scholarly journals A mechanism for migrating bacterial populations to non-genetically adapt to new environments

2021 ◽  
Author(s):  
Henry H Mattingly ◽  
Thierry Emonet
Keyword(s):  
Collective Behavior ◽  
Group Composition ◽  
Phenotypic Diversity ◽  
Population Expansion ◽  
Migration Speed ◽  
Diverse Population ◽  
Genetic Inheritance ◽  
Bacterial Populations ◽  
Physical Environments ◽  
Varying Environments

Populations of chemotactic bacteria can rapidly expand into new territory by consuming and chasing an attractant cue in the environment, increasing the population's overall growth in nutrient-rich environments. Although the migrating fronts driving this expansion contain cells of multiple swimming phenotypes, the consequences of non-genetic diversity for population expansion are unknown. Here, through theory and simulations, we predict that expanding populations non-genetically adapt their phenotype composition to migrate effectively through multiple physical environments. Swimming phenotypes in the migrating front are spatially sorted by chemotactic performance, but the mapping from phenotype to performance depends on the environment. Therefore, phenotypes that perform poorly localize to the back of the group, causing them to selectively fall behind. Over cell divisions, the group composition dynamically enriches for high-performers, enhancing migration speed and overall growth. Furthermore, non-genetic inheritance controls a trade-off between large composition shifts and slow responsiveness to new environments, enabling a diverse population to out-perform a non-diverse one in varying environments. These results demonstrate that phenotypic diversity and collective behavior can synergize to produce emergent functionalities. Non-genetic inheritance may generically enable bacterial populations to transiently adapt to new situations without mutations, emphasizing that genotype-to-phenotype mappings are dynamic and context-dependent.

scholarly journals PaReBrick: PArallel REarrangements and BReaks identification toolkit

2021 ◽  
Author(s):  
Alexey Zabelkin ◽  
Yulia Yakovleva ◽  
Olga Bochkareva ◽  
Nikita Alexeev
Keyword(s):  
Antigenic Variation ◽  
Phenotypic Diversity ◽  
Genome Rearrangements ◽  
Supplementary Information ◽  
High Plasticity ◽  
Bacterial Strains ◽  
Bacterial Genomes ◽  
Phyletic Pattern ◽  
Bacterial Populations ◽  
Different Strains

Abstract Motivation High plasticity of bacterial genomes is provided by numerous mechanisms including horizontal gene transfer and recombination via numerous flanking repeats. Genome rearrangements such as inversions, deletions, insertions, and duplications may independently occur in different strains, providing parallel adaptation or phenotypic diversity. Specifically, such rearrangements might be responsible for virulence, antibiotic resistance, and antigenic variation. However, identification of such events requires laborious manual inspection and verification of phyletic pattern consistency. Results Here we define the term “parallel rearrangements” as events that occur independently in phylogenetically distant bacterial strains and present a formalization of the problem of parallel rearrangements calling. We implement an algorithmic solution for the identification of parallel rearrangements in bacterial populations as a tool PaReBrick. The tool takes a collection of strains represented as a sequence of oriented synteny blocks and a phylogenetic tree as input data. It identifies rearrangements, tests them for consistency with a tree, and sorts the events by their parallelism score. The tool provides diagrams of the neighbors for each block of interest, allowing the detection of horizontally transferred blocks or their extra copies and the inversions in which copied blocks are involved.We demonstrated PaReBrick’s efficiency and accuracy and showed its potential to detect genome rearrangements responsible for pathogenicity and adaptation in bacterial genomes. Availability PaReBrick is written in Python and is available on GitHub https://github.com/ctlab/parallelrearrangements Supplementary information Supplementary data are available at Bioinformatics online.

Boundary-Driven Emergent Spatiotemporal Order in Growing Microbial Colonies

2018 ◽  
Author(s):  
Bhargav R. Karamched ◽  
William Ott ◽  
Ilya Timofeyev ◽  
Razan N. Alnahhas ◽  
Matthew R. Bennett ◽  
...  
Keyword(s):  
Collective Behavior ◽  
Mean Field ◽  
Population Level ◽  
Field Approximation ◽  
Cell Interactions ◽  
Boundary Effects ◽  
Mean Field Approximation ◽  
Bacterial Populations ◽  
Moran Model ◽  
Cell Cell

We introduce a tractable stochastic spatial Moran model to explain experimentally-observed patterns of rod-shaped bacteria growing in rectangular microfluidic traps. Our model shows that spatial patterns can arise as a result of a tug-of-war between boundary effects and modulations of growth rate due to cell-cell interactions. Cells align parallel to the long side of the trap when boundary effects dominate. However, when the magnitude of cell-cell interactions exceeds a critical value, cells align orthogonally to the trap’s long side. Our model is analytically tractable, and completely solvable under a mean-field approximation. This allows us to elucidate the mechanisms that govern the formation of population-level patterns. The model can be easily extended to examine various types of interactions that can shape the collective behavior in bacterial populations.

scholarly journals Genotypic and Phenotypic Diversity among Induced, stx2-Carrying Bacteriophages from Environmental Escherichia coli Strains

2008 ◽  
Vol 75 (2) ◽  
pp. 329-336 ◽  
Author(s):  
Cristina García-Aljaro ◽  
Maite Muniesa ◽  
Juan Jofre ◽  
Anicet R. Blanch
Keyword(s):  
Escherichia Coli ◽  
Shiga Toxin ◽  
Phenotypic Diversity ◽  
Morphological Diversity ◽  
Lytic Cycle ◽  
Animal Origin ◽  
Bacterial Populations ◽  
Shiga Toxin 2 ◽  
Different Strains ◽  
High Level

ABSTRACT Shiga toxin 2 (stx 2) gene-carrying bacteriophages have been shown to convert Escherichia coli strains to Shiga toxin-producing Escherichia coli (STEC). In this study, 79 E. coli strains belonging to 35 serotypes isolated from wastewaters of both human and animal origin were examined for the presence of stx2 -carrying bacteriophages in their genomes. The lytic cycle of the bacteriophages was induced by mitomycin, and the bacteriophage fraction was isolated and used for morphological and genetic characterization. The induced bacteriophages showed morphological diversity, as well as restriction fragment length polymorphism variation, in the different strains belonging to different serotypes. The ability to infect new hosts was highly variable, although most of the induced phages infected Shigella sonnei host strain 866. In summary, in spite of carrying either the same or different stx 2 variants and in spite of the fact that they were isolated from strains belonging to the same or different serotypes, the induced bacteriophages were highly variable. The high level of diversity and the great infectious capacity of these phages could enhance the spread of the stx 2 gene and variants of this gene among different bacterial populations in environments to which humans may be exposed.

scholarly journals Emergent behavioral organization in heterogeneous groups of a social insect

2020 ◽  
Author(s):  
Yuko Ulrich ◽  
Mari Kawakatsu ◽  
Christopher K. Tokita ◽  
Jonathan Saragosti ◽  
Vikram Chandra ◽  
...  
Keyword(s):  
Social Insects ◽  
Collective Behavior ◽  
Social Insect ◽  
Group Composition ◽  
Social Systems ◽  
Social Groups ◽  
Foraging Efficiency ◽  
Behavioral Organization ◽  
Theoretical Approaches ◽  
Mixed Groups

AbstractThe composition of social groups has profound effects on their function, from collective decision-making to foraging efficiency. But few social systems afford sufficient control over group composition to precisely quantify its effects on individual and collective behavior. Here we combine experimental and theoretical approaches to study the effect of group composition on individual behavior and division of labor (DOL) in a social insect. Experimentally, we use automated behavioral tracking to monitor 120 colonies of the clonal raider ant, Ooceraea biroi, with controlled variation in three key correlates of social insect behavior: genotype, age, and morphology. We find that each of these sources of heterogeneity generates a distinct pattern of behavioral organization, including the amplification or dampening of inherent behavioral differences in colonies with mixed types. Theoretically, we use a well-studied model of DOL to explore potential mechanisms underlying the experimental findings. We find that the simplest implementation of this model, which assumes that heterogeneous individuals differ only in response thresholds, could only partially recapitulate the empirically observed patterns of behavior. However, the full spectrum of observed phenomena was recapitulated by extending the model to incorporate two factors that are biologically meaningful but theoretically rarely considered: variation among workers in task performance efficiency and among larvae in task demand. Our results thus show that different sources of heterogeneity within social groups can generate different, sometimes non-intuitive, behavioral effects, but that relatively simple models can capture these dynamics and thereby begin to elucidate the basic organizational principles of DOL in social insects.Significance StatementWhen individuals interact in an aggregate, many factors that are not known a priori affect group dynamics. A social group will therefore show emergent properties that cannot easily be predicted from how its members behave in isolation. This problem is exacerbated in mixed groups, where different individuals have different behavioral tendencies. Here we describe different facets of collective behavioral organization in mixed groups of the clonal raider ant, and show that a simple theoretical model can capture even non-intuitive aspects of the behavioral data. These results begin to reveal the principles underlying emergent behavioral organization in social insects. Importantly, our insights might apply to complex biological systems more generally and be used to help engineer collective behavior in artificial systems.

scholarly journals Programmed Heterogeneity: Epigenetic Mechanisms in Bacteria

2013 ◽  
Vol 288 (20) ◽  
pp. 13929-13935 ◽  
Author(s):  
Josep Casadesús ◽  
David A. Low
Keyword(s):  
Dna Methylation ◽  
Single Cell Analysis ◽  
Phenotypic Diversity ◽  
Feedback Loops ◽  
Harsh Environments ◽  
Epigenetic Mechanisms ◽  
Cell Analysis ◽  
Bacterial Populations ◽  
Methylation Patterns ◽  
Simple Feedback

Contrary to the traditional view that bacterial populations are clonal, single-cell analysis reveals that phenotypic heterogeneity is common in bacteria. Formation of distinct bacterial lineages appears to be frequent during adaptation to harsh environments, including the colonization of animals by bacterial pathogens. Formation of bacterial subpopulations is often controlled by epigenetic mechanisms that generate inheritable phenotypic diversity without altering the DNA sequence. Such mechanisms are diverse, ranging from relatively simple feedback loops to complex self-perpetuating DNA methylation patterns.

scholarly journals Evolutionary learning of adaptation to varying environments through a transgenerational feedback

2016 ◽  
Vol 113 (40) ◽  
pp. 11266-11271 ◽  
Author(s):  
BingKan Xue ◽  
Stanislas Leibler
Keyword(s):  
Phenotypic Diversity ◽  
Epigenetic Inheritance ◽  
Model Organisms ◽  
Evolutionary Learning ◽  
Bet Hedging ◽  
Learning Mechanism ◽  
Environmental Variations ◽  
Varying Environments ◽  
Varying Environment

Organisms can adapt to a randomly varying environment by creating phenotypic diversity in their population, a phenomenon often referred to as “bet hedging.” The favorable level of phenotypic diversity depends on the statistics of environmental variations over timescales of many generations. Could organisms gather such long-term environmental information to adjust their phenotypic diversity? We show that this process can be achieved through a simple and general learning mechanism based on a transgenerational feedback: The phenotype of the parent is progressively reinforced in the distribution of phenotypes among the offspring. The molecular basis of this learning mechanism could be searched for in model organisms showing epigenetic inheritance.

scholarly journals Role of bacterial persistence in spatial population expansion

2021 ◽  
Author(s):  
Pintu Patra ◽  
Stefan Klumpp
Keyword(s):  
Population Expansion ◽  
Leading Edge ◽  
Bacterial Persistence ◽  
Persister Cells ◽  
Fitness Advantage ◽  
Expansion Speed ◽  
Phenotype Switching ◽  
Stochastic Switching ◽  
Varying Environments ◽  
Spatially Varying

Bacterial persistence, tolerance to antibiotics via stochastic phenotype switching provides a survival strategy and a fitness advantage in temporally fluctuating environments. Here we study its possible benefit in spatially varying environments using a Fisher wave approach. We study the spatial expansion of a population with stochastic switching between two phenotypes in spatially homogeneous conditions and in the presence of an antibiotic barrier. Our analytical results show that the expansion speed in growth-supporting conditions depends on the fraction of persister cells at the leading edge of the population wave. The leading edge contains a small fraction of persister cells, keeping the effect on the expansion speed minimal. The fraction of persisters increases gradually in the interior of the wave. This persister pool benefits the population when it is stalled by an antibiotic environment. In that case, the presence of persister enables the population to spread deeper into the antibiotic region and to cross an antibiotic region more rapidly. The interplay of population dynamics at the interface separating the two environments and phenotype switching in the antibiotic region results in a optimal switching rate. Overall, our results show that stochastic switching can promote population expansion in the presence of antibiotic barriers or other stressful environments.

Geographic patterns of phenotypic diversity in incipient species of North American blister beetles (Coleoptera: Meloidae) are not determined by species niches, but driven by demography along the speciation process

2018 ◽  
Vol 32 (3) ◽  
pp. 672 ◽  
Author(s):  
Vladimir Salvador de Jesús-Bonilla ◽  
Mario García-París ◽  
Carlos N. Ibarra-Cerdeña ◽  
Alejandro Zaldívar-Riverón
Keyword(s):  
Phenotypic Diversity ◽  
Incomplete Lineage Sorting ◽  
Demographic History ◽  
Population Expansion ◽  
Colour Pattern ◽  
Reciprocal Monophyly ◽  
Phenotypic Divergence ◽  
Speciation Process ◽  
Local Selection ◽  
Evolutionary Units

The Epicauta stigmata complex is a group of blister beetles composed of three parapatric or sympatric species that occur in central Mexico to southern USA: E. stigmata, E. uniforma and E. melanochroa. These species are morphologically very similar, and are mainly distinguished by body colour differences. Here we assessed whether phenotypic divergence in coloration patterns define evolutionary units within the complex. We studied the phylogenetic relationships, demographic history and concordances between morphological and ecological traits in the group. The complex apparently had a demographic history of recent population expansion during the last glaciation period 75000 to 9500 years ago. The three species show no reciprocal monophyly, and thus their allospecificity was not confirmed. The current distribution of haplotypes and the genetic divergences in these taxa can be explained by either recent mitochondrial introgression events caused by hybridisation or by incomplete lineage sorting. Colour pattern differences in the complex are not likely a product of local selection acting over a common genetic background. We suggest that phenotypic divergence in colour patterns during an incipient speciation process might be seen as an enhancing factor of cohesion within each of the three evolutionary units.

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