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Metagenomic water quality monitoring with a portable laboratory.

ABSTRACT: We describe the technical feasibility of metagenomic water quality analysis using only portable equipment, for example mini-vacuum pumps and filtration units, mini-centrifuges, mini-PCR machines and the memory-stick sized MinION of Oxford Nanopore Technologies, for the library preparation and sequencing of 16S rRNA gene amplicons. Using this portable toolbox on site, we successfully characterized the microbiome of water samples collected from Birtley Sewage Treatment Plant, UK, and its environs. We also demonstrated the applicability of the portable metagenomics toolbox in a low-income country by surveying water samples from the Akaki River around Addis Ababa, Ethiopia. The 16S rRNA gene sequencing workflow, including DNA extraction, PCR amplification, sequencing library preparation, and sequencing was accomplished within one working day. The metagenomic data became available within 24-72 h, depending on internet speed. Metagenomic analysis clearly distinguished the microbiome of pristine samples from sewage influenced water samples. Metagenomic analysis identified the potential role of two bacterial genera not conventionally monitored, Arcobacter and Aeromonas, as predominant faecal pollution indicators/waterborne hazards. Subsequent quantitative PCR analysis validated the high Arcobacter butzleri abundances observed in the urban influenced Akaki River water samples by portable next generation sequencing with the MinION device. Overall, our field deployable metagenomics toolbox advances the capability of scientists to comprehensively monitor microbiomes anywhere in the world, including in the water, food and drinks industries, the health services, agriculture and beyond.

SUBMITTER: Acharya K

PROVIDER: S-EPMC7347499 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Metagenomic water quality monitoring with a portable laboratory.

Acharya Kishor K Blackburn Adrian A Mohammed Jemila J Haile Alemseged Tamiru AT Hiruy Andualem Mekonnen AM Werner David D

Water research 20200710

We describe the technical feasibility of metagenomic water quality analysis using only portable equipment, for example mini-vacuum pumps and filtration units, mini-centrifuges, mini-PCR machines and the memory-stick sized MinION of Oxford Nanopore Technologies, for the library preparation and sequencing of 16S rRNA gene amplicons. Using this portable toolbox on site, we successfully characterized the microbiome of water samples collected from Birtley Sewage Treatment Plant, UK, and its environs. ...[more]

PMID: 32688150

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Project description:BackgroundPost-market surveillance is a key regulatory function to prevent substandard and falsified (SF) medicines from being consumed by patients. Field deployable technologies offer the potential for rapid objective screening for SF medicines.Methods and findingsWe evaluated twelve devices: three near infrared spectrometers (MicroPHAZIR RX, NIR-S-G1, Neospectra 2.5), two Raman spectrometers (Progeny, TruScan RM), one mid-infrared spectrometer (4500a), one disposable colorimetric assay (Paper Analytical Devices, PAD), one disposable immunoassay (Rapid Diagnostic Test, RDT), one portable liquid chromatograph (C-Vue), one microfluidic system (PharmaChk), one mass spectrometer (QDa), and one thin layer chromatography kit (GPHF-Minilab). Each device was tested with a series of field collected medicines (FCM) along with simulated medicines (SIM) formulated in a laboratory. The FCM and SIM ranged from samples with good quality active pharmaceutical ingredient (API) concentrations, reduced concentrations of API (80% and 50% of the API), no API, and the wrong API. All the devices had high sensitivities (91.5 to 100.0%) detecting medicines with no API or the wrong API. However, the sensitivities of each device towards samples with 50% and 80% API varied greatly, from 0% to 100%. The infrared and Raman spectrometers had variable sensitivities for detecting samples with 50% and 80% API (from 5.6% to 50.0%). The devices with the ability to quantitate API (C-Vue, PharmaChk, QDa) had sensitivities ranging from 91.7% to 100% to detect all poor quality samples. The specificity was lower for the quantitative C-Vue, PharmaChk, & QDa (50.0% to 91.7%) than for all the other devices in this study (95.5% to 100%).ConclusionsThe twelve devices evaluated could detect medicines with the wrong or none of the APIs, consistent with falsified medicines, with high accuracy. However, API quantitation to detect formulations similar to those commonly found in substandards proved more difficult, requiring further technological innovation.

Project description:The improvement of sequencing technologies has facilitated generalization of metagenomic sequencing, which has become a standard procedure for analyzing the structure and functionality of microbiomes. Bioinformatic analysis of sequencing results poses a challenge because it involves many different complex steps. SqueezeMeta is a fully automatic pipeline for metagenomics/metatranscriptomics, covering all steps of the analysis. SqueezeMeta includes multi-metagenome support that enables co-assembly of related metagenomes and retrieval of individual genomes via binning procedures. SqueezeMeta features several unique characteristics: co-assembly procedure or co-assembly of unlimited number of metagenomes via merging of individual assembled metagenomes, both with read mapping for estimation of the abundances of genes in each metagenome. It also includes binning and bin checking for retrieving individual genomes. Internal checks for the assembly and binning steps provide information about the consistency of contigs and bins. Moreover, results are stored in a MySQL database, where they can be easily exported and shared, and can be inspected anywhere using a flexible web interface that allows simple creation of complex queries. We illustrate the potential of SqueezeMeta by analyzing 32 gut metagenomes in a fully automatic way, enabling retrieval of several million genes and several hundreds of genomic bins. One of the motivations in the development of SqueezeMeta was producing a software capable of running in small desktop computers and thus amenable to all users and settings. We were also able to co-assemble two of these metagenomes and complete the full analysis in less than one day using a simple laptop computer. This reveals the capacity of SqueezeMeta to run without high-performance computing infrastructure and in absence of any network connectivity. It is therefore adequate for in situ, real time analysis of metagenomes produced by nanopore sequencing. SqueezeMeta can be downloaded from https://github.com/jtamames/SqueezeMeta.

Project description:Select bacteria, such as Escherichia coli or coliforms, have been widely used as sentinels of low water quality; however, there are concerns regarding their predictive accuracy for the protection of human and environmental health. To develop improved monitoring systems, a greater understanding of bacterial community structure, function, and variability across time is required in the context of different pollution types, such as agricultural and urban contamination. Here, we present a year-long survey of free-living bacterial DNA collected from seven sites along rivers in three watersheds with varying land use in Southwestern Canada. This is the first study to examine the bacterial metagenome in flowing freshwater (lotic) environments over such a time span, providing an opportunity to describe bacterial community variability as a function of land use and environmental conditions. Characteristics of the metagenomic data, such as sequence composition and average genome size (AGS), vary with sampling site, environmental conditions, and water chemistry. For example, AGS was correlated with hours of daylight in the agricultural watershed and, across the agriculturally and urban-affected sites, k-mer composition clustering corresponded to nutrient concentrations. In addition to indicating a community shift, this change in AGS has implications in terms of the normalization strategies required, and considerations surrounding such strategies in general are discussed. When comparing abundances of gene functional groups between high- and low-quality water samples collected from an agricultural area, the latter had a higher abundance of nutrient metabolism and bacteriophage groups, possibly reflecting an increase in agricultural runoff. This work presents a valuable dataset representing a year of monthly sampling across watersheds and an analysis targeted at establishing a foundational understanding of how bacterial lotic communities vary across time and land use. The results provide important context for future studies, including further analyses of watershed ecosystem health, and the identification and development of biomarkers for improved water quality monitoring systems.

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Metagenomic water quality monitoring with a portable laboratory.

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Metagenomic water quality monitoring with a portable laboratory.

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