Nutrient-dependent control of RNA polymerase II elongation rate regulates specific gene expression programs by alternative polyadenylation.

Transcription by RNA polymerase II (RNAPII) is a dynamic process with frequent variations in the elongation rate. However, the physiological relevance of variations in RNAPII elongation kinetics has remained unclear. Here we show in yeast that a RNAPII mutant that reduces the transcription elongation rate causes widespread changes in alternative polyadenylation (APA). We unveil two mechanisms by which APA affects gene expression in the slow mutant: 3' UTR shortening and gene derepression by premature transcription termination of upstream interfering noncoding RNAs. Strikingly, the genes affected by these mechanisms are enriched for functions involved in phosphate uptake and purine synthesis, processes essential for maintenance of the intracellular nucleotide pool. As nucleotide concentration regulates transcription elongation, our findings argue that RNAPII is a sensor of nucleotide availability and that genes important for nucleotide pool maintenance have adopted regulatory mechanisms responsive to reduced rates of transcription elongation.

Motif conservation, stability, and host gene expression are the main drivers of snoRNA expression across vertebrates.

Small nucleolar RNAs (snoRNAs) are structured noncoding RNAs present in multiple copies within eukaryotic genomes. snoRNAs guide chemical modifications on their target RNA and regulate processes like ribosome assembly and splicing. Most human snoRNAs are embedded within host gene introns, the remainder being independently expressed from intergenic regions. We recently characterized the abundance of snoRNAs and their host gene across several healthy human tissues and found that the level of most snoRNAs does not correlate with that of their host gene, with the observation that snoRNAs embedded within the same host gene often differ drastically in abundance. To better understand the determinants of snoRNA expression, we trained machine learning models to predict whether snoRNAs are expressed or not in human tissues based on more than 30 collected features related to snoRNAs and their genomic context. By interpreting the models' predictions, we find that snoRNAs rely on conserved motifs, a stable global structure and terminal stem, and a transcribed locus to be expressed. We observe that these features explain well the varying abundance of snoRNAs embedded within the same host gene. By predicting the expression status of snoRNAs across several vertebrates, we notice that only one-third of all annotated snoRNAs are expressed per genome, as in humans. Our results suggest that ancestral snoRNAs disseminated within vertebrate genomes, sometimes leading to the development of new functions and a probable gain in fitness and thereby conserving features favorable to the expression of these few snoRNAs, the large remainder often degenerating into pseudogenes.

Repression of pervasive antisense transcription is the primary role of fission yeast RNA polymerase II CTD serine 2 phosphorylation.

The RNA polymerase II carboxy-terminal domain (CTD) consists of conserved heptapeptide repeats that can be phosphorylated to influence distinct stages of the transcription cycle, including RNA processing. Although CTD-associated proteins have been identified, phospho-dependent CTD interactions have remained elusive. Proximity-dependent biotinylation (PDB) has recently emerged as an alternative approach to identify protein-protein associations in the native cellular environment. In this study, we present a PDB-based map of the fission yeast RNAPII CTD interactome in living cells and identify phospho-dependent CTD interactions by using a mutant in which Ser2 was replaced by alanine in every repeat of the fission yeast CTD. This approach revealed that CTD Ser2 phosphorylation is critical for the association between RNAPII and the histone methyltransferase Set2 during transcription elongation, but is not required for 3' end processing and transcription termination. Accordingly, loss of CTD Ser2 phosphorylation causes a global increase in antisense transcription, correlating with elevated histone acetylation in gene bodies. Our findings reveal that the fundamental role of CTD Ser2 phosphorylation is to establish a chromatin-based repressive state that prevents cryptic intragenic transcription initiation.

Pulse-SILAC and Interactomics Reveal Distinct DDB1-CUL4-Associated Factors, Cellular Functions, and Protein Substrates.

Cullin-RING finger ligases represent the largest family of ubiquitin ligases. They are responsible for the ubiquitination of ∼20% of cellular proteins degraded through the proteasome, by catalyzing the transfer of E2-loaded ubiquitin to a substrate. Seven cullins are described in vertebrates. Among them, cullin 4 (CUL4) associates with DNA damage-binding protein 1 (DDB1) to form the CUL4-DDB1 ubiquitin ligase complex, which is involved in protein ubiquitination and in the regulation of many cellular processes. Substrate recognition adaptors named DDB1/CUL4-associated factors (DCAFs) mediate the specificity of CUL4-DDB1 and have a short structural motif of approximately forty amino acids terminating in tryptophan (W)-aspartic acid (D) dipeptide, called the WD40 domain. Using different approaches (bioinformatics/structural analyses), independent studies suggested that at least sixty WD40-containing proteins could act as adaptors for the DDB1/CUL4 complex. To better define this association and classification, the interaction of each DCAFs with DDB1 was determined, and new partners and potential substrates were identified. Using BioID and affinity purification-mass spectrometry approaches, we demonstrated that seven WD40 proteins can be considered DCAFs with a high confidence level. Identifying protein interactions does not always lead to identifying protein substrates for E3-ubiquitin ligases, so we measured changes in protein stability or degradation by pulse-stable isotope labeling with amino acids in cell culture to identify changes in protein degradation, following the expression of each DCAF. In conclusion, these results provide new insights into the roles of DCAFs in regulating the activity of the DDB1-CUL4 complex, in protein targeting, and characterized the cellular processes involved.

A systematic approach to classify and characterize genomic islands driven by conjugative mobility using protein signatures.

Genomic islands (GIs) play a crucial role in the spread of antibiotic resistance, virulence factors and antiviral defense systems in a broad range of bacterial species. However, the characterization and classification of GIs are challenging due to their relatively small size and considerable genetic diversity. Predicting their intercellular mobility is of utmost importance in the context of the emerging crisis of multidrug resistance. Here, we propose a large-scale classification method to categorize GIs according to their mobility profile and, subsequently, analyze their gene cargo. We based our classification decision scheme on a collection of mobility protein motif definitions available in publicly accessible databases. Our results show that the size distribution of GI classes correlates with their respective structure and complexity. Self-transmissible GIs are usually the largest, except in Bacillota and Actinomycetota, accumulate antibiotic and phage resistance genes, and favour the use of a tyrosine recombinase to insert into a host's replicon. Non-mobilizable GIs tend to use a DDE transposase instead. Finally, although tRNA genes are more frequently targeted as insertion sites by GIs encoding a tyrosine recombinase, most GIs insert in a protein-encoding gene. This study is a stepping stone toward a better characterization of mobile GIs in bacterial genomes and their mechanism of mobility.

MetaboAnalyst 5.0: narrowing the gap between raw spectra and functional insights.

Since its first release over a decade ago, the MetaboAnalyst web-based platform has become widely used for comprehensive metabolomics data analysis and interpretation. Here we introduce MetaboAnalyst version 5.0, aiming to narrow the gap from raw data to functional insights for global metabolomics based on high-resolution mass spectrometry (HRMS). Three modules have been developed to help achieve this goal, including: (i) a LC-MS Spectra Processing module which offers an easy-to-use pipeline that can perform automated parameter optimization and resumable analysis to significantly lower the barriers to LC-MS1 spectra processing; (ii) a Functional Analysis module which expands the previous MS Peaks to Pathways module to allow users to intuitively select any peak groups of interest and evaluate their enrichment of potential functions as defined by metabolic pathways and metabolite sets; (iii) a Functional Meta-Analysis module to combine multiple global metabolomics datasets obtained under complementary conditions or from similar studies to arrive at comprehensive functional insights. There are many other new functions including weighted joint-pathway analysis, data-driven network analysis, batch effect correction, merging technical replicates, improved compound name matching, etc. The web interface, graphics and underlying codebase have also been refactored to improve performance and user experience. At the end of an analysis session, users can now easily switch to other compatible modules for a more streamlined data analysis. MetaboAnalyst 5.0 is freely available at https://www.metaboanalyst.ca.

Genome-scale metabolic modeling reveals key features of a minimal gene set.

Mesoplasma florum, a fast-growing near-minimal organism, is a compelling model to explore rational genome designs. Using sequence and structural homology, the set of metabolic functions its genome encodes was identified, allowing the reconstruction of a metabolic network representing ˜ 30% of its protein-coding genes. Growth medium simplification enabled substrate uptake and product secretion rate quantification which, along with experimental biomass composition, were integrated as species-specific constraints to produce the functional iJL208 genome-scale model (GEM) of metabolism. Genome-wide expression and essentiality datasets as well as growth data on various carbohydrates were used to validate and refine iJL208. Discrepancies between model predictions and observations were mechanistically explained using protein structures and network analysis. iJL208 was also used to propose an in silico reduced genome. Comparing this prediction to the minimal cell JCVI-syn3.0 and its parent JCVI-syn1.0 revealed key features of a minimal gene set. iJL208 is a stepping-stone toward model-driven whole-genome engineering.

Human plasma pregnancy-associated miRNAs and their temporal variation within the first trimester of pregnancy.

BACKGROUND: During pregnancy, maternal metabolism undergoes substantial changes to support the developing fetus. Such changes are finely regulated by different mechanisms carried out by effectors such as microRNAs (miRNAs). These small non-coding RNAs regulate numerous biological functions, mostly through post-transcriptional repression of gene expression. miRNAs are also secreted in circulation by numerous organs, such as the placenta. However, the complete plasmatic microtranscriptome of pregnant women has still not been fully described, although some miRNA clusters from the chromosome 14 (C14MC) and the chromosome 19 (C19MC and miR-371-3 cluster) have been proposed as being specific to pregnancy. Our aims were thus to describe the plasma microtranscriptome during the first trimester of pregnancy, by assessing the differences with non-pregnant women, and how it varies between the 4th and the 16th week of pregnancy. METHODS: Plasmatic miRNAs from 436 pregnant (gestational week 4 to 16) and 15 non-pregnant women were quantified using Illumina HiSeq next-generation sequencing platform. Differentially abundant miRNAs were identified using DESeq2 package (FDR q-value ≤ 0.05) and their targeted biological pathways were assessed with DIANA-miRpath. RESULTS: A total of 2101 miRNAs were detected, of which 191 were differentially abundant (fold change < 0.05 or > 2, FDR q-value ≤ 0.05) between pregnant and non-pregnant women. Of these, 100 miRNAs were less and 91 miRNAs were more abundant in pregnant women. Additionally, the abundance of 57 miRNAs varied according to gestational age at first trimester, of which 47 were positively and 10 were negatively associated with advancing gestational age. miRNAs from the C19MC were positively associated with both pregnancy and gestational age variation during the first trimester. Biological pathway analysis revealed that these 191 (pregnancy-specific) and 57 (gestational age markers) miRNAs targeted genes involved in fatty acid metabolism, ECM-receptor interaction and TGF-beta signaling pathways. CONCLUSION: We have identified circulating miRNAs specific to pregnancy and/or that varied with gestational age in first trimester. These miRNAs target biological pathways involved in lipid metabolism as well as placenta and embryo development, suggesting a contribution to the maternal metabolic adaptation to pregnancy and fetal growth.

Investigating the role of RNA structures in transcriptional pausing using in vitro assays and in silico analyses.

Transcriptional pausing occurs across the bacterial genome but the importance of this mechanism is still poorly understood. Only few pauses were observed during the previous decades, leaving an important gap in understanding transcription mechanisms. Using the well-known Escherichia coli hisL and trpL pause sites as models, we describe here the relation of pause sites with upstream RNA structures suspected to stabilize pausing. We find that the transcription factor NusA influences the pause half-life at leuL, pheL and thrL pause sites. Using a mutagenesis approach, we observe that transcriptional pausing is affected in all tested pause sites, suggesting that the upstream RNA sequence is important for transcriptional pausing. Compensatory mutations assessing the presence of RNA hairpins did not yield clear conclusions, indicating that complex RNA structures or transcriptional features may be playing a role in pausing. Moreover, using a bioinformatic approach, we explored the relation between a DNA consensus sequence important for pausing and putative hairpins among thousands of pause sites in E. coli. We identified 2125 sites presenting hairpin-dependent transcriptional pausing without consensus sequence, suggesting that this mechanism is widespread across E. coli. This study paves the way to understand the role of RNA structures in transcriptional pausing.

Integrative characterization of the near-minimal bacterium Mesoplasma florum.

The near-minimal bacterium Mesoplasma florum is an interesting model for synthetic genomics and systems biology due to its small genome (~ 800 kb), fast growth rate, and lack of pathogenic potential. However, fundamental aspects of its biology remain largely unexplored. Here, we report a broad yet remarkably detailed characterization of M. florum by combining a wide variety of experimental approaches. We investigated several physical and physiological parameters of this bacterium, including cell size, growth kinetics, and biomass composition of the cell. We also performed the first genome-wide analysis of its transcriptome and proteome, notably revealing a conserved promoter motif, the organization of transcription units, and the transcription and protein expression levels of all protein-coding sequences. We converted gene transcription and expression levels into absolute molecular abundances using biomass quantification results, generating an unprecedented view of the M. florum cellular composition and functions. These characterization efforts provide a strong experimental foundation for the development of a genome-scale model for M. florum and will guide future genome engineering endeavors in this simple organism.

Inactivation of the riboswitch-controlled GMP synthase GuaA in Clostridioides difficile is associated with severe growth defects and poor infectivity in a mouse model of infection.

Clostridioides difficile is the main cause of nosocomial antibiotic-associated diarrhoea. There is a need for new antimicrobials to tackle this pathogen. Guanine riboswitches have been proposed as promising new antimicrobial targets, but experimental evidence of their importance in C. difficile is missing. The genome of C. difficile encodes four distinct guanine riboswitches, each controlling a single gene involved in purine metabolism and transport. One of them controls the expression of guaA, encoding a guanosine monophosphate (GMP) synthase. Here, using in-line probing and GusA reporter assays, we show that these riboswitches are functional in C. difficile and cause premature transcription termination upon binding of guanine. All riboswitches exhibit a high affinity for guanine characterized by Kd values in the low nanomolar range. Xanthine and guanosine also bind the guanine riboswitches, although with less affinity. Inactivating the GMP synthase (guaA) in C. difficile strain 630 led to cell death in minimal growth conditions, but not in rich medium. Importantly, the capacity of a guaA mutant to colonize the mouse gut was significantly reduced. Together, these results demonstrate the importance of de novo GMP biosynthesis in C. difficile during infection, suggesting that targeting guanine riboswitches with analogues could be a viable therapeutic strategy.

The epiGenomic Efficient Correlator (epiGeEC) tool allows fast comparison of user datasets with thousands of public epigenomic datasets.

SUMMARY: In recent years, major initiatives such as the International Human Epigenome Consortium have generated thousands of high-quality genome-wide datasets for a large variety of assays and cell types. This data can be used as a reference to assess whether the signal from a user-provided dataset corresponds to its expected experiment, as well as to help reveal unexpected biological associations. We have developed the epiGenomic Efficient Correlator (epiGeEC) tool to enable genome-wide comparisons of very large numbers of datasets. A public Galaxy implementation of epiGeEC allows comparison of user datasets with thousands of public datasets in a few minutes. AVAILABILITY AND IMPLEMENTATION: The source code is available at https://bitbucket.org/labjacquespe/epigeec and the Galaxy implementation at http://epigeec.genap.ca. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data.

Genome-scale metabolic models (GEMs) are mathematically structured knowledge bases of metabolism that provide phenotypic predictions from genomic information. GEM-guided predictions of growth phenotypes rely on the accurate definition of a biomass objective function (BOF) that is designed to include key cellular biomass components such as the major macromolecules (DNA, RNA, proteins), lipids, coenzymes, inorganic ions and species-specific components. Despite its importance, no standardized computational platform is currently available to generate species-specific biomass objective functions in a data-driven, unbiased fashion. To fill this gap in the metabolic modeling software ecosystem, we implemented BOFdat, a Python package for the definition of a Biomass Objective Function from experimental data. BOFdat has a modular implementation that divides the BOF definition process into three independent modules defined here as steps: 1) the coefficients for major macromolecules are calculated, 2) coenzymes and inorganic ions are identified and their stoichiometric coefficients estimated, 3) the remaining species-specific metabolic biomass precursors are algorithmically extracted in an unbiased way from experimental data. We used BOFdat to reconstruct the BOF of the Escherichia coli model iML1515, a gold standard in the field. The BOF generated by BOFdat resulted in the most concordant biomass composition, growth rate, and gene essentiality prediction accuracy when compared to other methods. Installation instructions for BOFdat are available in the documentation and the source code is available on GitHub (https://github.com/jclachance/BOFdat).

A universal RNA polymerase II CTD cycle is orchestrated by complex interplays between kinase, phosphatase, and isomerase enzymes along genes.

Transcription by RNA polymerase II (RNAPII) is coupled to mRNA processing and chromatin modifications via the C-terminal domain (CTD) of its largest subunit, consisting of multiple repeats of the heptapeptide YSPTSPS. Pioneering studies showed that CTD serines are differentially phosphorylated along genes in a prescribed pattern during the transcription cycle. Genome-wide analyses challenged this idea, suggesting that this cycle is not uniform among different genes. Moreover, the respective role of enzymes responsible for CTD modifications remains controversial. Here, we systematically profiled the location of the RNAPII phosphoisoforms in wild-type cells and mutants for most CTD modifying enzymes. Together with results of in vitro assays, these data reveal a complex interplay between the modifying enzymes, and provide evidence that the CTD cycle is uniform across genes. We also identify Ssu72 as the Ser7 phosphatase and show that proline isomerization is a key regulator of CTD dephosphorylation at the end of genes.

The DNA double-strand "breakome" of mouse spermatids.

De novo germline mutations arise preferentially in male owing to fundamental differences between spermatogenesis and oogenesis. Post-meiotic chromatin remodeling in spermatids results in the elimination of most of the nucleosomal supercoiling and is characterized by transient DNA fragmentation. Using three alternative methods, DNA from sorted populations of mouse spermatids was used to confirm that double-strand breaks (DSB) are created in elongating spermatids and repaired at later steps. Specific capture of DSB was used for whole-genome mapping of DSB hotspots (breakome) for each population of differentiating spermatids. Hotspots are observed preferentially within introns and repeated sequences hence are more prevalent in the Y chromosome. When hotspots arise within genes, those involved in neurodevelopmental pathways become preferentially targeted reaching a high level of significance. Given the non-templated DNA repair in haploid spermatids, transient DSBs formation may, therefore, represent an important component of the male mutation bias and the etiology of neurological disorders, adding to the genetic variation provided by meiosis.

Global inhibition of transcription causes an increase in histone H2A.Z incorporation within gene bodies.

H2A.Z histone variant is an important regulator of gene transcription, which is enriched at regulatory regions but is also found within gene bodies. Recent evidence suggests that active recruitment of H2A.Z within gene bodies is required to induce gene repression. In contrast to this view, we show that global inhibition of transcription results in H2A.Z accumulation at gene transcription start sites, as well as within gene bodies. Our results indicate that accumulation of H2A.Z within repressed genes can also be a consequence of the repression of gene transcription rather than an active mechanism required to establish the repression.

Tomatidine Is a Lead Antibiotic Molecule That Targets Staphylococcus aureus ATP Synthase Subunit C.

Methicillin-resistant Staphylococcus aureus (MRSA) is a leading cause of deadly hospital-acquired infections. The discovery of anti-Staphylococcus antibiotics and new classes of drugs not susceptible to the mechanisms of resistance shared among bacteria is imperative. We recently showed that tomatidine (TO), a steroidal alkaloid from solanaceous plants, possesses potent antibacterial activity against S. aureus small-colony variants (SCVs), the notoriously persistent form of this bacterium that has been associated with recurrence of infections. Here, using genomic analysis of in vitro-generated TO-resistant S. aureus strains to identify mutations in genes involved in resistance, we identified the bacterial ATP synthase as the cellular target. Sequence alignments were performed to highlight the modified sequences, and the structural consequences of the mutations were evaluated in structural models. Overexpression of the atpE gene in S. aureus SCVs or introducing the mutation found in the atpE gene of one of the high-level TO-resistant S. aureus mutants into the Bacillus subtilis atpE gene provided resistance to TO and further validated the identity of the cellular target. FC04-100, a TO derivative which also possesses activity against non-SCV strains, prevents high-level resistance development in prototypic strains and limits the level of resistance observed in SCVs. An ATP synthesis assay allowed the observation of a correlation between antibiotic potency and ATP synthase inhibition. The selectivity index (inhibition of ATP production by mitochondria versus that of bacterial ATP synthase) is estimated to be >105-fold for FC04-100.

Clinical validity of phenotype-driven analysis software PhenoVar as a diagnostic aid for clinical geneticists in the interpretation of whole-exome sequencing data.

PURPOSE: We sought to determine the diagnostic yield of whole-exome sequencing (WES) combined with phenotype-driven analysis of variants in patients with suspected genetic disorders. METHODS: WES was performed on a cohort of 51 patients presenting dysmorphisms with or without neurodevelopmental disorders of undetermined etiology. For each patient, a clinical geneticist reviewed the phenotypes and used the phenotype-driven analysis software PhenoVar (http://phenovar.med.usherbrooke.ca/) to analyze WES variants. The prioritized list of potential diagnoses returned was reviewed by the clinical geneticist, who selected candidate variants to be confirmed by segregation analysis. Conventional analysis of the individual variants was performed in parallel. The resulting candidate variants were subsequently reviewed by the same geneticist, to identify any additional potential diagnoses. RESULTS: A molecular diagnosis was identified in 35% of the patients using the conventional analysis, and 17 of these 18 diagnoses were independently identified using PhenoVar. The only diagnosis initially missed by PhenoVar was rescued when the optional "minimal phenotypic cutoff" filter was omitted. PhenoVar reduced by half the number of potential diagnoses per patient compared with the conventional analysis. CONCLUSION: Phenotype-driven software prioritizes WES variants, provides an efficient diagnostic aid to clinical geneticists and laboratories, and should be incorporated in clinical practice.

Systems consequences of amplicon formation in human breast cancer.

Chromosomal structural variations play an important role in determining the transcriptional landscape of human breast cancers. To assess the nature of these structural variations, we analyzed eight breast tumor samples with a focus on regions of gene amplification using mate-pair sequencing of long-insert genomic DNA with matched transcriptome profiling. We found that tandem duplications appear to be early events in tumor evolution, especially in the genesis of amplicons. In a detailed reconstruction of events on chromosome 17, we found large unpaired inversions and deletions connect a tandemly duplicated ERBB2 with neighboring 17q21.3 amplicons while simultaneously deleting the intervening BRCA1 tumor suppressor locus. This series of events appeared to be unusually common when examined in larger genomic data sets of breast cancers albeit using approaches with lesser resolution. Using siRNAs in breast cancer cell lines, we showed that the 17q21.3 amplicon harbored a significant number of weak oncogenes that appeared consistently coamplified in primary tumors. Down-regulation of BRCA1 expression augmented the cell proliferation in ERBB2-transfected human normal mammary epithelial cells. Coamplification of other functionally tested oncogenic elements in other breast tumors examined, such as RIPK2 and MYC on chromosome 8, also parallel these findings. Our analyses suggest that structural variations efficiently orchestrate the gain and loss of cancer gene cassettes that engage many oncogenic pathways simultaneously and that such oncogenic cassettes are favored during the evolution of a cancer.

Translatome analysis of an NB-LRR immune response identifies important contributors to plant immunity in Arabidopsis.

An important branch of plant immunity involves the recognition of pathogens by nucleotide-binding, leucine-rich repeat (NB-LRR) proteins. However, signaling events downstream of NB-LRR activation are poorly understood. We have analysed the Arabidopsis translatome using ribosome affinity purification and RNA sequencing. Our results show that the translational status of hundreds of transcripts is differentially affected upon activation of the NB-LRR protein RPM1, showing an overall pattern of a switch away from growth-related activities to defense. Among these is the central translational regulator and growth promoter, Target of Rapamycin (TOR) kinase. Suppression of TOR expression leads to increased resistance to pathogens while overexpression of TOR results in increased susceptibility, indicating an important role for translational control in the switch from growth to defense. Furthermore, we show that several additional genes whose mRNAs are translationally regulated, including BIG, CCT2, and CIPK5, are required for both NB-LRR-mediated and basal plant innate immunity, identifying novel actors in plant defense.