purify an NLP subpopulation to 90% size homogeneity by taking extremely fine elutions from the SEC. With this purity, we generate high quality NLP crystals that were over 100 microm in size with little precipitate, which could not be obtained utilizing the traditional size exclusion techniques. This purification procedure and the methods for validation are broadly applicable to other lipoprotein particles.

Immobilization of His-tagged proteins on nickel-chelating nanolipoprotein particles.

Nanolipoprotein particles (NLPs) are nanometer-sized, discoidal particles that self-assemble from purified apolipoprotein and phospholipid. Their size and facile functionalization suggest potential application of NLPs as platforms for the presentation and delivery of recombinant proteins. To this end, we investigated incorporation of nickel-chelating lipids into NLPs (NiNLPs) and subsequent sequestration of polyhistidine (His)-tagged proteins. From initial lipid screens for NLP formation, the two phospholipids DMPC and DOPC were identified as suitable bulk lipids for incorporation of the nickel-chelating lipid DOGS-NTA-Ni into NLPs, and NiNLPs were successfully formed with varying amounts of DOGS-NTA-Ni. NiNLPs consisting of 10% DOGS-NTA-Ni with 90% bulk lipid (either DMPC or DOPC) were thoroughly characterized by size exclusion chromatography (SEC), non-denaturing gradient gel electrophoresis (NDGGE), and atomic force microscopy (AFM). Three different His-tagged proteins were sequestered on NiNLPs in a nickel-dependent manner, and the amount of immobilized protein was contingent on the size and composition of the NiNLP.

Cell-free expression for nanolipoprotein particles: building a high-throughput membrane protein solubility platform.

Membrane-associated proteins and protein complexes account for approximately a third or more of the proteins in the cell (1, 2). These complexes mediate essential cellular processes; including signal transduc-tion, transport, recognition, bioenergetics and cell-cell communication. In general, membrane proteins are challenging to study because of their insolubility and tendency to aggregate when removed from their protein lipid bilayer environment. This chapter is focused on describing a novel method for producing and solubilizing membrane proteins that can be easily adapted to high-throughput expression screening. This process is based on cell-free transcription and translation technology coupled with nanolipoprotein par ticles (NLPs), which are lipid bilayers confined within a ring of amphipathic protein of defined diameter. The NLPs act as a platform for inserting, solubilizing and characterizing functional membrane proteins. NLP component proteins (apolipoproteins), as well as membrane proteins can be produced by either traditional cell-based or as discussed here, cell-free expression methodologies.

Atomic force microscopy differentiates discrete size distributions between membrane protein containing and empty nanolipoprotein particles.

To better understand the incorporation of membrane proteins into discoidal nanolipoprotein particles (NLPs) we have used atomic force microscopy (AFM) to image and analyze NLPs assembled in the presence of bacteriorhodopsin (bR), lipoprotein E4 n-terminal 22k fragment scaffold and DMPC lipid. The self-assembly process produced two distinct NLP populations: those containing inserted bR (bR-NLPs) and those that did not (empty-NLPs). The bR-NLPs were distinguishable from empty-NLPs by an average increase in height of 1.0 nm as measured by AFM. Streptavidin binding to biotinylated bR confirmed that the original 1.0 nm height increase corresponds to br-NLP incorporation. AFM and ion mobility spectrometry (IMS) measurements suggest that NLP size did not vary around a single mean but instead there were several subpopulations, which were separated by discrete diameters. Interestingly, when bR was present during assembly the diameter distribution was shifted to larger particles and the larger particles had a greater likelihood of containing bR than smaller particles, suggesting that membrane proteins alter the mechanism of NLP assembly.

Cell-free co-expression of functional membrane proteins and apolipoprotein, forming soluble nanolipoprotein particles.

Here we demonstrate rapid production of solubilized and functional membrane protein by simultaneous cell-free expression of an apolipoprotein and a membrane protein in the presence of lipids, leading to the self-assembly of membrane protein-containing nanolipoprotein particles (NLPs). NLPs have shown great promise as a biotechnology platform for solubilizing and characterizing membrane proteins. However, current approaches are limited because they require extensive efforts to express, purify, and solubilize the membrane protein prior to insertion into NLPs. By the simple addition of a few constituents to cell-free extracts, we can produce membrane proteins in NLPs with considerably less effort. For this approach an integral membrane protein and an apolipoprotein scaffold are encoded by two DNA plasmids introduced into cell-free extracts along with lipids. For this study reported here we used plasmids encoding the bacteriorhodopsin (bR) membrane apoprotein and scaffold protein Delta1-49 apolipoprotein A-I fragment (Delta49A1). Cell free co-expression of the proteins encoded by these plasmids, in the presence of the cofactor all-trans-retinal and dimyristoylphosphatidylcholine, resulted in production of functional bR as demonstrated by a 5-nm shift in the absorption spectra upon light adaptation and characteristic time-resolved FT infrared difference spectra for the bR --> M transition. Importantly the functional bR was solubilized in discoidal bR.NLPs as determined by atomic force microscopy. A survey study of other membrane proteins co-expressed with Delta49A1 scaffold protein also showed significantly increased solubility of all of the membrane proteins, indicating that this approach may provide a general method for expressing membrane proteins enabling further studies.

Efficient macromolecular crystallization using microfluidics and randomized design of screening reagents.

Microfluidic technologies enable a relatively new approach to macromolecular crystallization, but offer several significant advantages over more traditional techniques. Microfluidic devices provide significant savings in the amount of material required to complete a set of experiments, although recent innovations with vapor diffusion and microbatch methods have also greatly reduced their material requirements. When compared with these other methods, microfluidic approaches still consume 5-100x less material. In addition, comparisons in one set of experiments suggest that microfluidic free-interface diffusion may also offer substantially higher success rates than sitting drop vapor diffusion. Microfluidic methods also provide opportunities for experimental strategies involving testing multiple samples in parallel. When combined with randomized design of screening reagents, microfluidic devices provide a highly efficient method for sampling crystallization space. Commercial microfluidic crystallization chips have been in circulation for a number of years now and stable protocols for their use, tips and tricks, and data on their success and failure are now available.