Metagenomic analysis reveals the response of microbial community in river sediment to accidental antimony contamination

1AbstractBackgroundAntimicrobial resistance is a significant global threat, posing major public health risks and economic costs to healthcare systems. Bacterial cultures are typically used to diagnose healthcare-acquired infections (HAI); however, culture-dependent methods provide limited presence/absence information and are not applicable to all pathogens. Next generation sequencing (NGS) has the capacity to detect a wide variety of pathogens, virulence elements, and antimicrobial resistance (AMR) signatures in healthcare settings without the need for culturing, but few research studies have explored how NGS could be used to detect viable human pathogen transmission events under different HAI-relevant scenarios.MethodsThe objective of this project was to assess the capability of NGS-based methods to detect the direct and indirect transmission of high priority healthcare-related pathogens. DNA was extracted and sequenced from a previously published study exploring pathogen transfer with simulated skin containing background microorganisms, which allowed for complementary culture and metagenomic analysis comparisons. RNA was also isolated from an additional set of samples to evaluate metatranscriptomic analysis methods at different concentrations.ResultsUsing various analysis methods and custom reference databases, both pathogenic and non-pathogenic members of the microbial community were taxonomically identified. Virulence and AMR genes known to reside within the community were also routinely detected. Ultimately, pathogen abundance within the overall microbial community played the largest role in successful taxonomic classification and gene identification.ConclusionsThese results illustrate the utility of metagenomic analysis in clinical settings or for epidemiological studies, but also highlight the limits associated with the detection and characterization of pathogens at low abundance in a microbial community.

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StrainPro – a highly accurate Metagenomic strain-level profiling tool

10.1101/807149 ◽

2019 ◽

Author(s):

Hsin-Nan Lin ◽

Yaw-Ling Lin ◽

Wen-Lian Hsu

Keyword(s):

Microbial Community ◽

Relative Abundance ◽

Taxonomic Diversity ◽

Evaluation Study ◽

Taxonomic Composition ◽

Strain Level ◽

Metagenomic Analysis ◽

Reference Database ◽

Analysis Tool ◽

Analysis Tools

ABSTRACTCharacterizing the taxonomic diversity of a microbial community is very important to understand the roles of microorganisms. Next generation sequencing (NGS) provides great potential for investigation of a microbial community and leads to Metagenomic studies. NGS generates DNA fragment sequences directly from microorganism samples, and it requires analysis tools to identify microbial species (or taxonomic composition) and estimate their relative abundance in the studied community. However, only a few tools could achieve strain-level identification and most tools estimate the microbial abundances simply according to the read counts. An evaluation study on metagenomic analysis tools concludes that the predicted abundance differed significantly from the true abundance. In this study, we present StrainPro, a novel metagenomic analysis tool which is highly accurate both at characterizing microorganisms at strain-level and estimating their relative abundances. A unique feature of StrainPro is it identifies representative sequence segments from reference genomes. We generate three simulated datasets using known strain sequences and another three simulated datasets using unknown strain sequences. We compare the performance of StrainPro with seven existing tools. The results show that StrainPro not only identifies metagenomes with high precision and recall, but it is also highly robust even when the metagenomes are not included in the reference database. Moreover, StrainPro estimates the relative abundance with high accuracy. We demonstrate that there is a strong positive linear relationship between observed and predicted abundances.

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Biodegradation and microbial community changes upon shrimp shell wastes amended in mangrove river sediment

Journal of Environmental Science and Health Part B ◽

10.1080/03601231003800305 ◽

2010 ◽

Vol 45 (5) ◽

pp. 473-477 ◽

Cited By ~ 3

Author(s):

Wen-Ching Chen ◽

Wan-Nine Tseng ◽

Jia-Lin Hsieh ◽

Yei-Shung Wang ◽

San-Lang Wang

Keyword(s):

Microbial Community ◽

River Sediment ◽

Shrimp Shell ◽

Community Changes

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Thermophilic Alkaline Fermentation Followed by Mesophilic Anaerobic Digestion for Efficient Hydrogen and Methane Production from Waste-Activated Sludge: Dynamics of Bacterial Pathogens as Revealed by the Combination of Metagenomic and Quantitative PCR Analyses

Applied and Environmental Microbiology ◽

10.1128/aem.02632-17 ◽

2018 ◽

Vol 84 (6) ◽

Cited By ~ 5

Author(s):

Jingjing Wan ◽

Yuhang Jing ◽

Yue Rao ◽

Shicheng Zhang ◽

Gang Luo

Keyword(s):

Microbial Community ◽

Anaerobic Digestion ◽

Activated Sludge ◽

Quantitative Pcr ◽

Methane Production ◽

Bacterial Pathogens ◽

Methane Yield ◽

Metagenomic Analysis ◽

Waste Activated Sludge ◽

Hydrogen Yield

ABSTRACT Thermophilic alkaline fermentation followed by mesophilic anaerobic digestion (TM) for hydrogen and methane production from waste-activated sludge (WAS) was investigated. The TM process was also compared to a process with mesophilic alkaline fermentation followed by a mesophilic anaerobic digestion (MM) and one-stage mesophilic anaerobic digestion (M) process. The results showed that both hydrogen yield (74.5 ml H 2 /g volatile solids [VS]) and methane yield (150.7 ml CH 4 /g VS) in the TM process were higher than those (6.7 ml H 2 /g VS and 127.8 ml CH 4 /g VS, respectively) in the MM process. The lowest methane yield (101.2 ml CH 4 /g VS) was obtained with the M process. Taxonomic results obtained from metagenomic analysis showed that different microbial community compositions were established in the hydrogen reactors of the TM and MM processes, which also significantly changed the microbial community compositions in the following methane reactors compared to that with the M process. The dynamics of bacterial pathogens were also evaluated. For the TM process, the reduced diversity and total abundance of bacterial pathogens in WAS were observed in the hydrogen reactor and were further reduced in the methane reactor, as revealed by metagenomic analysis. The results also showed not all bacterial pathogens were reduced in the reactors. For example, Collinsella aerofaciens was enriched in the hydrogen reactor, which was also confirmed by quantitative PCR (qPCR) analysis. The study further showed that qPCR was more sensitive for detecting bacterial pathogens than metagenomic analysis. Although there were some differences in the relative abundances of bacterial pathogens calculated by metagenomic and qPCR approaches, both approaches demonstrated that the TM process was more efficient for the removal of bacterial pathogens than the MM and M processes. IMPORTANCE This study developed an efficient process for bioenergy (H 2 and CH 4 ) production from WAS and elucidates the dynamics of bacterial pathogens in the process, which is important for the utilization and safe application of WAS. The study also made an attempt to combine metagenomic and qPCR analyses to reveal the dynamics of bacterial pathogens in anaerobic processes, which could overcome the limitations of each method and provide new insights regarding bacterial pathogens in environmental samples.

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Geothermal Gases Shape the Microbial Community of the Volcanic Soil of Pantelleria, Italy

mSystems ◽

10.1128/msystems.00517-20 ◽

2020 ◽

Vol 5 (6) ◽

Author(s):

Nunzia Picone ◽

Carmen Hogendoorn ◽

Geert Cremers ◽

Lianna Poghosyan ◽

Arjan Pol ◽

...

Keyword(s):

Microbial Community ◽

Greenhouse Gas ◽

Relative Abundance ◽

Hot Spots ◽

Microbial Community Composition ◽

Metagenomic Analysis ◽

Volcanic Soil ◽

Metabolic Potential ◽

Gas Emissions ◽

Geothermal Activity

ABSTRACT Volcanic and geothermal environments are characterized by low pH, high temperatures, and gas emissions consisting of mainly CO2 and varied CH4, H2S, and H2 contents which allow the formation of chemolithoautotrophic microbial communities. To determine the link between the emitted gases and the microbial community composition, geochemical and metagenomic analysis were performed. Soil samples of the geothermic region Favara Grande (Pantelleria, Italy) were taken at various depths (1 to 50 cm). Analysis of the gas composition revealed that CH4 and H2 have the potential to serve as the driving forces for the microbial community. Our metagenomic analysis revealed a high relative abundance of Bacteria in the top layer (1 to 10 cm), but the relative abundance of Archaea increased with depth from 32% to 70%. In particular, a putative hydrogenotrophic methanogenic archaeon, related to Methanocella conradii, appeared to have a high relative abundance (63%) in deeper layers. A variety of [NiFe]-hydrogenase genes were detected, showing that H2 was an important electron donor for microaerobic microorganisms in the upper layers. Furthermore, the bacterial population included verrucomicrobial and proteobacterial methanotrophs, the former showing an up to 7.8 times higher relative abundance. Analysis of the metabolic potential of this microbial community showed a clear capacity to oxidize CH4 aerobically, as several genes for distinct particulate methane monooxygenases and lanthanide-dependent methanol dehydrogenases (XoxF-type) were retrieved. Analysis of the CO2 fixation pathways showed the presence of the Calvin-Benson-Bassham cycle, the Wood-Ljungdahl pathway, and the (reverse) tricarboxylic acid (TCA) cycle, the latter being the most represented carbon fixation pathway. This study indicates that the methane emissions in the Favara Grande might be a combination of geothermal activity and biological processes and further provides insights into the diversity of the microbial population thriving on CH4 and H2. IMPORTANCE The Favara Grande nature reserve on the volcanic island of Pantelleria (Italy) is known for its geothermal gas emissions and high soil temperatures. These volcanic soil ecosystems represent “hot spots” of greenhouse gas emissions. The unique community might be shaped by the hostile conditions in the ecosystem, and it is involved in the cycling of elements such as carbon, hydrogen, sulfur, and nitrogen. Our metagenome study revealed that most of the microorganisms in this extreme environment are only distantly related to cultivated bacteria. The results obtained profoundly increased the understanding of these natural hot spots of greenhouse gas production/degradation and will help to enrich and isolate the microbial key players. After isolation, it will become possible to unravel the molecular mechanisms by which they adapt to extreme (thermo/acidophilic) conditions, and this may lead to new green enzymatic catalysts and technologies for industry.

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