Trawick, D. | bioRxiv Science

bioRxiv2024

Weather and leaf age separately contribute to temporal shifts in phyllosphere community structure and composition

Microbial communities living on plant leaves can positively or negatively influence plant health and, by extension, can impact whole ecosystems. Most research into the leaf microbiome consists of snapshots, and little is known about how microbial communities change over time. Weather and host physiological characteristics change over time and are often collinear with other time-varying factors, such as substrate availability, making it difficult to separate the factors driving microbial community change. We leveraged repeated measures over the course of an entire year to isolate the relative importance of environmental, host physiological, and substrate age-related factors on the assembly, structure, and composition of leaf-associated fungal communities. We applied both culturing and sequencing approaches to investigate these communities, focusing on a foundational, widely-distributed plant of conservation concern: basin big sagebrush (Artemisia tridentata subsp. tridentata). We found that changes in alpha diversity were independently affected by the age of a community and the air temperature. Surprisingly, total fungal abundance and species richness were not positively correlated and responded differently, sometimes oppositely, to weather. With regard to beta diversity, communities were more similar to each other across similar leaf ages, air temperatures, leaf types, and {delta}13C stable isotope ratios. Nine different genera were differentially abundant with air temperature, {delta}13C, leaf type, and leaf age, and a set of 20 genera were continuously present across the year. Our findings highlight the necessity for longer-term, repeated sampling to parse drivers of temporal change in leaf microbial communities. Open Research StatementAll ITS DNA amplicon sequence raw data are deposited in the NCBI Sequence Read Archive (SRA), BioProject number PRJNA1107252, data will be released upon publication. All community data, metadata, taxonomic data, and R code necessary to reproduce these results are deposited in the GitHub repository archived on Zenodo: 10.5281/zenodo.11106439.

ecology↗

bioRxiv2019

Categorical Assignment of Pulmonary Embolism is a Simple and More Accurate Indicator of Right Ventricular Dysfunction and Short Team Mortality

Several risk stratification tools are available to predict short-term mortality in patients with acute pulmonary embolism (PE). Right ventricular (RV) dysfunction, which is common to intermediate and high risk PE, is an independent predictor of mortality and may be a faster and simpler way to assess patient risk in acute care settings. We evaluated 571 patients presenting with acute PE as the primary diagnosis, stratifying them by the Pulmonary Embolism Severity Index (PESI), by the BOVA score, or categorically as low risk (no RV dysfunction by imaging), intermediate risk (RV dysfunction by imaging), or high risk PE (RV dysfunction by imaging with sustained hypotension). Using imaging data to firstly define the presence of RV dysfunction, and plasma cardiac troponin T (cTnT) and NT-proBNP as additional evidence for myocardial strain, we evaluated the PESI and BOVA scoring systems compared to categorical assignment of PE as low risk, submassive, and massive PE. Cardiac biomarkers poorly distinguished between PESI classes and BOVA stages in patients with acute PE. Cardiac TnT and NT-proBNP easily distinguished low risk from submassive PE with an area under the curve (AUC) of 0.84 (95% C.I. 0.73 - 0.95, p< 0.0001), and 0.88 (95% C.I. 0.79-0.97, p< 0.0001), respectively, and low risk from massive PE with an area under the curve (AUC) of 0.89 (95% C.I. 0.78 - 1.00, p< 0.0001), and 0.89 (95% C.I. 0.82-0.95, p< 0.0001), respectively. Predicted short-term mortality by PESI score or BOVA stage was lower than the observed mortality for submassive PE by a two-fold order of magnitude. These data suggest the presence of RV dysfunction in the context of acute PE is sufficient for the purposes of risk stratification, while more complicated risk stratification algorithms may under-estimate short-term mortality risk.

biochemistry↗