Data-Driven Models Reveal Mutant Cell Behaviors Important for Myxobacterial Aggregation

ABSTRACT Single mutations frequently alter several aspects of cell behavior but rarely reveal whether a particular statistically significant change is biologically significant. To determine which behavioral changes are most important for multicellular self-organization, we devised a new methodology...

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Autores principales:	Zhaoyang Zhang, Christopher R. Cotter, Zhe Lyu, Lawrence J. Shimkets, Oleg A. Igoshin
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2020
Materias:	self-organization development modeling Myxococcus xanthus developmental biology mathematical modeling Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/2269b62faf9e4ff69dc69a52084ab004
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spelling	oai:doaj.org-article:2269b62faf9e4ff69dc69a52084ab0042021-12-02T19:47:35ZData-Driven Models Reveal Mutant Cell Behaviors Important for Myxobacterial Aggregation10.1128/mSystems.00518-202379-5077https://doaj.org/article/2269b62faf9e4ff69dc69a52084ab0042020-08-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00518-20https://doaj.org/toc/2379-5077ABSTRACT Single mutations frequently alter several aspects of cell behavior but rarely reveal whether a particular statistically significant change is biologically significant. To determine which behavioral changes are most important for multicellular self-organization, we devised a new methodology using Myxococcus xanthus as a model system. During development, myxobacteria coordinate their movement to aggregate into spore-filled fruiting bodies. We investigate how aggregation is restored in two mutants, csgA and pilC, that cannot aggregate unless mixed with wild-type (WT) cells. To this end, we use cell tracking to follow the movement of fluorescently labeled cells in combination with data-driven agent-based modeling. The results indicate that just like WT cells, both mutants bias their movement toward aggregates and reduce motility inside aggregates. However, several aspects of mutant behavior remain uncorrected by WT, demonstrating that perfect recreation of WT behavior is unnecessary. In fact, synergies between errant behaviors can make aggregation robust. IMPORTANCE Self-organization into spatial patterns is evident in many multicellular phenomena. Even for the best-studied systems, our ability to dissect the mechanisms driving coordinated cell movement is limited. While genetic approaches can identify mutations perturbing multicellular patterns, the diverse nature of the signaling cues coupled to significant heterogeneity of individual cell behavior impedes our ability to mechanistically connect genes with phenotype. Small differences in the behaviors of mutant strains could be irrelevant or could sometimes lead to large differences in the emergent patterns. Here, we investigate rescue of multicellular aggregation in two mutant strains of Myxococcus xanthus mixed with wild-type cells. The results demonstrate how careful quantification of cell behavior coupled to data-driven modeling can identify specific motility features responsible for cell aggregation and thereby reveal important synergies and compensatory mechanisms. Notably, mutant cells do not need to precisely recreate wild-type behaviors to achieve complete aggregation.Zhaoyang ZhangChristopher R. CotterZhe LyuLawrence J. ShimketsOleg A. IgoshinAmerican Society for Microbiologyarticleself-organizationdevelopmentmodelingMyxococcus xanthusdevelopmental biologymathematical modelingMicrobiologyQR1-502ENmSystems, Vol 5, Iss 4 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	self-organization development modeling Myxococcus xanthus developmental biology mathematical modeling Microbiology QR1-502
spellingShingle	self-organization development modeling Myxococcus xanthus developmental biology mathematical modeling Microbiology QR1-502 Zhaoyang Zhang Christopher R. Cotter Zhe Lyu Lawrence J. Shimkets Oleg A. Igoshin Data-Driven Models Reveal Mutant Cell Behaviors Important for Myxobacterial Aggregation
description	ABSTRACT Single mutations frequently alter several aspects of cell behavior but rarely reveal whether a particular statistically significant change is biologically significant. To determine which behavioral changes are most important for multicellular self-organization, we devised a new methodology using Myxococcus xanthus as a model system. During development, myxobacteria coordinate their movement to aggregate into spore-filled fruiting bodies. We investigate how aggregation is restored in two mutants, csgA and pilC, that cannot aggregate unless mixed with wild-type (WT) cells. To this end, we use cell tracking to follow the movement of fluorescently labeled cells in combination with data-driven agent-based modeling. The results indicate that just like WT cells, both mutants bias their movement toward aggregates and reduce motility inside aggregates. However, several aspects of mutant behavior remain uncorrected by WT, demonstrating that perfect recreation of WT behavior is unnecessary. In fact, synergies between errant behaviors can make aggregation robust. IMPORTANCE Self-organization into spatial patterns is evident in many multicellular phenomena. Even for the best-studied systems, our ability to dissect the mechanisms driving coordinated cell movement is limited. While genetic approaches can identify mutations perturbing multicellular patterns, the diverse nature of the signaling cues coupled to significant heterogeneity of individual cell behavior impedes our ability to mechanistically connect genes with phenotype. Small differences in the behaviors of mutant strains could be irrelevant or could sometimes lead to large differences in the emergent patterns. Here, we investigate rescue of multicellular aggregation in two mutant strains of Myxococcus xanthus mixed with wild-type cells. The results demonstrate how careful quantification of cell behavior coupled to data-driven modeling can identify specific motility features responsible for cell aggregation and thereby reveal important synergies and compensatory mechanisms. Notably, mutant cells do not need to precisely recreate wild-type behaviors to achieve complete aggregation.
format	article
author	Zhaoyang Zhang Christopher R. Cotter Zhe Lyu Lawrence J. Shimkets Oleg A. Igoshin
author_facet	Zhaoyang Zhang Christopher R. Cotter Zhe Lyu Lawrence J. Shimkets Oleg A. Igoshin
author_sort	Zhaoyang Zhang
title	Data-Driven Models Reveal Mutant Cell Behaviors Important for Myxobacterial Aggregation
title_short	Data-Driven Models Reveal Mutant Cell Behaviors Important for Myxobacterial Aggregation
title_full	Data-Driven Models Reveal Mutant Cell Behaviors Important for Myxobacterial Aggregation
title_fullStr	Data-Driven Models Reveal Mutant Cell Behaviors Important for Myxobacterial Aggregation
title_full_unstemmed	Data-Driven Models Reveal Mutant Cell Behaviors Important for Myxobacterial Aggregation
title_sort	data-driven models reveal mutant cell behaviors important for myxobacterial aggregation
publisher	American Society for Microbiology
publishDate	2020
url	https://doaj.org/article/2269b62faf9e4ff69dc69a52084ab004
work_keys_str_mv	AT zhaoyangzhang datadrivenmodelsrevealmutantcellbehaviorsimportantformyxobacterialaggregation AT christopherrcotter datadrivenmodelsrevealmutantcellbehaviorsimportantformyxobacterialaggregation AT zhelyu datadrivenmodelsrevealmutantcellbehaviorsimportantformyxobacterialaggregation AT lawrencejshimkets datadrivenmodelsrevealmutantcellbehaviorsimportantformyxobacterialaggregation AT olegaigoshin datadrivenmodelsrevealmutantcellbehaviorsimportantformyxobacterialaggregation
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Data-Driven Models Reveal Mutant Cell Behaviors Important for Myxobacterial Aggregation

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