PaxDb, a database of protein abundance averages across all three domains of life

Universal distribution of mutational effects on protein stability, uncoupling of protein robustness from sequence evolution and distinct evolutionary modes of prokaryotic and eukaryotic proteins

Robustness to destabilizing effects of mutations is thought of as a key factor of protein evolution. The connections between two measures of robustness, the relative core size and the computationally estimated effect of mutations on protein stability (ΔΔG), protein abundance and the selection pressure on protein-coding genes (dN/dS) were analyzed for the organisms with a large number of available protein structures including four eukaryotes, two bacteria and one archaeon. The distribution of the effects of mutations in the core on protein stability is universal and indistinguishable in eukaryotes and bacteria, centered at slightly destabilizing amino acid replacements, and with a heavy tail of more strongly destabilizing replacements. The distribution of mutational effects in the hyperthermophilic archaeon Thermococcus gammatolerans is significantly shifted toward strongly destabilizing replacements which is indicative of stronger constraints that are imposed on proteins in hyperthermophiles. The median effect of mutations is strongly, positively correlated with the relative core size, in evidence of the congruence between the two measures of protein robustness. However, both measures show only limited correlations to the expression level and selection pressure on protein-coding genes. Thus, the degree of robustness reflected in the universal distribution of mutational effects appears to be a fundamental, ancient feature of globular protein folds whereas the observed variations are largely neutral and uncoupled from short term protein evolution. A weak anticorrelation between protein core size and selection pressure is observed only for surface residues in prokaryotes but a stronger anticorrelation is observed for all residues in eukaryotic proteins. This substantial difference between proteins of prokaryotes and eukaryotes is likely to stem from the demonstrable higher compactness of prokaryotic proteins.

Can "normal" protein expression ranges be estimated with high-throughput proteomics?

Although biological science discovery often involves comparing conditions to a normal state, in proteomics little is actually known about normal. Two Human Proteome studies featured in Nature offer new insights into protein expression and an opportunity to assess how high-throughput proteomics measures normal protein ranges. We use data from these studies to estimate technical and biological variability in protein expression and compare them to other expression data sets from normal tissue. Results show that measured protein expression across same-tissue replicates vary by ±4- to 10-fold for most proteins. Coefficients of variation (CV) for protein expression measurements range from 62% to 117% across different tissue experiments; however, adjusting for technical variation reduced this variability by as much as 50%. In addition, the CV could also be reduced by limiting comparisons to proteins with at least 3 or more unique peptide identifications as the CV was on average 33% lower than for proteins with 2 or fewer peptide identifications. We also selected 13 housekeeping proteins and genes that were expressed across all tissues with low variability to determine their utility as a reference set for normalization and comparative purposes. These results present the first step toward estimating normal protein ranges by determining the variability in expression measurements through combining publicly available data. They support an approach that combines standard protocols with replicates of normal tissues to estimate normal protein ranges for large numbers of proteins and tissues. This would be a tremendous resource for normal cellular physiology and comparisons of proteomics studies.

Sec17 can trigger fusion of trans-SNARE paired membranes without Sec18

Sec17 [soluble N-ethylmaleimide-sensitive factor (NSF) attachment protein; α-SNAP] and Sec18 (NSF) perform ATP-dependent disassembly of cis-SNARE complexes, liberating SNAREs for subsequent assembly of trans-complexes for fusion. A mutant of Sec17, with limited ability to stimulate Sec18, still strongly enhanced fusion when ample Sec18 was supplied, suggesting that Sec17 has additional functions. We used fusion reactions where the four SNAREs were initially separate, thus requiring no disassembly by Sec18. With proteoliposomes bearing asymmetrically disposed SNAREs, tethering and trans-SNARE pairing allowed slow fusion. Addition of Sec17 did not affect the levels of trans-SNARE complex but triggered sudden fusion of trans-SNARE paired proteoliposomes. Sec18 did not substitute for Sec17 in triggering fusion, but ADP- or ATPγS-bound Sec18 enhanced this Sec17 function. The extent of the Sec17 effect varied with the lipid headgroup and fatty acyl composition of the proteoliposomes. Two mutants further distinguished the two Sec17 functions: Sec17(L291A,L292A) did not stimulate Sec18 to disassemble cis-SNARE complex but triggered the fusion of trans-SNARE paired membranes. Sec17(F21S,M22S), with diminished apolar character to its hydrophobic loop, fully supported Sec18-mediated SNARE complex disassembly but had lost the capacity to stimulate the fusion of trans-SNARE paired membranes. To model the interactions of SNARE-bound Sec17 with membranes, we show that Sec17, but not Sec17(F21S,M22S), interacted synergistically with the soluble SNARE domains to enable their stable association with liposomes. We propose a model in which Sec17 binds to trans-SNARE complexes, oligomerizes, and inserts apolar loops into the apposed membranes, locally disturbing the lipid bilayer and thereby lowering the energy barrier for fusion.

Combined Label-Free Quantitative Proteomics and microRNA Expression Analysis of Breast Cancer Unravel Molecular Differences with Clinical Implications

Better knowledge of the biology of breast cancer has allowed the use of new targeted therapies, leading to improved outcome. High-throughput technologies allow deepening into the molecular architecture of breast cancer, integrating different levels of information, which is important if it helps in making clinical decisions. microRNA (miRNA) and protein expression profiles were obtained from 71 estrogen receptor-positive (ER(+)) and 25 triple-negative breast cancer (TNBC) samples. RNA and proteins obtained from formalin-fixed, paraffin-embedded tumors were analyzed by RT-qPCR and LC/MS-MS, respectively. We applied probabilistic graphical models representing complex biologic systems as networks, confirming that ER(+) and TNBC subtypes are distinct biologic entities. The integration of miRNA and protein expression data unravels molecular processes that can be related to differences in the genesis and clinical evolution of these types of breast cancer. Our results confirm that TNBC has a unique metabolic profile that may be exploited for therapeutic intervention.

Spatially-resolved metabolic cooperativity within dense bacterial colonies

Background

The exchange of metabolites and the reprogramming of metabolism in response to shifting microenvironmental conditions can drive subpopulations of cells within colonies toward divergent behaviors. Understanding the interactions of these subpopulations—their potential for competition as well as cooperation—requires both a metabolic model capable of accounting for a wide range of environmental conditions, and a detailed dynamic description of the cells’ shared extracellular space.

Results

Here we show that a cell’s position within an in silicoEscherichia coli colony grown on glucose minimal agar can drastically affect its metabolism: “pioneer” cells at the outer edge engage in rapid growth that expands the colony, while dormant cells in the interior separate two spatially distinct subpopulations linked by a cooperative form of acetate crossfeeding that has so far gone unnoticed. Our hybrid simulation technique integrates 3D reaction-diffusion modeling with genome-scale flux balance analysis (FBA) to describe the position-dependent metabolism and growth of cells within a colony. Our results are supported by imaging experiments involving strains of fluorescently-labeled E. coli. The spatial patterns of fluorescence within these experimental colonies identify cells with upregulated genes associated with acetate crossfeeding and are in excellent agreement with the predictions. Furthermore, the height-to-width ratios of both the experimental and simulated colonies are in good agreement over a growth period of 48 hours.

Conclusions

Our modeling paradigm can accurately reproduce a number of known features of E. coli colony growth, as well as predict a novel one that had until now gone unrecognized. The acetate crossfeeding we see has a direct analogue in a form of lactate crossfeeding observed in certain forms of cancer, and we anticipate future application of our methodology to models of tissues and tumors.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0155-1) contains supplementary material, which is available to authorized users.

Structural and evolutionary versatility in protein complexes with uneven stoichiometry

Proteins assemble into complexes with diverse quaternary structures. Although most heteromeric complexes of known structure have even stoichiometry, a significant minority have uneven stoichiometry--that is, differing numbers of each subunit type. To adopt this uneven stoichiometry, sequence-identical subunits must be asymmetric with respect to each other, forming different interactions within the complex. Here we first investigate the occurrence of uneven stoichiometry, demonstrating that it is common in vitro and is likely to be common in vivo. Next, we elucidate the structural determinants of uneven stoichiometry, identifying six different mechanisms by which it can be achieved. Finally, we study the frequency of uneven stoichiometry across evolution, observing a significant enrichment in bacteria compared with eukaryotes. We show that this arises due to a general increased tendency for bacterial proteins to self-assemble and form homomeric interactions, even within the context of a heteromeric complex.

Extracting high confidence protein interactions from affinity purification data: at the crossroads

Deriving protein-protein interactions from data generated by affinity-purification and mass spectrometry (AP-MS) techniques requires application of scoring methods to measure the reliability of detected putative interactions. Choosing the appropriate scoring method has become a major challenge. Here we apply six popular scoring methods to the same AP-MS dataset and compare their performance. The comparison was carried out for six distinct datasets from human, fly and yeast, which focus on different biological processes and differ in their coverage of the proteome. Results show that the performance of a given scoring method may vary substantially depending on the dataset. Disturbingly, we find that the high confidence (HC) PPI networks built by applying the six scoring methods to the same raw AP-MS dataset display very poor overlap, with only 1.7-4.1% of the HC interactions present in all the networks built, respectively, from the proteome-wide human, fly or yeast datasets. Various properties of the shared versus unique interactions in each network, including biases in protein abundance, suggest that current scoring methods are able to eliminate only the most obvious contaminants, but still fail to reliably single out specific interactions from the large body of spurious associations detected in the AP-MS experiments.

BIOLOGICAL SIGNIFICANCE

The fast progress in AP-MS techniques has prompted the development of a multitude of scoring methods, which are relied upon to remove contaminants and non-specific binders. Choosing the appropriate scoring scheme for a given AP-MS dataset has become a major challenge. The comparative analysis of 6 of the most popular scoring methods, presented here, reveals that overall these methods do not perform as expected. Evidence is provided that this is due to 3 closely related issues: the high 'noise' levels of the raw AP-MS data, the limited capacity of current scoring methods to deal with such high noise levels, and the biases introduced using Gold Standard datasets to benchmark the scoring functions and threshold the networks. For the field to move forward, all three issues will have to be addressed. This article is part of a Special Issue entitled: Protein dynamics in health and disease. Guest Editors: Pierre Thibault and Anne-Claude Gingras.

Version 4.0 of PaxDb: Protein abundance data, integrated across model organisms, tissues, and cell-lines

Protein quantification at proteome‐wide scale is an important aim, enabling insights into fundamental cellular biology and serving to constrain experiments and theoretical models. While proteome‐wide quantification is not yet fully routine, many datasets approaching proteome‐wide coverage are becoming available through biophysical and MS techniques. Data of this type can be accessed via a variety of sources, including publication supplements and online data repositories. However, access to the data is still fragmentary, and comparisons across experiments and organisms are not straightforward. Here, we describe recent updates to our database resource “PaxDb” (Protein Abundances Across Organisms). PaxDb focuses on protein abundance information at proteome‐wide scope, irrespective of the underlying measurement technique. Quantification data is reprocessed, unified, and quality‐scored, and then integrated to build a meta‐resource. PaxDb also allows evolutionary comparisons through precomputed gene orthology relations. Recently, we have expanded the scope of the database to include cell‐line samples, and more systematically scan the literature for suitable datasets. We report that a significant fraction of published experiments cannot readily be accessed and/or parsed for quantitative information, requiring additional steps and efforts. The current update brings PaxDb to 414 datasets in 53 organisms, with (semi‐) quantitative abundance information covering more than 300 000 proteins.

Web resources for mass spectrometry-based proteomics

With the development of high-resolution and high-throughput mass spectrometry (MS) technology, a large quantum of proteomic data is continually being generated. Collecting and sharing these data are a challenge that requires immense and sustained human effort. In this report, we provide a classification of important web resources for MS-based proteomics and present rating of these web resources, based on whether raw data are stored, whether data submission is supported, and whether data analysis pipelines are provided. These web resources are important for biologists involved in proteomics research.

Roles of intramolecular and intermolecular interactions in functional regulation of the Hsp70 J-protein co-chaperone Sis1

Unlike other Hsp70 molecular chaperones, those of the eukaryotic cytosol have four residues, EEVD, at their C-termini. EEVD(Hsp70) binds adaptor proteins of the Hsp90 chaperone system and mitochondrial membrane preprotein receptors, thereby facilitating processing of Hsp70-bound clients through protein folding and translocation pathways. Among J-protein co-chaperones functioning in these pathways, Sis1 is unique, as it also binds the EEVD(Hsp70) motif. However, little is known about the role of the Sis1:EEVD(Hsp70) interaction. We found that deletion of EEVD(Hsp70) abolished the ability of Sis1, but not the ubiquitous J-protein Ydj1, to partner with Hsp70 in in vitro protein refolding. Sis1 co-chaperone activity with Hsp70∆EEVD was restored upon substitution of a glutamic acid of the J-domain. Structural analysis revealed that this key glutamic acid, which is not present in Ydj1, forms a salt bridge with an arginine of the immediately adjacent glycine-rich region. Thus, restoration of Sis1 in vitro activity suggests that intramolecular interactions between the J-domain and glycine-rich region control co-chaperone activity, which is optimal only when Sis1 interacts with the EEVD(Hsp70) motif. However, we found that disruption of the Sis1:EEVD(Hsp70) interaction enhances the ability of Sis1 to substitute for Ydj1 in vivo. Our results are consistent with the idea that interaction of Sis1 with EEVD(Hsp70) minimizes transfer of Sis1-bound clients to Hsp70s that are primed for client transfer to folding and translocation pathways by their preassociation with EEVD binding adaptor proteins. These interactions may be one means by which cells triage Ydj1- and Sis1-bound clients to productive and quality control pathways, respectively.

EMILIN2 regulates platelet activation, thrombus formation, and clot retraction

Thrombosis, like other cardiovascular diseases, has a strong genetic component, with largely unknown determinants. EMILIN2, Elastin Microfibril Interface Located Protein2, was identified as a candidate gene for thrombosis in mouse and human quantitative trait loci studies. EMILIN2 is expressed during cardiovascular development, on cardiac stem cells, and in heart tissue in animal models of heart disease. In humans, the EMILIN2 gene is located on the short arm of Chromosome 18, and patients with partial and complete deletion of this chromosome region have cardiac malformations. To understand the basis for the thrombotic risk associated with EMILIN2, EMILIN2 deficient mice were generated. The findings of this study indicate that EMILIN2 influences platelet aggregation induced by adenosine diphosphate, collagen, and thrombin with both EMILIN2-deficient platelets and EMILIN2-deficient plasma contributing to the impaired aggregation response. Purified EMILIN2 added to platelets accelerated platelet aggregation and reduced clotting time when added to EMILIN2-deficient mouse and human plasma. Carotid occlusion time was 2-fold longer in mice with platelet-specific EMILIN2 deficiency, but stability of the clot was reduced in mice with both global EMILIN2 deficiency and with platelet-specific EMILIN2 deficiency. In vitro clot retraction was markedly decreased in EMILIN2 deficient mice, indicating that platelet outside-in signaling was dependent on EMILIN2. EMILIN1 deficient mice and EMILIN2:EMILIN1 double deficient mice had suppressed platelet aggregation and delayed clot retraction similar to EMILIN2 mice, but EMILIN2 and EMILIN1 had opposing affects on clot retraction, suggesting that EMILIN1 may attenuate the effects of EMILIN2 on platelet aggregation and thrombosis. In conclusion, these studies identify multiple influences of EMILIN2 in pathophysiology and suggest that its role as a prothrombotic risk factor may arise from its effects on platelet aggregation and platelet mediated clot retraction.

A conserved domain important for association of eukaryotic J-protein co-chaperones Jjj1 and Zuo1 with the ribosome

J-proteins, obligate co-chaperones, provide specialization for Hsp70 function in a variety of cellular processes. Two of the 13 J-proteins of the yeast cytosol/nucleus, Zuo1 and Jjj1, are associated with 60S ribosomal subunits. Abundant Zuo1 facilitates folding of nascent polypeptides; Jjj1, of much lower abundance, functions in ribosome biogenesis. However, overexpression of Jjj1 substantially rescues growth defects of cells lacking Zuo1. We analyzed a region held in common by Zuo1 and Jjj1, outside the signature J-domain found in all J-proteins. This shared "zuotin homology domain" (ZHD) is important for ribosome association of both proteins. An N-terminal segment of Jjj1, containing the J-domain and ZHD, is ribosome-associated and, like full-length Jjj1, is competent to rescue both the cold- and cation-sensitivity of ∆zuo1. However, this fragment, when expressed at normal levels, cannot rescue the cytosolic ribosome biogenesis defect of ∆jjj1. Our results are consistent with a model in which the primary functions of Zuo1 and Jjj1 occur in the cytosol. In addition, our data suggest that Zuo1 and Jjj1 bind overlapping sites on ribosomes due to an interaction via their common ZHDs, but Jjj1 binds primarily to pre-60S particles and Zuo1 to mature subunits. We hypothesize that ZUO1 and JJJ1, which are conserved throughout eukaryotes, arose from an ancient duplication of a progenitor J-protein gene that encoded the ZHD ribosome-binding region; subsequently, specialized roles and additional ribosome interaction sites evolved.

Myosin heavy chain 15 is associated with bovine pulmonary arterial pressure

Bovine pulmonary hypertension, brisket disease, causes significant morbidity and mortality at elevations above 2,000 m. Mean pulmonary arterial pressure (mPAP) is moderately heritable, with inheritance estimated to lie within a few major genes. Invasive mPAP measurement is currently the only tool available to identify cattle at risk of hypoxia-induced pulmonary hypertension. A genetic test could allow selection of cattle suitable for high altitude without the need for invasive testing. In this study we evaluated three candidate genes (myosin heavy chain 15 [MYH15], NADH dehydrogenase flavoprotein 2, and FK binding protein 1A) for association with mPAP in 166 yearling Angus bulls grazing at 2,182 m. The T allele (rs29016420) of MYH15 was linked to lower mPAP in a dominant manner (CC 47.2 ± 1.6 mmHg [mean ± standard error of the mean]; CT/TT 42.8 ± 0.7 mmHg; P = 0.02). The proportions of cattle with MYH15 CC, CT, and TT genotypes were 55%, 41%, and 4%, respectively. Given the high frequency of the deleterious allele, it is likely that the relative contribution of MYH15 polymorphisms to pulmonary hypertension is small, supporting previous predictions that the disease is polygenic. We evaluated allelic frequency of MYH15 in the Himalayan yak (Bos grunniens), a closely related species adapted to high altitude, and found 100% prevalence of T allele homozygosity. In summary, we identified a polymorphism in MYH15 significantly associated with mPAP. This finding may aid selection of cattle suitable for high altitude and contribute to understanding human hypoxia-induced pulmonary hypertension.

The yeast La related protein Slf1p is a key activator of translation during the oxidative stress response

The mechanisms by which RNA-binding proteins control the translation of subsets of mRNAs are not yet clear. Slf1p and Sro9p are atypical-La motif containing proteins which are members of a superfamily of RNA-binding proteins conserved in eukaryotes. RIP-Seq analysis of these two yeast proteins identified overlapping and distinct sets of mRNA targets, including highly translated mRNAs such as those encoding ribosomal proteins. In paralell, transcriptome analysis of slf1Δ and sro9Δ mutant strains indicated altered gene expression in similar functional classes of mRNAs following loss of each factor. The loss of SLF1 had a greater impact on the transcriptome, and in particular, revealed changes in genes involved in the oxidative stress response. slf1Δ cells are more sensitive to oxidants and RIP-Seq analysis of oxidatively stressed cells enriched Slf1p targets encoding antioxidants and other proteins required for oxidant tolerance. To quantify these effects at the protein level, we used label-free mass spectrometry to compare the proteomes of wild-type and slf1Δ strains following oxidative stress. This analysis identified several proteins which are normally induced in response to hydrogen peroxide, but where this increase is attenuated in the slf1Δ mutant. Importantly, a significant number of the mRNAs encoding these targets were also identified as Slf1p-mRNA targets. We show that Slf1p remains associated with the few translating ribosomes following hydrogen peroxide stress and that Slf1p co-immunoprecipitates ribosomes and members of the eIF4E/eIF4G/Pab1p ‘closed loop’ complex suggesting that Slf1p interacts with actively translated mRNAs following stress. Finally, mutational analysis of SLF1 revealed a novel ribosome interacting domain in Slf1p, independent of its RNA binding La-motif. Together, our results indicate that Slf1p mediates a translational response to oxidative stress via mRNA-specific translational control.

All organisms must respond to changes in their external environment such as exposure to different stresses. The availability of genome sequences and post-genomic technologies has enabled the analysis of these adaptive responses at the molecular level in terms of altered gene expression profiles. However, relatively few studies have focused on how cells regulate the translation of mRNA into protein in response to stress, despite its fundamental role in gene expression pathways. In this study, we show that a previously identified RNA-binding protein called Slf1p plays a major role in mRNA-specific regulation of translation during oxidative stress conditions and is necessary to promote the translation of stress-responsive mRNAs. This protein is a member of the so-called “La-related” family of proteins that have not been well characterized, although they are conserved throughout evolution. Exposure to oxidants is known to cause a general down-regulation of protein synthesis, although many stress response proteins are able to overcome this inhibition and increase their protein levels following stress by as yet unknown mechanisms. Our experiments offer one possible explanation, as they show that Slf1p plays a critical role in enhancing translation of many of these proteins, including many that are necessary for the cellular stress response.

Permanent proteins in the urine of healthy humans during the Mars-500 experiment

Urinary proteins serve as indicators of various conditions in human normal physiology and disease pathology. Using mass spectrometry proteome analysis, the permanent constituent of the urine was examined in the Mars-500 experiment (520 days isolation of healthy volunteers in a terrestrial complex with an autonomous life support system). Seven permanent proteins with predominant distribution in the liver and blood plasma as well as extracellular localization were identified. Analysis of the overrepresentation of the molecular functions and biological processes based on Gene Ontology revealed that the functional association among these proteins was low. The results showed that the identified proteins may be independent markers of the various conditions and processes in healthy humans and that they can be used as standards in determination of the concentration of other proteins in the urine.

Global mRNA selection mechanisms for translation initiation

Background

The selection and regulation of individual mRNAs for translation initiation from a competing pool of mRNA are poorly understood processes. The closed loop complex, comprising eIF4E, eIF4G and PABP, and its regulation by 4E-BPs are perceived to be key players. Using RIP-seq, we aimed to evaluate the role in gene regulation of the closed loop complex and 4E-BP regulation across the entire yeast transcriptome.

Results

We find that there are distinct populations of mRNAs with coherent properties: one mRNA pool contains many ribosomal protein mRNAs and is enriched specifically with all of the closed loop translation initiation components. This class likely represents mRNAs that rely heavily on the closed loop complex for protein synthesis. Other heavily translated mRNAs are apparently under-represented with most closed loop components except Pab1p. Combined with data showing a close correlation between Pab1p interaction and levels of translation, these data suggest that Pab1p is important for the translation of these mRNAs in a closed loop independent manner. We also identify a translational regulatory mechanism for the 4E-BPs; these appear to self-regulate by inhibiting translation initiation of their own mRNAs.

Conclusions

Overall, we show that mRNA selection for translation initiation is not as uniformly regimented as previously anticipated. Components of the closed loop complex are highly relevant for many mRNAs, but some heavily translated mRNAs interact poorly with this machinery. Therefore, alternative, possibly Pab1p-dependent mechanisms likely exist to load ribosomes effectively onto mRNAs. Finally, these studies identify and characterize a complex self-regulatory circuit for the yeast 4E-BPs.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0559-z) contains supplementary material, which is available to authorized users.

An introduction to systems toxicology

Systems toxicology combines novel and historical experimental data to generate increasingly complex models of the biological response to chemical exposure.

In-depth comparative proteomic analysis of yeast proteome using iTRAQ and SWATH based MS

SWATH is capable of quantifying proteins of lower abundance as compared to iTRAQ.

Prolongation of Chemically-Induced Methemoglobinemia in Mice Lacking α-synuclein: A Novel Pharmacologic and Toxicologic Phenotype

The protein α-synuclein is considered central to the pathogenesis of Parkinson disease (PD) on genetic and histopathological grounds. It is widely expressed in fetal life and continues to be highly expressed in adult neural tissues, red blood cells and platelets, while the remainder of adult tissues are reported to have little or no expression. Despite cellular and molecular evidence for a role in neuronal function including synaptic vesicle trafficking, neurotransmitter release, mitochondrial function, lipid metabolism, neurogenesis, neuroprotection, and neuromelanin biosynthesis, mice ablated for the gene encoding α-synuclein (Snca) have little or no neurological phenotype. Thus, nearly 20 years of intensive study have yet to reveal conclusively what the normal function of this highly abundant protein is in the nervous system. Interestingly, α-synuclein has also been shown to have enzymatic activity as a ferrireductase capable of reducing Fe⁺³ to Fe⁺². Given its abundant expression in red blood cells, we set out to explore the role of α-synuclein in converting chemically-induced Fe⁺³ methemoglobin to normal Fe⁺² hemoglobin. Initial in vivo experiments with the potent methemoglobin inducer, para-aminopropiophenone and its active metabolite, 4-hydroxy para-aminopropiophenone, demonstrated significantly greater and more prolonged methemoglobinemia in Snca−/− mice compared to Snca+/+ mice. In vitro experiments with red blood cells, however, and in vivo experiments in genetically engineered mouse strains that differ in their α-synuclein expression in various tissues, including the nervous system, red blood cells and liver, revealed that contrary to the initial hypothesis, a lack of expression of α-synuclein in red blood cells did not correlate with higher levels or more prolonged duration of methemoglobinemia. Instead, the greater sensitivity to chemically induced methemoglobinemia correlated with the absence of hepatic α-synuclein expression. We have uncovered a new and robust whole-animal phenotype in mice lacking α-synuclein that reflects its hitherto unrecognized role in xenobiotic detoxification.

Rationally designed, heterologous S. cerevisiae transcripts expose novel expression determinants

Deducing generic causal relations between RNA transcript features and protein expression profiles from endogenous gene expression data remains a major unsolved problem in biology. The analysis of gene expression from heterologous genes contributes significantly to solving this problem, but has been heavily biased toward the study of the effect of 5' transcript regions and to prokaryotes. Here, we employ a synthetic biology driven approach that systematically differentiates the effect of different regions of the transcript on gene expression up to 240 nucleotides into the ORF. This enabled us to discover new causal effects between features in previously unexplored regions of transcripts, and gene expression in natural regimes. We rationally designed, constructed, and analyzed 383 gene variants of the viral HRSVgp04 gene ORF, with multiple synonymous mutations at key positions along the transcript in the eukaryote S. cerevisiae. Our results show that a few silent mutations at the 5'UTR can have a dramatic effect of up to 15 fold change on protein levels, and that even synonymous mutations in positions more than 120 nucleotides downstream from the ORF 5'end can modulate protein levels up to 160%-300%. We demonstrate that the correlation between protein levels and folding energy increases with the significance of the level of selection of the latter in endogenous genes, reinforcing the notion that selection for folding strength in different parts of the ORF is related to translation regulation. Our measured protein abundance correlates notably(correlation up to r = 0.62 (p=0.0013)) with mean relative codon decoding times, based on ribosomal densities (Ribo-Seq) in endogenous genes, supporting the conjecture that translation elongation and adaptation to the tRNA pool can modify protein levels in a causal/direct manner. This report provides an improved understanding of transcript evolution, design principles of gene expression regulation, and suggests simple rules for engineering synthetic gene expression in eukaryotes.

Testing whether metazoan tyrosine loss was driven by selection against promiscuous phosphorylation

Protein tyrosine phosphorylation is a key regulatory modification in metazoans, and the corresponding kinase enzymes have diversified dramatically. This diversification is correlated with a genome-wide reduction in protein tyrosine content, and it was recently suggested that this reduction was driven by selection to avoid promiscuous phosphorylation that might be deleterious. We tested three predictions of this intriguing hypothesis. 1) Selection should be stronger on residues that are more likely to be phosphorylated due to local solvent accessibility or structural disorder. 2) Selection should be stronger on proteins that are more likely to be promiscuously phosphorylated because they are abundant. We tested these predictions by comparing distributions of tyrosine within and among human and yeast orthologous proteins. 3) Selection should be stronger against mutations that create tyrosine versus remove tyrosine. We tested this prediction using human population genomic variation data. We found that all three predicted effects are modest for tyrosine when compared with the other amino acids, suggesting that selection against deleterious phosphorylation was not dominant in driving metazoan tyrosine loss.

Three-dimensional eukaryotic genomic organization is strongly correlated with codon usage expression and function

It has been shown that the distribution of genes in eukaryotic genomes is not random; however, formerly reported relations between gene function and genomic organization were relatively weak. Previous studies have demonstrated that codon usage bias is related to all stages of gene expression and to protein function. Here we apply a novel tool for assessing functional relatedness, codon usage frequency similarity (CUFS), which measures similarity between genes in terms of codon and amino acid usage. By analyzing chromosome conformation capture data, describing the three-dimensional (3D) conformation of the DNA, we show that the functional similarity between genes captured by CUFS is directly and very strongly correlated with their 3D distance in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, mouse and human. This emphasizes the importance of three-dimensional genomic localization in eukaryotes and indicates that codon usage is tightly linked to genome architecture.

Exploiting hidden information interleaved in the redundancy of the genetic code without prior knowledge

MOTIVATION

Dozens of studies in recent years have demonstrated that codon usage encodes various aspects related to all stages of gene expression regulation. When relevant high-quality large-scale gene expression data are available, it is possible to statistically infer and model these signals, enabling analysing and engineering gene expression. However, when these data are not available, it is impossible to infer and validate such models.

RESULTS

In this current study, we suggest Chimera-an unsupervised computationally efficient approach for exploiting hidden high-dimensional information related to the way gene expression is encoded in the open reading frame (ORF), based solely on the genome of the analysed organism. One version of the approach, named Chimera Average Repetitive Substring (ChimeraARS), estimates the adaptability of an ORF to the intracellular gene expression machinery of a genome (host), by computing its tendency to include long substrings that appear in its coding sequences; the second version, named ChimeraMap, engineers the codons of a protein such that it will include long substrings of codons that appear in the host coding sequences, improving its adaptation to a new host's gene expression machinery. We demonstrate the applicability of the new approach for analysing and engineering heterologous genes and for analysing endogenous genes. Specifically, focusing on Escherichia coli, we show that it can exploit information that cannot be detected by conventional approaches (e.g. the CAI-Codon Adaptation Index), which only consider single codon distributions; for example, we report correlations of up to 0.67 for the ChimeraARS measure with heterologous gene expression, when the CAI yielded no correlation.

AVAILABILITY AND IMPLEMENTATION

For non-commercial purposes, the code of the Chimera approach can be downloaded from http://www.cs.tau.ac.il/∼tamirtul/Chimera/download.htm.

CONTACT

tamirtul@post.tau.ac.il

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Molecular principles of human virus protein-protein interactions

MOTIVATION

Viruses, from the human protein-protein interaction network perspective, target hubs, bottlenecks and interconnected nodes enriched in certain biological pathways. However, not much is known about the general characteristic features of the human proteins interacting with viral proteins (referred to as hVIPs) as well as the motifs and domains utilized by human-virus protein-protein interactions (referred to as Hu-Vir PPIs).

RESULTS

Our study has revealed that hVIPs are mostly disordered proteins, whereas viral proteins are mostly ordered proteins. Protein disorder in viral proteins and hVIPs varies from one subcellular location to another. In any given viral-human PPI pair, at least one of the two proteins is structurally disordered suggesting that disorder associated conformational flexibility as one of the characteristic features of virus-host interaction. Further analyses reveal that hVIPs are (i) slowly evolving proteins, (ii) associated with high centrality scores in human-PPI network, (iii) involved in multiple pathways, (iv) enriched in eukaryotic linear motifs (ELMs) associated with protein modification, degradation and regulatory processes, (v) associated with high number of splice variants and (vi) expressed abundantly across multiple tissues. These aforementioned findings suggest that conformational flexibility, spatial diversity, abundance and slow evolution are the characteristic features of the human proteins targeted by viral proteins. Hu-Vir PPIs are mostly mediated via domain-motif interactions (DMIs) where viral proteins employ motifs that mimic host ELMs to bind to domains in human proteins. DMIs are shared among viruses belonging to different families indicating a possible convergent evolution of these motifs to help viruses to adopt common strategies to subvert host cellular pathways.

AVAILABILITY AND IMPLEMENTATION

Hu-Vir PPI data, DDI and DMI data for human-virus PPI can be downloaded from http://cdfd.org.in/labpages/computational_biology_datasets.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Proteome folding kinetics is limited by protein halflife

How heterogeneous are proteome folding timescales and what physical principles, if any, dictate its limits? We answer this by predicting copy number weighted folding speed distribution – using the native topology – for E.coli and Yeast proteome. E.coli and Yeast proteomes yield very similar distributions with average folding times of 100 milliseconds and 170 milliseconds, respectively. The topology-based folding time distribution is well described by a diffusion-drift mutation model on a flat-fitness landscape in free energy barrier between two boundaries: i) the lowest barrier height determined by the upper limit of folding speed and ii) the highest barrier height governed by the lower speed limit of folding. While the fastest time scale of the distribution is near the experimentally measured speed limit of 1 microsecond (typical of barrier-less folders), we find the slowest folding time to be around seconds (8 seconds for Yeast distribution), approximately an order of magnitude less than the fastest halflife (approximately 2 minutes) in the Yeast proteome. This separation of timescale implies even the fastest degrading protein will have moderately high (96%) probability of folding before degradation. The overall agreement with the flat-fitness landscape model further hints that proteome folding times did not undergo additional major selection pressures – to make proteins fold faster – other than the primary requirement to “sufficiently beat the clock” against its lifetime. Direct comparison between the predicted folding time and experimentally measured halflife further shows 99% of the proteome have a folding time less than their corresponding lifetime. These two findings together suggest that proteome folding kinetics may be bounded by protein halflife.

The yeast enzyme Eht1 is an octanoyl-CoA:ethanol acyltransferase that also functions as a thioesterase

Fatty acid ethyl esters are secondary metabolites that are produced during microbial fermentation, in fruiting plants and in higher organisms during ethanol stress. In particular, volatile medium-chain fatty acid ethyl esters are important flavour compounds that impart desirable fruit aromas to fermented beverages, including beer and wine. The biochemical synthesis of medium-chain fatty acid ethyl esters is poorly understood but likely involves acyl-CoA:ethanol O-acyltransferases. Here, we characterize the enzyme ethanol hexanoyl transferase 1 (Eht1) from the brewer's yeast Saccharomyces cerevisiae. Full-length Eht1 was successfully overexpressed from a recombinant yeast plasmid and purified at the milligram scale after detergent solubilization of sedimenting membranes. Recombinant Eht1 was functional as an acyltransferase and, unexpectedly, was optimally active toward octanoyl-CoA, with k_cat = 0.28 ± 0.02/s and K_M = 1.9 ± 0.6 μm. Eht1 was also revealed to be active as a thioesterase but was not able to hydrolyse p-nitrophenyl acyl esters, in contrast to the findings of a previous study. Low-resolution structural data and site-directed mutagenesis provide experimental support for a predicted α/β-hydrolase domain featuring a Ser–Asp–His catalytic triad. The S. cerevisiae gene YBR177C/EHT1 should thus be reannotated as coding for an octanoyl-CoA:ethanol acyltransferase that can also function as a thioesterase. © 2014 The Authors. Yeast published by John Wiley & Sons, Ltd.

Amino Acid metabolism conflicts with protein diversity

The 20 protein-coding amino acids are found in proteomes with different relative abundances. The most abundant amino acid, leucine, is nearly an order of magnitude more prevalent than the least abundant amino acid, cysteine. Amino acid metabolic costs differ similarly, constraining their incorporation into proteins. On the other hand, a diverse set of protein sequences is necessary to build functional proteomes. Here, we present a simple model for a cost-diversity trade-off postulating that natural proteomes minimize amino acid metabolic flux while maximizing sequence entropy. The model explains the relative abundances of amino acids across a diverse set of proteomes. We found that the data are remarkably well explained when the cost function accounts for amino acid chemical decay. More than 100 organisms reach comparable solutions to the trade-off by different combinations of proteome cost and sequence diversity. Quantifying the interplay between proteome size and entropy shows that proteomes can get optimally large and diverse.

Varicella-zoster virus-derived major histocompatibility complex class I-restricted peptide affinity is a determining factor in the HLA risk profile for the development of postherpetic neuralgia

Postherpetic neuralgia (PHN) is the most common complication of herpes zoster and is typified by a lingering pain that can last months or years after the characteristic herpes zoster rash disappears. It is well known that there are risk factors for the development of PHN, such as its association with certain HLA alleles. In this study, previous HLA genotyping results were collected and subjected to a meta-analysis with increased statistical power. This work shows that the alleles HLA-A*33 and HLA-B*44 are significantly enriched in PHN patients, while HLA-A*02 and HLA-B*40 are significantly depleted. Prediction of the varicella-zoster virus (VZV) peptide affinity for these four HLA variants by using one in-house-developed and two existing state-of-the-art major histocompatibility complex (MHC) class I ligand prediction methods reveals that there is a great difference in their absolute and relative peptide binding repertoires. It was observed that HLA-A*02 displays a high affinity for an ∼7-fold-higher number of VZV peptides than HLA-B*44. Furthermore, after correction for HLA allele-specific limitations, the relative affinity of HLA-A*33 and HLA-B*44 for VZV peptides was found to be significantly lower than those of HLA-A*02 and HLA-B*40. In addition, HLA peptide affinity calculations indicate strong trends for VZV to avoid high-affinity peptides in some of its proteins, independent of the studied HLA allele.

IMPORTANCE

Varicella-zoster virus can cause two distinct diseases: chickenpox (varicella) and shingles (herpes zoster). Varicella is a common disease in young children, while herpes zoster is more frequent in older individuals. A common complication of herpes zoster is postherpetic neuralgia, a persistent and debilitating pain that can remain months up to years after the resolution of the rash. In this study, we show that the relative affinity of HLA variants associated with higher postherpetic neuralgia risk for varicella-zoster virus peptides is lower than that of variants with a lower risk. These results provide new insight into the development of postherpetic neuralgia and strongly support the hypothesis that one of its possible underlying causes is a suboptimal anti-VZV immune response due to weak HLA binding peptide affinity.

Ultrasensitivity part II: multisite phosphorylation, stoichiometric inhibitors, and positive feedback

In this series of reviews, we are examining ultrasensitive responses, the switch-like input-output relationships that contribute to signal processing in a wide variety of signaling contexts. In the first part of this series, we explored one mechanism for generating ultrasensitivity, zero-order ultrasensitivity, where the saturation of two converting enzymes allows the output to switch from low to high over a tight range of input levels. In this second installment, we focus on three conceptually distinct mechanisms for ultrasensitivity: multisite phosphorylation, stoichiometric inhibitors, and positive feedback. We also examine several related mechanisms and concepts, including cooperativity, reciprocal regulation, coherent feed-forward regulation, and substrate competition, and provide several examples of signaling processes where these mechanisms are known or are suspected to be applicable.

Identification of a Mg2+-sensitive ORF in the 5'-leader of TRPM7 magnesium channel mRNA

TRPM7 is an essential and ubiquitous channel-kinase regulating cellular influx of Mg²⁺. Although TRPM7 mRNA is highly abundant, very small amount of the protein is detected in cells, suggesting post-transcriptional regulation of trpm7 gene expression. We found that TRPM7 mRNA 5′-leader contains two evolutionarily conserved upstream open reading frames that act together to drastically inhibit translation of the TRPM7 reading frame at high magnesium levels and ensure its optimal translation at low magnesium levels, when the activity of the channel-kinase is most required. The study provides the first example of magnesium channel synthesis being controlled by Mg²⁺ in higher eukaryotes.

Proximity biotinylation and affinity purification are complementary approaches for the interactome mapping of chromatin-associated protein complexes

Mapping protein-protein interactions for chromatin-associated proteins remains challenging. Here we explore the use of BioID, a proximity biotinylation approach in which a mutated biotin ligase (BirA*) is fused to a bait of interest, allowing for the local activation of biotin and subsequent biotinylation of proteins in the bait vicinity. BioID allowed for successful interactome mapping of core histones and members of the mediator complex. We explored the background signal produced by the BioID approach and found that using distinct types of controls increased the stringency of our statistical analysis with SAINTexpress. A direct comparison of BioID with our AP-MS protocol optimized for chromatin-associated protein complexes revealed that the approaches identified few shared interaction partners and enriched for distinct biological processes; yet, both approaches permitted the recovery of biologically meaningful interactions. While no clear bias could be observed for either technique toward protein complexes of particular functions, BioID allowed for the purification of proteins of lower cellular abundance. Finally, we were able to identify a strong association of MED4 with the centrosome by BioID and validated this finding by immunofluorescence. In summary, BioID complements AP-MS for the study of chromatin-associated protein complexes.

BIOLOGICAL SIGNIFICANCE

This manuscript describes the application of BioID, a proximity biotinylation approach, to chromatin-associated proteins, namely core histones and members of the mediator complex. We observed that BioID was successful at identifying known interaction partners for the baits tested, but also allowed novel putative interaction partners to be identified. By performing a detailed comparison of BioID versus a standard method for interactome mapping (affinity purification coupled to mass spectrometry, AP-MS), we show that the approaches were complementary, allowing for purification of different interaction partners. These interaction partners were different in the biological processes they are associated with, but also in their abundance. BioID represents a significant technical development in the field of chromatin research by expanding the search space for interactome mapping beyond what is possible with AP-MS. This article is part of a Special Issue entitled: Protein dynamics in health and disease. Guest Editors: Pierre Thibault and Anne-Claude Gingras.

A mass spectrometry view of stable and transient protein interactions

Through an impressive range of dynamic interactions, proteins succeed to carry out the majority of functions in a cell. These temporally and spatially regulated interactions provide the means through which one single protein can perform diverse functions and modulate different cellular pathways. Understanding the identity and nature of these interactions is therefore critical for defining protein functions and their contribution to health and disease processes. Here, we provide an overview of workflows that incorporate immunoaffinity purifications and quantitative mass spectrometry (frequently abbreviated as IP-MS or AP-MS) for characterizing protein-protein interactions. We discuss experimental aspects that should be considered when optimizing the isolation of a protein complex. As the presence of nonspecific associations is a concern in these experiments, we discuss the common sources of nonspecific interactions and present label-free and metabolic labeling mass spectrometry-based methods that can help determine the specificity of interactions. The effective regulation of cellular pathways and the rapid reaction to various environmental stresses rely on the formation of stable, transient, and fast-exchanging protein-protein interactions. While determining the exact nature of an interaction remains challenging, we review cross-linking and metabolic labeling approaches that can help address this important aspect of characterizing protein interactions and macromolecular assemblies.

Open tubular lab-on-column/mass spectrometry for targeted proteomics of nanogram sample amounts

A novel open tubular nanoproteomic platform featuring accelerated on-line protein digestion and high-resolution nano liquid chromatography mass spectrometry (LC-MS) has been developed. The platform features very narrow open tubular columns, and is hence particularly suited for limited sample amounts. For enzymatic digestion of proteins, samples are passed through a 20 µm inner diameter (ID) trypsin + endoproteinase Lys-C immobilized open tubular enzyme reactor (OTER). Resulting peptides are subsequently trapped on a monolithic pre-column and transferred on-line to a 10 µm ID porous layer open tubular (PLOT) liquid chromatography LC separation column. Wnt/ß-catenein signaling pathway (Wnt-pathway) proteins of potentially diagnostic value were digested+detected in targeted-MS/MS mode in small cell samples and tumor tissues within 120 minutes. For example, a potential biomarker Axin1 was identifiable in just 10 ng of sample (protein extract of ∼1,000 HCT15 colon cancer cells). In comprehensive mode, the current OTER-PLOT set-up could be used to identify approximately 1500 proteins in HCT15 cells using a relatively short digestion+detection cycle (240 minutes), outperforming previously reported on-line digestion/separation systems. The platform is fully automated utilizing common commercial instrumentation and parts, while the reactor and columns are simple to produce and have low carry-over. These initial results point to automated solutions for fast and very sensitive MS based proteomics, especially for samples of limited size.

CKM and LILRB5 are associated with serum levels of creatine kinase

BACKGROUND

Statins (HMG-CoA reductase inhibitors) are the most prescribed class of lipid-lowering drugs for the treatment and prevention of cardiovascular disease. Creatine kinase (CK) is a commonly used biomarker to assist in the diagnosis of statin-induced myotoxicity but the normal range of CK concentrations is wide, which limits its use as a diagnostic biomarker.

METHODS AND RESULTS

We conducted a genome-wide association study of serum CK levels in 3412 statin users. Patients were recruited in Quebec, Canada, and genotyped on Illumina Human610-Quad and an iSelect panel enriched for lipid homeostasis, hypertension, and drug metabolism genes. We found a strong association signal between serum levels of CK and the muscle CK (CKM) gene (rs11559024: P=3.69×10(-16); R(2)=0.02) and with the leukocyte immunoglobulin-like receptor subfamily B member 5 (LILRB5) gene (rs2361797: P=1.96×10(-10); R(2)=0.01). Genetic variants in those 2 genes were independently associated with CK levels in statin users. Results were successfully replicated in 5330 participants from the Montreal Heart Institute Biobank in statin users for CKM (rs11559024: P=4.32×10(-16); R(2)=0.02) and LILRB5 (rs12975366 P=4.45×10(-10); R(2)=0.01) and statin nonusers (P=4.08×10(-7), R(2)=0.01; P=3.17×10(-9), R(2)=0.02, respectively).

CONCLUSIONS

This is the first genome-wide study to report on the underlying genetic determinants of CK variation in a population of statin users. We found statistically significant association for variants in the CKM and LILRB5 genes.

Proteome-wide subcellular topologies of E. coli polypeptides database (STEPdb)

Cell compartmentalization serves both the isolation and the specialization of cell functions. After synthesis in the cytoplasm, over a third of all proteins are targeted to other subcellular compartments. Knowing how proteins are distributed within the cell and how they interact is a prerequisite for understanding it as a whole. Surface and secreted proteins are important pathogenicity determinants. Here we present the STEP database (STEPdb) that contains a comprehensive characterization of subcellular localization and topology of the complete proteome of Escherichia coli. Two widely used E. coli proteomes (K-12 and BL21) are presented organized into thirteen subcellular classes. STEPdb exploits the wealth of genetic, proteomic, biochemical, and functional information on protein localization, secretion, and targeting in E. coli, one of the best understood model organisms. Subcellular annotations were derived from a combination of bioinformatics prediction, proteomic, biochemical, functional, topological data and extensive literature re-examination that were refined through manual curation. Strong experimental support for the location of 1553 out of 4303 proteins was based on 426 articles and some experimental indications for another 526. Annotations were provided for another 320 proteins based on firm bioinformatic predictions. STEPdb is the first database that contains an extensive set of peripheral IM proteins (PIM proteins) and includes their graphical visualization into complexes, cellular functions, and interactions. It also summarizes all currently known protein export machineries of E. coli K-12 and pairs them, where available, with the secretory proteins that use them. It catalogs the Sec- and TAT-utilizing secretomes and summarizes their topological features such as signal peptides and transmembrane regions, transmembrane topologies and orientations. It also catalogs physicochemical and structural features that influence topology such as abundance, solubility, disorder, heat resistance, and structural domain families. Finally, STEPdb incorporates prediction tools for topology (TMHMM, SignalP, and Phobius) and disorder (IUPred) and implements the BLAST2STEP that performs protein homology searches against the STEPdb.

Basal activity of a PARP1-NuA4 complex varies dramatically across cancer cell lines

Poly(ADP-ribose) polymerases (PARPs) catalyze poly(ADP-ribose) addition onto proteins, an important posttranslational modification involved in transcription, DNA damage repair, and stem cell identity. Previous studies established the activation of PARP1 in response to DNA damage, but little is known about PARP1 regulation outside of DNA repair. We developed an assay for measuring PARP activity in cell lysates and found that the basal activity of PARP1 was highly variable across breast cancer cell lines, independent of DNA damage. Sucrose gradient fractionation demonstrated that PARP1 existed in at least three biochemically distinct states in both high- and low-activity lines. A discovered complex containing the NuA4 chromatin-remodeling complex and PARP1 was responsible for high basal PARP1 activity, and NuA4 subunits were required for this activity. These findings present a pathway for PARP1 activation and a direct link between PARP1 and chromatin remodeling outside of the DNA damage response.

The complex evolutionary dynamics of Hsp70s: a genomic and functional perspective

Hsp70 molecular chaperones are ubiquitous. By preventing aggregation, promoting folding, and regulating degradation, Hsp70s are major factors in the ability of cells to maintain proteostasis. Despite a wealth of functional information, little is understood about the evolutionary dynamics of Hsp70s. We undertook an analysis of Hsp70s in the fungal clade Ascomycota. Using the well-characterized 14 Hsp70s of Saccharomyces cerevisiae, we identified 491 orthologs from 53 genomes. Saccharomyces cerevisiae Hsp70s fall into seven subfamilies: four canonical-type Hsp70 chaperones (SSA, SSB, KAR, and SSC) and three atypical Hsp70s (SSE, SSZ, and LHS) that play regulatory roles, modulating the activity of canonical Hsp70 partners. Each of the 53 surveyed genomes harbored at least one member of each subfamily, and thus establishing these seven Hsp70s as units of function and evolution. Genomes of some species contained only one member of each subfamily that is only seven Hsp70s. Overall, members of each subfamily formed a monophyletic group, suggesting that each diversified from their corresponding ancestral gene present in the common ancestor of all surveyed species. However, the pattern of evolution varied across subfamilies. At one extreme, members of the SSB subfamily evolved under concerted evolution. At the other extreme, SSA and SSC subfamilies exhibited a high degree of copy number dynamics, consistent with a birth–death mode of evolution. KAR, SSE, SSZ, and LHS subfamilies evolved in a simple divergent mode with little copy number dynamics. Together, our data revealed that the evolutionary history of this highly conserved and ubiquitous protein family was surprising complex and dynamic.

Recovery from rapamycin: drug-insensitive activity of yeast target of rapamycin complex 1 (TORC1) supports residual proliferation that dilutes rapamycin among progeny cells

The target of rapamycin complex 1 (TORC1) is a key conserved regulator of eukaryotic cell growth. The xenobiotic rapamycin is a potent inhibitor of the yeast complex. Surprisingly, the EGO complex, a nonessential in vivo activator of TORC1, is somehow required for yeast cells to recover efficiently from a period of treatment with rapamycin. Why? Here, we found that rapamycin is only a partial inhibitor of TORC1. We confirmed that saturating amounts of rapamycin do not fully inhibit proliferation of wild-type cells, and we found that the residual proliferation in the presence of the drug is dependent on the EGO complex and on the activity of TORC1. We found that this residual TORC1-dependent proliferation is key to recovery from rapamycin treatment. First, the residual proliferation rate correlates with the ability of cells to recover from treatment. Second, the residual proliferation rate persists long after washout of the drug and until cells recover. Third, the total observable pool of cell-associated rapamycin is extremely stable and decreases only with increasing cell number after washout of the drug. Finally, consideration of the residual proliferation rate alone accurately and quantitatively accounts for the kinetics of recovery of wild-type cells and for the nature and severity of the ego- mutant defect. Overall, our results revealed that rapamycin is a partial inhibitor of yeast TORC1, that persistence of the drug limits recovery, and that rapamycin is not detoxified by yeast but is passively diluted among progeny cells because of residual proliferation.

Roles of type 1A topoisomerases in genome maintenance in Escherichia coli

In eukaryotes, type 1A topoisomerases (topos) act with RecQ-like helicases to maintain the stability of the genome. Despite having been the first type 1A enzymes to be discovered, much less is known about the involvement of the E. coli topo I (topA) and III (topB) enzymes in genome maintenance. These enzymes are thought to have distinct cellular functions: topo I regulates supercoiling and R-loop formation, and topo III is involved in chromosome segregation. To better characterize their roles in genome maintenance, we have used genetic approaches including suppressor screens, combined with microscopy for the examination of cell morphology and nucleoid shape. We show that topA mutants can suffer from growth-inhibitory and supercoiling-dependent chromosome segregation defects. These problems are corrected by deleting recA or recQ but not by deleting recJ or recO, indicating that the RecF pathway is not involved. Rather, our data suggest that RecQ acts with a type 1A topo on RecA-generated recombination intermediates because: 1-topo III overproduction corrects the defects and 2-recQ deletion and topo IIII overproduction are epistatic to recA deletion. The segregation defects are also linked to over-replication, as they are significantly alleviated by an oriC::aph suppressor mutation which is oriC-competent in topA null but not in isogenic topA⁺ cells. When both topo I and topo III are missing, excess supercoiling triggers growth inhibition that correlates with the formation of extremely long filaments fully packed with unsegregated and diffuse DNA. These phenotypes are likely related to replication from R-loops as they are corrected by overproducing RNase HI or by genetic suppressors of double topA rnhA mutants affecting constitutive stable DNA replication, dnaT::aph and rne::aph, which initiates from R-loops. Thus, bacterial type 1A topos maintain the stability of the genome (i) by preventing over-replication originating from oriC (topo I alone) and R-loops and (ii) by acting with RecQ.

DNA topoisomerases are ubiquitous enzymes that solve the topological problems associated with replication, transcription and recombination. Eukaryotic enzymes of the type 1A family work with RecQ-like helicases such as BLM and Sgs1 and are involved in genome maintenance. Interestingly, E. coli topo I, a type 1A enzyme and the first topoisomerase to be discovered, appears to have distinct cellular functions that are related to supercoiling regulation and to the inhibition of R-loop formation. Here we present data strongly suggesting that these cellular functions are required to inhibit inappropriate replication originating from either oriC, the normal origin of replication, or R-loops that can otherwise lead to severe chromosome segregation defects. Avoiding such inappropriate replication appears to be a key cellular function for genome maintenance, since the other E. coli type 1A topo, topo III, is also involved. Furthermore, our data suggest that bacterial type 1A topos, like their eukaryotic counterparts, can act with RecQ in genome maintenance. Altogether, our data provide new insight into the role of type 1A topos in genome maintenance and reveal an interplay between these enzymes and R-loops, structures that can also significantly affect the stability of the genome as recently shown in numerous studies.

Amyloid-associated activity contributes to the severity and toxicity of a prion phenotype

The self-assembly of alternative conformations of normal proteins into amyloid aggregates has been implicated in both the acquisition of new functions and in the appearance and progression of disease. However, while these amyloidogenic pathways are linked to the emergence of new phenotypes, numerous studies have uncoupled the accumulation of aggregates from their biological consequences, revealing currently underappreciated complexity in the determination of these traits. Here, to explore the molecular basis of protein-only phenotypes, we focused on the S. cerevisiae Sup35/[PSI⁺] prion, which confers a translation termination defect and expression level-dependent toxicity in its amyloid form. Our studies reveal that aggregated Sup35 retains its normal function as a translation release factor. However, fluctuations in the composition and size of these complexes specifically alter the level of this aggregate-associated activity and thereby the severity and toxicity of the amyloid state. Thus, amyloid heterogeneity is a crucial contributor to protein-only phenotypes.

Biosynthesis of a central intermediate in hydrogen sulfide metabolism by a novel human sulfurtransferase and its yeast ortholog

Human sulfide:quinone oxidoreductase (SQOR) catalyzes the conversion of H2S to thiosulfate, the first step in mammalian H2S metabolism. SQOR's inability to produce the glutathione persulfide (GSS(-)) substrate for sulfur dioxygenase (SDO) suggested that a thiosulfate:glutathione sulfurtransferase (TST) was required to provide the missing link between the SQOR and SDO reactions. Although TST could be purified from yeast, attempts to isolate the mammalian enzyme were not successful. We used bioinformatic approaches to identify genes likely to encode human TST (TSTD1) and its yeast ortholog (RDL1). Recombinant TSTD1 and RDL1 catalyze a predicted thiosulfate-dependent conversion of glutathione to GSS(-). Both enzymes contain a rhodanese homology domain and a single catalytically essential cysteine, which is converted to cysteine persulfide upon reaction with thiosulfate. GSS(-) is a potent inhibitor of TSTD1 and RDL1, as judged by initial rate accelerations and ≥25-fold lower Km values for glutathione observed in the presence of SDO. The combined action of GSS(-) and SDO is likely to regulate the biosynthesis of the reactive metabolite. SDO drives to completion p-toluenethiosulfonate:glutathione sulfurtransferase reactions catalyzed by TSTD1 and RDL1. The thermodynamic coupling of the irreversible SDO and reversible TST reactions provides a model for the physiologically relevant reaction with thiosulfate as the sulfane donor. The discovery of bacterial Rosetta Stone proteins that comprise fusions of SDO and TSTD1 provides phylogenetic evidence of the association of these enzymes. The presence of adjacent bacterial genes encoding SDO-TSTD1 fusion proteins and human-like SQORs suggests these prokaryotes and mammals exhibit strikingly similar pathways for H2S metabolism.

Mass-spectrometry-based draft of the human proteome

Proteomes are characterized by large protein-abundance differences, cell-type- and time-dependent expression patterns and post-translational modifications, all of which carry biological information that is not accessible by genomics or transcriptomics. Here we present a mass-spectrometry-based draft of the human proteome and a public, high-performance, in-memory database for real-time analysis of terabytes of big data, called ProteomicsDB. The information assembled from human tissues, cell lines and body fluids enabled estimation of the size of the protein-coding genome, and identified organ-specific proteins and a large number of translated lincRNAs (long intergenic non-coding RNAs). Analysis of messenger RNA and protein-expression profiles of human tissues revealed conserved control of protein abundance, and integration of drug-sensitivity data enabled the identification of proteins predicting resistance or sensitivity. The proteome profiles also hold considerable promise for analysing the composition and stoichiometry of protein complexes. ProteomicsDB thus enables navigation of proteomes, provides biological insight and fosters the development of proteomic technology.

Phenotype prediction based on genome-wide DNA methylation data

Background

DNA methylation (DNAm) has important regulatory roles in many biological processes and diseases. It is the only epigenetic mark with a clear mechanism of mitotic inheritance and the only one easily available on a genome scale. Aberrant cytosine-phosphate-guanine (CpG) methylation has been discussed in the context of disease aetiology, especially cancer. CpG hypermethylation of promoter regions is often associated with silencing of tumour suppressor genes and hypomethylation with activation of oncogenes.

Supervised principal component analysis (SPCA) is a popular machine learning method. However, in a recent application to phenotype prediction from DNAm data SPCA was inferior to the specific method EVORA.

Results

We present Model-Selection-SPCA (MS-SPCA), an enhanced version of SPCA. MS-SPCA applies several models that perform well in the training data to the test data and selects the very best models for final prediction based on parameters of the test data.

We have applied MS-SPCA for phenotype prediction from genome-wide DNAm data. CpGs used for prediction are selected based on the quantification of three features of their methylation (average methylation difference, methylation variation difference and methylation-age-correlation). We analysed four independent case–control datasets that correspond to different stages of cervical cancer: (i) cases currently cytologically normal, but will later develop neoplastic transformations, (ii, iii) cases showing neoplastic transformations and (iv) cases with confirmed cancer. The first dataset was split into several smaller case–control datasets (samples either Human Papilloma Virus (HPV) positive or negative). We demonstrate that cytology normal HPV+ and HPV- samples contain DNAm patterns which are associated with later neoplastic transformations. We present evidence that DNAm patterns exist in cytology normal HPV- samples that (i) predispose to neoplastic transformations after HPV infection and (ii) predispose to HPV infection itself. MS-SPCA performs significantly better than EVORA.

Conclusions

MS-SPCA can be applied to many classification problems. Additional improvements could include usage of more than one principal component (PC), with automatic selection of the optimal number of PCs. We expect that MS-SPCA will be useful for analysing recent larger DNAm data to predict future neoplastic transformations.

Visual account of protein investment in cellular functions

Proteomics techniques generate an avalanche of data and promise to satisfy biologists' long-held desire to measure absolute protein abundances on a genome-wide scale. However, can this knowledge be translated into a clearer picture of how cells invest their protein resources? This article aims to give a broad perspective on the composition of proteomes as gleaned from recent quantitative proteomics studies. We describe proteomaps, an approach for visualizing the composition of proteomes with a focus on protein abundances and functions. In proteomaps, each protein is shown as a polygon-shaped tile, with an area representing protein abundance. Functionally related proteins appear in adjacent regions. General trends in proteomes, such as the dominance of metabolism and protein production, become easily visible. We make interactive visualizations of published proteome datasets accessible at www.proteomaps.net. We suggest that evaluating the way protein resources are allocated by various organisms and cell types in different conditions will sharpen our understanding of how and why cells regulate the composition of their proteomes.

MOPED 2.5--an integrated multi-omics resource: multi-omics profiling expression database now includes transcriptomics data

Multi-omics data-driven scientific discovery crucially rests on high-throughput technologies and data sharing. Currently, data are scattered across single omics repositories, stored in varying raw and processed formats, and are often accompanied by limited or no metadata. The Multi-Omics Profiling Expression Database (MOPED, http://moped.proteinspire.org ) version 2.5 is a freely accessible multi-omics expression database. Continual improvement and expansion of MOPED is driven by feedback from the Life Sciences Community. In order to meet the emergent need for an integrated multi-omics data resource, MOPED 2.5 now includes gene relative expression data in addition to protein absolute and relative expression data from over 250 large-scale experiments. To facilitate accurate integration of experiments and increase reproducibility, MOPED provides extensive metadata through the Data-Enabled Life Sciences Alliance (DELSA Global, http://delsaglobal.org ) metadata checklist. MOPED 2.5 has greatly increased the number of proteomics absolute and relative expression records to over 500,000, in addition to adding more than four million transcriptomics relative expression records. MOPED has an intuitive user interface with tabs for querying different types of omics expression data and new tools for data visualization. Summary information including expression data, pathway mappings, and direct connection between proteins and genes can be viewed on Protein and Gene Details pages. These connections in MOPED provide a context for multi-omics expression data exploration. Researchers are encouraged to submit omics data which will be consistently processed into expression summaries. MOPED as a multi-omics data resource is a pivotal public database, interdisciplinary knowledge resource, and platform for multi-omics understanding.

Unraveling the specificities of the different human methionine sulfoxide reductases

The oxidation of free and protein-bound methionine into methionine sulfoxide is a frequently occurring modification caused by ROS. Most organisms express methionine sulfoxide reductases (MSR enzymes) to repair this potentially damaging modification. Humans express three different MSRB enzymes which reside in different cellular compartments. In this study, we have explored the specificity of the human MSRB enzymes both by in silico modeling and by experiments on oxidized peptides. We found that MSRB1 is the least specific MSRB enzyme, which is in agreement with the observation that MSRB1 is the only MSRB enzyme found in the cytosol and the nucleus, and therefore requires a broad specificity to reduce all possible substrates. MSRB2 and MSRB3, which are both found in mitochondria, are more specific but because of their co-occurrence they can likely repair all possible substrates.