Shotgun metagenomic sequencing based microbial diversity assessment of Lasundra hot spring, India

Introduction: We have shown that gut microbial diversity is associated with hypertension in the Coronary Artery Risk Development in Young Adults (CARDIA) Study. Animal models have documented gut microbial effects on adiposity, a known risk factor for hypertension. The extent to which adiposity may mediate the association between the gut microbiome and hypertension has not been studied. Hypothesis: We hypothesize that adiposity is a mediator of the association between gut microbial diversity and hypertension. Methods: We analyzed data from the CARDIA Study (480 participants). Shotgun metagenomic sequencing was performed on DNA extracted from stool samples collected at the Year 30 exam (2015-2016). Taxonomic classification of sequenced reads was performed using Kraken2. Within-person gut microbial diversity was assessed at the genus level using the Shannon Diversity Index and richness (number of distinct genera); lower values indicate less diversity. Hypertension was defined as systolic BP ≥140, diastolic BP ≥90 mm Hg, or taking antihypertensive medication. We performed mediation analyses to quantify the percentage of the total estimated effect of gut microbial diversity on hypertension that is mediated by adiposity as assessed using body mass index (BMI). Results: Mean age of the participants was 55.1 (3.4) years, 47% were African American, and 53% were female. In multivariable-adjusted mediation analysis, BMI explained on average 26-34% of the association between gut microbiota diversity and hypertension (Table). Results were robust to adjustment for sociodemographic variables (Model 2) and health behaviors (Model 3). Conclusions: Approximately one-third of the total effect of gut microbial diversity on hypertension is mediated through adiposity.

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Microbial diversity of a full-scale UASB reactor applied to poultry slaughterhouse wastewater treatment: integration of 16S rRNA gene amplicon and shotgun metagenomic sequencing

MicrobiologyOpen ◽

10.1002/mbo3.443 ◽

2017 ◽

Vol 6 (3) ◽

pp. e00443 ◽

Cited By ~ 17

Author(s):

Tiago Palladino Delforno ◽

Gileno Vieira Lacerda Júnior ◽

Melline F. Noronha ◽

Isabel K. Sakamoto ◽

Maria Bernadete A. Varesche ◽

...

Keyword(s):

Wastewater Treatment ◽

16S Rrna ◽

16S Rrna Gene ◽

Microbial Diversity ◽

Full Scale ◽

Uasb Reactor ◽

Rrna Gene ◽

Metagenomic Sequencing ◽

Shotgun Metagenomic Sequencing ◽

Treatment Integration

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Loss of microbial diversity and pathogen domination of the gut microbiota in critically ill patients

10.1101/582494 ◽

2019 ◽

Cited By ~ 1

Author(s):

Anuradha Ravi ◽

Fenella D Halstead ◽

Amy Bamford ◽

Anna Casey ◽

Nicholas M. Thomson ◽

...

Keyword(s):

Gut Microbiota ◽

Microbial Diversity ◽

Patient Specific ◽

Metagenomic Sequencing ◽

Icu Patients ◽

Adult Intensive Care Unit ◽

Shotgun Metagenomic Sequencing ◽

Health And Disease ◽

Genome Analyses ◽

Phylogenetic Profiling

AbstractBackgroundFor long-stay patients on the adult intensive care unit, the gut microbiota plays a key role in determining the balance between health and disease. However, it remains unclear which ICU patients might benefit from interventions targeting the gut microbiota or the pathogens therein.MethodsWe undertook a prospective observational study of twenty-four ICU patients, in which serial faecal samples were subjected to shotgun metagenomic sequencing, phylogenetic profiling and microbial genome analyses.ResultsTwo-thirds of patients experienced a marked drop in gut microbial diversity (to an inverse Simpson’s index of <4) at some stage during their stay in ICU, often accompanied by absence or loss of beneficial commensal bacteria. Intravenous administration of the broad-spectrum antimicrobial agent meropenem was significantly associated with loss of gut microbial diversity, but administration of other antibiotics, including piperacillin-tazobactam, failed to trigger statistically detectable changes in microbial diversity. In three quarters of ICU patients, we documented episodes of gut domination by pathogenic strains, with evidence of cryptic nosocomial transmission ofEnterococcus faecium. In some patients we also saw domination of the gut microbiota by commensal organisms, such asMethanobrevibacter smithii.ConclusionsOur results support a role for metagenomic surveillance of the gut microbiota and pave the way for patient-specific interventions that maintain or restore gut microbial diversity in the ICU.

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Deciphering the microbiota of Tuwa hot spring, India using shotgun metagenomic sequencing approach

Genomics Data ◽

10.1016/j.gdata.2015.04.014 ◽

2015 ◽

Vol 4 ◽

pp. 153-155 ◽

Cited By ~ 20

Author(s):

Amitsinh Mangrola ◽

Pravin Dudhagara ◽

Prakash Koringa ◽

C.G. Joshi ◽

Mansi Parmar ◽

...

Keyword(s):

Hot Spring ◽

Metagenomic Sequencing ◽

Shotgun Metagenomic Sequencing

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

Microorganisms ◽

10.3390/microorganisms9040707 ◽

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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Discriminating between JCPyV and BKPyV in Urinary Virome Data Sets

Viruses ◽

10.3390/v13061041 ◽

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.

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Microbial Diversity of Terrestrial Geothermal Springs in Armenia and Nagorno-Karabakh: A Review

Microorganisms ◽

10.3390/microorganisms9071473 ◽

2021 ◽

Vol 9 (7) ◽

pp. 1473

Author(s):

Ani Saghatelyan ◽

Armine Margaryan ◽

Hovik Panosyan ◽

Nils-Kåre Birkeland

Keyword(s):

16S Rrna ◽

Microbial Diversity ◽

High Altitude ◽

Hot Springs ◽

Hot Spring ◽

Abiotic Factors ◽

Rrna Gene ◽

Geothermal Springs ◽

Bacterial Phyla ◽

Terrestrial Hot Springs

The microbial diversity of high-altitude geothermal springs has been recently assessed to explore their biotechnological potential. However, little is known regarding the microbiota of similar ecosystems located on the Armenian Highland. This review summarizes the known information on the microbiota of nine high-altitude mineralized geothermal springs (temperature range 25.8–70 °C and pH range 6.0–7.5) in Armenia and Nagorno-Karabakh. All these geothermal springs are at altitudes ranging from 960–2090 m above sea level and are located on the Alpide (Alpine–Himalayan) orogenic belt, a seismically active region. A mixed-cation mixed-anion composition, with total mineralization of 0.5 mg/L, has been identified for these thermal springs. The taxonomic diversity of hot spring microbiomes has been examined using culture-independent approaches, including denaturing gradient gel electrophoresis (DGGE), 16S rRNA gene library construction, 454 pyrosequencing, and Illumina HiSeq. The bacterial phyla Proteobacteria, Bacteroidetes, Cyanobacteria, and Firmicutes are the predominant life forms in the studied springs. Archaea mainly include the phyla Euryarchaeota, Crenarchaeota, and Thaumarchaeota, and comprise less than 1% of the prokaryotic community. Comparison of microbial diversity in springs from Karvachar with that described for other terrestrial hot springs revealed that Proteobacteria, Bacteroidetes, Actinobacteria, and Deinococcus–Thermus are the common bacterial groups in terrestrial hot springs. Contemporaneously, specific bacterial and archaeal taxa were observed in different springs. Evaluation of the carbon, sulfur, and nitrogen metabolism in these hot spring communities has revealed diversity in terms of metabolic activity. Temperature seems to be an important factor in shaping the microbial communities of these springs. Overall, the diversity and richness of the microbiota are negatively affected by increasing temperature. Other abiotic factors, including pH, mineralization, and geological history, also impact the structure and function of the microbial community. More than 130 bacterial and archaeal strains (Bacillus, Geobacillus, Parageobacillus, Anoxybacillus, Paenibacillus, Brevibacillus Aeribacillus, Ureibacillus, Thermoactinomyces, Sporosarcina, Thermus, Rhodobacter, Thiospirillum, Thiocapsa, Rhodopseudomonas, Methylocaldum, Desulfomicrobium, Desulfovibrio, Treponema, Arcobacter, Nitropspira, and Methanoculleus) have been reported, some of which may be representative of novel species (sharing 91–97% sequence identity with their closest matches in GenBank) and producers of thermozymes and biomolecules with potential biotechnological applications. Whole-genome shotgun sequencing of T. scotoductus K1, as well as of the potentially new Treponema sp. J25 and Anoxybacillus sp. K1, were performed. Most of the phyla identified by 16S rRNA were also identified using metagenomic approaches. Detailed characterization of thermophilic isolates indicate the potential of the studied springs as a source of biotechnologically valuable microbes and biomolecules.

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Physiological status and microbial diversity assessment of microbial mats: The signature lipid biomarker approach

Ophelia ◽

10.1080/00785236.2004.10410224 ◽

2004 ◽

Vol 58 (3) ◽

pp. 165-173 ◽

Cited By ~ 4

Author(s):

Laura Villanueva ◽

Antoni Navarrete ◽

Jordi Urmeneta ◽

David C. White ◽

Ricardo Guerrero

Keyword(s):

Microbial Diversity ◽

Microbial Mats ◽

Physiological Status ◽

Lipid Biomarker ◽

Diversity Assessment

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

Journal of Clinical Microbiology ◽

10.1128/jcm.01182-18 ◽

2018 ◽

Vol 57 (2) ◽

Cited By ~ 8

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.

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Human gut microbial communities dictate efficacy of anti-PD-1 therapy in a humanized microbiome mouse model of glioma

Neuro-Oncology Advances ◽

10.1093/noajnl/vdab023 ◽

2021 ◽

Vol 3 (1) ◽

Author(s):

Kory J Dees ◽

Hyunmin Koo ◽

J Fraser Humphreys ◽

Joseph A Hakim ◽

David K Crossman ◽

...

Keyword(s):

Mouse Model ◽

Microbial Communities ◽

Metagenomic Sequencing ◽

Sequencing Data ◽

Microbial Composition ◽

Healthy Human ◽

Fecal Transplantation ◽

Host Interaction ◽

Shotgun Metagenomic Sequencing ◽

Mouse Lines

Abstract Background Although immunotherapy works well in glioblastoma (GBM) preclinical mouse models, the therapy has not demonstrated efficacy in humans. To address this anomaly, we developed a novel humanized microbiome (HuM) model to study the response to immunotherapy in a preclinical mouse model of GBM. Methods We used 5 healthy human donors for fecal transplantation of gnotobiotic mice. After the transplanted microbiomes stabilized, the mice were bred to generate 5 independent humanized mouse lines (HuM1-HuM5). Results Analysis of shotgun metagenomic sequencing data from fecal samples revealed a unique microbiome with significant differences in diversity and microbial composition among HuM1-HuM5 lines. All HuM mouse lines were susceptible to GBM transplantation, and exhibited similar median survival ranging from 19 to 26 days. Interestingly, we found that HuM lines responded differently to the immune checkpoint inhibitor anti-PD-1. Specifically, we demonstrate that HuM1, HuM4, and HuM5 mice are nonresponders to anti-PD-1, while HuM2 and HuM3 mice are responsive to anti-PD-1 and displayed significantly increased survival compared to isotype controls. Bray-Curtis cluster analysis of the 5 HuM gut microbial communities revealed that responders HuM2 and HuM3 were closely related, and detailed taxonomic comparison analysis revealed that Bacteroides cellulosilyticus was commonly found in HuM2 and HuM3 with high abundances. Conclusions The results of our study establish the utility of humanized microbiome mice as avatars to delineate features of the host interaction with gut microbial communities needed for effective immunotherapy against GBM.

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