Cultured and uncultured metagenomic analysis of microbiome and resistome composition

Cultured and uncultured metagenomic analysis of microbiome and resistome composition

Abstrakt

Antibiotic resistance is a major global health and food safety concern, with hundreds of thousands of deaths annually linked to resistant infections. Resistance genes are commonly found in various environments, including water sources, soil, and animal waste such as chicken feces, highlighting the widespread nature of the problem. However, the full scope and diversity of these resistomes and associated bacteria have yet to be thoroughly investigated. In this study, we assessed the culture-based and culture-independent metagenomic sequencing approaches to identify and compare resistome and microbiome profile of chicken raised in farm in Czech Republic. The result revealed that bacterial orders such as Lactobacillales, Bacillales, and Bifidobacteriales predominated in the in vitro cultured samples, whereas Corynebacteriales and Micrococcales were abundant in uncultured metagenomic data. A total of 8 antibiotic classes were detected in the cultured samples compared with 12 in the uncultured ones. Furthermore, the HT-qPCR results indicated a higher number of positive detections of antibiotic resistance genes in the uncultured samples, reflecting greater overall ARG richness due to broader representation of the microbial community. These findings suggest that integrating culture-based methods with culture-independent metagenomic sequencing provides a more comprehensive and detailed dataset, significantly enhancing the depth and diversity of resistome and microbiome analysis. The dual approach captures a broader spectrum of microbial taxa ad resistance genes: cultured samples allow functional studies and detection of low-abundance cultivable organisms; while metagenomics reveals the full community, including unculturable or rare taxa. By combining these methods, researchers gain a more complete and accurate understanding of microbial diversity and antibiotic resistance dynamics across environmental samples. This strategy also improves the detection of rare and clinically relevant antibiotic resistance genes and bacterial strains that might otherwise remain undetected using a single methodology.

Antibiotic resistance is a major global health and food safety concern, with hundreds of thousands of deaths annually linked to resistant infections. Resistance genes are commonly found in various environments, including water sources, soil, and animal waste such as chicken feces, highlighting the widespread nature of the problem. However, the full scope and diversity of these resistomes and associated bacteria have yet to be thoroughly investigated. In this study, we assessed the culture-based and culture-independent metagenomic sequencing approaches to identify and compare resistome and microbiome profile of chicken raised in farm in Czech Republic. The result revealed that bacterial orders such as Lactobacillales, Bacillales, and Bifidobacteriales predominated in the in vitro cultured samples, whereas Corynebacteriales and Micrococcales were abundant in uncultured metagenomic data. A total of 8 antibiotic classes were detected in the cultured samples compared with 12 in the uncultured ones. Furthermore, the HT-qPCR results indicated a higher number of positive detections of antibiotic resistance genes in the uncultured samples, reflecting greater overall ARG richness due to broader representation of the microbial community. These findings suggest that integrating culture-based methods with culture-independent metagenomic sequencing provides a more comprehensive and detailed dataset, significantly enhancing the depth and diversity of resistome and microbiome analysis. The dual approach captures a broader spectrum of microbial taxa ad resistance genes: cultured samples allow functional studies and detection of low-abundance cultivable organisms; while metagenomics reveals the full community, including unculturable or rare taxa. By combining these methods, researchers gain a more complete and accurate understanding of microbial diversity and antibiotic resistance dynamics across environmental samples. This strategy also improves the detection of rare and clinically relevant antibiotic resistance genes and bacterial strains that might otherwise remain undetected using a single methodology.

Antibacterial Resistance Genes (ARGs), Resistome, Culture, Metagenomic sequencing

Antibacterial Resistance Genes (ARGs), Resistome, Culture, Metagenomic sequencing

Minoo Partovi Nasr, Darina Cejkova

09.06.2025

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https://clinicalmetagenomics.org/