Analysing the yeast complexome-the Complex Portal rising to the challenge.
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ABSTRACT:
SUBMITTER: Meldal BHM
PROVIDER: S-EPMC8034636 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundProteins in organisms, rather than act alone, usually form protein complexes to perform cellular functions. We analyze the topological network structure of protein complexes and their component proteins in the budding yeast in terms of the bipartite network and its projections, where the complexes and proteins are its two distinct components. Compared to conventional protein-protein interaction networks, the networks from the protein complexes show more homogeneous structures than those of the binary protein interactions, implying the formation of complexes that cause a relatively more uniform number of interaction partners. In addition, we suggest a new optimization method to determine the abundance and function of protein complexes, based on the information of their global organization. Estimating abundance and biological functions is of great importance for many researches, by providing a quantitative description of cell behaviors, instead of just a "catalogues" of the lists of protein interactions.ResultsWith our new optimization method, we present genome-wide assignments of abundance and biological functions for complexes, as well as previously unknown abundance and functions of proteins, which can provide significant information for further investigations in proteomics. It is strongly supported by a number of biologically relevant examples, such as the relationship between the cytoskeleton proteins and signal transduction and the metabolic enzyme Eno2's involvement in the cell division process.ConclusionsWe believe that our methods and findings are applicable not only to the specific area of proteomics, but also to much broader areas of systems biology with the concept of optimization principle.
| S-EPMC3169507 | biostudies-literature
Project description:The standard treatment for tuberculosis (TB) is lengthy, complex, and significantly toxic. Drug development for TB has stagnated for decades, but in recent years renewed commitment and coordinated research has generated a modest pipeline of new drugs that hold the potential to make treatment more effective, shorter, less complex, and less toxic in the near future. With a particular focus on bedaquiline (TMC207), the first anti-TB drug of a novel class to be approved by the US Food and Drug Administration (FDA) in 40 years, this review summarizes the recent evidence behind new developments in TB treatment. Novel drug classes, repurposed drugs, and host-directed therapies are reviewed. In parallel to these exciting developments in drug discovery, we propose that it is crucial to develop more rapid and comprehensive diagnostics that will allow the timely selection of the best regimen for individual patients.
| S-EPMC4237170 | biostudies-literature
Project description:The majority of cellular processes are carried out by protein complexes. Various size fractionation methods have previously been combined with mass spectrometry to identify protein complexes. However, most of these approaches lack the quantitative information which is required to understand how changes of protein complex abundance and composition affect metabolic fluxes. In this paper we present a proof of concept approach to quantitatively study the complexome in the model plant Arabidopsis thaliana at the end of the day (ED) and the end of the night (EN). We show that size-fractionation of native protein complexes by Clear-Native-PAGE (CN-PAGE), coupled with mass spectrometry can be used to establish abundance profiles along the molecular weight gradient. Furthermore, by deconvoluting complex protein abundance profiles, we were able to drastically improve the clustering of protein profiles. To identify putative interaction partners, and ultimately protein complexes, our approach calculates the Euclidian distance between protein profile pairs. Acceptable threshold values are based on a cut-off that is optimized by a receiver-operator characteristic (ROC) curve analysis. Our approach shows low technical variation and can easily be adapted to study in the complexome in any biological system.
| S-EPMC6687828 | biostudies-literature
Project description:Dehalococcoides mccartyi strain CBDB1 is a slow growing strictly anaerobic microorganism dependent on halogenated compounds as terminal electron acceptor for anaerobic respiration. Indications have been described that the membrane-bound proteinaceous organohalide respiration complex of strain CBDB1 is functional without quinone-mediated electron transfer. We here study this multi-subunit protein complex in depth in regard to participating protein subunits and interactions between the subunits using blue native gel electrophoresis coupled to mass spectrometric label-free protein quantification. Applying three different solubilization modes to detach the respiration complex from the membrane we describe different solubilization snapshots of the organohalide respiration complex. The results demonstrate the existence of a two-subunit hydrogenase module loosely binding to the rest of the complex, tight binding of the subunit HupX to OmeA and OmeB, predicted to be the two subunits of a molybdopterin-binding redox subcomplex, to form a second module, and the presence of two distinct reductive dehalogenase module variants with different sizes. In our data we obtained biochemical evidence for the specificity between a reductive dehalogenase RdhA (CbdbA80) and its membrane anchor protein RdhB (CbdbB3). We also observed weak interactions between the reductive dehalogenase and the hydrogenase module suggesting a not yet recognized contact surface between these two modules. Especially an interaction between the two integral membrane subunits OmeB and RdhB seems to promote the integrity of the complex. With the different solubilization strengths we observe successive disintegration of the complex into its subunits. The observed architecture would allow the association of different reductive dehalogenase modules RdhA/RdhB with the other two protein complex modules when the strain is growing on different electron acceptors. In the search for other respiratory complexes in strain CBDB1 the remarkable result is not the detection of a standard ATPase but the absence of any other abundant membrane complex although an 11-subunit version of complex I (Nuo) is encoded in the genome.
| S-EPMC6005880 | biostudies-literature
Project description:BACKGROUND:PLINK 1 is a widely used open-source C/C++ toolset for genome-wide association studies (GWAS) and research in population genetics. However, the steady accumulation of data from imputation and whole-genome sequencing studies has exposed a strong need for faster and scalable implementations of key functions, such as logistic regression, linkage disequilibrium estimation, and genomic distance evaluation. In addition, GWAS and population-genetic data now frequently contain genotype likelihoods, phase information, and/or multiallelic variants, none of which can be represented by PLINK 1's primary data format. FINDINGS:To address these issues, we are developing a second-generation codebase for PLINK. The first major release from this codebase, PLINK 1.9, introduces extensive use of bit-level parallelism, [Formula: see text]-time/constant-space Hardy-Weinberg equilibrium and Fisher's exact tests, and many other algorithmic improvements. In combination, these changes accelerate most operations by 1-4 orders of magnitude, and allow the program to handle datasets too large to fit in RAM. We have also developed an extension to the data format which adds low-overhead support for genotype likelihoods, phase, multiallelic variants, and reference vs. alternate alleles, which is the basis of our planned second release (PLINK 2.0). CONCLUSIONS:The second-generation versions of PLINK will offer dramatic improvements in performance and compatibility. For the first time, users without access to high-end computing resources can perform several essential analyses of the feature-rich and very large genetic datasets coming into use.
| S-EPMC4342193 | biostudies-literature
Project description:The genomic sequences of many important Triticeae crop species are hard to assemble and analyse due to their large genome sizes, (in part) polyploid genomes and high repeat content. Recently, the draft genomes of barley and bread wheat were reported thanks to cost-efficient and fast NGS technologies. The genome of barley is estimated to be 5 Gb in size whereas the genome of bread wheat accounts for 17 Gb and harbours an allo-hexaploid genome. Direct assembly of the sequence reads and access to the gene content is hampered by the repeat content. As a consequence, novel strategies and data analysis concepts had to be developed to provide much-needed whole genome sequence surveys and access to the gene repertoires. Here we describe some analytical strategies that now enable structuring of massive NGS data generated and pave the way towards structured and ordered sequence data and gene order. Specifically we report on the GenomeZipper, a synteny driven approach to order and structure NGS survey sequences of grass genomes that lack a physical map. In addition, to access and analyse the gene repertoire of allo-hexaploid bread wheat from the raw sequence reads, a reference-guided approach was developed utilizing representative genes from rice, Brachypodium distachyon, sorghum and barley. Stringent sub-assembly on the reference genes prevented collapsing of homeologous wheat genes and allowed to estimate gene retention rate and determine gene family sizes. Genomic sequences from the wheat sub-genome progenitors enabled to discriminate a large number of sub-assemblies between the wheat A, B or D sub-genome using machine learning algorithms. Many of the concepts outlined here can readily be applied to other complex plant and non-plant genomes.
| S-EPMC3847682 | biostudies-literature
Project description:Precision medicine, the concept that specific treatments can be targeted to groups of individuals with specific genetic, cellular, or molecular features, is a key aspect of modern healthcare, and its use is rapidly expanding. In diabetes, the application of precision medicine has been demonstrated in monogenic disease, where sulphonylureas are used to treat patients with neonatal diabetes due to mutations in ATP-dependent potassium (KATP) channel genes. However, diabetes is highly heterogeneous, both between and within polygenic and monogenic subtypes. Making the correct diagnosis and using the correct treatment from diagnosis can be challenging for clinicians, but it is crucial to prevent long-term morbidity and mortality. To facilitate precision medicine in diabetes, research is needed to develop a better understanding of disease heterogeneity and its impact on potential treatments for specific subtypes. Animal models have been used in diabetes research, but they are not translatable to humans in the majority of cases. Advances in molecular genetics and functional laboratory techniques and availability and sharing of large population data provide exciting opportunities for human studies. This review will map the key elements of future diabetes research in humans and its potential for clinical translation to promote precision medicine in all diabetes subtypes.
| S-EPMC6288579 | biostudies-other
Project description:The Complex Portal (www.ebi.ac.uk/complexportal) is a manually curated, encyclopaedic database of macromolecular complexes with known function from a range of model organisms. It summarizes complex composition, topology and function along with links to a large range of domain-specific resources (i.e. wwPDB, EMDB and Reactome). Since the last update in 2019, we have produced a first draft complexome for Escherichia coli, maintained and updated that of Saccharomyces cerevisiae, added over 40 coronavirus complexes and increased the human complexome to over 1100 complexes that include approximately 200 complexes that act as targets for viral proteins or are part of the immune system. The display of protein features in ComplexViewer has been improved and the participant table is now colour-coordinated with the nodes in ComplexViewer. Community collaboration has expanded, for example by contributing to an analysis of putative transcription cofactors and providing data accessible to semantic web tools through Wikidata which is now populated with manually curated Complex Portal content through a new bot. Our data license is now CC0 to encourage data reuse. Users are encouraged to get in touch, provide us with feedback and send curation requests through the 'Support' link.
| S-EPMC8689886 | biostudies-literature
Project description:INTRODUCTION:Prescription drug abuse is a major public health problem in rural and suburban areas of the United States, however its emergence in large urban settings with endemic injection drug use remains understudied. We examined temporal trends in injection drug use initiation and mortality among people who inject drugs (PWID) in Baltimore, Maryland. METHODS:Data were derived from the baseline assessment of PWID enrolled in a community-based cohort study with longitudinal follow-up for mortality assessment. PWID were recruited from 2005-2008 (N = 1,008) and 2015-2018 (N = 737). We compared characteristics by birth cohort (before/after 1980) and type of drug initiated (prescription opioids, prescription non-opioids, non-injection illicit drugs, or injection drugs). We calculated standardized mortality ratios (SMR) using the US general population as the reference. RESULTS:PWID born after 1980 were more likely to initiate drug use with prescription opioids and non-opioids and had higher levels of polysubstance prior to injection initiation, compared to individuals born before 1980. Overall mortality was high: 2.59 per 100 person-years (95% CI: 2.27-2.95 per 100 person-years). Compared to the US population, the highest SMRs were observed among participants between 40-44 years of age, with especially high mortality among women in this age group (SMR:29.89, 95% CI: 15.24-44.54). CONCLUSIONS:Mirroring national trends, the profile of PWID in Baltimore has changed with increased prescription drug abuse and high levels of polysubstance use among younger PWID. Interventions need to reach those using prescription drugs early after initiation of use in order to reduce transition to injecting. Urgent attention is warranted to address premature mortality, particularly among middle-aged and female PWID.
| S-EPMC6398863 | biostudies-literature
Project description:BackgroundThe yeast Saccharomyces cerevisiae responds to amino acid starvation by inducing the transcription factor Gcn4. This is mainly mediated via a translational control mechanism dependent upon the translation initiation eIF2·GTP·Met-tRNAiMet ternary complex, and the four short upstream open reading frames (uORFs) in its 5' mRNA leader. These uORFs act to attenuate GCN4 mRNA translation under normal conditions. During amino acid starvation, levels of ternary complex are reduced. This overcomes the GCN4 translation attenuation effect via a scanning/reinitiation control mechanism dependent upon uORF spacing.ResultsUsing published experimental data, we have developed and validated a probabilistic formulation of GCN4 translation using the Chemical Master Equation (Model 1). Model 1 explains GCN4 translation's nonlinear dependency upon uORF placements, and predicts that an as yet unidentified factor, which was proposed to regulate GCN4 translation under some conditions, only has pronounced effects upon GCN4 translation when intercistronic distances are unnaturally short. A simpler Model 2 that does not include this unidentified factor could well represent the regulation of a natural GCN4 mRNA. Using parameter values optimised for this algebraic Model 2, we performed stochastic simulations by Gillespie algorithm to investigate the distribution of ribosomes in different sections of GCN4 mRNA under distinct conditions. Our simulations demonstrated that ribosomal loading in the 5'-untranslated region is mainly determined by the ratio between the rates of 5'-initiation and ribosome scanning, but was not significantly affected by rate of ternary complex binding. Importantly, the translation rate for codons starved of cognate tRNAs is predicted to be the most significant contributor to the changes in ribosomal loading in the coding region under repressing and derepressing conditions.ConclusionsOur integrated probabilistic Models 1 and 2 explained GCN4 translation and helped to elucidate the role of a yet unidentified factor. The ensuing stochastic simulations evaluated different factors that may impact on the translation of GCN4 mRNA, and integrated translation status with ribosomal density.
| S-EPMC3201031 | biostudies-literature