V Cano, A. | bioRxiv Science

bioRxiv2026

Fine-scale behavioural dynamics separates adaptive sickness behaviour from injury and infection pathology

Animals commonly reduce activity during infection, but it remains unclear when such "sickness behaviours" reflect adaptive host regulation versus injury responses or pathogen-driven pathology. We combined high-resolution behavioural phenotyping with experimental partitioning of injury, immune stimulation, and live bacterial infection to dissect these effects in Drosophila melanogaster. Using an outbred fly population, we tracked individual locomotor activity at 1 minute resolution for 400 hours in males and females subjected to one of four treatments: unhandled control, septic injury with buffer, immune stimulation with heat killed Pseudomonas entomophila, or septic infection with live P. entomophila. Across the early post-challenge window, total activity diverged most strongly between the unhandled control and the challenged treatments. Fine-scale analyses revealed that immune challenge primarily reshaped the microstructure of movement: the number of activity bouts changed little, whereas active bout lengths were shorter and inactive periods were modestly prolonged, especially in females. Among infected flies, individuals that died early exhibited a collapse of bout structure, showing prolonged inactivity punctuated by brief, sometimes intense, movements, whereas longer-lived infected flies maintained patterns closer to controls. These behavioural differences were detectable in the very early stages of infection: within the first 24-hours post-infection early-dying flies had both a reduced probability of initiating movement from rest and a reduced probability of sustaining on-going activity, consistent with pathogen-induced debilitation; longer-lived infected flies showed near-normal state-transition profiles. This early suppression of activity in acutely dying males was positively associated with subsequent survival time, suggesting a contribution of adaptive restraint alongside pathology. By resolving fine-scale behaviour and state-transition dynamics, our approach clarifies which aspects of "sickness behaviour" are likely adaptive and which signal pathology.

animal behavior and cognition↗

bioRxiv2021

Mutation bias shapes the spectrum of adaptive substitutions

Evolutionary adaptation often occurs via the fixation of beneficial point mutations, but different types of mutation may differ in their relative frequencies within the collection of substitutions contributing to adaptation in any given species. Recent studies have established that this spectrum of adaptive substitutions is enriched for classes of mutations that occur at higher rates. Yet, little is known at a quantitative level about the precise extent of this enrichment, or its dependence on other factors such as the beneficial mutation supply or demographic conditions. Here we address the extent to which the mutation spectrum shapes the spectrum of adaptive amino acid substitutions by applying a codon-based negative binomial regression model to three large data sets that include thousands of amino acid changes identified in natural and experimental adaptation in S. cerevisiae, E. coli, and M. tuberculosis. We find that the mutation spectrum has a strong and roughly proportional influence on the spectrum of adaptive substitutions in all three species. In fact, we find that by inferring the mutation rates that best explain the spectrum of adaptive substitutions, we can accurately recover species-specific mutational spectra obtained via mutation accumulation experiments. We complement this empirical analysis with simulations to determine the factors that influence how closely the spectrum of adaptive substitutions mirrors the spectrum of amino acid variants introduced by mutation, and find that the predictive power of mutation depends on multiple factors including population size and the breadth of the mutational target for adaptation. SIGNIFICANCE STATEMENTHow do mutational biases influence the process of adaptation? Classical neo-Darwinian thinking assumes that selection alone determines the course of adaptation from abundant pre-existing variation. Yet, theoretical work shows that under some circumstances the mutation rate to a given variant may have a strong impact on the probability of that variant contributing to adaptation. Here we introduce a statistical approach to analyzing how mutation shapes protein sequence adaptation, and show that the mutation spectrum has a proportional influence on the changes fixed in adaptation observed in three large data sets. We also show via computer simulations that a variety of factors can influence how closely the spectrum of adaptive substitutions mirrors the spectrum of variants introduced by mutation.

evolutionary biology↗