Biology subjects

McNally, L.

Publications and source records attributed to McNally, L..

6 recordsLinked to original sources

bioRxiv2026

Evolutionary Coupling of Flagellar Motility and Type VI Secretion Systems Across Bacteria

Bacteria use both motility and antagonism to compete in spatially structured environments, but whether these traits evolve together across broad bacterial diversity remains unclear. We developed a spatial kin-competition model predicting that motility should couple robustly with contact-dependent weapons by increasing encounter rates with competitors, whereas coupling with diffusible weapons should be weaker and context-dependent. To test these predictions, we performed a comprehensive analysis of 11,365 bacterial genomes across the Tree of Life (ToL). By utilising large-scale homology-based searches, we annotated flagellar, T6SS, and bacteriocin components and then applied phylogenetic comparative models to examine evolutionary associations. T6SS presence was strongly associated with flagellar motility: T6SS-positive lineages were predominantly flagellated, and BayesTraits supported a dependent model of FliC and T6SS evolution. In contrast, bacteriocins showed no detectable evolutionary coupling with flagellar motility. Transition-rate analyses further indicated that T6SS gain was strongly biased towards motile lineages, even though T6SS loss was common overall. These results support an asymmetric macroevolutionary relationship between bacterial motility and antagonism, in which flagellar motility is robustly coupled to contact-dependent competition but not to diffusible antagonistic systems.

evolutionary biology↗

bioRxiv2026

Optimal virulence in ageing populations

Global populations are ageing at an unprecedented rate. For many diseases, age is a strong indicator of susceptibility, morbidity, or mortality. Principles of evolutionary biology can be leveraged to understand how pathogens may optimally exploit new populations, and the impact of this on the global burden of infectious-disease-induced mortality. We parameterised an age-specific R0 model with 2017 epidemiological data on Measles, Tuberculosis, Meningitis, and Ebola, and age-specific demographic estimates for 2017 and 2050, for the seven Global Burden of Disease super-regions. We explored the theoretical trade-offs between pathogen virulence & transmission, and virulence & host recovery, parameterising trade-off parameters using Latin Hypercube Sampling. Population ageing between 2017-2050 saw an increase in virulence induced mortality in four settings: 1) Ebola in sub-Saharan Africa, 2) Measles in central/eastern Europe & central Asia region, 3) Measles in North Africa & the Middle East and 4) Tuberculosis in the central/eastern Europe & central Asia region. The decrease in infection duration due to an increase of elderly people drives pathogen virulence down for diseases in the remaining settings. Understanding the mechanisms that shape pathogen dynamics and leveraging this to predict future challenges is key to endemic disease management in a rapidly changing world. Author SummaryKey aspects of disease transmission including susceptibility to infection, the severity of infection, and the probability of dying from that infection, are affected by host age. Global populations are rapidly ageing, so that the mean age of most populations is generally higher than it used to be and is set to continue on this trajectory. This suggests that the dynamics of infectious diseases are also likely to change, although infectious disease dynamics tend to be non-linear as these key parameters interact. We have developed a dynamic modelling framework to explore how changes in population age structure might impact the optimal level of pathogen virulence in a population. We have chosen four infectious diseases as case studies, that differentially impact certain age classes to illustrate these dynamics. We have parameterised this framework with open access data for each of the seven Global Burden of Disease super-regions and show that population ageing can increase virulence for several diseases in differing global regions, whilst increased background rates of mortality can drive virulence down in others.

evolutionary biology↗

bioRxiv2024

Easy come, easier go: mapping the loss of flagellar motility across the tree of life

Bacterial swimming is mostly powered by the bacterial flagellar motor and the number of proteins involved in the flagellar motor can vary. Quantifying the proteins present in flagellar motors from a range of species delivers insight into how motility has changed throughout history and provides a platform for estimating from its genome whether a species is likely to be motile. We conducted sequence and structural homology searches for 54 flagellar pathway proteins across 11,365 bacterial genomes and developed a classifier with up to 95% accuracy that could predict whether a strain was motile or not. We then mapped the evolution of flagellar motility across the GTDB bacterial tree of life. We confirmed that the last common bacterial ancestor had flagellar motility and that the rate of loss of this motility was four-fold higher than the rate of gain. We showed that the presence of filament protein homologues was highly phylogenetically correlated with motility and that all species classified as motile contained at least one filament homologue. We calculated the rate of gain and loss for each flagellar protein and that the filament protein FliC was highly correlated with motility across the tree of life. We then measured the correlation of each flagellar motor protein with FliC and showed that the filament, rotor, and rod and hook proteins were all highly correlated with FliC, and thus with motility. We calculated the differential rates of gain and loss for each flagellar protein and quantified which genomes encoded for partial sets of flagellar proteins, indicating potential pathways by which motility could be lost. Overall, we show that filament, rod and hook and rotor proteins are conserved when flagellar motility is preserved and that the presence or absence of a FliC homologue is a good, simple predictor of whether or not a species has flagellar motility.

microbiology↗

bioRxiv2020

A mixed model approach for estimating drivers of microbiota community composition and differential taxonomic abundance

O_LINext-generation sequencing (NGS) and meta-barcoding approaches have revolutionized understanding of within-host communities, such as the gut microbiome, in humans and laboratory animals. The application of such approaches in wild animal populations is growing, but there is a disconnect between the widely-applied generalised linear mixed model (GLMM) approaches commonly used to study phenotypic variation and the statistical toolkit from community ecology which is typically applied to meta-barcoding data. C_LIO_LIHere, we describe and illustrate a novel GLMM-based approach for analysing the taxon-specific sequence read counts derived from standard meta-barcoding data. This approach allows us to decompose the contribution of different drivers of variation in community structure (e.g. year, season, individual host), via interaction terms in the random effects structure of the model. We also show how these models can be used to determine the degree to which specific taxa or taxonomic groups are responsible for variance attributed to different drivers. C_LIO_LITo illustrate this approach, we applied it to two cross-sectional meta-barcoding data sets from the Soay Sheep population of St. Kilda. The GLMM approach yielded results that were in agreement with more classical approaches from community ecology, showing that variation the gut microbiota community in these sheep was better explained by age group than by season. We were able to quantify the contributions of different sources of variation to community structure, and also to drill down into the model predictions to show that the age effects we observed were principally due to increases in taxa of the phyla Bacteroidetes and declines in taxa of the phyla Firmicutes. C_LIO_LIOur proposed models offer a powerful new approach to understanding the drivers of variation in estimates of community structure derived from meta-barcoding data. We discuss how our approach could be readily adapted to allow researchers to estimate that contribution of host genotype, environment, and microbial/parasite phylogeny to observed community structure, and thus provide a powerful means to answer emerging questions surrounding the ecological and evolutionary roles of within-host communities. C_LI

evolutionary biology↗

bioRxiv2018

Focussing on resistance to front-line drugs is the most effective way to combat the antimicrobial resistance crisis

In medical, scientific and political arenas relating to antimicrobial resistance (AMR) there is currently an intense focus on multi-drug resistant pathogens that render last-line antimicrobial treatments ineffective. We question the current emphasis of attention on resistance to last-line antimicrobials, arguing that tackling resistance to front-line antimicrobials has a greater public health benefit. Using AMR monitoring data on 25 drug-pathogen combinations from across Europe, here we show that the presence of front-line pathogen resistance initiates a cascade of resistance selection that ultimately leads to pathogen resistance to last-line antimicrobials. We then interrogate, by modelling the dynamics of resistance evolution, whether 3 key interventions in the strategic response to AMR are more effectively targeted at front-line or last-line treatment. We show that interventions that make front-line therapy more effective by use of antimicrobial adjuvants or front-line resistance diagnostics or by introduction of a novel, front-line antimicrobial all lead to a larger reduction in mortality and morbidity than the same interventions implemented in last-line therapy. Mass use of a newly discovered antimicrobial in front-line infection management to maximise its public health benefit is contrary to current policy but may provide valuable incentives for drug developers. We demonstrate that funding, publications, and attention to those publications do not reflect the importance of front-line antimicrobials and are disproportionately devoted to last-line antimicrobials that account for less than 10% of antimicrobial prescriptions. While studying resistance to last-line drugs is undoubtedly important, our work relays a strong message to public health agencies, funding bodies, and researchers that allocating resources to front-line infections can be a more effective way to combat the antimicrobial resistance crisis.

evolutionary biology↗

bioRxiv2017

Division of labor, bet hedging, and the evolution of mixed biofilm investment strategies

Bacterial cells, like many other organisms, face a tradeoff between longevity and fecundity. Planktonic cells are fast growing and fragile, while biofilm cells are often slower growing but stress resistant. Here we ask: why do bacterial lineages invest simultaneously in both fast and slow growing types? We develop a population dynamical model of lineage expansion across a patchy environment, and find that mixed investment is favored across a broad range of environmental conditions, even when transmission is entirely via biofilm cells. This mixed strategy is favored because of a division of labor, where exponentially dividing planktonic cells can act as an engine for the production of future biofilm cells, which grow more slowly. We use experimental evolution to test our predictions, and show that phenotypic heterogeneity is persistent even under selection for purely planktonic or purely biofilm transmission. Furthermore, simulations suggest that maintenance of a biofilm subpopulation serves as a cost-effective hedge against environmental uncertainty, which is also consistent with our experimental findings.

microbiology↗