12 research outputs found
Population Dynamics of Microorganisms in Spatially Structured Environments
Okinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyMicrobial populations live and grow in spatially structured environments. These structures lead to spatial patterns in populations and alter the course of their natural evolution. Such phenomena are theoretically studied using spatially explicit models. However, these models are still poorly understood due to their analytical and numerical complexity. In this thesis, we study two systems of microorganisms living and proliferating in different spatially structured environments. The first system consists of populations of Escherichia coli growing in rectangular microchannels with two open ends. We study such populations with a lattice model in which cells shift each other along lanes as they reproduce. The model predicts rapid diversity loss along the lanes, with neutral mutations appearing in the middle of the channel being the most likely to fixate. These theoretical predictions are in agreement with our experimental observations. The second system is constituted by planktonic microorganisms that are transported by chaotic oceanic currents. To replicate their dynamics, we employ an individual-based coalescence model. The model predicts the effect of oceanic currents on the biodiversity of planktonic communities, as observed in metabarcoding data sampled from oceans and lakes around the world.doctoral thesi
Population genetics in microchannels
Spatial constraints such as rigid barriers affect the dynamics of cell
populations, potentially altering the course of natural evolution. In this
paper, we study the population genetics of Escherichia coli proliferating in
microchannels with open ends. Our experiments reveal that competition among two
fluorescently labeled E. coli strains growing in a microchannel generates a
self-organized stripe pattern aligned with the axial direction of the channel.
To account for this observation, we employ a lattice population model in which
reproducing cells push entire lanes of cells towards the open ends of the
channel. By combining mathematical theory, numerical simulations, and
experiments, we find that the fixation dynamics is extremely fast along the
axial direction, with a logarithmic dependence on the number of cells per lane.
In contrast, competition among lanes is a much slower process. We also
demonstrate that random mutations appearing in the middle of the channel and
close to its walls are much more likely to reach fixation than mutations
occurring elsewhere.Comment: 21 pages, 14 figure
Rapid task-dependent tuning of the mouse olfactory bulb
Adapting neural representation to rapidly changing behavioural demands is a key challenge for the nervous system. Here, we demonstrate that the output of the primary olfactory area of the mouse, the olfactory bulb, is already a target of dynamic and reproducible modulation. The modulation depends on the stimulus tuning of a given neuron, making olfactory responses more discriminable through selective amplification in a demand-specific way
Generation and Characterization of a Cell Type-Specific, Inducible Cre-Driver Line to Study Olfactory Processing
In sensory systems of the brain, mechanisms exist to extract distinct features from stimuli to generate a variety of behavioral repertoires. These often correspond to different cell types at various stages in sensory processing. In the mammalian olfactory system, complex information processing starts in the olfactory bulb, whose output is conveyed by mitral cells (MCs) and tufted cells (TCs). Despite many differences between them, and despite the crucial position they occupy in the information hierarchy, Cre-driver lines that distinguish them do not yet exist. Here, we sought to identify genes that are differentially expressed between MCs and TCs of the mouse, with an ultimate goal to generate a cell type-specific Cre-driver line, starting from a transcriptome analysis using a large and publicly available single-cell RNA-seq dataset (Zeisel et al., 2018). Many genes were differentially expressed, but only a few showed consistent expressions in MCs and at the specificity required. After further validating these putative markers using ISH, two genes (i.e., Pkib and Lbdh2) remained as promising candidates. Using CRISPR/Cas9-mediated gene editing, we generated Cre-driver lines and analyzed the resulting recombination patterns. This indicated that our new inducible Cre-driver line, Lbhd2-CreERT2, can be used to genetically label MCs in a tamoxifen dose-dependent manner, both in male and female mice, as assessed by soma locations, projection patterns, and sensory-evoked responses in vivo. Hence, this is a promising tool for investigating cell type-specific contributions to olfactory processing and demonstrates the power of publicly accessible data in accelerating science
Population Dynamics of Microorganisms in Spatially Structured Environments
Okinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyMicrobial populations live and grow in spatially structured environments. These structures lead to spatial patterns in populations and alter the course of their natural evolution. Such phenomena are theoretically studied using spatially explicit models. However, these models are still poorly understood due to their analytical and numerical complexity. In this thesis, we study two systems of microorganisms living and proliferating in different spatially structured environments. The first system consists of populations of Escherichia coli growing in rectangular microchannels with two open ends. We study such populations with a lattice model in which cells shift each other along lanes as they reproduce. The model predicts rapid diversity loss along the lanes, with neutral mutations appearing in the middle of the channel being the most likely to fixate. These theoretical predictions are in agreement with our experimental observations. The second system is constituted by planktonic microorganisms that are transported by chaotic oceanic currents. To replicate their dynamics, we employ an individual-based coalescence model. The model predicts the effect of oceanic currents on the biodiversity of planktonic communities, as observed in metabarcoding data sampled from oceans and lakes around the world.doctoral thesi
空間的構造を有する環境中の微生物の個体群集ダイナミクス
Microbial populations live and grow in spatially structured environments. These structures lead to spatial patterns in populations and alter the course of their natural evolution. Such phenomena are theoretically studied using spatially explicit models. However, these models are still poorly understood due to their analytical and numerical complexity. In this thesis, we study two systems of microorganisms living and proliferating in different spatially structured environments. The first system consists of populations of Escherichia coli growing in rectangular microchannels with two open ends. We study such populations with a lattice model in which cells shift each other along lanes as they reproduce. The model predicts rapid diversity loss along the lanes, with neutral mutations appearing in the middle of the channel being the most likely to fixate. These theoretical predictions are in agreement with our experimental observations. The second system is constituted by planktonic microorganisms that are transported by chaotic oceanic currents. To replicate their dynamics, we employ an individual-based coalescence model. The model predicts the effect of oceanic currents on the biodiversity of planktonic communities, as observed in metabarcoding data sampled from oceans and lakes around the world
Coalescent dynamics of planktonic communities
Planktonic communities are extremely diverse and include a vast number of
rare species. The dynamics of these rare species is best described by
individual-based models. However, individual-based approaches to planktonic
diversity face substantial difficulties, due to the large number of individuals
required to make realistic predictions. In this paper, we study diversity of
planktonic communities by means of a spatial coalescence model, that
incorporates transport by oceanic currents. As a main advantage, our approach
requires simulating a number of individuals equal to the size of the sample one
is interested in, rather than the size of the entire community. By theoretical
analysis and simulations, we explore the conditions upon which our coalescence
model is equivalent to individual-based dynamics. As an application, we use our
model to predict the impact of chaotic advection by oceanic currents on
biodiversity. We conclude that the coalescent approach permits to simulate
marine microbial communities much more efficiently than with individual-based
models