Biology subjects

Karamched, B. R.

Publications and source records attributed to Karamched, B. R..

5 recordsLinked to original sources

bioRxiv2025

Signed, Sealed, Delivered: A Generalizable Model for Probiotic Delivery and Metabolism in the Gut

As genetic engineering advances, so does the need for quantitative models to inform biological engineering. This is particularly true for the nascent field of synthetic probiotic therapy of the gut microbiome. Gut microbiome health is linked to health of the host organism. Decline in microbiome health is correlated with severe metabolic disorders. However, as far as we know, there are no models that account for ingestion and transfer of a synthetic probiotic as well as its intended metabolic effect. We present here the first model that accounts for such effects. We call our model the bacterial compartment absorption and transit (BCAT) model. It is a generalization of the pharmacokinetic compartment absorption and transit (CAT) model As a specific example, we employ the BCAT model in the context of trimethylaminuria (TMAU), a metabolic disorder characterized by a persistent fishy odor emanating from affected individuals. The BCAT model predicts the dose of probiotic required for adequate medical treatment of TMAU. Moreover, our model is flexible to apply to any metabolic disorder pertaining to the gut microbiome.

systems biology↗

bioRxiv2025

Heterogeneous monotonic and non-monotonic responses to odor in mitral/tufted glomeruli of the mouse olfactory bulb

Animals can recognize and discriminate between different odors and the same odor over a range of concentrations. Processing within the mouse olfactory bulb (OB) may be involved, yet the underlying mechanisms remain unclear. Each olfactory receptor neuron (ORN) type maps to the OB in olfactory receptor specific channels called glomeruli where they connect with the dendrites of mitral/tufted cells (MTCs), which project their axons to the rest of the brain. Differences between input and output define the functions carried out by a brain region. Using in vivo dual-color 2-photon Ca2+ imaging from the ORNs and MTCs innervating the same glomeruli in the mouse OB, we identified a novel MTC response type with a non-monotonic concentration-response relationship. We used mathematical modeling to demonstrate that non-monotonic response types are consistent with a form of interglomerular processing, which we propose is a mechanism to facilitate odor discrimination and the ability to achieve concentration-invariant odor perception. Graphical AbstractThe olfactory bulb input-output transformation was imaged using dual-color 2-photon imaging. (Top) Cartoon and histological examples of labeling the olfactory bulb input and output using spectrally distinct optical sensors. (Middle) Modeling and experimental work reveal that input neurons that respond with primarily monotonic concentration-response relationships are transformed into a mix of monotonic and non-monotonic responses. (Bottom) Olfactory bulb output state space for a population of 3 glomeruli with exclusively monotonic responses (black), and with both monotonic and non-monotonic responses (red). Each trajectory represents a cloud of points that reflects variations in the fluctuations of molecular components present in natural odor stimuli. Monotonic responses alone cluster together, while multiple response types broaden coverage of MTC state space. Greater coverage of state space makes it easier to discriminate one odor from another, even though the dimension of olfactory bulb state space is larger than 3. Key PointsO_LIAlthough the olfactory bulb is the first stage of olfactory sensory processing, its role in transforming sensory information remains poorly understood. C_LIO_LIDifferent olfactory receptor neuron types map to the olfactory bulb in olfactory receptor specific channels called glomeruli, where they interact with the dendrites of mitral/tufted cells, which project to the rest of the brain. C_LIO_LIWe used dual-color 2-photon Ca2+ imaging to image the input-output transformation olfactory receptor neuron (ORN) and mitral/tufted (MTC) glomeruli across a wide concentration range. C_LIO_LIThe ORN input to all tested glomeruli responded to increasing concentration changes with monotonic increases, while the corresponding MTCs outputs of each glomerulus responded with monotonic and non-monotonic changes. C_LIO_LIThe results were consistent with a mathematical model of the olfactory bulb incorporating feed-forward and lateral inhibition. C_LI

neuroscience↗

bioRxiv2024

Walk This Way: Modeling Foraging Ant Dynamics in Multiple Food Source Environments

Foraging for resources is an essential process for the daily life of an ant colony. What makes this process so fascinating is the self-organization of ants into trails using chemical pheromone in the absence of direct communication. Here we present a stochastic lattice model that captures essential features of foraging ant dynamics inspired by recent agent-based models while forgoing more detailed interactions that may not be essential to trail formation. Nevertheless, our models results coincide with those presented in more sophisticated theoretical models and experiment. Furthermore, it captures the phenomenon of multiple trail formation in environments with multiple food sources. This latter phenomenon is not described well by other more detailed models. An additional feature of this approach is the ability to derive a corresponding macroscopic PDE from the stochastic lattice model which can be described via first principle interactions and is amenable to analysis. Linear stability analysis of this PDE reveals the key biophysical parameters that give rise to trail formation. We also highlight universal features of the modeling framework that this simple formation may allow it to be used to study complex systems beyond ants.

ecology↗

bioRxiv2021

Emergent spatiotemporal population dynamics with cell-length control of synthetic microbial consortia

AO_SCPLOWBSTRACTC_SCPLOWIncreased complexity of engineered microbial biocircuits highlights the need for distributed cell functionality due to concomitant increases of metabolic and regulatory burdens imposed on single-strain topologies. Distributed systems, however, introduce additional challenges since consortium composition and spatiotemporal dynamics of constituent strains must be robustly controlled to achieve desired circuit behaviors. Here, we address these challenges with a modeling-based investigation of emergent spatiotemporal population dynamics that result from cell-length control of monolayer, two-strain bacterial consortia. We demonstrate that with dynamic control of a strains division length, nematic cell alignment in close-packed monolayers can be destabilized. We found this destabilization conferred an emergent, competitive advantage on smaller-length strains--but by mechanisms that differed depending on the spatial patterns of the population. We used complementary modeling approaches to elucidate underlying mechanisms: an agent-based model to simulate detailed mechanical and signaling interactions between the competing strains and a reductive, stochastic lattice model to represent cell-cell interactions with a single rotational parameter. Our modeling suggests that spatial strain-fraction oscillations can be generated when cell-length control is coupled to quorum-sensing signaling in negative feedback topologies. Our research employs novel methods of population control and points the way to programming strain fraction dynamics in consortial synthetic biology. Engineered microbial collectives are more versatile and robust than single strain populations. However, the function of such collectives is sensitive to their spatiotemporal organization. Here, we demonstrate control of the spatiotemporal composition of synthetic microbial consortia by dynamically modulating the average cell length of constituent strains. Such modulation confers an emergent "mechanical fitness" advantage upon the shorter length strain. We used both a biophysically realistic agent-based model to test the impact of cell shape on spatiotemporal dynamics and a conceptually simpler stochastic lattice model to explain the essential mechanisms driving the dynamics.

biophysics↗

bioRxiv2020

Delay-Induced Uncertainty in Physiological Systems

AO_SCPLOWBSTRACTC_SCPLOWMedical practice in the intensive care unit is based on the supposition that physiological systems such as the human glucose-insulin system are reliabile. Reliability of dynamical systems refers to response to perturbation: A dynamical system is reliable if it behaves predictably following a perturbation. Here, we demonstrate that reliability fails for an archetypal physiological model, the Ultradian glucose-insulin model. Reliability failure arises because of the presence of delay. Using the theory of rank one maps from smooth dynamical systems, we precisely explain the nature of the resulting delay-induced uncertainty (DIU). We develop a recipe one may use to diagnose DIU in a general dynamical system. Guided by this recipe, we analyze DIU emergence first in a classical linear shear flow model and then in the Ultradian model. Our results potentially apply to a broad class of physiological systems that involve delay.

physiology↗