Detecting macroecological patterns in bacterial communities across independent studies of global soils

Kelly S. Ramirez*, Christopher G. Knight, Mattias de Hollander, Francis Q. Brearley, Bede Constantinides, Anne Cotton, Si Creer, Thomas W. Crowther, John Davison, Manuel Delgado-Baquerizo, Ellen Dorrepaal, David R. Elliott, Graeme Fox, Robert I. Griffiths, Chris Hale, Kyle Hartman, Ashley Houlden, David L. Jones, Eveline J. Krab, Fernando T. Maestre & 16 others Krista L. McGuire, Sylvain Monteux, Caroline H. Orr, Wim H. van der Putten, Ian S. Roberts, David A. Robinson, Jennifer D. Rocca, Jennifer Rowntree, Klaus Schlaeppi, Matthew Shepherd, Brajesh K. Singh, Angela L. Straathof, Jennifer M. Bhatnagar, Cécile Thion, Marcel G.A. van der Heijden, Franciska T. de Vries

*Corresponding author for this work

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

The emergence of high-throughput DNA sequencing methods provides unprecedented opportunities to further unravel bacterial biodiversity and its worldwide role from human health to ecosystem functioning. However, despite the abundance of sequencing studies, combining data from multiple individual studies to address macroecological questions of bacterial diversity remains methodically challenging and plagued with biases. Here, using a machine-learning approach that accounts for differences among studies and complex interactions among taxa, we merge 30 independent bacterial data sets comprising 1,998 soil samples from 21 countries. Whereas previous meta-analysis efforts have focused on bacterial diversity measures or abundances of major taxa, we show that disparate amplicon sequence data can be combined at the taxonomy-based level to assess bacterial community structure. We find that rarer taxa are more important for structuring soil communities than abundant taxa, and that these rarer taxa are better predictors of community structure than environmental factors, which are often confounded across studies. We conclude that combining data from independent studies can be used to explore bacterial community dynamics, identify potential ‘indicator’ taxa with an important role in structuring communities, and propose hypotheses on the factors that shape bacterial biogeography that have been overlooked in the past.

Original languageEnglish
Pages (from-to)189-196
Number of pages8
JournalNature Microbiology
Volume3
Issue number2
Early online date20 Nov 2017
DOIs
Publication statusPublished - 28 Feb 2018

Fingerprint

Soil
Bacterial Structures
High-Throughput Nucleotide Sequencing
Biodiversity
Ecosystem
Meta-Analysis
Health
Machine Learning
Datasets

Keywords

  • biodiversity
  • microbial ecology

ASJC Scopus subject areas

  • Microbiology
  • Immunology
  • Applied Microbiology and Biotechnology
  • Genetics
  • Microbiology (medical)
  • Cell Biology

Cite this

Ramirez, K. S., Knight, C. G., de Hollander, M., Brearley, F. Q., Constantinides, B., Cotton, A., ... de Vries, F. T. (2018). Detecting macroecological patterns in bacterial communities across independent studies of global soils. Nature Microbiology, 3(2), 189-196. https://doi.org/10.1038/s41564-017-0062-x

Detecting macroecological patterns in bacterial communities across independent studies of global soils. / Ramirez, Kelly S.; Knight, Christopher G.; de Hollander, Mattias; Brearley, Francis Q.; Constantinides, Bede; Cotton, Anne; Creer, Si; Crowther, Thomas W.; Davison, John; Delgado-Baquerizo, Manuel; Dorrepaal, Ellen; Elliott, David R.; Fox, Graeme; Griffiths, Robert I.; Hale, Chris; Hartman, Kyle; Houlden, Ashley; Jones, David L.; Krab, Eveline J.; Maestre, Fernando T.; McGuire, Krista L.; Monteux, Sylvain; Orr, Caroline H.; van der Putten, Wim H.; Roberts, Ian S.; Robinson, David A.; Rocca, Jennifer D.; Rowntree, Jennifer; Schlaeppi, Klaus; Shepherd, Matthew; Singh, Brajesh K.; Straathof, Angela L.; Bhatnagar, Jennifer M.; Thion, Cécile; van der Heijden, Marcel G.A.; de Vries, Franciska T.

In: Nature Microbiology, Vol. 3, No. 2, 28.02.2018, p. 189-196.

Research output: Contribution to journalArticle

Ramirez, KS, Knight, CG, de Hollander, M, Brearley, FQ, Constantinides, B, Cotton, A, Creer, S, Crowther, TW, Davison, J, Delgado-Baquerizo, M, Dorrepaal, E, Elliott, DR, Fox, G, Griffiths, RI, Hale, C, Hartman, K, Houlden, A, Jones, DL, Krab, EJ, Maestre, FT, McGuire, KL, Monteux, S, Orr, CH, van der Putten, WH, Roberts, IS, Robinson, DA, Rocca, JD, Rowntree, J, Schlaeppi, K, Shepherd, M, Singh, BK, Straathof, AL, Bhatnagar, JM, Thion, C, van der Heijden, MGA & de Vries, FT 2018, 'Detecting macroecological patterns in bacterial communities across independent studies of global soils', Nature Microbiology, vol. 3, no. 2, pp. 189-196. https://doi.org/10.1038/s41564-017-0062-x
Ramirez KS, Knight CG, de Hollander M, Brearley FQ, Constantinides B, Cotton A et al. Detecting macroecological patterns in bacterial communities across independent studies of global soils. Nature Microbiology. 2018 Feb 28;3(2):189-196. https://doi.org/10.1038/s41564-017-0062-x
Ramirez, Kelly S. ; Knight, Christopher G. ; de Hollander, Mattias ; Brearley, Francis Q. ; Constantinides, Bede ; Cotton, Anne ; Creer, Si ; Crowther, Thomas W. ; Davison, John ; Delgado-Baquerizo, Manuel ; Dorrepaal, Ellen ; Elliott, David R. ; Fox, Graeme ; Griffiths, Robert I. ; Hale, Chris ; Hartman, Kyle ; Houlden, Ashley ; Jones, David L. ; Krab, Eveline J. ; Maestre, Fernando T. ; McGuire, Krista L. ; Monteux, Sylvain ; Orr, Caroline H. ; van der Putten, Wim H. ; Roberts, Ian S. ; Robinson, David A. ; Rocca, Jennifer D. ; Rowntree, Jennifer ; Schlaeppi, Klaus ; Shepherd, Matthew ; Singh, Brajesh K. ; Straathof, Angela L. ; Bhatnagar, Jennifer M. ; Thion, Cécile ; van der Heijden, Marcel G.A. ; de Vries, Franciska T. / Detecting macroecological patterns in bacterial communities across independent studies of global soils. In: Nature Microbiology. 2018 ; Vol. 3, No. 2. pp. 189-196.
@article{3c9bf1c99a484604abe59e8c56777737,
title = "Detecting macroecological patterns in bacterial communities across independent studies of global soils",
abstract = "The emergence of high-throughput DNA sequencing methods provides unprecedented opportunities to further unravel bacterial biodiversity and its worldwide role from human health to ecosystem functioning. However, despite the abundance of sequencing studies, combining data from multiple individual studies to address macroecological questions of bacterial diversity remains methodically challenging and plagued with biases. Here, using a machine-learning approach that accounts for differences among studies and complex interactions among taxa, we merge 30 independent bacterial data sets comprising 1,998 soil samples from 21 countries. Whereas previous meta-analysis efforts have focused on bacterial diversity measures or abundances of major taxa, we show that disparate amplicon sequence data can be combined at the taxonomy-based level to assess bacterial community structure. We find that rarer taxa are more important for structuring soil communities than abundant taxa, and that these rarer taxa are better predictors of community structure than environmental factors, which are often confounded across studies. We conclude that combining data from independent studies can be used to explore bacterial community dynamics, identify potential ‘indicator’ taxa with an important role in structuring communities, and propose hypotheses on the factors that shape bacterial biogeography that have been overlooked in the past.",
keywords = "biodiversity, microbial ecology",
author = "Ramirez, {Kelly S.} and Knight, {Christopher G.} and {de Hollander}, Mattias and Brearley, {Francis Q.} and Bede Constantinides and Anne Cotton and Si Creer and Crowther, {Thomas W.} and John Davison and Manuel Delgado-Baquerizo and Ellen Dorrepaal and Elliott, {David R.} and Graeme Fox and Griffiths, {Robert I.} and Chris Hale and Kyle Hartman and Ashley Houlden and Jones, {David L.} and Krab, {Eveline J.} and Maestre, {Fernando T.} and McGuire, {Krista L.} and Sylvain Monteux and Orr, {Caroline H.} and {van der Putten}, {Wim H.} and Roberts, {Ian S.} and Robinson, {David A.} and Rocca, {Jennifer D.} and Jennifer Rowntree and Klaus Schlaeppi and Matthew Shepherd and Singh, {Brajesh K.} and Straathof, {Angela L.} and Bhatnagar, {Jennifer M.} and C{\'e}cile Thion and {van der Heijden}, {Marcel G.A.} and {de Vries}, {Franciska T.}",
note = "We thank all the people who contributed data and input to this study. This study was conducted at a workshop (May 2015, Manchester, UK) funded by the British Ecological Society’s special interest group Plants-Soils-Ecosystems and organized by F.T.d.V. and K.S.R. This study and participants were funded in part by ERC Advanced Grant 26055290 (K.S.R., and W.H.v.d.P.); BBSRC David Phillips Fellowship (BB/L02456X/1) (F.T.d.V.); ERC Grant Agreements 242658 (BIOCOM) and 647038 (BIODESERT) (F.T.M.); the European Regional Development Fund (Centre of Excellence EcolChange) (J.D.); Yorkshire Agricultural Society, Nafferton Ecological Farming Group, and the Northumbria University Research Development Fund (C.H.O.); BBSRC Training Grant (BB/K501943/1) (C.H.); Wallenberg Academy Fellowship (KAW 2012.0152), Formas (214-2011-788) and Vetenskapsr{\aa}det (612-2011-5444) (E.D.); the Glastir Monitoring & Evaluation Programme (contract reference: C147/2010/11) and the full support of the GMEP team on the Glastir project (D.L.J., S.C., and D.A.R.). Computing was facilitated by the University of Manchester Condor pool and the CLIMB infrastructure (http://www.climb.ac.uk).",
year = "2018",
month = "2",
day = "28",
doi = "10.1038/s41564-017-0062-x",
language = "English",
volume = "3",
pages = "189--196",
journal = "Nature Microbiology",
issn = "2058-5276",
publisher = "Nature Publishing Group",
number = "2",

}

TY - JOUR

T1 - Detecting macroecological patterns in bacterial communities across independent studies of global soils

AU - Ramirez, Kelly S.

AU - Knight, Christopher G.

AU - de Hollander, Mattias

AU - Brearley, Francis Q.

AU - Constantinides, Bede

AU - Cotton, Anne

AU - Creer, Si

AU - Crowther, Thomas W.

AU - Davison, John

AU - Delgado-Baquerizo, Manuel

AU - Dorrepaal, Ellen

AU - Elliott, David R.

AU - Fox, Graeme

AU - Griffiths, Robert I.

AU - Hale, Chris

AU - Hartman, Kyle

AU - Houlden, Ashley

AU - Jones, David L.

AU - Krab, Eveline J.

AU - Maestre, Fernando T.

AU - McGuire, Krista L.

AU - Monteux, Sylvain

AU - Orr, Caroline H.

AU - van der Putten, Wim H.

AU - Roberts, Ian S.

AU - Robinson, David A.

AU - Rocca, Jennifer D.

AU - Rowntree, Jennifer

AU - Schlaeppi, Klaus

AU - Shepherd, Matthew

AU - Singh, Brajesh K.

AU - Straathof, Angela L.

AU - Bhatnagar, Jennifer M.

AU - Thion, Cécile

AU - van der Heijden, Marcel G.A.

AU - de Vries, Franciska T.

N1 - We thank all the people who contributed data and input to this study. This study was conducted at a workshop (May 2015, Manchester, UK) funded by the British Ecological Society’s special interest group Plants-Soils-Ecosystems and organized by F.T.d.V. and K.S.R. This study and participants were funded in part by ERC Advanced Grant 26055290 (K.S.R., and W.H.v.d.P.); BBSRC David Phillips Fellowship (BB/L02456X/1) (F.T.d.V.); ERC Grant Agreements 242658 (BIOCOM) and 647038 (BIODESERT) (F.T.M.); the European Regional Development Fund (Centre of Excellence EcolChange) (J.D.); Yorkshire Agricultural Society, Nafferton Ecological Farming Group, and the Northumbria University Research Development Fund (C.H.O.); BBSRC Training Grant (BB/K501943/1) (C.H.); Wallenberg Academy Fellowship (KAW 2012.0152), Formas (214-2011-788) and Vetenskapsrådet (612-2011-5444) (E.D.); the Glastir Monitoring & Evaluation Programme (contract reference: C147/2010/11) and the full support of the GMEP team on the Glastir project (D.L.J., S.C., and D.A.R.). Computing was facilitated by the University of Manchester Condor pool and the CLIMB infrastructure (http://www.climb.ac.uk).

PY - 2018/2/28

Y1 - 2018/2/28

N2 - The emergence of high-throughput DNA sequencing methods provides unprecedented opportunities to further unravel bacterial biodiversity and its worldwide role from human health to ecosystem functioning. However, despite the abundance of sequencing studies, combining data from multiple individual studies to address macroecological questions of bacterial diversity remains methodically challenging and plagued with biases. Here, using a machine-learning approach that accounts for differences among studies and complex interactions among taxa, we merge 30 independent bacterial data sets comprising 1,998 soil samples from 21 countries. Whereas previous meta-analysis efforts have focused on bacterial diversity measures or abundances of major taxa, we show that disparate amplicon sequence data can be combined at the taxonomy-based level to assess bacterial community structure. We find that rarer taxa are more important for structuring soil communities than abundant taxa, and that these rarer taxa are better predictors of community structure than environmental factors, which are often confounded across studies. We conclude that combining data from independent studies can be used to explore bacterial community dynamics, identify potential ‘indicator’ taxa with an important role in structuring communities, and propose hypotheses on the factors that shape bacterial biogeography that have been overlooked in the past.

AB - The emergence of high-throughput DNA sequencing methods provides unprecedented opportunities to further unravel bacterial biodiversity and its worldwide role from human health to ecosystem functioning. However, despite the abundance of sequencing studies, combining data from multiple individual studies to address macroecological questions of bacterial diversity remains methodically challenging and plagued with biases. Here, using a machine-learning approach that accounts for differences among studies and complex interactions among taxa, we merge 30 independent bacterial data sets comprising 1,998 soil samples from 21 countries. Whereas previous meta-analysis efforts have focused on bacterial diversity measures or abundances of major taxa, we show that disparate amplicon sequence data can be combined at the taxonomy-based level to assess bacterial community structure. We find that rarer taxa are more important for structuring soil communities than abundant taxa, and that these rarer taxa are better predictors of community structure than environmental factors, which are often confounded across studies. We conclude that combining data from independent studies can be used to explore bacterial community dynamics, identify potential ‘indicator’ taxa with an important role in structuring communities, and propose hypotheses on the factors that shape bacterial biogeography that have been overlooked in the past.

KW - biodiversity

KW - microbial ecology

UR - http://www.scopus.com/inward/record.url?scp=85034611619&partnerID=8YFLogxK

U2 - 10.1038/s41564-017-0062-x

DO - 10.1038/s41564-017-0062-x

M3 - Article

VL - 3

SP - 189

EP - 196

JO - Nature Microbiology

JF - Nature Microbiology

SN - 2058-5276

IS - 2

ER -