Biology subjects

Bruns, E.

Publications and source records attributed to Bruns, E..

5 recordsLinked to original sources

bioRxiv2026

When should a pathogen strike? Navigating the landscape of birth pulses and mating season

Susceptibility to pathogens often differs across host life stages, which in turn depends on seasonal host phenology. For many species, juveniles are highly susceptible relative to adults, which given constrained birth periods can lead to seasonal variation in the average host susceptibility. Similarly, for pathogens with complex lifecycles, or seasonally dependent development, peak transmission may be temporally constrained. Maximum pathogen transmission may therefore coincide with a greater abundance of either juvenile or adult hosts. For instance, the birthing season presents a highly susceptible pool of hosts while the mating season presents a higher rate of contact between potentially less susceptible hosts. When these two transmission opportunities are separated in time, it is unclear whether pathogens should evolve a single, intermediate transmission timing or undergo disruptive selection to exploit different host life stages. To investigate how pathogens might navigate this complex landscape, we developed an age-structured model that allows us to test the impacts of host life history on pathogen prevalence and evolution, inspired by a fungal plant pathogen. Parameterizing the model for Silene latifolia, we find that disease prevalence is highest when seed germination coincides with flowering, and that separating the two reduces disease. Using invasion analysis, we find that at the estimated S. latifolia parameters, a single evolutionarily stable transmission timing closely tracks germination time, with infectious flowering centered about seven weeks after the median germination day. When juveniles mature faster or are much more susceptible than adults, or under parameters for Dianthus pavonius, a pathogen genotype that transmits to spring-germinating juveniles and one that transmits later in the year can instead each invade the other and coexist as a polymorphic population when germination is split between spring and summer cohorts. Our model may help explain observed phenological differences seen in wild populations of infected plants.

evolutionary biology↗

bioRxiv2025

Dicer is essential for proper maturation, composition, and function in the postnatal retina.

microRNAs (miRNAs) play a pivotal role during the early phases of retinal development, but their impact on late-phase retinogenesis is unknown. We depleted miRNAs in late retinal progenitor/precursor cells (RPCs/PCs) via a conditional Dicer knock-out. Optical coherence tomography (OCT), electroretinography (ERG), histological, and transcriptional analyses were conducted in young and adult mice. Alterations in gene expression of late-born cells were observed as early as postnatal day 7 (P7), resulting in impaired rod function, a significantly reduced number of rod bipolar cells and their associated function, and a decreased Muller glia population at adult age. These defects appear to be caused by a delay in differentiation/ incomplete maturation, as indicated by an enlarged progenitor/precursor population at young ages that persists into adulthood. Notably, an increased population of HuC/D+ amacrine cells was found. Luciferase assays led us to speculate that this increase may be due to the absence of Elavl3 suppression via RPC-miRNAs. This suggests that Dicer/miRNAs in late RPC/PCs are essential for the proper formation and maturation of late RPC progenies and may also play a role in regulating cell state. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/635135v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@9e0950org.highwire.dtl.DTLVardef@1757e2corg.highwire.dtl.DTLVardef@aeb5ecorg.highwire.dtl.DTLVardef@29accb_HPS_FORMAT_FIGEXP M_FIG C_FIG Summary statementLate-retinal progenitor microRNAs are essential for proper postnatal retinogenesis and retinal function.

developmental biology↗

bioRxiv2023

Neural Correlates of Self-Referential Belief Processes

BackgroundBelief processing as well as self-referential processing have both been consistently associated with cortical midline structures. In addition, seminal neuroimaging papers have implicated cortical regions such as the vmPFC in general belief processing. However, the neural correlates of self-referential belief are yet to be investigated in functional magnetic resonance imaging (fMRI). MethodsIn this fMRI study, we presented 120 statements with trait adjectives as target words to N=27 young healthy participants and asked them to judge whether they believed that these trait adjectives applied to themselves, a self-chosen close person, or a public person (the German chancellor at that time). Participants subsequently rated how certain (0-100%) they were in their judgment. ResultsAs expected, self-referential processing evoked a large cluster in the vmPFC, ACC and dmPFC. For belief, we found an activated cluster in the vmPFC during statement presentation, which partly overlapped with the cluster for self-referential processing. The cluster for self-belief vs. disbelief was similar in location and size to the cluster for general belief processing and distinct from the cluster for self-referential processing. We also found dmPFC activation for uncertainty in belief evaluations. DiscussionWe successfully replicated vmPFC involvement in belief processing and found a common neural correlate for belief and self-belief in the vmPFC. The activation clusters for self-belief versus self-referential processing were distinct, implying distinct neural processes. This insight will prove relevant for investigations in clinical populations with aberrant (self-)belief processing. Furthermore, we replicated the role of the dmPFC in uncertainty, supporting a dual neural process model of belief and certainty.

neuroscience↗

bioRxiv2023

Host-pathogen coevolution promotes the evolution of general, broad-spectrum resistance and reduces foreign pathogen spillover risk

Genetic variation for disease resistance within host populations can strongly impact the spread of endemic pathogens. In plants, recent work has shown that within-population variation in resistance can also affect the transmission of foreign spillover pathogens if that resistance is general. However, most hosts also possess specific resistance mechanisms that provide strong defenses against coevolved endemic pathogens. Here we use a modeling approach to ask how antagonistic coevolution between hosts and their endemic pathogen at the specific resistance locus can affect the frequency of general resistance, and therefore a hosts vulnerability to foreign pathogens. We develop a two-locus model with variable recombination that incorporates both general (resistance to all pathogens) and specific (resistance to endemic pathogens only). We find that introducing coevolution into our model greatly expands the regions where general resistance can evolve, decreasing the risk of foreign pathogen invasion. Furthermore, coevolution greatly expands which conditions maintain polymorphisms at both resistance loci, thereby driving greater genetic diversity within host populations. This genetic diversity often leads to positive correlations between host resistance to foreign and endemic pathogens, similar to those observed in natural populations. However, if resistance loci become linked, the resistance correlations can shift to negative. If we include a third, linkage modifying locus into our model, we find that selection often favors complete linkage. Our model demonstrates how coevolutionary dynamics with an endemic pathogen can mold the resistance structure of host populations in ways that affect its susceptibility to foreign pathogen spillovers, and that the nature of these outcomes depends on resistance costs, as well as the degree of linkage between resistance genes.

evolutionary biology↗

bioRxiv2022

Multimodal disease transmission as a limiting factor for the spatial extent of a host plant

Theoretical models suggest that infectious diseases could play a substantial role in determining species ranges, but few studies have collected the empirical data required to test this hypothesis. Pathogens that sterilize their hosts or spread through frequency-dependent transmission could have especially strong effects on the limits of species distributions because sterilized hosts can serve as long-lived disease reservoirs and frequency-dependent transmission mechanisms are effective even at very low population densities. We collected spatial disease prevalence data and population abundance data for alpine carnations infected by the sterilizing pathogen M. violaceum, a disease that is spread through both frequency-dependent (vector-borne) and density-dependent (aerial spore transmission) mechanisms. Our 13-year study reveals rapid declines in population abundance without a compensatory decrease in disease prevalence. We apply a stochastic, spatial model of disease spread that accommodates spatial habitat heterogeneity to investigate how the population dynamics depend on multimodal (frequency-dependent and density-dependent) transmission. We found that the observed rate of population decline can be readily explained by multimodal transmission, but is unlikely to be explained by either frequency-dependent or density-dependent mechanisms alone. Multimodal disease transmission rates high enough to explain the observed decline predicted that eventual local extinction of the host species is highly likely. Our results add to a growing body of literature showing how multimodal transmission can constrain species distributions in nature. Open ResearchAll scripts associated with the analyses in this manuscript, as well as the data we collected, are available at https://github.com/uricchio/antherSmutDis.

ecology↗