Biology subjects

Babayan, S. A.

Publications and source records attributed to Babayan, S. A..

12 recordsLinked to original sources

bioRxiv2026

Helminth coinfection facilitates gammaherpesvirus infection in the wood mouse Apodemus sylvaticus

Helminths are widespread parasites that can modulate host immunity, potentially increasing susceptibility to viral infections. However, evidence for these effects varies across systems and environments, and links between laboratory and wild populations remain unclear. We developed a tractable system using wood mice, Heligmosomoides spp. nematodes, and wood mouse herpes virus (WMHV) to bridge this gap. Combining laboratory and field experiments with population modelling, we examined how helminth infection, anthelmintic treatment and diet affect viral dynamics. Across lab and field data, helminth infection consistently increased WMHV risk, with stronger effects at higher worm burdens. Field results showed that anthelmintic treatment reduced viral infection, and laboratory experiments showed that improved nutrition mitigates helminth-induced increases in viral susceptibility. Our population-level modelling suggested that helminth burden-dependent facilitation can generate nonlinear effects on viral spread, dependent on helminth virulence. Our findings highlight the potential importance of helminths as facilitators of viral infections, and suggest that anthelmintic treatment may provide indirect benefits for viral control. We also show the value of integrating lab and field approaches on the same (or closely related) species, in particular the potential offered by the wood mouse - Heligmosomoides - WMHV system, to understand the drivers and consequences of host-helminth-viral interactions.

ecology↗

bioRxiv2026

TAUS: Target-Age Unified Survival. Survival analysis without assuming proportional hazards or parameterising the survival function.

O_LIStandard survival analysis methods often rely on the assumption of proportional hazards (PH) or parameterisations of the survival function that might not be appropriate for wild populations. C_LIO_LITo enable survival analysis without these modelling constraints, we developed an approach that combines the Kaplan-Meier estimator with conditional probability theory to compute age-specific probabilities of survival up to some target age of choice{tau} . Marginalising this probability over the age distribution of the population yields O{tau}, the probability that a randomly sampled individual of unknown age will outlive the target age{tau} . Notably, the value for{tau} is set by the analyst for each group independently, which allows accounting for differences in pace of life across populations. C_LIO_LIWe tested its application using a simulation study and two real-world datasets, and compared its performance against that of Cox PH and parametric survival models. The PH assumption was violated in the three examples, rendering the Cox PH models inappropriate. Parametric models offered a better alternative, but the best parametric fit missed at least some key survival patterns in all examples. The TAUS model provided a valid description of survival patterns in all cases. Its richer output also allowed finer analysis of survival differences between populations. C_LIO_LIThe TAUS model is also available as an R package (https://github.com/casasgomezuribarri/TAUS). This new approach to survival analysis without PH or parametric assumptions allows the comparison of survival probabilities across populations with different age structures and rates of pace of life. This makes it suitable for a wide range of ecological applications, including in population viability analysis, epidemiology, or life-history theory C_LI

ecology↗

bioRxiv2025

Resource supplementation alters host exposure, susceptibility, and infection dynamics across a diverse parasite community

Resource availability is crucial in shaping exposure and resistance to parasites. Although effects are expected to vary across parasite species, most of our knowledge comes from single-host, single-parasite studies. In a wild wood mouse population (Apodemus sylvaticus), we supplemented dietary resources over 3 years and quantified effects on a diverse parasite community alongside host behaviour and physiology. Resource supplementation had diverse impacts on 12 parasite taxa including positive (3/12), negative (6/12), and null (3/12) results. Supplementation also influenced host biology, with supplemented mice moving less, experiencing higher conspecific densities, improved conditions, and increased reproduction. These findings experimentally demonstrate that resource availability can multifacetedly affect disease dynamics. The complexity likely arises due to combined effects on exposure and susceptibility processes. Our study advances understanding of disease drivers at the human-wild interface and underscores the importance of assessing whole parasite communities to predict responses to changing resource landscapes in the wild.

ecology↗

bioRxiv2025

Environmental drivers of low vaccine responsiveness in a lab-to-wild rodent model

Vaccination is the most effective way to prevent infectious diseases and safeguard public health. Yet, most new vaccines fail in late clinical trials, and even estab-lished ones often underperform in populations apart from those in which they were initially tested. This can lead to reduced vaccine responsiveness, breakthrough infections, and prevent or delay herd immunity. While the causes of vaccine hypore-sponsiveness remain difficult to identify, quantify, and therefore address, numerous reports indicate a predominant role of environmental factors. This has notably been demonstrated by a reduction in the immunogenicity and efficacy of various vaccines when transitioning from urban to rural human populations. Here, we tested whether and, if so, how the environment can cause vaccine hyporesponsive-ness. We hypothesised that if the leading causes of vaccine hyporesponsiveness were environmental, then the reduced efficacy would be exacerbated when indi-viduals are under nutritional stress; specifically predicting that high quality diet supplementation would increase vaccine responsiveness. Finally, we predicted that parasitic helminth infection, which are more common in rural populations, would degrade vaccine responsiveness, e.g. due to their ability to suppress host immunity, and that anthelmintic treatment could rescue vaccine responsiveness in infected individuals. To test these hypotheses, we coupled lab and field experiments with structural causal modelling, and measured antibody responses of paired conspecific cohorts of laboratory-reared and wild wood mice (Apodemus sylvaticus) to a single or two doses of diphtheria toxoid vaccine formulated with alum; with and without diet supplementation. We found that vaccine-specific IgG1 antibodies were [~]47% lower in the wild wood mice compared to the laboratory reared population. We also demonstrate that, across both habitats (wild and lab), substantial variation in vaccine responsiveness was caused by diet. However, contrary to our predictions, this high quality dietary supplementation resulted in lower vaccine responsiveness. Further, once the effects of habitat, diet, and sex were adjusted for, increasing hel-minth infection burdens negatively affected vaccine-specific antibody production. Using counterfactual modelling, we show that targeting anthelmintic treatment at heavily infected individuals would have improved their vaccine responsiveness by 2 to 4-fold. Our results indicate that the wild environment and access to a high-quality diet play a dramatic role in shaping the immune systems response to immunisation. Further, we show that laboratory settings, even when using a genetic diverse, non-traditional model, may systematically overestimate vaccine performance by failing to capture natural environmental variability. Our study provides a robust, causally explicit modelling approach to disentangle and quantify the complex factors that drive vaccine responsiveness in focal populations. This framework offers a path-way for predicting vaccine performance across diverse populations and identifying targeted interventions to enhance immunisation outcomes in real-world settings.

systems biology↗

bioRxiv2025

Reducing food stress and parasitism may have unexpected consequences on faecal corticosterone in a wild rodent

In wild animals, glucocorticoid hormones play a key role in responses to environmental stressors and the maintenance of homeostasis, allocating energy between energy-demanding processes. Although acute rises in glucocorticoids are beneficial for short-term survival, prolonged exposure can be detrimental to reproduction and survival. Thus, understanding the factors driving glucocorticoid concentrations is crucial for understanding key processes in ecology and evolution. Here, we examined how manipulation of two environmental stressors - food availability and parasite burden, influence levels of faecal corticosterone in a wild population of wood mice (Apodemus sylvaticus). To do so, we experimentally altered nutrition via food supplementation and reduced gastrointestinal nematode infection by anthelmintic treatment, using Heligmosomoides polygyrus as an indicator of treatment efficacy. Faecal corticosterone was not found to be impacted by food supplementation or anthelminthic treatment. However, our results may be mediated by variation in resource availability or masked by other factors that affect corticosterone. For example, corticosterone declined seasonally and was higher in adult, female mice. While we expected higher food availability and lower worm burden to decrease stress, putatively higher rates of reproduction in food supplemented areas could neutralise any decreases in corticosterone associated with alleviation of food and parasite stress. Thus, alleviating stress in the wild may have unintended consequences on fitness.

evolutionary biology↗

bioRxiv2025

A DNA methylation-based clock for age estimates in the wood mouse (Apodemus sylvaticus)

Environmental stressors are expected to accelerate senescence but demonstrating this requires both a measure of senescence and knowledge of chronological age - data rarely available for most wild animals. Here, we constructed a DNA methylation-based epigenetic clock for the wood mouse (Apodemus sylvaticus) using known-aged laboratory individuals and applied it to a wild population of unknown ages. This represents one of the first demonstrations that a laboratory-trained epigenetic clock can be used to infer age structure in free-living animals. Multiple lines of evidence validated use of the clock in wild individuals: age estimates fell within expected ranges, recapitulated population demographic structure, and recovered predicted signatures of senescence, including an increase in infection probability with age. Moreover, wild mice given experimental food supplementation and parasite-removal drugs exhibited slower epigenetic ageing rates. Together, our findings demonstrate that epigenetic clocks can infer both chronological age and ageing rates in the wild, providing a powerful framework to identify the ecological and individual determinants of ageing.

genomics↗

bioRxiv2024

Density-dependent network structuring within and across wild animal systems

High population density should drive individuals to more frequently share space and interact, producing better-connected spatial and social networks [1-4]. Although this theory is fundamental to our understanding of disease dynamics [2,5-8], it remains unconfirmed how local density generally drives individuals positions within their networks, which reduces our ability to understand and predict density-dependent processes [4,9,10]. Here we provide the first general evidence that density drives greater network connectedness at fine spatiotemporal scales, at the scale of individuals within wild animal populations. We analysed 36 datasets of simultaneous spatial and social behaviour in >58,000 individual animals, spanning 30 species of fish, reptiles, birds, mammals, and insects. 80% of systems exhibited strong positive relationships between local density and network centrality. However, >80% of relationships were nonlinear and 75% became shallower at higher values, signifying that demographic and behavioural processes counteract densitys effects, thereby producing saturating trends [11-15]. Densitys effect was much stronger and less saturating for spatial than social networks, such that individuals become disproportionately spatially connected rather than socially at higher densities. Consequently, ecological processes that depend on spatial connections (e.g. indirect pathogen transmission, resource competition, and territory formation) are likely more density-dependent than those involving social interactions (e.g. direct pathogen transmission, aggression, and social learning). These findings reveal fundamental ecological rules governing societal structuring, with widespread implications. Identifying scaling rules based on processes that generalise across systems, such as these patterns of density dependence, might provide the ability to predict network structures in novel systems.

ecology↗

bioRxiv2024

Advancing age grading techniques for Glossina morsitans morsitans, vectors of African trypanosomiasis, through mid-infrared spectroscopy and machine learning

Tsetse are the insects responsible for transmitting African trypanosomes, which cause sleeping sickness in humans and animal trypanosomiasis in wildlife and livestock. Knowing the age of these flies is important when assessing the effectiveness of vector control programs and modelling disease risk. However, current methods to assess fly age are labour-intensive, slow, and often inaccurate as skilled personnel are in short supply. Mid-infrared spectroscopy (MIRS), a fast and cost-effective tool to accurately estimate several biological traits of insects, offers a promising alternative. This is achieved by characterising the biochemical composition of the insect cuticle using infrared light coupled with machine learning algorithms to estimate the traits of interest. We tested the performance of MIRS in estimating tsetse sex and age for the first time using spectra obtained from their cuticle. We used 541 insectary-reared Glossina m. morsitans of two different age groups for males (5 and 7 weeks) and three age groups for females (3 days, 5 weeks, and 7 weeks). Spectra were collected from the head, thorax, and abdomen of each sample. Machine learning models differentiated between male and female flies with a 96% accuracy and predicted the age group with 94% and 87% accuracy for males and females, respectively. The key infrared regions important for discriminating sex and age classification were characteristic of lipid and protein content. Our results support the use of MIRS as a fast and accurate way to identify tsetse sex and age with minimal pre-processing. Further validation using wild-caught tsetse can pave the way for this technique to be implemented as a routine surveillance tool in vector control programmes. Author summaryMale and female tsetse transmit the parasites that cause sleeping sickness in humans and nagana in livestock. To control these diseases, knowing the age of these flies is important, as it helps evaluate the efficacy of control measures and assess disease risk. However, current age-grading methods are laborious, often unreliable, and in the case of male tsetse, highly inaccurate. This study explores a novel approach that uses mid-infrared spectroscopy (MIRS) to estimate the age of individual tsetse. Machine learning can detect signatures in MIRS that help identify the composition of a flys cuticle, which differs between sexes and changes as they age. We trained machine learning models that distinguished male from female flies with 96% accuracy and predicted the correct age group with 94% accuracy for males and 87% accuracy for females. MIRS offers a fast and reliable way to identify tsetse sex and age with minimal preparation. If this method is successfully validated with wild flies, it holds the potential to vastly increase the accuracy of the way we monitor and combat these disease-carrying insects, thus offering significant advantages in our efforts to control them.

biochemistry↗

bioRxiv2022

Using transfer learning and dimensionality reduction techniques to improve generalisability of machine-learning predictions of mosquito ages from mid-infrared spectra

Accurate prediction of mosquito population age structures can improve the evaluation of mosquito-targeted interventions since old mosquitoes are more likely to transmit malaria than young ones. Mid-infrared spectroscopy (MIRS) reveals age-associated variation in the biochemical composition of the mosquito cuticle, which can then be used to train machine learning (ML) models to predict mosquito ages. However, these MIRS-ML models are not always generalisable across different mosquito populations. Here, we investigated whether dimensionality reduction applied to the MIRS input data and transfer learning could improve the generalisability of MIRS-ML predictions for mosquito ages. We reared adults of the malaria vector, Anopheles arabiensis, in two insectaries (Ifakara, Tanzania and Glasgow, UK). The heads and thoraces of female mosquitoes of two age classes (1-9 day-olds and 10-17 day-olds) were scanned using an attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectrometer (4000 cm-1 to 400 cm-1). The dimensionality of the spectra data was reduced using unsupervised principal component analysis (PCA) or t-distributed stochastic neighbour embedding (t-SNE), and then the spectra were used to train deep learning (DL) and standard machine learning (ML) classifiers. Transfer learning was also evaluated for improving the computational cost of the models when predicting mosquito age classes from new populations. Model accuracies for predicting the age of test mosquitoes from the same insectary as the training samples reached 99% for DL and 92% for ML, but did not generalise to a different insectary, achieving only 46% and 48% for ML for DL, respectively. Dimensionality reduction did not improve the model generalisability between locations but reduced computational time up to 5-fold. However, transfer learning by updating pre-trained models with 2% of mosquitoes from the alternate location brought both DL and standard ML model performance to ~98% accuracy for predicting mosquito age classes in the alternative insectary. Combining dimensionality reduction and transfer learning can reduce computational costs and improve the transferability of both deep learning and standard machine learning models for predicting the age of mosquitoes. Future studies could investigate the optimal quantities and diversity of training data necessary for transfer learning, and implications for broader generalisability to unseen datasets.

bioinformatics↗

bioRxiv2021

The right time and place: time- and age-dependent vaccine-enhanced mucosal immunity to parasite infection

Individuals vary broadly in their response to vaccination and subsequent exposure to infection, causing persistence of both infection and transmission. The prevalence of poor vaccine responders hampers the development of vaccines, especially against parasitic helminths. Yet despite having substantial economic and societal impact, the immune mechanisms that underlie such variability, especially at the site of parasite infection, remain poorly understood. Previous trials using a prototype vaccine for the control of the gastric parasitic Teladorsagia circumcincta, one of the highest impact parasites affecting sheep, revealed substantial variation in protection between individuals, which we hypothesised may in part be driven by age at vaccination. Here, to characterise how immunity at the mucosal site of infection developed in vaccinated lambs, we inserted gastric cannulae into the abomasa (true stomachs) of three-month- and six-month-old lambs before vaccination, and performed a longitudinal analysis of their local immune response during subsequent challenge infection. We found that the vaccine caused systemic changes in the baseline immune profile within the abomasum before any parasite exposure had occurred and reduced parasite burden and egg output once lambs were infected, regardless of age. However, age affected how vaccinated lambs responded to subsequent infection across multiple immune pathways, with only a minority of protective immune pathways being independent of age. This resulted in younger lambs being more susceptible to infection regardless of vaccine status. The identification of age-dependent (mostly adaptive) and age-independent (mostly innate) protective immune pathways should help refine the formulation of vaccines against these and potentially other helminth parasites of ruminants, and could indicate specificities of anti-helminth immunity more generally.

immunology↗

bioRxiv2019

Supplemented nutrition increases immunity and drug efficacy in a natural host-helminth system

Gastrointestinal helminths are common parasites of humans, wildlife, and livestock, leading to chronic infections in large parts of the world. In humans, there is also an overlap in the incidence of malnutrition and helminth infections which can predispose individuals to higher infection burdens and reduced anthelmintic efficacy due to compromised immunity. This relationship has been well-studied in laboratory models by testing for the impact of dramatic reductions of specific nutrients on infection outcomes. However, much less is known about the benefits of whole-diet supplementation in natural host-helminth systems. We experimentally supplemented the diet of wood mice (Apodemus sylvaticus) and measured resistance to the gastrointestinal nematode Heligmosomoides polygyrus and anthelmintic treatment efficacy in both natural and captive populations. Supplemented wood mice were more resistant to H. polygyrus infection, cleared worms more efficiently after treatment, produced stronger general and parasite-specific antibody responses, and maintained better body condition. In addition, supplemented nutrition in conjunction with anthelminthic treatment significantly reduced H. polygyrus transmission potential. These large-scale improvements in condition and immunity of supplemented nutrition found in controlled and wild environments show the rapid and extensive benefits of a well-balanced diet and have important implications for using diet interventions to improve disease control programmes. Author SummaryGastrointestinal helminths are ubiquitous parasites which cause chronic infections and debilitating symptoms worldwide for human and animal populations alike. Efforts to control helminth infections rely primarily on deworming drugs. However, despite high availability and low cost of these drugs, reinfection is common and helminths remain a substantial problem in many areas of the world. One factor which contributes to the persistence of helminth infections is co-occurrence of malnutrition. Extensive work in model laboratory systems has shown that deficiencies in both macro- and micronutrients can impair host immune responses to helminth infections, but how this relationship translates to natural host-helminth systems and drug efficacy is still poorly understood. Here, we used a combination of experimental nutrition supplementation and deworming treatment in paired wood mouse populations in both wild and captive environments to determine the role of a well-balanced diet for infection control in a natural host-helminth system. We found that mice on a supplemented diet had lower burden of infection and increased drug efficacy, body condition, and immune responses. We also found that supplementation lowered transmission potential of hosts. These broad and rapid effects of increased nutrition quality have important implications for the benefits of diet interventions alongside deworming drugs.

ecology↗

bioRxiv2018

Prediction of malaria mosquito species and population age structure using mid-infrared spectroscopy and supervised machine learning

Despite the global efforts made in the fight against malaria, the disease is resurging. One of the main causes is the resistance that Anopheles mosquitoes, vectors of the disease, have developed to insecticides. Anopheles must survive for at least 12 days to possibly transmit malaria. Therefore, to evaluate and improve malaria vector control interventions, it is imperative to monitor and accurately estimate the age distribution of mosquito populations as well as total population sizes. However, estimating mosquito age is currently a slow, imprecise, and labour-intensive process that can only distinguish under-from over-four-day-old female mosquitoes. Here, we demonstrate a machine-learning based approach that utilizes mid-infrared spectra of mosquitoes to characterize simultaneously, and with unprecedented accuracy, both age and species identity of females of the malaria vectors Anopheles gambiae and An. arabiensis mosquitoes within their respective populations. The prediction of the age structures was statistically indistinguishable from true modelled distributions. The method has a negligible cost per mosquito, does not require highly trained personnel, is substantially faster than current techniques, and so can be easily applied in both laboratory and field settings. Our results show that, with larger mid-infrared spectroscopy data sets, this technique can be further improved and expanded to vectors of other diseases such as Zika and Dengue.

bioinformatics↗