DNA extraction and host depletion methods significantly impact and potentially bias bacterial detection in a biological fluid

Erika Ganda, Kristen L. Beck, Niina Haiminen, Justin D. Silverman, Ban Kawas, Brittany D. Cronk, Renee R. Anderson, Laura B. Goodman, Martin Wiedmann

Research output: Contribution to journalArticlepeer-review

Abstract

Untargeted sequencing of nucleic acids present in food can inform the detection of food safety and origin, as well as product tampering and mislabeling issues. The application of such technologies to food analysis may reveal valuable insights that are simply unobtainable by targeted testing, leading to the efforts of applying such technologies in the food industry. However, before these approaches can be applied, it is imperative to verify that the most appropriate methods are used at every step of the process: Gathering of primary material, laboratory methods, data analysis, and interpretation. The focus of this study is on gathering the primary material, in this case, DNA. We used bovine milk as a model to (i) evaluate commercially available kits for their ability to extract nucleic acids from inoculated bovine milk, (ii) evaluate host DNA depletion methods for use with milk, and (iii) develop and evaluate a selective lysis-propidium monoazide (PMA)-based protocol for host DNA depletion in milk. Our results suggest that magnetically based nucleic acid extraction methods are best for nucleic acid isolation of bovine milk. Removal of host DNA remains a challenge for untargeted sequencing of milk, highlighting the finding that the individual matrix characteristics should always be considered in food testing. Some reported methods introduce bias against specific types of microbes, which may be particularly problematic in food safety, where the detection of Gram-negative pathogens and hygiene indicators is essential. Continuous efforts are needed to develop and validate new approaches for untargeted metagenomics in samples with large amounts of DNA from a single host.

Original languageEnglish (US)
Article numbere00619-21
JournalmSystems
Volume6
Issue number3
DOIs
StatePublished - Jun 2021

All Science Journal Classification (ASJC) codes

  • Microbiology
  • Ecology, Evolution, Behavior and Systematics
  • Biochemistry
  • Physiology
  • Modeling and Simulation
  • Molecular Biology
  • Genetics
  • Computer Science Applications

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