Recurrent chromosomal translocations in sarcomas create a megacomplex that mislocalizes NuA4/TIP60 to Polycomb target loci.

Chromosomal translocations frequently promote carcinogenesis by producing gain-of-function fusion proteins. Recent studies have identified highly recurrent chromosomal translocations in patients with endometrial stromal sarcomas (ESSs) and ossifying fibromyxoid tumors (OFMTs), leading to an in-frame fusion of PHF1 (PCL1) to six different subunits of the NuA4/TIP60 complex. While NuA4/TIP60 is a coactivator that acetylates chromatin and loads the H2A.Z histone variant, PHF1 is part of the Polycomb repressive complex 2 (PRC2) linked to transcriptional repression of key developmental genes through methylation of histone H3 on lysine 27. In this study, we characterize the fusion protein produced by the EPC1-PHF1 translocation. The chimeric protein assembles a megacomplex harboring both NuA4/TIP60 and PRC2 activities and leads to mislocalization of chromatin marks in the genome, in particular over an entire topologically associating domain including part of the HOXD cluster. This is linked to aberrant gene expression-most notably increased expression of PRC2 target genes. Furthermore, we show that JAZF1-implicated with a PRC2 component in the most frequent translocation in ESSs, JAZF1-SUZ12-is a potent transcription activator that physically associates with NuA4/TIP60, its fusion creating outcomes similar to those of EPC1-PHF1 Importantly, the specific increased expression of PRC2 targets/HOX genes was also confirmed with ESS patient samples. Altogether, these results indicate that most chromosomal translocations linked to these sarcomas use the same molecular oncogenic mechanism through a physical merge of NuA4/TIP60 and PRC2 complexes, leading to mislocalization of histone marks and aberrant Polycomb target gene expression.

LC-SRM Combined With Machine Learning Enables Fast Identification and Quantification of Bacterial Pathogens in Urinary Tract Infections.

Urinary tract infections (UTIs) are a worldwide health problem. Fast and accurate detection of bacterial infection is essential to provide appropriate antibiotherapy to patients and to avoid the emergence of drug-resistant pathogens. While the gold standard requires 24 h to 48 h of bacteria culture prior to MALDI-TOF species identification, we propose a culture-free workflow, enabling bacterial identification and quantification in less than 4 h using 1 ml of urine. After rapid and automatable sample preparation, a signature of 82 bacterial peptides, defined by machine learning, was monitored in LC-MS, to distinguish the 15 species causing 84% of the UTIs. The combination of the sensitivity of the SRM mode on a triple quadrupole TSQ Altis instrument and the robustness of capillary flow enabled us to analyze up to 75 samples per day, with 99.2% accuracy on bacterial inoculations of healthy urines. We have also shown our method can be used to quantify the spread of the infection, from 8 × 104 to 3 × 107 CFU/ml. Finally, the workflow was validated on 45 inoculated urines and on 84 UTI-positive urine from patients, with respectively 93.3% and 87.1% of agreement with the culture-MALDI procedure at a level above 1 × 105 CFU/ml corresponding to an infection requiring antibiotherapy.

Use of Elasticsearch-based business intelligence tools for integration and visualization of biological data.

The emergence of massive datasets exploring the multiple levels of molecular biology has made their analysis and knowledge transfer more complex. Flexible tools to manage big biological datasets could be of great help for standardizing the usage of developed data visualizations and integration methods. Business intelligence (BI) tools have been used in many fields as exploratory tools. They have numerous connectors to link numerous data repositories with a unified graphic interface, offering an overview of data and facilitating interpretation for decision makers. BI tools could be a flexible and user-friendly way of handling molecular biological data with interactive visualizations. However, it is rather uncommon to see such tools used for the exploration of massive and complex datasets in biological fields. We believe that two main obstacles could be the reason. Firstly, we posit that the way to import data into BI tools are not compatible with biological databases. Secondly, BI tools may not be adapted to certain particularities of complex biological data, namely, the size, the variability of datasets and the availability of specialized visualizations. This paper highlights the use of five BI tools (Elastic Kibana, Siren Investigate, Microsoft Power BI, Salesforce Tableau and Apache Superset) onto which the massive data management repository engine called Elasticsearch is compatible. Four case studies will be discussed in which these BI tools were applied on biological datasets with different characteristics. We conclude that the performance of the tools depends on the complexity of the biological questions and the size of the datasets.

Non-canonical transcriptional regulation of the poor prognostic factor UGT2B17 in chronic lymphocytic leukemic and normal B cells.

BACKGROUND: High expression of the glycosyltransferase UGT2B17 represents an independent adverse prognostic marker in chronic lymphocytic leukemia (CLL). It also constitutes a predictive marker for therapeutic response and a drug resistance mechanism. The key determinants driving expression of the UGT2B17 gene in normal and leukemic B-cells remain undefined. The UGT2B17 transcriptome is complex and is comprised of at least 10 alternative transcripts, identified by previous RNA-sequencing of liver and intestine. We hypothesized that the transcriptional program regulating UGT2B17 in B-lymphocytes is distinct from the canonical expression previously characterized in the liver. RESULTS: RNA-sequencing and genomics data revealed a specific genomic landscape at the UGT2B17 locus in normal and leukemic B-cells. RNA-sequencing and quantitative PCR data indicated that the UGT2B17 enzyme is solely encoded by alternative transcripts expressed in CLL patient cells and not by the canonical transcript widely expressed in the liver and intestine. Chromatin accessible regions (ATAC-Seq) in CLL cells mapped with alternative promoters and non-coding exons, which may be derived from endogenous retrotransposon elements. By luciferase reporter assays, we identified key cis-regulatory STAT3, RELA and interferon regulatory factor (IRF) binding sequences driving the expression of UGT2B17 in lymphoblastoid and leukemic B-cells. Electrophoretic mobility shift assays and pharmacological inhibition demonstrated key roles for the CLL prosurvival transcription factors STAT3 and NF-κB in the leukemic expression of UGT2B17. CONCLUSIONS: UGT2B17 expression in B-CLL is driven by key regulators of CLL progression. Our data suggest that a NF-κB/STAT3/IRF/UGT2B17 axis may represent a novel B-cell pathway promoting disease progression and drug resistance.

Behavioral as well as hippocampal transcriptomic and microglial responses differ across sexes in adult mouse offspring exposed to a dual genetic and environmental challenge.

INTRODUCTION: A wide range of positive, negative, and cognitive symptoms compose the clinical presentation of schizophrenia. Schizophrenia is a multifactorial disorder in which genetic and environmental risk factors interact for a full emergence of the disorder. Infectious challenges during pregnancy are a well-known environmental risk factor for schizophrenia. Also, genetic variants affecting the function of fractalkine signaling between neurons and microglia were linked to schizophrenia. Translational animal models recapitulating these complex gene-environment associations have a great potential to untangle schizophrenia neurobiology and propose new therapeutic strategies. METHODS: Given that genetic variants affecting the function of fractalkine signaling between neurons and microglia were linked to schizophrenia, we compared the outcomes of a well-characterized model of maternal immune activation induced using the viral mimetic polyinosinic:polycytidylic acid (Poly I:C) in wild-type versus fractalkine receptor knockout mice. Possible behavioral and immune alterations were assessed in male and female offspring during adulthood. Considering the role of the hippocampus in schizophrenia, microglial analyses and bulk RNA sequencing were performed within this region to assess the neuroimmune dynamics at play. Males and females were examined separately. RESULTS: Offspring exposed to the dual challenge paradigm exhibited symptoms relevant to schizophrenia and unpredictably to mood disorders. Males displayed social and cognitive deficits related to schizophrenia, while females mainly presented anxiety-like behaviors related to mood disorders. Hippocampal microglia in females exposed to the dual challenge were hypertrophic, indicative of an increased surveillance, whereas those in males showed on the other end of the spectrum blunted morphologies with a reduced phagocytosis. Hippocampal bulk-RNA sequencing further revealed a downregulation in females of genes related to GABAergic transmission, which represents one of the main proposed causes of mood disorders. CONCLUSIONS: Building on previous results, we identified in the current study distinctive behavioral phenotypes in female mice exposed to a dual genetic and environmental challenge, thus proposing a new model of neurodevelopmentally-associated mood and affective symptoms. This paves the way to future sex-specific investigations into the susceptibility to developmental challenges using animal models based on genetic and immune vulnerability as presented here.

Immune-related transcriptomic and epigenetic reconfiguration in BV2 cells after lipopolysaccharide exposure: an in vitro omics integrative study.

BACKGROUND: Molecular alterations affecting microglia have been consistently associated with the inflammatory response. These cells can have pro- or anti-inflammatory activity, phenotypes thought to be regulated by epigenetic mechanisms. Still, little is known about the details on how epigenetic marks regulate the expression of genes in the context of an inflammatory response. METHODS: Through CUT&RUN, we profiled four genome-wide histone marks (HM) (H3K4me1, H3K4me3, H3K27ac, and H3K27me3) in lipopolysaccharide-exposed cells and compared their distributions to control cells. Transcriptomic profiles were determined through RNA-seq and differentially expressed genes were identified and contrasted with the epigenetic landscapes. Other downstream analyses were also included in this study. RESULTS: Our results illustrate an effectively induced M1 phenotype in microglial cells derived from LPS exposure. We observed differential bound regions associated with the genes classically involved in the inflammatory response in the expected direction according to each histone modification. Consistently, our transcriptomic analysis yielded a conspicuous illustration of the LPS-induced immune activity showing the up-regulation of Nf-κB-induced mRNAs (TNF-α, nfκbiz, nfκbia) and other important genes (Marco, Il-6, etc.). Furthermore, we integrated both omics profiles and identified an important reconfiguration of the genome induced by LPS. The latter was depicted by 8 different chromatin states that changed between conditions and that associated with unique clusters of differentially expressed genes, which not only represented regulatory elements, but also underlined distinct biological functions (inhibition of morphogenesis; changes in metabolism, homeostasis, and cytokine regulation; activation of the inflammatory response). CONCLUSION: This study exhibits important differences in the distribution of histone modifications in treated and control BV2 cells, constituting an epigenetic reconfiguration that leads to the inflammatory response. Also, it highlights the importance of these marks' regulatory role in gene expression and provides possible targets for further studies in the context of inflammation.

MRG Proteins Are Shared by Multiple Protein Complexes With Distinct Functions.

MRG15/MORF4L1 is a highly conserved protein in eukaryotes that contains a chromodomain (CHD) recognizing methylation of lysine 36 on histone H3 (H3K36me3) in chromatin. Intriguingly, it has been reported in the literature to interact with several different factors involved in chromatin modifications, gene regulation, alternative mRNA splicing, and DNA repair by homologous recombination. To get a complete and reliable picture of associations in physiological conditions, we used genome editing and tandem affinity purification to analyze the stable native interactome of human MRG15, its paralog MRGX/MORF4L2 that lacks the CHD, and MRGBP (MRG-binding protein) in isogenic K562 cells. We found stable interchangeable association of MRG15 and MRGX with the NuA4/TIP60 histone acetyltransferase/chromatin remodeler, Sin3B histone deacetylase/demethylase, ASH1L histone methyltransferase, and PALB2-BRCA2 DNA repair protein complexes. These associations were further confirmed and analyzed by CRISPR tagging of endogenous proteins and comparison of expressed isoforms. Importantly, based on structural information, point mutations could be introduced that specifically disrupt MRG15 association with some complexes but not others. Most interestingly, we also identified a new abundant native complex formed by MRG15/X-MRGBP-BRD8-EP400NL (EP400 N-terminal like) that is functionally similar to the yeast TINTIN (Trimer Independent of NuA4 for Transcription Interactions with Nucleosomes) complex. Our results show that EP400NL, being homologous to the N-terminal region of NuA4/TIP60 subunit EP400, creates TINTIN by competing for BRD8 association. Functional genomics indicate that human TINTIN plays a role in transcription of specific genes. This is most likely linked to the H4ac-binding bromodomain of BRD8 along the H3K36me3-binding CHD of MRG15 on the coding region of transcribed genes. Taken together, our data provide a complete detailed picture of human MRG proteins-associated protein complexes, which are essential to understand and correlate their diverse biological functions in chromatin-based nuclear processes.

Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver.

BACKGROUND: Vitamin C (ascorbate) is a water-soluble antioxidant and an important cofactor for various biosynthetic and regulatory enzymes. Mice can synthesize vitamin C thanks to the key enzyme gulonolactone oxidase (Gulo) unlike humans. In the current investigation, we used Gulo-/- mice, which cannot synthesize their own ascorbate to determine the impact of this vitamin on both the transcriptomics and proteomics profiles in the whole liver. The study included Gulo-/- mouse groups treated with either sub-optimal or optimal ascorbate concentrations in drinking water. Liver tissues of females and males were collected at the age of four months and divided for transcriptomics and proteomics analysis. Immunoblotting, quantitative RT-PCR, and polysome profiling experiments were also conducted to complement our combined omics studies. RESULTS: Principal component analyses revealed distinctive differences in the mRNA and protein profiles as a function of sex between all the mouse cohorts. Despite such sexual dimorphism, Spearman analyses of transcriptomics data from females and males revealed correlations of hepatic ascorbate levels with transcripts encoding a wide array of biological processes involved in glucose and lipid metabolisms as well as in the acute-phase immune response. Moreover, integration of the proteomics data showed that ascorbate modulates the abundance of various enzymes involved in lipid, xenobiotic, organic acid, acetyl-CoA, and steroid metabolism mainly at the transcriptional level, especially in females. However, several proteins of the mitochondrial complex III significantly correlated with ascorbate concentrations in both males and females unlike their corresponding transcripts. Finally, poly(ribo)some profiling did not reveal significant enrichment difference for these mitochondrial complex III mRNAs between Gulo-/- mice treated with sub-optimal and optimal ascorbate levels. CONCLUSIONS: Thus, the abundance of several subunits of the mitochondrial complex III are regulated by ascorbate at the post-transcriptional levels. Our extensive omics analyses provide a novel resource of altered gene expression patterns at the transcriptional and post-transcriptional levels under ascorbate deficiency.

Interpretation of network-based integration from multi-omics longitudinal data.

Multi-omics integration is key to fully understand complex biological processes in an holistic manner. Furthermore, multi-omics combined with new longitudinal experimental design can unreveal dynamic relationships between omics layers and identify key players or interactions in system development or complex phenotypes. However, integration methods have to address various experimental designs and do not guarantee interpretable biological results. The new challenge of multi-omics integration is to solve interpretation and unlock the hidden knowledge within the multi-omics data. In this paper, we go beyond integration and propose a generic approach to face the interpretation problem. From multi-omics longitudinal data, this approach builds and explores hybrid multi-omics networks composed of both inferred and known relationships within and between omics layers. With smart node labelling and propagation analysis, this approach predicts regulation mechanisms and multi-omics functional modules. We applied the method on 3 case studies with various multi-omics designs and identified new multi-layer interactions involved in key biological functions that could not be revealed with single omics analysis. Moreover, we highlighted interplay in the kinetics that could help identify novel biological mechanisms. This method is available as an R package netOmics to readily suit any application.

A Machine Learning Approach to Identify Key Residues Involved in Protein-Protein Interactions Exemplified with SARS-CoV-2 Variants.

Human infection with the coronavirus disease 2019 (COVID-19) is mediated by the binding of the spike protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to the human angiotensin-converting enzyme 2 (ACE2). The frequent mutations in the receptor-binding domain (RBD) of the spike protein induced the emergence of variants with increased contagion and can hinder vaccine efficiency. Hence, it is crucial to better understand the binding mechanisms of variant RBDs to human ACE2 and develop efficient methods to characterize this interaction. In this work, we present an approach that uses machine learning to analyze the molecular dynamics simulations of RBD variant trajectories bound to ACE2. Along with the binding free energy calculation, this method was used to characterize the major differences in ACE2-binding capacity of three SARS-CoV-2 RBD variants-namely the original Wuhan strain, Omicron BA.1, and the more recent Omicron BA.5 sublineages. Our analyses assessed the differences in binding free energy and shed light on how it affects the infectious rates of different variants. Furthermore, this approach successfully characterized key binding interactions and could be deployed as an efficient tool to predict different binding inhibitors to pave the way for new preventive and therapeutic strategies.

Transcriptomic Analysis of Mineralized Adipose-Derived Stem Cell Tissues for Calcific Valve Disease Modelling.

Calcific aortic valve disease (CAVD) is characterized by the fibrosis and mineralization of the aortic valve, which leads to aortic stenosis and heart failure. At the cellular level, this is due to the osteoblastic-like differentiation of valve interstitial cells (VICs), resulting in the calcification of the tissue. Unfortunately, human VICs are not readily available to study CAVD pathogenesis and the implicated mechanisms in vitro; however, adipose-derived stromal/stem cells (ASCs), carrying the patient's specific genomic features, have emerged as a promising cell source to model cardiovascular diseases due to their multipotent nature, availability, and patient-specific characteristics. In this study, we describe a comprehensive transcriptomic analysis of tissue-engineered, scaffold-free, ASC-embedded mineralized tissue sheets using bulk RNA sequencing. Bioinformatic and gene set enrichment analyses revealed the up-regulation of genes associated with the organization of the extracellular matrix (ECM), suggesting that the ECM could play a vital role in the enhanced mineralization observed in these tissue-engineered ASC-embedded sheets. Upon comparison with publicly available gene expression datasets from CAVD patients, striking similarities emerged regarding cardiovascular diseases and ECM functions, suggesting a potential link between ECM gene expression and CAVDs pathogenesis. A matrisome-related sub-analysis revealed the ECM microenvironment promotes the transcriptional activation of the master gene runt-related transcription factor 2 (RUNX2), which is essential in CAVD development. Tissue-engineered ASC-embedded sheets with enhanced mineralization could be a valuable tool for research and a promising avenue for the identification of more effective aortic valve replacement therapies.

Chromosome-level assembly of the Rangifer tarandus genome and validation of cervid and bovid evolution insights.

BACKGROUND: Genome assembly into chromosomes facilitates several analyses including cytogenetics, genomics and phylogenetics. Despite rapid development in bioinformatics, however, assembly beyond scaffolds remains challenging, especially in species without closely related well-assembled and available reference genomes. So far, four draft genomes of Rangifer tarandus (caribou or reindeer, a circumpolar distributed cervid species) have been published, but none with chromosome-level assembly. This emblematic northern species is of high interest in ecological studies and conservation since most populations are declining. RESULTS: We have designed specific probes based on Oligopaint FISH technology to upgrade the latest published reindeer and caribou chromosome-level genomes. Using this oligonucleotide-based method, we found six mis-assembled scaffolds and physically mapped 68 of the largest scaffolds representing 78% of the most recent R. tarandus genome assembly. Combining physical mapping and comparative genomics, it was possible to document chromosomal evolution among Cervidae and closely related bovids. CONCLUSIONS: Our results provide validation for the current chromosome-level genome assembly as well as resources to use chromosome banding in studies of Rangifer tarandus.

Specific alterations in riboproteomes composition of isonicotinic acid treated arabidopsis seedlings.

Plants have developed strategies to deal with the great variety of challenges they are exposed to. Among them, common targets are the regulation of transcription and translation to finely modulate protein levels during both biotic and abiotic stresses. Increasing evidence suggests that ribosomes are highly adaptable modular supramolecular structures which remodel to adapt to stresses. Each Arabidopsis thaliana ribosome consists of approximately 81 distinct ribosomal proteins (RPs), each of which is encoded by two to seven genes. To investigate the identity of ribosomal proteins of the small subunit (RPS) and of the large subunit (RPL) as well as ribosomes-associated proteins, we analysed by LC/MS/MS immunopurified ribosomes from A. thaliana leaves treated with isonicotinic acid (INA), an inducer of plant innate immunity. We quantified a total of 2084 proteins. 165 ribosome-associated proteins showed increased abundance while 52 were less abundant. Of the 52 identified RPS (from a possibility of 104 encoding genes), 15 were deregulated. Similarly, from the 148 possible RPL, 80 were detected and 9 were deregulated. Our results revealed potential candidates involved in innate immunity that could be interesting targets for functional genomic studies.

Early Diagnosis: End-to-End CNN-LSTM Models for Mass Spectrometry Data Classification.

Liquid chromatography-mass spectrometry (LC-MS) is a powerful method for cell profiling. The use of LC-MS technology is a tool of choice for cancer research since it provides molecular fingerprints of analyzed tissues. However, the ubiquitous presence of noise, the peaks shift between acquisitions, and the huge amount of information owing to the high dimensionality of the data make rapid and accurate cancer diagnosis a challenging task. Deep learning (DL) models are not only effective classifiers but are also well suited to jointly learn feature representation and classification tasks. This is particularly relevant when applied to raw LC-MS data and hence avoid the need for costly preprocessing and complicated feature selection. In this study, we propose a new end-to-end DL methodology that addresses all of the above challenges at once, while preserving the high potential of LC-MS data. Our DL model is designed to early discriminate between tumoral and normal tissues. It is a combination of a convolutional neural network (CNN) and a long short-term memory (LSTM) Network. The CNN network allows for significantly reducing the high dimensionality of the data while learning spatially relevant features. The LSTM network enables our model to capture temporal patterns. We show that our model outperforms not only benchmark models but also state-of-the-art models developed on the same data. Our framework is a promising strategy for improving early cancer detection during a diagnostic process.

Integrative analysis of green ash phloem transcripts and proteins during an emerald ash borer infestation.

BACKGROUND: Emerald ash borer (Agrilus planipennis; EAB) is an Asian insect species that has been invasive to North America for 20 years. During this time, the emerald ash borer has killed tens of millions of American ash (Fraxinus spp) trees. Understanding the inherent defenses of susceptible American ash trees will provide information to breed new resistant varieties of ash trees. RESULTS: We have performed RNA-seq on naturally infested green ash (F. pennsylvanica) trees at low, medium and high levels of increasing EAB infestation and proteomics on low and high levels of EAB infestation. Most significant transcript changes we detected occurred between the comparison of medium and high levels of EAB infestation, indicating that the tree is not responding to EAB until it is highly infested. Our integrative analysis of the RNA-Seq and proteomics data identified 14 proteins and 4 transcripts that contribute most to the difference between highly infested and low infested trees. CONCLUSIONS: The putative functions of these transcripts and proteins suggests roles of phenylpropanoid biosynthesis and oxidation, chitinase activity, pectinesterase activity, strigolactone signaling, and protein turnover.

Hedgehog signaling regulates Wolffian duct development through the primary cilium†.

Primary cilia play pivotal roles in embryonic patterning and organogenesis through transduction of the Hedgehog signaling pathway (Hh). Although mutations in Hh morphogens impair the development of the gonads and trigger male infertility, the contribution of Hh and primary cilia in the development of male reproductive ductules, including the epididymis, remains unknown. From a Pax2Cre; IFT88fl/fl knock-out mouse model, we found that primary cilia deletion is associated with imbalanced Hh signaling and morphometric changes in the Wolffian duct (WD), the embryonic precursor of the epididymis. Similar effects were observed following pharmacological blockade of primary cilia formation and Hh modulation on WD organotypic cultures. The expression of genes involved in extracellular matrix, mesenchymal-epithelial transition, canonical Hh and WD development was significantly altered after treatments. Altogether, we identified the primary cilia-dependent Hh signaling as a master regulator of genes involved in WD development. This provides new insights regarding the etiology of sexual differentiation and male infertility issues.

timeOmics: an R package for longitudinal multi-omics data integration.

MOTIVATION: Multi-omics data integration enables the global analysis of biological systems and discovery of new biological insights. Multi-omics experimental designs have been further extended with a longitudinal dimension to study dynamic relationships between molecules. However, methods that integrate longitudinal multi-omics data are still in their infancy. RESULTS: We introduce the R package timeOmics, a generic analytical framework for the integration of longitudinal multi-omics data. The framework includes pre-processing, modeling and clustering to identify molecular features strongly associated with time. We illustrate this framework in a case study to detect seasonal patterns of mRNA, metabolites, gut taxa and clinical variables in patients with diabetes mellitus from the integrative Human Microbiome Project. AVAILABILITYAND IMPLEMENTATION: timeOmics is available on Bioconductor and github.com/abodein/timeOmics. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Multi-Omics Data Integration Reveals Key Variables Contributing to Subgingival Microbiome Dysbiosis-Induced Inflammatory Response in a Hyperglycemic Microenvironment.

Subgingival microbiome dysbiosis promotes the development of periodontitis, an irreversible chronic inflammatory disease associated with metabolic diseases. However, studies regarding the effects of a hyperglycemic microenvironment on host-microbiome interactions and host inflammatory response during periodontitis are still scarce. Here, we investigated the impacts of a hyperglycemic microenvironment on the inflammatory response and transcriptome of a gingival coculture model stimulated with dysbiotic subgingival microbiomes. HGF-1 cells overlaid with U937 macrophage-like cells were stimulated with subgingival microbiomes collected from four healthy donors and four patients with periodontitis. Pro-inflammatory cytokines and matrix metalloproteinases were measured while the coculture RNA was submitted to a microarray analysis. Subgingival microbiomes were submitted to 16s rRNA gene sequencing. Data were analyzed using an advanced multi-omics bioinformatic data integration model. Our results show that the genes krt76, krt27, pnma5, mansc4, rab41, thoc6, tm6sf2, and znf506 as well as the pro-inflammatory cytokines IL-1ß, GM-CSF, FGF2, IL-10, the metalloproteinases MMP3 and MMP8, and bacteria from the ASV 105, ASV 211, ASV 299, Prevotella, Campylobacter and Fretibacterium genera are key intercorrelated variables contributing to periodontitis-induced inflammatory response in a hyperglycemic microenvironment. In conclusion, our multi-omics integration analysis unveiled the complex interrelationships involved in the regulation of periodontal inflammation in response to a hyperglycemic microenvironment.

Design and validation of a 63K genome-wide SNP-genotyping platform for caribou/reindeer (Rangifer tarandus).

BACKGROUND: Development of large single nucleotide polymorphism (SNP) arrays can make genomic data promptly available for conservation problematic. Medium and high-density panels can be designed with sufficient coverage to offer a genome-wide perspective and the generated genotypes can be used to assess different genetic metrics related to population structure, relatedness, or inbreeding. SNP genotyping could also permit sexing samples with unknown associated metadata as it is often the case when using non-invasive sampling methods favored for endangered species. Genome sequencing of wild species provides the necessary information to design such SNP arrays. We report here the development of a SNP-array for endangered Rangifer tarandus using a multi-platform sequencing approach from animals found in diverse populations representing the entire circumpolar distribution of the species. RESULTS: From a very large comprehensive catalog of SNPs detected over the entire sample set (N = 894), a total of 63,336 SNPs were selected. SNP selection accounted for SNPs evenly distributed across the entire genome (~ every 50Kb) with known minor alleles across populations world-wide. In addition, a subset of SNPs was selected to represent rare and local alleles found in Eastern Canada which could be used for ecotype and population assignments - information urgently needed for conservation planning. In addition, heterozygosity from SNPs located in the X-chromosome and genotyping call-rate of SNPs located into the SRY gene of the Y-chromosome yielded an accurate and robust sexing assessment. All SNPs were validated using a high-throughput SNP-genotyping chip. CONCLUSION: This design is now integrated into the first genome-wide commercially available genotyping platform for Rangifer tarandus. This platform would pave the way to future genomic investigation of populations for this endangered species, including estimation of genetic diversity parameters, population assignments, as well as animal sexing from genetic SNP data for non-invasive samples.

Mapping the Human Herpesvirus 6B transcriptome.

The "omics" revolution of recent years has simplified the study of RNA transcripts produced during viral infection and under specific defined conditions. In the quest to find new and differentially expressed transcripts during the course of human Herpesvirus 6B (HHV-6B) infection, we made use of large-scale RNA sequencing to analyze the HHV-6B transcriptome during productive infection of human Molt-3 T-cells. Analyses were performed at different time points following infection and specific inhibitors were used to classify the kinetic class of each open reading frame (ORF) reported in the annotated genome of HHV-6B Z29 strain. The initial search focussed on HHV-6B-specific reads matching new HHV-6B transcripts. Differential expression of new HHV-6B transcripts were observed in all samples analyzed. The presence of many of these new HHV-6B transcripts were confirmed by RT-PCR and Sanger sequencing. Many of these transcripts represented new splice variants of previously reported ORFs, including some transcripts that have yet to be defined. Overall, our work demonstrates the diversity and the complexity of the HHV-6B transcriptome.IMPORTANCERNA sequencing (RNA-seq) is an important tool for studying RNA transcripts, particularly during active viral infection. We made use of RNA-seq to study human Herpesvirus 6B (HHV-6B) infection. Using six different time points, we were able to identify the presence of differentially spliced genes at 6, 9, 12, 24, 48 and 72 hours post-infection. Determination of the RNA profiles in the presence of cycloheximide (CHX) or phosphonoacetic acid (PAA) also permitted identification of the kinetic class of each ORF described in the annotated GenBank file. We also identified new spliced transcripts for certain genes and evaluated their relative expression over time. These data and next-generation sequencing (NGS) of the viral DNA have led us to propose a new version of the HHV-6B Z29 GenBank annotated file, without changing ORF names in order to facilitate trace back and correlate our work with previous studies on HHV-6B.