Standardized multi-omics of Earth’s microbiomes reveals microbial and metabolite diversity DOI Creative Commons
Justin P. Shaffer, Louis‐Félix Nothias, Luke Thompson

et al.

Nature Microbiology, Journal Year: 2022, Volume and Issue: 7(12), P. 2128 - 2150

Published: Nov. 28, 2022

Despite advances in sequencing, lack of standardization makes comparisons across studies challenging and hampers insights into the structure function microbial communities multiple habitats on a planetary scale. Here we present multi-omics analysis diverse set 880 community samples collected for Earth Microbiome Project. We include amplicon (16S, 18S, ITS) shotgun metagenomic sequence data, untargeted metabolomics data (liquid chromatography-tandem mass spectrometry gas chromatography spectrometry). used standardized protocols analytical methods to characterize communities, focusing relationships co-occurrences microbially related metabolites taxa environments, thus allowing us explore diversity at extraordinary In addition reference database metabolomic provide framework incorporating additional studies, enabling expansion existing knowledge form an evolving resource. demonstrate utility this by testing hypothesis that every microbe metabolite is everywhere but environment selects. Our results show exhibits turnover nestedness both environment, whereas relative abundances vary co-occur with specific consortia habitat-specific manner. additionally power certain chemistry, particular terpenoids, distinguishing Earth's environments (for example, terrestrial plant surfaces soils, freshwater marine animal stool), as well microbes including Conexibacter woesei (terrestrial soils), Haloquadratum walsbyi (marine deposits) Pantoea dispersa detritus). This Resource provides insight within from Earth, informing chemical ecology, foundation microbiome hosts environment.

Language: Английский

Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England DOI Creative Commons
Nicholas G. Davies, Sam Abbott, Rosanna C. Barnard

et al.

Science, Journal Year: 2021, Volume and Issue: 372(6538)

Published: March 3, 2021

UK variant transmission Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has the capacity to generate variants with major genomic changes. The B.1.1.7 (also known as VOC 202012/01) many mutations that alter virus attachment and entry into human cells. Using a variety of statistical dynamic modeling approaches, Davies et al. characterized spread in United Kingdom. authors found is 43 90% more transmissible than predecessor lineage but saw no clear evidence for change disease severity, although enhanced will lead higher incidence hospital admissions. Large resurgences are likely occur after easing control measures, it may be necessary greatly accelerate vaccine roll-out epidemic. Science , this issue p. eabg3055

Language: Английский

Citations

2466
Analysis of compositions of microbiomes with bias correction DOI Creative Commons
Huang Lin, Shyamal Peddada

Nature Communications, Journal Year: 2020, Volume and Issue: 11(1)

Published: July 14, 2020

Abstract Differential abundance (DA) analysis of microbiome data continues to be a challenging problem due the complexity data. In this article we define notion “sampling fraction” and demonstrate major hurdle in performing DA is bias introduced by differences sampling fractions across samples. We introduce methodology called Analysis Compositions Microbiomes with Bias Correction ( ANCOM-BC ), which estimates unknown corrects induced their among The absolute are modeled using linear regression framework. This formulation makes fundamental advancement field because, unlike existing methods, it (a) provides statistically valid test appropriate p-values, (b) confidence intervals for differential each taxon, (c) controls False Discovery Rate (FDR), (d) maintains adequate power, (e) computationally simple implement.

Language: Английский

Citations

1433
Climate warming enhances microbial network complexity and stability DOI
Mengting Yuan, Xue Guo, Linwei Wu

et al.

Nature Climate Change, Journal Year: 2021, Volume and Issue: 11(4), P. 343 - 348

Published: Feb. 22, 2021

Language: Английский

Citations

1363
Microbiome differential abundance methods produce different results across 38 datasets DOI Creative Commons
Jacob T. Nearing, Gavin M. Douglas,

Molly G. Hayes

et al.

Nature Communications, Journal Year: 2022, Volume and Issue: 13(1)

Published: Jan. 17, 2022

Identifying differentially abundant microbes is a common goal of microbiome studies. Multiple methods are used interchangeably for this purpose in the literature. Yet, there few large-scale studies systematically exploring appropriateness using these tools interchangeably, and scale significance differences between them. Here, we compare performance 14 differential abundance testing on 38 16S rRNA gene datasets with two sample groups. We test amplicon sequence variants operational taxonomic units (ASVs) Our findings confirm that identified drastically different numbers sets significant ASVs, results depend data pre-processing. For many number features correlate aspects data, such as size, sequencing depth, effect size community differences. ALDEx2 ANCOM-II produce most consistent across agree best intersect from approaches. Nevertheless, recommend researchers should use consensus approach based multiple to help ensure robust biological interpretations. Many available, but it lacks systematic comparison among authors groups, show results.

Language: Английский

Citations

580
Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England DOI Creative Commons
Nicholas G. Davies, Sam Abbott,

Rosanna C. Barnard

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2020, Volume and Issue: unknown

Published: Dec. 26, 2020

A novel SARS-CoV-2 variant, VOC 202012/01 (lineage B.1.1.7), emerged in southeast England November 2020 and is rapidly spreading towards fixation. Using a variety of statistical dynamic modelling approaches, we estimate that this variant has 43–90% (range 95% credible intervals 38–130%) higher reproduction number than preexisting variants. fitted two-strain transmission model shows will lead to large resurgences COVID-19 cases. Without stringent control measures, including limited closure educational institutions greatly accelerated vaccine roll-out, hospitalisations deaths across 2021 exceed those 2020. Concerningly, spread globally exhibits similar increase (59–74%) Denmark, Switzerland, the United States.

Language: Английский

Citations

517
QIIME 2 Enables Comprehensive End‐to‐End Analysis of Diverse Microbiome Data and Comparative Studies with Publicly Available Data DOI Creative Commons
Mehrbod Estaki, Lingjing Jiang, Nicholas A. Bokulich

et al.

Current Protocols in Bioinformatics, Journal Year: 2020, Volume and Issue: 70(1)

Published: April 28, 2020

QIIME 2 is a completely re-engineered microbiome bioinformatics platform based on the popular platform, which it has replaced. facilitates comprehensive and fully reproducible data science, improving accessibility to diverse users by adding multiple user interfaces. can be combined with Qiita, an open-source web-based re-use available for meta-analysis. The following basic protocol describes how install single computer analyze sequence data, from processing of raw DNA reads through generating publishable interactive figures. These figures allow readers study interact same ease as its authors, advancing science transparency reproducibility. We also show plug-ins developed community add analysis capabilities installed used 2, enhancing various aspects analyses-e.g., taxonomic classification accuracy. Finally, we illustrate perform meta-analyses combining different datasets using readily public Qiita. In this tutorial, subset Early Childhood Antibiotics Microbiome (ECAM) study, tracked composition development 43 infants in United States birth years age, identifying associations antibiotic exposure, delivery mode, diet. For more information about see https://qiime2.org. To troubleshoot or ask questions analysis, join active at https://forum.qiime2.org. © 2020 Authors. Basic Protocol: Using Support Further analyses.

Language: Английский

Citations

372
Mass spectrometry-based metabolomics in microbiome investigations DOI
Anelize Bauermeister, Helena Mannochio-Russo, Letícia V. Costa‐Lotufo

et al.

Nature Reviews Microbiology, Journal Year: 2021, Volume and Issue: 20(3), P. 143 - 160

Published: Sept. 22, 2021

Language: Английский

Citations

334
Pan-cancer analyses reveal cancer-type-specific fungal ecologies and bacteriome interactions DOI Creative Commons
Lian Narunsky-Haziza, Gregory D. Sepich‐Poore, Ilana Livyatan

et al.

Cell, Journal Year: 2022, Volume and Issue: 185(20), P. 3789 - 3806.e17

Published: Sept. 1, 2022

Cancer-microbe associations have been explored for centuries, but cancer-associated fungi rarely examined. Here, we comprehensively characterize the cancer mycobiome within 17,401 patient tissue, blood, and plasma samples across 35 types in four independent cohorts. We report fungal DNA cells at low abundances many major human cancers, with differences community compositions that differ among types, even when accounting technical background. Fungal histological staining of tissue microarrays supported intratumoral presence frequent spatial association macrophages. Comparing communities matched bacteriomes immunomes revealed co-occurring bi-domain ecologies, often permissive, rather than competitive, microenvironments distinct immune responses. Clinically focused assessments suggested prognostic diagnostic capacities mycobiomes, stage I synergistic predictive performance bacteriomes.

Language: Английский

Citations

333
Translocation of Viable Gut Microbiota to Mesenteric Adipose Drives Formation of Creeping Fat in Humans DOI Creative Commons
Connie Ha, Anthony Martin, Gregory D. Sepich‐Poore

et al.

Cell, Journal Year: 2020, Volume and Issue: 183(3), P. 666 - 683.e17

Published: Sept. 28, 2020

Language: Английский

Citations

318
Comparative Analyses of Vertebrate Gut Microbiomes Reveal Convergence between Birds and Bats DOI Creative Commons
Se Jin Song, Jon G. Sanders, Frédéric Delsuc

et al.

mBio, Journal Year: 2020, Volume and Issue: 11(1)

Published: Jan. 6, 2020

In this comprehensive survey of microbiomes >900 species, including 315 mammals and 491 birds, we find a striking convergence the birds animals that fly. nonflying mammals, diet short-term evolutionary relatedness drive microbiome, many microbial species are specific to particular kind mammal, but flying break pattern with microbes shared across different little correlation either or hosts. This finding suggests adaptation flight breaks long-held relationships between hosts their microbes.

Language: Английский

Citations

308