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

Amino acid compositions contribute to the proteins' evolution under the influence of their abundances and genomic GC content

Inconsistent results on the association between evolutionary rates and amino acid composition of proteins have been reported in eukaryotes. However, there are few studies of how amino acid composition can influence evolutionary rates in bacteria. Thus, we constructed linear regression models between composition frequencies of amino acids and evolutionary rates for bacteria. Compositions of all amino acids can on average explain 21.5% of the variation in evolutionary rates among 273 investigated bacterial organisms. In five model organisms, amino acid composition contributes more to variation in evolutionary rates than protein abundance, and frequency of optimal codons. The contribution of individual amino acid composition to evolutionary rate varies among organisms. The closer the GC-content of genome to its maximum or minimum, the better the correlation between the amino acid content and the evolutionary rate of proteins would appear in that genome. The types of amino acids that significantly contribute to evolutionary rates can be grouped into GC-rich and AT-rich amino acids. Besides, the amino acid with high composition also contributes more to evolutionary rates than amino acid with low composition in proteome. In summary, amino acid composition significantly contributes to the rate of evolution in bacterial organisms and this in turn is impacted by GC-content.

Abundant plasma protein depletion using ammonium sulfate precipitation and Protein A affinity chromatography

Plasma is a highly valuable resource for biomarker research since it is easy obtainable and contains a high amount of information on patient health status. Although advancements in the field of proteomics enabled analysis of the plasma proteome, identification of low abundant proteins remains challenging due to high complexity and large dynamic range. In order to reduce the dynamic range of protein concentrations, a tandem depletion technique consisting of ammonium sulfate precipitation and Protein A affinity chromatography was developed. Using this method, 50% of albumin, together with other high abundant proteins such as alpha-1-antitrypsin, was depleted from the plasma sample at 20% to 40% ammonium sulfate saturation levels. In combination with immunoglobulin removal using a Protein A column, this technique delivered up to 40 new low- to medium abundance protein identifications when performing a shotgun mass spectrometry analysis. Compared to non-depleted plasma, 270 additional protein spots were observed during 2D-PAGE analysis. These results illustrate that this tandem depletion method is equivalent to commercial kits which are based on immune-affinity chromatography. Moreover, this method using Protein A immunoglobulin depletion was shown to be highly reproducible and a minimal amount of non-target proteins was depleted. The combination of ammonium sulfate precipitation and Protein A affinity chromatography offers a low cost, efficient, straightforward and reproducible alternative to commercial kits, with proteins remaining in native conformation, allowing protein activity and protein interaction studies.

Unification of Protein Abundance Datasets Yields a Quantitative Saccharomyces cerevisiae Proteome

Protein activity is the ultimate arbiter of function in most cellular pathways, and protein concentration is fundamentally connected to protein action. While the proteome of yeast has been subjected to the most comprehensive analysis of any eukaryote, existing datasets are difficult to compare, and there is no consensus abundance value for each protein. We evaluated 21 quantitative analyses of the S. cerevisiae proteome, normalizing and converting all measurements of protein abundance into the intuitive measurement of absolute molecules per cell. We estimate the cellular abundance of 92% of the proteins in the yeast proteome and assess the variation in each abundance measurement. Using our protein abundance dataset, we find that a global response to diverse environmental stresses is not detected at the level of protein abundance, we find that protein tags have only a modest effect on protein abundance, and we identify proteins that are differentially regulated at the mRNA abundance, mRNA translation, and protein abundance levels.

Ribosome biogenesis in cancer: new players and therapeutic avenues

The ribosome is a complex molecular machine composed of numerous distinct proteins and nucleic acids and is responsible for protein synthesis in every living cell. Ribosome biogenesis is one of the most multifaceted and energy- demanding processes in biology, involving a large number of assembly and maturation factors, the functions of which are orchestrated by multiple cellular inputs, including mitogenic signals and nutrient availability. Although causal associations between inherited mutations affecting ribosome biogenesis and elevated cancer risk have been established over the past decade, mechanistic data have emerged suggesting a broader role for dysregulated ribosome biogenesis in the development and progression of most spontaneous cancers. In this Opinion article, we highlight the most recent findings that provide new insights into the molecular basis of ribosome biogenesis in cancer and offer our perspective on how these observations present opportunities for the design of new targeted cancer treatments.

Defining the Mammalian Peroxisomal Proteome

The current view on peroxisomes has changed dramatically from being human cell oddities to vital organelles that host several key metabolic pathways. To fulfil over 50 different enzymatic functions, human peroxisomes host either unique peroxisomal proteins or dual-localized proteins. The identification and characterization of the complete peroxisomal proteome in humans is important for diagnosis and treatment of patients with peroxisomal disorders as well as for uncovering novel peroxisomal functions and regulatory modules. Hence, here we compiled a comprehensive list of mammalian peroxisomal and peroxisome-associated proteins by curating results of several quantitative and non-quantitative proteomic studies together with entries in the UniProtKB and Compartments knowledge channel databases. Our analysis gives a holistic view on the mammalian peroxisomal proteome and brings to light potential new peroxisomal and peroxisome-associated proteins. We believe that this dataset, represents a valuable surrogate map of the human peroxisomal proteome.

Expitope 2.0: a tool to assess immunotherapeutic antigens for their potential cross-reactivity against naturally expressed proteins in human tissues

BACKGROUND

Adoptive immunotherapy offers great potential for treating many types of cancer but its clinical application is hampered by cross-reactive T cell responses in healthy human tissues, representing serious safety risks for patients. We previously developed a computational tool called Expitope for assessing cross-reactivity (CR) of antigens based on tissue-specific gene expression. However, transcript abundance only indirectly indicates protein expression. The recent availability of proteome-wide human protein abundance information now facilitates a more direct approach for CR prediction. Here we present a new version 2.0 of Expitope, which computes all naturally possible epitopes of a peptide sequence and the corresponding CR indices using both protein and transcript abundance levels weighted by a proposed hierarchy of importance of various human tissues.

RESULTS

We tested the tool in two case studies: The first study quantitatively assessed the potential CR of the epitopes used for cancer immunotherapy. The second study evaluated HLA-A*02:01-restricted epitopes obtained from the Immune Epitope Database for different disease groups and demonstrated for the first time that there is a high variation in the background CR depending on the disease state of the host: compared to a healthy individual the CR index is on average two-fold higher for the autoimmune state, and five-fold higher for the cancer state.

CONCLUSIONS

The ability to predict potential side effects in normal tissues helps in the development and selection of safer antigens, enabling more successful immunotherapy of cancer and other diseases.

Emerging whole-cell modeling principles and methods

Whole-cell computational models aim to predict cellular phenotypes from genotype by representing the entire genome, the structure and concentration of each molecular species, each molecular interaction, and the extracellular environment. Whole-cell models have great potential to transform bioscience, bioengineering, and medicine. However, numerous challenges remain to achieve whole-cell models. Nevertheless, researchers are beginning to leverage recent progress in measurement technology, bioinformatics, data sharing, rule-based modeling, and multi-algorithmic simulation to build the first whole-cell models. We anticipate that ongoing efforts to develop scalable whole-cell modeling tools will enable dramatically more comprehensive and more accurate models, including models of human cells.

Elucidating the 16S rRNA 3' boundaries and defining optimal SD/aSD pairing in Escherichia coli and Bacillus subtilis using RNA-Seq data

Bacterial translation initiation is influenced by base pairing between the Shine-Dalgarno (SD) sequence in the 5' UTR of mRNA and the anti-SD (aSD) sequence at the free 3' end of the 16S rRNA (3' TAIL) due to: 1) the SD/aSD sequence binding location and 2) SD/aSD binding affinity. In order to understand what makes an SD/aSD interaction optimal, we must define: 1) terminus of the 3' TAIL and 2) extent of the core aSD sequence within the 3' TAIL. Our approach to characterize these components in Escherichia coli and Bacillus subtilis involves 1) mapping the 3' boundary of the mature 16S rRNA using high-throughput RNA sequencing (RNA-Seq), and 2) identifying the segment within the 3' TAIL that is strongly preferred in SD/aSD pairing. Using RNA-Seq data, we resolve previous discrepancies in the reported 3' TAIL in B. subtilis and recovered the established 3' TAIL in E. coli. Furthermore, we extend previous studies to suggest that both highly and lowly expressed genes favor SD sequences with intermediate binding affinity, but this trend is exclusive to SD sequences that complement the core aSD sequences defined herein.

New insights into the membrane association mechanism of the glycosyltransferase WaaG from Escherichia coli

Monotopic glycosyltransferases (GTs) interact with membranes via electrostatic interactions. The N-terminal domain is permanently anchored to the membrane while the membrane interaction of the C-terminal domain is believed to be weaker so that it undergoes a functionally relevant conformational change upon donor or acceptor binding. Here, we studied the applicability of this model to the glycosyltransferase WaaG. WaaG is involved in the synthesis of lipopolysaccharides (LPS) in Gram-negative bacteria and was previously categorized as a monotopic GT. We analyzed the binding of WaaG to membranes by stopped-flow fluorescence and NMR diffusion experiments. We find that electrostatic interactions are required to bind WaaG to membranes while mere hydrophobic interactions are not sufficient. WaaG senses the membrane's surface charge density but there is no preferential binding to specific anionic lipids. However, the binding is weaker than expected for monotopic GTs but similar to peripheral GTs. Therefore, WaaG may be a peripheral GT and this could be of functional relevance in vivo since LPS synthesis occurs only when WaaG is membrane-bound. We could not observe a C-terminal domain movement under our experimental conditions.

Multiple marker abundance profiling: combining selected reaction monitoring and data-dependent acquisition for rapid estimation of organelle abundance in subcellular samples

Measuring changes in protein or organelle abundance in the cell is an essential, but challenging aspect of cell biology. Frequently-used methods for determining organelle abundance typically rely on detection of a very few marker proteins, so are unsatisfactory. In silico estimates of protein abundances from publicly available protein spectra can provide useful standard abundance values but contain only data from tissue proteomes, and are not coupled to organelle localization data. A new protein abundance score, the normalized protein abundance scale (NPAS), expands on the number of scored proteins and the scoring accuracy of lower-abundance proteins in Arabidopsis. NPAS was combined with subcellular protein localization data, facilitating quantitative estimations of organelle abundance during routine experimental procedures. A suite of targeted proteomics markers for subcellular compartment markers was developed, enabling independent verification of in silico estimates for relative organelle abundance. Estimation of relative organelle abundance was found to be reproducible and consistent over a range of tissues and growth conditions. In silico abundance estimations and localization data have been combined into an online tool, multiple marker abundance profiling, available in the SUBA4 toolbox (http://suba.live).

Tagging and Enriching Proteins Enables Cell-Specific Proteomics

Cell-specific proteomics in multicellular systems and whole animals is a promising approach to understand the differentiated functions of cells and tissues. Here, we extend our stochastic orthogonal recoding of translation (SORT) approach for the co-translational tagging of proteomes with a cyclopropene-containing amino acid in response to diverse codons in genetically targeted cells, and create a tetrazine-biotin probe containing a cleavable linker that offers a way to enrich and identify tagged proteins. We demonstrate that SORT with enrichment, SORT-E, efficiently recovers and enriches SORT tagged proteins and enables specific identification of enriched proteins via mass spectrometry, including low-abundance proteins. We show that tagging at distinct codons enriches overlapping, but distinct sets of proteins, suggesting that tagging at more than one codon enhances proteome coverage. Using SORT-E, we accomplish cell-specific proteomics in the fly. These results suggest that SORT-E will enable the definition of cell-specific proteomes in animals during development, disease progression, and learning and memory.

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A tetrazine-biotin probe containing a cleavable linker was created

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Proteomes labeled with cyclopropene amino acids were enriched and identified

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Proteome coverage is increased by targeting the amino acids to multiple codons

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Cell-specific proteomics was accomplished in the fly

A conserved NAD+ binding pocket that regulates protein-protein interactions during aging

DNA repair is essential for life, yet its efficiency declines with age for reasons that are unclear. Numerous proteins possess Nudix homology domains (NHDs) that have no known function. We show that NHDs are NAD⁺ (oxidized form of nicotinamide adenine dinucleotide) binding domains that regulate protein-protein interactions. The binding of NAD⁺ to the NHD domain of DBC1 (deleted in breast cancer 1) prevents it from inhibiting PARP1 [poly(adenosine diphosphate-ribose) polymerase], a critical DNA repair protein. As mice age and NAD⁺ concentrations decline, DBC1 is increasingly bound to PARP1, causing DNA damage to accumulate, a process rapidly reversed by restoring the abundance of NAD⁺ Thus, NAD⁺ directly regulates protein-protein interactions, the modulation of which may protect against cancer, radiation, and aging.

Transcription termination factor Rho and microbial phenotypic heterogeneity

Populations of genetically identical microorganisms exhibit high degree of cell-to-cell phenotypic diversity even when grown in uniform environmental conditions. Heterogeneity is a genetically determined trait, which ensures bacterial adaptation and survival in the ever changing environmental conditions. Fluctuations in gene expression (noise) at the level of transcription initiation largely contribute to cell-to-cell variability within population. Not surprisingly, the analyses of the mechanisms driving phenotypic heterogeneity are mainly focused on the activity of promoters and transcriptional factors. Less attention is currently given to a role of intrinsic and factor-dependent transcription terminators. Here, we discuss recent advances in understanding the regulatory role of the multi-functional transcription termination factor Rho, the major inhibitor of pervasive transcription in bacteria and the emerging global regulator of gene expression. We propose that termination activity of Rho might be among the mechanisms by which cells manage the intensity of transcriptional noise, thus affecting population heterogeneity.

Intrinsic protein disorder reduces small-scale gene duplicability

Whereas the rate of gene duplication is relatively high, only certain duplications survive the filter of natural selection and can contribute to genome evolution. However, the reasons why certain genes can be retained after duplication whereas others cannot remain largely unknown. Many proteins contain intrinsically disordered regions (IDRs), whose structures fluctuate between alternative conformational states. Due to their high flexibility, IDRs often enable protein–protein interactions and are the target of post-translational modifications. Intrinsically disordered proteins (IDPs) have characteristics that might either stimulate or hamper the retention of their encoding genes after duplication. On the one hand, IDRs may enable functional diversification, thus promoting duplicate retention. On the other hand, increased IDP availability is expected to result in deleterious unspecific interactions. Here, we interrogate the proteomes of human, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Arabidopsis thaliana and Escherichia coli, in order to ascertain the impact of protein intrinsic disorder on gene duplicability. We show that, in general, proteins encoded by duplicated genes tend to be less disordered than those encoded by singletons. The only exception is proteins encoded by ohnologs, which tend to be more disordered than those encoded by singletons or genes resulting from small-scale duplications. Our results indicate that duplication of genes encoding IDPs outside the context of whole-genome duplication (WGD) is often deleterious, but that IDRs facilitate retention of duplicates in the context of WGD. We discuss the potential evolutionary implications of our results.

Cytosolic Protein Vms1 Links Ribosome Quality Control to Mitochondrial and Cellular Homeostasis

Eukaryotic cells have evolved extensive protein quality-control mechanisms to remove faulty translation products. Here, we show that yeast cells continually produce faulty mitochondrial polypeptides that stall on the ribosome during translation but are imported into the mitochondria. The cytosolic protein Vms1, together with the E3 ligase Ltn1, protects against the mitochondrial toxicity of these proteins and maintains cell viability under respiratory conditions. In the absence of these factors, stalled polypeptides aggregate after import and sequester critical mitochondrial chaperone and translation machinery. Aggregation depends on C-terminal alanyl/threonyl sequences (CAT-tails) that are attached to stalled polypeptides on 60S ribosomes by Rqc2. Vms1 binds to 60S ribosomes at the mitochondrial surface and antagonizes Rqc2, thereby facilitating import, impeding aggregation, and directing aberrant polypeptides to intra-mitochondrial quality control. Vms1 is a key component of a rescue pathway for ribosome-stalled mitochondrial polypeptides that are inaccessible to ubiquitylation due to coupling of translation and translocation.

Fructose-1,6-bisphosphate couples glycolytic flux to activation of Ras

Yeast and cancer cells share the unusual characteristic of favoring fermentation of sugar over respiration. We now reveal an evolutionary conserved mechanism linking fermentation to activation of Ras, a major regulator of cell proliferation in yeast and mammalian cells, and prime proto-oncogene product. A yeast mutant (tps1∆) with overactive influx of glucose into glycolysis and hyperaccumulation of Fru1,6bisP, shows hyperactivation of Ras, which causes its glucose growth defect by triggering apoptosis. Fru1,6bisP is a potent activator of Ras in permeabilized yeast cells, likely acting through Cdc25. As in yeast, glucose triggers activation of Ras and its downstream targets MEK and ERK in mammalian cells. Biolayer interferometry measurements show that physiological concentrations of Fru1,6bisP stimulate dissociation of the pure Sos1/H-Ras complex. Thermal shift assay confirms direct binding to Sos1, the mammalian ortholog of Cdc25. Our results suggest that the Warburg effect creates a vicious cycle through Fru1,6bisP activation of Ras, by which enhanced fermentation stimulates oncogenic potency.

Yeast and cancer cells both favor sugar fermentation in aerobic conditions. Here the authors describe a conserved mechanism from yeast to mammals where the glycolysis intermediate fructose-1,6-bisphosphate binds Cdc25/Sos1 and couples increased glycolytic flux to increased Ras proto-oncoprotein activity.

Selection on start codons in prokaryotes and potential compensatory nucleotide substitutions

Reconstruction of the evolution of start codons in 36 groups of closely related bacterial and archaeal genomes reveals purifying selection affecting AUG codons. The AUG starts are replaced by GUG and especially UUG significantly less frequently than expected under the neutral expectation derived from the frequencies of the respective nucleotide triplet substitutions in non-coding regions and in 4-fold degenerate sites. Thus, AUG is the optimal start codon that is actively maintained by purifying selection. However, purifying selection on start codons is significantly weaker than the selection on the same codons in coding sequences, although the switches between the codons result in conservative amino acid substitutions. The only exception is the AUG to UUG switch that is strongly selected against among start codons. Selection on start codons is most pronounced in evolutionarily conserved, highly expressed genes. Mutation of the start codon to a sub-optimal form (GUG or UUG) tends to be compensated by mutations in the Shine-Dalgarno sequence towards a stronger translation initiation signal. Together, all these findings indicate that in prokaryotes, translation start signals are subject to weak but significant selection for maximization of initiation rate and, consequently, protein production.

Formation of a TBX20-CASZ1 protein complex is protective against dilated cardiomyopathy and critical for cardiac homeostasis

By the age of 40, one in five adults without symptoms of cardiovascular disease are at risk for developing congestive heart failure. Within this population, dilated cardiomyopathy (DCM) remains one of the leading causes of disease and death, with nearly half of cases genetically determined. Though genetic and high throughput sequencing-based approaches have identified sporadic and inherited mutations in a multitude of genes implicated in cardiomyopathy, how combinations of asymptomatic mutations lead to cardiac failure remains a mystery. Since a number of studies have implicated mutations of the transcription factor TBX20 in congenital heart diseases, we investigated the underlying mechanisms, using an unbiased systems-based screen to identify novel, cardiac-specific binding partners. We demonstrated that TBX20 physically and genetically interacts with the essential transcription factor CASZ1. This interaction is required for survival, as mice heterozygous for both Tbx20 and Casz1 die post-natally as a result of DCM. A Tbx20 mutation associated with human familial DCM sterically interferes with the TBX20-CASZ1 interaction and provides a physical basis for how this human mutation disrupts normal cardiac function. Finally, we employed quantitative proteomic analyses to define the molecular pathways mis-regulated upon disruption of this novel complex. Collectively, our proteomic, biochemical, genetic, and structural studies suggest that the physical interaction between TBX20 and CASZ1 is required for cardiac homeostasis, and further, that reduction or loss of this critical interaction leads to DCM. This work provides strong evidence that DCM can be inherited through a digenic mechanism.

A molecular understanding of cardiomyocyte development is an essential goal for improving clinical approaches to CHD. While TBX20 is an essential transcription factor for heart development and its disease relevance is well established, many fundamental questions remain about the mechanism of TBX20 function. Principle among these is how TBX20 mutations associated with adult dilated cardiomyopathy circumvent (DCM) the essential embryonic requirement for TBX20 in heart development. Here we report using an integrated approach that TBX20 complexes with the cardiac transcription factor CASZ1 in vivo. We confirmed TBX20 and CASZ1 interact biochemically and genetically, and show mice heterozygous for both Tbx20 and Casz1 die, beginning at 4 to 8 weeks post birth, exhibiting hallmarks of DCM. Interestingly, the human mutant TBX20^F256I bypasses the early essential requirement for TBX20 but leads to DCM. We report here that TBX20^F256I disrupts the TBX20-CASZ1 interaction, ascribing clinical relevance to this protein complex. Further, by using quantitative proteomics we have identified the molecular pathways altered in TBX20-CASZ1-mediated DCM. Together, these results identify a novel interaction between TBX20 and CASZ1 that is essential for maintaining cardiac homeostasis and imply that DCM can be inherited through a digenic mechanism.

Localized redox relays as a privileged mode of cytoplasmic hydrogen peroxide signaling

Hydrogen peroxide (H2O2) is a key signaling agent. Its best characterized signaling actions in mammalian cells involve the early oxidation of thiols in cytoplasmic phosphatases, kinases and transcription factors. However, these redox targets are orders of magnitude less H2O2-reactive and abundant than cytoplasmic peroxiredoxins. How can they be oxidized in a signaling time frame? Here we investigate this question using computational reaction-diffusion models of H2O2 signaling. The results show that at H2O2 supply rates commensurate with mitogenic signaling a H2O2 concentration gradient with a length scale of a few tenths of μm is established. Even near the supply sites H2O2 concentrations are far too low to oxidize typical targets in an early mitogenic signaling time frame. Furthermore, any inhibition of the peroxiredoxin or increase in H2O2 supply able to drastically increase the local H2O2 concentration would collapse the concentration gradient and/or cause an extensive oxidation of the peroxiredoxins I and II, inconsistent with experimental observations. In turn, the local concentrations of peroxiredoxin sulfenate and disulfide forms exceed those of H2O2 by several orders of magnitude. Redox targets reacting with these forms at rate constants much lower than that for, say, thioredoxin could be oxidized within seconds. Moreover, the spatial distribution of the concentrations of these peroxiredoxin forms allows them to reach targets within 1 μm from the H2O2 sites while maintaining signaling localized. The recruitment of peroxiredoxins to specific sites such as caveolae can dramatically increase the local concentrations of the sulfenic and disulfide forms, thus further helping these species to outcompete H2O2 for the oxidation of redox targets. Altogether, these results suggest that H2O2 signaling is mediated by localized redox relays whereby peroxiredoxins are oxidized to sulfenate and disulfide forms at H2O2 supply sites and these forms in turn oxidize the redox targets near these sites.

Immunoproteomics technologies in the discovery of autoantigens in autoimmune diseases

Proteomics technologies are often used for the identification of protein targets of the immune system. Here, we discuss the immunoproteomics technologies used for the discovery of autoantigens in autoimmune diseases where immune system dysregulation plays a central role in disease onset and progression. These autoantigens and associated autoantibodies can be used as potential biomarkers for disease diagnostics, prognostics and predicting/monitoring drug responsiveness (theranostics). Here, we compare a variety of methods such as mass spectrometry (MS)-based [serological proteome analysis (SERPA), antibody mediated identification of antigens (AMIDA), circulating immune complexome (CIC) analysis, surface enhanced laser desorption/ionization-time of flight (SELDI-TOF)], nucleic acid based serological analysis of antigens by recombinant cDNA expression cloning (SEREX), phage immunoprecipitation sequencing (PhIP-seq) and array-based immunoscreening (proteomic microarrays), luciferase immunoprecipitation systems (LIPS), nucleic acid programmable protein array (NAPPA) methods. We also review the relevance of immunoproteomic data generated in the last 10 years, with a focus on the aforementioned MS based methods.

The Role of +4U as an Extended Translation Termination Signal in Bacteria

Termination efficiency of stop codons depends on the first 3' flanking (+4) base in bacteria and eukaryotes. In both Escherichia coli and Saccharomyces cerevisiae, termination read-through is reduced in the presence of +4U; however, the molecular mechanism underlying +4U function is poorly understood. Here, we perform comparative genomics analysis on 25 bacterial species (covering Actinobacteria, Bacteriodetes, Cyanobacteria, Deinococcus-Thermus, Firmicutes, Proteobacteria, and Spirochaetae) with bioinformatics approaches to examine the influence of +4U in bacterial translation termination by contrasting highly- and lowly-expressed genes (HEGs and LEGs, respectively). We estimated gene expression using the recently formulated Index of Translation Elongation, ITE, and identified stop codon near-cognate transfer RNAs (tRNAs) from well-annotated genomes. We show that +4U was consistently overrepresented in UAA-ending HEGs relative to LEGs. The result is consistent with the interpretation that +4U enhances termination mainly for UAA. Usage of +4U decreases in GC-rich species where most stop codons are UGA and UAG, with few UAA-ending genes, which is expected if UAA usage in HEGs drives up +4U usage. In HEGs, +4U usage increases significantly with abundance of UAA nc_tRNAs (near-cognate tRNAs that decode codons differing from UAA by a single nucleotide), particularly those with a mismatch at the first stop codon site. UAA is always the preferred stop codon in HEGs, and our results suggest that UAAU is the most efficient translation termination signal in bacteria.

Influence of node abundance on signaling network state and dynamics analyzed by mass cytometry

Signaling networks are key regulators of cellular function. Although the concentrations of signaling proteins are perturbed in disease states, such as cancer, and are modulated by drug therapies, our understanding of how such changes shape the properties of signaling networks is limited. Here we couple mass cytometry-based single-cell analysis with overexpression of tagged signaling proteins to study the dependence of signaling relationships and dynamics on protein node abundance. Focusing on the epidermal growth factor receptor (EGFR) signaling network in HEK293T cells, we analyze 20 signaling proteins during a one hour EGF stimulation time course using a panel of 35 antibodies. Data analysis with BP-R², a measure that quantifies complex signaling relationships, reveals abundance-dependent network states and identifies novel signaling relationships. Further, we show that upstream signaling proteins have abundance-dependent effects on downstream signaling dynamics. Our approach elucidates the influence of node abundance on signal transduction networks and will further our understanding of signaling in health and disease.

Protein Bioinformatics Databases and Resources

Many publicly available data repositories and resources have been developed to support protein-related information management, data-driven hypothesis generation, and biological knowledge discovery. To help researchers quickly find the appropriate protein-related informatics resources, we present a comprehensive review (with categorization and description) of major protein bioinformatics databases in this chapter. We also discuss the challenges and opportunities for developing next-generation protein bioinformatics databases and resources to support data integration and data analytics in the Big Data era.

Drift Barriers to Quality Control When Genes Are Expressed at Different Levels

Gene expression is imperfect, sometimes leading to toxic products. Solutions take two forms: globally reducing error rates, or ensuring that the consequences of erroneous expression are relatively harmless. The latter is optimal, but because it must evolve independently at so many loci, it is subject to a stringent "drift barrier"-a limit to how weak the effects of a deleterious mutation s can be, while still being effectively purged by selection, expressed in terms of the population size N of an idealized population such that purging requires s < -1/N In previous work, only large populations evolved the optimal local solution, small populations instead evolved globally low error rates, and intermediate populations were bistable, with either solution possible. Here, we take into consideration the fact that the effectiveness of purging varies among loci, because of variation in gene expression level, and variation in the intrinsic vulnerabilities of different gene products to error. The previously found dichotomy between the two kinds of solution breaks down, replaced by a gradual transition as a function of population size. In the extreme case of a small enough population, selection fails to maintain even the global solution against deleterious mutations, explaining the nonmonotonic relationship between effective population size and transcriptional error rate that was recently observed in experiments on Escherichia coli, Caenorhabditis elegans, and Buchnera aphidicola.

Depletion of Shine-Dalgarno Sequences Within Bacterial Coding Regions Is Expression Dependent

Efficient and accurate protein synthesis is crucial for organismal survival in competitive environments. Translation efficiency (the number of proteins translated from a single mRNA in a given time period) is the combined result of differential translation initiation, elongation, and termination rates. Previous research identified the Shine-Dalgarno (SD) sequence as a modulator of translation initiation in bacterial genes, while codon usage biases are frequently implicated as a primary determinant of elongation rate variation. Recent studies have suggested that SD sequences within coding sequences may negatively affect translation elongation speed, but this claim remains controversial. Here, we present a metric to quantify the prevalence of SD sequences in coding regions. We analyze hundreds of bacterial genomes and find that the coding sequences of highly expressed genes systematically contain fewer SD sequences than expected, yielding a robust correlation between the normalized occurrence of SD sites and protein abundances across a range of bacterial taxa. We further show that depletion of SD sequences within ribosomal protein genes is correlated with organismal growth rates, supporting the hypothesis of strong selection against the presence of these sequences in coding regions and suggesting their association with translation efficiency in bacteria.

Proteome complexity and the forces that drive proteome imbalance

The cellular proteome is a complex microcosm of structural and regulatory networks that requires continuous surveillance and modification to meet the dynamic needs of the cell. It is therefore crucial that the protein flux of the cell remains in balance to ensure proper cell function. Genetic alterations that range from chromosome imbalance to oncogene activation can affect the speed, fidelity and capacity of protein biogenesis and degradation systems, which often results in proteome imbalance. An improved understanding of the causes and consequences of proteome imbalance is helping to reveal how these systems can be targeted to treat diseases such as cancer.

Essentiality Is a Strong Determinant of Protein Rates of Evolution during Mutation Accumulation Experiments in Escherichia coli

The Neutral Theory of Molecular Evolution is considered the most powerful theory to understand the evolutionary behavior of proteins. One of the main predictions of this theory is that essential proteins should evolve slower than dispensable ones owing to increased selective constraints. Comparison of genomes of different species, however, has revealed only small differences between the rates of evolution of essential and nonessential proteins. In some analyses, these differences vanish once confounding factors are controlled for, whereas in other cases essentiality seems to have an independent, albeit small, effect. It has been argued that comparing relatively distant genomes may entail a number of limitations. For instance, many of the genes that are dispensable in controlled lab conditions may be essential in some of the conditions faced in nature. Moreover, essentiality can change during evolution, and rates of protein evolution are simultaneously shaped by a variety of factors, whose individual effects are difficult to isolate. Here, we conducted two parallel mutation accumulation experiments in Escherichia coli, during 5,500–5,750 generations, and compared the genomes at different points of the experiments. Our approach (a short-term experiment, under highly controlled conditions) enabled us to overcome many of the limitations of previous studies. We observed that essential proteins evolved substantially slower than nonessential ones during our experiments. Strikingly, rates of protein evolution were only moderately affected by expression level and protein length.

FOXO/DAF-16 Activation Slows Down Turnover of the Majority of Proteins in C. elegans

Most aging hypotheses assume the accumulation of damage, resulting in gradual physiological decline and, ultimately, death. Avoiding protein damage accumulation by enhanced turnover should slow down the aging process and extend the lifespan. However, lowering translational efficiency extends rather than shortens the lifespan in C. elegans. We studied turnover of individual proteins in the long-lived daf-2 mutant by combining SILeNCe (stable isotope labeling by nitrogen in Caenorhabditiselegans) and mass spectrometry. Intriguingly, the majority of proteins displayed prolonged half-lives in daf-2, whereas others remained unchanged, signifying that longevity is not supported by high protein turnover. This slowdown was most prominent for translation-related and mitochondrial proteins. In contrast, the high turnover of lysosomal hydrolases and very low turnover of cytoskeletal proteins remained largely unchanged. The slowdown of protein dynamics and decreased abundance of the translational machinery may point to the importance of anabolic attenuation in lifespan extension, as suggested by the hyperfunction theory.

Protective and Pathogenic Roles of CD8+ T Lymphocytes in Murine Orientia tsutsugamushi Infection

T cells are known to contribute to immune protection against scrub typhus, a potentially fatal infection caused by the obligate intracellular bacterium Orientia (O.) tsutsugamushi. However, the contribution of CD8+ T cells to protection and pathogenesis during O. tsutsugamushi infection is still unknown. Using our recently developed BALB/c mouse model that is based on footpad inoculation of the human-pathogenic Karp strain, we show that activated CD8+ T cells infiltrate spleen and lung during the third week of infection. Depletion of CD8+ T cells with monoclonal antibodies resulted in uncontrolled pathogen growth and mortality. Adoptive transfer of CD8+ T cells from infected animals protected naïve BALB/c mice from lethal outcome of intraperitoneal challenge. In C57Bl/6 mice, the pulmonary lymphocyte compartment showed an increased percentage of CD8+ T cells for at least 135 days post O. tsutsugamushi infection. Depletion of CD8+ T cells at 84 days post infection caused reactivation of bacterial growth. In CD8+ T cell-deficient beta 2-microglobulin knockout mice, bacterial replication was uncontrolled, and all mice succumbed to the infection, despite higher serum IFN-γ levels and stronger macrophage responses in liver and lung. Moreover, we show that CD8+ T cells but not NKT cells were required for hepatocyte injury: elevated concentrations of serum alanine aminotransferase and infection-induced subcapsular necrotic liver lesions surrounded by macrophages were found in C57Bl/6 and CD1d-deficient mice, but not in beta 2-microglobulin knockout mice. In the lungs, peribronchial macrophage infiltrations also depended on CD8+ T cells. In summary, our results demonstrate that CD8+ T cells restrict growth of O. tsutsugamushi during acute and persistent infection, and are required to protect from lethal infections in BALB/c and C57BL/6 mice. However, they also elicit specific pathologic tissue lesions in liver and lung.

Uniform spatial distribution of collagen fibril radii within tendon implies local activation of pC-collagen at individual fibrils

Collagen fibril cross-sectional radii show no systematic variation between the interior and the periphery of fibril bundles, indicating an effectively constant rate of collagen incorporation into fibrils throughout the bundle. Such spatially homogeneous incorporation constrains the extracellular diffusion of collagen precursors from sources at the bundle boundary to sinks at the growing fibrils. With a coarse-grained diffusion equation we determine stringent bounds, using parameters extracted from published experimental measurements of tendon development. From the lack of new fibril formation after birth, we further require that the concentration of diffusing precursors stays below the critical concentration for fibril nucleation. We find that the combination of the diffusive bound, which requires larger concentrations to ensure homogeneous fibril radii, and lack of nucleation, which requires lower concentrations, is only marginally consistent with fully processed collagen using conservative bounds. More realistic bounds may leave no consistent concentrations. Therefore, we propose that unprocessed pC-collagen diffuses from the bundle periphery followed by local C-proteinase activity and subsequent collagen incorporation at each fibril. We suggest that C-proteinase is localized within bundles, at fibril surfaces, during radial fibrillar growth. The much greater critical concentration of pC-collagen, as compared to fully processed collagen, then provides broad consistency between homogeneous fibril radii and the lack of fibril nucleation during fibril growth.

Human Sirtuin 2 Localization, Transient Interactions, and Impact on the Proteome Point to Its Role in Intracellular Trafficking

Human sirtuin 2 (SIRT2) is an NAD⁺-dependent deacetylase that primarily functions in the cytoplasm, where it can regulate α-tubulin acetylation levels. SIRT2 is linked to cancer progression, neurodegeneration, and infection with bacteria or viruses. However, the current knowledge about its interactions and the means through which it exerts its functions has remained limited. Here, we aimed to gain a better understanding of its cellular functions by characterizing SIRT2 subcellular localization, the identity and relative stability of its protein interactions, and its impact on the proteome of primary human fibroblasts. To assess the relative stability of SIRT2 interactions, we used immunoaffinity purification in conjunction with both label-free and metabolic labeling quantitative mass spectrometry. In addition to the expected associations with cytoskeleton proteins, including its known substrate TUBA1A, our results reveal that SIRT2 specifically interacts with proteins functioning in membrane trafficking, secretory processes, and transcriptional regulation. By quantifying their relative stability, we found most interactions to be transient, indicating a dynamic SIRT2 environment. We discover that SIRT2 localizes to the ER-Golgi intermediate compartment (ERGIC), and that this recruitment requires an intact ER-Golgi trafficking pathway. Further expanding these findings, we used microscopy and interaction assays to establish the interaction and coregulation of SIRT2 with liprin-β1 scaffolding protein (PPFiBP1), a protein with roles in focal adhesions disassembly. As SIRT2 functions may be accomplished via interactions, enzymatic activity, and transcriptional regulation, we next assessed the impact of SIRT2 levels on the cellular proteome. SIRT2 knockdown led to changes in the levels of proteins functioning in membrane trafficking, including some of its interaction partners. Altogether, our study expands the knowledge of SIRT2 cytoplasmic functions to define a previously unrecognized involvement in intracellular trafficking pathways, which may contribute to its roles in cellular homeostasis and human diseases.

ER arrival sites for COPI vesicles localize to hotspots of membrane trafficking

COPI-coated vesicles mediate retrograde membrane traffic from the cis-Golgi to the endoplasmic reticulum (ER) in all eukaryotic cells. However, it is still unknown whether COPI vesicles fuse everywhere or at specific sites with the ER membrane. Taking advantage of the circumstance that the vesicles still carry their coat when they arrive at the ER, we have visualized active ER arrival sites (ERAS) by monitoring contact between COPI coat components and the ER-resident Dsl tethering complex using bimolecular fluorescence complementation (BiFC). ERAS form punctate structures near Golgi compartments, clearly distinct from ER exit sites. Furthermore, ERAS are highly polarized in an actin and myosin V-dependent manner and are localized near hotspots of plasma membrane expansion. Genetic experiments suggest that the COPI•Dsl BiFC complexes recapitulate the physiological interaction between COPI and the Dsl complex and that COPI vesicles are mistargeted in dsl1 mutants. We conclude that the Dsl complex functions in confining COPI vesicle fusion sites.

High resolution laser mass spectrometry bioimaging

Mass spectrometry imaging (MSI) was introduced more than five decades ago with secondary ion mass spectrometry (SIMS) and a decade later with laser desorption/ionization (LDI) mass spectrometry (MS). Large biomolecule imaging by matrix-assisted laser desorption/ionization (MALDI) was developed in the 1990s and ambient laser MS a decade ago. Although SIMS has been capable of imaging with a moderate mass range at sub-micrometer lateral resolution from its inception, laser MS requires additional effort to achieve a lateral resolution of 10μm or below which is required to image at the size scale of single mammalian cells. This review covers untargeted large biomolecule MSI using lasers for desorption/ionization or laser desorption and post-ionization. These methods include laser microprobe (LDI) MSI, MALDI MSI, laser ambient and atmospheric pressure MSI, and near-field laser ablation MS. Novel approaches to improving lateral resolution are discussed, including oversampling, beam shaping, transmission geometry, reflective and through-hole objectives, microscope mode, and near-field optics.

Regulation of the Na+/K+-ATPase Ena1 Expression by Calcineurin/Crz1 under High pH Stress: A Quantitative Study

Regulated expression of the Ena1 Na+-ATPase is a crucial event for adaptation to high salt and/or alkaline pH stress in the budding yeast Saccharomyces cerevisiae. ENA1 expression is under the control of diverse signaling pathways, including that mediated by the calcium-regulatable protein phosphatase calcineurin and its downstream transcription factor Crz1. We present here a quantitative study of the expression of Ena1 in response to alkalinization of the environment and we analyze the contribution of Crz1 to this response. Experimental data and mathematical models substantiate the existence of two stress-responsive Crz1-binding sites in the ENA1 promoter and estimate that the contribution of Crz1 to the early response of the ENA1 promoter is about 60%. The models suggest the existence of a second input with similar kinetics, which would be likely mediated by high pH-induced activation of the Snf1 kinase.

A Concentration-Dependent Liquid Phase Separation Can Cause Toxicity upon Increased Protein Expression

Multiple human diseases are associated with a liquid-to-solid phase transition resulting in the formation of amyloid fibers or protein aggregates. Here, we present an alternative mechanism for cellular toxicity based on a concentration-dependent liquid-liquid demixing. Analyzing proteins that are toxic when their concentration is increased in yeast reveals that they share physicochemical properties with proteins that participate in physiological liquid-liquid demixing in the cell. Increasing the concentration of one of these proteins indeed results in the formation of cytoplasmic foci with liquid properties. Demixing occurs at the onset of toxicity and titrates proteins and mRNAs from the cytoplasm. Focus formation is reversible, and resumption of growth occurs as the foci dissolve as protein concentration falls. Preventing demixing abolishes the dosage sensitivity of the protein. We propose that triggering inappropriate liquid phase separation may be an important cause of dosage sensitivity and a determinant of human disease.

A theoretical estimate for nucleotide sugar demand towards Chinese Hamster Ovary cellular glycosylation

Glycosylation greatly influences the safety and efficacy of many of the highest-selling recombinant therapeutic proteins (rTPs). In order to define optimal cell culture feeding strategies that control rTP glycosylation, it is necessary to know how nucleotide sugars (NSs) are consumed towards host cell and rTP glycosylation. Here, we present a theoretical framework that integrates the reported glycoproteome of CHO cells, the number of N-linked and O-GalNAc glycosylation sites on individual host cell proteins (HCPs), and the carbohydrate content of CHO glycosphingolipids to estimate the demand of NSs towards CHO cell glycosylation. We have identified the most abundant N-linked and O-GalNAc CHO glycoproteins, obtained the weighted frequency of N-linked and O-GalNAc glycosites across the CHO cell proteome, and have derived stoichiometric coefficients for NS consumption towards CHO cell glycosylation. By combining the obtained stoichiometric coefficients with previously reported data for specific growth and productivity of CHO cells, we observe that the demand of NSs towards glycosylation is significant and, thus, is required to better understand the burden of glycosylation on cellular metabolism. The estimated demand of NSs towards CHO cell glycosylation can be used to rationally design feeding strategies that ensure optimal and consistent rTP glycosylation.

An organelle-specific protein landscape identifies novel diseases and molecular mechanisms

Cellular organelles provide opportunities to relate biological mechanisms to disease. Here we use affinity proteomics, genetics and cell biology to interrogate cilia: poorly understood organelles, where defects cause genetic diseases. Two hundred and seventeen tagged human ciliary proteins create a final landscape of 1,319 proteins, 4,905 interactions and 52 complexes. Reverse tagging, repetition of purifications and statistical analyses, produce a high-resolution network that reveals organelle-specific interactions and complexes not apparent in larger studies, and links vesicle transport, the cytoskeleton, signalling and ubiquitination to ciliary signalling and proteostasis. We observe sub-complexes in exocyst and intraflagellar transport complexes, which we validate biochemically, and by probing structurally predicted, disruptive, genetic variants from ciliary disease patients. The landscape suggests other genetic diseases could be ciliary including 3M syndrome. We show that 3M genes are involved in ciliogenesis, and that patient fibroblasts lack cilia. Overall, this organelle-specific targeting strategy shows considerable promise for Systems Medicine.

Mutations in proteins that localize to primary cilia cause devastating diseases, yet the primary cilium is a poorly understood organelle. Here the authors use interaction proteomics to identify a network of human ciliary proteins that provides new insights into several biological processes and diseases.

Dual mechanisms regulate the recruitment of spindle assembly checkpoint proteins to the budding yeast kinetochore

Quantitative knowledge of the recruitment of spindle assembly checkpoint (SAC) proteins by the kinetochore is essential to understanding the mechanisms that regulate protein recruitment and hence the strength of the SAC. Here this recruitment is quantified, and novel mechanisms are identified that strongly modulate SAC protein recruitment by the kinetochore.

Recruitment of spindle assembly checkpoint (SAC) proteins by an unattached kinetochore leads to SAC activation. This recruitment is licensed by the Mps1 kinase, which phosphorylates the kinetochore protein Spc105 at one or more of its six MELT repeats. Spc105 then recruits the Bub3-Bub1 and Mad1-Mad2 complexes, which produce the inhibitory signal that arrests cell division. The strength of this signal depends, in part, on the number of Bub3-Bub1 and Mad1-Mad2 molecules that Spc105 recruits. Therefore regulation of this recruitment will influence SAC signaling. To understand this regulation, we established the physiological binding curves that describe the binding of Bub3-Bub1 and Mad1-Mad2 to the budding yeast kinetochore. We find that the binding of both follows the mass action law. Mps1 likely phosphorylates all six MELT repeats of Spc105. However, two mechanisms prevent Spc105 from recruiting six Bub3-Bub1 molecules: low Bub1 abundance and hindrance in the binding of more than one Bub3-Bub1 molecule to the same Spc105. Surprisingly, the kinetochore recruits two Mad1-Mad2 heterotetramers for every Bub3-Bub1 molecule. Finally, at least three MELT repeats per Spc105 are needed for accurate chromosome segregation. These data reveal that kinetochore-intrinsic and -extrinsic mechanisms influence the physiological operation of SAC signaling, potentially to maximize chromosome segregation accuracy.

Genic insights from integrated human proteomics in GeneCards

GeneCards is a one-stop shop for searchable human gene annotations (http://www.genecards.org/). Data are automatically mined from ∼120 sources and presented in an integrated web card for every human gene. We report the application of recent advances in proteomics to enhance gene annotation and classification in GeneCards. First, we constructed the Human Integrated Protein Expression Database (HIPED), a unified database of protein abundance in human tissues, based on the publically available mass spectrometry (MS)-based proteomics sources ProteomicsDB, Multi-Omics Profiling Expression Database, Protein Abundance Across Organisms and The MaxQuant DataBase. The integrated database, residing within GeneCards, compares favourably with its individual sources, covering nearly 90% of human protein-coding genes. For gene annotation and comparisons, we first defined a protein expression vector for each gene, based on normalized abundances in 69 normal human tissues. This vector is portrayed in the GeneCards expression section as a bar graph, allowing visual inspection and comparison. These data are juxtaposed with transcriptome bar graphs. Using the protein expression vectors, we further defined a pairwise metric that helps assess expression-based pairwise proximity. This new metric for finding functional partners complements eight others, including sharing of pathways, gene ontology (GO) terms and domains, implemented in the GeneCards Suite. In parallel, we calculated proteome-based differential expression, highlighting a subset of tissues that overexpress a gene and subserving gene classification. This textual annotation allows users of VarElect, the suite’s next-generation phenotyper, to more effectively discover causative disease variants. Finally, we define the protein–RNA expression ratio and correlation as yet another attribute of every gene in each tissue, adding further annotative information. The results constitute a significant enhancement of several GeneCards sections and help promote and organize the genome-wide structural and functional knowledge of the human proteome.

Database URL: http://www.genecards.org/

Positive Selection and Centrality in the Yeast and Fly Protein-Protein Interaction Networks

Proteins within a molecular network are expected to be subject to different selective pressures depending on their relative hierarchical positions. However, it is not obvious what genes within a network should be more likely to evolve under positive selection. On one hand, only mutations at genes with a relatively high degree of control over adaptive phenotypes (such as those encoding highly connected proteins) are expected to be “seen” by natural selection. On the other hand, a high degree of pleiotropy at these genes is expected to hinder adaptation. Previous analyses of the human protein-protein interaction network have shown that genes under long-term, recurrent positive selection (as inferred from interspecific comparisons) tend to act at the periphery of the network. It is unknown, however, whether these trends apply to other organisms. Here, we show that long-term positive selection has preferentially targeted the periphery of the yeast interactome. Conversely, in flies, genes under positive selection encode significantly more connected and central proteins. These observations are not due to covariation of genes' adaptability and centrality with confounding factors. Therefore, the distribution of proteins encoded by genes under recurrent positive selection across protein-protein interaction networks varies from one species to another.

Operon Gene Order Is Optimized for Ordered Protein Complex Assembly

The assembly of heteromeric protein complexes is an inherently stochastic process in which multiple genes are expressed separately into proteins, which must then somehow find each other within the cell. Here, we considered one of the ways by which prokaryotic organisms have attempted to maximize the efficiency of protein complex assembly: the organization of subunit-encoding genes into operons. Using structure-based assembly predictions, we show that operon gene order has been optimized to match the order in which protein subunits assemble. Exceptions to this are almost entirely highly expressed proteins for which assembly is less stochastic and for which precisely ordered translation offers less benefit. Overall, these results show that ordered protein complex assembly pathways are of significant biological importance and represent a major evolutionary constraint on operon gene organization.

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Operon-encoded subunits tend to be encoded by neighboring genes and form large interfaces

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Operon gene order is often optimized for the order of protein complex assembly

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Exceptions are mostly highly expressed proteins for which assembly is less stochastic

2016 update of the PRIDE database and its related tools

The PRoteomics IDEntifications (PRIDE) database is one of the world-leading data repositories of mass spectrometry (MS)-based proteomics data. Since the beginning of 2014, PRIDE Archive (http://www.ebi.ac.uk/pride/archive/) is the new PRIDE archival system, replacing the original PRIDE database. Here we summarize the developments in PRIDE resources and related tools since the previous update manuscript in the Database Issue in 2013. PRIDE Archive constitutes a complete redevelopment of the original PRIDE, comprising a new storage backend, data submission system and web interface, among other components. PRIDE Archive supports the most-widely used PSI (Proteomics Standards Initiative) data standard formats (mzML and mzIdentML) and implements the data requirements and guidelines of the ProteomeXchange Consortium. The wide adoption of ProteomeXchange within the community has triggered an unprecedented increase in the number of submitted data sets (around 150 data sets per month). We outline some statistics on the current PRIDE Archive data contents. We also report on the status of the PRIDE related stand-alone tools: PRIDE Inspector, PRIDE Converter 2 and the ProteomeXchange submission tool. Finally, we will give a brief update on the resources under development 'PRIDE Cluster' and 'PRIDE Proteomes', which provide a complementary view and quality-scored information of the peptide and protein identification data available in PRIDE Archive.

Exploring the potential of public proteomics data

In a global effort for scientific transparency, it has become feasible and good practice to share experimental data supporting novel findings. Consequently, the amount of publicly available MS-based proteomics data has grown substantially in recent years. With some notable exceptions, this extensive material has however largely been left untouched. The time has now come for the proteomics community to utilize this potential gold mine for new discoveries, and uncover its untapped potential. In this review, we provide a brief history of the sharing of proteomics data, showing ways in which publicly available proteomics data are already being (re-)used, and outline potential future opportunities based on four different usage types: use, reuse, reprocess, and repurpose. We thus aim to assist the proteomics community in stepping up to the challenge, and to make the most of the rapidly increasing amount of public proteomics data.

Wide-Ranging Effects of the Yeast Ptc1 Protein Phosphatase Acting Through the MAPK Kinase Mkk1

The Saccharomyces cerevisiae type 2C protein phosphatase Ptc1 is required for a wide variety of cellular functions, although only a few cellular targets have been identified. A genetic screen in search of mutations in protein kinase-encoding genes able to suppress multiple phenotypic traits caused by the ptc1 deletion yielded a single gene, MKK1, coding for a MAPK kinase (MAPKK) known to activate the cell-wall integrity (CWI) Slt2 MAPK. In contrast, mutation of the MKK1 paralog, MKK2, had a less significant effect. Deletion of MKK1 abolished the increased phosphorylation of Slt2 induced by the absence of Ptc1 both under basal and CWI pathway stimulatory conditions. We demonstrate that Ptc1 acts at the level of the MAPKKs of the CWI pathway, but only the Mkk1 kinase activity is essential for ptc1 mutants to display high Slt2 activation. We also show that Ptc1 is able to dephosphorylate Mkk1 in vitro. Our results reveal the preeminent role of Mkk1 in signaling through the CWI pathway and strongly suggest that hyperactivation of Slt2 caused by upregulation of Mkk1 is at the basis of most of the phenotypic defects associated with lack of Ptc1 function.

Development of viable TAP-tagged dengue virus for investigation of host-virus interactions in viral replication

Dengue virus (DENV) is a mosquito-borne flavivirus responsible for life-threatening dengue haemorrhagic fever (DHF) and dengue shock syndrome (DSS). The viral replication machinery containing the core non-structural protein 5 (NS5) is implicated in severe dengue symptoms but molecular details remain obscure. To date, studies seeking to catalogue and characterize interaction networks between viral NS5 and host proteins have been limited to the yeast two-hybrid system, computational prediction and co-immunoprecipitation (IP) of ectopically expressed NS5. However, these traditional approaches do not reproduce a natural course of infection in which a number of DENV NS proteins colocalize and tightly associate during the replication process. Here, we demonstrate the development of a recombinant DENV that harbours a TAP tag in NS5 to study host-virus interactions in vivo. We show that our engineered DENV was infective in several human cell lines and that the tags were stable over multiple viral passages, suggesting negligible structural and functional disturbance of NS5. We further provide proof-of-concept for the use of rationally tagged virus by revealing a high confidence NS5 interaction network in human hepatic cells. Our analysis uncovered previously unrecognized hnRNP complexes and several low-abundance fatty acid metabolism genes, which have been implicated in the viral life cycle. This study sets a new standard for investigation of host-flavivirus interactions.

Single file diffusion into a semi-infinite tube

We investigate single file diffusion (SFD) of large particles entering a semi-infinite tube, such as luminal diffusion of proteins into microtubules or flagella. While single-file effects have no impact on the evolution of particle density, we report significant single-file effects for individually tracked tracer particle motion. Both exact and approximate ordering statistics of particles entering semi-infinite tubes agree well with our stochastic simulations. Considering initially empty semi-infinite tubes, with particles entering at one end starting from an initial time t = 0, tracked particles are initially super-diffusive after entering the system, but asymptotically diffusive at later times. For finite time intervals, the ratio of the net displacement of individual single-file particles to the average displacement of untracked particles is reduced at early times and enhanced at later times. When each particle is numbered, from the first to enter (n = 1) to the most recent (n = N), we find good scaling collapse of this distance ratio for all n. Experimental techniques that track individual particles, or local groups of particles, such as photo-activation or photobleaching of fluorescently tagged proteins, should be able to observe these single-file effects. However, biological phenomena that depend on local concentration, such as flagellar extension or luminal enzymatic activity, should not exhibit single-file effects.