IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-34409-z.html
   My bibliography  Save this article

De novo identification of microbial contaminants in low microbial biomass microbiomes with Squeegee

Author

Listed:
  • Yunxi Liu

    (Rice University, Department of Computer Science)

  • R. A. Leo Elworth

    (Rice University, Department of Computer Science)

  • Michael D. Jochum

    (Baylor College of Medicine and Texas Children’s Hospital)

  • Kjersti M. Aagaard

    (Baylor College of Medicine and Texas Children’s Hospital)

  • Todd J. Treangen

    (Rice University, Department of Computer Science)

Abstract

Computational analysis of host-associated microbiomes has opened the door to numerous discoveries relevant to human health and disease. However, contaminant sequences in metagenomic samples can potentially impact the interpretation of findings reported in microbiome studies, especially in low-biomass environments. Contamination from DNA extraction kits or sampling lab environments leaves taxonomic "bread crumbs" across multiple distinct sample types. Here we describe Squeegee, a de novo contamination detection tool that is based upon this principle, allowing the detection of microbial contaminants when negative controls are unavailable. On the low-biomass samples, we compare Squeegee predictions to experimental negative control data and show that Squeegee accurately recovers putative contaminants. We analyze samples of varying biomass from the Human Microbiome Project and identify likely, previously unreported kit contamination. Collectively, our results highlight that Squeegee can identify microbial contaminants with high precision and thus represents a computational approach for contaminant detection when negative controls are unavailable.

Suggested Citation

  • Yunxi Liu & R. A. Leo Elworth & Michael D. Jochum & Kjersti M. Aagaard & Todd J. Treangen, 2022. "De novo identification of microbial contaminants in low microbial biomass microbiomes with Squeegee," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-34409-z
    DOI: 10.1038/s41467-022-34409-z
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-34409-z
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-022-34409-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Lisa Ekman & Elisabeth Bagge & Ann Nyman & Karin Persson Waller & Märit Pringle & Bo Segerman, 2020. "A shotgun metagenomic investigation of the microbiota of udder cleft dermatitis in comparison to healthy skin in dairy cows," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-22, December.
    2. Peter J. Turnbaugh & Micah Hamady & Tanya Yatsunenko & Brandi L. Cantarel & Alexis Duncan & Ruth E. Ley & Mitchell L. Sogin & William J. Jones & Bruce A. Roe & Jason P. Affourtit & Michael Egholm & Be, 2009. "A core gut microbiome in obese and lean twins," Nature, Nature, vol. 457(7228), pages 480-484, January.
    3. Karthik Anantharaman & Christopher T. Brown & Laura A. Hug & Itai Sharon & Cindy J. Castelle & Alexander J. Probst & Brian C. Thomas & Andrea Singh & Michael J. Wilkins & Ulas Karaoz & Eoin L. Brodie , 2016. "Thousands of microbial genomes shed light on interconnected biogeochemical processes in an aquifer system," Nature Communications, Nature, vol. 7(1), pages 1-11, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Patrick D Schloss, 2009. "A High-Throughput DNA Sequence Aligner for Microbial Ecology Studies," PLOS ONE, Public Library of Science, vol. 4(12), pages 1-9, December.
    2. John Molloy & Katrina Allen & Fiona Collier & Mimi L. K. Tang & Alister C. Ward & Peter Vuillermin, 2013. "The Potential Link between Gut Microbiota and IgE-Mediated Food Allergy in Early Life," IJERPH, MDPI, vol. 10(12), pages 1-22, December.
    3. Bharati Patel & Kadamb Patel & Shabbir Moochhala, 2020. "Diet-Derived Post-Biotic Metabolites to Promote Microbiota Function and Human Health," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 28(2), pages 21520-21524, June.
    4. Ahmed A Metwally & Philip S Yu & Derek Reiman & Yang Dai & Patricia W Finn & David L Perkins, 2019. "Utilizing longitudinal microbiome taxonomic profiles to predict food allergy via Long Short-Term Memory networks," PLOS Computational Biology, Public Library of Science, vol. 15(2), pages 1-16, February.
    5. Pirjo Wacklin & Harri Mäkivuokko & Noora Alakulppi & Janne Nikkilä & Heli Tenkanen & Jarkko Räbinä & Jukka Partanen & Kari Aranko & Jaana Mättö, 2011. "Secretor Genotype (FUT2 gene) Is Strongly Associated with the Composition of Bifidobacteria in the Human Intestine," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-10, May.
    6. C. E. Dubé & M. Ziegler & A. Mercière & E. Boissin & S. Planes & C. A. -F. Bourmaud & C. R. Voolstra, 2021. "Naturally occurring fire coral clones demonstrate a genetic and environmental basis of microbiome composition," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    7. Mariana F. Fernández & Iris Reina-Pérez & Juan Manuel Astorga & Andrea Rodríguez-Carrillo & Julio Plaza-Díaz & Luis Fontana, 2018. "Breast Cancer and Its Relationship with the Microbiota," IJERPH, MDPI, vol. 15(8), pages 1-20, August.
    8. Kelly J. Whaley-Martin & Lin-Xing Chen & Tara Colenbrander Nelson & Jennifer Gordon & Rose Kantor & Lauren E. Twible & Stephanie Marshall & Sam McGarry & Laura Rossi & Benoit Bessette & Christian Baro, 2023. "O2 partitioning of sulfur oxidizing bacteria drives acidity and thiosulfate distributions in mining waters," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    9. Morten Kam Dahl Dueholm & Marta Nierychlo & Kasper Skytte Andersen & Vibeke Rudkjøbing & Simon Knutsson & Mads Albertsen & Per Halkjær Nielsen, 2022. "MiDAS 4: A global catalogue of full-length 16S rRNA gene sequences and taxonomy for studies of bacterial communities in wastewater treatment plants," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    10. Thomas J Sharpton & Samantha J Riesenfeld & Steven W Kembel & Joshua Ladau & James P O'Dwyer & Jessica L Green & Jonathan A Eisen & Katherine S Pollard, 2011. "PhylOTU: A High-Throughput Procedure Quantifies Microbial Community Diversity and Resolves Novel Taxa from Metagenomic Data," PLOS Computational Biology, Public Library of Science, vol. 7(1), pages 1-13, January.
    11. Xianzhe Gong & Álvaro Rodríguez Río & Le Xu & Zhiyi Chen & Marguerite V. Langwig & Lei Su & Mingxue Sun & Jaime Huerta-Cepas & Valerie Anda & Brett J. Baker, 2022. "New globally distributed bacterial phyla within the FCB superphylum," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    12. Sanjeena Subedi & Drew Neish & Stephen Bak & Zeny Feng, 2020. "Cluster analysis of microbiome data by using mixtures of Dirichlet–multinomial regression models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1163-1187, November.
    13. Shinji Fukuda & Yumiko Nakanishi & Eisuke Chikayama & Hiroshi Ohno & Tsuneo Hino & Jun Kikuchi, 2009. "Evaluation and Characterization of Bacterial Metabolic Dynamics with a Novel Profiling Technique, Real-Time Metabolotyping," PLOS ONE, Public Library of Science, vol. 4(3), pages 1-10, March.
    14. S. Emil Ruff & Pauline Humez & Isabella Hrabe Angelis & Muhe Diao & Michael Nightingale & Sara Cho & Liam Connors & Olukayode O. Kuloyo & Alan Seltzer & Samuel Bowman & Scott D. Wankel & Cynthia N. Mc, 2023. "Hydrogen and dark oxygen drive microbial productivity in diverse groundwater ecosystems," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    15. Mark Reppell & John Novembre, 2018. "Using pseudoalignment and base quality to accurately quantify microbial community composition," PLOS Computational Biology, Public Library of Science, vol. 14(4), pages 1-23, April.
    16. Hannah Lees & Jonathan Swann & Simon M Poucher & Jeremy K Nicholson & Elaine Holmes & Ian D Wilson & Julian R Marchesi, 2014. "Age and Microenvironment Outweigh Genetic Influence on the Zucker Rat Microbiome," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-11, September.
    17. Ernestina Hauptfeld & Nikolaos Pappas & Sandra Iwaarden & Basten L. Snoek & Andrea Aldas-Vargas & Bas E. Dutilh & F. A. Bastiaan Meijenfeldt, 2024. "Integrating taxonomic signals from MAGs and contigs improves read annotation and taxonomic profiling of metagenomes," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    18. Xinhui Wang & Marinus J C Eijkemans & Jacco Wallinga & Giske Biesbroek & Krzysztof Trzciński & Elisabeth A M Sanders & Debby Bogaert, 2012. "Multivariate Approach for Studying Interactions between Environmental Variables and Microbial Communities," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-7, November.
    19. Ming Peng & Chun-Yang Li & Xiu-Lan Chen & Beth T. Williams & Kang Li & Ya-Nan Gao & Peng Wang & Ning Wang & Chao Gao & Shan Zhang & Marie C. Schoelmerich & Jillian F. Banfield & J. Benjamin Miller & N, 2022. "Insights into methionine S-methylation in diverse organisms," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    20. Liat Shenhav & Ori Furman & Leah Briscoe & Mike Thompson & Justin D Silverman & Itzhak Mizrahi & Eran Halperin, 2019. "Modeling the temporal dynamics of the gut microbial community in adults and infants," PLOS Computational Biology, Public Library of Science, vol. 15(6), pages 1-21, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-34409-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.