Quantitative genetic analysis deciphers the impact of cis and trans regulation on cell-to-cell variability in protein expression levels

The authors wish to thank Dr Arianne Richard and Dr Luis Barreiro for their critical reading of the manuscript. The authors also wish to extend their gratitude to TwinsUK for sharing data. TwinsUK is funded by the Wellcome Trust, Medical Research Council, European Union, the National Institute for Health Research (NIHR)-funded BioResource, Clinical Research Facility and Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London.Peer reviewe

Quantification of stochastic noise of splicing and polyadenylation in Entamoeba histolytica

Alternative splicing and polyadenylation were observed pervasively in eukaryotic messenger RNAs. These alternative isoforms could either be consequences of physiological regulation or stochastic noise of RNA processing. To quantify the extent of stochastic noise in splicing and polyadenylation, we analyzed the alternative usage of splicing and polyadenylation sites in Entamoeba histolytica using RNA-Seq. First, we identified a large number of rarely spliced alternative junctions and then showed that the occurrence of these alternative splicing events is correlated with splicing site sequence, occurrence of constitutive splicing events and messenger RNA abundance. Our results implied the majority of these alternative splicing events are likely to be stochastic error of splicing machineries, and we estimated the corresponding error rates. Second, we observed extensive microheterogeneity of polyadenylation cleavage sites, and the extent of such microheterogeneity is correlated with the occurrence of constitutive cleavage events, suggesting most of such microheterogeneity is likely to be stochastic. Overall, we only observed a small fraction of alternative splicing and polyadenylation isoforms that are unlikely to be solely stochastic, implying the functional relevance of alternative splicing and polyadenylation in E. histolytica is limited. Lastly, we revised the gene models and annotated their 3′UTR in AmoebaDB, providing valuable resources to the community

Expansion of the SOS regulon of Vibrio cholerae through extensive transcriptome analysis and experimental validation

The SOS response is an almost ubiquitous response of cells to genotoxic stresses. The full complement of genes in the SOS regulon for Vibrio species has only been addressed through bioinformatic analyses predicting LexA binding box consensus and in vitro validation. Here, we perform whole transcriptome sequencing from Vibrio cholerae treated with mitomycin C as an SOS inducer to characterize the SOS regulon and other pathways affected by this treatment. Comprehensive transcriptional profiling allowed us to define the full landscape of promoters and transcripts active in V. cholerae. We performed extensive transcription start site (TSS) mapping as well as detection/quantification of the coding and non-coding RNA (ncRNA) repertoire in strain N16961. To improve TSS detection, we developed a new technique to treat RNA extracted from cells grown in various conditions. This allowed for identification of 3078 TSSs with an average 5'UTR of 116 nucleotides, and peak distribution between 16 and 64 nucleotides; as well as 629 ncRNAs. Mitomycin C treatment induced transcription of 737 genes and 28 ncRNAs at least 2 fold, while it repressed 231 genes and 17 ncRNAs. Data analysis revealed that in addition to the core genes known to integrate the SOS regulon, several metabolic pathways were induced. This study allowed for expansion of the Vibrio SOS regulon, as twelve genes (ubiEJB, tatABC, smpA, cep, VC0091, VC1190, VC1369-1370) were found to be co-induced with their adjacent canonical SOS regulon gene(s), through transcriptional read-through. Characterization of UV and mitomycin C susceptibility for mutants of these newly identified SOS regulon genes and other highly induced genes and ncRNAs confirmed their role in DNA damage rescue and protection. We show that genotoxic stress induces a pervasive transcriptional response, affecting almost 20% of the V. cholerae genes. We also demonstrate that the SOS regulon is larger than previously known, and its syntenic organization is conserved among Vibrio species. Furthermore, this specific co-localization is found in other γ-proteobacteria for genes recN-smpA and rmuC-tatABC, suggesting SOS regulon conservation in this phylum. Finally, we comment on the limitations of widespread NGS approaches for identification of all RNA species in bacteria

Human pre-valvular endocardial cells derived from pluripotent stem cells recapitulate cardiac pathophysiological valvulogenesis

Genetically modified mice have advanced our understanding of valve development and disease. Yet, human pathophysiological valvulogenesis remains poorly understood. Here we report that, by combining single cell sequencing and in vivo approaches, a population of human pre-valvular endocardial cells (HPVCs) can be derived from pluripotent stem cells. HPVCs express gene patterns conforming to the E9.0 mouse atrio-ventricular canal (AVC) endocardium signature. HPVCs treated with BMP2, cultured on mouse AVC cushions, or transplanted into the AVC of embryonic mouse hearts, undergo endothelial-to-mesenchymal transition and express markers of valve interstitial cells of different valvular layers, demonstrating cell specificity. Extending this model to patient-specific induced pluripotent stem cells recapitulates features of mitral valve prolapse and identified dysregulation of the SHH pathway. Concurrently increased ECM secretion can be rescued by SHH inhibition, thus providing a putative therapeutic target. In summary, we report a human cell model of valvulogenesis that faithfully recapitulates valve disease in a dish.We thank the Leducq Fondation for supporting Tui Neri, and funding this research under the framework of the MITRAL network and for generously awarding us for the equipment of our cell imaging facility in the frame of their program “Equipement de Recherche et Plateformes Technologiques” (ERPT to M.P.), the Genopole at Evry and the Fondation de la recherche Medicale (grant DEQ20100318280) for supporting the laboratory of Michel Puceat. Part of this work in South Carolina University was conducted in a facility constructed with support from the National Institutes of Health, Grant Number C06 RR018823 from the Extramural Research Facilities Program of the National Center for Research Resources. Other funding sources: National Heart Lung and Blood Institute: RO1-HL33756 (R.R.M.), COBRE P20RR016434–07 (R.R.M., R.A. N.), P20RR016434–09S1 (R.R.M. and R.A.N.); American Heart Association: 11SDG5270006 (R.A.N.); National Science Foundation: EPS-0902795 (R.R.M. and R.A. N.); American Heart Association: 10SDG2630130 (A.C.Z.), NIH: P01HD032573 (A.C. Z.), NIH: U54 HL108460 (A.C.Z), NCATS: UL1TR000100 (A.C.Z.); EH was supported by a fellowship of the Ministere de la recherche et de l’éducation in France.TM-M was supported by a fellowship from the Fondation Foulon Delalande and the Leducq Foundation. P.v.V. was sponsored by a UC San Diego Cardiovascular Scholarship Award and a Postdoctoral Fellowship from the California Institute for Regenerative Medicine (CIRM) Interdisciplinary Stem Cell Training Program II. S.M.E. was funded by a grant from the National Heart, Lung, and Blood Institute (HL-117649). A.T. is supported by the National Heart, Lung, and Blood Institute (R01-HL134664).S

Predicting structure and function of amino acid sequences using bioinformatical methods

Titelseiten, Inhaltsverzeichnis Abkürzungsverzeichnis KAPITEL 1 Einleitung > Schnittstellen humaner Signalpeptide > Konformation der Peptidylprolylbindung > Peptid Docking KAPITEL 2 Daten > Sequenzen der Schnittstellenregion humaner sekretorischer Proteine > Peptidylprolylsequenzen > Liganden-Docking KAPITEL 3 Methoden > Gütekriterien > Kodierung der Daten > Vergleich von Kodierungen > Informationsanalyse > Lineare Trennverfahren > Schwerpunktanalyse (Zentroid-Verfahren) > Bayes-Prediktor > Mahalanobis-Distanzanalyse > Künstliche Neuronale Netze > Perzeptron > Mehrlagige Neuronale Netze > Neuronale Netze mit adaptiver Kodierung > Lernstrategien > Identifikation von Schnittstellen in Sequenzen unter Verwendung von Künstlichen Neuronalen Netzen > Selbstorganisierende Karten (Kohonenkarten, SOK) > Peptid Docking KAPITEL 4 Ergebnisse > Schnittstellen humaner Signalpeptide > Informationsanalyse > Positionsabhängige Häufigkeitsverteilung von Aminosäuren in Schnittstellenpeptiden > Schwerpunktanalyse > Bayes-Prediktor > Hauptkomponentenanalyse (PCA) > Mahalanobis-Distanzanalyse > Künstliche Neuronale Netze > Lernstrategien > Vergleich von Kodierungsmethoden > Kohonen Netze > Vorhersage der cis/trans- Konformation von Peptidylprolylbindungen > Informationsanalyse > Schwerpunktanalyse > Hauptkomponentenanalyse > Mahalanobis-Distanzanalyse > Adaptive Kodierung > Kohonennetze > Klassifikation und Information der Oberflächeneigenschaften > 3D-Umgebung > Sekundärstruktur am Prolin > Design von Proteinliganden > Simulierte Molekulare Evolution > Peptid-Docking KAPITEL 5 Diskussion > Schnittstellen humaner Signalpeptide > Konformationsvorhersage der Peptidylprolylbindungen > Ligandendesign > Simulierte Molekulare Evolution > Peptid-Docking KAPITEL 6 Literaturverzeichnis Zusammenfassung KAPITEL 8 Anhang I > Humane Schnittstellendaten KAPITEL 9 Anhang II > Physikochemische Eigenschaften von Amiosäuren KAPITEL 10 Anhang III: > Gruppierung der PDB Datenbank nach WechselwirkungsklassenVerschiede Methoden zur Funktions- und Strukturvorhersage ausgehend von der Primärstruktur wurden vorgestellt. Ein adaptiv kodierendes Neuronales Netz (ACN) ist entwickelt worden, mit dem es möglich ist, die charakteristischen physikochemischen Eigenschaften in Proteinsequenzen zu bestimmen. Hiermit ist es möglich, 96% der experimentell verifizierten Schnittstellen von humanen sekretorischen Proteinen vorherzusagen. Bisher waren nur Vorhersagen mit einer Genauigkeit von bis zu 68% möglich. Außerdem können mit den ACN Mutationen in den Schnittstellenregionen humaner sekretorischer Proteine korrekt vorhergesagt werden. Es wurde somit erfolgreich gezeigt, wie aus der Sequenzinformation auf eine Funktion geschlossen werden kann. Die Vorhersage der Konformation von Peptidylprolylbindungen ist mit dem vorliegenden Datensatz nicht zufriedenstellend lösbar. Für eine erfolgversprechende Analyse müßte die 10- bis 20-fache Menge an Daten vorliegen. Trotzdem konnte gezeigt werden, daß die MHC-I Proteine eine charakteristische cis-Prolingruppe besitzen, die eine Unterscheidung von anderen Proteinen erlaubt. Die Simulierte Molekulare Evolution wurde erfolgreich zum Entwurf zellprotektiver Peptide angewendet. Ein Algorithmus zum Design inhibitorischer Proteine, basierend auf der Analyse von Protein-Protein-Wechselwirkungen, wurde entwickelt und erfolgreich auf zellprotektive Experimente getestet.Serveral methods were presented for the prediction of function and structure based on the primary structure of proteins. An adaptive coding artificial neural network (ACN) was developed that characterizes the physico chemical features in protein sequences. It is now possible to identify 96% of experimentally verified cleavage sites in human secretory proteins. Hitherto only 68% of an independent test data were correctly identified. Furthermore mutations within the cleavage site region of human secretory proteins are correctly predicted. It is shown how to use ACN to build up a sequence activity relation. It was not possible to predict the conformation of the peptidyl prolyl bond using the available data. However there should be 10 - 20 times more non-homologues sequence data to make reliable predictions. Nevertheless, it was possible to show that MHC-I proteins have a characteristic cis-proline group that can be used to distinguish those proteins from others. The simulated molecular evolution was successfully applied to design cell protective peptides against the Human Rhinovirus. An algorithm for the design of inhibitory peptides using the structual information of the receptor protein has been developed. Using this method other peptides were designed. All peptides were experimentally tested, showing that theoretical and practical results are in agreement

SCHNAPPs -Single Cell sHiNy APPlication(s)

ABSTRACTMotivation Single-cell RNA-sequencing (scRNAseq) experiments are becoming a standard tool for bench-scientists to explore the cellular diversity present in all tissues. On one hand, the data produced by scRNASeq is technically complex, with analytical workflows that are still very much an active field of bioinformatics research, and on the other hand, a wealth of biological background knowledge is often needed to guide the investigation. Therefore, 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.Results We present SCHNAPPs, a computer program designed to enable bench-scientists to autonomously explore and interpret single cell RNA-seq expression data and associated annotations. The Shiny-based application allows selecting genes and cells of interest, performing quality control, normalization, clustering, and differential expression analyses, applying standard workflows from Seurat (Stuart et al., 2019) or Scran (Lun et al., 2016) packages, and most of the common visualizations. An R-markdown report can be generated that tracks the modifications, and selected visualizations facilitating communication and reproducibility between bench-scientist and bioinformatician. The modular design of the tool allows to easily integrate new visualizations and analyses by bioinformaticians. We still recommend that a data analysis specialist oversees the analysis and interpretation.Availability The SCHNAPPs application, docker file, and documentation are available on GitHub: https://c3bi-pasteur-fr.github.io/UTechSCB-SCHNAPPs; Example contribution are available at the following GitHub site: https://github.com/baj12/SCHNAPPsContributions

SpdC, a novel virulence factor, controls histidine kinase activity in Staphylococcus aureus.

The success of Staphylococcus aureus, as both a human and animal pathogen, stems from its ability to rapidly adapt to a wide spectrum of environmental conditions. Two-component systems (TCSs) play a crucial role in this process. Here, we describe a novel staphylococcal virulence factor, SpdC, an Abi-domain protein, involved in signal sensing and/or transduction. We have uncovered a functional link between the WalKR essential TCS and the SpdC Abi membrane protein. Expression of spdC is positively regulated by the WalKR system and, in turn, SpdC negatively controls WalKR regulon genes, effectively constituting a negative feedback loop. The WalKR system is mainly involved in controlling cell wall metabolism through regulation of autolysin production. We have shown that SpdC inhibits the WalKR-dependent synthesis of four peptidoglycan hydrolases, SceD, SsaA, LytM and AtlA, as well as impacting S. aureus resistance towards lysostaphin and cell wall antibiotics such as oxacillin and tunicamycin. We have also shown that SpdC is required for S. aureus biofilm formation and virulence in a murine septicemia model. Using protein-protein interactions in E. coli as well as subcellular localization in S. aureus, we showed that SpdC and the WalK kinase are both localized at the division septum and that the two proteins interact. In addition to WalK, our results indicate that SpdC also interacts with nine other S. aureus histidine kinases, suggesting that this membrane protein may act as a global regulator of TCS activity. Indeed, using RNA-Seq analysis, we showed that SpdC controls the expression of approximately one hundred genes in S. aureus, many of which belong to TCS regulons

Molecular signature of the imprintosome complex at the mating-type locus in fission yeast.

International audienceGenetic and molecular studies have indicated that an epigenetic imprint at mat1, the sexual locus of fission yeast, initiates mating type switching. The polar DNA replication of mat1 generates an imprint on the Watson strand. The process by which the imprint is formed and maintained through the cell cycle remains unclear. To understand better the mechanism of imprint formation and stability, we characterized the recruitment of early players of mating type switching at the mat1 region. We found that the switch activating protein 1 (Sap1) is preferentially recruited inside the mat1M allele on a sequence (SS13) that enhances the imprint. The lysine specific demethylases, Lsd1/2, that control the replication fork pause at MPS1 and the formation of the imprint are specifically drafted inside of mat1, regardless of the allele. The CENP-B homolog, Abp1, is highly enriched next to mat1 but it is not required in the process. Additionally, we established the computational signature of the imprint. Using this signature, we show that both sides of the imprinted molecule are bound by Lsd1/2 and Sap1, suggesting a nucleoprotein protective structure defined as imprintosome