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Refined Quantification of Infection Bottlenecks and Pathogen Dissemination with STAMPR

Pathogen population dynamics during infection are critical determinants of infection susceptibility and define patterns of dissemination. However, deciphering these dynamics, particularly founding population sizes in host organs and patterns of dissemination between organs, is difficult because meas...

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Autores principales: Hullahalli, Karthik, Pritchard, Justin R., Waldor, Matthew K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8407386/
https://www.ncbi.nlm.nih.gov/pubmed/34402636
http://dx.doi.org/10.1128/mSystems.00887-21
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author Hullahalli, Karthik
Pritchard, Justin R.
Waldor, Matthew K.
author_facet Hullahalli, Karthik
Pritchard, Justin R.
Waldor, Matthew K.
author_sort Hullahalli, Karthik
collection PubMed
description Pathogen population dynamics during infection are critical determinants of infection susceptibility and define patterns of dissemination. However, deciphering these dynamics, particularly founding population sizes in host organs and patterns of dissemination between organs, is difficult because measuring bacterial burden alone is insufficient to observe these patterns. Introduction of allelic diversity into otherwise identical bacteria using DNA barcodes enables sequencing-based measurements of these parameters, in a method known as STAMP (Sequence Tag-based Analysis of Microbial Populations). However, bacteria often undergo unequal expansion within host organs, resulting in marked differences in the frequencies of barcodes in input and output libraries. Here, we show that these differences confound STAMP-based analyses of founding population sizes and dissemination patterns. We present STAMPR, a successor to STAMP, which accounts for such population expansions. Using data from systemic infection of barcoded extraintestinal pathogenic E. coli, we show that this new framework, along with the metrics it yields, enhances the fidelity of measurements of bottlenecks and dissemination patterns. STAMPR was also validated on an independent barcoded Pseudomonas aeruginosa data set, uncovering new patterns of dissemination within the data. This framework (available at https://github.com/hullahalli/stampr_rtisan), when coupled with barcoded data sets, enables a more complete assessment of within-host bacterial population dynamics. IMPORTANCE Barcoded bacteria are often employed to monitor pathogen population dynamics during infection. The accuracy of these measurements is diminished by unequal bacterial expansion rates. Here, we develop computational tools to circumvent this limitation and establish additional metrics that collectively enhance the fidelity of measuring within-host pathogen founding population sizes and dissemination patterns. These new tools will benefit future studies of the dynamics of pathogens and symbionts within their respective hosts and may have additional barcode-based applications beyond host-microbe interactions.
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spelling pubmed-84073862021-09-09 Refined Quantification of Infection Bottlenecks and Pathogen Dissemination with STAMPR Hullahalli, Karthik Pritchard, Justin R. Waldor, Matthew K. mSystems Methods and Protocols Pathogen population dynamics during infection are critical determinants of infection susceptibility and define patterns of dissemination. However, deciphering these dynamics, particularly founding population sizes in host organs and patterns of dissemination between organs, is difficult because measuring bacterial burden alone is insufficient to observe these patterns. Introduction of allelic diversity into otherwise identical bacteria using DNA barcodes enables sequencing-based measurements of these parameters, in a method known as STAMP (Sequence Tag-based Analysis of Microbial Populations). However, bacteria often undergo unequal expansion within host organs, resulting in marked differences in the frequencies of barcodes in input and output libraries. Here, we show that these differences confound STAMP-based analyses of founding population sizes and dissemination patterns. We present STAMPR, a successor to STAMP, which accounts for such population expansions. Using data from systemic infection of barcoded extraintestinal pathogenic E. coli, we show that this new framework, along with the metrics it yields, enhances the fidelity of measurements of bottlenecks and dissemination patterns. STAMPR was also validated on an independent barcoded Pseudomonas aeruginosa data set, uncovering new patterns of dissemination within the data. This framework (available at https://github.com/hullahalli/stampr_rtisan), when coupled with barcoded data sets, enables a more complete assessment of within-host bacterial population dynamics. IMPORTANCE Barcoded bacteria are often employed to monitor pathogen population dynamics during infection. The accuracy of these measurements is diminished by unequal bacterial expansion rates. Here, we develop computational tools to circumvent this limitation and establish additional metrics that collectively enhance the fidelity of measuring within-host pathogen founding population sizes and dissemination patterns. These new tools will benefit future studies of the dynamics of pathogens and symbionts within their respective hosts and may have additional barcode-based applications beyond host-microbe interactions. American Society for Microbiology 2021-08-17 /pmc/articles/PMC8407386/ /pubmed/34402636 http://dx.doi.org/10.1128/mSystems.00887-21 Text en Copyright © 2021 Hullahalli et al. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Methods and Protocols
Hullahalli, Karthik
Pritchard, Justin R.
Waldor, Matthew K.
Refined Quantification of Infection Bottlenecks and Pathogen Dissemination with STAMPR
title Refined Quantification of Infection Bottlenecks and Pathogen Dissemination with STAMPR
title_full Refined Quantification of Infection Bottlenecks and Pathogen Dissemination with STAMPR
title_fullStr Refined Quantification of Infection Bottlenecks and Pathogen Dissemination with STAMPR
title_full_unstemmed Refined Quantification of Infection Bottlenecks and Pathogen Dissemination with STAMPR
title_short Refined Quantification of Infection Bottlenecks and Pathogen Dissemination with STAMPR
title_sort refined quantification of infection bottlenecks and pathogen dissemination with stampr
topic Methods and Protocols
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8407386/
https://www.ncbi.nlm.nih.gov/pubmed/34402636
http://dx.doi.org/10.1128/mSystems.00887-21
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