Biology subjects

Adelman, J.

Publications and source records attributed to Adelman, J..

6 recordsLinked to original sources

bioRxiv2026

Immediate and carryover reproductive costs of infection in female but not male house finches

Wildlife diseases cause well-documented and often dramatic reductions in host survival. However, the impact of infectious diseases on host reproduction remains understudied, especially with respect to effects of prior and/or current pathogen exposure on reproductive development. Here we experimentally tested how prior and/or current infection with a common bacterial pathogen, Mycoplasma gallisepticum ( MG), alters reproductive development for female versus male house finches (Haemorhous mexicanus). Finches were inoculated with either MG or sterile media while in wintering condition and subsequently received one of these treatments while in breeding condition. In females, MG exposure had both immediate and carry-over effects on reproduction: controls had higher odds of laying eggs compared to females inoculated with MG in spring only, higher odds than females inoculated in both winter and spring, and higher odds than females given MG in the winter only. Conversely, breeding-condition males inoculated with MG in spring had higher testosterone levels than males receiving only control inoculations, and there were no carryover effects of winter MG inoculation or inoculations during both seasons on testosterone. Sex bias in the reproductive impacts of infectious diseases may have important knock-on effects on the epidemiology and population-regulating effects of pathogens, thereby warranting further study.

ecology↗

bioRxiv2025

Paying upfront: successful initial infections protect against severe future infections

Understanding the consistency with which individual hosts respond to repeated pathogen exposures is crucial for accurately modeling pathogen transmission and eco-evolutionary dynamics. When hosts face repeated pathogen exposures, immune memory is expected to reduce the probability and/or severity of subsequent infections, yet it remains unclear whether individuals remain consistent in their level of response relative to others. We investigated this question in house finches (Haemorhous mexicanus) from two populations varying in history of endemism of the bacterial pathogen Mycoplasma gallisepticum (MG). Individuals were confirmed to be MG-naive at capture and then experimentally inoculated twice with MG, allowing recovery between inoculations. We then asked if host responses to the second inoculation were predicted by responses to initial inoculation, sex, or population of origin. Our results suggest that individuals were not consistent in their relative response levels; rather, a successful initial infection provided protection against a severe second infection, increasing both tolerance and resistance. While we found no population differences in response to the second inoculation, males showed higher susceptibility to the second inoculation than females. Investigating and accounting for individual variation in response to subsequent exposures may improve the precision and accuracy of transmission models for wildlife pathogens.

ecology↗

bioRxiv2025

Host prior exposure augments heterogeneity in gene expression in both host and pathogen during in vivo infection

Variability in acquired protection, whether from prior pathogen exposure or vaccination, is increasingly recognized as a key determinant of host population-level variation in disease traits. It remains unclear whether this extends to the within-host physiological environment and what the consequences are for reinfecting pathogens. Here, we asked whether prior pathogen exposure of hosts induces gene expression heterogeneity in the host and/or pathogen during infection. We quantified gene expression in vivo following high-dose pathogen challenge of house finches (Haemorhous mexicanus) previously given controlled, varied exposure histories to a bacterial pathogen (Mycoplasma gallisepticum; MG). To measure gene expression heterogeneity, we collected transcriptomic data from two host tissues (conjunctiva and spleen), and, simultaneously, from pathogen infecting the primary site of infection (conjunctiva). In the conjunctiva, but not the spleen, prior pathogen exposure induced significant heterogeneity in host gene expression relative to pathogen-naive hosts. Further, hosts that received a lower prior exposure dose rather than a higher primary dose showed the greatest within-group heterogeneity in expression during re-challenge. Functional enrichment analyses for significantly variable host genes indicated an over-representation of terms involved in the immune systems response to pathogens, namely a diversified inflammatory response, in birds with prior pathogen exposure. The infecting pathogen from the conjunctiva followed similar patterns of heterogeneity in host gene expression, where pathogen infecting hosts with prior exposure had more heterogeneous expression than those infecting pathogen-naive hosts. While the exact mechanisms that underlie greater variation in gene expression cannot be resolved by this study, our results are consistent with the hypothesis that prior host exposure induces a within-host environment that promotes heterogeneous gene expression across both hosts and pathogens. This suggests that to understand the coevolutionary dynamics of infectious diseases we must consider not only the genetic sequence variation, but also gene expression variation in host and pathogen.

ecology↗

bioRxiv2025

Infected host competence overshadows heterogeneity in susceptibility in shaping experimental epizootics

The accelerated rate of disease emergence in recent decades underscores the need to understand conditions that promote or dampen epidemics. Theoretical models consistently show that epidemics are smaller in populations with higher among-individual heterogeneity in susceptibility. Experimental tests of these predictions are rare but critical for understanding how heterogeneity in susceptibility shapes epidemics in natural systems. We directly link data-parameterized models from previous dose response experiments in the house finch and Mycoplasma gallisepticum system to experimental epidemics in replicated aviary mesocosm flocks. We manipulated flock-level heterogeneity in susceptibility by seeding epidemics in flocks composed of either pathogen-naive or previously exposed birds, which prior work showed have higher heterogeneity in susceptibility relative to pathogen-naive populations. We tracked epidemics for over two months, combining empirical data and stochastic compartmental models to address how heterogeneity in susceptibility changes epidemic severity. Consistent with previous work, estimates of heterogeneity in susceptibility based on coefficients of variation were higher for flocks given prior pathogen exposure relative to pathogen-naive flocks. However, in contrast with prior work on individually-housed birds which showed relatively homogeneous susceptibility for pathogen-naive birds, the pathogen-naive flocks in this study were better described by heterogeneous, rather than homogenous, models of susceptibility. This suggests that flock-level epidemics captured sources of heterogeneity absent in controlled experiments, such as transmission heterogeneity. Finally, although prior exposure conferred protection from disease at the individual level, we did not detect predicted effects of prior exposure and its associated flock-level heterogeneity on prevalence. However, our ability to detect effects of prior exposure on flock-level prevalence was obscured by unexpected variation in the competence of the initially pathogen-naive index birds that seeded each epidemic. This variation in infectiousness among index birds significantly predicted flock-level prevalence, with low index bird infectiousness contributing to the absence of detectable epidemics in two of the three naive flocks. Our stochastic simulations generated a wide range of prevalence outcomes for small epidemics over the timescales examined, further underscoring the challenges of measuring transmission dynamics in naturalistic settings, where unexpected variation in host traits such as competence can obscure other factors of interest. Open research statementData are not yet provided. Data and code will be permanently and publicly archived in the Virginia Tech Data Repository if the paper is accepted for publication

ecology↗

bioRxiv2022

A Suite of Advanced Tutorials for the WESTPA 2.0 Rare-Events Sampling Software

We present six advanced tutorials instructing users in the best practices of using key new features and plugins/extensions of the WESTPA 2.0 software package, which consists of major upgrades for enabling applications of the weighted ensemble (WE) path sampling strategy to even larger systems and/or slower processes. The tutorials demonstrate the use of the following key features: (i) a generalized resampler module for the creation of "binless" schemes, (ii) a minimal adaptive binning scheme for more efficient surmounting of free energy barriers, (iii) streamlined handling of large simulation datasets using an HDF5 framework, (iv) two different schemes for more efficient rate-constant estimation, (v) a Python API for simplified analysis of WE simulations, and (vi) plugins/extensions for Markovian Weighted Ensemble Milestoning and WE rule-based modeling at the system biology level. Applications of the tutorials range from atomistic to residue-level to non-spatial models, and include complex processes such as protein folding and the membrane permeability of a drug-like molecule. Users are expected to already have significant experience with running conventional molecular dynamics simulations and completed the previous suite of WESTPA tutorials.

biophysics↗

bioRxiv2021

WESTPA 2.0: High-performance upgrades for weighted ensemble simulations and analysis of longer-timescale applications

The weighted ensemble (WE) family of methods is one of several statistical-mechanics based path sampling strategies that can provide estimates of key observables (rate constants, pathways) using a fraction of the time required by direct simulation methods such as molecular dynamics or discrete-state stochastic algorithms. WE methods oversee numerous parallel trajectories using intermittent overhead operations at fixed time intervals, enabling facile interoperability with any dynamics engine. Here, we report on major upgrades to the WESTPA software package, an open-source, high-performance framework that implements both basic and recently developed WE methods. These upgrades offer substantial improvements over traditional WE. Key features of the new WESTPA 2.0 software enhance efficiency and ease of use: an adaptive binning scheme for more efficient surmounting of large free energy barriers, streamlined handling of large simulation datasets, exponentially improved analysis of kinetics, and developer-friendly tools for creating new WE methods, including a Python API and resampler module for implementing both binned and "binless" WE strategies. Table of Contents/Abstract ImageFor the manuscript "WESTPA 2.0: High-performance upgrades for weighted ensemble simulations and analysis of longer-timescale applications" by Russo et al. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/471280v2_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@575710org.highwire.dtl.DTLVardef@151c3dorg.highwire.dtl.DTLVardef@1f0f525org.highwire.dtl.DTLVardef@6e5956_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗