In silico identification of bacteriocin gene clusters in the gastrointestinal tract, based on the Human Microbiome Project’s reference genome database

Autor: Calum J. Walsh, Colin Hill, Caitriona M. Guinane, Paul D. Cotter, Paul W. O'Toole, R. Paul Ross
Přispěvatelé: Science Foundation Ireland, SFI/11/PI/1137
Jazyk: angličtina
Rok vydání: 2015
Předmět:
Human Microbiome Project
Unclassified drug
Bacteriocin gene
Gut flora
computer.software_genre
Lantibiotic
Bacterium
Bacteriocins
Gram positive bacterium
Ruminococcus
2. Zero hunger
0303 health sciences
education.field_of_study
Intestine flora
Database
Bacteriolysin
Microbiota
Gastrointestinal Microbiome
3. Good health
Actinobacteria
Synergistetes
Multigene Family
Roseburia
Human gut microbiota
Research Article
Microbiology (medical)
Bacterium isolate
Bacteriocin
In silico
Population
Firmicutes
Bacterial genome
Gut microbiota
Biology
Microbiology
Fusobacteria
03 medical and health sciences
Proteobacteria
Humans
Computer Simulation
Gene cluster
education
030304 developmental biology
030306 microbiology
Bacteroidetes
Computational Biology
biology.organism_classification
Biosynthetic Pathways
Gastrointestinal Tract
bacteriocin gene clusters
bacteria
Bifidobacterium
Sactipeptide
computer
Reference genome
Zdroj: BMC Microbiology
Popis: peer-reviewed Background The human gut microbiota comprises approximately 100 trillion microbial cells which significantly impact many aspects of human physiology - including metabolism, nutrient absorption and immune function. Disturbances in this population have been implicated in many conditions and diseases, including obesity, type-2 diabetes and inflammatory bowel disease. This suggests that targeted manipulation or shaping of the gut microbiota, by bacteriocins and other antimicrobials, has potential as a therapeutic tool for the prevention or treatment of these conditions. With this in mind, several studies have used traditional culture-dependent approaches to successfully identify bacteriocin-producers from the mammalian gut. In silico-based approaches to identify novel gene clusters are now also being utilised to take advantage of the vast amount of data currently being generated by next generation sequencing technologies. In this study, we employed an in silico screening approach to mine potential bacteriocin clusters in genome-sequenced isolates from the gastrointestinal tract (GIT). More specifically, the bacteriocin genome-mining tool BAGEL3 was used to identify potential bacteriocin producers in the genomes of the GIT subset of the Human Microbiome Project’s reference genome database. Each of the identified gene clusters were manually annotated and potential bacteriocin-associated genes were evaluated. Results We identified 74 clusters of note from 59 unique members of the Firmicutes, Bacteroidetes, Actinobacteria, Fusobacteria and Synergistetes. The most commonly identified class of bacteriocin was the >10 kDa class, formerly known as bacteriolysins, followed by lantibiotics and sactipeptides. Conclusions Multiple bacteriocin gene clusters were identified in a dataset representative of the human gut microbiota. Interestingly, many of these were associated with species and genera which are not typically associated with bacteriocin production. CJW, CMG and PDC are supported by a SFI PI award to PDC “Obesibiotics” (11/PI/1137).
Databáze: OpenAIRE