Social demographics determinants for resistome and microbiome variation of a multiethnic community in Southern Malaysia.
Jacky DwiyantoM A L HuëtM H HussainT T SuJoash Ban Lee TanKai Yee TohJ W J LeeS RahmanChong Chun WiePublished in: NPJ biofilms and microbiomes (2023)
The prevalence of antibiotic-resistant bacteria in Southeast Asia is a significant concern, yet there is limited research on the gut resistome and its correlation with lifestyle and environmental factors in the region. This study aimed to profile the gut resistome of 200 individuals in Malaysia using shotgun metagenomic sequencing and investigate its association with questionnaire data comprising demographic and lifestyle variables. A total of 1038 antibiotic resistance genes from 26 classes were detected with a mean carriage rate of 1.74 ± 1.18 gene copies per cell per person. Correlation analysis identified 14 environmental factors, including hygiene habits, health parameters, and intestinal colonization, that were significantly associated with the resistome (adjusted multivariate PERMANOVA, p < 0.05). Notably, individuals with positive yeast cultures exhibited a reduced copy number of 15 antibiotic resistance genes. Network analysis highlighted Escherichia coli as a major resistome network hub, with a positive correlation to 36 antibiotic-resistance genes. Our findings suggest that E. coli may play a pivotal role in shaping the resistome dynamics in Segamat, Malaysia, and its abundance is strongly associated with the community's health and lifestyle habits. Furthermore, the presence of yeast appears to be associated with the suppression of antibiotic-resistance genes.
Keyphrases
- antibiotic resistance genes
- copy number
- wastewater treatment
- network analysis
- microbial community
- healthcare
- mental health
- escherichia coli
- anaerobic digestion
- metabolic syndrome
- public health
- weight loss
- physical activity
- cardiovascular disease
- single cell
- genome wide
- health information
- risk factors
- electronic health record
- type diabetes
- gene expression
- stem cells
- big data
- cross sectional
- transcription factor
- cell wall
- cystic fibrosis
- cell therapy
- artificial intelligence
- risk assessment
- human health