The proteome landscape of the kingdoms of life.

Proteins carry out the vast majority of functions in all biological domains, but for technological reasons their large-scale investigation has lagged behind the study of genomes. Since the first essentially complete eukaryotic proteome was reported1, advances in mass-spectrometry-based proteomics2 have enabled increasingly comprehensive identification and quantification of the human proteome3-6. However, there have been few comparisons across species7,8, in stark contrast with genomics initiatives9. Here we use an advanced proteomics workflow-in which the peptide separation step is performed by a microstructured and extremely reproducible chromatographic system-for the in-depth study of 100 taxonomically diverse organisms. With two million peptide and 340,000 stringent protein identifications obtained in a standardized manner, we double the number of proteins with solid experimental evidence known to the scientific community. The data also provide a large-scale case study for sequence-based machine learning, as we demonstrate by experimentally confirming the predicted properties of peptides from Bacteroides uniformis. Our results offer a comparative view of the functional organization of organisms across the entire evolutionary range. A remarkably high fraction of the total proteome mass in all kingdoms is dedicated to protein homeostasis and folding, highlighting the biological challenge of maintaining protein structure in all branches of life. Likewise, a universally high fraction is involved in supplying energy resources, although these pathways range from photosynthesis through iron sulfur metabolism to carbohydrate metabolism. Generally, however, proteins and proteomes are remarkably diverse between organisms, and they can readily be explored and functionally compared at www.proteomesoflife.org.

Quantitative proteome comparison of human hearts with those of model organisms.

Delineating human cardiac pathologies and their basic molecular mechanisms relies on research conducted in model organisms. Yet translating findings from preclinical models to humans present a significant challenge, in part due to differences in cardiac protein expression between humans and model organisms. Proteins immediately determine cellular function, yet their large-scale investigation in hearts has lagged behind those of genes and transcripts. Here, we set out to bridge this knowledge gap: By analyzing protein profiles in humans and commonly used model organisms across cardiac chambers, we determine their commonalities and regional differences. We analyzed cardiac tissue from each chamber of human, pig, horse, rat, mouse, and zebrafish in biological replicates. Using mass spectrometry-based proteomics workflows, we measured and evaluated the abundance of approximately 7,000 proteins in each species. The resulting knowledgebase of cardiac protein signatures is accessible through an online database: atlas.cardiacproteomics.com. Our combined analysis allows for quantitative evaluation of protein abundances across cardiac chambers, as well as comparisons of cardiac protein profiles across model organisms. Up to a quarter of proteins with differential abundances between atria and ventricles showed opposite chamber-specific enrichment between species; these included numerous proteins implicated in cardiac disease. The generated proteomics resource facilitates translational prospects of cardiac studies from model organisms to humans by comparisons of disease-linked protein networks across species.

An integrated view of cisplatin-induced nephrotoxicity, hepatotoxicity, and cardiotoxicity: characteristics, common molecular mechanisms, and current clinical management.

Cisplatin (CP) is a chemotherapy drug widely prescribed to treat various neoplasms. Although fundamental for the therapeutic action of the drug, its cytotoxic mechanisms trigger adverse effects in several tissues, such as the kidney, liver, and heart, which limit its clinical use. In this sense, studies point to an essential role of damage to nuclear and mitochondrial DNA associated with oxidative stress, inflammation, and apoptosis in the pathophysiology of tissue injuries. Due to the limitation of effective preventive and therapeutic measures against CP-induced toxicity, new strategies with potential cytoprotective effects have been studied. Therefore, this article is timely in reviewing the characteristics and main molecular mechanisms common to renal, hepatic, and cardiac toxicity previously described, in addition to addressing the main validated strategies for the current management of these adverse events in clinical practice. We also handle the main promising antioxidant substances recently presented in the literature to encourage the development of new research that consolidates their potential preventive and therapeutic effects against CP-induced cytotoxicity.

Dynamic human liver proteome atlas reveals functional insights into disease pathways.

Deeper understanding of liver pathophysiology would benefit from a comprehensive quantitative proteome resource at cell type resolution to predict outcome and design therapy. Here, we quantify more than 150,000 sequence-unique peptides aggregated into 10,000 proteins across total liver, the major liver cell types, time course of primary cell cultures, and liver disease states. Bioinformatic analysis reveals that half of hepatocyte protein mass is comprised of enzymes and 23% of mitochondrial proteins, twice the proportion of other liver cell types. Using primary cell cultures, we capture dynamic proteome remodeling from tissue states to cell line states, providing useful information for biological or pharmaceutical research. Our extensive data serve as spectral library to characterize a human cohort of non-alcoholic steatohepatitis and cirrhosis. Dramatic proteome changes in liver tissue include signatures of hepatic stellate cell activation resembling liver cirrhosis and providing functional insights. We built a web-based dashboard application for the interactive exploration of our resource (www.liverproteome.org).

Assessment of Reversibility for Covalent Cysteine Protease Inhibitors Using Quantum Mechanics/Molecular Mechanics Free Energy Surfaces.

We have used molecular dynamics (MD) simulations with hybrid quantum mechanics/molecular mechanics (QM/MM) potentials to investigate the reaction mechanism for covalent inhibition of cathepsin K and assess the reversibility of inhibition. The computed free energy profiles suggest that a nucleophilic attack by the catalytic cysteine on the inhibitor warhead and proton transfer from the catalytic histidine occur in a concerted manner. The results indicate that the reaction is more strongly exergonic for the alkyne-based inhibitors, which bind irreversibly to cathepsin K, than for the nitrile-based inhibitor odanacatib, which binds reversibly. Gas-phase energies were also calculated for the addition of methanethiol to structural prototypes for a number of warheads of interest in cysteine protease inhibitor design in order to assess electrophilicity. The approaches presented in this study are particularly applicable to assessment of novel warheads, and computed transition state geometries can be incorporated into molecular models for covalent docking.

COVID-19 and Acute Kidney Injury - Direct and Indirect Pathophysiological Mechanisms Underlying Lesion Development.

COVID-19 is a pandemic disease caused by the SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) responsible for millions of deaths worldwide. Although the respiratory system is the main target of COVID-19, the disease can affect other organs, including the kidneys. Acute Kidney Injury (AKI), commonly seen in patients infected with COVID-19, has a multifactorial cause. Several studies associate this injury with the direct involvement of the virus in renal cells and the indirect damage stimulated by the infection. The direct cytopathic effects of SARS-CoV-2 are due to the entry and replication of the virus in renal cells, changing several regulatory pathways, especially the renin-angiotensin-aldosterone system (RAAS), with repercussions on the kallikrein-kinin system (KKS). Furthermore, the virus can deregulate the immune system, leading to an exaggerated response of inflammatory cells, characterizing the state of hypercytokinemia. The such exaggerated inflammatory response is commonly associated with hemodynamic changes, reduced renal perfusion, tissue hypoxia, generation of reactive oxygen species (ROS), endothelial damage, and coagulopathies, which can result in severe damage to the renal parenchyma. Thereby, understanding the molecular mechanisms and pathophysiology of kidney injuries induced by SARS-COV-2 is of fundamental importance to obtaining new therapeutic insights for the prevention and management of AKI.

Assessment of the PETase conformational changes induced by poly(ethylene terephthalate) binding.

Recently, a bacterium strain of Ideonella sakaiensis was identified with the uncommon ability to degrade the poly(ethylene terephthalate) (PET). The PETase from I. sakaiensis strain 201-F6 (IsPETase) catalyzes the hydrolysis of PET converting it to mono(2-hydroxyethyl) terephthalic acid (MHET), bis(2-hydroxyethyl)-TPA (BHET), and terephthalic acid (TPA). Despite the potential of this enzyme for mitigation or elimination of environmental contaminants, one of the limitations of the use of IsPETase for PET degradation is the fact that it acts only at moderate temperature due to its low thermal stability. Besides, molecular details of the main interactions of PET in the active site of IsPETase remain unclear. Herein, molecular docking and molecular dynamics (MD) simulations were applied to analyze structural changes of IsPETase induced by PET binding. Results from the essential dynamics revealed that the ß1-ß2 connecting loop is very flexible. This loop is located far from the active site of IsPETase and we suggest that it can be considered for mutagenesis to increase the thermal stability of IsPETase. The free energy landscape (FEL) demonstrates that the main change in the transition between the unbound to the bound state is associated with the ß7-α5 connecting loop, where the catalytic residue Asp206 is located. Overall, the present study provides insights into the molecular binding mechanism of PET into the IsPETase structure and a computational strategy for mapping flexible regions of this enzyme, which can be useful for the engineering of more efficient enzymes for recycling plastic polymers using biological systems.

Integrative proteomics reveals principles of dynamic phosphosignaling networks in human erythropoiesis.

Human erythropoiesis is an exquisitely controlled multistep developmental process, and its dysregulation leads to numerous human diseases. Transcriptome and epigenome studies provided insights into system-wide regulation, but we currently lack a global mechanistic view on the dynamics of proteome and post-translational regulation coordinating erythroid maturation. We established a mass spectrometry (MS)-based proteomics workflow to quantify and dynamically track 7,400 proteins and 27,000 phosphorylation sites of five distinct maturation stages of in vitro reconstituted erythropoiesis of CD34+ HSPCs. Our data reveal developmental regulation through drastic proteome remodeling across stages of erythroid maturation encompassing most protein classes. This includes various orchestrated changes in solute carriers indicating adjustments to altered metabolic requirements. To define the distinct proteome of each maturation stage, we developed a computational deconvolution approach which revealed stage-specific marker proteins. The dynamic phosphoproteomes combined with a kinome-targeted CRISPR/Cas9 screen uncovered coordinated networks of erythropoietic kinases and pinpointed downregulation of c-Kit/MAPK signaling axis as key driver of maturation. Our system-wide view establishes the functional dynamic of complex phosphosignaling networks and regulation through proteome remodeling in erythropoiesis.

Plasma proteome profiling discovers novel proteins associated with non-alcoholic fatty liver disease.

Non-alcoholic fatty liver disease (NAFLD) affects 25% of the population and can progress to cirrhosis with limited treatment options. As the liver secretes most of the blood plasma proteins, liver disease may affect the plasma proteome. Plasma proteome profiling of 48 patients with and without cirrhosis or NAFLD revealed six statistically significantly changing proteins (ALDOB, APOM, LGALS3BP, PIGR, VTN, and AFM), two of which are already linked to liver disease. Polymeric immunoglobulin receptor (PIGR) was significantly elevated in both cohorts by 170% in NAFLD and 298% in cirrhosis and was further validated in mouse models. Furthermore, a global correlation map of clinical and proteomic data strongly associated DPP4, ANPEP, TGFBI, PIGR, and APOE with NAFLD and cirrhosis. The prominent diabetic drug target DPP4 is an aminopeptidase like ANPEP, ENPEP, and LAP3, all of which are up-regulated in the human or mouse data. Furthermore, ANPEP and TGFBI have potential roles in extracellular matrix remodeling in fibrosis. Thus, plasma proteome profiling can identify potential biomarkers and drug targets in liver disease.

Evaluating QM/MM Free Energy Surfaces for Ranking Cysteine Protease Covalent Inhibitors.

One tactic for cysteine protease inhibition is to form a covalent bond between an electrophilic atom of the inhibitor and the thiol of the catalytic cysteine. In this study, we evaluate the reaction free energy obtained from a hybrid quantum mechanical/molecular mechanical (QM/MM) free energy profile as a predictor of affinity for reversible, covalent inhibitors of rhodesain. We demonstrate that the reaction free energy calculated with the PM6/MM potential is in agreement with the experimental data and suggest that the free energy profile for covalent bond formation in a protein environment may be a useful tool for the inhibitor design.

miRandola 2017: a curated knowledge base of non-invasive biomarkers.

miRandola (http://mirandola.iit.cnr.it/) is a database of extracellular non-coding RNAs (ncRNAs) that was initially published in 2012, foreseeing the relevance of ncRNAs as non-invasive biomarkers. An increasing amount of experimental evidence shows that ncRNAs are frequently dysregulated in diseases. Further, ncRNAs have been discovered in different extracellular forms, such as exosomes, which circulate in human body fluids. Thus, miRandola 2017 is an effort to update and collect the accumulating information on extracellular ncRNAs that is spread across scientific publications and different databases. Data are manually curated from 314 articles that describe miRNAs, long non-coding RNAs and circular RNAs. Fourteen organisms are now included in the database, and associations of ncRNAs with 25 drugs, 47 sample types and 197 diseases. miRandola also classifies extracellular RNAs based on their extracellular form: Argonaute2 protein, exosome, microvesicle, microparticle, membrane vesicle, high density lipoprotein and circulating. We also implemented a new web interface to improve the user experience.

The ISCB Student Council Internship Program: Expanding computational biology capacity worldwide.

Education and training are two essential ingredients for a successful career. On one hand, universities provide students a curriculum for specializing in one's field of study, and on the other, internships complement coursework and provide invaluable training experience for a fruitful career. Consequently, undergraduates and graduates are encouraged to undertake an internship during the course of their degree. The opportunity to explore one's research interests in the early stages of their education is important for students because it improves their skill set and gives their career a boost. In the long term, this helps to close the gap between skills and employability among students across the globe and balance the research capacity in the field of computational biology. However, training opportunities are often scarce for computational biology students, particularly for those who reside in less-privileged regions. Aimed at helping students develop research and academic skills in computational biology and alleviating the divide across countries, the Student Council of the International Society for Computational Biology introduced its Internship Program in 2009. The Internship Program is committed to providing access to computational biology training, especially for students from developing regions, and improving competencies in the field. Here, we present how the Internship Program works and the impact of the internship opportunities so far, along with the challenges associated with this program.

The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible.

A system-wide understanding of cellular function requires knowledge of all functional interactions between the expressed proteins. The STRING database aims to collect and integrate this information, by consolidating known and predicted protein-protein association data for a large number of organisms. The associations in STRING include direct (physical) interactions, as well as indirect (functional) interactions, as long as both are specific and biologically meaningful. Apart from collecting and reassessing available experimental data on protein-protein interactions, and importing known pathways and protein complexes from curated databases, interaction predictions are derived from the following sources: (i) systematic co-expression analysis, (ii) detection of shared selective signals across genomes, (iii) automated text-mining of the scientific literature and (iv) computational transfer of interaction knowledge between organisms based on gene orthology. In the latest version 10.5 of STRING, the biggest changes are concerned with data dissemination: the web frontend has been completely redesigned to reduce dependency on outdated browser technologies, and the database can now also be queried from inside the popular Cytoscape software framework. Further improvements include automated background analysis of user inputs for functional enrichments, and streamlined download options. The STRING resource is available online, at http://string-db.org/.

Computational Investigation of Bisphosphate Inhibitors of 3-Deoxy-d-manno-octulosonate 8-phosphate Synthase.

The synthase, 3-deoxy-d-manno-octulosonate 8-phosphate (KDO8P), is a key enzyme for the lipopolysaccharide (LPS) biosynthesis of gram-negative bacteria and a potential target for developing new antimicrobial agents. In this study, computational molecular modeling methods were used to determine the complete structure of the KDO8P synthase from Neisseria meningitidis and to investigate the molecular mechanism of its inhibition by three bisphosphate inhibitors: BPH1, BPH2, and BPH3. Our results showed that BPH1 presented a protein-ligand complex with the highest affinity, which is in agreement with experimental data. Furthermore, molecular dynamics (MD) simulations showed that BPH1 is more active due to the many effective interactions, most of which are derived from its phosphoenolpyruvate moiety. Conversely, BPH2 exhibited few hydrogen interactions during the MD simulations with key residues located at the active sites of the KDO8P synthase. In addition, we hydroxylated BPH2 to create the hypothetical molecule named BPH3, to investigate the influence of the hydroxyl groups on the affinity of the bisphosphate inhibitors toward the KDO8P synthase. Overall, we discuss the main interactions between the KDO8P synthase and the bisphosphate inhibitors that are potential starting points for the design of new molecules with significant antibiotic activities.

Experimental study and computational modelling of cruzain cysteine protease inhibition by dipeptidyl nitriles.

Chagas disease affects millions of people in Latin America. This disease is caused by the protozoan parasite Trypanossoma cruzi. The cysteine protease cruzain is a key enzyme for the survival and propagation of this parasite lifecycle. Nitrile-based inhibitors are efficient inhibitors of cruzain that bind by forming a covalent bond with this enzyme. Here, three nitrile-based inhibitors dubbed Neq0409, Neq0410 and Neq0570 were synthesized, and the thermodynamic profile of the bimolecular interaction with cruzain was determined using isothermal titration calorimetry (ITC). The result suggests the inhibition process is enthalpy driven, with a detrimental contribution of entropy. In addition, we have used hybrid Quantum Mechanical/Molecular Mechanical (QM/MM) and Molecular Dynamics (MD) simulations to investigate the reaction mechanism of reversible covalent modification of cruzain by Neq0409, Neq0410 and Neq0570. The computed free energy profile shows that the nucleophilic attack of Cys25 on the carbon C1 of inhibitiors and the proton transfer from His162 to N1 of the dipeptidyl nitrile inhibitor take place in a single step. The calculated free energy of the inhibiton reaction is in agreement with covalent experimental binding. Altogether, the results reported here suggests that nitrile-based inhibitors are good candidates for the development of reversible covalent inhibitors of cruzain and other cysteine proteases.

STITCH 5: augmenting protein-chemical interaction networks with tissue and affinity data.

Interactions between proteins and small molecules are an integral part of biological processes in living organisms. Information on these interactions is dispersed over many databases, texts and prediction methods, which makes it difficult to get a comprehensive overview of the available evidence. To address this, we have developed STITCH ('Search Tool for Interacting Chemicals') that integrates these disparate data sources for 430 000 chemicals into a single, easy-to-use resource. In addition to the increased scope of the database, we have implemented a new network view that gives the user the ability to view binding affinities of chemicals in the interaction network. This enables the user to get a quick overview of the potential effects of the chemical on its interaction partners. For each organism, STITCH provides a global network; however, not all proteins have the same pattern of spatial expression. Therefore, only a certain subset of interactions can occur simultaneously. In the new, fifth release of STITCH, we have implemented functionality to filter out the proteins and chemicals not associated with a given tissue. The STITCH database can be downloaded in full, accessed programmatically via an extensive API, or searched via a redesigned web interface at http://stitch.embl.de.

Cyclebase 3.0: a multi-organism database on cell-cycle regulation and phenotypes.

The eukaryotic cell division cycle is a highly regulated process that consists of a complex series of events and involves thousands of proteins. Researchers have studied the regulation of the cell cycle in several organisms, employing a wide range of high-throughput technologies, such as microarray-based mRNA expression profiling and quantitative proteomics. Due to its complexity, the cell cycle can also fail or otherwise change in many different ways if important genes are knocked out, which has been studied in several microscopy-based knockdown screens. The data from these many large-scale efforts are not easily accessed, analyzed and combined due to their inherent heterogeneity. To address this, we have created Cyclebase--available at http://www.cyclebase.org--an online database that allows users to easily visualize and download results from genome-wide cell-cycle-related experiments. In Cyclebase version 3.0, we have updated the content of the database to reflect changes to genome annotation, added new mRNA and protein expression data, and integrated cell-cycle phenotype information from high-content screens and model-organism databases. The new version of Cyclebase also features a new web interface, designed around an overview figure that summarizes all the cell-cycle-related data for a gene.

STRING v10: protein-protein interaction networks, integrated over the tree of life.

The many functional partnerships and interactions that occur between proteins are at the core of cellular processing and their systematic characterization helps to provide context in molecular systems biology. However, known and predicted interactions are scattered over multiple resources, and the available data exhibit notable differences in terms of quality and completeness. The STRING database (http://string-db.org) aims to provide a critical assessment and integration of protein-protein interactions, including direct (physical) as well as indirect (functional) associations. The new version 10.0 of STRING covers more than 2000 organisms, which has necessitated novel, scalable algorithms for transferring interaction information between organisms. For this purpose, we have introduced hierarchical and self-consistent orthology annotations for all interacting proteins, grouping the proteins into families at various levels of phylogenetic resolution. Further improvements in version 10.0 include a completely redesigned prediction pipeline for inferring protein-protein associations from co-expression data, an API interface for the R computing environment and improved statistical analysis for enrichment tests in user-provided networks.

Adenoid bacterial colonization in a paediatric population.

Adenoids play a key role in both respiratory and ear infection in children. It has also been shown that adenoidectomy improves these symptoms in this population. The main goal of the present study was to evaluate adenoid bacterial colonization and document a possible relation with infectious respiratory disease. A prospective observational study was designed to evaluate the proposed hypothesis in a paediatric population submitted to adenoidectomy by either infectious or non-infectious indications and compare these two cohorts. A total of 62 patients with ages ranging from 1 to 12 years old were enrolled in the study. Adenoid surface, adenoid core and middle meatus microbiota were compared. A close association between adenoid colonization and nasal infection was found, supporting that adenoids may function as bacterial reservoir for upper airway infection. The obtained results also contribute to explain the success of adenoidectomy in patients with infectious indications.

IntOGen-mutations identifies cancer drivers across tumor types.

The IntOGen-mutations platform (http://www.intogen.org/mutations/) summarizes somatic mutations, genes and pathways involved in tumorigenesis. It identifies and visualizes cancer drivers, analyzing 4,623 exomes from 13 cancer sites. It provides support to cancer researchers, aids the identification of drivers across tumor cohorts and helps rank mutations for better clinical decision-making.