Vemparala, B. | Search bioRxiv

bioRxiv2023

Antiviral capacity of the early CD8 T-cell response is predictive of natural control of SIV infection

While most individuals suffer progressive disease following HIV infection, a small fraction spontaneously controls the infection. Although CD8 T-cells have been implicated in this natural control, their mechanistic roles are yet to be established. Here, we combined mathematical modeling and analysis of data from 16 SIV-infected macaques, of which 12 were natural controllers, to elucidate the role of CD8 T-cells in natural control. For each macaque, we considered, in addition to the canonical in vivo plasma viral load and SIV DNA data, longitudinal ex vivo measurements of the virus suppressive capacity of CD8 T-cells. Available mathematical models do not allow analysis of such combined in vivo-ex vivo datasets. By explicitly modeling the ex vivo assay and integrating it with in vivo dynamics, we developed a new framework that enabled the analysis. Our model fit the data well and estimated that the recruitment rate and/or maximal killing rate of CD8 T-cells was up to 2-fold higher in controllers than non-controllers (p=0.013). Importantly, the cumulative suppressive capacity of CD8 T-cells over the first 4-6 weeks of infection was associated with virus control (Spearmans {rho}=- 0.51; p=0.05). Thus, our analysis identified the early cumulative suppressive capacity of CD8 T-cells as a predictor of natural control. Furthermore, simulating a large virtual population, our model quantified the minimum capacity of this early CD8 T-cell response necessary for long-term control. Our study presents new, quantitative insights into the role of CD8 T-cells in the natural control of HIV infection and has implications for remission strategies.

microbiology↗

bioRxiv2022

An evolutionary paradigm favoring crosstalk between bacterial two-component signaling systems

The prevalent paradigm governing bacterial two-component signaling systems (TCSs) is specificity, wherein the histidine kinase (HK) of a TCS exclusively activates its cognate response regulator (RR). Crosstalk, where HKs activate noncognate RRs, is considered evolutionarily disadvantageous because it can compromise adaptive responses by leaking signals. Yet, crosstalk is observed in several bacteria. Here, to resolve this paradox, we propose an alternative paradigm where crosstalk can be advantageous. We envisioned programmed environments, wherein signals appear in predefined sequences. In such environments, crosstalk that primes bacteria to upcoming signals may improve adaptive responses and confer evolutionary benefits. To test this hypothesis, we employed mathematical modeling of TCS signaling networks and stochastic evolutionary dynamics simulations. We considered the comprehensive set of bacterial phenotypes, comprising thousands of distinct crosstalk patterns, competing in varied signaling environments. Our simulations predicted that in programmed environments phenotypes with crosstalk facilitating priming would outcompete phenotypes without crosstalk. In environments where signals appear randomly, bacteria without crosstalk would dominate, explaining the specificity widely seen. Additionally, a testable prediction was that the phenotypes selected in programmed environments would display one-way crosstalk, ensuring priming to future signals. Interestingly, the crosstalk networks we deduced from available data on TCSs of Mycobacterium tuberculosis all displayed one-way crosstalk, offering strong support to our predictions. Our study thus identifies potential evolutionary underpinnings of crosstalk in bacterial TCSs, suggests a reconciliation of specificity and crosstalk, makes testable predictions of the nature of crosstalk patterns selected, and has implications for understanding bacterial adaptation and the response to interventions. IMPORTANCEBacteria use two-component signaling systems (TCSs) to sense and respond to environmental changes. The prevalent paradigm governing TCSs is specificity, where signal flow through TCSs is insulated; leakage to other TCSs is considered evolutionarily disadvantageous. Yet, crosstalk between TCSs is observed in many bacteria. Here, we present a potential resolution of this paradox. We envision programmed environments, wherein stimuli appear in predefined sequences. Crosstalk that primes bacteria to upcoming stimuli could then confer evolutionary benefits. We demonstrate this benefit using mathematical modeling and evolutionary simulations. Interestingly, we found signatures of predicted crosstalk patterns in Mycobacterium tuberculosis. Furthermore, specificity was selected in environments where stimuli occurred randomly, thus reconciling specificity and crosstalk. Implications follow for understanding bacterial evolution and for interventions.

microbiology↗