Biology subjects

Savage, V. M.

Publications and source records attributed to Savage, V. M..

9 recordsLinked to original sources

bioRxiv2024

Mean daily temperatures can predict the thermal limits of malaria transmission better than rate summation

Temperature shapes the distribution, seasonality, and magnitude of mosquito-borne disease outbreaks. Mechanistic models predicting transmission often use mosquito and pathogen thermal responses from constant temperature experiments. However, mosquitoes live in fluctuating environments. Rate summation (nonlinear averaging) is a common approach to infer performance in fluctuating environments, but its accuracy is rarely validated. We measured three mosquito traits that impact transmission (bite rate, survival, fecundity) in a malaria mosquito (Anopheles stephensi) across temperature gradients with three diurnal temperature ranges (0, 9 and 12{degrees}C). We compared thermal suitability models with temperature-trait relationships observed under constant temperatures, fluctuating temperatures, and those predicted by rate summation. We mapped results across An. stephenesis native Asian and invasive African ranges. We found: 1) daily temperature fluctuation significantly altered trait thermal responses; 2) rate summation partially captured decreases in performance near thermal optima, but also incorrectly predicted increases near thermal limits; and 3) while thermal suitability characterized across constant temperatures did not perfectly capture suitability in fluctuating environments, it was more accurate for estimating and mapping thermal limits than predictions from rate summation. Our study provides insight into methods for predicting mosquito-borne disease risk and emphasizes the need to improve understanding of organismal performance under fluctuating conditions.

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↗

bioRxiv2024

Evolution Under Thermal Stress Affects Escherichia colis Resistance to Antibiotics

Exposure to both antibiotics and temperature changes can induce similar physiological responses in bacteria. Thus, changes in growth temperature may affect antibiotic resistance. Previous studies have found that evolution under antibiotic stress causes shifts in the optimal growth temperature of bacteria. However, little is known about how evolution under thermal stress affects antibiotic resistance. We examined 100+ heat-evolved strains of Escherichia coli that evolved under thermal stress. We asked whether evolution under thermal stress affects optimal growth temperature, if there are any correlations between evolving in high temperatures and antibiotic resistance, and if these strains antibiotic efficacy changes depending on the local environments temperature. We found that: (1) surprisingly, most of the heat-evolved strains displayed a decrease in optimal growth temperature and overall growth relative to the ancestor strain, (2) there were complex patterns of changes in antibiotic resistance when comparing the heat-evolved strains to the ancestor strain, and (3) there were few significant correlations among changes in antibiotic resistance, optimal growth temperature, and overall growth. ImportanceEscherichia coli, a bacteria species often found within the intestinal tract of warm-blooded organisms, can be harmful to humans. Like all species of bacteria, E. coli can evolve, particularly in the presence of stressful conditions such as extreme temperatures or antibiotic treatments. Recent evidence suggests that when encountering one source of stress, an organisms ability to deal with a different source of stress is also affected. With global climate change and the continued evolution of antibiotic-resistant bacteria, the need to further investigate how temperature and antibiotics interact is clear. The significance of our research is in identifying possible correlations between temperature and antibiotic stress, broadening our understanding of how stressors affect organisms, and allowing for insights into possible future evolutionary pathways.

evolutionary biology↗

bioRxiv2023

Neuronal Branching is Increasingly Asymmetric Near Synapses, Potentially Enabling Plasticity While Minimizing Energy Dissipation and Conduction Time

Neurons primary function is to encode and transmit information in the brain and body. The branching architecture of axons and dendrites must compute, respond, and make decisions while obeying the rules of the substrate in which they are enmeshed. Thus, it is important to delineate and understand the principles that govern these branching patterns. Here, we present evidence that asymmetric branching is a key factor in understanding the functional properties of neurons. First, we derive novel predictions for asymmetric scaling exponents that encapsulate branching architecture associated with crucial principles such as conduction time, power minimization, and material costs. We compare our predictions with extensive data extracted from images to associate specific principles with specific biophysical functions and cell types. Notably, we find that asymmetric branching models lead to predictions and empirical findings that correspond to different weightings of the importance of maximum, minimum, or total path lengths from the soma to the synapses. These different path lengths quantitatively and qualitatively affect energy, time, and materials. Moreover, we generally observe that higher degrees of asymmetric branching-- potentially arising from extrinsic environmental cues and synaptic plasticity in response to activity-- occur closer to the tips than the soma (cell body).

neuroscience↗

bioRxiv2022

Meta-analysis using new methods for three-stressor combinations reveal substantial higher-order interactions and emergent properties

Although natural populations are typically subjected to multiple stressors, most past research has focused on single stressors and two-stressor interactions, with little attention paid to higher-order interactions among three or more stressors. However, higher-order interactions increasingly appear to be widespread. Consequently, we used a recently introduced and improved framework to re-analyze higher-order ecological interactions. We conducted a literature review of the last 100 years (1920-2020) and reanalyzed 151 ecological three-stressor interactions from 45 published papers. We found that 89% (n=134) of the three-stressor combinations resulted in new or different interactions than previously reported. We also found substantial levels of emergent properties-- interactions that are only revealed when all three stressors are present. Antagonism was the most prevalent net interaction whereas synergy was the most prevalent emergent interaction. Understanding multiple stressor interactions is crucial for fundamental questions in ecology and also has implications for conservation biology and population management.

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↗

bioRxiv2019

Unraveling Why We Sleep: Quantitative Analysis Reveals Abrupt Transition from Neural Reorganization to Repair in Early Development

Sleep serves disparate functions, most notably neural repair, metabolite clearance and circuit reorganization, yet the relative importance of these functions remains hotly debated. Here, we create a novel mechanistic framework for understanding and predicting how sleep changes during ontogeny (why babies sleep twice as long as adults) and across phylogeny (why mice sleep roughly five times that of whales). We use this theory to quantitatively distinguish between sleep used for neural reorganization versus repair. We conduct a comprehensive, quantitative analysis of human sleep using total sleep time, cerebral metabolic rate, brain size, synaptic density, and REM sleep (used here to also refer to Active Sleep in infants and children). Our findings reveal an abrupt transition, between 2 and 3 years of age in humans. Specifically, our results show that differences in sleep across phylogeny and during late ontogeny (after 2 or 3 years in humans) are primarily due to sleep functioning for repair or clearance, while changes in sleep during early ontogeny (before 2 - 3 years in humans) primarily support neural reorganization and learning. Moreover, our analysis shows that neuroplastic reorganization occurs primarily in REM sleep but not in NREM. In accordance with the developmental role of neuroplasticity, the percent of time spent in REM sleep is independent of brain size across species but decreases dramatically as brain size grows through development. Furthermore, the ratio of NREM sleep time to awake time emerges as a new invariant across development. This developmental transition and fundamental shift across ontogeny and phylogeny suggests a complex interplay between developmental and evolutionary constraints on sleep.

neuroscience↗

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↗