Quantifying Live Microbial Load in Human Saliva Samples over Time Reveals Stable Composition and Dynamic Load

ABSTRACT Evaluating microbial community composition through next-generation sequencing has become increasingly accessible. However, metagenomic sequencing data sets provide researchers with only a snapshot of a dynamic ecosystem and do not provide information about the total microbial number, or loa...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Clarisse Marotz, James T. Morton, Perris Navarro, Joanna Coker, Pedro Belda-Ferre, Rob Knight, Karsten Zengler
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2021
Materias:	16S sequencing flow cytometry longitudinal microbial load microbiome propidium monoazide (PMA) Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/296026916dac47c2862614df68d4258f
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:296026916dac47c2862614df68d4258f
record_format	dspace
spelling	oai:doaj.org-article:296026916dac47c2862614df68d4258f2021-12-02T17:07:26ZQuantifying Live Microbial Load in Human Saliva Samples over Time Reveals Stable Composition and Dynamic Load10.1128/mSystems.01182-202379-5077https://doaj.org/article/296026916dac47c2862614df68d4258f2021-02-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.01182-20https://doaj.org/toc/2379-5077ABSTRACT Evaluating microbial community composition through next-generation sequencing has become increasingly accessible. However, metagenomic sequencing data sets provide researchers with only a snapshot of a dynamic ecosystem and do not provide information about the total microbial number, or load, of a sample. Additionally, DNA can be detected long after a microorganism is dead, making it unsafe to assume that all microbial sequences detected in a community came from living organisms. By combining relic DNA removal by propidium monoazide (PMA) with microbial quantification with flow cytometry, we present a novel workflow to quantify live microbial load in parallel with metagenomic sequencing. We applied this method to unstimulated saliva samples, which can easily be collected longitudinally and standardized by passive collection time. We found that the number of live microorganisms detected in saliva was inversely correlated with salivary flow rate and fluctuated by an order of magnitude throughout the day in healthy individuals. In an acute perturbation experiment, alcohol-free mouthwash resulted in a massive decrease in live bacteria, which would have been missed if we did not consider dead cell signal. While removing relic DNA from saliva samples did not greatly impact the microbial composition, it did increase our resolution among samples collected over time. These results provide novel insight into the dynamic nature of host-associated microbiomes and underline the importance of applying scale-invariant tools in the analysis of next-generation sequencing data sets. IMPORTANCE Human microbiomes are dynamic ecosystems often composed of hundreds of unique microbial taxa. To detect fluctuations over time in the human oral microbiome, we developed a novel workflow to quantify live microbial cells with flow cytometry in parallel with next-generation sequencing, and applied this method to over 150 unstimulated, timed saliva samples. Microbial load was inversely correlated with salivary flow rate and fluctuated by an order of magnitude within a single participant throughout the day. Removing relic DNA improved our ability to distinguish samples over time and revealed that the percentage of sequenced bacteria in a given saliva sample that are alive can range from nearly 0% up to 100% throughout a typical day. These findings highlight the dynamic ecosystem of the human oral microbiome and the benefit of removing relic DNA signals in longitudinal microbiome study designs.Clarisse MarotzJames T. MortonPerris NavarroJoanna CokerPedro Belda-FerreRob KnightKarsten ZenglerAmerican Society for Microbiologyarticle16S sequencingflow cytometrylongitudinalmicrobial loadmicrobiomepropidium monoazide (PMA)MicrobiologyQR1-502ENmSystems, Vol 6, Iss 1 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	16S sequencing flow cytometry longitudinal microbial load microbiome propidium monoazide (PMA) Microbiology QR1-502
spellingShingle	16S sequencing flow cytometry longitudinal microbial load microbiome propidium monoazide (PMA) Microbiology QR1-502 Clarisse Marotz James T. Morton Perris Navarro Joanna Coker Pedro Belda-Ferre Rob Knight Karsten Zengler Quantifying Live Microbial Load in Human Saliva Samples over Time Reveals Stable Composition and Dynamic Load
description	ABSTRACT Evaluating microbial community composition through next-generation sequencing has become increasingly accessible. However, metagenomic sequencing data sets provide researchers with only a snapshot of a dynamic ecosystem and do not provide information about the total microbial number, or load, of a sample. Additionally, DNA can be detected long after a microorganism is dead, making it unsafe to assume that all microbial sequences detected in a community came from living organisms. By combining relic DNA removal by propidium monoazide (PMA) with microbial quantification with flow cytometry, we present a novel workflow to quantify live microbial load in parallel with metagenomic sequencing. We applied this method to unstimulated saliva samples, which can easily be collected longitudinally and standardized by passive collection time. We found that the number of live microorganisms detected in saliva was inversely correlated with salivary flow rate and fluctuated by an order of magnitude throughout the day in healthy individuals. In an acute perturbation experiment, alcohol-free mouthwash resulted in a massive decrease in live bacteria, which would have been missed if we did not consider dead cell signal. While removing relic DNA from saliva samples did not greatly impact the microbial composition, it did increase our resolution among samples collected over time. These results provide novel insight into the dynamic nature of host-associated microbiomes and underline the importance of applying scale-invariant tools in the analysis of next-generation sequencing data sets. IMPORTANCE Human microbiomes are dynamic ecosystems often composed of hundreds of unique microbial taxa. To detect fluctuations over time in the human oral microbiome, we developed a novel workflow to quantify live microbial cells with flow cytometry in parallel with next-generation sequencing, and applied this method to over 150 unstimulated, timed saliva samples. Microbial load was inversely correlated with salivary flow rate and fluctuated by an order of magnitude within a single participant throughout the day. Removing relic DNA improved our ability to distinguish samples over time and revealed that the percentage of sequenced bacteria in a given saliva sample that are alive can range from nearly 0% up to 100% throughout a typical day. These findings highlight the dynamic ecosystem of the human oral microbiome and the benefit of removing relic DNA signals in longitudinal microbiome study designs.
format	article
author	Clarisse Marotz James T. Morton Perris Navarro Joanna Coker Pedro Belda-Ferre Rob Knight Karsten Zengler
author_facet	Clarisse Marotz James T. Morton Perris Navarro Joanna Coker Pedro Belda-Ferre Rob Knight Karsten Zengler
author_sort	Clarisse Marotz
title	Quantifying Live Microbial Load in Human Saliva Samples over Time Reveals Stable Composition and Dynamic Load
title_short	Quantifying Live Microbial Load in Human Saliva Samples over Time Reveals Stable Composition and Dynamic Load
title_full	Quantifying Live Microbial Load in Human Saliva Samples over Time Reveals Stable Composition and Dynamic Load
title_fullStr	Quantifying Live Microbial Load in Human Saliva Samples over Time Reveals Stable Composition and Dynamic Load
title_full_unstemmed	Quantifying Live Microbial Load in Human Saliva Samples over Time Reveals Stable Composition and Dynamic Load
title_sort	quantifying live microbial load in human saliva samples over time reveals stable composition and dynamic load
publisher	American Society for Microbiology
publishDate	2021
url	https://doaj.org/article/296026916dac47c2862614df68d4258f
work_keys_str_mv	AT clarissemarotz quantifyinglivemicrobialloadinhumansalivasamplesovertimerevealsstablecompositionanddynamicload AT jamestmorton quantifyinglivemicrobialloadinhumansalivasamplesovertimerevealsstablecompositionanddynamicload AT perrisnavarro quantifyinglivemicrobialloadinhumansalivasamplesovertimerevealsstablecompositionanddynamicload AT joannacoker quantifyinglivemicrobialloadinhumansalivasamplesovertimerevealsstablecompositionanddynamicload AT pedrobeldaferre quantifyinglivemicrobialloadinhumansalivasamplesovertimerevealsstablecompositionanddynamicload AT robknight quantifyinglivemicrobialloadinhumansalivasamplesovertimerevealsstablecompositionanddynamicload AT karstenzengler quantifyinglivemicrobialloadinhumansalivasamplesovertimerevealsstablecompositionanddynamicload
_version_	1718381544214626304

Quantifying Live Microbial Load in Human Saliva Samples over Time Reveals Stable Composition and Dynamic Load

Ejemplares similares