scholarly journals Metagenomic Insights into The Diversity and Functions of Microbial Assemblages in Tasik Kenyir Ecosystem

2017 ◽  
Author(s):  
Mohd Ezhar Mohd Noor ◽  
Sharifah Noor Emilia Syed Jamil Fadaak ◽  
Mohd Noor Mat Isa ◽  
Mohd Faizal Abu Bakar ◽  
Muhd Danish-Daniel Abdullah
Keyword(s):  
Carbon Fixation ◽  
Dna Isolation ◽  
Metagenomic Data ◽  
Data Sets ◽  
Metagenomic Sequencing ◽  
Microbial Species ◽  
Disturbed Area ◽  
Shotgun Metagenomic Sequencing ◽  
Pristine Area ◽  
Disturbed Areas

AbstractTropical freshwater lake such as Tasik Kenyir are underrepresented among the growing number of environmental metagenomic data sets. In Tasik Kenyir, water from two different sites, pristine and disturbed areas were sampled. After the filtration process, genomic DNA from both sites were extracted using Meta-G-nome DNA isolation kit and shotgun metagenomic sequencing was carried out on Illumina HiSeq2500 Desktop Sequencer (Illumina, Inc.). Raw data were then trimmed and assembled using Metagenomic Assembler program, MetaVelvet. Data analysis was carried out using software Blast2GO (BioBam Bioinformatic S.L). The total number of sequence reads was 189,158 from TKS1.5m (disturbed area) and 246,577 from TKS2.5m (pristine area).The results indicate that sequence reads of microbial species were presence at disturbed area near the aquaculture zone was lower than the sequence reads of microbial species were presence at pristine area. When compared to archaea, both samples were dominated by bacteria (more than 90%) suggesting that bacteria are absolutely dominant in the prokaryotic communities in the freshwater samples. The lake appears to contain a mixture of autotrophs and heterotrophs capable of performing main biogeochemical cycles like nitrogen fixation byKlebsiellasp for TKS1.5m andPontibactersp. for TKS2.5m. and carbon fixation by heterotrophicAlcaligenessp. andShewanella decolorationiin TKS1.5m, and byPantoeasp. in TKS2.5m. Present study will advance our understanding of the importance of freshwater microbial communities for ecosystem and human health.

scholarly journals Discriminating between JCPyV and BKPyV in Urinary Virome Data Sets

Viruses ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1041
Author(s):  
Rita Mormando ◽  
Alan J. Wolfe ◽  
Catherine Putonti
Keyword(s):  
Jc Virus ◽  
Sequence Similarity ◽  
Bk Virus ◽  
Data Sets ◽  
Metagenomic Sequencing ◽  
Significant Sequence Similarity ◽  
Sequence Identity ◽  
Shotgun Metagenomic Sequencing ◽  
Urinary Microbiome ◽  
Six Genes

Polyomaviruses are abundant in the human body. The polyomaviruses JC virus (JCPyV) and BK virus (BKPyV) are common viruses in the human urinary tract. Prior studies have estimated that JCPyV infects between 20 and 80% of adults and that BKPyV infects between 65 and 90% of individuals by age 10. However, these two viruses encode for the same six genes and share 75% nucleotide sequence identity across their genomes. While prior urinary virome studies have repeatedly reported the presence of JCPyV, we were interested in seeing how JCPyV prevalence compares to BKPyV. We retrieved all publicly available shotgun metagenomic sequencing reads from urinary microbiome and virome studies (n = 165). While one third of the data sets produced hits to JCPyV, upon further investigation were we able to determine that the majority of these were in fact BKPyV. This distinction was made by specifically mining for JCPyV and BKPyV and considering uniform coverage across the genome. This approach provides confidence in taxon calls, even between closely related viruses with significant sequence similarity.

scholarly journals Evaluation of the CosmosID Bioinformatics Platform for Prosthetic Joint-Associated Sonicate Fluid Shotgun Metagenomic Data Analysis

2018 ◽  
Vol 57 (2) ◽  
Author(s):  
Qun Yan ◽  
Yu Mi Wi ◽  
Matthew J. Thoendel ◽  
Yash S. Raval ◽  
Kerryl E. Greenwood-Quaintance ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Metagenomic Data ◽  
Metagenomic Sequencing ◽  
Antibacterial Resistance ◽  
Sequencing Data ◽  
Bacterial Detection ◽  
Shotgun Metagenomic Sequencing ◽  
Prosthetic Joint ◽  
Validation Set ◽  
Fluid Culture

ABSTRACT We previously demonstrated that shotgun metagenomic sequencing can detect bacteria in sonicate fluid, providing a diagnosis of prosthetic joint infection (PJI). A limitation of the approach that we used is that data analysis was time-consuming and specialized bioinformatics expertise was required, both of which are barriers to routine clinical use. Fortunately, automated commercial analytic platforms that can interpret shotgun metagenomic data are emerging. In this study, we evaluated the CosmosID bioinformatics platform using shotgun metagenomic sequencing data derived from 408 sonicate fluid samples from our prior study with the goal of evaluating the platform vis-à-vis bacterial detection and antibiotic resistance gene detection for predicting staphylococcal antibacterial susceptibility. Samples were divided into a derivation set and a validation set, each consisting of 204 samples; results from the derivation set were used to establish cutoffs, which were then tested in the validation set for identifying pathogens and predicting staphylococcal antibacterial resistance. Metagenomic analysis detected bacteria in 94.8% (109/115) of sonicate fluid culture-positive PJIs and 37.8% (37/98) of sonicate fluid culture-negative PJIs. Metagenomic analysis showed sensitivities ranging from 65.7 to 85.0% for predicting staphylococcal antibacterial resistance. In conclusion, the CosmosID platform has the potential to provide fast, reliable bacterial detection and identification from metagenomic shotgun sequencing data derived from sonicate fluid for the diagnosis of PJI. Strategies for metagenomic detection of antibiotic resistance genes for predicting staphylococcal antibacterial resistance need further development.

Bacteria Responsible for Nitrate-dependent Antimonite Oxidation in Antimony-contaminated Paddy Soil Revealed by the Combination of DNA-SIP and Metagenomics

2020 ◽  
Author(s):  
Miaomiao Zhang ◽  
Zhe Li ◽  
Max M. Häggblom ◽  
Lily Young ◽  
Fangbai Li ◽  
...  
Keyword(s):  
Paddy Soil ◽  
Carbon Fixation ◽  
Current Knowledge ◽  
Stable Isotope Probing ◽  
Metagenomic Sequencing ◽  
Proof Of Concept ◽  
Ecological Role ◽  
Shotgun Metagenomic Sequencing ◽  
Anoxic Environments ◽  
Contaminated Paddy Soil

Abstract Background: Antimonite (Sb(III)) oxidation (SbO) can decrease the toxicity of antimony (Sb) and its uptake into plants (e.g., rice), thus serving an ecological role in bioremediation of Sb contamination. In some anoxic environments, Sb(III) can be oxidized coupled with nitrate as the electron acceptor. Here we investigate the potential for nitrate-dependent SbO in Sb contaminated rice paddies and identify nitrate-dependent Sb(III)-oxidizing bacteria (SbOB) using stable isotope probing (SIP) coupled with amplicon and shotgun metagenomic sequencing.Results: Anaerobic SbO was exclusively observed in the paddy soil amended with both Sb(III) and NO3-, whereas no apparent SbO was detected in the soil amended with Sb(III) only. The increasing abundance of the arsenite oxidase (aioA) gene suggests that nitrate-dependent SbO was catalysed by microorganisms harbouring the aioA gene. After 60-day DNA-SIP incubation, obvious shift in the aioA gene to heavy DNA fractions only in the treatment amended with 13C-NaHCO3, Sb(III) and NO3- suggested the incorporation of 13C by nitrate-dependent SbOB. Accordingly, DNA-SIP identified a number of putative nitrate-dependent SbOB in the paddy soil, including Azoarcus, Azospira and Chelativorans. Metagenomic analysis further revealed that they contained aioA gene and genes involved in denitrification and carbon fixation, supporting their capability for nitrate-dependent SbO.Conclusions: These observations in this study suggested the occurrence of nitrate-dependent SbO in paddy soils. A number of putative nitrate-dependent SbOB (i.e., Azoarcus, Azospira and Chelativorans) were reported here, which expands our current knowledge regarding the diversity of nitrate-dependent SbOB. In addition, this study provides a proof of concept using DNA-SIP to identify nitrate-dependent SbOB.

What Is Metagenomics Teaching Us, and What Is Missed?

2020 ◽  
Vol 74 (1) ◽  
pp. 117-135 ◽  
Author(s):  
Felicia N. New ◽  
Ilana L. Brito
Keyword(s):  
Environmental Sustainability ◽  
Metagenomic Data ◽  
Model Organisms ◽  
Metagenomic Sequencing ◽  
Shotgun Metagenomic Sequencing ◽  
Metagenome Assembly ◽  
Environmental Bacteria ◽  
And Function ◽  
Analytical Tools ◽  
Technological Platforms

Shotgun metagenomic sequencing has revolutionized our ability to detect and characterize the diversity and function of complex microbial communities. In this review, we highlight the benefits of using metagenomics as well as the breadth of conclusions that can be made using currently available analytical tools, such as greater resolution of species and strains across phyla and functional content, while highlighting challenges of metagenomic data analysis. Major challenges remain in annotating function, given the dearth of functional databases for environmental bacteria compared to model organisms, and the technical difficulties of metagenome assembly and phasing in heterogeneous environmental samples. In the future, improvements and innovation in technology and methodology will lead to lowered costs. Data integration using multiple technological platforms will lead to a better understanding of how to harness metagenomes. Subsequently, we will be able not only to characterize complex microbiomes but also to manipulate communities to achieve prosperous outcomes for health, agriculture, and environmental sustainability.

scholarly journals MetaLAFFA: a flexible, end-to-end, distributed computing-compatible metagenomic functional annotation pipeline

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Alexander Eng ◽  
Adrian J. Verster ◽  
Elhanan Borenstein
Keyword(s):  
Distributed Computing ◽  
Functional Annotation ◽  
Sequence Data ◽  
Metagenomic Data ◽  
Metagenomic Sequencing ◽  
Distributed Computing Systems ◽  
Annotation Pipeline ◽  
Shotgun Metagenomic Sequencing ◽  
End To End ◽  
Functional Profiles

Abstract Background Microbial communities have become an important subject of research across multiple disciplines in recent years. These communities are often examined via shotgun metagenomic sequencing, a technology which can offer unique insights into the genomic content of a microbial community. Functional annotation of shotgun metagenomic data has become an increasingly popular method for identifying the aggregate functional capacities encoded by the community’s constituent microbes. Currently available metagenomic functional annotation pipelines, however, suffer from several shortcomings, including limited pipeline customization options, lack of standard raw sequence data pre-processing, and insufficient capabilities for integration with distributed computing systems. Results Here we introduce MetaLAFFA, a functional annotation pipeline designed to take unfiltered shotgun metagenomic data as input and generate functional profiles. MetaLAFFA is implemented as a Snakemake pipeline, which enables convenient integration with distributed computing clusters, allowing users to take full advantage of available computing resources. Default pipeline settings allow new users to run MetaLAFFA according to common practices while a Python module-based configuration system provides advanced users with a flexible interface for pipeline customization. MetaLAFFA also generates summary statistics for each step in the pipeline so that users can better understand pre-processing and annotation quality. Conclusions MetaLAFFA is a new end-to-end metagenomic functional annotation pipeline with distributed computing compatibility and flexible customization options. MetaLAFFA source code is available at https://github.com/borenstein-lab/MetaLAFFA and can be installed via Conda as described in the accompanying documentation.

scholarly journals Performance evaluation of a new custom, multi-component DNA isolation method optimized for use in shotgun metagenomic sequencing-based aerosol microbiome research

2019 ◽  
Author(s):  
Kari Oline Bøifot ◽  
Jostein Gohli ◽  
Line Victoria Moen ◽  
Marius Dybwad
Keyword(s):  
Microbial Community ◽  
Real World ◽  
Dna Isolation ◽  
New Method ◽  
Metagenomic Sequencing ◽  
Isolation Method ◽  
Air Samples ◽  
Shotgun Metagenomic Sequencing ◽  
Isolation Methods ◽  
Microbiome Research

ABSTRACTBackgroundAerosol microbiome research advances our understanding of bioaerosols, including how airborne microorganisms affect our health and surrounding environment. Traditional microbiological/molecular methods are commonly used to study bioaerosols, but do not allow for generic, unbiased microbiome profiling. Recent studies have adopted shotgun metagenomic sequencing (SMS) to address this issue. However, SMS requires relatively large DNA inputs, which are challenging when studying low biomass air environments, and puts high requirements on air sampling, sample processing and DNA isolation protocols. Previous SMS studies have consequently adopted various mitigation strategies, including long-duration sampling, sample pooling, and whole genome amplification, each associated with some inherent drawbacks/limitations.ResultsHere, we demonstrate a new custom, multi-component DNA isolation method optimized for SMS-based aerosol microbiome research. The method achieves improved DNA yields from filter-collected air samples by isolating DNA from the entire filter extract, and ensures unbiased microbiome representation by combining chemical, enzymatic and mechanical lysis. Benchmarking against two state-of-the-art DNA isolation methods was performed with a mock microbial community and real-world subway air samples. All methods demonstrated similar performance regarding DNA yield and community representation with the mock community. However, with subway air samples, the new method obtained drastically improved DNA yields, while SMS revealed that the new method reported higher diversity and gave better taxonomic coverage. The new method involves intermediate filter extract separation into a pellet and supernatant fraction. Using subway air samples, we demonstrate that supernatant inclusion results in improved DNA yields. Furthermore, SMS of pellet and supernatant fractions revealed overall similar taxonomic composition but also identified differences that could bias the microbiome profile, emphasizing the importance of processing the entire filter extract.ConclusionsBy demonstrating and benchmarking a new DNA isolation method optimized for SMS-based aerosol microbiome research with both a mock microbial community and real-world air samples, this study contributes to improved selection, harmonization, and standardization of DNA isolation methods. Our findings highlight the importance of ensuring end-to-end sample integrity and using methods with well-defined performance characteristics. Taken together, the demonstrated performance characteristics suggest the new method could be used to improve the quality of SMS-based aerosol microbiome research in low biomass air environments.

scholarly journals Evaluation of the effects of library preparation procedure and sample characteristics on the accuracy of metagenomic profiles

2021 ◽  
Author(s):  
Christopher Gaulke ◽  
Emily R Schmeltzer ◽  
Mark Dasenko ◽  
Brett M Tyler ◽  
Rebecca Vega Thurber ◽  
...  
Keyword(s):  
Microbial Community ◽  
Cost Effective ◽  
Low Complexity ◽  
Careful Consideration ◽  
Metagenomic Data ◽  
Metagenomic Sequencing ◽  
Library Preparation ◽  
Dna Amount ◽  
Preparation Methods ◽  
Shotgun Metagenomic Sequencing

Shotgun metagenomic sequencing has transformed our understanding of microbial community ecology. However, preparing metagenomic libraries for high-throughput DNA sequencing remains a costly, labor-intensive, and time-consuming procedure, which in turn limits the utility of metagenomes. Several library preparation procedures have recently been developed to offset these costs, but it is unclear how these newer procedures compare to current standards in the field. In particular, it is not clear if all such procedures perform equally well across different types of microbial communities, or if features of the biological samples being processed (e.g., DNA amount) impact the accuracy of the approach. To address these questions, we assessed how five different shotgun DNA sequence library preparation methods, including the commonly used Nextera® Flex kit, perform when applied to metagenomic DNA. We measured each method's ability to produce metagenomic data that accurately represents the underlying taxonomic and genetic diversity of the community. We performed these analyses across a range of microbial community types (e.g., soil, coral-associated, mouse-gut-associated) and input DNA amounts. We find that the type of community and amount of input DNA influence each method’s performance, indicating that careful consideration may be needed when selecting between methods, especially for low complexity communities. However, cost-effective preparation methods we assessed are generally comparable to the current gold standard Nextera® DNA Flex kit for high-complexity communities. Overall, the results from this analysis will help expand and even facilitate access to metagenomic approaches in future studies.

scholarly journals Metaviral SPAdes: assembly of viruses from metagenomic data

2020 ◽  
Vol 36 (14) ◽  
pp. 4126-4129 ◽  
Author(s):  
Dmitry Antipov ◽  
Mikhail Raiko ◽  
Alla Lapidus ◽  
Pavel A Pevzner
Keyword(s):  
Markov Models ◽  
State Of The Art ◽  
Supplementary Information ◽  
Metagenomic Data ◽  
Metagenomic Sequencing ◽  
Coverage Depth ◽  
Viral Genomes ◽  
Shotgun Metagenomic Sequencing ◽  
Bacterial Chromosomes ◽  
Metagenomic Assembly

Abstract Motivation Although the set of currently known viruses has been steadily expanding, only a tiny fraction of the Earth’s virome has been sequenced so far. Shotgun metagenomic sequencing provides an opportunity to reveal novel viruses but faces the computational challenge of identifying viral genomes that are often difficult to detect in metagenomic assemblies. Results We describe a MetaviralSPAdes tool for identifying viral genomes in metagenomic assembly graphs that is based on analyzing variations in the coverage depth between viruses and bacterial chromosomes. We benchmarked MetaviralSPAdes on diverse metagenomic datasets, verified our predictions using a set of virus-specific Hidden Markov Models and demonstrated that it improves on the state-of-the-art viral identification pipelines. Availability and implementation Metaviral SPAdes includes ViralAssembly, ViralVerify and ViralComplete modules that are available as standalone packages: https://github.com/ablab/spades/tree/metaviral_publication, https://github.com/ablab/viralVerify/ and https://github.com/ablab/viralComplete/. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Culture-Independent Genotyping, Virulence and Antimicrobial Resistance Gene Identification of Staphylococcus aureus from Orthopaedic Implant-Associated Infections

2021 ◽  
Vol 9 (4) ◽  
pp. 707
Author(s):  
J. Christopher Noone ◽  
Fabienne Antunes Ferreira ◽  
Hege Vangstein Aamot
Keyword(s):  
Staphylococcus Aureus ◽  
Antimicrobial Resistance ◽  
Resistance Genes ◽  
Virulence Gene ◽  
Orthopaedic Implant ◽  
Metagenomic Sequencing ◽  
Gene Detection ◽  
Shotgun Metagenomic Sequencing ◽  
Antimicrobial Resistance Genes ◽  
Culture Independent

Our culture-independent nanopore shotgun metagenomic sequencing protocol on biopsies has the potential for same-day diagnostics of orthopaedic implant-associated infections (OIAI). As OIAI are frequently caused by Staphylococcus aureus, we included S. aureus genotyping and virulence gene detection to exploit the protocol to its fullest. The aim was to evaluate S. aureus genotyping, virulence and antimicrobial resistance genes detection using the shotgun metagenomic sequencing protocol. This proof of concept study included six patients with S. aureus-associated OIAI at Akershus University Hospital, Norway. Five tissue biopsies from each patient were divided in two: (1) conventional microbiological diagnostics and genotyping, and whole genome sequencing (WGS) of S. aureus isolates; (2) shotgun metagenomic sequencing of DNA from the biopsies. Consensus sequences were analysed using spaTyper, MLST, VirulenceFinder, and ResFinder from the Center for Genomic Epidemiology (CGE). MLST was also compared using krocus. All spa-types, one CGE and four krocus MLST results matched Sanger sequencing results. Virulence gene detection matched between WGS and shotgun metagenomic sequencing. ResFinder results corresponded to resistance phenotype. S. aureus spa-typing, and identification of virulence and antimicrobial resistance genes are possible using our shotgun metagenomics protocol. MLST requires further optimization. The protocol has potential application to other species and infection types.

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