Biology subjects

Cruz-Loya, M.

Publications and source records attributed to Cruz-Loya, M..

7 recordsLinked to original sources

bioRxiv2026

Mosquito infection-mediated trait variation alters temperature-dependent transmission of West Nile virus

Rising global temperatures are reshaping species interactions and the ecological conditions governing vector-borne disease transmission. Although previous studies show that West Nile virus (WNV) infection alters mosquito longevity, fecundity, blood-feeding behavior, and the thermal performance of these traits, trait-based R models largely rely on data from uninfected mosquitoes, implicitly assuming homogeneous vector populations. This overlooks infection-induced trait variation that may influence transmission dynamics. Here, we examined how temperature, infection status, and viral strain interact to shape transmission potential for WNV in Culex pipiens. Life-history traits of WNV-exposed and unexposed mosquitoes were measured across constant temperatures ranging from 10{degrees}C to 33{degrees}C, as well as under a fluctuating temperature regime of 25{degrees}C {+/-} 5{degrees}C. These data were used to generate thermal performance curves and estimate temperature-dependent relative R across treatments. Infection altered the thermal performance of mosquito life-history traits, vector competence, and overall transmission potential. We also found evidence for a bimodal effect of temperature on vector competence, potentially driven by tradeoffs between viral replication and mosquito immune responses. Incorporating infection-sensitive traits into relative R calculations reduced estimated transmission intensity across much of the thermal range without shifting thermal optima or limits, suggesting that current models may overestimate transmission.

microbiology↗

bioRxiv2025

Temperature influences West Nile virus evolution and adaptation

Abstract bodyWest Nile virus (WNV), the most common mosquito-borne disease in the continental U.S., is vectored by Culex spp. mosquitoes. Since its introduction to New York State (NYS) in 1999, WNV has become endemic. NYS temperatures have risen by 0.14{degrees}C per decade since 1900, with larger increases linked to higher WNV transmission. Using surveillance and sequencing data, we find a significant correlation between rising temperatures, increased WNV genetic diversity, and higher prevalence. Given the experimentally demonstrated role of temperature influencing WNV fitness, we hypothesized that contemporary strains should exhibit greater fitness in mosquitoes at higher temperatures compared to historic strains. To test this, we analyzed genetically distinct WNV strains from mosquitoes collected during recent warm summers (2017 and 2018) and cooler historic summers (2003 and 2004). Assessing Culex pipiens vector competence and calculating the relative R at 20{degrees}C, 24{degrees}C, and 28{degrees}C, we found that contemporary strains exhibit higher transmission potential at increased temperatures. Our results show that contemporary WNV strains possess greater phenotypic and genotypic diversity, facilitating the emergence of strains with enhanced transmission potential in a warming climate.

molecular biology↗

bioRxiv2025

Nonlinear effects of temperature on mosquito parasite infection across a large geographic climate gradient

Temperature drives ectothermic host - parasite interactions, making them particularly sensitive to climatic variation and change. To isolate the role of temperature, lab-based studies are increasingly used to assess and forecast disease risk under current and future climate conditions. However, in the field, the effects of temperature on parasitism may be mediated by other sources of variation, including local adaptation of hosts and parasites to one another and to the environment. To address the key knowledge gaps of how temperature influences host - parasite interactions and whether thermal responses measured in controlled experiments capture infection across temperature gradients in nature, we paired an extensive field survey of parasitism--by the ciliate Lambornella clarki on its tree hole mosquito host, Aedes sierrensis--with laboratory experiments describing parasitism thermal performance curves (TPCs) for six host populations from varying climates. We also investigated the mechanisms underlying the thermal biology of the host - parasite interaction by separately measuring TPCs for infection, host immunity, and parasite growth rates. Along the west coast of North America, across an 1100 km climate gradient spanning 12{degrees}C mean rainy season temperature variation, we found that parasitism peaked at intermediately cold temperatures of 9.2 - 10{degrees}C, and was consistent both between field seasons and with the lab experiment results. In the laboratory experiments, infection thermal responses were consistently nonlinear and peaked at 8.4 - 10{degrees}C, showing no evidence of host intraspecific variation in temperature sensitivity to parasitism. Importantly, parasitism peaked at temperatures below the thermal optimum for free-living L. clarki due to the balance of temperature effects on parasite growth and reproduction against the strength of the host melanization immune response. The results suggest that nonlinear responses to temperature drive parasitism in nature, and that simple lab and field studies can accurately capture the thermal biology of multilayered host - parasite interactions.

ecology↗

bioRxiv2024

A flexible model for thermal performance curves

Temperature responses of many biological traits--including population growth, survival, and development--are described by thermal performance curves (TPCs) with phenomenological models like the Briere function or mechanistic models related to chemical kinetics. Existing TPC models are either simple but inflexible in shape, or flexible yet difficult to interpret in biological terms. Here we present flexTPC: a model that is parameterized exclusively in terms of biologically interpretable quantities, including the thermal minimum, optimum, and maximum, and the maximum trait value. FlexTPC can describe unimodal temperature responses of any skewness and thermal breadth, enabling direct comparisons across populations, traits, or taxa with a single model. We apply flexTPC to various microbial and entomological datasets, compare results with the Briere model, and find that flexTPC often has better predictive performance. The interpretability of flexTPC makes it ideal for modeling how thermal responses change with ecological stressors or evolve over time.

ecology↗

bioRxiv2020

Antibiotics shift the temperature response curve of Escherichia coli growth

Temperature variation--through time and across climatic gradients--affects individuals, populations, and communities. Yet how the thermal response of biological systems is altered by environmental stressors is poorly understood. Here we quantify two key features--optimal temperature and temperature breadth--to investigate how temperature responses vary in the presence of antibiotics. We use high-throughput screening to measure growth of Escherichia coli under single and pairwise combinations of 12 antibiotics across seven temperatures that range from 22{degrees}C to 46{degrees}C. We find that antibiotic stress often results in considerable changes in the optimal temperature for growth and a narrower temperature breadth. The direction of the optimal temperature shifts can be explained by the similarities between antibiotic-induced and temperature-induced damage to the physiology of the bacterium. We also find that the effects of pairs of stressors in the temperature response can often be explained by just one antibiotic out of the pair. Our study has implications for a general understanding of how ecological systems adapt and evolve to environmental changes.

ecology↗

bioRxiv2018

Transitions in interaction landscapes of multidrug combinations

Drug combinations are a promising strategy to increase killing efficiency and to decrease the likelihood of evolving resistance. A major challenge is to gain a detailed understanding of how drugs interact in a dose-specific manner, especially for interactions involving more than two drugs. Here we introduce a direct and intuitive visual representation that we term \"interaction landscapes\". We use these landscapes to clearly show that the interaction type of two drugs typically transitions smoothly from antagonism to no interaction to synergy as drug doses increase. This finding contradicts prevailing assumptions that interaction type is always the same. Our results, from 56 interaction landscapes, are derived from all possible three-drug combinations among 8 antibiotics, each varied across a range of 7 concentrations and applied to a pathogenic Escherichia coli strain. Such comprehensive data and analysis are only recently possible through implementation of an automated high-throughput drug-delivery system and an explicit mathematical framework that disentangles pairwise versus three-way as well as net (any effect) versus emergent (requiring all three drugs) interactions. Altogether, these landscapes partly capture and encapsulate selective pressures that correspond to different dose regions and could help optimize treatment strategies. Consequently, interaction landscapes have profound consequences for choosing effective drug-dose combinations because there are regions where small changes in dose can cause large changes in pathogen killing efficiency and selective pressure.

evolutionary biology↗

bioRxiv2017

Prevalence and patterns of higher-order interactions

Interactions and emergent processes are essential for research on complex systems involving many components. Most studies focus solely on pairwise interactions and ignore higher-order interactions among three or more components. To gain deeper insights into higher-order interactions and complex environments, we study antibiotic combinations applied to pathogenic Escherichia coli and obtain unprecedented amounts of detailed data (251 two-drug combinations, 1512 three-drug combinations, 5670 four-drug combinations, and 13608 five-drug combinations). Directly opposite to previous assumptions and reports, we find higher-order interactions increase in frequency with the number of drugs in the bacterias environment. Furthermore, we observe a shift towards net synergy (effect greater than expected based on independent individual effects) and towards emergent antagonism (effect less than expected based on lower-order interaction effects). These findings have implications for the potential efficacy of drug combinations and are crucial for better navigating problems associated with the combinatorial complexity of multi-component systems.

systems biology↗