scholarly journals A traveling-wave solution for bacterial chemotaxis with growth

2021 ◽  
Vol 118 (48) ◽  
pp. e2105138118
Author(s):  
Avaneesh V. Narla ◽  
Jonas Cremer ◽  
Terence Hwa
Keyword(s):  
Bacterial Chemotaxis ◽  
Population Expansion ◽  
Environmental Parameters ◽  
Traveling Wave Solution ◽  
Rapid Expansion ◽  
Mathematical Framework ◽  
Bacterial Cells ◽  
Bacterial Populations ◽  
Analytical Relations ◽  
Expanding Population

Bacterial cells navigate their environment by directing their movement along chemical gradients. This process, known as chemotaxis, can promote the rapid expansion of bacterial populations into previously unoccupied territories. However, despite numerous experimental and theoretical studies on this classical topic, chemotaxis-driven population expansion is not understood in quantitative terms. Building on recent experimental progress, we here present a detailed analytical study that provides a quantitative understanding of how chemotaxis and cell growth lead to rapid and stable expansion of bacterial populations. We provide analytical relations that accurately describe the dependence of the expansion speed and density profile of the expanding population on important molecular, cellular, and environmental parameters. In particular, expansion speeds can be boosted by orders of magnitude when the environmental availability of chemicals relative to the cellular limits of chemical sensing is high. Analytical understanding of such complex spatiotemporal dynamic processes is rare. Our analytical results and the methods employed to attain them provide a mathematical framework for investigations of the roles of taxis in diverse ecological contexts across broad parameter regimes.

scholarly journals A Metabolic Model of Intestinal Secretions: The Link between Human Microbiota and Colorectal Cancer Progression

Metabolites ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 456
Author(s):  
Pejman Salahshouri ◽  
Modjtaba Emadi-Baygi ◽  
Mahdi Jalili ◽  
Faiz M. Khan ◽  
Olaf Wolkenhauer ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Progression ◽  
Gut Microbiome ◽  
Metabolic Model ◽  
System Level ◽  
Mathematical Framework ◽  
Bacterial Populations ◽  
Colorectal Cancer Progression ◽  
Genome Scale ◽  
High Throughput Data Analysis

The human gut microbiota plays a dual key role in maintaining human health or inducing disorders, for example, obesity, type 2 diabetes, and cancers such as colorectal cancer (CRC). High-throughput data analysis, such as metagenomics and metabolomics, have shown the diverse effects of alterations in dynamic bacterial populations on the initiation and progression of colorectal cancer. However, it is well established that microbiome and human cells constantly influence each other, so it is not appropriate to study them independently. Genome-scale metabolic modeling is a well-established mathematical framework that describes the dynamic behavior of these two axes at the system level. In this study, we created community microbiome models of three conditions during colorectal cancer progression, including carcinoma, adenoma and health status, and showed how changes in the microbial population influence intestinal secretions. Conclusively, our findings showed that alterations in the gut microbiome might provoke mutations and transform adenomas into carcinomas. These alterations include the secretion of mutagenic metabolites such as H2S, NO compounds, spermidine and TMA, as well as the reduction of butyrate. Furthermore, we found that the colorectal cancer microbiome can promote inflammation, cancer progression (e.g., angiogenesis) and cancer prevention (e.g., apoptosis) by increasing and decreasing certain metabolites such as histamine, glutamine and pyruvate. Thus, modulating the gut microbiome could be a promising strategy for the prevention and treatment of CRC.

scholarly journals Stochasticity in Colonial Growth Dynamics of Individual Bacterial Cells

2013 ◽  
Vol 79 (7) ◽  
pp. 2294-2301 ◽  
Author(s):  
Konstantinos P. Koutsoumanis ◽  
Alexandra Lianou
Keyword(s):  
Kinetic Parameters ◽  
Single Cells ◽  
Growth Curves ◽  
Growth Dynamics ◽  
Time Lapse ◽  
Initial Population ◽  
Bacterial Cells ◽  
Stochastic Growth ◽  
Bacterial Populations ◽  
Content Type

ABSTRACTConventional bacterial growth studies rely on large bacterial populations without considering the individual cells. Individual cells, however, can exhibit marked behavioral heterogeneity. Here, we present experimental observations on the colonial growth of 220 individual cells ofSalmonella entericaserotype Typhimurium using time-lapse microscopy videos. We found a highly heterogeneous behavior. Some cells did not grow, showing filamentation or lysis before division. Cells that were able to grow and form microcolonies showed highly diverse growth dynamics. The quality of the videos allowed for counting the cells over time and estimating the kinetic parameters lag time (λ) and maximum specific growth rate (μmax) for each microcolony originating from a single cell. To interpret the observations, the variability of the kinetic parameters was characterized using appropriate probability distributions and introduced to a stochastic model that allows for taking into account heterogeneity using Monte Carlo simulation. The model provides stochastic growth curves demonstrating that growth of single cells or small microbial populations is a pool of events each one of which has its own probability to occur. Simulations of the model illustrated how the apparent variability in population growth gradually decreases with increasing initial population size (N0). For bacterial populations withN0of >100 cells, the variability is almost eliminated and the system seems to behave deterministically, even though the underlying law is stochastic. We also used the model to demonstrate the effect of the presence and extent of a nongrowing population fraction on the stochastic growth of bacterial populations.

scholarly journals Influence of Quaternary environmental changes on mole populations inferred from mitochondrial sequences and evolutionary rate estimation

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Azusa Nakamoto ◽  
Masashi Harada ◽  
Reiko Mitsuhashi ◽  
Kimiyuki Tsuchiya ◽  
Alexey P. Kryukov ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Environmental Changes ◽  
Late Quaternary ◽  
Population Expansion ◽  
Rapid Expansion ◽  
Dependent Manner ◽  
Distribution Analysis ◽  
Land Bridge ◽  
Mismatch Distribution Analysis ◽  
Expansion Event

AbstractQuaternary environmental changes fundamentally influenced the genetic diversity of temperate-zone terrestrial animals, including those in the Japanese Archipelago. The genetic diversity of present-day populations is taxon- and region-specific, but its determinants are poorly understood. Here, we analyzed cytochrome b gene (Cytb) sequences (1140 bp) of mitochondrial DNA (mtDNA) to elucidate the factors determining the genetic variation in three species of large moles: Mogera imaizumii and Mogera wogura, which occur in central and southern mainland Japan (Honshu, Shikoku, and Kyushu), and Mogera robusta, which occurs on the nearby Asian continent. Network construction with the Cytb sequences revealed 10 star-shaped clusters with apparent geographic affinity. Mismatch distribution analysis showed that modes of pairwise nucleotide differences (τ values) were grouped into five classes in terms of the level, implying the occurrence of five stages for rapid expansion. It is conceivable that severe cold periods and subsequent warm periods during the late Quaternary were responsible for the population expansion events. The first and third oldest events included island-derived haplotypes, indicative of the involvement of land bridge formation between remote islands, hence suggesting an association of the ends of the penultimate (PGM, ca. 130,000 years ago) and last (LGM, ca. 15,000 years ago) glacial maxima, respectively. Since the third event was followed by the fourth, it is plausible that the termination of the Younger Dryas and subsequent abrupt warming ca. 11,500 years ago facilitated the fourth expansion event. The second event most likely corresponded to early marine isotope stage (MIS) 3 (ca. 53,000 years ago) when the glaciation and subsequent warming period were predicted to have influenced biodiversity. Utilization of the critical times of 130,000, 53,000, 15,000, and 11,500 years ago as calibration points yielded evolutionary rates of 0.03, 0.045, 0.10 and 0.10 substitutions/site/million years, respectively, showing a time-dependent manner whose pattern was similar to that seen in small rodents reported in our previous studies. The age of the fifth expansion event was calculated to be 5800 years ago with a rate of 0.10 substitutions/site/million years ago during the mid-Holocene, suggestive of the influence of humans or other unspecified reasons, such as the Jomon marine transgression.

scholarly journals Prokaryotic Single-Cell RNA Sequencing by In Situ Combinatorial Indexing

2019 ◽  
Author(s):  
Sydney B. Blattman ◽  
Wenyan Jiang ◽  
Panos Oikonomou ◽  
Saeed Tavazoie
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Low Cost ◽  
Bacterial Cells ◽  
Single Experiment ◽  
Bacterial Populations ◽  
Single Cell Rna Sequencing ◽  
Gene Expression Heterogeneity ◽  
Mrna Polyadenylation

AbstractDespite longstanding appreciation of gene expression heterogeneity in isogenic bacterial populations, affordable and scalable technologies for studying single bacterial cells have been limited. While single-cell RNA sequencing (scRNA-seq) has revolutionized studies of transcriptional heterogeneity in diverse eukaryotic systems, application of scRNA-seq to prokaryotes has been hindered by their extremely low mRNA abundance, lack of mRNA polyadenylation, and thick cell walls. Here, we present Prokaryotic Expression-profiling by Tagging RNA In Situ and sequencing (PETRI-seq), a low-cost, high-throughput, prokaryotic scRNA-seq pipeline that overcomes these technical obstacles. PETRI-seq uses in situ combinatorial indexing to barcode transcripts from tens of thousands of cells in a single experiment. PETRI-seq captures single cell transcriptomes of Gram-negative and Gram-positive bacteria with high purity and low bias, with median capture rates >200 mRNAs/cell for exponentially growing E. coli. These characteristics enable robust discrimination of cell-states corresponding to different phases of growth. When applied to wild-type S. aureus, PETRI-seq revealed a rare sub-population of cells undergoing prophage induction. We anticipate broad utility of PETRI-seq in defining single-cell states and their dynamics in complex microbial communities.

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 Bacteriophages Limit the Existence Conditions for Conjugative Plasmids

mBio ◽  
2015 ◽  
Vol 6 (3) ◽  
Author(s):  
Ellie Harrison ◽  
A. Jamie Wood ◽  
Calvin Dytham ◽  
Jonathan W. Pitchford ◽  
Julie Truman ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Experimental Evolution ◽  
Phage Resistance ◽  
Bacterial Cells ◽  
Resistance Mutations ◽  
Weak Selection ◽  
Bacterial Populations ◽  
Conjugative Plasmids ◽  
Existence Conditions ◽  
Selection For

ABSTRACTBacteriophages are a major cause of bacterial mortality and impose strong selection on natural bacterial populations, yet their effects on the dynamics of conjugative plasmids have rarely been tested. We combined experimental evolution, mathematical modeling, and individual-based simulations to explain how the ecological and population genetics effects of bacteriophages upon bacteria interact to determine the dynamics of conjugative plasmids and their persistence. The ecological effects of bacteriophages on bacteria are predicted to limit the existence conditions for conjugative plasmids, preventing persistence under weak selection for plasmid accessory traits. Experiments showed that phages drove faster extinction of plasmids in environments where the plasmid conferred no benefit, but they also revealed more complex effects of phages on plasmid dynamics under these conditions, specifically, the temporary maintenance of plasmids at fixation followed by rapid loss. We hypothesized that the population genetic effects of bacteriophages, specifically, selection for phage resistance mutations, may have caused this. Further mathematical modeling and individual-based simulations supported our hypothesis, showing that conjugative plasmids may hitchhike with phage resistance mutations in the bacterial chromosome.IMPORTANCEConjugative plasmids are infectious loops of DNA capable of transmitting DNA between bacterial cells and between species. Because plasmids often carry extra genes that allow bacteria to live in otherwise-inhospitable environments, their dynamics are central to understanding bacterial adaptive evolution. The plasmid-bacterium interaction has typically been studied in isolation, but in natural bacterial communities, bacteriophages, viruses that infect bacteria, are ubiquitous. Using experiments, mathematical models, and computer simulations we show that bacteriophages drive plasmid dynamics through their ecological and evolutionary effects on bacteria and ultimately limit the conditions allowing plasmid existence. These results advance our understanding of bacterial adaptation and show that bacteriophages could be used to select against plasmids carrying undesirable traits, such as antibiotic resistance.

scholarly journals Off Earth Identification of Bacterial Populations Using 16S rDNA Nanopore Sequencing

Genes ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 76 ◽  
Author(s):  
Aaron S. Burton ◽  
Sarah E. Stahl ◽  
Kristen K. John ◽  
Miten Jain ◽  
Sissel Juul ◽  
...  
Keyword(s):  
High Performance ◽  
Space Station ◽  
Bacterial Cells ◽  
Sequencing Data ◽  
Mock Community ◽  
Bacterial Populations ◽  
Microbial Identification ◽  
Staphylococcus Capitis ◽  
Staphylococcus Hominis ◽  
Community Standard

The MinION sequencer has made in situ sequencing feasible in remote locations. Following our initial demonstration of its high performance off planet with Earth-prepared samples, we developed and tested an end-to-end, sample-to-sequencer process that could be conducted entirely aboard the International Space Station (ISS). Initial experiments demonstrated the process with a microbial mock community standard. The DNA was successfully amplified, primers were degraded, and libraries prepared and sequenced. The median percent identities for both datasets were 84%, as assessed from alignment of the mock community. The ability to correctly identify the organisms in the mock community standard was comparable for the sequencing data obtained in flight and on the ground. To validate the process on microbes collected from and cultured aboard the ISS, bacterial cells were selected from a NASA Environmental Health Systems Surface Sample Kit contact slide. The locations of bacterial colonies chosen for identification were labeled, and a small number of cells were directly added as input into the sequencing workflow. Prepared DNA was sequenced, and the data were downlinked to Earth. Return of the contact slide to the ground allowed for standard laboratory processing for bacterial identification. The identifications obtained aboard the ISS, Staphylococcus hominis and Staphylococcus capitis, matched those determined on the ground down to the species level. This marks the first ever identification of microbes entirely off Earth, and this validated process could be used for in-flight microbial identification, diagnosis of infectious disease in a crewmember, and as a research platform for investigators around the world.

scholarly journals Symbiotic Outcome Modified by the Diversification from 7 to over 700 Nodule-Specific Cysteine-Rich Peptides

Genes ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 348 ◽  
Author(s):  
Proyash Roy ◽  
Mingkee Achom ◽  
Helen Wilkinson ◽  
Beatriz Lagunas ◽  
Miriam L. Gifford
Keyword(s):  
Morphological Changes ◽  
Expression Patterns ◽  
Terminal State ◽  
Rapid Expansion ◽  
Bacterial Cells ◽  
Positive Regulators ◽  
Bacterial Cell Cycle ◽  
Species Specific ◽  
Secreted Peptides

Legume-rhizobium symbiosis represents one of the most successfully co-evolved mutualisms. Within nodules, the bacterial cells undergo distinct metabolic and morphological changes and differentiate into nitrogen-fixing bacteroids. Legumes in the inverted repeat lacking clade (IRLC) employ an array of defensin-like small secreted peptides (SSPs), known as nodule-specific cysteine-rich (NCR) peptides, to regulate bacteroid differentiation and activity. While most NCRs exhibit bactericidal effects in vitro, studies confirm that inside nodules they target the bacterial cell cycle and other cellular pathways to control and extend rhizobial differentiation into an irreversible (or terminal) state where the host gains control over bacteroids. While NCRs are well established as positive regulators of effective symbiosis, more recent findings also suggest that NCRs affect partner compatibility. The extent of bacterial differentiation has been linked to species-specific size and complexity of the NCR gene family that varies even among closely related species, suggesting a more recent origin of NCRs followed by rapid expansion in certain species. NCRs have diversified functionally, as well as in their expression patterns and responsiveness, likely driving further functional specialisation. In this review, we evaluate the functions of NCR peptides and their role as a driving force underlying the outcome of rhizobial symbiosis, where the plant is able to determine the outcome of rhizobial interaction in a temporal and spatial manner.

scholarly journals Chemoreceptors in Caulobacter crescentus: Trimers of Receptor Dimers in a Partially Ordered Hexagonally Packed Array

2008 ◽  
Vol 190 (20) ◽  
pp. 6805-6810 ◽  
Author(s):  
Cezar M. Khursigara ◽  
Xiongwu Wu ◽  
Sriram Subramaniam
Keyword(s):  
Caulobacter Crescentus ◽  
Electron Tomography ◽  
Bacterial Chemotaxis ◽  
Bacterial Cells ◽  
Molecular Architecture ◽  
Cellular Motility ◽  
Partially Ordered ◽  
Order And Disorder ◽  
Cryo Electron Tomography ◽  
Receptor Dimers

ABSTRACT Chemoreceptor arrays are macromolecular complexes that form extended assemblies primarily at the poles of bacterial cells and mediate chemotaxis signal transduction, ultimately controlling cellular motility. We have used cryo-electron tomography to determine the spatial distribution and molecular architecture of signaling molecules that comprise chemoreceptor arrays in wild-type Caulobacter crescentus cells. We demonstrate that chemoreceptors are organized as trimers of receptor dimers, forming partially ordered hexagonally packed arrays of signaling complexes in the cytoplasmic membrane. This novel organization at the threshold between order and disorder suggests how chemoreceptors and associated molecules are arranged in signaling assemblies to respond dynamically in the activation and adaptation steps of bacterial chemotaxis.

scholarly journals Modeling Bacterial Population Growth from Stochastic Single-Cell Dynamics

2014 ◽  
Vol 80 (17) ◽  
pp. 5241-5253 ◽  
Author(s):  
Antonio A. Alonso ◽  
Ignacio Molina ◽  
Constantinos Theodoropoulos
Keyword(s):  
Differential Equation ◽  
Population Growth ◽  
Single Cell ◽  
Bacterial Cells ◽  
Estimation Of Parameters ◽  
Deterministic Models ◽  
Cell Dynamics ◽  
Bacterial Populations ◽  
Content Type ◽  
Number Of Individuals

ABSTRACTA few bacterial cells may be sufficient to produce a food-borne illness outbreak, provided that they are capable of adapting and proliferating on a food matrix. This is why any quantitative health risk assessment policy must incorporate methods to accurately predict the growth of bacterial populations from a small number of pathogens. In this aim, mathematical models have become a powerful tool. Unfortunately, at low cell concentrations, standard deterministic models fail to predict the fate of the population, essentially because the heterogeneity between individuals becomes relevant. In this work, a stochastic differential equation (SDE) model is proposed to describe variability within single-cell growth and division and to simulate population growth from a given initial number of individuals. We provide evidence of the model ability to explain the observed distributions of times to division, including the lag time produced by the adaptation to the environment, by comparing model predictions with experiments from the literature forEscherichia coli,Listeria innocua, andSalmonella enterica. The model is shown to accurately predict experimental growth population dynamics for both small and large microbial populations. The use of stochastic models for the estimation of parameters to successfully fit experimental data is a particularly challenging problem. For instance, if Monte Carlo methods are employed to model the required distributions of times to division, the parameter estimation problem can become numerically intractable. We overcame this limitation by converting the stochastic description to a partial differential equation (backward Kolmogorov) instead, which relates to the distribution of division times. Contrary to previous stochastic formulations based on random parameters, the present model is capable of explaining the variability observed in populations that result from the growth of a small number of initial cells as well as the lack of it compared to populations initiated by a larger number of individuals, where the random effects become negligible.

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