J 2024

Detecting horizontal gene transfer among microbiota: an innovative pipeline for identifying co-shared genes within the mobilome through advanced comparative analysis

SCHWARZEROVA, Jana, Michal ZEMAN, Vladimir BABAK, Katerina JURECKOVA, Marketa NYKRYNOVA et. al.

Basic information

Original name

Detecting horizontal gene transfer among microbiota: an innovative pipeline for identifying co-shared genes within the mobilome through advanced comparative analysis

Authors

SCHWARZEROVA, Jana (203 Czech Republic), Michal ZEMAN (203 Czech Republic), Vladimir BABAK (203 Czech Republic), Katerina JURECKOVA (203 Czech Republic), Marketa NYKRYNOVA (203 Czech Republic), Margaret VARGA (203 Czech Republic), Wolfram WECKWERTH (203 Czech Republic), Monika DOLEJSKA (203 Czech Republic), Valentine PROVAZNÍK (203 Czech Republic, belonging to the institution), Ivan RYCHLIK (203 Czech Republic) and Darina CEJKOVA (203 Czech Republic, guarantor)

Edition

Microbiology spectrum, WASHINGTON, AMER SOC MICROBIOLOGY, 2024, 2165-0497

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10606 Microbiology

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

Impact factor

Impact factor: 3.700 in 2022

Organization unit

Faculty of Medicine

DOI

http://dx.doi.org/10.1128/spectrum.01964-23

UT WoS

001126360200003

Keywords in English

animal microbiome; genome evolution; mobile genetic elements; mobilome; resistance genes; horizontal gene transfer; gut microbiota

Tags

14110515, rivok

Tags

International impact, Reviewed
Změněno: 12/7/2024 12:57, Mgr. Tereza Miškechová

Abstract

V originále

The study presents an innovative pipeline for detecting horizontal gene transfer (HGT) among a collection of sequenced genomes from gut microbiota. Herein, chicken and porcine gut microbiota were analyzed. Based on statistical analysis, we propose that nearly identical genes co-shared between distinct genera can be evidence for a previous event of mobilization of that gene from genome to genome via HGT. Data mining, computational analysis, and network analysis were used to investigate genomes of 452 isolates of chicken or porcine origin to detect genes involved in HGT. The proposed pipeline is user-friendly and includes network visualization. The study highlights that different species and strains of the same genera typically carry different cargo of mobilized genes. The pipeline is capable of identifying not yet characterized genes, as well as genes that are usually co-transferred with genes involved in resistance, virulence, and/or mobilization. Among the analyzed genome collection, the main reservoirs of the HGT genes were found in Phocaeicola spp. (Bacteroidaceae) and UBA9475 spp. (early Pseudoflavonifractor, Oscillospiraceae). Altogether, over 6,000 genes suspected of HGT were identified. Genes associated with intracellular trafficking and secretion and DNA repair were enriched, while genes of unknown and general functions were dominant but not enriched. Only 15 genes were co-shared between Gram-positive and Gram-negative bacteria, mostly genes directly associated with mobilome or antibiotic resistance. However, most HGTs were identified among different genera of the same phylum. Therefore, we suggest that a significant selection pressure exists on gene variants at the phylum level.IMPORTANCEHorizontal gene transfer (HGT) is a key driver in the evolution of bacterial genomes. The acquisition of genes mediated by HGT may enable bacteria to adapt to ever-changing environmental conditions. Long-term application of antibiotics in intensive agriculture is associated with the dissemination of antibiotic resistance genes among bacteria with the consequences causing public health concern. Commensal farm-animal-associated gut microbiota are considered the reservoir of the resistance genes. Therefore, in this study, we identified known and not-yet characterized mobilized genes originating from chicken and porcine fecal samples using our innovative pipeline followed by network analysis to provide appropriate visualization to support proper interpretation.
Displayed: 11/11/2024 00:08