CTCF regulates hepatitis B virus cccDNA chromatin topology.

Hepatitis B Virus (HBV) is a small DNA virus that replicates via an episomal covalently closed circular DNA (cccDNA) that serves as the transcriptional template for viral mRNAs. The host protein, CCCTC-binding factor (CTCF), is a key regulator of cellular transcription by maintaining epigenetic boundaries, nucleosome phasing, stabilisation of long-range chromatin loops and directing alternative exon splicing. We previously reported that CTCF binds two conserved motifs within Enhancer I of the HBV genome and represses viral transcription, however, the underlying mechanisms were not identified. We show that CTCF depletion in cells harbouring cccDNA-like HBV molecules and in de novo infected cells resulted in an increase in spliced transcripts, which was most notable in the abundant SP1 spliced transcript. In contrast, depletion of CTCF in cell lines with integrated HBV DNA had no effect on the abundance of viral transcripts and in line with this observation there was limited evidence for CTCF binding to viral integrants, suggesting that CTCF-regulation of HBV transcription is specific to episomal cccDNA. Analysis of HBV chromatin topology by Assay for Transposase Accessible Chromatin Sequencing (ATAC-Seq) revealed an accessible region spanning Enhancers I and II and the basal core promoter (BCP). Mutating the CTCF binding sites within Enhancer I resulted in a dramatic rearrangement of chromatin accessibility where the open chromatin region was no longer detected, indicating loss of the phased nucleosome up- and down-stream of the HBV enhancer/BCP. These data demonstrate that CTCF functions to regulate HBV chromatin conformation and nucleosomal positioning in episomal maintained cccDNA, which has important consequences for HBV transcription regulation.

Key findings from the UKCCMP cohort of 877 patients with haematological malignancy and COVID-19: disease control as an important factor relative to recent chemotherapy or anti-CD20 therapy.

Patients with haematological malignancies have a high risk of severe infection and death from SARS-CoV-2. In this prospective observational study, we investigated the impact of cancer type, disease activity, and treatment in 877 unvaccinated UK patients with SARS-CoV-2 infection and active haematological cancer. The primary end-point was all-cause mortality. In a multivariate analysis adjusted for age, sex and comorbidities, the highest mortality was in patients with acute leukaemia [odds ratio (OR) = 1·73, 95% confidence interval (CI) 1·1-2·72, P = 0·017] and myeloma (OR 1·3, 95% CI 0·96-1·76, P = 0·08). Having uncontrolled cancer (newly diagnosed awaiting treatment as well as relapsed or progressive disease) was associated with increased mortality risk (OR = 2·45, 95% CI 1·09-5·5, P = 0·03), as was receiving second or beyond line of treatment (OR = 1·7, 95% CI 1·08-2·67, P = 0·023). We found no association between recent cytotoxic chemotherapy or anti-CD19/anti-CD20 treatment and increased risk of death within the limitations of the cohort size. Therefore, disease control is an important factor predicting mortality in the context of SARS-CoV-2 infection alongside the possible risks of therapies such as cytotoxic treatment or anti-CD19/anti-CD20 treatments.

Severity of COVID-19 in children with cancer: Report from the United Kingdom Paediatric Coronavirus Cancer Monitoring Project.

BACKGROUND: Children with cancer are frequently immunocompromised. While children are generally thought to be at less risk of severe SARS-CoV-2 infection than adults, comprehensive population-based evidence for the risk in children with cancer is unavailable. We aimed to produce evidence of the incidence and outcomes from SARS-CoV-2 in children with cancer attending all hospitals treating this population across the UK. METHODS: Retrospective and prospective observational study of all children in the UK under 16 diagnosed with cancer through data collection from all hospitals providing cancer care to this population. Eligible patients tested positive for SARS-CoV-2 on reverse transcription polymerase chain reaction (RT-PCR). The primary end-point was death, discharge or end of active care for COVID-19 for those remaining in hospital. RESULTS: Between 12 March 2020 and 31 July 2020, 54 cases were identified: 15 (28%) were asymptomatic, 34 (63%) had mild infections and 5 (10%) moderate, severe or critical infections. No patients died and only three patients required intensive care support due to COVID-19. Estimated incidence of hospital identified SARS-CoV-2 infection in children with cancer under 16 was 3%. CONCLUSIONS: Children with cancer with SARS-CoV-2 infection do not appear at increased risk of severe infection compared to the general paediatric population. This is reassuring and supports the continued delivery of standard treatment.

COVID-19 mortality in patients with cancer on chemotherapy or other anticancer treatments: a prospective cohort study.

BACKGROUND: Individuals with cancer, particularly those who are receiving systemic anticancer treatments, have been postulated to be at increased risk of mortality from COVID-19. This conjecture has considerable effect on the treatment of patients with cancer and data from large, multicentre studies to support this assumption are scarce because of the contingencies of the pandemic. We aimed to describe the clinical and demographic characteristics and COVID-19 outcomes in patients with cancer. METHODS: In this prospective observational study, all patients with active cancer and presenting to our network of cancer centres were eligible for enrolment into the UK Coronavirus Cancer Monitoring Project (UKCCMP). The UKCCMP is the first COVID-19 clinical registry that enables near real-time reports to frontline doctors about the effects of COVID-19 on patients with cancer. Eligible patients tested positive for severe acute respiratory syndrome coronavirus 2 on RT-PCR assay from a nose or throat swab. We excluded patients with a radiological or clinical diagnosis of COVID-19, without a positive RT-PCR test. The primary endpoint was all-cause mortality, or discharge from hospital, as assessed by the reporting sites during the patient hospital admission. FINDINGS: From March 18, to April 26, 2020, we analysed 800 patients with a diagnosis of cancer and symptomatic COVID-19. 412 (52%) patients had a mild COVID-19 disease course. 226 (28%) patients died and risk of death was significantly associated with advancing patient age (odds ratio 9·42 [95% CI 6·56-10·02]; p<0·0001), being male (1·67 [1·19-2·34]; p=0·003), and the presence of other comorbidities such as hypertension (1·95 [1·36-2·80]; p<0·001) and cardiovascular disease (2·32 [1·47-3·64]). 281 (35%) patients had received cytotoxic chemotherapy within 4 weeks before testing positive for COVID-19. After adjusting for age, gender, and comorbidities, chemotherapy in the past 4 weeks had no significant effect on mortality from COVID-19 disease, when compared with patients with cancer who had not received recent chemotherapy (1·18 [0·81-1·72]; p=0·380). We found no significant effect on mortality for patients with immunotherapy, hormonal therapy, targeted therapy, radiotherapy use within the past 4 weeks. INTERPRETATION: Mortality from COVID-19 in cancer patients appears to be principally driven by age, gender, and comorbidities. We are not able to identify evidence that cancer patients on cytotoxic chemotherapy or other anticancer treatment are at an increased risk of mortality from COVID-19 disease compared with those not on active treatment. FUNDING: University of Birmingham, University of Oxford.

Srrm234, but not canonical SR and hnRNP proteins, drive inclusion of Dscam exon 9 variable exons.

Alternative splicing of pre-mRNA is a major mechanism to diversify protein functionality in metazoans from a limited number of genes. The Drosophila melanogaster Down syndrome cell adhesion molecule (Dscam) gene, which is important for neuronal wiring and phagocytosis of bacteria, can generate up to 38,016 isoforms by mutually exclusive alternative splicing in four clusters of variable exons. However, it is not understood how a specific exon is chosen from the many variables and how variable exons are prevented from being spliced together. A main role in the regulation of Dscam alternative splicing has been attributed to RNA binding proteins (RBPs), but how they impact on exon selection is not well understood. Serine-arginine rich (SR) proteins and hnRNP proteins are the two main types of RBPs with major roles in exon definition and splice site selection. Here, we analyzed the role of SR and hnRNP proteins in Dscam exon 9 alternative splicing in mutant Drosophila melanogaster embryos because of their essential function for development. Strikingly, loss or overexpression of canonical SR and hnRNP proteins even when multiple proteins are depleted together, does not affect Dscam alternative exon selection very dramatically. Conversely, noncanonical SR protein Serine-arginine repetitive matrix 2/3/4 (Srrm234) is a main determinant of exon inclusion in the Dscam exon 9 cluster. Since long-range base-pairings are absent in the exon 9 cluster, our data argue for a small complement of regulatory factors as main determinants of exon inclusion in the Dscam exon 9 cluster.

Exploiting differential Wnt target gene expression to generate a molecular biomarker for colorectal cancer stratification.

OBJECTIVE: Pathological Wnt pathway activation is a conserved hallmark of colorectal cancer. Wnt-activating mutations can be divided into: i) ligand-independent (LI) alterations in intracellular signal transduction proteins (Adenomatous polyposis coli, ß-catenin), causing constitutive pathway activation and ii) ligand-dependent (LD) mutations affecting the synergistic R-Spondin axis (RNF43, RSPO-fusions) acting through amplification of endogenous Wnt signal transmembrane transduction. Our aim was to exploit differential Wnt target gene expression to generate a mutation-agnostic biomarker for LD tumours. DESIGN: We undertook harmonised multi-omic analysis of discovery (n=684) and validation cohorts (n=578) of colorectal tumours collated from publicly available data and the Stratification in Colorectal Cancer Consortium. We used mutation data to establish molecular ground truth and subdivide lesions into LI/LD tumour subsets. We contrasted transcriptional, methylation, morphological and clinical characteristics between groups. RESULTS: Wnt disrupting mutations were mutually exclusive. Desmoplastic stromal upregulation of RSPO may compensate for absence of epithelial mutation in a subset of stromal-rich tumours. Key Wnt negative regulator genes were differentially expressed between LD/LI tumours, with targeted hypermethylation of some genes (AXIN2, NKD1) occurring even in CIMP-negative LD cancers. AXIN2 mRNA expression was used as a discriminatory molecular biomarker to distinguish LD/LI tumours (area under the curve >0.93). CONCLUSIONS: Epigenetic suppression of appropriate Wnt negative feedback loops is selectively advantageous in LD tumours and differential AXIN2 expression in LD/LI lesions can be exploited as a molecular biomarker. Distinguishing between LD/LI tumour types is important; patients with LD tumours retain sensitivity to Wnt ligand inhibition and may be stratified at diagnosis to clinical trials of Porcupine inhibitors.

COVID-19 prevalence and mortality in patients with cancer and the effect of primary tumour subtype and patient demographics: a prospective cohort study.

BACKGROUND: Patients with cancer are purported to have poor COVID-19 outcomes. However, cancer is a heterogeneous group of diseases, encompassing a spectrum of tumour subtypes. The aim of this study was to investigate COVID-19 risk according to tumour subtype and patient demographics in patients with cancer in the UK. METHODS: We compared adult patients with cancer enrolled in the UK Coronavirus Cancer Monitoring Project (UKCCMP) cohort between March 18 and May 8, 2020, with a parallel non-COVID-19 UK cancer control population from the UK Office for National Statistics (2017 data). The primary outcome of the study was the effect of primary tumour subtype, age, and sex and on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prevalence and the case-fatality rate during hospital admission. We analysed the effect of tumour subtype and patient demographics (age and sex) on prevalence and mortality from COVID-19 using univariable and multivariable models. FINDINGS: 319 (30·6%) of 1044 patients in the UKCCMP cohort died, 295 (92·5%) of whom had a cause of death recorded as due to COVID-19. The all-cause case-fatality rate in patients with cancer after SARS-CoV-2 infection was significantly associated with increasing age, rising from 0·10 in patients aged 40-49 years to 0·48 in those aged 80 years and older. Patients with haematological malignancies (leukaemia, lymphoma, and myeloma) had a more severe COVID-19 trajectory compared with patients with solid organ tumours (odds ratio [OR] 1·57, 95% CI 1·15-2·15; p<0·0043). Compared with the rest of the UKCCMP cohort, patients with leukaemia showed a significantly increased case-fatality rate (2·25, 1·13-4·57; p=0·023). After correction for age and sex, patients with haematological malignancies who had recent chemotherapy had an increased risk of death during COVID-19-associated hospital admission (OR 2·09, 95% CI 1·09-4·08; p=0·028). INTERPRETATION: Patients with cancer with different tumour types have differing susceptibility to SARS-CoV-2 infection and COVID-19 phenotypes. We generated individualised risk tables for patients with cancer, considering age, sex, and tumour subtype. Our results could be useful to assist physicians in informed risk-benefit discussions to explain COVID-19 risk and enable an evidenced-based approach to national social isolation policies. FUNDING: University of Birmingham and University of Oxford.

Proteome-wide analysis of phospho-regulated PDZ domain interactions.

A key function of reversible protein phosphorylation is to regulate protein-protein interactions, many of which involve short linear motifs (3-12 amino acids). Motif-based interactions are difficult to capture because of their often low-to-moderate affinities. Here, we describe phosphomimetic proteomic peptide-phage display, a powerful method for simultaneously finding motif-based interaction and pinpointing phosphorylation switches. We computationally designed an oligonucleotide library encoding human C-terminal peptides containing known or predicted Ser/Thr phosphosites and phosphomimetic variants thereof. We incorporated these oligonucleotides into a phage library and screened the PDZ (PSD-95/Dlg/ZO-1) domains of Scribble and DLG1 for interactions potentially enabled or disabled by ligand phosphorylation. We identified known and novel binders and characterized selected interactions through microscale thermophoresis, isothermal titration calorimetry, and NMR We uncover site-specific phospho-regulation of PDZ domain interactions, provide a structural framework for how PDZ domains accomplish phosphopeptide binding, and discuss ligand phosphorylation as a switching mechanism of PDZ domain interactions. The approach is readily scalable and can be used to explore the potential phospho-regulation of motif-based interactions on a large scale.

Tropomyosins: Potential Biomarkers for Urothelial Bladder Cancer.

Despite the incidence and prevalence of urothelial bladder cancer (UBC), few advances in treatment and diagnosis have been made in recent years. In this review, we discuss potential biomarker candidates: the tropomyosin family of genes, encoded by four loci in the human genome. The expression of these genes is tissue-specific. Tropomyosins are responsible for diverse cellular roles, most notably based upon their interplay with actin to maintain cellular processes, integrity and structure. Tropomyosins exhibit a large variety of splice forms, and altered isoform expression levels have been associated with cancer, including UBC. Notably, tropomyosin isoforms are detectable in urine, offering the potential for non-invasive diagnosis and risk-stratification. This review collates the basic knowledge on tropomyosin and its isoforms, and discusses their relationships with cancer-related phenomena, most specifically in UBC.

EffectiveDB--updates and novel features for a better annotation of bacterial secreted proteins and Type III, IV, VI secretion systems.

Protein secretion systems play a key role in the interaction of bacteria and hosts. EffectiveDB (http://effectivedb.org) contains pre-calculated predictions of bacterial secreted proteins and of intact secretion systems. Here we describe a major update of the database, which was previously featured in the NAR Database Issue. EffectiveDB bundles various tools to recognize Type III secretion signals, conserved binding sites of Type III chaperones, Type IV secretion peptides, eukaryotic-like domains and subcellular targeting signals in the host. Beyond the analysis of arbitrary protein sequence collections, the new release of EffectiveDB also provides a 'genome-mode', in which protein sequences from nearly complete genomes or metagenomic bins can be screened for the presence of three important secretion systems (Type III, IV, VI). EffectiveDB contains pre-calculated predictions for currently 1677 bacterial genomes from the EggNOG 4.0 database and for additional bacterial genomes from NCBI RefSeq. The new, user-friendly and informative web portal offers a submission tool for running the EffectiveDB prediction tools on user-provided data.

Large-scale interaction profiling of PDZ domains through proteomic peptide-phage display using human and viral phage peptidomes.

The human proteome contains a plethora of short linear motifs (SLiMs) that serve as binding interfaces for modular protein domains. Such interactions are crucial for signaling and other cellular processes, but are difficult to detect because of their low to moderate affinities. Here we developed a dedicated approach, proteomic peptide-phage display (ProP-PD), to identify domain-SLiM interactions. Specifically, we generated phage libraries containing all human and viral C-terminal peptides using custom oligonucleotide microarrays. With these libraries we screened the nine PSD-95/Dlg/ZO-1 (PDZ) domains of human Densin-180, Erbin, Scribble, and Disks large homolog 1 for peptide ligands. We identified several known and putative interactions potentially relevant to cellular signaling pathways and confirmed interactions between full-length Scribble and the target proteins ß-PIX, plakophilin-4, and guanylate cyclase soluble subunit α-2 using colocalization and coimmunoprecipitation experiments. The affinities of recombinant Scribble PDZ domains and the synthetic peptides representing the C termini of these proteins were in the 1- to 40-µM range. Furthermore, we identified several well-established host-virus protein-protein interactions, and confirmed that PDZ domains of Scribble interact with the C terminus of Tax-1 of human T-cell leukemia virus with micromolar affinity. Previously unknown putative viral protein ligands for the PDZ domains of Scribble and Erbin were also identified. Thus, we demonstrate that our ProP-PD libraries are useful tools for probing PDZ domain interactions. The method can be extended to interrogate all potential eukaryotic, bacterial, and viral SLiMs and we suggest it will be a highly valuable approach for studying cellular and pathogen-host protein-protein interactions.

Quantitative genome-wide genetic interaction screens reveal global epistatic relationships of protein complexes in Escherichia coli.

Large-scale proteomic analyses in Escherichia coli have documented the composition and physical relationships of multiprotein complexes, but not their functional organization into biological pathways and processes. Conversely, genetic interaction (GI) screens can provide insights into the biological role(s) of individual gene and higher order associations. Combining the information from both approaches should elucidate how complexes and pathways intersect functionally at a systems level. However, such integrative analysis has been hindered due to the lack of relevant GI data. Here we present a systematic, unbiased, and quantitative synthetic genetic array screen in E. coli describing the genetic dependencies and functional cross-talk among over 600,000 digenic mutant combinations. Combining this epistasis information with putative functional modules derived from previous proteomic data and genomic context-based methods revealed unexpected associations, including new components required for the biogenesis of iron-sulphur and ribosome integrity, and the interplay between molecular chaperones and proteases. We find that functionally-linked genes co-conserved among γ-proteobacteria are far more likely to have correlated GI profiles than genes with divergent patterns of evolution. Overall, examining bacterial GIs in the context of protein complexes provides avenues for a deeper mechanistic understanding of core microbial systems.

PAT: predictor for structured units and its application for the optimization of target molecules for the generation of synthetic antibodies.

BACKGROUND: The identification of structured units in a protein sequence is an important first step for most biochemical studies. Importantly for this study, the identification of stable structured region is a crucial first step to generate novel synthetic antibodies. While many approaches to find domains or predict structured regions exist, important limitations remain, such as the optimization of domain boundaries and the lack of identification of non-domain structured units. Moreover, no integrated tool exists to find and optimize structural domains within protein sequences. RESULTS: Here, we describe a new tool, PAT ( http://www.kimlab.org/software/pat ) that can efficiently identify both domains (with optimized boundaries) and non-domain putative structured units. PAT automatically analyzes various structural properties, evaluates the folding stability, and reports possible structural domains in a given protein sequence. For reliability evaluation of PAT, we applied PAT to identify antibody target molecules based on the notion that soluble and well-defined protein secondary and tertiary structures are appropriate target molecules for synthetic antibodies. CONCLUSION: PAT is an efficient and sensitive tool to identify structured units. A performance analysis shows that PAT can characterize structurally well-defined regions in a given sequence and outperforms other efforts to define reliable boundaries of domains. Specially, PAT successfully identifies experimentally confirmed target molecules for antibody generation. PAT also offers the pre-calculated results of 20,210 human proteins to accelerate common queries. PAT can therefore help to investigate large-scale structured domains and improve the success rate for synthetic antibody generation.

Novel function discovery with GeneMANIA: a new integrated resource for gene function prediction in Escherichia coli.

MOTIVATION: The model bacterium Escherichia coli is among the best studied prokaryotes, yet nearly half of its proteins are still of unknown biological function. This is despite a wealth of available large-scale physical and genetic interaction data. To address this, we extended the GeneMANIA function prediction web application developed for model eukaryotes to support E.coli. RESULTS: We integrated 48 distinct E.coli functional interaction datasets and used the GeneMANIA algorithm to produce thousands of novel functional predictions and prioritize genes for further functional assays. Our analysis achieved cross-validation performance comparable to that reported for eukaryotic model organisms, and revealed new functions for previously uncharacterized genes in specific bioprocesses, including components required for cell adhesion, iron-sulphur complex assembly and ribosome biogenesis. The GeneMANIA approach for network-based function prediction provides an innovative new tool for probing mechanisms underlying bacterial bioprocesses. CONTACT: gary.bader@utoronto.ca; mohan.babu@uregina.ca SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SIMAP--the database of all-against-all protein sequence similarities and annotations with new interfaces and increased coverage.

The Similarity Matrix of Proteins (SIMAP, http://mips.gsf.de/simap/) database has been designed to massively accelerate computationally expensive protein sequence analysis tasks in bioinformatics. It provides pre-calculated sequence similarities interconnecting the entire known protein sequence universe, complemented by pre-calculated protein features and domains, similarity clusters and functional annotations. SIMAP covers all major public protein databases as well as many consistently re-annotated metagenomes from different repositories. As of September 2013, SIMAP contains >163 million proteins corresponding to ∼70 million non-redundant sequences. SIMAP uses the sensitive FASTA search heuristics, the Smith-Waterman alignment algorithm, the InterPro database of protein domain models and the BLAST2GO functional annotation algorithm. SIMAP assists biologists by facilitating the interactive exploration of the protein sequence universe. Web-Service and DAS interfaces allow connecting SIMAP with any other bioinformatic tool and resource. All-against-all protein sequence similarity matrices of project-specific protein collections are generated on request. Recent improvements allow SIMAP to cover the rapidly growing sequenced protein sequence universe. New Web-Service interfaces enhance the connectivity of SIMAP. Novel tools for interactive extraction of protein similarity networks have been added. Open access to SIMAP is provided through the web portal; the portal also contains instructions and links for software access and flat file downloads.

Localization of Burkholderia cepacia complex bacteria in cystic fibrosis lungs and interactions with Pseudomonas aeruginosa in hypoxic mucus.

The localization of Burkholderia cepacia complex (Bcc) bacteria in cystic fibrosis (CF) lungs, alone or during coinfection with Pseudomonas aeruginosa, is poorly understood. We performed immunohistochemistry for Bcc and P. aeruginosa bacteria on 21 coinfected or singly infected CF lungs obtained at transplantation or autopsy. Parallel in vitro experiments examined the growth of two Bcc species, Burkholderia cenocepacia and Burkholderia multivorans, in environments similar to those occupied by P. aeruginosa in the CF lung. Bcc bacteria were predominantly identified in the CF lung as single cells or small clusters within phagocytes and mucus but not as "biofilm-like structures." In contrast, P. aeruginosa was identified in biofilm-like masses, but densities appeared to be reduced during coinfection with Bcc bacteria. Based on chemical analyses of CF and non-CF respiratory secretions, a test medium was defined to study Bcc growth and interactions with P. aeruginosa in an environment mimicking the CF lung. When test medium was supplemented with alternative electron acceptors under anaerobic conditions, B. cenocepacia and B. multivorans used fermentation rather than anaerobic respiration to gain energy, consistent with the identification of fermentation products by high-performance liquid chromatography (HPLC). Both Bcc species also expressed mucinases that produced carbon sources from mucins for growth. In the presence of P. aeruginosa in vitro, both Bcc species grew anaerobically but not aerobically. We propose that Bcc bacteria (i) invade a P. aeruginosa-infected CF lung when the airway lumen is anaerobic, (ii) inhibit P. aeruginosa biofilm-like growth, and (iii) expand the host bacterial niche from mucus to also include macrophages.

A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities.

Improved efforts are necessary to define the functional product of cancer mutations currently being revealed through large-scale sequencing efforts. Using genome-scale pooled shRNA screening technology, we mapped negative genetic interactions across a set of isogenic cancer cell lines and confirmed hundreds of these interactions in orthogonal co-culture competition assays to generate a high-confidence genetic interaction network of differentially essential or differential essentiality (DiE) genes. The network uncovered examples of conserved genetic interactions, densely connected functional modules derived from comparative genomics with model systems data, functions for uncharacterized genes in the human genome and targetable vulnerabilities. Finally, we demonstrate a general applicability of DiE gene signatures in determining genetic dependencies of other non-isogenic cancer cell lines. For example, the PTEN(-/-) DiE genes reveal a signature that can preferentially classify PTEN-dependent genotypes across a series of non-isogenic cell lines derived from the breast, pancreas and ovarian cancers. Our reference network suggests that many cancer vulnerabilities remain to be discovered through systematic derivation of a network of differentially essential genes in an isogenic cancer cell model.

eggNOG v3.0: orthologous groups covering 1133 organisms at 41 different taxonomic ranges.

Orthologous relationships form the basis of most comparative genomic and metagenomic studies and are essential for proper phylogenetic and functional analyses. The third version of the eggNOG database (http://eggnog.embl.de) contains non-supervised orthologous groups constructed from 1133 organisms, doubling the number of genes with orthology assignment compared to eggNOG v2. The new release is the result of a number of improvements and expansions: (i) the underlying homology searches are now based on the SIMAP database; (ii) the orthologous groups have been extended to 41 levels of selected taxonomic ranges enabling much more fine-grained orthology assignments; and (iii) the newly designed web page is considerably faster with more functionality. In total, eggNOG v3 contains 721,801 orthologous groups, encompassing a total of 4,396,591 genes. Additionally, we updated 4873 and 4850 original COGs and KOGs, respectively, to include all 1133 organisms. At the universal level, covering all three domains of life, 101,208 orthologous groups are available, while the others are applicable at 40 more limited taxonomic ranges. Each group is amended by multiple sequence alignments and maximum-likelihood trees and broad functional descriptions are provided for 450,904 orthologous groups (62.5%).

Genetic interaction maps in Escherichia coli reveal functional crosstalk among cell envelope biogenesis pathways.

As the interface between a microbe and its environment, the bacterial cell envelope has broad biological and clinical significance. While numerous biosynthesis genes and pathways have been identified and studied in isolation, how these intersect functionally to ensure envelope integrity during adaptive responses to environmental challenge remains unclear. To this end, we performed high-density synthetic genetic screens to generate quantitative functional association maps encompassing virtually the entire cell envelope biosynthetic machinery of Escherichia coli under both auxotrophic (rich medium) and prototrophic (minimal medium) culture conditions. The differential patterns of genetic interactions detected among > 235,000 digenic mutant combinations tested reveal unexpected condition-specific functional crosstalk and genetic backup mechanisms that ensure stress-resistant envelope assembly and maintenance. These networks also provide insights into the global systems connectivity and dynamic functional reorganization of a universal bacterial structure that is both broadly conserved among eubacteria (including pathogens) and an important target.