Engineering a human P2X2 receptor with altered ligand selectivity in yeast

P2X receptors are a family of ligand gated ion channels found in a range of eukaryotic species including humans but are not naturally present in the yeast Saccharomyces cerevisiae. We demonstrate the first recombinant expression and functional gating of the P2X2 receptor in baker's yeast. We leverage the yeast host for facile genetic screens of mutant P2X2 by performing site saturation mutagenesis at residues of interest, including SNPs implicated in deafness and at residues involved in native binding. Deep mutational analysis and rounds of genetic engineering yield mutant P2X2 F303Y A304W, which has altered ligand selectivity toward the ATP analog AMP-PNP. The F303Y A304W variant shows over 100-fold increased intracellular calcium amplitudes with AMP-PNP compared to the WT receptor and has a much lower desensitization rate. Since AMP-PNP does not naturally activate P2X receptors, the F303Y A304W P2X2 may be a starting point for downstream applications in chemogenetic cellular control. Interestingly, the A304W mutation selectively destabilizes the desensitized state, which may provide a mechanistic basis for receptor opening with suboptimal agonists. The yeast system represents an inexpensive, scalable platform for ion channel characterization and engineering by circumventing the more expensive and time-consuming methodologies involving mammalian hosts.

Systematic profiling of ale yeast protein dynamics across fermentation and repitching

Studying the genetic and molecular characteristics of brewing yeast strains is crucial for understanding their domestication history and adaptations accumulated over time in fermentation environments, and for guiding optimizations to the brewing process itself. Saccharomyces cerevisiae (brewing yeast) is among the most profiled organisms on the planet, yet the temporal molecular changes that underlie industrial fermentation and beer brewing remain understudied. Here, we characterized the genomic makeup of a Saccharomyces cerevisiae ale yeast widely used in the production of Hefeweizen beers, and applied shotgun mass spectrometry to systematically measure the proteomic changes throughout 2 fermentation cycles which were separated by 14 rounds of serial repitching. The resulting brewing yeast proteomics resource includes 64,740 protein abundance measurements. We found that this strain possesses typical genetic characteristics of Saccharomyces cerevisiae ale strains and displayed progressive shifts in molecular processes during fermentation based on protein abundance changes. We observed protein abundance differences between early fermentation batches compared to those separated by 14 rounds of serial repitching. The observed abundance differences occurred mainly in proteins involved in the metabolism of ergosterol and isobutyraldehyde. Our systematic profiling serves as a starting point for deeper characterization of how the yeast proteome changes during commercial fermentations and additionally serves as a resource to guide fermentation protocols, strain handling, and engineering practices in commercial brewing and fermentation environments. Finally, we created a web interface (https://brewing-yeast-proteomics.ccbb.utexas.edu/) to serve as a valuable resource for yeast geneticists, brewers, and biochemists to provide insights into the global trends underlying commercial beer production.

SARS-COV-2 Omicron variants conformationally escape a rare quaternary antibody binding mode

The ongoing evolution of SARS-CoV-2 into more easily transmissible and infectious variants has provided unprecedented insight into mutations enabling immune escape. Understanding how these mutations affect the dynamics of antibody-antigen interactions is crucial to the development of broadly protective antibodies and vaccines. Here we report the characterization of a potent neutralizing antibody (N3-1) identified from a COVID-19 patient during the first disease wave. Cryogenic electron microscopy revealed a quaternary binding mode that enables direct interactions with all three receptor-binding domains of the spike protein trimer, resulting in extraordinary avidity and potent neutralization of all major variants of concern until the emergence of Omicron. Structure-based rational design of N3-1 mutants improved binding to all Omicron variants but only partially restored neutralization of the conformationally distinct Omicron BA.1. This study provides new insights into immune evasion through changes in spike protein dynamics and highlights considerations for future conformationally biased multivalent vaccine designs.

Systematic Profiling of Ale Yeast Protein Dynamics across Fermentation and Repitching

Studying the genetic and molecular characteristics of brewing yeast strains is crucial for understanding their domestication history and adaptations accumulated over time in fermentation environments, and for guiding optimizations to the brewing process itself. Saccharomyces cerevisiae (brewing yeast) is amongst the most profiled organisms on the planet, yet the temporal molecular changes that underlie industrial fermentation and beer brewing remain understudied. Here, we characterized the genomic makeup of a Saccharomyces cerevisiae ale yeast widely used in the production of Hefeweizen beers, and applied shotgun mass spectrometry to systematically measure the proteomic changes throughout two fermentation cycles which were separated by 14 rounds of serial repitching. The resulting brewing yeast proteomics resource includes 64,740 protein abundance measurements. We found that this strain possesses typical genetic characteristics of Saccharomyces cerevisiae ale strains and displayed progressive shifts in molecular processes during fermentation based on protein abundance changes. We observed protein abundance differences between early fermentation batches compared to those separated by 14 rounds of serial repitching. The observed abundance differences occurred mainly in proteins involved in the metabolism of ergosterol and isobutyraldehyde. Our systematic profiling serves as a starting point for deeper characterization of how the yeast proteome changes during commercial fermentations and additionally serves as a resource to guide fermentation protocols, strain handling, and engineering practices in commercial brewing and fermentation environments. Finally, we created a web interface (https://brewing-yeast-proteomics.ccbb.utexas.edu/) to serve as a valuable resource for yeast geneticists, brewers, and biochemists to provide insights into the global trends underlying commercial beer production.

Rapid, scalable, combinatorial genome engineering by marker-less enrichment and recombination of genetically engineered loci in yeast

A major challenge to rationally building multi-gene processes in yeast arises due to the combinatorics of combining all of the individual edits into the same strain. Here, we present a precise and multi-site genome editing approach that combines all edits without selection markers using CRISPR-Cas9. We demonstrate a highly efficient gene drive that selectively eliminates specific loci by integrating CRISPR-Cas9-mediated double-strand break (DSB) generation and homology-directed recombination with yeast sexual assortment. The method enables marker-less enrichment and recombination of genetically engineered loci (MERGE). We show that MERGE converts single heterologous loci to homozygous loci at ∼100% efficiency, independent of chromosomal location. Furthermore, MERGE is equally efficient at converting and combining multiple loci, thus identifying compatible genotypes. Finally, we establish MERGE proficiency by engineering a fungal carotenoid biosynthesis pathway and most of the human α-proteasome core into yeast. Therefore, MERGE lays the foundation for scalable, combinatorial genome editing in yeast.

Antibody escape and cryptic cross-domain stabilization in the SARS-CoV-2 Omicron spike protein

The worldwide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the repeated emergence of variants of concern. For the Omicron variant, sub-lineages BA.1 and BA.2, respectively, contain 33 and 29 nonsynonymous and indel spike protein mutations. These amino acid substitutions and indels are implicated in increased transmissibility and enhanced immune evasion. By reverting individual spike mutations of BA.1 or BA.2, we characterize the molecular effects of the Omicron spike mutations on expression, ACE2 receptor affinity, and neutralizing antibody recognition. We identified key mutations enabling escape from neutralizing antibodies at a variety of epitopes. Stabilizing mutations in the N-terminal and S2 domains of the spike protein can compensate for destabilizing mutations in the receptor binding domain, enabling the record number of mutations in Omicron. Our results provide a comprehensive account of the mutational effects in the Omicron spike protein and illustrate previously uncharacterized mechanisms of host evasion.

Functional expression of opioid receptors and other human GPCRs in yeast engineered to produce human sterols

The yeast Saccharomyces cerevisiae is powerful for studying human G protein-coupled receptors as they can be coupled to its mating pathway. However, some receptors, including the mu opioid receptor, are non-functional, which may be due to the presence of the fungal sterol ergosterol instead of cholesterol. Here we engineer yeast to produce cholesterol and introduce diverse mu, delta, and kappa opioid receptors to create sensitive opioid biosensors that recapitulate agonist binding profiles and antagonist inhibition. Additionally, human mu opioid receptor variants, including those with clinical relevance, largely display expected phenotypes. By testing mu opioid receptor-based biosensors with systematically adjusted cholesterol biosynthetic intermediates, we relate sterol profiles to biosensor sensitivity. Finally, we apply sterol-modified backgrounds to other human receptors revealing sterol influence in SSTR5, 5-HTR4, FPR1, and NPY1R signaling. This work provides a platform for generating human G protein-coupled receptor-based biosensors, facilitating receptor deorphanization and high-throughput screening of receptors and effectors.

Rapid characterization of spike variants via mammalian cell surface display

The SARS-CoV-2 spike protein is a critical component of vaccines and a target for neutralizing monoclonal antibodies (nAbs). Spike is also undergoing immunogenic selection with variants that increase infectivity and partially escape convalescent plasma. Here, we describe Spike Display, a high-throughput platform to rapidly characterize glycosylated spike ectodomains across multiple coronavirus-family proteins. We assayed ∼200 variant SARS-CoV-2 spikes for their expression, ACE2 binding, and recognition by 13 nAbs. An alanine scan of all five N-terminal domain (NTD) loops highlights a public epitope in the N1, N3, and N5 loops recognized by most NTD-binding nAbs. NTD mutations in variants of concern B.1.1.7 (alpha), B.1.351 (beta), B.1.1.28 (gamma), B.1.427/B.1.429 (epsilon), and B.1.617.2 (delta) impact spike expression and escape most NTD-targeting nAbs. Finally, B.1.351 and B.1.1.28 completely escape a potent ACE2 mimic. We anticipate that Spike Display will accelerate antigen design, deep scanning mutagenesis, and antibody epitope mapping for SARS-CoV-2 and other emerging viral threats.

Influenza vaccination in the elderly boosts antibodies against conserved viral proteins and egg-produced glycans

Seasonal influenza vaccination elicits a diminished adaptive immune response in the elderly, and the mechanisms of immunosenescence are not fully understood. Using Ig-Seq, we found a marked increase with age in the prevalence of cross-reactive (CR) serum antibodies that recognize both the H1N1 (vaccine-H1) and H3N2 (vaccine-H3) components of an egg-produced split influenza vaccine. CR antibodies accounted for 73% ± 18% of the serum vaccine responses in a cohort of elderly donors, 65% ± 15% in late middle-aged donors, and only 13% ± 5% in persons under 35 years of age. The antibody response to non-HA antigens was boosted by vaccination. Recombinant expression of 19 vaccine-H1+H3 CR serum monoclonal antibodies (s-mAbs) revealed that they predominantly bound to non-HA influenza proteins. A sizable fraction of vaccine-H1+H3 CR s-mAbs recognized with high affinity the sulfated glycans, in particular sulfated type 2 N-acetyllactosamine (Galβ1-4GalNAcβ), which is found on egg-produced proteins and thus unlikely to contribute to protection against influenza infection in humans. Antibodies against sulfated glycans in egg-produced vaccine had been identified in animals but were not previously characterized in humans. Collectively, our results provide a quantitative basis for how repeated exposure to split influenza vaccine correlates with unintended focusing of serum antibody responses to non-HA antigens that may result in suboptimal immunity against influenza.

Prevalent, protective, and convergent IgG recognition of SARS-CoV-2 non-RBD spike epitopes

The molecular composition and binding epitopes of the immunoglobulin G (IgG) antibodies that circulate in blood plasma after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are unknown. Proteomic deconvolution of the IgG repertoire to the spike glycoprotein in convalescent subjects revealed that the response is directed predominantly (>80%) against epitopes residing outside the receptor binding domain (RBD). In one subject, just four IgG lineages accounted for 93.5% of the response, including an amino (N)-terminal domain (NTD)-directed antibody that was protective against lethal viral challenge. Genetic, structural, and functional characterization of a multidonor class of "public" antibodies revealed an NTD epitope that is recurrently mutated among emerging SARS-CoV-2 variants of concern. These data show that "public" NTD-directed and other non-RBD plasma antibodies are prevalent and have implications for SARS-CoV-2 protection and antibody escape.

Synthetic repertoires derived from convalescent COVID-19 patients enable discovery of SARS-CoV-2 neutralizing antibodies and a novel quaternary binding modality

The ongoing evolution of SARS-CoV-2 into more easily transmissible and infectious variants has sparked concern over the continued effectiveness of existing therapeutic antibodies and vaccines. Hence, together with increased genomic surveillance, methods to rapidly develop and assess effective interventions are critically needed. Here we report the discovery of SARS-CoV-2 neutralizing antibodies isolated from COVID-19 patients using a high-throughput platform. Antibodies were identified from unpaired donor B-cell and serum repertoires using yeast surface display, proteomics, and public light chain screening. Cryo-EM and functional characterization of the antibodies identified N3-1, an antibody that binds avidly (Kd,app = 68 pM) to the receptor binding domain (RBD) of the spike protein and robustly neutralizes the virus in vitro. This antibody likely binds all three RBDs of the trimeric spike protein with a single IgG. Importantly, N3-1 equivalently binds spike proteins from emerging SARS-CoV-2 variants of concern, neutralizes UK variant B.1.1.7, and binds SARS-CoV spike with nanomolar affinity. Taken together, the strategies described herein will prove broadly applicable in interrogating adaptive immunity and developing rapid response biological countermeasures to emerging pathogens.

Prevalent, protective, and convergent IgG recognition of SARS-CoV-2 non-RBD spike epitopes in COVID-19 convalescent plasma

Although humoral immunity is essential for control of SARS-CoV-2, the molecular composition, binding epitopes and effector functions of the immunoglobulin G (IgG) antibodies that circulate in blood plasma following infection are unknown. Proteomic deconvolution of the circulating IgG repertoire (Ig-Seq ¹ ) to the spike ectodomain (S-ECD ² ) in four convalescent study subjects revealed that the plasma response is oligoclonal and directed predominantly (>80%) to S-ECD epitopes that lie outside the receptor binding domain (RBD). When comparing antibodies directed to either the RBD, the N-terminal domain (NTD) or the S2 subunit (S2) in one subject, just four IgG lineages (1 anti-S2, 2 anti-NTD and 1 anti-RBD) accounted for 93.5% of the repertoire. Although the anti-RBD and one of the anti-NTD antibodies were equally potently neutralizing in vitro , we nonetheless found that the anti-NTD antibody was sufficient for protection to lethal viral challenge, either alone or in combination as a cocktail where it dominated the effect of the other plasma antibodies. We identified in vivo protective plasma anti-NTD antibodies in 3/4 subjects analyzed and discovered a shared class of antibodies targeting the NTD that utilize unmutated or near-germline IGHV1-24, the most electronegative IGHV gene in the human genome. Structural analysis revealed that binding to NTD is dominated by interactions with the heavy chain, accounting for 89% of the entire interfacial area, with germline residues uniquely encoded by IGHV1-24 contributing 20% (149 Å ² ). Together with recent reports of germline IGHV1-24 antibodies isolated by B-cell cloning ^3,4 our data reveal a class of shared IgG antibodies that are readily observed in convalescent plasma and underscore the role of NTD-directed antibodies in protection against SARS-CoV-2 infection.

Transcript degradation and codon usage regulate gene expression in a lytic phage

Many viral genomes are small, containing only single- or double-digit numbers of genes and relatively few regulatory elements. Yet viruses successfully execute complex regulatory programs as they take over their host cells. Here, we propose that some viruses regulate gene expression via a carefully balanced interplay between transcription, translation, and transcript degradation. As our model system, we employ bacteriophage T7, whose genome of approximately sixty genes is well annotated and for which there is a long history of computational models of gene regulation. We expand upon prior modeling work by implementing a stochastic gene expression simulator that tracks individual transcripts, polymerases, ribosomes, and ribonucleases participating in the transcription, translation, and transcript-degradation processes occurring during a T7 infection. By combining this detailed mechanistic modeling of a phage infection with high-throughput gene expression measurements of several strains of bacteriophage T7, evolved and engineered, we can show that both the dynamic interplay between transcription and transcript degradation, and between these two processes and translation, appear to be critical components of T7 gene regulation. Our results point to targeted degradation as a generic gene regulation strategy that may have evolved in many other viruses. Further, our results suggest that detailed mechanistic modeling may uncover the biological mechanisms at work in both evolved and engineered virus variants.

Systematic bromodomain protein screens identify homologous recombination and R-loop suppression pathways involved in genome integrity

Bromodomain proteins (BRD) are key chromatin regulators of genome function and stability as well as therapeutic targets in cancer. Here, we systematically delineate the contribution of human BRD proteins for genome stability and DNA double-strand break (DSB) repair using several cell-based assays and proteomic interaction network analysis. Applying these approaches, we identify 24 of the 42 BRD proteins as promoters of DNA repair and/or genome integrity. We identified a BRD-reader function of PCAF that bound TIP60-mediated histone acetylations at DSBs to recruit a DUB complex to deubiquitylate histone H2BK120, to allowing direct acetylation by PCAF, and repair of DSBs by homologous recombination. We also discovered the bromo-and-extra-terminal (BET) BRD proteins, BRD2 and BRD4, as negative regulators of transcription-associated RNA-DNA hybrids (R-loops) as inhibition of BRD2 or BRD4 increased R-loop formation, which generated DSBs. These breaks were reliant on topoisomerase II, and BRD2 directly bound and activated topoisomerase I, a known restrainer of R-loops. Thus, comprehensive interactome and functional profiling of BRD proteins revealed new homologous recombination and genome stability pathways, providing a framework to understand genome maintenance by BRD proteins and the effects of their pharmacological inhibition.

Sera Antibody Repertoire Analyses Reveal Mechanisms of Broad and Pandemic Strain Neutralizing Responses after Human Norovirus Vaccination

Rapidly evolving RNA viruses, such as the GII.4 strain of human norovirus (HuNoV), and their vaccines elicit complex serological responses associated with previous exposure. Specific correlates of protection, moreover, remain poorly understood. Here, we report the GII.4-serological antibody repertoire—pre- and post-vaccination—and select several antibody clonotypes for epitope and structural analysis. The humoral response was dominated by GII.4-specific antibodies that blocked ancestral strains or by antibodies that bound to divergent genotypes and did not block viral-entry-ligand interactions. However, one antibody, A1431, showed broad blockade toward tested GII.4 strains and neutralized the pandemic GII.P16-GII.4 Sydney strain. Structural mapping revealed conserved epitopes, which were occluded on the virion or partially exposed, allowing for broad blockade with neutralizing activity. Overall, our results provide high-resolution molecular information on humoral immune responses after HuNoV vaccination and demonstrate that infection-derived and vaccine-elicited antibodies can exhibit broad blockade and neutralization against this prevalent human pathogen.

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Serum vaccine response is dominated by a small number of abundant antibody clonotypes

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Vaccine-boosted antibodies predominantly target conserved norovirus epitopes

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Identified cross-genogroup and strain-specific epitopes

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Discovered a pandemic-genotype neutralizing antibody recognizing a conserved epitope

Persistent Antibody Clonotypes Dominate the Serum Response to Influenza over Multiple Years and Repeated Vaccinations

Humans are repeatedly exposed to influenza virus via infections and vaccinations. Understanding how multiple exposures and pre-existing immunity impact antibody responses is essential for vaccine development. Given the recent prevalence of influenza H1N1 A/California/7/2009 (CA09), we examined the clonal composition and dynamics of CA09 hemagglutinin (HA)-reactive IgG repertoire over 5 years in a donor with multiple influenza exposures. The anti-CA09 HA polyclonal response in this donor comprised 24 persistent antibody clonotypes, accounting for 72.6% ± 10.0% of the anti-CA09 HA repertoire over 5 years. These persistent antibodies displayed higher somatic hypermutation relative to transient serum antibodies detected at one time point. Additionally, persistent antibodies predominantly demonstrated cross-reactivity and potent neutralization toward a phylogenetically distant H5N1 A/Vietnam/1203/2004 (VT04) strain, a feature correlated with HA stem recognition. This analysis reveals how "serological imprinting" impacts responses to influenza and suggests that once elicited, cross-reactive antibodies targeting the HA stem can persist for years.

Large-scale analysis of post-translational modifications in E. coli under glucose-limiting conditions

Background

Post-translational modification (PTM) of proteins is central to many cellular processes across all domains of life, but despite decades of study and a wealth of genomic and proteomic data the biological function of many PTMs remains unknown. This is especially true for prokaryotic PTM systems, many of which have only recently been recognized and studied in depth. It is increasingly apparent that a deep sampling of abundance across a wide range of environmental stresses, growth conditions, and PTM types, rather than simply cataloging targets for a handful of modifications, is critical to understanding the complex pathways that govern PTM deposition and downstream effects.

Results

We utilized a deeply-sampled dataset of MS/MS proteomic analysis covering 9 timepoints spanning the Escherichia coli growth cycle and an unbiased PTM search strategy to construct a temporal map of abundance for all PTMs within a 400 Da window of mass shifts. Using this map, we are able to identify novel targets and temporal patterns for N-terminal N α acetylation, C-terminal glutamylation, and asparagine deamidation. Furthermore, we identify a possible relationship between N-terminal N α acetylation and regulation of protein degradation in stationary phase, pointing to a previously unrecognized biological function for this poorly-understood PTM.

Conclusions

Unbiased detection of PTM in MS/MS proteomics data facilitates the discovery of novel modification types and previously unobserved dynamic changes in modification across growth timepoints.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3676-8) contains supplementary material, which is available to authorized users.

Proteome-wide dataset supporting the study of ancient metazoan macromolecular complexes

Our analysis examines the conservation of multiprotein complexes among metazoa through use of high resolution biochemical fractionation and precision mass spectrometry applied to soluble cell extracts from 5 representative model organisms Caenorhabditis elegans, Drosophila melanogaster, Mus musculus, Strongylocentrotus purpuratus, and Homo sapiens. The interaction network obtained from the data was validated globally in 4 distant species (Xenopus laevis, Nematostella vectensis, Dictyostelium discoideum, Saccharomyces cerevisiae) and locally by targeted affinity-purification experiments. Here we provide details of our massive set of supporting biochemical fractionation data available via ProteomeXchange (PXD002319-PXD002328), PPIs via BioGRID (185267); and interaction network projections via (http://metazoa.med.utoronto.ca) made fully accessible to allow further exploration. The datasets here are related to the research article on metazoan macromolecular complexes in Nature [1].

Panorama of ancient metazoan macromolecular complexes

Macromolecular complexes are essential to conserved biological processes, but their prevalence across animals is unclear. By combining extensive biochemical fractionation with quantitative mass spectrometry, we directly examined the composition of soluble multiprotein complexes among diverse metazoan models. Using an integrative approach, we then generated a draft conservation map consisting of >1 million putative high-confidence co-complex interactions for species with fully sequenced genomes that encompasses functional modules present broadly across all extant animals. Clustering revealed a spectrum of conservation, ranging from ancient Eukaryal assemblies likely serving cellular housekeeping roles for at least 1 billion years, ancestral complexes that have accrued contemporary components, and rarer metazoan innovations linked to multicellularity. We validated these projections by independent co-fractionation experiments in evolutionarily distant species, by affinity-purification and by functional analyses. The comprehensiveness, centrality and modularity of these reconstructed interactomes reflect their fundamental mechanistic significance and adaptive value to animal cell systems.

Controlled Measurement and Comparative Analysis of Cellular Components in E. coli Reveals Broad Regulatory Changes in Response to Glucose Starvation

How do bacteria regulate their cellular physiology in response to starvation? Here, we present a detailed characterization of Escherichia coli growth and starvation over a time-course lasting two weeks. We have measured multiple cellular components, including RNA and proteins at deep genomic coverage, as well as lipid modifications and flux through central metabolism. Our study focuses on the physiological response of E. coli in stationary phase as a result of being starved for glucose, not on the genetic adaptation of E. coli to utilize alternative nutrients. In our analysis, we have taken advantage of the temporal correlations within and among RNA and protein abundances to identify systematic trends in gene regulation. Specifically, we have developed a general computational strategy for classifying expression-profile time courses into distinct categories in an unbiased manner. We have also developed, from dynamic models of gene expression, a framework to characterize protein degradation patterns based on the observed temporal relationships between mRNA and protein abundances. By comparing and contrasting our transcriptomic and proteomic data, we have identified several broad physiological trends in the E. coli starvation response. Strikingly, mRNAs are widely down-regulated in response to glucose starvation, presumably as a strategy for reducing new protein synthesis. By contrast, protein abundances display more varied responses. The abundances of many proteins involved in energy-intensive processes mirror the corresponding mRNA profiles while proteins involved in nutrient metabolism remain abundant even though their corresponding mRNAs are down-regulated.

Bacteria frequently experience starvation conditions in their natural environments. Yet how they modify their physiology in response to these conditions remains poorly understood. Here, we performed a detailed, two-week starvation experiment in E. coli. We exhaustively monitored changes in cellular components, such as RNA and protein abundances, over time. We subsequently compared and contrasted these measurements using novel computational approaches we developed specifically for analyzing gene-expression time-course data. Using these approaches, we could identify systematic trends in the E. coli starvation response. In particular, we found that cells systematically limit mRNA and protein production, degrade proteins involved in energy-intensive processes, and maintain or increase the amount of proteins involved in energy production. Thus, the bacteria assume a cellular state in which their ongoing energy use is limited while they are poised to take advantage of any nutrients that may become available.

Proteomic identification of monoclonal antibodies from serum

Characterizing the in vivo dynamics of the polyclonal antibody repertoire in serum, such as that which might arise in response to stimulation with an antigen, is difficult due to the presence of many highly similar immunoglobulin proteins, each specified by distinct B lymphocytes. These challenges have precluded the use of conventional mass spectrometry for antibody identification based on peptide mass spectral matches to a genomic reference database. Recently, progress has been made using bottom-up analysis of serum antibodies by nanoflow liquid chromatography/high-resolution tandem mass spectrometry combined with a sample-specific antibody sequence database generated by high-throughput sequencing of individual B cell immunoglobulin variable domains (V genes). Here, we describe how intrinsic features of antibody primary structure, most notably the interspersed segments of variable and conserved amino acid sequences, generate recurring patterns in the corresponding peptide mass spectra of V gene peptides, greatly complicating the assignment of correct sequences to mass spectral data. We show that the standard method of decoy-based error modeling fails to account for the error introduced by these highly similar sequences, leading to a significant underestimation of the false discovery rate. Because of these effects, antibody-derived peptide mass spectra require increased stringency in their interpretation. The use of filters based on the mean precursor ion mass accuracy of peptide-spectrum matches is shown to be particularly effective in distinguishing between "true" and "false" identifications. These findings highlight important caveats associated with the use of standard database search and error-modeling methods with nonstandard data sets and custom sequence databases.

A proteomic survey of widespread protein aggregation in yeast

Many normally cytosolic yeast proteins form insoluble intracellular bodies in response to nutrient depletion, suggesting the potential for widespread protein aggregation in stressed cells. Nearly 200 such bodies have been found in yeast by screening libraries of fluorescently tagged proteins. In order to more broadly characterize the formation of these bodies in response to stress, we employed a proteome-wide shotgun mass spectrometry assay in order to measure shifts in the intracellular solubilities of endogenous proteins following heat stress. As quantified by mass spectrometry, heat stress tended to shift the same proteins into insoluble form as did nutrient depletion; many of these proteins were also known to form foci in response to arsenic stress. Affinity purification of several foci-forming proteins showed enrichment for co-purifying chaperones, including Hsp90 chaperones. Tests of induction conditions and co-localization of metabolic enzymes participating in the same metabolic pathways suggested those foci did not correspond to multi-enzyme organizing centers. Thus, in yeast, the formation of stress bodies appears common across diverse, normally diffuse cytoplasmic proteins and is induced by multiple types of cell stress, including thermal, chemical, and nutrient stress.

A census of human soluble protein complexes

Cellular processes often depend on stable physical associations between proteins. Despite recent progress, knowledge of the composition of human protein complexes remains limited. To close this gap, we applied an integrative global proteomic profiling approach, based on chromatographic separation of cultured human cell extracts into more than one thousand biochemical fractions that were subsequently analyzed by quantitative tandem mass spectrometry, to systematically identify a network of 13,993 high-confidence physical interactions among 3,006 stably associated soluble human proteins. Most of the 622 putative protein complexes we report are linked to core biological processes and encompass both candidate disease genes and unannotated proteins to inform on mechanism. Strikingly, whereas larger multiprotein assemblies tend to be more extensively annotated and evolutionarily conserved, human protein complexes with five or fewer subunits are far more likely to be functionally unannotated or restricted to vertebrates, suggesting more recent functional innovations.

Sequence signatures and mRNA concentration can explain two-thirds of protein abundance variation in a human cell line

We provide a large-scale dataset on absolute protein and matching mRNA concentrations from the human medulloblastoma cell line Daoy. The correlation between mRNA and protein concentrations is significant and positive (R_s=0.46, R²=0.29, P-value<2e16), although non-linear.

Out of ∼200 tested sequence features, sequence length, frequency and properties of amino acids, as well as translation initiation-related features are the strongest individual correlates of protein abundance when accounting for variation in mRNA concentration.

When integrating mRNA expression data and all sequence features into a non-parametric regression model (Multivariate Adaptive Regression Splines), we were able to explain up to 67% of the variation in protein concentrations. Half of the contributions were attributed to mRNA concentrations, the other half to sequence features relating to regulation of translation and protein degradation. The sequence features are primarily linked to the coding and 3′ untranslated region. To our knowledge, this is the most comprehensive predictive model of human protein concentrations achieved so far.

mRNA decay, translation regulation and protein degradation are essential parts of eukaryotic gene expression regulation (Hieronymus and Silver, 2004; Mata et al, 2005), which enable the dynamics of cellular systems and their responses to external and internal stimuli without having to rely exclusively on transcription regulation. The importance of these processes is emphasized by the generally low correlation between mRNA and protein concentrations. For many prokaryotic and eukaryotic organisms, <50% of variation in protein abundance variation is explained by variation in mRNA concentrations (de Sousa Abreu et al, 2009).

Given the plethora of regulatory mechanisms involved, most studies have focused so far on individual regulators and specific targets. Particularly in human, we currently lack system-wide, quantitative analyses that evaluate the relative contribution of regulatory elements encoded in the mRNA and protein sequence. Existing studies have been carried out only in bacteria and yeast (Nie et al, 2006; Brockmann et al, 2007; Tuller et al, 2007; Wu et al, 2008). Here, we present the first comprehensive analysis on the impact of translation and protein degradation on protein abundance variation in a human cell line. For this purpose, we experimentally measured absolute protein and mRNA concentrations in the Daoy medulloblastoma cell line, using shotgun proteomics and microarrays, respectively (Figure 1). These data comprise one of the largest such sets available today for human. We focused on sequence features that likely impact protein translation and protein degradation, including length, nucleotide composition, structure of the untranslated regions (UTRs), coding sequence, composition of the translation initiation site, presence of upstream open reading frames putative target sites of miRNAs, codon usage, amino-acid composition and protein degradation signals.

Three types of tests have been conducted: (a) we examined partial Spearman's rank correlation of numerical features (e.g. length) with protein concentration, accounting for variation in mRNA concentrations; (b) for numerical and categorical features (e.g. function), we compared two extreme populations with Welch's t-test and (c) using a Multivariate Adaptive Regression Splines model, we analyzed the combined contributions of mRNA expression and sequence features to protein abundance variation (Figure 1). To account for the non-linearity of many relationships, we use non-parametric approaches throughout the analysis.

We observed a significant positive correlation between mRNA and protein concentrations, larger than many previous measurements (de Sousa Abreu et al, 2009). We also show that the contribution of translation and protein degradation is at least as important as the contribution of mRNA transcription and stability to the abundance variation of the final protein products. Although variation in mRNA expression explains ∼25–30% of the variation in protein abundance, another 30–40% can be accounted for by characteristics of the sequences, which we identified in a comparative assessment of global correlates. Among these characteristics, sequence length, amino-acid frequencies and also nucleotide frequencies in the coding region are of strong influence (Figure 3A). Characteristics of the 3′UTR and of the 5′UTR, that is length, nucleotide composition and secondary structures, describe another part of the variation, leaving 33% expression variation unexplained. The unexplained fraction may be accounted for by mechanisms not considered in this analysis (e.g. regulation by RNA-binding proteins or gene-specific structural motifs), as well as expression and measurement noise.

Our combined model including mRNA concentration and sequence features can explain 67% of the variation of protein abundance in this system—and thus has the highest predictive power for human protein abundance achieved so far (Figure 3B).

Transcription, mRNA decay, translation and protein degradation are essential processes during eukaryotic gene expression, but their relative global contributions to steady-state protein concentrations in multi-cellular eukaryotes are largely unknown. Using measurements of absolute protein and mRNA abundances in cellular lysate from the human Daoy medulloblastoma cell line, we quantitatively evaluate the impact of mRNA concentration and sequence features implicated in translation and protein degradation on protein expression. Sequence features related to translation and protein degradation have an impact similar to that of mRNA abundance, and their combined contribution explains two-thirds of protein abundance variation. mRNA sequence lengths, amino-acid properties, upstream open reading frames and secondary structures in the 5′ untranslated region (UTR) were the strongest individual correlates of protein concentrations. In a combined model, characteristics of the coding region and the 3′UTR explained a larger proportion of protein abundance variation than characteristics of the 5′UTR. The absolute protein and mRNA concentration measurements for >1000 human genes described here represent one of the largest datasets currently available, and reveal both general trends and specific examples of post-transcriptional regulation.

Two-tiered approach identifies a network of cancer and liver disease-related genes regulated by miR-122

MicroRNAs function as important regulators of gene expression and are commonly linked to development, differentiation, and diseases such as cancer. To better understand their roles in various biological processes, identification of genes targeted by microRNAs is necessary. Although prediction tools have significantly helped with this task, experimental approaches are ultimately required for extensive target search and validation. We employed two independent yet complementary high throughput approaches to map a large set of mRNAs regulated by miR-122, a liver-specific microRNA implicated in regulation of fatty acid and cholesterol metabolism, hepatitis C infection, and hepatocellular carcinoma. The combination of luciferase reporter-based screening and shotgun proteomics resulted in the identification of 260 proteins significantly down-regulated in response to miR-122 in at least one method, 113 of which contain predicted miR-122 target sites. These proteins are enriched for functions associated with the cell cycle, differentiation, proliferation, and apoptosis. Among these miR-122-sensitive proteins, we identified a large group with strong connections to liver metabolism, diseases, and hepatocellular carcinoma. Additional analyses, including examination of consensus binding motifs for both miR-122 and target sequences, provide further insight into miR-122 function.

Protein abundances are more conserved than mRNA abundances across diverse taxa

Proteins play major roles in most biological processes; as a consequence, protein expression levels are highly regulated. While extensive post-transcriptional, translational and protein degradation control clearly influence protein concentration and functionality, it is often thought that protein abundances are primarily determined by the abundances of the corresponding mRNAs. Hence surprisingly, a recent study showed that abundances of orthologous nematode and fly proteins correlate better than their corresponding mRNA abundances. We tested if this phenomenon is general by collecting and testing matching large-scale protein and mRNA expression data sets from seven different species: two bacteria, yeast, nematode, fly, human, and rice. We find that steady-state abundances of proteins show significantly higher correlation across these diverse phylogenetic taxa than the abundances of their corresponding mRNAs (p=0.0008, paired Wilcoxon). These data support the presence of strong selective pressure to maintain protein abundances during evolution, even when mRNA abundances diverge.

Ultrafast ultraviolet photodissociation at 193 nm and its applicability to proteomic workflows

Ultraviolet photodissociation (UVPD) at 193 nm was implemented on a linear ion trap mass spectrometer for high-throughput proteomic workflows. Upon irradiation by a single 5 ns laser pulse, efficient photodissociation of tryptic peptides was achieved with production of a, b, c, x, y, and z sequence ions, in addition to immonium ions and v and w side-chain loss ions. The factors that influence the UVPD mass spectra and subsequent in silico database searching via SEQUEST were evaluated. Peptide sequence aromaticity and the precursor charge state were found to influence photodissociation efficiency more so than the number of amide chromophores, and the ion trap q-value and number of laser pulses significantly affected the number and abundances of diagnostic product ions (e.g., sequence and immonium ions). Also, photoionization background subtraction was shown to dramatically improve SEQUEST results, especially when peptide signals were low. A liquid chromatography-mass spectrometry (LC-MS)/UVPD strategy was implemented and yielded comparable or better results relative to LC-MS/collision induced dissociation (CID) for analysis of proteolyzed bovine serum albumin and lysed human HT-1080 cytosolic fibrosarcoma cells.

Discovery of a thermophilic protein complex stabilized by topologically interlinked chains

A growing number of organisms have been discovered inhabiting extreme environments, including temperatures in excess of 100 degrees C. How cellular proteins from such organisms retain their native folds under extreme conditions is still not fully understood. Recent computational and structural studies have identified disulfide bonding as an important mechanism for stabilizing intracellular proteins in certain thermophilic microbes. Here, we present the first proteomic analysis of intracellular disulfide bonding in the hyperthermophilic archaeon Pyrobaculum aerophilum. Our study reveals that the utilization of disulfide bonds extends beyond individual proteins to include many protein-protein complexes. We report the 1.6 A crystal structure of one such complex, a citrate synthase homodimer. The structure contains two intramolecular disulfide bonds, one per subunit, which result in the cyclization of each protein chain in such a way that the two chains are topologically interlinked, rendering them inseparable. This unusual feature emphasizes the variety and sophistication of the molecular mechanisms that can be achieved by evolution.

The genomics of disulfide bonding and protein stabilization in thermophiles

Thermophilic organisms flourish in varied high-temperature environmental niches that are deadly to other organisms. Recently, genomic evidence has implicated a critical role for disulfide bonds in the structural stabilization of intracellular proteins from certain of these organisms, contrary to the conventional view that structural disulfide bonds are exclusively extracellular. Here both computational and structural data are presented to explore the occurrence of disulfide bonds as a protein-stabilization method across many thermophilic prokaryotes. Based on computational studies, disulfide-bond richness is found to be widespread, with thermophiles containing the highest levels. Interestingly, only a distinct subset of thermophiles exhibit this property. A computational search for proteins matching this target phylogenetic profile singles out a specific protein, known as protein disulfide oxidoreductase, as a potential key player in thermophilic intracellular disulfide-bond formation. Finally, biochemical support in the form of a new crystal structure of a thermophilic protein with three disulfide bonds is presented together with a survey of known structures from the literature. Together, the results provide insight into biochemical specialization and the diversity of methods employed by organisms to stabilize their proteins in exotic environments. The findings also motivate continued efforts to sequence genomes from divergent organisms.

Certain thermophiles are found to stabilize their proteins in extreme environments with additional disulfide bonds. A phylogenetic profile identifies a protein disulfide oxidoreductase critical to the stabilization process.

Genomic evidence that the intracellular proteins of archaeal microbes contain disulfide bonds

Disulfide bonds have only rarely been found in intracellular proteins. That pattern is consistent with the chemically reducing environment inside the cells of well-studied organisms. However, recent experiments and new calculations based on genomic data of archaea provide striking contradictions to this pattern. Our results indicate that the intracellular proteins of certain hyperthermophilic archaea, especially the crenarchaea Pyrobaculum aerophilum and Aeropyrum pernix, are rich in disulfide bonds. This finding implicates disulfide bonding in stabilizing many thermostable proteins and points to novel chemical environments inside these microbes. These unexpected results illustrate the wealth of biochemical insights available from the growing reservoir of genomic data.

Crystal structure of a protein repair methyltransferase from Pyrococcus furiosus with its L-isoaspartyl peptide substrate

Protein L-isoaspartyl (D-aspartyl) methyltransferases (EC 2.1.1.77) are found in almost all organisms. These enzymes catalyze the S-adenosylmethionine (AdoMet)-dependent methylation of isomerized and racemized aspartyl residues in age-damaged proteins as part of an essential protein repair process. Here, we report crystal structures of the repair methyltransferase at resolutions up to 1.2 A from the hyperthermophilic archaeon Pyrococcus furiosus. Refined structures include binary complexes with the active cofactor AdoMet, its reaction product S-adenosylhomocysteine (AdoHcy), and adenosine. The enzyme places the methyl-donating cofactor in a deep, electrostatically negative pocket that is shielded from solvent. Across the multiple crystal structures visualized, the presence or absence of the methyl group on the cofactor correlates with a significant conformational change in the enzyme in a loop bordering the active site, suggesting a role for motion in catalysis or cofactor exchange. We also report the structure of a ternary complex of the enzyme with adenosine and the methyl-accepting polypeptide substrate VYP(L-isoAsp)HA at 2.1 A. The substrate binds in a narrow active site cleft with three of its residues in an extended conformation, suggesting that damaged proteins may be locally denatured during the repair process in cells. Manual and computer-based docking studies on different isomers help explain how the enzyme uses steric effects to make the critical distinction between normal L-aspartyl and age-damaged L-isoaspartyl and D-aspartyl residues.