Biology subjects

Uppal, G.

Publications and source records attributed to Uppal, G..

6 recordsLinked to original sources

bioRxiv2024

MCSPACE: inferring microbiome spatiotemporal dynamics from high-throughput co-localization data

Recent advances in high-throughput approaches for estimating co-localization of microbes, such as SAMPL-seq, allow characterization of the biogeography of the gut microbiome longitudinally and at unprecedented scale. However, these high-dimensional data are complex and have unique noise properties. To address these challenges, we developed MCSPACE, a probabilistic AI method that infers from microbiome co-localization data spatially coherent assemblages of taxa, their dynamics over time, and their responses to perturbations. To evaluate MCSPACEs capabilities, we generated the largest longitudinal microbiome co-localization dataset to date, profiling spatial relationships of microbes in the guts of mice subjected to serial dietary perturbations over 76 days. Analyses of these data and an existing human longitudinal dataset demonstrated superior benchmarking performance of MCSPACE over existing methods, and moreover yielded insights into spatiotemporal structuring of the gut microbiome, including identifying temporally persistent and dynamic microbial assemblages in the human gut, and shifts in assemblages in the murine gut induced by specific dietary components. Our results highlight the utility of our method, which we make available to the community as an open-source software tool, for elucidating dynamics of microbiome biogeography and gaining insights into the role of spatial relationships in host-microbial ecosystem function.

microbiology↗

bioRxiv2021

Circulatory systems and mortality rates

Aging is a complex process involving multiple factors and subcellular processes, ultimately leading to the death of an organism. The microscopic processes that cause aging are relatively well understood and effective macroscopic theories help explain the universality of aging in complex systems. However, these theories fail to explain the diversity of aging observed for various lifeforms. As such, more complete "mesoscopic" theories of aging are needed, combining the biophysical details of microscopic failure and the macroscopic structure of complex systems. Here we explore two models: (1) a network theoretic model, and (2) a convection diffusion model emphasizing the biophysical details of communicated signals. The first model allows us to explore the effects of connectivity structures on aging. In our second model, cells interact through cooperative and antagonistic factors. We find by varying the ratio at which these factors affect cell death, as well as the reaction kinetics, diffusive and flow parameters, we obtain a wide diversity of mortality curves. As such, the connectivity structures as well as the biophysical details of how various factors are transported in an organism may explain the diversity of aging observed across different lifeforms.

biophysics↗

bioRxiv2020

Tissue failure propagation as mediated by circulatory flow

Aging is driven by subcellular processes that are relatively well-understood. However the qualitative mechanisms and quantitative dynamics of how these micro-level failures cascade to a macro-level catastrophe in a tissue or organs remain largely unexplored. Here we experimentally and theoretically study how cell failure propagates in a synthetic tissue in the presence of advective flow. We argue that cells secrete cooperative factors, thereby forming a network of interdependence governed by diffusion and flow, which fails with a propagating front parallel to advective circulation. SIGNIFICANCEMortality rates typically increase for complex organisms as they age. This leads us to suggest that aging depends on interactions between cells. As cells become damaged, the effect propagates to other cells, eventually leading to a systemic catastrophe. Yet it is unclear how this failure dynamically propagates. Here we present experiments with synthetic tissues and analogous analytical models to investigate the dynamics of failure propagation. Our main contribution is a detailed investigation of failure propagation when interactions are mediated by advective flow. We find analytical expressions for when a pronounced propagation occurs, its velocity, and acceleration in terms of system parameters.

biophysics↗

bioRxiv2020

Evolution of chemotactic hitchhiking

Bacteria typically reside in heterogeneous environments with various chemogradients where motile cells can gain an advantage over non-motile cells. Since motility is energetically costly, cells must optimize their swimming speed and behavior to maximize their fitness. Here we investigate how cheating strategies might evolve where slow or non-motile microbes exploit faster ones by sticking together and hitching a ride. Starting with physical and biological first-principles we computationally study the effects of sticking on the evolution of motility in a controlled chemostat environment. We find stickiness allows slow cheaters to dominate when nutrients are dispersed at intermediate distances. Here, slow microbes exploit faster ones until they consume the population, leading to a tragedy of commons. For long races, slow microbes do gain an initial advantage from sticking, but eventually fall behind. Here, fast microbes are more likely to stick to other fast microbes, and cooperate to increase their own population. We therefore find the nature of the hitchhiking interaction, parasitic or mutualistic, depends on the nutrient distribution.

evolutionary biology↗

bioRxiv2019

Evolution of specialization in dynamic fluids

Previously we found mechanical factors involving diffusion and fluid shear promote evolution of social behavior in microbial populations Uppal and Vural (2018). Here, we extend this model to study the evolution of specialization using realistic physical simulations of bacteria that secrete two public goods in a dynamic fluid. Through this first principles approach, we find physical factors such as diffusion, flow patterns, and decay rates are as influential as fitness economics in governing the evolution of community structure, to the extent that when mechanical factors are taken into account, (1) Generalist communities can resist becoming specialists, despite the invasion fitness of specialization (2) Generalist and specialists can both resist cheaters despite the invasion fitness of free-riding. (3) Multiple community structures can coexist despite the opposing force of competitive exclusion. Our results emphasize the role of spatial assortment and physical forces on niche partitioning and the evolution of diverse community structures.

bioinformatics↗

bioRxiv2017

Shearing in flow environment promotes evolution of social behavior in microbial populations

It is advantageous for microbes to form social aggregates when they commonly benefit from secreting a public good. However, cooperating microbial groups can be evolutionarily unstable, since a cheating strain that does not secrete the public good can reproduce quicker and take over. Here we study the effects of fluid advection patterns on group reproduction as a mechanism to enable or enhance social behavior in microbial populations. We use a realistic advection-diffusion-reaction model to describe microbial growth and mutation in a flow environment. Social groups arise naturally from our model as self-reproducing Turing patterns that can avoid mutant takeovers at steady state. Our central finding is that flow shear enables and promotes social behavior in microbes by limiting the spread of cheating strains. Regions of the flow domain with higher shear admits high cooperativity and large population density, whereas low shear regions are devoid of life due to opportunistic mutations.

bioinformatics↗