scholarly journals Metagenomic evidence for a polymicrobial signature of sepsis

2020 ◽  
Author(s):  
Cedric Chih Shen Tan ◽  
Mislav Acman ◽  
Lucy van Dorp ◽  
Francois Balloux
Keyword(s):  
Microbial Communities ◽  
High Performance ◽  
Metagenomic Data ◽  
Healthy Controls ◽  
Clinical Testing ◽  
Healthy Individuals ◽  
Significant Progress ◽  
Clinical Diagnostic ◽  
Boosted Tree ◽  
Host Component

AbstractOur understanding of the host component of sepsis has made significant progress. However, detailed study of the microorganisms causing sepsis, either as single pathogens or microbial assemblages, has received far less attention. Metagenomic data offer opportunities to characterise the microbial communities found in septic and healthy individuals. In this study we apply gradient-boosted tree classifiers and a novel computational decontamination technique built upon SHapley Additive exPlanations (SHAP) to identify microbial hallmarks which discriminate blood metagenomic samples of septic patients from that of healthy individuals. Classifiers had high performance when using the read assignments to microbial genera (AUROC = 0.995), including after removal of species ‘confirmed’ as the cause of sepsis through clinical testing (AUROC = 0.915). Models trained on single genera were inferior to those employing a polymicrobial model and we identified multiple co-occurring bacterial genera absent from healthy controls.ImportanceWhile prevailing diagnostic paradigms seek to identify single pathogens, our results point to the involvement of a polymicrobial community in sepsis. We demonstrate the importance of the microbial component in characterising sepsis, which may offer new biological insights into the aetiology of sepsis and allow the development of clinical diagnostic or even prognostic tools.

scholarly journals Metagenomic evidence for a polymicrobial signature of sepsis

2021 ◽  
Vol 7 (9) ◽  
Author(s):  
Cedric Chih Shen Tan ◽  
Mislav Acman ◽  
Lucy van Dorp ◽  
Francois Balloux
Keyword(s):  
Microbial Communities ◽  
High Performance ◽  
Operating Characteristic ◽  
Metagenomic Data ◽  
Healthy Controls ◽  
Clinical Testing ◽  
Healthy Individuals ◽  
Significant Progress ◽  
Boosted Tree ◽  
Host Component

Our understanding of the host component of sepsis has made significant progress. However, detailed study of the microorganisms causing sepsis, either as single pathogens or microbial assemblages, has received far less attention. Metagenomic data offer opportunities to characterize the microbial communities found in septic and healthy individuals. In this study we apply gradient-boosted tree classifiers and a novel computational decontamination technique built upon SHapley Additive exPlanations (SHAP) to identify microbial hallmarks which discriminate blood metagenomic samples of septic patients from that of healthy individuals. Classifiers had high performance when using the read assignments to microbial genera [area under the receiver operating characteristic (AUROC=0.995)], including after removal of species ‘culture-confirmed’ as the cause of sepsis through clinical testing (AUROC=0.915). Models trained on single genera were inferior to those employing a polymicrobial model and we identified multiple co-occurring bacterial genera absent from healthy controls. While prevailing diagnostic paradigms seek to identify single pathogens, our results point to the involvement of a polymicrobial community in sepsis. We demonstrate the importance of the microbial component in characterising sepsis, which may offer new biological insights into the aetiology of sepsis, and ultimately support the development of clinical diagnostic or even prognostic tools.

The decision-making levels of urine tetrasaccharide for the diagnosis of Pompe disease in the Turkish population

2020 ◽  
Vol 33 (3) ◽  
pp. 391-395 ◽  
Author(s):  
Erhan Canbay ◽  
Melisa Vural ◽  
Sema Kalkan Uçar ◽  
Ebru Demirel Sezer ◽  
Hatice Karasoy ◽  
...  
Keyword(s):  
Decision Making ◽  
Pompe Disease ◽  
High Performance ◽  
Late Onset ◽  
Turkish Population ◽  
Reference Intervals ◽  
Healthy Controls ◽  
Age Group ◽  
Healthy Individuals ◽  
First Year Of Life

AbstractBackgroundRecently, urinary excretion of the tetrasaccharide 6-α-D-glucopyranosyl-maltotriose (Glc4) has been proposed as a marker for the diagnosis and monitoring of Pompe disease (PD). We aimed to determine the reference intervals and reliable decision-making levels of urine tetrasaccharide concentrations for the diagnosis of infantile- and late-onset Pompe patients in the Turkish population.MethodsIn this study, nine patients with PD (five of them with late-onset PD [LOPD]) and 226 healthy individuals (aged 0–64 years) were included. Urine Glc4 concentrations were determined using the ultra-high-performance liquid chromatography (UHPLC) tandem mass spectrometry (MS/MS) method.ResultsOur data showed that the urine tetrasaccharide levels decreased with age in healthy individuals (p < 0.001, r = −0.256). It was higher especially during the first year of life compared to that in the elder subjects. The tetrasaccharide level of Pompe patients was higher compared to that of healthy controls of the same age: 99 ± 68 mmol/mol creatinine for infantile onset vs. 4.0 ± 3.0 mmol/mol creatinine for healthy controls of the same age group and 12.1 ± 17.4 mmol/mol creatinine for late onset vs. 1.7±1.2 mmol/mol creatinine for healthy controls of the same age group.ConclusionsThe results of this study showed that the reference intervals of tetrasaccharide in urine changed over time; therefore, it is critically important to define age-based decision levels for the diagnosis of LOPD.

scholarly journals GMrepo: a database of curated and consistently annotated human gut metagenomes

2019 ◽  
Vol 48 (D1) ◽  
pp. D545-D553 ◽  
Author(s):  
Sicheng Wu ◽  
Chuqing Sun ◽  
Yanze Li ◽  
Teng Wang ◽  
Longhao Jia ◽  
...  
Keyword(s):  
Relevant Information ◽  
Metagenomic Data ◽  
Data Repository ◽  
Healthy Controls ◽  
Healthy Individuals ◽  
Human Gut ◽  
Meta Data ◽  
Biologically Relevant ◽  
Manual Curation ◽  
State Of Art

Abstract GMrepo (data repository for Gut Microbiota) is a database of curated and consistently annotated human gut metagenomes. Its main purpose is to facilitate the reusability and accessibility of the rapidly growing human metagenomic data. This is achieved by consistently annotating the microbial contents of collected samples using state-of-art toolsets and by manual curation of the meta-data of the corresponding human hosts. GMrepo organizes the collected samples according to their associated phenotypes and includes all possible related meta-data such as age, sex, country, body-mass-index (BMI) and recent antibiotics usage. To make relevant information easier to access, GMrepo is equipped with a graphical query builder, enabling users to make customized, complex and biologically relevant queries. For example, to find (1) samples from healthy individuals of 18 to 25 years old with BMIs between 18.5 and 24.9, or (2) projects that are related to colorectal neoplasms, with each containing &gt;100 samples and both patients and healthy controls. Precomputed species/genus relative abundances, prevalence within and across phenotypes, and pairwise co-occurrence information are all available at the website and accessible through programmable interfaces. So far, GMrepo contains 58 903 human gut samples/runs (including 17 618 metagenomes and 41 285 amplicons) from 253 projects concerning 92 phenotypes. GMrepo is freely available at: https://gmrepo.humangut.info.

Clin-mNGS: Automated Pipeline for Pathogen Detection from Clinical Metagenomic Data

2020 ◽  
Vol 15 ◽  
Author(s):  
Akshatha Prasanna ◽  
Vidya Niranjan
Keyword(s):  
Antimicrobial Resistance ◽  
High Performance ◽  
Pathogen Detection ◽  
Bacterial Species ◽  
Workflow Management ◽  
Metagenomic Data ◽  
Antimicrobial Resistance Genes ◽  
Culture Independent ◽  
Automated Pipeline ◽  
User Friendly

Background: Since bacteria are the earliest known organisms, there has been significant interest in their variety and biology, most certainly concerning human health. Recent advances in Metagenomics sequencing (mNGS), a culture-independent sequencing technology have facilitated an accelerated development in clinical microbiology and our understanding of pathogens. Objective: For the implementation of mNGS in routine clinical practice to become feasible, a practical and scalable strategy for the study of mNGS data is essential. This study presents a robust automated pipeline to analyze clinical metagenomic data for pathogen identification and classification. Method: The proposed Clin-mNGS pipeline is an integrated, open-source, scalable, reproducible, and user-friendly framework scripted using the Snakemake workflow management software. The implementation avoids the hassle of manual installation and configuration of the multiple command-line tools and dependencies. The approach directly screens pathogens from clinical raw reads and generates consolidated reports for each sample. Results: The pipeline is demonstrated using publicly available data and is tested on a desktop Linux system and a High-performance cluster. The study compares variability in results from different tools and versions. The versions of the tools are made user modifiable. The pipeline results in quality check, filtered reads, host subtraction, assembled contigs, assembly metrics, relative abundances of bacterial species, antimicrobial resistance genes, plasmid finding, and virulence factors identification. The results obtained from the pipeline are evaluated based on sensitivity and positive predictive value. Conclusion: Clin-mNGS is an automated Snakemake pipeline validated for the analysis of microbial clinical metagenomics reads to perform taxonomic classification and antimicrobial resistance prediction.

scholarly journals Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kazutoshi Yoshitake ◽  
Gaku Kimura ◽  
Tomoko Sakami ◽  
Tsuyoshi Watanabe ◽  
Yukiko Taniuchi ◽  
...  
Keyword(s):  
Time Series ◽  
Microbial Communities ◽  
Pacific Coast ◽  
Three Dimensional ◽  
Amplicon Sequencing ◽  
Metagenomic Data ◽  
Shotgun Metagenomics ◽  
Functional Features ◽  
Pacific Coast Of Japan ◽  
Marine Microbial Communities

AbstractAlthough numerous metagenome, amplicon sequencing-based studies have been conducted to date to characterize marine microbial communities, relatively few have employed full metagenome shotgun sequencing to obtain a broader picture of the functional features of these marine microbial communities. Moreover, most of these studies only performed sporadic sampling, which is insufficient to understand an ecosystem comprehensively. In this study, we regularly conducted seawater sampling along the northeastern Pacific coast of Japan between March 2012 and May 2016. We collected 213 seawater samples and prepared size-based fractions to generate 454 subsets of samples for shotgun metagenome sequencing and analysis. We also determined the sequences of 16S rRNA (n = 111) and 18S rRNA (n = 47) gene amplicons from smaller sample subsets. We thereafter developed the Ocean Monitoring Database for time-series metagenomic data (http://marine-meta.healthscience.sci.waseda.ac.jp/omd/), which provides a three-dimensional bird’s-eye view of the data. This database includes results of digital DNA chip analysis, a novel method for estimating ocean characteristics such as water temperature from metagenomic data. Furthermore, we developed a novel classification method that includes more information about viruses than that acquired using BLAST. We further report the discovery of a large number of previously overlooked (TAG)n repeat sequences in the genomes of marine microbes. We predict that the availability of this time-series database will lead to major discoveries in marine microbiome research.

scholarly journals Serum Metabolomics in PCOS Women with Different Body Mass Index

2021 ◽  
Vol 10 (13) ◽  
pp. 2811
Author(s):  
Katarzyna Ożegowska ◽  
Szymon Plewa ◽  
Urszula Mantaj ◽  
Leszek Pawelczyk ◽  
Jan Matysiak
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
High Performance ◽  
Polycystic Ovary ◽  
Multiple Reaction Monitoring ◽  
Reproductive Age ◽  
Healthy Controls ◽  
Metabolic Disturbances ◽  
Hormonal Imbalance ◽  
Spectrometry Technique

Polycystic ovary syndrome (PCOS) is the most prevalent endocrine and metabolic disorder, affecting 5–10% of women of reproductive age. It results from complex environmental factors, genetic predisposition, hyperinsulinemia, hormonal imbalance, neuroendocrine abnormalities, chronic inflammation, and autoimmune disorders. PCOS impacts menstrual regularities, fertility, and dermatological complications, and may induce metabolic disturbances, diabetes, and coronary heart disease. Comprehensive metabolic profiling of patients with PCOS may be a big step in understanding and treating the disease. The study aimed to search for potential differences in metabolites concentrations among women with PCOS according to different body mass index (BMI) in comparison to healthy controls. We used broad-spectrum targeted metabolomics to evaluate metabolites’ serum concentrations in PCOS patients and compared them with healthy controls. The measurements were performed using high-performance liquid chromatography coupled with the triple quadrupole tandem mass spectrometry technique, which has highly selective multiple reaction monitoring modes. The main differences were found in glycerophospholipid concentrations, with no specific tendency to up-or down-regulation. Insulin resistance and elevated body weight influence acylcarnitine C2 levels more than PCOS itself. Sphingomyelin (SM) C18:1 should be more intensively observed and examined in future studies and maybe serve as one of the PCOS biomarkers. No significant correlations were observed between anthropometric and hormonal parameters and metabolome results.

scholarly journals Phenotypic and Functional Alterations of Immune Effectors in Periodontitis; A Multifactorial and Complex Oral Disease

2021 ◽  
Vol 10 (4) ◽  
pp. 875
Author(s):  
Kawaljit Kaur ◽  
Shahram Vaziri ◽  
Marcela Romero-Reyes ◽  
Avina Paranjpe ◽  
Anahid Jewett
Keyword(s):  
Periodontal Disease ◽  
Peripheral Blood ◽  
Mononuclear Cells ◽  
Oral Disease ◽  
Healthy Controls ◽  
Healthy Individuals ◽  
Tnf Α ◽  
Blood Mononuclear Cells ◽  
Ifn Γ ◽  
And Function

Survival and function of immune subsets in the oral blood, peripheral blood and gingival tissues of patients with periodontal disease and healthy controls were assessed. NK and CD8 + T cells within the oral blood mononuclear cells (OBMCs) expressed significantly higher levels of CD69 in patients with periodontal disease compared to those from healthy controls. Similarly, TNF-α release was higher from oral blood of patients with periodontal disease when compared to healthy controls. Increased activation induced cell death of peripheral blood mononuclear cells (PBMCs) but not OBMCs from patients with periodontal disease was observed when compared to those from healthy individuals. Unlike those from healthy individuals, OBMC-derived supernatants from periodontitis patients exhibited decreased ability to induce secretion of IFN-γ by allogeneic healthy PBMCs treated with IL-2, while they triggered significant levels of TNF-α, IL-1β and IL-6 by untreated PBMCs. Interaction of PBMCs, or NK cells with intact or NFκB knock down oral epithelial cells in the presence of a periodontal pathogen, F. nucleatum, significantly induced a number of pro-inflammatory cytokines including IFN-γ. These studies indicated that the relative numbers of immune subsets obtained from peripheral blood may not represent the composition of the immune cells in the oral environment, and that orally-derived immune effectors may differ in survival and function from those of peripheral blood.

scholarly journals Microbial drivers of methane emissions from unrestored industrial salt ponds

2021 ◽  
Author(s):  
Jinglie Zhou ◽  
Susanna M. Theroux ◽  
Clifton P. Bueno de Mesquita ◽  
Wyatt H. Hartman ◽  
Ye Tian ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Methane Flux ◽  
Methane Emissions ◽  
Metagenomic Data ◽  
Rrna Gene ◽  
Salt Ponds ◽  
Salt Pond ◽  
Reference Wetlands ◽  
Reference Wetland ◽  
The Impact

AbstractWetlands are important carbon (C) sinks, yet many have been destroyed and converted to other uses over the past few centuries, including industrial salt making. A renewed focus on wetland ecosystem services (e.g., flood control, and habitat) has resulted in numerous restoration efforts whose effect on microbial communities is largely unexplored. We investigated the impact of restoration on microbial community composition, metabolic functional potential, and methane flux by analyzing sediment cores from two unrestored former industrial salt ponds, a restored former industrial salt pond, and a reference wetland. We observed elevated methane emissions from unrestored salt ponds compared to the restored and reference wetlands, which was positively correlated with salinity and sulfate across all samples. 16S rRNA gene amplicon and shotgun metagenomic data revealed that the restored salt pond harbored communities more phylogenetically and functionally similar to the reference wetland than to unrestored ponds. Archaeal methanogenesis genes were positively correlated with methane flux, as were genes encoding enzymes for bacterial methylphosphonate degradation, suggesting methane is generated both from bacterial methylphosphonate degradation and archaeal methanogenesis in these sites. These observations demonstrate that restoration effectively converted industrial salt pond microbial communities back to compositions more similar to reference wetlands and lowered salinities, sulfate concentrations, and methane emissions.

scholarly journals A Circulating Exosome RNA Signature Is a Potential Diagnostic Marker for Pancreatic Cancer, a Systematic Study

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2565
Author(s):  
Yixing Wu ◽  
Hongmei Zeng ◽  
Qing Yu ◽  
Huatian Huang ◽  
Beatrice Fervers ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Chronic Pancreatitis ◽  
Early Detection ◽  
Validation Dataset ◽  
Healthy Controls ◽  
Rna Seq ◽  
Healthy Individuals ◽  
Kras Mutations ◽  
Significant Difference ◽  
Rna Signature

Several exosome proteins, miRNAs and KRAS mutations have been investigated in the hope of carrying out the early detection of pancreatic cancer with high sensitivity and specificity, but they have proven to be insufficient. Exosome RNAs, however, have not been extensively evaluated in the diagnosis of pancreatic cancer. The purpose of this study was to investigate the potential of circulating exosome RNAs in pancreatic cancer detection. By retrieving RNA-seq data from publicly accessed databases, differential expression and random-effects meta-analyses were performed. The results showed that pancreatic cancer had a distinct circulating exosome RNA signature in healthy individuals, and that the top 10 candidate exosome RNAs could distinguish patients from healthy individuals with an area under the curve (AUC) of 1.0. Three (HIST2H2AA3, LUZP6 and HLA-DRA) of the 10 genes in exosomes had similar differential patterns to those in tumor tissues based on RNA-seq data. In the validation dataset, the levels of these three genes in exosomes displayed good performance in distinguishing cancer from both chronic pancreatitis (AUC = 0.815) and healthy controls (AUC = 0.8558), whereas a slight difference existed between chronic pancreatitis and healthy controls (AUC = 0.586). Of the three genes, the level of HIST2H2AA3 was positively associated with KRAS status. However, there was no significant difference in the levels of the three genes across the disease stages (stages I–IV). These findings indicate that circulating exosome RNAs have a potential early detection value in pancreatic cancer, and that a distinct exosome RNA signature exists in distinguishing pancreatic cancer from healthy individuals.

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