Biology subjects

Huynh, B.-T.

Publications and source records attributed to Huynh, B.-T..

4 recordsLinked to original sources

bioRxiv2026

From sewage to shoreline: Tracing antibiotic resistance gene trends through tropical island wastewater treatment pathways

Wastewater is a key reservoir and transmission route for antibiotic resistance genes (ARGs), enabling their spread from influent to effluent and into receiving environments. However, how combined selective pressures (antibiotics, biocides, heavy metals, pharmaceuticals) influence resistant bacteria and ARG persistence over space and time remains poorly understood. Likewise, the role of the wastewater microbiome in ARG dynamics is still unclear, as few studies integrate microbiome shifts with chemical and environmental drivers. Here, we investigated how microbiome dynamics, chemical exposures, and environmental conditions shape clinically relevant ARG dynamics from sewage to receiving environments in Guadeloupe, French Caribbean. We analysed data collected from three wastewater continuums, (hospital-based, domestic, touristic) over four campaigns (September 2021-February 2023). We characterised ARG and microbiome composition spatiotemporal patterns and used a mixed-effect model to investigate ARG associations with potential drivers, including exposome factors, microbiome dissimilarity and environmental factors. Several ARGs were negatively associated with microbiome dissimilarity (Bray-Curtis distances) (aac(6)-Ib, aph(3)-III, blaSHV, blaTEM, intI1, qnrS, sul1 and tetM). Negative associations were also observed between upstream-downstream differences in anti-inflammatory drug concentrations and the abundance of aac(6)-Ib, aph(3)-III, blaCTX-M, ermB, intI1, and tetM. In contrast, ARG relative abundance was positively associated with upstream-downstream differences in antibiotic concentrations, suggesting selection along the continuum. These findings indicate that ARG dissemination along wastewater-to-coastal pathways is shaped by opposing processes, with microbiome turnover potentially limiting ARG persistence while chemical gradients promote specific gene enrichment. The outcome is ARG-specific, with implications for antimicrobial resistance risks associated with recreational waters, seafood consumption, and coastal ecosystem interactions.

microbiology↗

bioRxiv2025

Impacts of wastewater treatment and the exposome on antibiotic resistance gene dynamics: Insights from Guadeloupe, a French Caribbean Island

Wastewater treatment plants (WWTPs) are global hotspots for the dissemination of antibiotic resistance genes (ARGs), primarily driven by different anthropogenic activities. Chemical compounds commonly found in wastewater, including antibiotics, biocides, non-steroidal anti-inflammatory drugs (NSAIDs), and heavy metals, along with environmental factors such as temperature and precipitation, might enhance the selection of antibiotic-resistant bacteria (ARB) even at low concentrations, inadvertently promoting the proliferation of ARGs. Since WWTPs can vary in their removal efficiency and influent compositions, it is important to assess their impact in influencing the relative abundance of ARGs and pollutant concentrations in discharged effluent. We analyzed data collected in Guadeloupe, French Caribbean, using random forest and lasso to investigate changes in the resistome and exposome within untreated wastewater influents and treated effluents from three WWTPs. These WWTPs represented three distinct wastewater continuums--hospital-based, urban non-touristic, and urban touristic--each with unique influent compositions. The study, which spanned four sampling campaigns from September 2021 to January 2023, revealed that the reduction in ARG abundance by the WWTPs was lower than expected. Of the 16 clinically relevant genes and mobile genetic elements examined, the relative abundance of aph(3)-III, blaOXA, blaSHV, blaTEM, ermB, intI1, qnrS, and tetM was reduced by 59.8% to 89.9% across the three WWTPs. An increasing trend in the relative abundance of the mcr-1 gene was observed, showing a 9.52-fold increase in the treated effluent in the hospital continuum. Of the nine antibiotics tested, trimethoprim levels dropped by 70.8% in the touristic continuum and 78.8% in the non-touristic, while ciprofloxacin saw a significant 64.4% reduction only in the touristic continuum, while no other antibiotics or biocides among the eight tested were effectively removed. Regarding heavy metals, significant reductions were observed only in the non-touristic continuum, with cadmium (Cd), copper (Cu), and mercury (Hg) concentrations reduced by 32.5%, 21.1%, and 36.2%, respectively. Our findings provide insights into the associations between environmental factors and the relative abundance of ARGs in Guadeloupe. Generally, depending on the continuum, biocides, the antibiotic erythromycin, certain heavy metals (As, Cd, Cu, Cr, and Hg) and water temperature were associated with the relative abundance of clinically relevant ARGs. This study was not able to assess the impact of climate. Future research should include longitudinal studies with more frequent sampling to better investigate the evolution of antibiotic resistance in bacterial species and its associated drivers, including pollutants and climate-related factors.

microbiology↗

bioRxiv2019

Clonal transmission and new mechanism of resistance to trimethoprim-sulfamethoxazole in Stenotrophomonas maltophilia strains isolated in a neonatology unit at Antananarivo, Madagascar, deciphered by whole genome sequence analysis

Stenotrophomonas maltophilia has been recognized as an emerging multidrug resistant organism in hospital settings due to its resistance to a broad range of antimicrobial agents. These include {beta}-lactams and aminoglycosides, afforded by the existence of intrinsic and acquired resistance mechanisms. Trimethoprim/sulfamethoxazole (SXT) is recommended as one of the best treatment choices against S. maltophilia infections; however increasing resistance to SXT has complicated the treatment. From July 2014 to March 2015, individuals and surfaces from a neonatology ward in Antananarivo, Madagascar, were longitudinally followed to assess the transmission of bacteria resistant to antibiotics between neonates, individuals (parents and nurses) and ward environments. Four S. maltophilia strains were successively isolated from a water-tap (N=1), from feces obtained from a newborn (N=1), and nursing staff (N=2). Antimicrobial susceptibility testing and whole genome sequencing were performed on each isolate. Based on coregenome alignment, all strains were identical and belonged to the new sequence type ST-288. They were resistant to trimethoprim-sulfamethoxazole, carbapenems and intermediate to levofloxacin. Each isolate carried the aadB, strA, strB and sul1 genes located in a class I integron but variants of the dfrA gene were absent. We assessed by PROVEAN analysis the single nucleotide mutations found in folA, folC and folM genes and only the mutation in folA (A114T:GCC[->]ACC) has an effect on the activity of trimethoprim. Our findings demonstrated the prolonged presence of SXT-resistant S. maltophilia in a clinical setting with consecutive transfers from the environment to a newborn and staff based on the isolation dates. We also hypothesized that single nucleotide mutations in folA could be responsible for trimethoprim resistance.

microbiology↗

bioRxiv2018

Inference of significant microbial interactions from longitudinal metagenomics sequencing data

Data of next-generation sequencing (NGS) and their analysis have been facilitating advances in our understanding of microbial ecosystems such as human gut microbiota. However, inference of microbial interactions occurring within an ecosystem is still a challenge mainly due to metagenomics sequencing (e.g., 16S rDNA sequences) providing relative abundance of microbes instead of absolute cell count. In order to describe the population dynamics in microbial communities and estimate the involved microbial interactions, we introduce a procedure by integrating generalized Lotka-Volterra equations, forward stepwise regression and bootstrap aggregation. First, we successfully identify experimentally confirmed microbial interactions with relative abundance data of a cheese microbial community. Then, we apply the procedure to time-series of 16S rDNA sequences of gut microbiomes of children who were progressing to Type 1 diabetes (T1D progressors), and compare their gut microbial interactions to a healthy control group. Our results suggest that the number of inferred microbial interactions increased over time during the first three years of life. More microbial interactions are found in the gut flora of healthy children than the T1D progressors. The inhibitory effects from Actinobacteria and Bacilli to Bacteroidia, from Bacteroidia to Clostridia, and the benifit effect from Clostridia to Bacteroidia are shared between healthy children and T1D progressors. An inhibition of Clostridia by Gammaproteobacteria is found in healthy children that maintains through their first three years of life. This suppression appears in T1D progressors during the first year of life, which transforms to a commensalism relationship at the age of three years old. Gammaproteobacteria is found exerting an inhibition on Bacteroidia in the T1D progressors, which is not identified in the healthy controls.

ecology↗