Biology subjects

Janzen, T.

Publications and source records attributed to Janzen, T..

16 recordsLinked to original sources

bioRxiv2026

Caste-specific ageing emerges from the evolution of resource allocation in eusocial insects

Eusocial insects have extreme intraspecific lifespan variation, where queens are long-lived (up to 30 years) whereas workers only live for a few months or years at most. Several studies have invoked the disposable soma theory to explain the evolution of caste-specific ageing in eusocial insects, which proposes that senescence results from a resource allocation trade-off between maintenance vs. reproduction. An extension of this theory to eusocial insects is that caste-specific ageing could emerge from a resource allocation trade-off between castes. However, to date this idea has not been formalised in a theoretical model. Here, we present an individual-based model for the evolution of ageing in social insects. In our model, queens and workers die when their nutritional state becomes too low. The evolving trait in our model is the age-specific resource allocation of individual workers, who can allocate resources between themselves, other workers, and the queen. We find that lifespan differences between queens and workers emerge from the evolved resource allocation within colonies, which are within the range of empirically observed lifespans of queens and workers in monogynous eusocial insects. Caste-specific ageing evolves in our model because queens obtain large amounts of resources, which allows them to be long-lived and highly fertile, whereas workers evolve to give resources away to enhance the queens reproduction and thereby their own indirect fitness. We also observe that age polyethism emerges, where young workers nurse the brood and older workers forage. Overall, our model demonstrates that both caste-specific ageing and age-related worker division of labour emerge as a consequence of evolved within-colony resource allocation.

evolutionary biology↗

bioRxiv2025

Programming alphavirus with IFN-γ overrides the adverse effects of macrophages on oncolytic virotherapy

Interference by tumor-associated macrophages may significantly reduce the efficacy of therapeutic viruses designed to infect cancer cells and activate antitumor T-cells. Using a computational model, we hypothesized that viruses encoding a T cell-stimulating signal, like IFN-{gamma}, could overcome this barrier. We engineered an alphavirus-based replicon expressing IFN-{gamma} and evaluated its effect in various human-derived tumor-immune coculture systems and an in vivo murine model. While alphavirus replicons do not replicate in macrophages, macrophages acted as a barrier, limiting tumor infection in a frequency-dependent but phenotype-independent manner. Nonetheless, T-cell activation occurred even when only a fraction of infected tumor cells expressed IFN-{gamma}, regardless of macrophage presence, frequency, or phenotype. Additionally, viral stimulation drove macrophage-repolarization towards a pro-inflammatory phenotype favoring T-cell activation. These findings highlight a strategy for optimizing virotherapy in macrophage-rich tumors by designing viruses that stimulate T-cell activation, ensuring therapeutic efficacy.

immunology↗

bioRxiv2024

Inbreeding and demography interact to impact population recovery from bottlenecks

Biodiversity loss driven by climate change and human activities poses a critical global challenge. Population restoration and reintroduction programs are essential for mitigating this threat, yet their outcomes are often unpredictable due to poorly understood success factors. The conservation program of the crested ibis (Nipponia nippon) marks a successful example where the population rose from seven survivors to over 9,000 in the past four decades. To learn whether this successful restoration was due to chance or largely repeatable, we developed an individual-based model that simulates the restoration process by incorporating life-history parameters from empirical data. Our simulation results closely mirror empirical findings, including the time taken to reach the current population size and population-level inbreeding coefficients. We further analyzed the model to compare the effectiveness of two reintroduction strategies and analyzed how inbreeding depression interacts with demography to influence the chance of recovery from bottlenecks. The reintroduction simulations reveal that the firework approach (one-source translocations) outperforms the stepping-stone (serial translocations) approach in restoration effectiveness. Our simulations over broad demographic parameters demonstrate that the net effect of inbreeding varies with species-specific demography, and highlight the importance of considering this interaction when interpreting conservation outcomes and designing future reintroduction programs.

ecology↗

bioRxiv2024

Phylogenetic tree statistics: a systematic overview using the new R package 'treestats'

Phylogenetic trees are believed to contain a wealth of information on diversification processes. Comparing phylogenetic trees is not straightforward due to their high dimensionality. Researchers have therefore defined a wide range of one-dimensional summary statistics. However, it remains unexplored to what extent these summary statistics cover the same underlying information and what summary statistics best explain observed variation across phylogenies. Furthermore, a large subset of available summary statistics focusses on measuring the topological features of a phylogenetic tree, but are often only explored at the extreme edge cases of the fully balanced or unbalanced tree and not for trees of intermediate balance. Here, we introduce a new R package that provides speed optimized code to compute 54 summary statistics. We study correlations between summary statistics on empirical trees and on trees simulated using several diversification models. Furthermore, we introduce an algorithm to create intermediately balanced trees in a well-defined manner, in order to explore variation in summary statistics across a balance gradient. We find that almost all summary statistics are correlated with tree size, and it is difficult if not impossible to correct for tree size, unless the tree generating model is known. Furthermore, we find that across empirical and simulated trees, at least two large clusters of correlated summary statistics can be found, where statistics group together based on information used (topology or branching times). However, the finer grained correlation structure appears to depend strongly on either the taxonomic group studied (in empirical studies) or the diversification model (in simulation studies). Nevertheless, we can identify multiple groups of summary statistics that are strongly and consistently correlated, indicating that these statistics measure the same underlying property of a tree. Lastly, we find that almost all topological summary statistics vary non-linearly and sometimes even non-monotonically with our intuitive balance gradient. Therefore, in order to avoid introducing biases and missing underlying information, we advocate for selecting as many summary statistics as possible in phylogenetic analyses. With the introduction of the treestats package, which provides fast and reliable calculations, such an approach is now routinely possible.

bioinformatics↗

bioRxiv2023

The evolutionary age-range size relationship is modulated by insularity and dispersal in plants and animals

Earth is home to millions of plant and animal species, with more than 40 thousand species facing extinction worldwide (Diaz et al. 2019). Species range size is particularly important in this context because it influences extinction risk (Purvis et al. 2000, Gaston & Fuller 2009), but the causes underlying the wide natural variation in range size remain poorly known. Here, we investigate how evolutionary age is related to present-day range size for over 25,000 species of mammals, birds, reptiles, amphibians, reef fishes, and plants. We show that, on average, older species have significantly larger ranges, but the effect of age on range size is modulated by clade, geographical context and dispersal ability. Specifically, age does not affect range size for island species, because islands limit dispersal and hence range size, regardless of species age. Furthermore, species from clades with high dispersal capabilities obtain large ranges faster, thereby further neutralizing the relationship between age and range size. Our results can help supporting global conservation priorities, by showing that species that are young, occupy islands, and/or are dispersal limited often have small ranges and therefore increased extinction risk.

ecology↗

bioRxiv2023

From Fossils to Living Canids: Two Contrasting Perspectives on Biogeographic Diversification

The Canidae are an ecologically important group of dog-like carnivores that arose in North America and spread across the planet around 10 million years ago. The current distribution patterns of species, coupled with their phylogenetic structure, suggest that Canidae diversification may have occurred at varying rates across different biogeographic areas. However, such extant-only analyses undervalued the groups rich fossil history because of a limitation in methods development. Current State-dependent Speciation and Extinction (SSE) models are (i) often parameter-rich which hinders reliable application to relatively small clades such as the Caninae (the only extant subclade of the Canidae consisting of 36 extant species); and (ii) often assume as possible states only the states that extant species present. Here we extend the SSE method SecSSE to apply to phylogenies with extinct species as well (111 Caninae species) and compare the results to those of analyses with the extant-species-only phylogeny. The results on the extant-species tree suggest that distinct diversification patterns are related to geographic areas, but the results on the complete tree do not support this conclusion. Furthermore, our extant-species analysis yielded an unrealistically low estimate of the extinction rate. These contrasting findings suggest that information from extinct species is different from information from extant species. A possible explanation for our results is that extinct species may have characteristics (causing their extinction), which may be different from the characteristics of extant species that caused them to be extant. Hence, we conclude that differences in biogeographic areas probably did not contribute much to the variation in diversification rates in Caninae.

evolutionary biology↗

bioRxiv2022

Resource sharing leads to the emergence of division of labour

Division of labour occurs in a broad range of organisms. Yet, how division of labour can emerge in the absence of pre-existing interindividual differences is poorly understood. Using a simple but realistic model, we show that in a group of initially identical individuals, division of labour emerges spontaneously if returning foragers share part of their resources with other group members. In the absence of resource sharing, individuals follow an activity schedule of alternating between foraging and other tasks. If non-foraging individuals are fed by other individuals, their alternating activity schedule becomes interrupted, leading to task specialisation and the emergence of division of labour. Furthermore, nutritional differences between individuals reinforce division of labour. Such differences can be caused by increased metabolic rates during foraging or by dominance interactions during resource sharing. Our model proposes a plausible mechanism for the self-organised emergence of division of labour in animal groups of initially identical individuals. This mechanism could also play a role for the emergence of division of labour during the major evolutionary transitions to eusociality and multicellularity.

evolutionary biology↗

bioRxiv2022

Modelling the spatial dynamics of oncolytic virotherapy in the presence of virus-resistant tumor cells

Oncolytic virotherapy is a promising form of cancer treatment that uses native or genetically engineered viruses to target, infect and kill cancer cells. Unfortunately, this form of therapy is not effective in a substantial proportion of cancer patients, partly due to the occurrence of infection-resistant tumor cells. To shed new light on the mechanisms underlying therapeutic failure and to discover strategies that improve therapeutic efficacy we designed a cell-based model of viral infection. The model allows to investigate the dynamics of infection-sensitive and infection-resistant cells in tumor tissue in presence of the virus. To reflect the importance of the spatial configuration of the tumor on the efficacy of virotherapy, we compare three variants of the model: two 2D models of a monolayer of tumor cells and a 3D model. In all model variants, we systematically investigate how the therapeutic outcome is affected by properties of the virus (e.g. the rate of viral spread), the tumor (e.g. production rate of resistant cells, cost of resistance), the healthy stromal cells (e.g. degree of resistance to virus) and the timing of treatment. We find that various therapeutic outcomes are possible when resistant cancer cells arise at low frequency in the tumor. These outcomes depend in an intricate but predictable way on the death rate of infected cells, where faster death leads to rapid virus clearance and cancer persistence. Our simulations reveal three different causes of therapy failure: rapid clearance of the virus, rapid selection of resistant cancer cells, and a low rate of viral spread due to the presence of infection-resistant healthy cells. Our models suggest that improved therapeutic efficacy can be achieved by sensitizing healthy stromal cells to infection, although this remedy has to be weighed against the toxicity induced in the healthy tissue.

cancer biology↗

bioRxiv2021

DETECTING PHYLODIVERSITY-DEPENDENT DIVERSIFICATION WITH A GENERAL PHYLOGENETIC INFERENCE FRAMEWORK

AO_SCPLOWBSTRACTC_SCPLOWDiversity-dependent diversification models have been extensively used to study the effect of ecological limits and feedback of community structure on species diversification processes, such as speciation and extinction. Current diversity-dependent diversification models characterise ecological limits by carrying capacities for species richness. Such ecological limits have been justified by niche filling arguments: as species diversity increases, the number of available niches for diversification decreases. However, as species diversify they may diverge from one another phenotypically, which may open new niches for new species. Alternatively, this phenotypic divergence may not affect the species diversification process or even inhibit further diversification. Hence, it seems natural to explore the consequences of phylogenetic diversity-dependent (or phylodiversity-dependent) diversification. Current likelihood methods for estimating diversity-dependent diversification parameters cannot be used for this, as phylodiversity is continuously changing as time progresses and species form and become extinct. Here, we present a new method based on Monte Carlo Expectation-Maximization (MCEM), designed to perform statistical inference on a general class of species diversification models and implemented in the R package emphasis. We use the method to fit phylodiversity-dependent diversification models to 14 phylogenies, and compare the results to the fit of a richness-dependent diversification model. We find that in a number of phylogenies, phylogenetic divergence indeed spurs speciation even though species richness reduces it. Not only do we thus shine a new light on diversity-dependent diversification, we also argue that our inference framework can handle a large class of diversification models for which currently no inference method exists.

evolutionary biology↗

bioRxiv2020

Individual-based simulations of genome evolution with ancestry: the GENOMEADMIXR R package

O_LIHybridization between populations or species results in a mosaic of the two parental genomes. This and other types of genome admixture have received increasing attention for their implications in speciation, human evolution, Evolve and Resequence (E&R) and genetic mapping. However, a thorough understanding of how local ancestry changes after admixture, and how selection affects patterns of local ancestry remains elusive. The complexity of these questions limits analytical treatment, but these scenarios are specifically suitable for simulation. C_LIO_LIHere, we present the R package GO_SCPLOWENOMEC_SCPLOWAO_SCPLOWDMIXC_SCPLOWR, which uses an individual-based model to simulate genomic patterns following admixture forward in time. GO_SCPLOWENOMEC_SCPLOWAO_SCPLOWDMIXC_SCPLOWR provides user-friendly functions to set up and analyze simulations under evolutionary scenarios with selection, linkage and migration. C_LIO_LIWe show the flexible functionality of the GO_SCPLOWENOMEC_SCPLOWAO_SCPLOWDMIXC_SCPLOWR workflow by demonstrating 1) how to design an E&R simulation using GO_SCPLOWENOMEC_SCPLOWAO_SCPLOWDMIXC_SCPLOWR and 2) how to use GO_SCPLOWENOMEC_SCPLOWAO_SCPLOWDMIXC_SCPLOWR to verify analytical expectations following from the theory of junctions. C_LIO_LIGO_SCPLOWENOMEC_SCPLOWAO_SCPLOWDMIXC_SCPLOWR provides a mechanistic approach to explore expected genome responses to realistic admixture scenarios. With this package, we aim to aid researchers in testing specific hypotheses based on empirical findings involving admixing populations. C_LI

bioinformatics↗

bioRxiv2020

Estimating the time since admixture from phased and unphased molecular data

After admixture, recombination breaks down genomic blocks of contiguous ancestry. The breakdown of these blocks forms a new molecular clock, that ticks at a much faster rate than the mutation clock, enabling accurate dating of admixture events in the recent past. However, existing theory on the break down of these blocks, or the accumulation of delineations between blocks, so called junctions, has mostly been limited to using regularly spaced markers on phased data. Here, we present an extension to the theory of junctions using the Ancestral Recombination Graph that describes the expected number of junctions for any distribution of markers along the genome. Furthermore, we provide a new framework to infer the time since admixture using unphased data. We demonstrate both the phased and unphased methods on simulated data and show that our new extensions performs better than previous methods, especially for smaller population sizes and for more ancient admixture times. Lastly, we demonstrate the applicability of our method on an empirical dataset of labcrosses of yeast (Saccharomyces cerevisae) and on two case studies of hybridization in swordtail fish and Populus trees.

evolutionary biology↗

bioRxiv2020

Nucleotide substitutions during speciation may explain substitution rate variation

Although molecular mechanisms associated with the generation of mutations are highly conserved across taxa, there is widespread variation in mutation rates between evolutionary lineages. When phylogenies are reconstructed based on nucleotide sequences, such variation is typically accounted for by the assumption of a relaxed molecular clock, which is just a statistical distribution of mutation rates without much underlying biological mechanism. Here, we propose that variation in accumulated mutations may be partly explained by an elevated mutation rate during speciation. Using simulations, we show how shifting mutations from branches to speciation events impacts inference of branching times in phylogenetic reconstruction. Furthermore, the resulting nucleotide alignments are better described by a relaxed than by a strict molecular clock. Thus, elevated mutation rates during speciation potentially explain part of the variation in substitution rates that is observed across the tree of life.

evolutionary biology↗

bioRxiv2020

Alternative phage-host interaction in Lactococcus lactis: the carrier state drives rapid evolution of phages

Lactococcus lactis is a lactic acid bacterium widely used as starter culture for the manufacture of fermented milk products like quark, buttermilk and cheese. Bacteriophage infection of starter cultures is one of the biggest causes of fermentation failure and, therefore, lactococcal phages have received great attention from the scientific community in the past decades. In this work we present evidence for the establishment of a carrier state life cycle (CSLC) by a bacteriophage belonging to the c2 species, in the model laboratory strain L. lactis MG1363. Our results show that infection of L. lactis MG1363 with a second, dissimilar, c2 bacteriophage can induce the CSLC phage to enter an active lytic life cycle. The viral progeny obtained after this infection is a mixed population of phages with differences in their genome sequences and host ranges, indicative of an extremely rapid evolution process. We discuss the possible implications of this phage-host interaction, both with respect to bacteriophage evolution and phage adaptation to different hosts. IMPORTANCEOur results broaden the current know-how on the yet poorly investigated phage-host interaction mechanism of CSLC, propose a new bacteriophage evolution mechanism, and demonstrate that the outcome of phage infections is possibly more intricate than presently acknowledged.

evolutionary biology↗

bioRxiv2019

Recombining your way out of trouble: The genetic architecture of hybrid fitness under environmental stress

Hybridization between species is a fundamental evolutionary force that can both promote and delay adaptation. There is a deficit in our understanding of the genetic basis of hybrid fitness, especially in non-domesticated organisms. We also know little about how hybrid fitness changes as a function of environmental stress. Here, we made genetically variable F2 hybrid populations from two divergent Saccharomyces yeast species, exposed populations to ten toxins, and sequenced the most resilient hybrids on low coverage using ddRADseq. We expected to find strong negative epistasis and heterozygote advantage in the hybrid genomes. We investigated three aspects of hybridness: 1) hybridity, 2) interspecific heterozygosity, and 3) epistasis (positive or negative associations between non-homologous chromosomes). Linear mixed effect models revealed strong genotype-by-environment interactions with many chromosomes and chromosomal interactions showing species-biased content depending on the environment. Against our predictions, we found extensive selection against heterozygosity such that homozygous allelic combinations from the same species were strongly overrepresented in an otherwise hybrid genomic background. We also observed multiple cases of positive epistasis between chromosomes from opposite species, confirmed by epistasis- and selection-free simulations, which is surprising given the large divergence of the parental species (~15% genome-wide). Together, these results suggest that stress-resilient hybrid genomes can be assembled from the best features of both parents, without paying high costs of negative epistasis across large evolutionary distances. Our findings illustrate the importance of measuring genetic trait architecture in an environmental context when determining the evolutionary potential of hybrid populations.

evolutionary biology↗

bioRxiv2017

A simple spatially explicit neutral model explains range size distribution of reef fishes

AimThe great variation in range sizes among species has fascinated ecologists for decades. In reef-associated fish species, which live in fragmented habitats and adopt a wide range of dispersal strategies, we may expect species with greater dispersal ability to spread over larger ranges. However, empirical evidence for such a positive relationship between dispersal and range size in reef fishes remains scarce. Here, we unveil the more nuanced role of dispersal on the range size distribution of reef associated fishes using empirical data and a novel spatially explicit model.\n\nLocationTropical Eastern Pacific\n\nMajor taxa studiedReef-associated fishes\n\nMethodsWe estimated range size distributions for six different guilds of all reef-associated fishes with different dispersal abilities. We used a one-dimensional spatially explicit neutral model, which simulates the distribution of species along a linear coastline to explored the effect of dispersal, speciation and sampling on the distribution of range sizes. Our model adopts a more realistic gradual speciation process (protracted speciation) and incorporates important long distance dispersal events with a fat-tail dispersal kernel. We simulated our model using a highly efficient coalescence approach, which guarantees the metacommunity, is sampled at dynamic equilibrium. We fitted the model to the empirical data using an approximate Bayesian computation approach, with a sequential Monte Carlo algorithm.\n\nResultsStochastic birth, death, speciation and dispersal events alone can accurately explain empirical range size distributions for six different guilds of tropical, reef-associated fishes. Variation in range size distributions among guilds are explained purely by differences in dispersal ability with the best dispersers covering larger ranges.\n\nMain conclusionsA simple combination of neutral processes with guild-specific dispersal ability provides a general explanation for both within- and across-guild range size variation. Our results support the theoretically expected, but empirically much debated, hypothesis that dispersal promotes range size.

ecology↗

bioRxiv2016

Inferring the role of habitat dynamics in driving diversification: evidence for a species pump in Lake Tanganyika cichlids

Geographic isolation that drives speciation is often assumed to slowly increase over time, for instance through the formation of rivers, the formation of mountains or the movement of tectonic plates. Cyclic changes in connectivity between areas may occur with the advancement and retraction of glaciers, with water level fluctuations in seas between islands or in lakes that have an uneven bathymetry. These habitat dynamics may act as a driver of allopatric speciation and propel local diversity. Here we present a parsimonious model of the interaction between cyclical (but not necessarily periodic) changes in the environment and speciation, and provide an ABC-SMC method to infer the rates of allopatric and sympatric speciation from a phylogenetic tree. We apply our approach to the posterior sample of an updated phylogeny of the Lamprologini, a tribe of cichlid fish from Lake Tanganyika where such cyclic changes in water level have occurred. We find that water level changes play a crucial role in driving diversity in Lake Tanganyika. We note that if we apply our analysis to the Most Credible Consensus (MCC) tree, we do not find evidence for water level changes influencing diversity in the Lamprologini, suggesting that the MCC tree is a misleading representation of the true species tree. Furthermore, we note that the signature of habitat dynamics is found in the posterior sample despite the fact that this sample was constructed using a species tree prior that ignores habitat dynamics. However, in other cases this species tree prior might erase this signature. Hence we argue that in order to improve inference of the effect of habitat dynamics on biodiversity, phylogenetic reconstruction methods should include tree priors that explicitly take into account such dynamics.

evolutionary biology↗