Environmental and Physiological Factors Affecting High-Throughput Measurements of Bacterial Growth

ABSTRACT Bacterial growth under nutrient-rich and starvation conditions is intrinsically tied to the environmental history and physiological state of the population. While high-throughput technologies have enabled rapid analyses of mutant libraries, technical and biological challenges complicate dat...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Esha Atolia, Spencer Cesar, Heidi A. Arjes, Manohary Rajendram, Handuo Shi, Benjamin D. Knapp, Somya Khare, Andrés Aranda-Díaz, Richard E. Lenski, Kerwyn Casey Huang
Formato: article
Lenguaje:EN
Publicado: American Society for Microbiology 2020
Materias:
Acceso en línea:https://doaj.org/article/7ba8cdbef49643fca248f598ea6e92fd
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
id oai:doaj.org-article:7ba8cdbef49643fca248f598ea6e92fd
record_format dspace
spelling oai:doaj.org-article:7ba8cdbef49643fca248f598ea6e92fd2021-11-15T16:19:08ZEnvironmental and Physiological Factors Affecting High-Throughput Measurements of Bacterial Growth10.1128/mBio.01378-202150-7511https://doaj.org/article/7ba8cdbef49643fca248f598ea6e92fd2020-10-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mBio.01378-20https://doaj.org/toc/2150-7511ABSTRACT Bacterial growth under nutrient-rich and starvation conditions is intrinsically tied to the environmental history and physiological state of the population. While high-throughput technologies have enabled rapid analyses of mutant libraries, technical and biological challenges complicate data collection and interpretation. Here, we present a framework for the execution and analysis of growth measurements with improved accuracy over that of standard approaches. Using this framework, we demonstrate key biological insights that emerge from consideration of culturing conditions and history. We determined that quantification of the background absorbance in each well of a multiwell plate is critical for accurate measurements of maximal growth rate. Using mathematical modeling, we demonstrated that maximal growth rate is dependent on initial cell density, which distorts comparisons across strains with variable lag properties. We established a multiple-passage protocol that alleviates the substantial effects of glycerol on growth in carbon-poor media, and we tracked growth rate-mediated fitness increases observed during a long-term evolution of Escherichia coli in low glucose concentrations. Finally, we showed that growth of Bacillus subtilis in the presence of glycerol induces a long lag in the next passage due to inhibition of a large fraction of the population. Transposon mutagenesis linked this phenotype to the incorporation of glycerol into lipoteichoic acids, revealing a new role for these envelope components in resuming growth after starvation. Together, our investigations underscore the complex physiology of bacteria during bulk passaging and the importance of robust strategies to understand and quantify growth. IMPORTANCE How starved bacteria adapt and multiply under replete nutrient conditions is intimately linked to their history of previous growth, their physiological state, and the surrounding environment. While automated equipment has enabled high-throughput growth measurements, data interpretation and knowledge gaps regarding the determinants of growth kinetics complicate comparisons between strains. Here, we present a framework for growth measurements that improves accuracy and attenuates the effects of growth history. We determined that background absorbance quantification and multiple passaging cycles allow for accurate growth rate measurements even in carbon-poor media, which we used to reveal growth-rate increases during long-term laboratory evolution of Escherichia coli. Using mathematical modeling, we showed that maximum growth rate depends on initial cell density. Finally, we demonstrated that growth of Bacillus subtilis with glycerol inhibits the future growth of most of the population, due to lipoteichoic acid synthesis. These studies highlight the challenges of accurate quantification of bacterial growth behaviors.Esha AtoliaSpencer CesarHeidi A. ArjesManohary RajendramHanduo ShiBenjamin D. KnappSomya KhareAndrés Aranda-DíazRichard E. LenskiKerwyn Casey HuangAmerican Society for Microbiologyarticledensity-dependent growthglycerollag phaselong-term evolution experimentsteichoic acidsMicrobiologyQR1-502ENmBio, Vol 11, Iss 5 (2020)
institution DOAJ
collection DOAJ
language EN
topic density-dependent growth
glycerol
lag phase
long-term evolution experiments
teichoic acids
Microbiology
QR1-502
spellingShingle density-dependent growth
glycerol
lag phase
long-term evolution experiments
teichoic acids
Microbiology
QR1-502
Esha Atolia
Spencer Cesar
Heidi A. Arjes
Manohary Rajendram
Handuo Shi
Benjamin D. Knapp
Somya Khare
Andrés Aranda-Díaz
Richard E. Lenski
Kerwyn Casey Huang
Environmental and Physiological Factors Affecting High-Throughput Measurements of Bacterial Growth
description ABSTRACT Bacterial growth under nutrient-rich and starvation conditions is intrinsically tied to the environmental history and physiological state of the population. While high-throughput technologies have enabled rapid analyses of mutant libraries, technical and biological challenges complicate data collection and interpretation. Here, we present a framework for the execution and analysis of growth measurements with improved accuracy over that of standard approaches. Using this framework, we demonstrate key biological insights that emerge from consideration of culturing conditions and history. We determined that quantification of the background absorbance in each well of a multiwell plate is critical for accurate measurements of maximal growth rate. Using mathematical modeling, we demonstrated that maximal growth rate is dependent on initial cell density, which distorts comparisons across strains with variable lag properties. We established a multiple-passage protocol that alleviates the substantial effects of glycerol on growth in carbon-poor media, and we tracked growth rate-mediated fitness increases observed during a long-term evolution of Escherichia coli in low glucose concentrations. Finally, we showed that growth of Bacillus subtilis in the presence of glycerol induces a long lag in the next passage due to inhibition of a large fraction of the population. Transposon mutagenesis linked this phenotype to the incorporation of glycerol into lipoteichoic acids, revealing a new role for these envelope components in resuming growth after starvation. Together, our investigations underscore the complex physiology of bacteria during bulk passaging and the importance of robust strategies to understand and quantify growth. IMPORTANCE How starved bacteria adapt and multiply under replete nutrient conditions is intimately linked to their history of previous growth, their physiological state, and the surrounding environment. While automated equipment has enabled high-throughput growth measurements, data interpretation and knowledge gaps regarding the determinants of growth kinetics complicate comparisons between strains. Here, we present a framework for growth measurements that improves accuracy and attenuates the effects of growth history. We determined that background absorbance quantification and multiple passaging cycles allow for accurate growth rate measurements even in carbon-poor media, which we used to reveal growth-rate increases during long-term laboratory evolution of Escherichia coli. Using mathematical modeling, we showed that maximum growth rate depends on initial cell density. Finally, we demonstrated that growth of Bacillus subtilis with glycerol inhibits the future growth of most of the population, due to lipoteichoic acid synthesis. These studies highlight the challenges of accurate quantification of bacterial growth behaviors.
format article
author Esha Atolia
Spencer Cesar
Heidi A. Arjes
Manohary Rajendram
Handuo Shi
Benjamin D. Knapp
Somya Khare
Andrés Aranda-Díaz
Richard E. Lenski
Kerwyn Casey Huang
author_facet Esha Atolia
Spencer Cesar
Heidi A. Arjes
Manohary Rajendram
Handuo Shi
Benjamin D. Knapp
Somya Khare
Andrés Aranda-Díaz
Richard E. Lenski
Kerwyn Casey Huang
author_sort Esha Atolia
title Environmental and Physiological Factors Affecting High-Throughput Measurements of Bacterial Growth
title_short Environmental and Physiological Factors Affecting High-Throughput Measurements of Bacterial Growth
title_full Environmental and Physiological Factors Affecting High-Throughput Measurements of Bacterial Growth
title_fullStr Environmental and Physiological Factors Affecting High-Throughput Measurements of Bacterial Growth
title_full_unstemmed Environmental and Physiological Factors Affecting High-Throughput Measurements of Bacterial Growth
title_sort environmental and physiological factors affecting high-throughput measurements of bacterial growth
publisher American Society for Microbiology
publishDate 2020
url https://doaj.org/article/7ba8cdbef49643fca248f598ea6e92fd
work_keys_str_mv AT eshaatolia environmentalandphysiologicalfactorsaffectinghighthroughputmeasurementsofbacterialgrowth
AT spencercesar environmentalandphysiologicalfactorsaffectinghighthroughputmeasurementsofbacterialgrowth
AT heidiaarjes environmentalandphysiologicalfactorsaffectinghighthroughputmeasurementsofbacterialgrowth
AT manoharyrajendram environmentalandphysiologicalfactorsaffectinghighthroughputmeasurementsofbacterialgrowth
AT handuoshi environmentalandphysiologicalfactorsaffectinghighthroughputmeasurementsofbacterialgrowth
AT benjamindknapp environmentalandphysiologicalfactorsaffectinghighthroughputmeasurementsofbacterialgrowth
AT somyakhare environmentalandphysiologicalfactorsaffectinghighthroughputmeasurementsofbacterialgrowth
AT andresarandadiaz environmentalandphysiologicalfactorsaffectinghighthroughputmeasurementsofbacterialgrowth
AT richardelenski environmentalandphysiologicalfactorsaffectinghighthroughputmeasurementsofbacterialgrowth
AT kerwyncaseyhuang environmentalandphysiologicalfactorsaffectinghighthroughputmeasurementsofbacterialgrowth
_version_ 1718426909785718784