Biology subjects

Kessler, D. A.

Publications and source records attributed to Kessler, D. A..

4 recordsLinked to original sources

bioRxiv2024

Pulse Instabilities Can Shape Virus-Immune Co-evolution

Adaptive immune systems engage in an arms race with evolving viruses, trying to generate new responses to viral strains that continually move away from the set of genetically-varying strains that have already elicited a functional immune response. It has been argued that this dynamical process can lead to a propagating pulse of an ever-changing viral population and concomitant immune response. Here, we introduce a new stochastic model of viral-host co-evolution, taking into account finite-sized host populations and varying processes of immune "forgetting". Using both stochastic and determinstic calculations, we show that there is indeed a possible pulse solution, but for a large host population size and for finite memory capacity, the pulse becomes unstable to the generation of new infections in its wake. This instability leads to an extended endemic infection pattern, demonstrating that the population-level behavior of virus infections can exhibit a wider range of behavior than had been previously realized.

biophysics↗

bioRxiv2022

Minimal frustration underlies the usefulness of incomplete and inexact regulatory network models in biology

Regulatory networks as large and complex as those implicated in cell-fate choice are expected to exhibit intricate, very high-dimensional dynamics. Cell-fate choice, however, is a macroscopically simple process. Additionally, regulatory network models are almost always incomplete and / or inexact, and do not incorporate all the regulators and interactions that may be involved in cellfate regulation. In spite of these issues, regulatory network models have proven to be incredibly effective tools for understanding cell-fate choice across contexts and for making useful predictions. Here, we show that minimal frustration--a feature of biological networks across contexts but not of random networks--can compel simple, low-dimensional steady-state behavior even in large and complex networks. Moreover, the steady-state behavior of minimally frustrated networks can be recapitulated by simpler networks such as those lacking many of the nodes and edges, and those that treat multiple regulators as one. The present study provides a theoretical explanation for the success of network models in biology and for the challenges in network inference.

systems biology↗

bioRxiv2019

Ordered Hexagonal Patterns via Notch-Delta Signaling

Many developmental processes in biology utilize Notch-Delta signaling to construct an ordered pattern of cellular differentiation. This signaling modality is based on nearest-neighbor contact, as opposed to the more familiar mechanism driven by the release of diffusible ligands. Here, we show that this "juxtracrine" property allows for an exact treatment of the pattern formation problem via a system of nine coupled ordinary differential equations. Furthermore, we show that the possible patterns that are realized can be analyzed by considering a co-dimension 2 pitchfork bifurcation of this system. This analysis explains the observed prevalence of hexagonal patterns with high Delta at their center, as opposed to those with central high Notch levels. Also, our theory suggests a simple strategy for producing defect-free patterns.

biophysics↗

bioRxiv2016

Darwinian Selection Induces Lamarckian Adaptation in a Holobiont Model

BackgroundThe relatively fast selection of symbiotic bacteria within hosts and the potential transmission of these bacteria across generations of hosts raise the question of whether interactions between host and bacteria support emergent adaptive capabilities beyond those of germ-free hosts.\n\nResultsTo investigate possibilities for emergent adaptations that may distinguish composite host-microbiome systems from germ-free hosts, we introduce a population genetics model of a host-microbiome system with vertical transmission of bacteria. The host and its bacteria are jointly exposed to a toxic agent, creating a toxic stress that can be alleviated by selection of resistant individuals and by secretion of a detoxification agent (\"detox\"). We show that toxic exposure in one generation of hosts leads to selection of resistant bacteria, which in turn, increases the toxic tolerance of the hosts offspring. Prolonged exposure to toxin over many host generations promotes additional form of emergent adaptation due to selection of hosts based on detox capabilities of their bacterial community as a whole (as opposed to properties of individual bacteria).\n\nConclusionsThese findings show that interactions between pure Darwinian selections of host and its bacteria can give rise to emergent adaptive capabilities, including Lamarckian-like adaptation of the host-microbiome system.

evolutionary biology↗