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

ABSTRACT Microbiome analyses of low-biomass samples are challenging because of contamination and inefficiencies, leading many investigators to employ low-throughput methods with minimal controls. We developed a new automated protocol, KatharoSeq (from the Greek katharos [clean]), that outperforms si...

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Autores principales:	Jeremiah J. Minich, Qiyun Zhu, Stefan Janssen, Ryan Hendrickson, Amnon Amir, Russ Vetter, John Hyde, Megan M. Doty, Kristina Stillwell, James Benardini, Jae H. Kim, Eric E. Allen, Kasthuri Venkateswaran, Rob Knight
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2018
Materias:	16S rRNA amplicon Acinetobacter Staphylococcus Vibrio abalone built environment Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/431a4178ad1346269f6fc3fc3aaaf300
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spelling	oai:doaj.org-article:431a4178ad1346269f6fc3fc3aaaf3002021-12-02T18:15:45ZKatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples10.1128/mSystems.00218-172379-5077https://doaj.org/article/431a4178ad1346269f6fc3fc3aaaf3002018-06-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00218-17https://doaj.org/toc/2379-5077ABSTRACT Microbiome analyses of low-biomass samples are challenging because of contamination and inefficiencies, leading many investigators to employ low-throughput methods with minimal controls. We developed a new automated protocol, KatharoSeq (from the Greek katharos [clean]), that outperforms single-tube extractions while processing at least five times as fast. KatharoSeq incorporates positive and negative controls to reveal the whole bacterial community from inputs of as few as 50 cells and correctly identifies 90.6% (standard error, 0.013%) of the reads from 500 cells. To demonstrate the broad utility of KatharoSeq, we performed 16S rRNA amplicon and shotgun metagenome analyses of the Jet Propulsion Laboratory spacecraft assembly facility (SAF; n = 192, 96), 52 rooms of a neonatal intensive care unit (NICU; n = 388, 337), and an endangered-abalone-rearing facility (n = 192, 123), obtaining spatially resolved, unique microbiomes reproducible across hundreds of samples. The SAF, our primary focus, contains 32 sOTUs (sub-OTUs, defined as exact sequence matches) and their inferred variants identified by the deblur algorithm, with four (Acinetobacter lwoffii, Paracoccus marcusii, Mycobacterium sp., and Novosphingobium) being present in >75% of the samples. According to microbial spatial topography, the most abundant cleanroom contaminant, A. lwoffii, is related to human foot traffic exposure. In the NICU, we have been able to discriminate environmental exposure related to patient infectious disease, and in the abalone facility, we show that microbial communities reflect the marine environment rather than human input. Consequently, we demonstrate the feasibility and utility of large-scale, low-biomass metagenomic analyses using the KatharoSeq protocol. IMPORTANCE 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.Jeremiah J. MinichQiyun ZhuStefan JanssenRyan HendricksonAmnon AmirRuss VetterJohn HydeMegan M. DotyKristina StillwellJames BenardiniJae H. KimEric E. AllenKasthuri VenkateswaranRob KnightAmerican Society for Microbiologyarticle16S rRNA ampliconAcinetobacterStaphylococcusVibrioabalonebuilt environmentMicrobiologyQR1-502ENmSystems, Vol 3, Iss 3 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	16S rRNA amplicon Acinetobacter Staphylococcus Vibrio abalone built environment Microbiology QR1-502
spellingShingle	16S rRNA amplicon Acinetobacter Staphylococcus Vibrio abalone built environment Microbiology QR1-502 Jeremiah J. Minich Qiyun Zhu Stefan Janssen Ryan Hendrickson Amnon Amir Russ Vetter John Hyde Megan M. Doty Kristina Stillwell James Benardini Jae H. Kim Eric E. Allen Kasthuri Venkateswaran Rob Knight KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples
description	ABSTRACT Microbiome analyses of low-biomass samples are challenging because of contamination and inefficiencies, leading many investigators to employ low-throughput methods with minimal controls. We developed a new automated protocol, KatharoSeq (from the Greek katharos [clean]), that outperforms single-tube extractions while processing at least five times as fast. KatharoSeq incorporates positive and negative controls to reveal the whole bacterial community from inputs of as few as 50 cells and correctly identifies 90.6% (standard error, 0.013%) of the reads from 500 cells. To demonstrate the broad utility of KatharoSeq, we performed 16S rRNA amplicon and shotgun metagenome analyses of the Jet Propulsion Laboratory spacecraft assembly facility (SAF; n = 192, 96), 52 rooms of a neonatal intensive care unit (NICU; n = 388, 337), and an endangered-abalone-rearing facility (n = 192, 123), obtaining spatially resolved, unique microbiomes reproducible across hundreds of samples. The SAF, our primary focus, contains 32 sOTUs (sub-OTUs, defined as exact sequence matches) and their inferred variants identified by the deblur algorithm, with four (Acinetobacter lwoffii, Paracoccus marcusii, Mycobacterium sp., and Novosphingobium) being present in >75% of the samples. According to microbial spatial topography, the most abundant cleanroom contaminant, A. lwoffii, is related to human foot traffic exposure. In the NICU, we have been able to discriminate environmental exposure related to patient infectious disease, and in the abalone facility, we show that microbial communities reflect the marine environment rather than human input. Consequently, we demonstrate the feasibility and utility of large-scale, low-biomass metagenomic analyses using the KatharoSeq protocol. IMPORTANCE 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.
format	article
author	Jeremiah J. Minich Qiyun Zhu Stefan Janssen Ryan Hendrickson Amnon Amir Russ Vetter John Hyde Megan M. Doty Kristina Stillwell James Benardini Jae H. Kim Eric E. Allen Kasthuri Venkateswaran Rob Knight
author_facet	Jeremiah J. Minich Qiyun Zhu Stefan Janssen Ryan Hendrickson Amnon Amir Russ Vetter John Hyde Megan M. Doty Kristina Stillwell James Benardini Jae H. Kim Eric E. Allen Kasthuri Venkateswaran Rob Knight
author_sort	Jeremiah J. Minich
title	KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples
title_short	KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples
title_full	KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples
title_fullStr	KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples
title_full_unstemmed	KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples
title_sort	katharoseq enables high-throughput microbiome analysis from low-biomass samples
publisher	American Society for Microbiology
publishDate	2018
url	https://doaj.org/article/431a4178ad1346269f6fc3fc3aaaf300
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KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples

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