Improved quantitative microbiome profiling and environmental antibiotic resistance surveillance
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB42314 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR5035920_1.fastq.gz | Fastqsanger.gz | |||
| ERR5035920_2.fastq.gz | Fastqsanger.gz | |||
| ERR5035930_1.fastq.gz | Fastqsanger.gz | |||
| ERR5035930_2.fastq.gz | Fastqsanger.gz | |||
| ERR5035940_1.fastq.gz | Fastqsanger.gz |
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Project description:BackgroundUnderstanding environmental microbiomes and antibiotic resistance (AR) is hindered by over reliance on relative abundance data from next-generation sequencing. Relative data limits our ability to quantify changes in microbiomes and resistomes over space and time because sequencing depth is not considered and makes data less suitable for Quantitative Microbial Risk Assessments (QMRA), critical in quantifying environmental AR exposure and transmission risks.ResultsHere we combine quantitative microbiome profiling (QMP; parallelization of amplicon sequencing and 16S rRNA qPCR to estimate cell counts) and absolute resistome profiling (based on high-throughput qPCR) to quantify AR along an anthropogenically impacted river. We show QMP overcomes biases caused by relative taxa abundance data and show the benefits of using unified Hill number diversities to describe environmental microbial communities. Our approach overcomes weaknesses in previous methods and shows Hill numbers are better for QMP in diversity characterisation.ConclusionsMethods here can be adapted for any microbiome and resistome research question, but especially providing more quantitative data for QMRA and other environmental applications.
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Project description:Freshwater environments such as rivers receive effluent discharges from wastewater treatment plants, representing a potential hotspot for antibiotic resistance genes (ARGs). These effluents also contain low levels of different antimicrobials including biocides and antibiotics such as sulfonamides that can be frequently detected in rivers. The impact of such exposure on ARG prevalence and microbial diversity of riverine environment is unknown, so the aim of this study was to investigate the release of a sub-lethal concentration (<4 g L-1) of the sulfonamide compound sulfamethoxazole (SMX) on the river bacterial microbiome using a microflume system. This system was a semi-natural in-vitro microflume using river water (30 L) and sediment, with circulation to mimic river flow. A combination of ‘omics’ approaches were conducted to study the impact of SMX exposure on the microbiomes within the microflumes. Metaproteomics did not show differences in ARGs expression with SMX exposure in water.
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Project description:Antimicrobial resistance genes (ARGs) present in the environment pose a risk to human health due to potential for transfer to human pathogens. Surveillance is an integral part of mitigating environmental dissemination. Quantification of the mobile genetic element class 1 integron-integrase gene (intI1) has been proposed as a surrogate to measuring multiple ARGs. Measurement of such indicator genes can be further simplified by adopting emerging nucleic acids methods such as loop mediated isothermal amplification (LAMP). In this study, LAMP assays were designed and tested for estimating relative abundance of the intI1 gene, which included design of a universal bacteria 16S rRNA gene assay. Following validation of sensitivity and specificity with known bacterial strains, the assays were tested using DNA extracted from river and lake samples. Results showed a significant Pearson correlation (R2 = 0.8) between the intI1 gene LAMP assay and ARG relative abundance (measured via qPCR). To demonstrate the ruggedness of the LAMP assays, experiments were also run in the hands of relatively "untrained" personnel by volunteer undergraduate students at a local community college using a hand-held real-time DNA analysis device - Gene-Z. Overall, results support use of the intI1 gene as an indicator of ARGs and the LAMP assays exhibit the opportunity for volunteers to monitor environmental samples for anthropogenic pollution outside of a specialized laboratory.
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Project description:Schistosomiasis is a water-based, infectious disease with high morbidity and significant economic burdens affecting >250 million people globally. Disease control has, with notable success, for decades focused on drug treatment of infected human populations, but a recent paradigm shift now entails moving from control to elimination. To achieve this ambitious goal, more sensitive diagnostic tools are needed to monitor progress toward transmission interruption in the environment, especially in low-intensity infection areas. We report on the development of an environmental DNA (eDNA)-based tool to efficiently detect DNA traces of the parasite Schistosoma mansoni directly in the aquatic environment, where the nonhuman part of the parasite life cycle occurs. This is a report of the successful detection of S. mansoni in freshwater samples by using aquatic eDNA. True eDNA was detected in as few as 10 cercariae per liter of water in laboratory experiments. The field applicability of the method was tested at known transmission sites in Kenya, where comparison of schistosome detection by conventional snail surveys (snail collection and cercariae shedding) with eDNA (water samples) showed 71% agreement between the methods. The eDNA method furthermore detected schistosome presence at two additional sites where snail shedding failed, demonstrating a higher sensitivity of eDNA sampling. We conclude that eDNA provides a promising tool to substantially improve the environmental surveillance of S. mansoni Given the proper method and guideline development, eDNA could become an essential future component of the schistosomiasis control tool box needed to achieve the goal of elimination.
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