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AMiGA: Software for Automated Analysis of Microbial Growth Assays
The analysis of microbial growth is one of the central methods in the field of microbiology. Microbial growth dynamics can be characterized by meaningful parameters, including carrying capacity, exponential growth rate, and growth lag. However, microbial assays with clinical isolates, fastidious org...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Microbiology
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8409736/ https://www.ncbi.nlm.nih.gov/pubmed/34254821 http://dx.doi.org/10.1128/mSystems.00508-21 |
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author | Midani, Firas S. Collins, James Britton, Robert A. |
author_facet | Midani, Firas S. Collins, James Britton, Robert A. |
author_sort | Midani, Firas S. |
collection | PubMed |
description | The analysis of microbial growth is one of the central methods in the field of microbiology. Microbial growth dynamics can be characterized by meaningful parameters, including carrying capacity, exponential growth rate, and growth lag. However, microbial assays with clinical isolates, fastidious organisms, or microbes under stress often produce atypical growth shapes that do not follow the classical microbial growth pattern. Here, we introduce the analysis of microbial growth assays (AMiGA) software, which streamlines the analysis of growth curves without any assumptions about their shapes. AMiGA can pool replicates of growth curves and infer summary statistics for biologically meaningful growth parameters. In addition, AMiGA can quantify death phases and characterize diauxic shifts. It can also statistically test for differential growth under distinct experimental conditions. Altogether, AMiGA streamlines the organization, analysis, and visualization of microbial growth assays. IMPORTANCE Our current understanding of microbial physiology relies on the simple method of measuring microbial populations’ sizes over time and under different conditions. Many advances have increased the throughput of those assays and enabled the study of nonlab-adapted microbes under diverse conditions that widely affect their growth dynamics. Our software provides an all-in-one tool for estimating the growth parameters of microbial cultures and testing for differential growth in a high-throughput and user-friendly fashion without any underlying assumptions about how microbes respond to their growth conditions. |
format | Online Article Text |
id | pubmed-8409736 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American Society for Microbiology |
record_format | MEDLINE/PubMed |
spelling | pubmed-84097362021-09-09 AMiGA: Software for Automated Analysis of Microbial Growth Assays Midani, Firas S. Collins, James Britton, Robert A. mSystems Methods and Protocols The analysis of microbial growth is one of the central methods in the field of microbiology. Microbial growth dynamics can be characterized by meaningful parameters, including carrying capacity, exponential growth rate, and growth lag. However, microbial assays with clinical isolates, fastidious organisms, or microbes under stress often produce atypical growth shapes that do not follow the classical microbial growth pattern. Here, we introduce the analysis of microbial growth assays (AMiGA) software, which streamlines the analysis of growth curves without any assumptions about their shapes. AMiGA can pool replicates of growth curves and infer summary statistics for biologically meaningful growth parameters. In addition, AMiGA can quantify death phases and characterize diauxic shifts. It can also statistically test for differential growth under distinct experimental conditions. Altogether, AMiGA streamlines the organization, analysis, and visualization of microbial growth assays. IMPORTANCE Our current understanding of microbial physiology relies on the simple method of measuring microbial populations’ sizes over time and under different conditions. Many advances have increased the throughput of those assays and enabled the study of nonlab-adapted microbes under diverse conditions that widely affect their growth dynamics. Our software provides an all-in-one tool for estimating the growth parameters of microbial cultures and testing for differential growth in a high-throughput and user-friendly fashion without any underlying assumptions about how microbes respond to their growth conditions. American Society for Microbiology 2021-07-13 /pmc/articles/PMC8409736/ /pubmed/34254821 http://dx.doi.org/10.1128/mSystems.00508-21 Text en Copyright © 2021 Midani 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 Midani, Firas S. Collins, James Britton, Robert A. AMiGA: Software for Automated Analysis of Microbial Growth Assays |
title | AMiGA: Software for Automated Analysis of Microbial Growth Assays |
title_full | AMiGA: Software for Automated Analysis of Microbial Growth Assays |
title_fullStr | AMiGA: Software for Automated Analysis of Microbial Growth Assays |
title_full_unstemmed | AMiGA: Software for Automated Analysis of Microbial Growth Assays |
title_short | AMiGA: Software for Automated Analysis of Microbial Growth Assays |
title_sort | amiga: software for automated analysis of microbial growth assays |
topic | Methods and Protocols |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8409736/ https://www.ncbi.nlm.nih.gov/pubmed/34254821 http://dx.doi.org/10.1128/mSystems.00508-21 |
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