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Datasets generated by shotgun sequencing of metagenomic libraries of the guajataca water reservoir.

ABSTRACT: The Guajataca Water Reservoir (GWR) was constructed for irrigation and to bring potable water to the northwestern region of Puerto Rico. The generation of DNA sequencing data from aquatic bodies (AB) using culture-independent approaches allows the investigation of the total microbial diversity as well as the potential anthropogenic impact. Metagenomic libraries were constructed for two GWR sampling sites and genomic information access through shotgun sequencing. After removing the bacterial host cell genome and the library fosmid sequences, the environmental genome was processed through Rapid Annotation using Subsystems Technology for Metagenomes (MG-RAST). The sequences consisted primarily of bacteria (95.70%), followed by viruses (2.94%), other sequences (0.28%) and eukaryote (0.09%). The most abundant species were Enterobacter cloacae (31%), Enterobacter sp. 638 (20%), Enterobacter cancerogenus (10%) and Escherichia coli (11%). Furthermore, the subsystem data showed that 13% of the genes belong to carbohydrates functionality, 12% to clustering-based-subsystems and another 9% related to virulence-disease-and-defense (out of which 8% pertain to genes of antibiotic resistance and toxic compounds). This unique data input will serve as a baseline to a better understanding not only the microbial communities present in the AB, but also the microbial activities with potential application in biotechnological and biomedical fields.

SUBMITTER: Soriano BM

PROVIDER: S-EPMC6288454 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Datasets generated by shotgun sequencing of metagenomic libraries of the guajataca water reservoir.

Soriano Berliza M BM Del Valle-Perez Laura M LM Morales-Vale Luis L Rios-Velazquez Carlos C

Data in brief 20181127

The Guajataca Water Reservoir (GWR) was constructed for irrigation and to bring potable water to the northwestern region of Puerto Rico. The generation of DNA sequencing data from aquatic bodies (AB) using culture-independent approaches allows the investigation of the total microbial diversity as well as the potential anthropogenic impact. Metagenomic libraries were constructed for two GWR sampling sites and genomic information access through shotgun sequencing. After removing the bacterial host ...[more]

PMID: 30560161

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Project description:BackgroundLong-read shotgun metagenomic sequencing is gaining in popularity and offers many advantages over short-read sequencing. The higher information content in long reads is useful for a variety of metagenomics analyses, including taxonomic classification and profiling. The development of long-read specific tools for taxonomic classification is accelerating, yet there is a lack of information regarding their relative performance. Here, we perform a critical benchmarking study using 11 methods, including five methods designed specifically for long reads. We applied these tools to several mock community datasets generated using Pacific Biosciences (PacBio) HiFi or Oxford Nanopore Technology sequencing, and evaluated their performance based on read utilization, detection metrics, and relative abundance estimates.ResultsOur results show that long-read classifiers generally performed best. Several short-read classification and profiling methods produced many false positives (particularly at lower abundances), required heavy filtering to achieve acceptable precision (at the cost of reduced recall), and produced inaccurate abundance estimates. By contrast, two long-read methods (BugSeq, MEGAN-LR & DIAMOND) and one generalized method (sourmash) displayed high precision and recall without any filtering required. Furthermore, in the PacBio HiFi datasets these methods detected all species down to the 0.1% abundance level with high precision. Some long-read methods, such as MetaMaps and MMseqs2, required moderate filtering to reduce false positives to resemble the precision and recall of the top-performing methods. We found read quality affected performance for methods relying on protein prediction or exact k-mer matching, and these methods performed better with PacBio HiFi datasets. We also found that long-read datasets with a large proportion of shorter reads (< 2 kb length) resulted in lower precision and worse abundance estimates, relative to length-filtered datasets. Finally, for classification methods, we found that the long-read datasets produced significantly better results than short-read datasets, demonstrating clear advantages for long-read metagenomic sequencing.ConclusionsOur critical assessment of available methods provides best-practice recommendations for current research using long reads and establishes a baseline for future benchmarking studies.

Project description:UnlabelledWhile commonplace in clinical settings, DNA-based assays for identification or enumeration of drinking water pathogens and other biological contaminants remain widely unadopted by the monitoring community. In this study, shotgun metagenomics was used to identify taste-and-odor producers and toxin-producing cyanobacteria over a 2-year period in a drinking water reservoir. The sequencing data implicated several cyanobacteria, including Anabaena spp., Microcystis spp., and an unresolved member of the order Oscillatoriales as the likely principal producers of geosmin, microcystin, and 2-methylisoborneol (MIB), respectively. To further demonstrate this, quantitative PCR (qPCR) assays targeting geosmin-producing Anabaena and microcystin-producing Microcystis were utilized, and these data were fitted using generalized linear models and compared with routine monitoring data, including microscopic cell counts, sonde-based physicochemical analyses, and assays of all inorganic and organic nitrogen and phosphorus forms and fractions. The qPCR assays explained the greatest variation in observed geosmin (adjusted R(2) = 0.71) and microcystin (adjusted R(2) = 0.84) concentrations over the study period, highlighting their potential for routine monitoring applications. The origin of the monoterpene cyclase required for MIB biosynthesis was putatively linked to a periphytic cyanobacterial mat attached to the concrete drinking water inflow structure. We conclude that shotgun metagenomics can be used to identify microbial agents involved in water quality deterioration and to guide PCR assay selection or design for routine monitoring purposes. Finally, we offer estimates of microbial diversity and metagenomic coverage of our data sets for reference to others wishing to apply shotgun metagenomics to other lacustrine systems.ImportanceCyanobacterial toxins and microbial taste-and-odor compounds are a growing concern for drinking water utilities reliant upon surface water resources. Specific identification of the microorganism(s) responsible for water quality degradation is often complicated by the presence of co-occurring taxa capable of producing these undesirable metabolites. Here we present a framework for how shotgun metagenomics can be used to definitively identify problematic microorganisms and how these data can guide the development of rapid genetic assays for routine monitoring purposes.

Project description:Dengue virus (DENV) represents a public health threat and economic burden in affected countries. The availability of genomic data is key to understanding viral evolution and dynamics, supporting improved control strategies. Currently, the use of high-throughput sequencing (HTS) technologies, which can be applied both directly to patient samples (shotgun metagenomics) and to PCR-amplified viral sequences (amplicon sequencing), is potentially the most informative approach to monitor viral dissemination and genetic diversity by providing, in a single methodological step, identification and characterization of the whole viral genome at the nucleotide level. Despite many advantages, these technologies require bioinformatics expertise and appropriate infrastructure for the analysis and interpretation of the resulting data. In addition, the many software solutions available can hamper the reproducibility and comparison of results. Here we present DEN-IM, a one-stop, user-friendly, containerized and reproducible workflow for the analysis of DENV short-read sequencing data from both amplicon and shotgun metagenomics approaches. It is able to infer the DENV coding sequence (CDS), identify the serotype and genotype, and generate a phylogenetic tree. It can easily be run on any UNIX-like system, from local machines to high-performance computing clusters, performing a comprehensive analysis without the requirement for extensive bioinformatics expertise. Using DEN-IM, we successfully analysed two types of DENV datasets. The first comprised 25 shotgun metagenomic sequencing samples from patients with variable serotypes and genotypes, including an in vitro spiked sample containing the four known serotypes. The second consisted of 106 paired-end and 76 single-end amplicon sequences of DENV 3 genotype III and DENV 1 genotype I, respectively, where DEN-IM allowed detection of the intra-genotype diversity. The DEN-IM workflow, parameters and execution configuration files, and documentation are freely available at https://github.com/B-UMMI/DEN-IM).

Project description:Spoilage and pathogenic spore-forming bacteria are a major cause of concern for producers of dairy products. Traditional agar-based detection methods employed by the dairy industry have limitations with respect to their sensitivity and specificity. The aim of this study was to identify low-abundance sporeformers in samples of a powdered dairy product, whey powder, produced monthly over 1 year, using novel culture-independent shotgun metagenomics-based approaches. Although mesophilic sporeformers were the main target of this study, in one instance thermophilic sporeformers were also targeted using this culture-independent approach. For comparative purposes, mesophilic and thermophilic sporeformers were also tested for within the same sample using culture-based approaches. Ultimately, the approaches taken highlighted differences in the taxa identified due to treatment and isolation methods. Despite this, low levels of transient, mesophilic, and in some cases potentially pathogenic sporeformers were consistently detected in powder samples. Although the specific sporeformers changed from one month to the next, it was apparent that 3 groups of mesophilic sporeformers, namely, Bacillus cereus, Bacillus licheniformis/Bacillusparalicheniformis, and a third, more heterogeneous group containing Brevibacillus brevis, dominated across the 12 samples. Total thermophilic sporeformer taxonomy was considerably different from mesophilic taxonomy, as well as from the culturable thermophilic taxonomy, in the one sample analyzed by all four approaches. Ultimately, through the application of shotgun metagenomic sequencing to dairy powders, the potential for this technology to facilitate the detection of undesirable bacteria present in these food ingredients is highlighted.IMPORTANCE The ability of sporeformers to remain dormant in a desiccated state is of concern from a safety and spoilage perspective in dairy powder. Traditional culturing techniques are slow and provide little information without further investigation. We describe the identification of mesophilic sporeformers present in powders produced over 1 year, using novel shotgun metagenomic sequencing. This method allows detection and identification of possible pathogens and spoilage bacteria in parallel. Strain-level analysis and functional gene analysis, such as identification of toxin genes, were also performed. This approach has the potential to be of great value with respect to the detection of spore-forming bacteria and could allow a processor to make an informed decision surrounding process changes to reduce the risk of spore contamination.

Dataset Information

Datasets generated by shotgun sequencing of metagenomic libraries of the guajataca water reservoir.

Publications

Datasets generated by shotgun sequencing of metagenomic libraries of the guajataca water reservoir.

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