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Epithelial cells are the first point of contact for bacteria entering the respiratory tract. Streptococcus pneumoniae is an obligate human pathobiont of the nasal mucosa, carried asymptomatically but also the cause of severe pneumonia. The role of the epithelium in maintaining homeostatic interactions or mounting an inflammatory response to invasive S. pneumoniae is currently poorly understood. However, studies have shown that chromatin modifications, at the histone level, induced by bacterial pathogens interfere with the host transcriptional program and promote infection. In this study, we demonstrate that S. pneumoniae actively induces di-methylation of lysine 4 on histone H3 (H3K4me2), which persists for at least 9 days upon clearance of bacteria with antibiotics. We show that infection establishes a unique epigenetic program affecting the transcriptional response of epithelial cells, rendering them more permissive upon secondary infection. Our results establish H3K4me2 as a unique modification induced by infection, distinct from H3K4me3, which localizes to enhancer regions genome-wide. Therefore, this study reveals evidence that bacterial infection leaves a memory in epithelial cells after bacterial clearance, in an epigenomic mark, thereby altering cellular responses for subsequent infection.

We present ePeak, a Snakemake-based pipeline for the identification and quantification of reproducible peaks from raw ChIP-seq, CUT&RUN and CUT&Tag epigenomic profiling techniques. It also includes a statistical module to perform tailored differential marking and binding analysis with state of the art methods. ePeak streamlines critical steps like the quality assessment of the immunoprecipitation, spike-in calibration and the selection of reproducible peaks between replicates for both narrow and broad peaks. It generates complete reports for data quality control assessment and optimal interpretation of the results. We advocate for a differential analysis that accounts for the biological dynamics of each chromatin factor. Thus, ePeak provides linear and nonlinear methods for normalisation as well as conservative and stringent models for variance estimation and significance testing of the observed marking/binding differences. Using a published ChIP-seq dataset, we show that distinct populations of differentially marked/bound peaks can be identified. We study their dynamics in terms of read coverage and summit position, as well as the expression of the neighbouring genes. We propose that ePeak can be used to measure the richness of the epigenomic landscape underlying a biological process by identifying diverse regulatory regimes.

International audience; Single-cell RNA-sequencing (scRNAseq) experiments are becoming a standard tool for bench-scientists to explore the cellular diversity present in all tissues. Data produced by scRNAseq is technically complex and requires analytical workflows that are an active field of bioinformatics research, whereas a wealth of biological background knowledge is needed to guide the investigation. Thus, there is an increasing need to develop applications geared towards bench-scientists to help them abstract the technical challenges of the analysis so that they can focus on the science at play. It is also expected that such applications should support closer collaboration between bioinformaticians and bench-scientists by providing reproducible science tools. We present SCHNAPPs, a Graphical User Interface (GUI), designed to enable bench-scientists to autonomously explore and interpret scRNAseq data and associated annotations. The R/Shiny-based application allows following different steps of scRNAseq analysis workflows from Seurat or Scran packages: performing quality control on cells and genes, normalizing the expression matrix, integrating different samples, dimension reduction, clustering, and differential gene expression analysis. Visualization tools for exploring each step of the process include violin plots, 2D projections, Box-plots, alluvial plots, and histograms. An R-markdown report can be generated that tracks modifications and selected visualizations. The modular design of the tool allows it to easily integrate new visualizations and analyses by bioinformaticians. We illustrate the main features of the tool by applying it to the characterization of T cells in a scRNAseq and Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq) experiment of two healthy individuals.

Cockayne syndrome (CS) and UV-sensitivity syndrome (UVSS) are rare genetic disorders caused by mutation of the DNA repair and chromatin remodelling proteins CSA or CSB, but only CS patients display a progeroid and neurodegenerative phenotype. As epigenetic modifications constitute a well-established hallmark of ageing, we characterized genome-wide DNA methylation (DNAm) of fibroblasts from CS versus UVSS patients and healthy donors. The analysis of differentially methylated positions and regions revealed a CS-specific epigenetic signature, enriched in developmental transcription factors, transmembrane transporters, and cell adhesion factors. The CS-specific signature compared to DNAm changes in other progeroid diseases and regular ageing, identifyied commonalities and differences in epigenetic remodelling. CS shares DNAm changes with normal ageing more than other progeroid diseases do, and according to the methylation clock CS samples show up to 13-fold accelerated ageing. Thus, CS is characterized by a specific epigenomic signature that partially overlaps with and exacerbates DNAm changes occurring in physiological aging. Our results unveil new genes and pathways that are potentially relevant for the progeroid/degenerative CS phenotype.

We present ChIPflow, a Snakemake-based pipeline for epigenomic data from the raw fastq files to the differential analysis. It can be applied to any chromatin factor, e.g. histone modification or transcription factor, which can be profiled with ChIP-seq. ChIPflow streamlines critical steps like the quality assessment of the immunoprecipitation using cross-correlation and the replicate comparison for both narrow and broad peaks. For the differential analysis ChIPflow provides linear and nonlinear methods for normalisation between samples as well as conservative and stringent models for estimating the variance and testing the significance of the observed binding/marking differences.ChIPflow can process in parallel multiple chromatin factors with different experimental designs, number of biological replicates and/or conditions. It also facilitates the specific parametrisation of each dataset allowing both narrow or broad peak calling, as well as comparisons between the conditions using multiple statistical settings. Finally, complete reports are produced at the end of the bioinformatic and the statistical part of the analysis, which facilitate the data quality control and the interpretation of the results.We explored the discriminative power of the statistical settings for the differential analysis, using a published dataset of three histone marks (H3K4me3, H3K27ac and H3K4me1) and two transcription factors (Oct4 and Klf4) profiled with ChIP-seq in two biological conditions (shControl and shUbc9). We show that distinct results are obtained depending on the sources of ChIP-seq variability and the dynamics of the chromatin factor under study. We propose that ChIPflow can be used to measure the richness of the epigenomic landscape underlying a biological process by identifying diverse regulatory regimes and the associated genes sets.

Virulence of the neonatal pathogen Group B Streptococcus depends on the master regulator CovR. Inactivation of CovR leads to large-scale transcriptome remodeling and impairs almost every step of the interaction between the pathogen and the host. However, comparative analyses suggested a plasticity of the CovR signalling pathway in clinical isolates, probably due to the host selective pressure and leading to phenotypic heterogeneity in the bacterial population. Here, we characterize the CovR regulatory network in a strain representative of the hypervirulent lineage responsible of the majority of late-onset meningitidis. Genome-wide binding and transcriptome analysis demonstrated that CovR acts as a direct and global repressor of virulence genes, either as a primary regulator or with specialized co-regulators. Remarkably, CovR directly regulates genes of the pan-genome, including the two specific hypervirulent adhesins and horizontally acquired genes, as well as core-genes showing mutational biases in the population. Parallel analysis of the CovR network in a second isolate links strain-specificities to micro-evolutions in CovR-regulated promoters and to broad difference due to variability in CovR activation by phosphorylation. Our results highlight the direct, coordinated, and strain-specific regulation of virulence genes by CovR. This intra-species evolution of the signalling network reshapes bacterial-host interactions, increasing the potential for adaptation and the emergence of clone associated with specific diseases.

Supplemental Digital Content is available in the text, Rationale: Nocardia species are not commonly referred as primary infectious entities but rather as opportunistic pathogens. Infectious cases of Nocardia spp. in immunocompetent individuals are rare. Patient concerns: An immunocompetent 58-year-old patient presented with recurrent headaches. Diagnosis: A brain abscess was found and surgically drained. Matrix-assisted laser desorption ionization–time-of-flight mass spectrometry and heat shock protein 65/16S-23S rRNA gene intergenic spacer genotyping from the sample revealed the etiological agent as Nocardia beijingensis. Interventions: Meropenem/amikacin/Trimethoprim-sulfamethoxazole were administered. Outcomes: The infection persisted leading to the patient's death. Lessons: Here we present the first case of N. beijingensis infection of the central nervous system in an immunocompetent patient from Latin America. Further inquiry is needed to establish whether this species is more virulent than other Nocardia isolates.

International audience; Understanding general principles that safeguard cellular identity should reveal critical insights into common mechanisms underlying specification of varied cell types. Here, we show that SUMO modification acts to stabilize cell fate in a variety of contexts. Hyposumoylation enhances pluripotency reprogramming in vitro and in vivo, increases lineage transdifferentiation, and facilitates leukemic cell differentiation. Suppressing sumoylation in embryonic stem cells (ESCs) promotes their conversion into 2-cell-embryo-like (2C-like) cells. During reprogramming to pluripotency, SUMO functions on fibroblastic enhancers to retain somatic transcription factors together with Oct4, Sox2, and Klf4, thus impeding somatic enhancer inactivation. In contrast, in ESCs, SUMO functions on heterochromatin to silence the 2C program, maintaining both proper H3K9me3 levels genome-wide and repression of the Dux locus by triggering recruitment of the sumoylated PRC1.6 and Kap/Setdb1 repressive complexes. Together, these studies show that SUMO acts on chromatin as a glue to stabilize key determinants of somatic and pluripotent states.

Background Enterococcus faecium is ranked worldwide as one of the top ten pathogens identified in healthcare-associated infections (HAI) and is classified as one of the high priority pathogens for research and development of new antibiotics worldwide. Due to molecular biology techniques’ higher costs, the approach for identifying and controlling infectious diseases in developing countries has been based on clinical and epidemiological perspectives. Nevertheless, after an abrupt vancomycin-resistant Enterococcus faecium dissemination in the Méderi teaching hospital, ending up in an outbreak, further measures needed to be taken into consideration. The present study describes the vancomycin-resistant Enterococcus faecium pattern within Colombian’s largest installed-bed capacity hospital in 2016. Methods Thirty-three vancomycin-resistant Enterococcus faecium isolates were recovered during a 5-month period in 2016. Multilocus variable-number tandem-repeat analysis was used for molecular typing to determine clonality amongst strains. A modified time-place-sequence algorithm was used to trace VREfm spread patterns during the outbreak period and estimate transmission routes. Results Four clonal profiles were identified. Chronological clonal profile follow-up suggested a transitional spread from profile “A” to profile “B”, returning to a higher prevalence of “A” by the end of the study. Antibiotic susceptibility indicated high-level vancomycin-resistance in most isolates frequently matching vanA gene identification. Discussion Transmission analysis suggested cross-contamination via healthcare workers. Despite epidemiological control of the outbreak, post-outbreak isolates were still being identified as having outbreak-related clonal profile (A), indicating reduction but not eradication of this clonality. This study supports the use of combined molecular and epidemiological strategies in an approach to controlling infectious diseases. It contributes towards a more accurate evaluation of the effectiveness of the epidemiological measures taken regarding outbreak control and estimates the main cause related to the spread of this microorganism. Electronic supplementary material The online version of this article (10.1186/s12879-019-3877-7) contains supplementary material, which is available to authorized users.

Post-translational modifications of histones are important components of chromatin-level control of genome activity in eukaryotes. In order to clarify the biological function of chromatin marks, classification methods have been developed that partition genomic regions based on their chromatin composition. Spatial enrichment of histone modifications over genes is one of the many epigenomic dimensions that reflect the impact of chromatin dynamics on gene regulation. Using a clustering approach, we have classified genes according to their H3K27me3 and H3K4me3 marking in Arabidopsis leaves and find that multiple spatial profiles with specific functional properties can be distinguished in both cases. In particular, we show that different profiles specify distinct levels of gene expression. In addition, we find that genes with different H3K27me3 profiles can be distinguished by the length of their first intron and that the length of the first exon is an important parameter that shapes the distinct H3K4me3 profi...

Despite evolutionary conserved mechanisms to silence transposable element activity, there are drastic differences in the abundance of transposable elements even among closely related plant species. We conducted a de novo assembly for the 375 Mb genome of the perennial model plant, Arabis alpina. Analysing this genome revealed long-lasting and recent transposable element activity predominately driven by Gypsy long terminal repeat retrotransposons, which extended the low-recombining pericentromeres and transformed large formerly euchromatic regions into repeat-rich pericentromeric regions. This reduced capacity for long terminal repeat retrotransposon silencing and removal in A. alpina co-occurs with unexpectedly low levels of DNA methylation. Most remarkably, the striking reduction of symmetrical CG and CHG methylation suggests weakened DNA methylation maintenance in A. alpina compared with Arabidopsis thaliana. Phylogenetic analyses indicate a highly dynamic evolution of some components of methylation maintenance machinery that might be related to the unique methylation in A. alpina. Fil: Willing, Eva Maria. Max Planck Institute for Plant Breeding Research; Alemania Fil: Rawat, Vimal. Central European Institute of Technology; República Checa Fil: Mandáková, Terezie. Central European Institute of Technology; República Checa Fil: Maumus, Florian. INRA. Research Unit in Genomics; Francia Fil: James, Geo Velikkakam. Max Planck Institute for Plant Breeding Research; Alemania Fil: Nordström, Karl J. V.. Max Planck Institute for Plant Breeding Research; Alemania Fil: Becker, Claude. Max Planck Institute for Developmental Biology; Alemania Fil: Warthmann, Norman. Max Planck Institute for Developmental Biology; Alemania. The Australian National University; Australia Fil: Chica, Claudia. Centre National de la Recherche Scientifique; Francia Fil: Szarzynska, Bogna. Centre National de la Recherche Scientifique; Francia Fil: Zytnicki, Matthias. Max Planck Institute for Developmental Biology; Alemania Fil: Albani, Maria C.. Max Planck Institute for Plant Breeding Research; Alemania Fil: Kiefer, Christiane. Max Planck Institute for Plant Breeding Research; Alemania Fil: Bergonzi, Sara. Max Planck Institute for Plant Breeding Research; Alemania Fil: Castaings, Loren. Max Planck Institute for Plant Breeding Research; Alemania Fil: Mateos, Julieta Lisa. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina. Max Planck Institute for Plant Breeding Research; Alemania Fil: Berns, Markus C.. Max Planck Institute for Plant Breeding Research; Alemania Fil: Bujdoso, Nora. Max Planck Institute for Plant Breeding Research; Alemania Fil: Piofczyk, Thomas. Max Planck Institute for Plant Breeding Research; Alemania Fil: Roudier, François. Centre National de la Recherche Scientifique; Francia Fil: Carbonero, Pilar. Universidad Politécnica de Madrid; España Fil: Paz Ares, Javier. Consejo Superior de Investigaciones Cientificas; España Fil: Davis, Seth J.. Max Planck Institute for Plant Breeding Research; Alemania Fil: Pecinka, Ales. Max Planck Institute for Plant Breeding Research; Alemania Fil: Quesneville, Hadi. INRA. Research Unit in Genomics; Francia Fil: Colot, Vincent. Centre National de la Recherche Scientifique; Francia Fil: Lysak, Martin A.. Central European Institute of Technology; República Checa Fil: Weigel, Detlef. Max Planck Institute for Developmental Biology; Alemania Fil: Coupland, George. Max Planck Institute for Plant Breeding Research; Alemania Fil: Schneeberger, Korbinian. Max Planck Institute for Plant Breeding Research; Alemania

Se considera que los ácidos grasos provenientes de la biomasa microalgal tienen el potencial de ser utilizados como materia prima para la producción de biocombustibles como el biodiesel o para suplementos alimenticios. El tratamiento experimental consistió en cultivar las microalgas bajo diferentes parámetros de luz, incluidos el fotoperiodo y la longitud de onda. Para cada tratamiento, se cultivó la microalga Chlorella sp desde 0.5 ml y se escaló hasta 5 litros; se determinó la velocidad decrecimiento de cada microalga, y la composición de ácidos grasos de uno de los tratamientos fue establecida. El tratamiento de luz roja bajo un fotoperiodo de doce horas luz y doce horas oscuridad presentó la mayor tasa de crecimiento de 2.339 células/día;los ácidos grasos obtenidos mostraron una importante cantidad de ácido oleico, indicando un fuerte potencial de la biomasa de las microalgas paraser utilizadas en la industria alimenticia

Linear motifs are short, evolutionarily plastic components of regulatory proteins and provide low-affinity interaction interfaces. These compact modules play central roles in mediating every aspect of the regulatory functionality of the cell. They are particularly prominent in mediating cell signaling, controlling protein turnover and directing protein localization. Given their importance, our understanding of motifs is surprisingly limited, largely as a result of the difficulty of discovery, both experimentally and computationally. The Eukaryotic Linear Motif (ELM) resource at http://elm.eu.org provides the biological community with a comprehensive database of known experimentally validated motifs, and an exploratory tool to discover putative linear motifs in user-submitted protein sequences. The current update of the ELM database comprises 1800 annotated motif instances representing 170 distinct functional classes, including approximately 500 novel instances and 24 novel classes. Several older motif class entries have been also revisited, improving annotation and adding novel instances. Furthermore, addition of full-text search capabilities, an enhanced interface and simplified batch download has improved the overall accessibility of the ELM data. The motif discovery portion of the ELM resource has added conservation, and structural attributes have been incorporated to aid users to discriminate biologically relevant motifs from stochastically occurring non-functional instances. Author has checked copyright DG 09/11/12 Names (!) JG 2012-11-26

The Phospho.ELM resource ( http://phospho.elm.eu.org ) is a relational database designed to store in vivo and in vitro phosphorylation data extracted from the scientific literature and phosphoproteomic analyses. The resource has been actively developed for more than 7 years and currently comprises 42 574 serine, threonine and tyrosine non-redundant phosphorylation sites. Several new features have been implemented, such as structural disorder/order and accessibility information and a conservation score. Additionally, the conservation of the phosphosites can now be visualized directly on the multiple sequence alignment used for the score calculation. Finally, special emphasis has been put on linking to external resources such as interaction networks and other databases.

Linear motifs are short segments of multidomain proteins that provide regulatory functions independently of protein tertiary structure. Much of intracellular signalling passes through protein modifications at linear motifs. Many thousands of linear motif instances, most notably phosphorylation sites, have now been reported. Although clearly very abundant, linear motifs are difficult to predict de novo in protein sequences due to the difficulty of obtaining robust statistical assessments. The ELM resource at http://elm.eu.org/ provides an expanding knowledge base, currently covering 146 known motifs, with annotation that includes >1300 experimentally reported instances. ELM is also an exploratory tool for suggesting new candidates of known linear motifs in proteins of interest. Information about protein domains, protein structure and native disorder, cellular and taxonomic contexts is used to reduce or deprecate false positive matches. Results are graphically displayed in a ‘Bar Code’ format, which also displays known instances from homologous proteins through a novel ‘Instance Mapper’ protocol based on PHI-BLAST. ELM server output provides links to the ELM annotation as well as to a number of remote resources. Using the links, researchers can explore the motifs, proteins, complex structures and associated literature to evaluate whether candidate motifs might be worth experimental investigation. publishedVersion

Linear motifs are short and evolutionarily variable sequence patterns associated with particular functions often involving post-translational modifications, such as phosphorylation, acetylation, glycosylation, targeting signals for cellular compartments, protein cleavage sites and protein–protein interaction.Experimentally they are often neglected because their short length (4-10 residues long), and the fact that they often reside in disordered regions in proteins makes them difficult to detect. For a similar reason, using the sole regular expression to detect linear motifs matches in sequences has almost no predictive power because they are both statistically insignificant and prone to massive over-prediction.The Eukaryotic Linear Motif resource (ELM - "http://elm.eu.org":http://elm.eu.org) is a bioinformatics facility for investigating candidate short functional motifs in eukaryotic proteins. The ELM database to date has collected more than 140 motifs and their regular expressions patterns as well as information about their instances of occurrence, distribution, crystal structure, publications, etc.In order to reduce the over-prediction inherent to pattern matching against protein sequences and to discriminate true from false positive motif matches, context-based rules and logical filters are applied. The current version includes cell compartment, phylogeny, globular domain clash filters and the more recent structural filter based on known three-dimensional information that relies on structural information, such as residue solvent accessibility and secondary structure features. This implies that a candidate motif can be excluded from further consideration if the protein resides in the wrong cellular compartment or the motif is buried in the core of a globular domain. By considering additional types of context information, we expect that prediction of functional sites by ELM can be considerably improved. In cases where the user cannot provide relevant context information, we consider providing predictions of contextual information in order to improve the ELM performance. For example, since the ELM motif database has been annotated with biological process GO terms, the system could be prepared for addition of a new context filter using biological process.

BACKGROUND: Linear motifs are short modules of protein sequences that play a crucial role in mediating and regulating many protein-protein interactions. The function of linear motifs strongly depends on the context, e.g. functional instances mainly occur inside flexible regions that are accessible for interaction. Sometimes linear motifs appear as isolated islands of conservation in multiple sequence alignments. However, they also occur in larger blocks of sequence conservation, suggesting an active role for the neighbouring amino acids. RESULTS: The evolution of regions flanking 116 functional linear motif instances was studied. The conservation of the amino acid sequence and order/disorder tendency of those regions was related to presence/absence of the instance. For the majority of the analysed instances, the pairs of sequences conserving the linear motif were also observed to maintain a similar local structural tendency and/or to have higher local sequence conservation when compared to pairs of sequences where one is missing the linear motif. Furthermore, those instances have a higher chance to co-evolve with the neighbouring residues in comparison to the distant ones. Those findings are supported by examples where the regulation of the linear motif-mediated interaction has been shown to depend on the modifications (e.g. phosphorylation) at neighbouring positions or is thought to benefit from the binding versatility of disordered regions. CONCLUSION: The results suggest that flanking regions are relevant for linear motif-mediated interactions, both at the structural and sequence level. More interestingly, they indicate that the prediction of linear motif instances can be enriched with contextual information by performing a sequence analysis similar to the one presented here. This can facilitate the understanding of the role of these predicted instances in determining the protein function inside the broader context of the cellular network where they arise.

It is now clear that a detailed picture of cell regulation requires a comprehensive understanding of the abundant short protein motifs through which signaling is channeled. The current body of knowledge has slowly accumulated through piecemeal experimental investigation of individual motifs in signaling. Computational methods contributed little to this process. A new generation of bioinformatics tools will aid the future investigation of motifs in regulatory proteins, and the disordered polypeptide regions in which they frequently reside. Allied to high throughput methods such as phosphoproteomics, signaling networks are becoming amenable to experimental deconstruction. In this review, we summarise the current state of linear motif biology, which uses low affinity interactions to create cooperative, combinatorial and highly dynamic regulatory protein complexes. The discrete deterministic properties implicit to these assemblies suggest that models for cell regulatory networks in systems biology should neither be overly dependent on stochastic nor on smooth deterministic approximations.

Background Linear motifs (LMs) are abundant short regulatory sites used for modulating the functions of many eukaryotic proteins. They play important roles in post-translational modification, cell compartment targeting, docking sites for regulatory complex assembly and protein processing and cleavage. Methods for LM detection are now being developed that are strongly dependent on scores for motif conservation in homologous proteins. However, most LMs are found in natively disordered polypeptide segments that evolve rapidly, unhindered by structural constraints on the sequence. These regions of modular proteins are difficult to align using classical multiple sequence alignment programs that are specifically optimised to align the globular domains. As a consequence, poor motif alignment quality is hindering efforts to detect new LMs. Results We have developed a new benchmark, as part of the BAliBASE suite, designed to assess the ability of standard multiple alignment methods to detect and align LMs. The reference alignments are organised into different test sets representing real alignment problems and contain examples of experimentally verified functional motifs, extracted from the Eukaryotic Linear Motif (ELM) database. The benchmark has been used to evaluate and compare a number of multiple alignment programs. With distantly related proteins, the worst alignment program correctly aligns 48% of LMs compared to 73% for the best program. However, the performance of all the programs is adversely affected by the introduction of other sequences containing false positive motifs. The ranking of the alignment programs based on LM alignment quality is similar to that observed when considering full-length protein alignments, however little correlation was observed between LM and overall alignment quality for individual alignment test cases. Conclusion We have shown that none of the programs currently available is capable of reliably aligning LMs in distantly related sequences and we have highlighted a number of specific problems. The results of the tests suggest possible ways to improve program accuracy for difficult, divergent sequences.

Background The structure of many eukaryotic cell regulatory proteins is highly modular. They are assembled from globular domains, segments of natively disordered polypeptides and short linear motifs. The latter are involved in protein interactions and formation of regulatory complexes. The function of such proteins, which may be difficult to define, is the aggregate of the subfunctions of the modules. It is therefore desirable to efficiently predict linear motifs with some degree of accuracy, yet sequence database searches return results that are not significant. Results We have developed a method for scoring the conservation of linear motif instances. It requires only primary sequence-derived information (e.g. multiple alignment and sequence tree) and takes into account the degenerate nature of linear motif patterns. On our benchmarking, the method accurately scores 86% of the known positive instances, while distinguishing them from random matches in 78% of the cases. The conservation score is implemented as a real time application designed to be integrated into other tools. It is currently accessible via a Web Service or through a graphical interface. Conclusion The conservation score improves the prediction of linear motifs, by discarding those matches that are unlikely to be functional because they have not been conserved during the evolution of the protein sequences. It is especially useful for instances in non-structured regions of the proteins, where a domain masking filtering strategy is not applicable.

We study the nonrandomness of proteome sequences by analysing the correlations that arise between amino acids at a short and medium range, more specifically, between amino acids located 10 or 100 residues apart; respectively. We show that statistical models that consider these two types of correlation are more likely to seize the information contained in protein sequences and thus achieve good compression rates. Finally, we propose that the cause for this redundancy is related to the evolutionary origin of proteomes and protein sequences.

SUMMARYSenescent cells play important physiological- and pathophysiological roles in tumor suppression, tissue regeneration, and aging. While select genetic and epigenetic elements crucial for senescence induction were identified, the dynamics, underlying epigenetic mechanisms, and regulatory networks defining senescence competence, induction and maintenance remain poorly understood, precluding a deliberate therapeutic manipulation of these dynamic processes. Here, we show, using dynamic analyses of transcriptome and epigenome profiles, that the epigenetic state of enhancers predetermines their sequential activation during senescence. We demonstrate that activator protein 1 (AP-1) ‘imprints’ the senescence enhancer landscape effectively regulating transcriptional activities pertinent to the timely execution of the senescence program. We define and validate a hierarchical transcription factor (TF) network model and demonstrate its effectiveness for the design of senescence reprogramming experiments. Together, our findings define the dynamic nature and organizational principles of gene-regulatory elements driving the senescence program and reveal promising inroads for therapeutic manipulation of senescent cells.