scholarly journals PangenomeNet: a pan-genome-based network reveals functional modules on antimicrobial resistome for Escherichia coli strains

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Hsuan-Lin Her ◽  
Po-Ting Lin ◽  
Yu-Wei Wu
Keyword(s):  
Escherichia Coli ◽  
Resistance Genes ◽  
Biological Networks ◽  
Functional Organization ◽  
Association Studies ◽  
Functional Network ◽  
Gene Repertoire ◽  
Functional Roles ◽  
Protein Protein Interaction ◽  
Pan Genome

Abstract Background Discerning genes crucial to antimicrobial resistance (AMR) mechanisms is becoming more and more important to accurately and swiftly identify AMR pathogenic strains. Pangenome-wide association studies (e.g. Scoary) identified numerous putative AMR genes. However, only a tiny proportion of the putative resistance genes are annotated by AMR databases or Gene Ontology. In addition, many putative resistance genes are of unknown function (termed hypothetical proteins). An annotation tool is crucially needed in order to reveal the functional organization of the resistome and expand our knowledge of the AMR gene repertoire. Results We developed an approach (PangenomeNet) for building co-functional networks from pan-genomes to infer functions for hypothetical genes. Using Escherichia coli as an example, we demonstrated that it is possible to build co-functional network from its pan-genome using co-inheritance, domain-sharing, and protein–protein-interaction information. The investigation of the network revealed that it fits the characteristics of biological networks and can be used for functional inferences. The subgraph consisting of putative meropenem resistance genes consists of clusters of stress response genes and resistance gene acquisition pathways. Resistome subgraphs also demonstrate drug-specific AMR genes such as beta-lactamase, as well as functional roles shared among multiple classes of drugs, mostly in the stress-related pathways. Conclusions By demonstrating the idea of pan-genome-based co-functional network on the E. coli species, we showed that the network can infer functional roles of the genes, including those without functional annotations, and provides holistic views on the putative antimicrobial resistomes. We hope that the pan-genome network idea can help formulate hypothesis for targeted experimental works.

scholarly journals Deriving disease modules from the compressed transcriptional space embedded in a deep autoencoder

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Sanjiv K. Dwivedi ◽  
Andreas Tjärnberg ◽  
Jesper Tegnér ◽  
Mika Gustafsson
Keyword(s):  
Biological Networks ◽  
Biological Network ◽  
Association Studies ◽  
Disease Genes ◽  
Genome Wide Association Studies ◽  
Protein Protein Interaction ◽  
Genome Wide ◽  
Significant Enrichment ◽  
Disease Related Genes ◽  
Disease Modules

AbstractDisease modules in molecular interaction maps have been useful for characterizing diseases. Yet biological networks, that commonly define such modules are incomplete and biased toward some well-studied disease genes. Here we ask whether disease-relevant modules of genes can be discovered without prior knowledge of a biological network, instead training a deep autoencoder from large transcriptional data. We hypothesize that modules could be discovered within the autoencoder representations. We find a statistically significant enrichment of genome-wide association studies (GWAS) relevant genes in the last layer, and to a successively lesser degree in the middle and first layers respectively. In contrast, we find an opposite gradient where a modular protein–protein interaction signal is strongest in the first layer, but then vanishing smoothly deeper in the network. We conclude that a data-driven discovery approach is sufficient to discover groups of disease-related genes.

scholarly journals Pan-Genome Analysis of Human Gastric PathogenH. pylori: Comparative Genomics and Pathogenomics Approaches to Identify Regions Associated with Pathogenicity and Prediction of Potential Core Therapeutic Targets

2015 ◽  
Vol 2015 ◽  
pp. 1-17 ◽  
Author(s):  
Amjad Ali ◽  
Anam Naz ◽  
Siomar C Soares ◽  
Marriam Bakhtiar ◽  
Sandeep Tiwari ◽  
...  
Keyword(s):  
Phylogenetic Analyses ◽  
Therapeutic Targets ◽  
Gene Families ◽  
Gene Repertoire ◽  
Potential Core ◽  
Protein Protein Interaction ◽  
Pan Genome ◽  
H Pylori ◽  
Conserved Gene ◽  
Genome Analyses

Helicobacter pyloriis a human gastric pathogen implicated as the major cause of peptic ulcer and second leading cause of gastric cancer (~70%) around the world. Conversely, an increased resistance to antibiotics and hindrances in the development of vaccines againstH. pyloriare observed. Pan-genome analyses of the global representativeH. pyloriisolates consisting of 39 complete genomes are presented in this paper. Phylogenetic analyses have revealed close relationships among geographically diverse strains ofH. pylori. The conservation among these genomes was further analyzed by pan-genome approach; the predicted conserved gene families (1,193) constitute ~77% of the averageH. pylorigenome and 45% of the global gene repertoire of the species. Reverse vaccinology strategies have been adopted to identify and narrow down the potential core-immunogenic candidates. Total of 28 nonhost homolog proteins were characterized as universal therapeutic targets againstH. pyloribased on their functional annotation and protein-protein interaction. Finally, pathogenomics and genome plasticity analysis revealed 3 highly conserved and 2 highly variable putative pathogenicity islands in all of theH. pylorigenomes been analyzed.

scholarly journals Genome-wide analysis in Escherichia coli unravels an unprecedented level of genetic homoplasy associated with cefotaxime resistance

2020 ◽  
Author(s):  
Jordy P.M. Coolen ◽  
Evert P.M. den Drijver ◽  
Jaco J. Verweij ◽  
Jodie A. Schildkraut ◽  
Kornelia Neveling ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Antibiotic Resistance ◽  
Resistance Genes ◽  
Promoter Region ◽  
Association Studies ◽  
Antibiotics Resistance ◽  
Sequencing Data ◽  
E Coli ◽  
Genome Wide Analysis ◽  
Genome Wide

ABSTRACTCefotaxime (CTX) is a commonly used third-generation cephalosporin (3GC) to treat infections caused by Escherichia coli. Two genetic mechanisms have been associated with 3GC resistance in E. coli. The first is the conjugative transfer of a plasmid harboring antibiotic resistance genes. The second is the introduction of mutations in the promoter region of the ampC β-lactamase gene that cause chromosomal-encoded β-lactamase hyperproduction. A wide variety of promoter mutations related to AmpC hyperproduction have been described. However, their link to a specific 3GC such as CTX resistance has not been reported. Here, we measured CTX MICs in 172 cefoxitin resistant E. coli isolates and performed genome-wide analysis of homoplastic mutations associated with CTX resistance by comparing Illumina whole-genome sequencing data of all isolates to a PacBio tailored-made reference chromosome. We mapped the mutations on the reference chromosome and determined their occurrence in the phylogeny, revealing extreme homoplasy at the −42 position of the ampC promoter. The 24 occurrences of a “T” at the −42 position rather than the wild type “C”, resulted from 18 independent C>T mutations in 5 phylogroups. The −42 C>T mutation was only observed in E. coli lacking a plasmid-encoded ampC gene. The association of the −42 C>T mutation with CTX resistance was confirmed to be significant (FDR < 0.05). To conclude, genome-wide analysis of homoplasy in combination with CTX resistance identifies the −42 C>T mutation of the ampC promotor as significantly associated with CTX resistance and underline the role of recurrent mutations in the spread of antibiotics resistance.Impact StatementIn the past decades, the worldwide spread of extended spectrum beta-lactamases (ESBLs) has led to a substantial increase in the prevalence of resistant common pathogens, thereby restricting available treatment options. Although acquired resistance genes, e.g. ESBLs, get most attention, chromosome-encoded resistance mechanisms may play an important role as well. In E. coli chromosome-encoded β-lactam resistance can be caused by alterations in the promoter region of the ampC gene. To improve our understanding of how frequently these alterations occur, a comprehensive interpretation of the evolution of these mutations is essential. This study is the first to apply genome-wide homoplasy analysis to better perceive adaptation of the E. coli genome to antibiotics. Thereby, this study grants insights into how chromosomal-encoded antibiotic resistance evolves and, by combining genome-wide association studies with homoplasy analyses, provides potential strategies for future association studies into the causes of antibiotics resistance.Data summaryAll data is available under BioProject: PRJNA592140. Raw Illumina sequencing data and metadata of all 171 E. coli isolates used in this study is available from the Sequence Read Archive database under accession no. SAMN15052485 to SAMN15052655. Full reference chromosome of ampC_0069 is available via GenBank accession no. CP046396.1 and NCBI Reference Sequence: NZ_CP046396.1.

Analysis of Protein-Protein Interaction Networks through Computational Approaches

2020 ◽  
Vol 27 (4) ◽  
pp. 265-278 ◽  
Author(s):  
Ying Han ◽  
Liang Cheng ◽  
Weiju Sun
Keyword(s):  
Protein Interaction ◽  
Biological Networks ◽  
Interaction Networks ◽  
Computational Techniques ◽  
Cellular Functions ◽  
Protein Protein Interaction ◽  
Comprehensive Information ◽  
Protein Interaction Prediction ◽  
Or Gene ◽  
Experimental Findings

The interactions among proteins and genes are extremely important for cellular functions. Molecular interactions at protein or gene levels can be used to construct interaction networks in which the interacting species are categorized based on direct interactions or functional similarities. Compared with the limited experimental techniques, various computational tools make it possible to analyze, filter, and combine the interaction data to get comprehensive information about the biological pathways. By the efficient way of integrating experimental findings in discovering PPIs and computational techniques for prediction, the researchers have been able to gain many valuable data on PPIs, including some advanced databases. Moreover, many useful tools and visualization programs enable the researchers to establish, annotate, and analyze biological networks. We here review and list the computational methods, databases, and tools for protein−protein interaction prediction.

Plant Elite Squad: First Defense Line and Resistance Genes – Identification, Diversity and Functional Roles

2017 ◽  
Vol 18 (4) ◽  
pp. 294-310 ◽  
Author(s):  
Ana Wanderley-Nogueira ◽  
Joao Bezerra-Neto ◽  
Ederson Kido ◽  
Flavia Araujo ◽  
Lidiane Amorim ◽  
...  
Keyword(s):  
Resistance Genes ◽  
Functional Roles

scholarly journals Virulence Properties of mcr-1-Positive Escherichia coli Isolated from Retail Poultry Meat

2021 ◽  
Vol 9 (2) ◽  
pp. 308
Author(s):  
Michaela Kubelová ◽  
Ivana Koláčková ◽  
Tereza Gelbíčová ◽  
Martina Florianová ◽  
Alžběta Kalová ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Resistance Genes ◽  
Antibiotic Resistance Genes ◽  
Poultry Meat ◽  
Human Populations ◽  
E Coli ◽  
Antimicrobial Resistance Genes ◽  
Mlst Type ◽  
On Line ◽  
Sequence Types

The great plasticity and diversity of the Escherichia coli genome, together with the ubiquitous occurrence, make E. coli a bacterium of world-wide concern. Of particular interest are pathogenic strains and strains harboring antimicrobial resistance genes. Overlapping virulence-associated traits between avian-source E. coli and human extraintestinal pathogenic E. coli (ExPEC) suggest zoonotic potential and safety threat of poultry food products. We analyzed whole-genome sequencing (WGS) data of 46 mcr-1-positive E. coli strains isolated from retail raw meat purchased in the Czech Republic. The investigated strains were characterized by their phylogroup—B1 (43%), A (30%), D (11%), E (7%), F (4%), B2 (2%), C (2%), MLST type, and serotype. A total of 30 multilocus sequence types (STs), of which ST744 was the most common (11%), were identified, with O8 and O89 as the most prevalent serogroups. Using the VirulenceFinder tool, 3 to 26 virulence genes were detected in the examined strains and a total of 7 (15%) strains met the pathogenic criteria for ExPEC. Four strains were defined as UPEC (9%) and 18 (39%) E. coli strains could be classified as APEC. The WGS methods and available on-line tools for their evaluation enable a comprehensive approach to the diagnosis of virulent properties of E. coli strains and represent a suitable and comfortable platform for their detection. Our results show that poultry meat may serve as an important reservoir of strains carrying both virulence and antibiotic resistance genes for animal and human populations.

scholarly journals Genome evolution and the emergence of pathogenicity in avian Escherichia coli

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Leonardos Mageiros ◽  
Guillaume Méric ◽  
Sion C. Bayliss ◽  
Johan Pensar ◽  
Ben Pascoe ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Association Studies ◽  
Virulence Gene ◽  
Systemic Infection ◽  
Disease Status ◽  
Evolutionary Mechanisms ◽  
Sustainable Food ◽  
E Coli ◽  
Common Birds ◽  
Systemic Infections

AbstractChickens are the most common birds on Earth and colibacillosis is among the most common diseases affecting them. This major threat to animal welfare and safe sustainable food production is difficult to combat because the etiological agent, avian pathogenic Escherichia coli (APEC), emerges from ubiquitous commensal gut bacteria, with no single virulence gene present in all disease-causing isolates. Here, we address the underlying evolutionary mechanisms of extraintestinal spread and systemic infection in poultry. Combining population scale comparative genomics and pangenome-wide association studies, we compare E. coli from commensal carriage and systemic infections. We identify phylogroup-specific and species-wide genetic elements that are enriched in APEC, including pathogenicity-associated variation in 143 genes that have diverse functions, including genes involved in metabolism, lipopolysaccharide synthesis, heat shock response, antimicrobial resistance and toxicity. We find that horizontal gene transfer spreads pathogenicity elements, allowing divergent clones to cause infection. Finally, a Random Forest model prediction of disease status (carriage vs. disease) identifies pathogenic strains in the emergent ST-117 poultry-associated lineage with 73% accuracy, demonstrating the potential for early identification of emergent APEC in healthy flocks.

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