Biology subjects

Seif, Y.

Publications and source records attributed to Seif, Y..

13 recordsLinked to original sources

bioRxiv2022

Phenotypic response of yeast metabolic network to availability of proteinogenic aminoacids

Genome-scale metabolism can best be described as a highly interconnected network of biochemical reactions and metabolites. The flow of metabolites, i.e., flux, throughout these networks can be predicted and analyzed using approaches such as flux balance analysis (FBA). By knowing the network topology and employing only a few simple assumptions, FBA can efficiently predict metabolic functions at the genome scale as well as microbial phenotypes. The network topology is represented in the form of genome-scale metabolic models (GEMs), which provide a direct mapping between network structure and function via the enzyme-coding genes and corresponding metabolic capacity. Recently, the role of protein limitations in shaping metabolic phenotypes have been extensively studied following the reconstruction of enzyme-constrained GEMs. This framework has been shown to significantly improve the accuracy of predicting microbial phenotypes, and it has demonstrated that a global limitation in protein availability can prompt the ubiquitous metabolic strategy of overflow metabolism. Being one of the most abundant and differentially expressed proteome sectors, metabolic proteins constitute a major cellular demand on proteinogenic amino acids. However, little is known about the impact and sensitivity of amino acid availability with regards to genome-scale metabolism. Here, we explore these aspects by extending on the enzyme-constrained GEM framework by also accounting for the usage of amino acids in expressing the metabolic proteome. Including amino acids in an enzyme-constrained GEM of Saccharomyces cerevisiae, we demonstrate that the expanded model is capable of accurately reproducing experimental amino acid levels. We further show that the metabolic proteome exerts variable demands on amino acid supplies in a condition-dependent manner, suggesting that S. cerevisiae must have evolved to efficiently fine-tune the synthesis of amino acids for expressing its metabolic proteins in response to changes in the external environment. Finally, our results demonstrate how the metabolic network of S. cerevisiae is robust towards perturbations of individual amino acids, while simultaneously being highly sensitive when the relative amino acid availability is set to mimic a priori distributions of both yeast and non-yeast origins.

systems biology↗

bioRxiv2022

Pan-genomic analysis of transcriptional modules across Salmonella Typhimurium reveals the regulatory landscape of different strains

Salmonella enterica Typhimurium is a serious pathogen that is involved in human nontyphoidal infections. Tackling Typhimurium infections is difficult due to the species dynamic adaptation to its environment, which is dictated by a complex transcriptional regulatory network (TRN). While traditional biomolecular methods provide characterizations of specific regulators, it is laborious to construct the global TRN structure from this bottom-up approach. Here, we used a machine learning technique to understand the transcriptional signatures of S. enterica Typhimurium from the top down, as a whole and in individual strains. Furthermore, we conducted cross-strain comparison of 6 strains in serovar Typhimurium to investigate similarities and differences in their TRNs with pan-genomic analysis. By decomposing all the publicly available RNA-Seq data of Typhimurium with independent component analysis (ICA), we obtained over 400 independently modulated sets of genes, called iModulons. Through analysis of these iModulons, we 1) discover three transport iModulons linked to antibiotic resistance, 2) describe concerted responses to cationic antimicrobial peptides (CAMPs), 3) uncover evidence towards new regulons, and 4) identify two iModulons linked to bile responses in strain ST4/74. We extend this analysis across the pan-genome to show that strain-specific iModulons 5) reveal different genetic signatures in pathogenicity islands that explain phenotypes and 6) capture the activity of different phages in the studied strains. Using all high-quality publicly-available RNA-Seq data to date, we present a comprehensive, data-driven Typhimurium TRN. It is conceivable that with more high-quality datasets from more strains, the approach used in this study will continue to guide our investigation in understanding the pan-transcriptome of Typhimurium. Interactive dashboards for all gene modules in this project are available at https://imodulondb.org/ under the "Salmonella Typhimurium" page to enable browsing for interested researchers.

systems biology↗

bioRxiv2021

Mining all publicly available expression data to compute dynamic microbial transcriptional regulatory networks

We are firmly in the era of biological big data. Millions of omics datasets are publicly accessible and can be employed to support scientific research or build a holistic view of an organism. Here, we introduce a workflow that converts all public gene expression data for a microbe into a dynamic representation of the organisms transcriptional regulatory network. This five-step process walks researchers through the mining, processing, curation, analysis, and characterization of all available expression data, using Bacillus subtilis as an example. The resulting reconstruction of the B. subtilis regulatory network can be leveraged to predict new regulons and analyze datasets in the context of all published data. The results are hosted at https://imodulondb.org/, and additional analyses can be performed using the PyModulon Python package. As the number of publicly available datasets increases, this pipeline will be applicable to a wide range of microbial pathogens and cell factories.

bioinformatics↗

bioRxiv2021

Elucidating the CodY regulon in Staphylococcus aureus USA300 substrains

CodY is a conserved broad acting transcription factor that regulates the expression of genes related to amino acid metabolism and virulence in methicillin-resistant Staphylococcus aureus (MRSA). CodY target genes have been studied by using in vitro DNA affinity purification and deep sequencing (IDAP-Seq). Here we performed the first in vivo determination of CodY target genes using a novel CodY monoclonal antibody in established ChIP-exo protocols. Our results showed, 1) the same 135 CodY promoter binding sites regulating 165 target genes identified in two closely related virulent S. aureus USA300 TCH1516 and LAC strains; 2) The differential binding intensity for the same target genes under the same conditions was due to sequence differences in the same CodY binding site in the two strains; 3) Based on transcriptomic data, a CodY regulon comprising 72 target genes that are differentially regulated relative to a CodY deletion strain, representing genes that are mainly involved in amino acid transport and metabolism, inorganic ion transport and metabolism, transcription and translation, and virulence; and 4) CodY systematically regulated central metabolic flux to generate branched-chain amino acids (BCAAs) by mapping the CodY regulon onto a genome-scale metabolic model of S. aureus. Our study performed the first system-level analysis of CodY in two closely related USA300 TCH1516 and LAC strains giving new insights into the similarities and differences of CodY regulatory roles between the closely related strains. ImportanceWith the increasing availability of whole genome sequences for many strains within the same pathogenic species, a comparative analysis of key regulators is needed to understand how the different strains uniquely coordinate metabolism and expression of virulence. To successfully infect the human host, Staphylococcus aureus USA300 relies on the transcription factor CodY to reorganize metabolism and express virulence factors. While CodY is a known key transcription factor, its target genes are not characterized on a genome-wide basis. We performed a comparative analysis to describe the transcriptional regulation of CodY between two dominant USA300 strains. This study motivates the characterization of common pathogenic strains and an evaluation of the possibility of developing specialized treatments for major strains circulating in the population.

microbiology↗

bioRxiv2020

Elucidation of regulatory modes for five two-component systems in Escherichia coli reveals novel relationships

Escherichia coli uses two-component systems (TCSs) to respond to environmental signals. TCSs affect gene expression and are parts of E. coli’s global transcriptional regulatory network (TRN). Here, we identified the regulons of five TCSs in E. coli MG1655: BaeSR and CpxAR, which were stimulated by ethanol stress; KdpDE and PhoRB, induced by limiting potassium and phosphate, respectively; and ZraSR, stimulated by zinc. We analyzed RNA-seq data using independent component analysis (ICA). ChIP-exo data was used to validate condition-specific target gene binding sites. Based on this data we (1) identify the target genes for each TCS; (2) show how the target genes are transcribed in response to stimulus; and (3) reveal novel relationships between TCSs, which indicate non-cognate inducers for various response regulators, such as BaeR to iron starvation, CpxR to phosphate limitation, and PhoB and ZraR to cell envelope stress. Our understanding of the TRN in E. coli is thus notably expanded.Importance E. coli is a common commensal microbe found in human gut microenvironment; however, some strains cause diseases like diarrhea, urinary tract infections and meningitis. E. coli’s two-component system (TCS) modulates target gene expression, specially related to virulence, pathogenesis and anti-microbial peptides, in response to environmental stimuli. Thus, it is of utmost importance to understand the transcriptional regulation of the TCSs to infer its environmental adaptation and disease pathogenicity. Utilizing a combinatorial approach integrating RNAseq, independent component analysis, ChIP-exo and data mining, we show that TCSs have five different modes of transcriptional regulation. Our data further highlights non-cognate inducers of TCSs emphasizing cross-regulatory nature of TCSs in E. coli and suggests that TCSs may have a role beyond their cognate functionalities. In summary, these results when further incorporated with genome scale metabolic models can lead to understanding of metabolic capabilities of bacteria and correctly predict complex phenotype under diverse conditions.View Full Text

systems biology↗

bioRxiv2020

Environmental conditions dictate differential evolution of vancomycin resistance in Staphylococcus aureus

While microbiological resistance to vancomycin in Staphylococcus aureus is rare, clinical vancomycin treatment failures are common, and methicillin-resistant S. aureus (MRSA) strains isolated from patients after prolonged vancomycin treatment failure remain susceptible. Adaptive laboratory evolution was utilized to uncover mutational mechanisms associated with MRSA vancomycin resistance in a bacteriological medium used in clinical susceptibility testing and a physiological medium. Sequencing of resistant clones revealed shared and media-specific mutational outcomes, with an overlap in cell wall regulons (walKRyycHI, vraSRT). Evolved strains displayed similar genetic and phenotypic traits to resistant clinical isolates. Importantly, resistant phenotypes that developed in physiological media did not translate into resistance in bacteriological media. Further, a bacteriological media-specific mechanism for vancomycin resistance enabled by a mutated mprF was confirmed. This study bridges the gap of understanding between clinical and microbiological vancomycin resistance in S. aureus and expands the number of allelic variants that result in vancomycin resistance phenotypes.

microbiology↗

bioRxiv2020

Reconstruction of Fur pan-regulon uncovers the complexity and diversity of transcriptional regulation in E. coli

Regulons for many transcription factors have been elucidated in model strains leading to an understanding of their role in producing physiological states. Comparative analysis of a regulon and its target genes between different strains of the same species is lacking. Ferric uptake regulator (Fur), involved in iron homeostasis, is one of the most conserved TFs, and is present in a wide range of bacteria. Using ChIP-exo experiments, we performed a comprehensive study of Fur binding sites in nine Escherichia coli strains with different lifestyles. 79 of the 431 target genes (18%) found belong to Fur core regulon, comprising genes involved in ion transport and metabolism, energy production and conversion, and amino acid metabolism and transport. 179 of the target genes (42%) comprise the accessory regulon, most of which were related to cell wall structure and biogenesis, and virulence factor pathways. The remaining target genes (173 or 40%) were in the unique regulon, with gene functions that were largely unknown. Furthermore, deletion of the fur gene led to distinct phenotypes in growth, motility, antibiotic resistance, and the change of siderophore production. These results provide a more complete understanding of how Fur regulates a set of target genes with surprising variation in closely related bacteria.

systems biology↗

bioRxiv2020

Characterizing the response of Acinetobacter baumannii ATCC 17978 to azithromycin in multiple in vitro growth conditions

Multi-drug resistant (MDR) Acinetobacter baumannii is one of the most concerning pathogens in hospital infections. A. baumannii is categorized as an "Urgent Threat" by the U.S. Centers for Disease Control and the highest priority pathogen by the World Health Organization due to its propensity for broad antibiotic resistance and its associated high mortality rates. New treatment options are urgently needed for MDR A. baumannii infections. Our prior studies have demonstrated an unappreciated utility of the macrolide azithromycin (AZM) against MDR A. baumannii in tissue-culture medium. This finding is all the more surprising since AZM has no appreciable activity against A. baumannii in standard bacteriological media. The basis for this media-dependent activity of AZM against A. baumannii is not fully defined. In this study, we utilize a variety of techniques (growth dynamics, bacterial cytological profiling, RNA sequencing, and LC/MS) to profile the response of MDR A. baumannii to AZM in both standard bacteriological and more physiological relevant mammalian tissue-culture medium. [Table 1]

microbiology↗

bioRxiv2020

Identifying the effect of vancomycin on HA-MRSA strains using bacteriological and physiological media

Healthcare-associated methicillin-resistant Staphylococcus aureus (HA-MRSA) USA100 strains are of major concern due to their evolving antibiotic resistant. They are resistant to a broad class of antibiotics like macrolides, aminoglycosides, fluoroquinolones, and many more. The selection of appropriate antibiotic susceptibility examination media is very important. Thus, we use bacteriological (CA-MHB) as well as physiological (R10LB) media to determine the effect of vancomycin on USA100 strains. The study includes the profiling behaviour of HA-MRSA USA100 D592 and D712 strains in the presence of vancomycin through various high-throughput assays. The US100 D592 and D712 strains were characterized at sub-inhibitory concentrations through growth curves, RNA sequencing, bacterial cytological profiling, and exo-metabolomics high throughput experiments. The study reveals the vancomycin resistance behavior of USA100 strains in dual media conditions using wide-ranging experiments.

microbiology↗

bioRxiv2020

Profiling the effect of nafcillin on HA-MRSA D592 using bacteriological and physiological media

Staphylococcus aureus is a leading human pathogen associated with both hospital-acquired and community-acquired infections. The bacterium has steadily gained resistance to {beta}-lactams and other important first-line antibiotics culminating in its categorization as an urgent threat by the U.S. Centers for Disease Control and Prevention. Observations of a varying response to antimicrobial exposure as a function of media type has revealed that clinical susceptibility testing performed in standard bacteriological media might not adequately represent pharmacological responses in the patient. Such observations have encouraged research designed to identify media types that more closely mimic the in vivo environment. In this study, we examine the response of a hospital-acquired USA100 lineage methicillin-resistant, vancomycin-intermediate S. aureus (MRSA/VISA) strain (D592) to nafcillin in a bacteriological compared to a more physiological tissue culture-based medium. We performed multi-dimensional analysis including growth and bacterial cytological profiling, RNA sequencing, and exo-metabolomics measurements (both HPLC and LC/MS) to shed light on the media-dependent activity of the commonly prescribed {beta}-lactam antibiotic nafcillin. O_TBL View this table: org.highwire.dtl.DTLVardef@85b95borg.highwire.dtl.DTLVardef@14c1504org.highwire.dtl.DTLVardef@1f7e976org.highwire.dtl.DTLVardef@100598dorg.highwire.dtl.DTLVardef@1f770e9_HPS_FORMAT_FIGEXP M_TBL C_TBL

microbiology↗

bioRxiv2020

Pangenome analytics reveal two-component systems as conserved targets in ESKAPEE pathogens

Bacteria sense and respond to environmental stimuli through two-component systems (TCSs), that are composed of histidine kinase sensing and response regulator elements. TCSs are ubiquitous and participate in numerous cellular functions. TCSs across the ESKAPEE pathogens, representing the leading causes of nosocomial infections, were characterized using pangenome analytics, including annotation, mapping, pangenomic status, gene orientation, sequence variation, and structure. Our findings fall into two categories. 1) phylogenetic distribution of TCSs: (i) the number and types of TCSs varies between species of the ESKAPEE pathogens; (ii) TCSs are group-specific, i.e., Gram-positive and Gram-negative, except for KdpDE; (iii) most TCSs are conserved among genomes of an ESKAPEE, except in Pseudomonas aeruginosa. 2) sequence variation: (i) at the operon level, the genomic architecture of a TCS operon stratifies into a few discrete classes; and (ii) at the gene sequence level, histidine kinases, responsible for signal sensing, show sequence and structural variability as compared to response regulators that show a high degree of conservation. Taken together, this first comprehensive pangenomic assessment of TCSs reveals a range of strategies deployed by the ESKAPEE pathogens to manifest pathogenicity and antibiotic resistance. It further suggests that the conserved features of TCSs makes them an attractive group of potential targets with which to address antibiotic resistance.

microbiology↗

bioRxiv2020

Revealing 29 sets of independently modulated genes in Staphylococcus aureus, their regulators and role in key physiological responses

The ability of Staphylococcus aureus to infect many different tissue sites is enabled, in part, by its Transcriptional Regulatory Network (TRN) that coordinates its gene expression to respond to different environments. We elucidated the organization and activity of this TRN by applying Independent Component Analysis (ICA) to a compendium of 108 RNAseq expression profiles from two S. aureus clinical strains (TCH1516 and LAC). ICA decomposed the S. aureus transcriptome into 29 independently modulated sets of genes (i-modulons) that revealed (1) high confidence associations between 21 i-modulons and known regulators; (2) an association between an i-modulon and {sigma}S, whose regulatory role was previously undefined; (3) the regulatory organization of 65 virulence factors in the form of three i-modulons associated with AgrR, SaeR and Vim-3, (4) the roles of three key transcription factors (codY, Fur and ccpA) in coordinating the metabolic and regulatory networks; and (5) a low dimensional representation, involving the function of few transcription factors, of changes in gene expression between two laboratory media (RPMI, CAMHB) and two physiological media (blood and serum). This representation of the TRN covers 842 genes representing 76% of the variance in gene expression that provides a quantitative reconstruction of transcriptional modules in S. aureus, and a platform enabling its full elucidation. Significance StatementStaphylococcus aureus infections impose an immense burden on the healthcare system. To establish a successful infection in a hostile host environment, S. aureus must coordinate its gene expression to respond to a wide array of challenges. This balancing act is largely orchestrated by the Transcriptional Regulatory Network (TRN). Here, we present a model of 29 independently modulated sets of genes that form the basis for a segment of the TRN in clinical USA300 strains of S. aureus. Using this model, we demonstrate the concerted role of various cellular systems (e.g. metabolism, virulence and stress response) underlying key physiological responses, including response during blood infection.

microbiology↗

bioRxiv2018

BOFdat: generating biomass objective function stoichiometric coefficients from experimental data

Genome-scale models (GEMs) rely on a biomass objective function (BOF) to predict phenotype from genotype. Here we present BOFdat, a Python package that offers functions to generate biomass objective function stoichiometric coefficients (BOFsc) from macromolecular cell composition and relative abundances of macromolecules obtained from omic datasets. Growth-associated and non-growth associated maintenance (GAM and NGAM) costs can also be calculated by BOFdat.\n\nBOFdat is freely available on the Python Package Index (pip install BOFdat). The source code and an example usage (Jupyter Notebook and example files) are available on GitHub (https://github.com/jclachance/BOFdat). The documentation and API are available through ReadTheDocs (https://bofdat.readthedocs.io).\n\nContactjean-christophe.lachance@usherbrooke.ca, zaking@eng.ucsd.edu, pierre-etienne.jacques@usherbrooke.ca

systems biology↗