Search for: All records

ABSTRACT Microorganisms grow despite imbalances in the availability of nutrients and energy. The biochemical and elemental adjustments that bacteria employ to sustain growth when these resources are suboptimal are not well understood. We assessed howPseudomonas putidaKT2440 adjusts its physiology at differing dilution rates (to approximate growth rates) in response to carbon (C), nitrogen (N), and phosphorus (P) stress using chemostats. Cellular elemental and biomolecular pools were variable in response to different limiting resources at a slow dilution rate of 0.12 h⁻¹, but these pools were more similar across treatments at a faster rate of 0.48 h⁻¹. At slow dilution rates, limitation by P and C appeared to alter cell growth efficiencies as reflected by changes in cellular C quotas and rates of oxygen consumption, both of which were highest under P- and lowest under C- stress. Underlying these phenotypic changes was differential gene expression of terminal oxidases used for ATP generation that allows for increased energy generation efficiency. In all treatments under fast dilution rates, KT2440 formed aggregates and biofilms, a physiological response that hindered an accurate assessment of growth rate, but which could serve as a mechanism that allows cells to remain in conditions where growth is favorable. Our findings highlight the ways that microorganisms dynamically adjust their physiology under different resource supply conditions, with distinct mechanisms depending on the limiting resource at slow growth and convergence toward an aggregative phenotype with similar compositions under conditions that attempt to force fast growth. IMPORTANCEAll organisms experience suboptimal growth conditions due to low nutrient and energy availability. Their ability to survive and reproduce under such conditions determines their evolutionary fitness. By imposing suboptimal resource ratios under different dilution rates on the model organismPseudomonas putidaKT2440, we show that this bacterium dynamically adjusts its elemental composition, morphology, pools of biomolecules, and levels of gene expression. By examining the ability of bacteria to respond to C:N:P imbalance, we can begin to understand how stoichiometric flexibility manifests at the cellular level and impacts the flow of energy and elements through ecosystems. 

ABSTRACT Aquatic insects cope with hypoxia and anoxia using a variety of behavioral and physiological responses. Most stoneflies (Plecoptera) occur in highly oxygenated surface waters, but some species live underground in alluvial aquifers containing heterogeneous oxygen concentrations. Aquifer stoneflies appear to be supported by methane-derived food resources, which they may exploit using anoxia-resistant behaviors. We documented dissolved oxygen dynamics and collected stoneflies over 5 years in floodplain wells of the Flathead River, Montana. Hypoxia regularly occurred in two wells, and nymphs of Paraperla frontalis were collected during hypoxic periods. We measured mass-specific metabolic rates (MSMRs) at different oxygen concentrations (12, 8, 6, 4, 2, 0.5 mg l −1 , and during recovery) for 111 stonefly nymphs to determine whether aquifer and benthic taxa differed in hypoxia tolerance. Metabolic rates of aquifer taxa were similar across oxygen concentrations spanning 2 to 12 mg l −1 ( P >0.437), but the MSMRs of benthic taxa dropped significantly with declining oxygen ( P <0.0001; 2.9-times lower at 2 vs. 12 mg l −1 ). Aquifer taxa tolerated short-term repeated exposure to extreme hypoxia surprisingly well (100% survival), but repeated longer-term (>12 h) exposures resulted in lower survival (38–91%) and lower MSMRs during recovery. Our work suggests that aquifer stoneflies have evolved a remarkable set of behavioral and physiological adaptations that allow them to exploit the unique food resources available in hypoxic zones. These adaptations help to explain how large-bodied consumers might thrive in the underground aquifers of diverse and productive river floodplains. 

Abstract Estimation of the effective number of breeders per reproductive event (Nb) using single sample DNA-marker-based methods has rapidly grown in recent years. However, estimating Nb is difficult in age-structured populations because the performance of estimators is influenced by the Nb / Ne ratio, which varies among species with different life histories. We provide a computer program, AgeStrucNb, to simulate age-structured populations (including life history) and also estimate Nb. The AgeStrucNb program is composed of 4 major components to simulate, subsample, estimate, and then visualize Nb time series data. AgeStrucNb allows users to also quantify the precision and accuracy of any set of loci or sample size to estimate Nb for many species and populations. AgeStrucNb allows users to conduct power analysis to evaluate sensitivity to detect changes in Nb or the power to detect a correlation between trends in Nb and environmental variables (e.g., temperature, habitat quality, predator or pathogen abundance) that could be driving changes in Nb. The software provides Nb estimates for empirical data sets using the LDNe (linkage disequilibrium) method, includes publication-quality output graphs, and outputs genotype files in Genepop format for use in other programs. AgeStrucNb will help advance the application of genetic markers for monitoring Nb, which will help biologists to detect population declines and growth, which is crucial for research and conservation of natural and managed populations. 

Abstract A current challenge in the fields of evolutionary, ecological, and conservation genomics is balancing production of large-scale datasets with additional training often required to handle such datasets. Thus, there is an increasing need for conservation geneticists to continually learn and train to stay up-to-date through avenues such as symposia, meetings, and workshops. The ConGen meeting is a near-annual workshop that strives to guide participants in understanding population genetics principles, study design, data processing, analysis, interpretation, and applications to real-world conservation issues. Each year of ConGen gathers a diverse set of instructors, students, and resulting lectures, hands-on sessions, and discussions. Here, we summarize key lessons learned from the 2019 meeting and more recent updates to the field with a focus on big data in conservation genomics. First, we highlight classical and contemporary issues in study design that are especially relevant to working with big datasets, including the intricacies of data filtering. We next emphasize the importance of building analytical skills and simulating data, and how these skills have applications within and outside of conservation genetics careers. We also highlight recent technological advances and novel applications to conservation of wild populations. Finally, we provide data and recommendations to support ongoing efforts by ConGen organizers and instructors—and beyond—to increase participation of underrepresented minorities in conservation and eco-evolutionary sciences. The future success of conservation genetics requires both continual training in handling big data and a diverse group of people and approaches to tackle key issues, including the global biodiversity-loss crisis. 

Abstract Little is known about the life histories, genetic structure and population connectivity of shallow groundwater organisms. We used next-generation sequencing (RAD-seq) to analyse population genomic structure in two aquifer species: Paraperla frontalis (Banks, 1902), a stonefly with groundwater larvae and aerial (winged) adults; and Stygobromus sp., a groundwater-obligate amphipod. We found similar genetic differentiation in each species between floodplains separated by ~70 river km in the Flathead River basin of north-west Montana, USA. Given that Stygobromus lacks the above-ground life stage of P. frontalis, our findings suggest that connectivity and the magnitude of genetic structure cannot be definitively assumed from life history differences.