Linking leaf veins to growth and mortality rates: an example from a subtropical tree community

A fundamental goal in ecology is to link variation in species function to performance, but functional trait–performance investigations have had mixed success. This indicates that less commonly measured functional traits may more clearly elucidate trait–performance relationships. Despite the potential importance of leaf vein traits, which are expected to be related to resource delivery rates and photosynthetic capacity, there are few studies, which examine associations between these traits and demographic performance in communities. Here, we examined the associations between species traits including leaf venation traits and demographic rates (Relative Growth Rate, RGR and mortality) as well as the spatial distributions of traits along soil environment for 54 co‐occurring species in a subtropical forest. Size‐related changes in demographic rates were estimated using a hierarchical Bayesian approach. Next, Kendall's rank correlations were quantified between traits and estimated demographic rates at a given size and between traits and species‐average soil environment. Species with denser venation, smaller areoles, less succulent, or thinner leaves showed higher RGR for a wide range of size classes. Species with leaves of denser veins, larger area, cheaper construction costs or thinner, or low‐density wood were associated with high mortality rates only in small size classes. Lastly, contrary to our expectations, acquisitive traits were not related to resource‐rich edaphic conditions. This study shows that leaf vein traits are weakly, but significantly related to tree demographic performance together with other species traits. Because leaf traits associated with an acquisitive strategy such as denser venation, less succulence, and thinner leaves showed higher growth rate, but similar leaf traits were not associated with mortality, different pathways may shape species growth and survival. This study suggests that we are still not measuring some of key traits related to resource‐use strategies, which dictate the demography and distributions of species.     

Intra-host mathematical model of chronic wasting disease dynamics in deer (Odocoileus)

Bioassays of native cervid hosts have established the presence of infectious chronic wasting disease (CWD) prions in saliva, blood, urine, and feces of clinically diseased and pre-clinical infected deer. The intra-host trafficking of prions from the time of initial infection to shedding has been less well defined. We created a discrete-time compartmentalized model to simulate the misfolding catalysis, trafficking, and shedding of infectious prions throughout the organ systems of CWD-infected cervids. Using parameter values derived from experimental infections of North American deer (Odocoileus spp.), the exponential-based model predicts prion deposition over time with: 1) nervous tissues containing the highest deposition of prions at 20 months post-infection and 2) excreted fluids containing low levels of prions throughout infection with the highest numbers of prions predicted to be shed in saliva and feces (as high as 10 lethal doses (1.34 × 10²⁹ prions) in 11–15 months). These findings are comparable to prion deposition described in literature as assayed by conventional and ultrasensitive amplification assays. The comparison of our model to published data suggests that highly sensitive assays (sPMCA, RT-QuIC, and bioassay) are appropriate for early prion detection in bodily fluids and secretions. The model provides a view of intra-host prion catalysis leading to pre-clinical shedding and provides a framework for continued development of antemortem diagnostic methods.     

Kinetic Characterization of 100 Glycoside Hydrolase Mutants Enables the Discovery of Structural Features Correlated with Kinetic Constants

The use of computational modeling algorithms to guide the design of novel enzyme catalysts is a rapidly growing field. Force-field based methods have now been used to engineer both enzyme specificity and activity. However, the proportion of designed mutants with the intended function is often less than ten percent. One potential reason for this is that current force-field based approaches are trained on indirect measures of function rather than direct correlation to experimentally-determined functional effects of mutations. We hypothesize that this is partially due to the lack of data sets for which a large panel of enzyme variants has been produced, purified, and kinetically characterized. Here we report the k_cat and K_M values of 100 purified mutants of a glycoside hydrolase enzyme. We demonstrate the utility of this data set by using machine learning to train a new algorithm that enables prediction of each kinetic parameter based on readily-modeled structural features. The generated dataset and analyses carried out in this study not only provide insight into how this enzyme functions, they also provide a clear path forward for the improvement of computational enzyme redesign algorithms.     

Ligation of Glycophorin A Generates Reactive Oxygen Species Leading to Decreased Red Blood Cell Function

Acute, inflammatory conditions associated with dysregulated complement activation are characterized by significant increases in blood concentration of reactive oxygen species (ROS) and ATP. The mechanisms by which these molecules arise are not fully understood. In this study, using luminometric- and fluorescence-based methods, we show that ligation of glycophorin A (GPA) on human red blood cells (RBCs) results in a 2.1-fold, NADPH-oxidase-dependent increase in intracellular ROS that, in turn, trigger multiple downstream cascades leading to caspase-3 activation, ATP release, and increased band 3 phosphorylation. Functionally, using 2D microchannels to assess membrane deformability, GPS-ligated RBCs travel 33% slower than control RBCs, and lipid mobility was hindered by 10% using fluorescence recovery after photobleaching (FRAP). These outcomes were preventable by pretreating RBCs with cell-permeable ROS scavenger glutathione monoethyl ester (GSH-ME). Our results obtained in vitro using anti-GPA antibodies were validated using complement-altered RBCs isolated from control and septic patients. Our results suggest that during inflammatory conditions, circulating RBCs significantly contribute to capillary flow dysfunctions, and constitute an important but overlooked source of intravascular ROS and ATP, both critical mediators responsible for endothelial cell activation, microcirculation impairment, platelet activation, as well as long-term dysregulated adaptive and innate immune responses.     

Fish reduce anuran abundance and decrease herpetofaunal species richness in wetlands

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A teleofunctional account of evolutionary mismatch

When the environment in which an organism lives deviates in some essential way from that to which it is adapted, this is described as “evolutionary mismatch,” or “evolutionary novelty.” The notion of mismatch plays an important role, explicitly or implicitly, in evolution-informed cognitive psychology, clinical psychology, and medicine. The evolutionary novelty of our contemporary environment is thought to have significant implications for our health and well-being. However, scientists have generally been working without a clear definition of mismatch. This paper defines mismatch as deviations in the environment that render biological traits unable, or impaired in their ability, to produce their selected effects (i.e., to perform their proper functions in Neander’s sense). The machinery developed by Millikan in connection with her account of proper function, and with her related teleosemantic account of representation, is used to identify four major types, and several subtypes, of evolutionary mismatch. While the taxonomy offered here does not in itself resolve any scientific debates, the hope is that it can be used to better formulate empirical hypotheses concerning the effects of mismatch. To illustrate, it is used to show that the controversial hypothesis that general intelligence evolved as an adaptation to handle evolutionary novelty can, contra some critics, be formulated in a conceptually coherent way.     

Examining the sensitivity of molecular species delimitations to the choice of mitochondrial marker

Defining and understanding species diversity forms the basis of a wide range of biological and conservation work. Traditional taxonomy can be complemented and accelerated using molecular methods of species delimitation, such as the widely used Generalised Mixed Yule-Coalescent (GMYC) approach. This method uses time-calibrated phylogenetic trees in order to identify transition points between inter- and intraspecific divergence processes. Despite some important limitations, the GMYC approach appears to be robust to a wide range of dataset characteristics. It is one of the few model-based species-delimitation methods that remain practical for analysing molecular datasets with a large numbers of taxa. Most GMYC analyses have been based on datasets consisting of one or a small number of mitochondrial genes. To investigate the sensitivity of GMYC to the choice of mitochondrial marker, we compared GMYC estimates from 15 mitochondrial genes for three vertebrate datasets (cetaceans, ursids and whitefish). Despite the shared evolutionary history among mitochondrial genes, different markers exhibited substantial variation in GMYC delimitation results across all three datasets. This variability was not restricted to specific genes or taxa and extended to commonly used barcoding genes such as COI and CYTB. Using multiple concatenated markers mitigated these problems in two of the datasets, but exacerbated systematic biases present in a third. Our findings indicate the need to consider multiple markers, loci and lines of evidence when performing molecular species delimitation.