Predicting pathogenicity behavior in Escherichia coli population through a state dependent model and TRS profiling

Autor: Marta Majchrzak, Anna B. Kubiak-Szeligowska, Pawel Parniewski, Ingemar Kaj, Krzysztof Bartoszek, Sebastian Sakowski
Jazyk: angličtina
Rok vydání: 2018
Předmět:
0301 basic medicine
Conservation Biology
Physiology
Speciation
Population genetics
Pathogenesis
Urine
Pathology and Laboratory Medicine
medicine.disease_cause
Polymerase Chain Reaction
Trinucleotide Repeats
Medicine and Health Sciences
Sannolikhetsteori och statistik
Probability Theory and Statistics
lcsh:QH301-705.5
Escherichia coli Infections
Phylogeny
Conservation Science
education.field_of_study
Bioinformatics (Computational Biology)
Virulence
Ecology
Body Fluids
Bacterial Pathogens
Phenotype
Computational Theory and Mathematics
Medical Microbiology
Modeling and Simulation
Urinary Tract Infections
Microsatellite
Pathogens
Anatomy
Research Article
Diarrhea
Evolutionary Processes
Virulence Factors
Genetic Speciation
030106 microbiology
Population
Computational biology
Bioinformatik och systembiologi
Biology
Extinction
Biological
Microbiology
Models
Biological
03 medical and health sciences
Cellular and Molecular Neuroscience
Phylogenetics
Escherichia coli
Genetics
medicine
Humans
Computer Simulation
education
Microbial Pathogens
Molecular Biology
Species Extinction
Ecology
Evolution
Behavior and Systematics
Probability
Branching process
Evolutionary Biology
Population Biology
Models
Genetic
Bioinformatics and Systems Biology
Ecology and Environmental Sciences
Biology and Life Sciences
Computational Biology
Gene Expression Regulation
Bacterial
Gastrointestinal Tract
030104 developmental biology
lcsh:Biology (General)
Bioinformatik (beräkningsbiologi)
Digestive System
Population Genetics
Software
Microsatellite Repeats
Zdroj: PLoS Computational Biology, Vol 14, Iss 1, p e1005931 (2018)
PLoS Computational Biology
Popis: The Binary State Speciation and Extinction (BiSSE) model is a branching process based model that allows the diversification rates to be controlled by a binary trait. We develop a general approach, based on the BiSSE model, for predicting pathogenicity in bacterial populations from microsatellites profiling data. A comprehensive approach for predicting pathogenicity in E. coli populations is proposed using the state-dependent branching process model combined with microsatellites TRS-PCR profiling. Additionally, we have evaluated the possibility of using the BiSSE model for estimating parameters from genetic data. We analyzed a real dataset (from 251 E. coli strains) and confirmed previous biological observations demonstrating a prevalence of some virulence traits in specific bacterial sub-groups. The method may be used to predict pathogenicity of other bacterial taxa.
Author summary An important challenge in Computational Biology is the analysis of genetic molecular data through sophisticated computer science and mathematical methods that are implemented by interdisciplinary research groups. The resulting comprehensive approach, based on the BiSSE model and microsatellites profiling (TRS-PCR), can be used to predict pathogenicity behavior in bacterial taxa. As proof of concept, we applied the procedure to real clinical data sets of genetic information obtained from a unique collection of bacterial populations (251 strains). Our results showed that a state-dependent model was able to predict pathogenicity behavior of E. coli population. Furthermore, we confirmed previous biological observations indicating a prevalence of some virulence genetic traits in bacteria.
Databáze: OpenAIRE
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