Biology subjects

Sommer, S.

Publications and source records attributed to Sommer, S..

13 recordsLinked to original sources

bioRxiv2026

DICAROS: Diffeomorphic Ancestral Shape Reconstruction on Phylogenies

Reconstructing ancestral morphologies on a phylogenetic tree is a central task in evolutionary morphometrics. Established reconstruction methods, including multivariate Brownian-motion approaches, rely on linear assumptions and do not directly model the correlations between landmarks within a shape, which can oversimplify the reconstructed morphology. The DICAROS method (Diffeomorphic Independent Contrasts for Ancestral Reconstruction of Shapes; Severinsen et al., 2026) instead fuses sibling shapes along branches with large-deformation diffeomorphic (LDDMM) landmark dynamics that model these correlations, so that ancestors remain on the shape manifold. DICAROS was shown to outperform ordinary least-squares, Brownian-motion, and penalized-likelihood reconstruction, particularly on non-symmetric trees. The dicaros package repackages that pipeline as a documented, pip-installable tool that runs on arbitrary landmark datasets from a single command. It handles 2D and 3D landmarks, Newick and NEXUS trees, a choice of Euclidean or Frechet species means, optional anchor-based alignment, and tips backed by a single specimen, and it returns the reconstructed shapes for all nodes together with the tree relabelled at its internal nodes. We demonstrate dicaros on two new datasets: a 2D leaf dataset (217 species) and a 3D guenon skull dataset (22 species).

evolutionary biology↗

bioRxiv2026

Dissociation kinetics and avidity gate SARS-CoV-2 neutralization by HR2 stem helix antibodies

SARS-CoV-2 evolution has reduced the efficacy of clinical monoclonal antibodies, underscoring the need for therapeutics targeting conserved viral regions. The Spike (S) heptad repeat 2 (HR2) stem helix is highly conserved across SARS-CoV-2 variants and related betacoronaviruses. Although antibodies to this region can neutralize infection, their natural occurrence and evolution remain poorly understood. We previously identified human neutralizing antibodies to a conserved peptide within this region (HR2 coldspot). Here, we show that plasma IgG reactivity to this region remains rare, even after repeated antigen exposure. Longitudinal analysis over 30 months revealed continued somatic hypermutation of HR2-specific antibodies, yet none surpassed the potency or breadth of hr2.016, which emerged shortly after primary infection. Crystal structures of four HR2 stem helix antibodies revealed convergent recognition across distinct antibody lineages. Comparison of hr2.016 with its non-neutralizing clonal relative hr2.086 showed that structural convergence masks distinct binding kinetics. Surface plasmon resonance and molecular dynamics simulations revealed a more stable interaction network for hr2.016, with slower dissociation and prolonged S residence time. Neutralization required the IgG format, supporting an avidity-driven mechanism. Together, these findings define kinetic and avidity constraints governing neutralization at the HR2 stem helix and position hr2.016 as a resilient therapeutic candidate.

immunology↗

bioRxiv2026

Monitoring microscope performance in an imaging facility using OMERO-metrics.

Microscopes are essential tools for discoveries on a scale invisible to the unaided human eye. The development of immuno-fluorescence followed by molecular biology techniques and fluorescent fusion proteins have revolutionised the use of optical microscopy in bioscience. The quality of the data produced is dependent upon the sample, its preparation and the instrument used. However, instruments can degrade over time without easily visible changes to the produced images and, in turn, negatively impacts results. By testing instruments and doing comparisons between results over time and between different instruments, problems can be highlighted and corrective action can be taken. Using small fluorescent beads the point spread function (PSF) of the microscope can be recorded and the image resolution measured. Beads were prepared in a concentration matched to the field of view size and dried onto coverslips and mounted on slides. The beads were then imaged as 3D Z-stacks of sufficient size to fully enclose the PSF of the system. This data was uploaded to OMERO and processed using OMERO-metrics, an OMERO plugin developed for this purpose. This paper summarizes the development of workflows and protocols to enable this process, presents the results obtained and demonstrates the detection of significant instrument issues.

biophysics↗

bioRxiv2026

From nest to hatchling: nidobiome assembly and host selection in oviparous vertebrates without parental care

Early microbial assembly is fundamental for host development and fitness, yet in oviparous vertebrates lacking parental care, the mechanisms by which eggs and neonates acquire their microbiome remain poorly understood. The nidobiome concept predicts that maternal and environmental sources, and host selection, collectively shape early microbial communities. To test this, we conducted a longitudinal study on microbial assembly in the yellow-spotted Amazon river turtle (Podocnemis unifilis). We sampled maternal mucosa, freshly laid outer eggshells, and nest sand before incubation, along with hatchery sand, outer and inner eggshells, and hatchling cloaca after incubation. Using 16S and ITS amplicon sequencing to quantify microbial diversity, we observed that freshly laid outer eggshells shared bacterial diversity with maternal mucosa, whereas nest sand harboured a distinct community, providing evidence of early vertical transmission. After incubation, eggshell microbial communities became more even without a change in richness, while nest sand communities exhibited the opposite pattern, reflecting divergent host-environment assembly dynamics. SourceTracker analyses confirmed contributions from both maternal and environmental sources, yet inner eggshells and hatchling cloaca assembled distinct communities compared with outer eggshells, indicating that host selection is largely deterministic. Interkingdom interactions favoured beneficial microorganisms, suggesting active host filtering throughout development. Even in the presence of fusariosis, a widespread threat in turtle nests, host selection enriched protective taxa, linking microbiome composition to hatching success. These findings demonstrate that maternal seeding, priority effects, and deterministic host selection govern early-life microbiome assembly in oviparous reptiles without parental care, with direct implications for microbe-informed conservation strategies. ImportanceUnderstanding early-life microbial assembly is critical for uncovering the ecological and evolutionary drivers of host-microbiome interactions. This study reveals how microbial communities develop in oviparous vertebrates lacking parental care, highlighting key mechanisms such as vertical transmission, host selection, and environmental modulation that shape early-life microbiomes. Our results demonstrate that maternal microbiota seeding and priority effects play fundamental roles in structuring egg-associated microbial communities, directly influencing host fitness and survival. By identifying deterministic processes that enrich beneficial microorganisms during early development, this research underscores the pivotal role of microbiomes in host resilience and adaptation. These insights carry urgent conservation implications, offering microbe-informed strategies to mitigate emerging threats, such as diseases in vulnerable species like the yellow-spotted Amazon river turtle, and emphasising the broader importance of microbiome stewardship for ecosystem health.

ecology↗

bioRxiv2026

Morphological integration of the avian beak facilitates evolution along lines of least resistance

Innovation of the avian beak has facilitated a grand radiation of >11,000 species, with vast morphological disparity suggesting limited developmental constraints on beak diversification. We assess four macroevolutionary currencies - integration, disparity, phenotypic evolutionary rates, and ecological specialization - using 3D beak landmarks for 8,627 species mapped to a complete avian supertree with a resolved genomic backbone. We introduce a Gini coefficient-based metric of ecological specialization, measuring evolutionary time spent across trophic niches. Phylogenetic regressions show that lineages with faster phenotypic rates exhibit stronger beak integration (landmark covariation) and more generalised diets, while beak disparity declines with greater trophic specialization. These results suggest that integration facilitates, rather than constrains, phenotypic evolution, by channeling variation along lines of least resistance. Future work should explore modular structure of the bird beak, which arises from multiple genetic and developmental factors.

evolutionary biology↗

bioRxiv2025

Synergistic 3D, multispectral, and thermal image analysis via supervised machine learning for improved detection of root rot symptoms in hydroponically-grown flat-leaf parsley

Root rot in hydroponically-grown leafy vegetables is difficult to detect via conventional manual and machine vision-based approaches as symptoms of infection are not clearly visible on the canopy at earlier stages of infection. Hence, the present study investigates the potential of using machine learning for assessing canopy information obtained from multiple imaging platforms synergistically to improve root rot detection. Herein, flat-leaf parsley seedlings were grown in an experimental hydroponic vertical farm and inoculated with Pythium irregulare and Phytophthora nicotianae. Subsequently, the seedlings were imaged via 3D, multispectral, and thermal sensors at various stages of growth to obtain twenty-six image-based plant features. Following a preliminary screening of redundant features via regression analysis, data for seventeen image features associated with morphometric, spectral, and thermal attributes was co-analyzed using supervised machine learning by Support Vector Machines (SVM). Exhaustive feature selection using different SVM kernels and maximum feature thresholds was performed to identify optimal feature subsets. It was observed that combining parameters obtained from all three imaging platforms enabled better identification of infected samples (>99%) than using a higher number of attributes from individual imaging systems. In addition, model performance was improved considerably by including temporal information during model training. Hence, it may be inferred that fusion of data from multiple imaging systems and using it with temporal information can enable better real-time high-throughput monitoring of root rot.

plant biology↗

bioRxiv2025

Stochastic Phylogenetic Models of Shape

Phylogenetic modeling of morphological shape in two or three dimensions is one of the most challenging statistical problems in evolutionary biology. As shape data are inherently correlated and non-linear, most naive methods for phylogenetic analysis of morphological shape fail to capture the biological realities of evolving shapes. In this study we propose a novel framework for evolutionary analysis of morphological shape which facilitates stochastic character mapping on landmark shapes. Our framework is based on recent advances in mathematical shape analysis and models the evolution of shape as a diffusion process that accounts for the evolutionary correlation between nearby landmarks. The diffusion process we consider is parametrized in terms of meaningful parameters describing the evolutionary rate and the degree of spatial autocorrelation among landmarks. The framework we propose assumes that the phylogenetic tree is fixed and uses a Metropolis-Hastings Markov Chain Monte Carlo sampling scheme for inferring ancestral shapes and parameters of the model. We evaluate the new inference algorithm using simulations and show that the method leads to improved estimates of the shape at the root and well-calibrated credible sets of shapes at internal nodes. In addition, we also compare the diffusion parameter describing the degree of spatial autocorrelation to an existing metric of integration and find that they quantify integration in a shape in a similar way. To illustrate the method, we also apply it to a previously published data set of butterfly wing images.

evolutionary biology↗

bioRxiv2025

Diffeomorphic Independent Contrasts for Ancestral Reconstruction of Shapes

AO_SCPLOWBSTRACTC_SCPLOWAncestral reconstruction is a fundamental challenge in evolutionary biology, requiring methods that can capture complex morphological changes while accounting for phylogenetic relationships. Current approaches are based on linear assumptions that often oversimplify the spatial relationships between anatomical features and fail to account for landmark correlations within shapes. Here, we introduce a novel method that combines the ability of Large Deformation Diffeomorphic Metric Mapping (LDDMM) to model smooth, invertible transformations between shapes while preserving the relationships between landmarks with Felsensteins Independent Contrasts (IC) to iteratively reconstruct ancestral shapes along the branches of a phylogenetic tree. We call this method Diffeomorphic Independent Contrasts for Ancestral Reconstruction of Shapes (DICAROS). We validate DICAROS against two existing methods: (1) Linear predictors using Ordinary Least Squares and (2) Ancestral character estimation using maximum likelihood under Brownian Motion and apply DICAROS to a dataset of swallowtail butterfly species (Family Papilonidae, Order Lepiodetra) to reconstruct the ancestral shape and visualize evolutionary trajectories in a phylomorphospace from the contrasts. We conclude that DICAROS outperforms the existing methods in terms of accuracy and provides a more accurate reconstruction of the ancestral shape for non-symmetric phylogenetic trees. With DICAROS we show a transition between un-tailed and tailed papilinodae species while also illustrating how images of modern species would look under the DICAROS ancestral reconstruction

evolutionary biology↗

bioRxiv2024

Fertilization impacts microbiomes along the grassland trophic chain

Agricultural grasslands are often managed intensively, influencing soil properties and microbial communities. This can result in significant community changes and challenges to health and function at different levels along the trophic chain. This study investigates how fertilization affects microbial communities in grassland ecosystems in multiple connected trophic compartments. Shifts in microbial composition occurred in response to fertilization with effects being host-dependent and changes being more pronounced in belowground compartments. Strong interactions between trophic levels facilitated transmission of bacterial genera from soil and roots to higher trophic levels. Pig slurry- derived microbes were found in all compartments, but their low prevalence suggests an indirect effect of fertilisation, primarily due to changes in nutrient availability. Our findings emphasize the importance of considering both individual compartments and trophic interactions in ecosystems to fully understand the effects of anthropogenic disturbances on environmental and human health.

microbiology↗

bioRxiv2022

Anthropogenic disturbance impacts gut microbiome homeostasis in a Malagasy primate

Increasing anthropogenic disturbances in Madagascar are exerting constrains on endemic Malagasy lemurs and their habitats, with possible effects on their health and survival. An important component of health is the gut microbiome, which might be disrupted by various stressors associated with environmental change. We have studied the gut microbiome of grey-brown mouse lemurs (Microcebus griseorufus), one of the smallest Malagasy primates and an important model of the convergent evolution of diseases. We sampled two sites: one situated in a national park and the other consisting of a more disturbed site around human settlement. We found that more intense anthropogenic disturbances indeed disrupted the gut microbiome of this lemur species with a marked reduction in its diversity and led to a shift in microbial community composition. Interestingly, we noted a decrease in beneficial bacteria together with a slight increase in disease-associated bacteria and alterations in microbial metabolic functions. Because of the crucial services provided by the microbiome to host health and in disease, such negative alterations in the gut microbiome of the lemur from anthropogenically disturbed habitat might impact the health of mouse lemurs, rendering them susceptible to diseases and ultimately affecting their survival in the shrinking biodiversity seen in Madagascar. Gut microbiome analyses might thus serve as an early warning signal for pending threats to lemur populations.

microbiology↗

bioRxiv2021

Evidence of MHC class I and II influencing viral and helminth infection via the microbiome in a non-human primate

Until recently, the study of major histocompability complex (MHC) mediated immunity has focused on the direct link between MHC variability and susceptibility to parasite infection. However, MHC genes can also influence host health indirectly through the sculpting of the bacterial community that in turn shape immune responses. We investigated the links between MHC class I and II gene variability gut microbiome diversity and micro- (adenovirus, AdV) and macro- (helminth) parasite infection probabilities in a wild population of non-human primates, mouse lemurs of Madagascar. This setup encompasses a plethora of underlying interactions between parasites, microbes and adaptive immunity in natural populations. Both MHC classes explained shifts in microbiome composition and the effect was driven by a few select microbial taxa. Among them were three taxa (Odoribacter, Campylobacter and Prevotellaceae-UCG-001) which were in turn linked to AdV and helminth infection status, evidence of the indirect effect of the MHC via the microbiome. Our study provides support for the coupled role of MHC variability and microbial flora as contributing factors of parasite infection. Author summaryThe selective pressure of the major histocompatibility complex (MHC) on microbial communities, and the potential role of this interaction in driving parasite resistance has been largely neglected. Using a natural population of the primate Microcebus griseorufus, we provide evidence of two outstanding findings: that MHCI and MHCII diversity shapes the composition of the gut microbiota; and that select taxa associated with MHC variability predicted adenovirus and helminth infection status. Our study highlights the importance of incorporating the microbiome when investigating parasite-mediated MHC selection.

evolutionary biology↗

bioRxiv2019

A novel workflow to improve multi-locus genotyping of wildlife species: an experimental set-up with a known model system

AO_SCPCAPBSTRACTC_SCPCAPGenotyping novel complex multigene systems is particularly challenging in non-model organisms. Target primers frequently amplify simultaneously multiple loci leading to high PCR and sequencing artefacts such as chimeras and allele amplification bias. Most next-generation sequencing genotyping pipelines have been validated in non-model systems whereby the real genotype is unknown and the generation of artefacts may be highly repeatable. Further hindering accurate genotyping, the relationship between artefacts and copy number variation (CNV) within a PCR remains poorly described. Here we investigate the latter by experimentally combining multiple known major histocompatibility complex (MHC) haplotypes of a model organism (chicken, Gallus gallus, 43 artificial genotypes with 2-13 alleles per amplicon). In addition to well defined "optimal" primers, we simulated a non-model species situation by designing "naive" primers, with sequence data from closely related Galliform species. We applied a novel open-source genotyping pipeline (ACACIA) to the data, and compared its performance with another, previously published, pipeline. ACACIA yielded very high allele calling accuracy (>98%). Non-chimeric artefacts increased linearly with increasing CNV but chimeric artefacts leveled when amplifying more than 4-6 alleles. As expected, we found heterogeneous amplification efficiency of allelic variants when co-amplifying multiple loci. Using our validated ACACIA pipeline and the example data of this study, we discuss in detail the pitfalls researchers should avoid in order to reliably genotype complex multigene systems. ACACIA and the datasets used in this study are publicly available at GitLab and FigShare (https://gitlab.com/psc_santos/ACACIA and https://figshare.com/projects/ACACIA/66485).

molecular biology↗

bioRxiv2018

Earthworms and Cadmium - heavy metal resistant gut bacteria as indicators for heavy metal pollution in soils?

Preservation of the soil resources stability is of paramount importance for the ecosystem, particularly in the current era of environmental change, which presents a severe pollution burden (e.g. by heavy metals) to soil ecosystems and its fauna. Gut microbiomes are becoming recognized as important players in organism health, with comprehension of their perturbations in the polluted environment offering new insights into the nature and extent of heavy metal effects on the health of soil biota. Our aim was therefore to evaluate the effect of environmentally relevant heavy metal concentrations of cadmium (Cd) on the earthworm gut microbiota. Cd exposure led to perturbations of several heavy metal resistant taxa as well as taxa able to bind heavy metals, revealing the potential of the earthworm-microbiota system in overcoming humancaused heavy metal pollution. An indicator species analysis linked bacterial genera Paenibacillus and Flavobacterium, and members of the order Actinomycetales with Cd treatment, suggesting the possible use of these bacterial taxa as biomarkers of exposure for Cd stressed soils. The results of this study will be essential to understanding of the soil fauna health, under anthropogenic disturbance, and will have implications for environmental monitoring and protection of soil resources.\n\nImportanceSoil heavy metal pollution presents a severe burden for soil invertebrates and can have impact on their health, which in turn reflects on the health of the entire ecosystem. Gut microbiome is recognized as a central driver of the host health and its shifts can have severe consequences for the host. In this study we investigated the impact of cadmium (Cd) on earthworm gut microbiota, in a controlled experiment using cutting edge next generation sequencing and state of the art bioinformatics tools. The significance of this study is in identifying the gut bacterial taxa which are indicators for Cd treatment and are potential biomarkers of exposure to Cd. Therefore, this study contributes to develop efficient measures to qualify environmental pollution and to protect fragile soil resources and ultimately human health.

microbiology↗