KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples

Minich, Jeremiah J.; Zhu, Qiyun; Janssen, Stefan; Hendrickson, Ryan; Amir, Amnon; Vetter, Russ; Hyde, John; Doty, Megan M.; Stillwell, Kristina; Benardini, James; Kim, Jae H.; Allen, Eric E.; Venkateswaran, Kasthuri; Knight, Rob

doi:10.1128/msystems.00218-17

i

KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples

Public Domain

2018
By Minich, Jeremiah J. ; Zhu, Qiyun ; Janssen, Stefan ; ...

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Journal Title:

mSystems
Personal Author:

Minich, Jeremiah J. ; Zhu, Qiyun ; Janssen, Stefan ; Hendrickson, Ryan ; Amir, Amnon ; Vetter, Russ ; Hyde, John ; Doty, Megan M. ; Stillwell, Kristina ; Benardini, James ; Kim, Jae H. ; Allen, Eric E. ; Venkateswaran, Kasthuri ; Knight, Rob
NOAA Program & Office:

NMFS (National Marine Fisheries Service) ; SWFSC (Southwest Fisheries Science Center)
Description:

Various indoor, outdoor, and host-associated environments contain small quantities of microbial biomass and represent a niche that is often understudied because of technical constraints. Many studies that attempt to evaluate these low-biomass microbiome samples are riddled with erroneous results that are typically false positive signals obtained during the sampling process. We have investigated various low-biomass kits and methods to determine the limit of detection of these pipelines. Here we present KatharoSeq, a high-throughput protocol combining laboratory and bioinformatic methods that can differentiate a true positive signal in samples with as few as 50 to 500 cells. We demonstrate the application of this method in three unique low-biomass environments, including a SAF, a hospital NICU, and an abalone-rearing facility.
Keywords:

Biochemistry Computer Science Applications Ecology, Evolution, Behavior And Systematics Genetics Microbiology Modeling And Simulation Molecular Biology Physiology Ecology, Evolution, Behavior And Systematics Modeling And Simulation Modeling And Simulation
Source:

mSystems, 3(3)
DOI:

https://doi.org/10.1128/msystems.00218-17
ISSN:

2379-5077
Format:

PDF
Publisher:

American Society for Microbiology
Document Type:

Journal Article
License:

https://creativecommons.org/licenses/by/4.0/
Rights Information:

CC BY
Compliance:

Library
Main Document Checksum:

urn:sha256:ef77c51c096b443d2fab0a236d2b83deff7ccaf18ef1133358e6d80ac1e8f907
Download URL:

https://repository.library.noaa.gov/view/noaa/54107/noaa_54107_DS1.pdf
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[PDF - 1.68 MB ]

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