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Unlocking the microbiome
No full textIndividual species of bacteria and yeast present in the food of wild fruit flies work together to provide the nutrients needed for larval growth
A suite of selective pressures supports the maintenance of alleles of a Drosophila immune peptide
No full textA grant from the One-University Open Access Fund at the University of Kansas was used to defray the author's publication fees in this Open Access journal. The Open Access Fund, administered by librarians from the KU, KU Law, and KUMC libraries, is made possible by contributions from the offices of KU Provost, KU Vice Chancellor for Research & Graduate Studies, and KUMC Vice Chancellor for Research. For more information about the Open Access Fund, please see http://library.kumc.edu/authors-fund.xml.The innate immune system provides hosts with a crucial first line of defense against pathogens. While immune genes are often among the fastest evolving genes in the genome, in Drosophila, antimicrobial peptides (AMPs) are notable exceptions. Instead, AMPs may be under balancing selection, such that over evolutionary timescales multiple alleles are maintained in populations. In this study, we focus on the Drosophila antimicrobial peptide Diptericin A, which has a segregating amino acid polymorphism associated with differential survival after infection with the Gram-negative bacteria Providencia rettgeri. Diptericin A also helps control opportunistic gut infections by common Drosophila gut microbes, especially those of Lactobacillus plantarum. In addition to genotypic effects on gut immunity, we also see strong sex-specific effects that are most prominent in flies without functional diptericin A. To further characterize differences in microbiomes between different diptericin genotypes, we used 16S metagenomics to look at the microbiome composition. We used both lab reared and wild caught flies for our sequencing and looked at overall composition as well as the differential abundance of individual bacterial families. Overall, we find flies that are homozygous serine for diptericin A are better equipped to survive a systemic infection from P. rettgeri, but in general homozygous arginine flies have a longer lifespan after being fed common gut commensals. Our results suggest a possible mechanism for the maintenance of genetic variation of diptericin A through the complex interactions of sex, systemic immunity, and the maintenance of the gut microbiome
Review: Computational analysis of human skeletal remains in ancient DNA and forensic genetics
No full textDegraded DNA is used to answer questions in the fields of ancient DNA (aDNA) and forensic genetics. While aDNA studies typically center around human evolution and past history, and forensic genetics is often more concerned with identifying a specific individual, scientists in both fields face similar challenges. The overlap in source material has prompted periodic discussions and studies on the advantages of collaboration between fields toward mutually beneficial methodological advancements. However, most have been centered around wet laboratory methods (sampling, DNA extraction, library preparation, etc.). In this review, we focus on the computational side of the analytical workflow. We discuss limitations and considerations to consider when working with degraded DNA. We hope this review provides a framework to researchers new to computational workflows for how to think about analyzing highly degraded DNA and prompts an increase of collaboration between the forensic genetics and aDNA fields
Protection against Aβ-induced neuronal damage by KU-32: PDHK1 inhibition as important target
No full textA feature of most neurodegenerative diseases is the presence of “mis-folded proteins” that form aggregates, suggesting suboptimal activity of neuronal molecular chaperones. Heat shock protein 90 (Hsp90) is the master regulator of cell responses to “proteotoxic” stresses. Some Hsp90 modulators activate cascades leading to upregulation of additional chaperones. Novobiocin is a modulator at the C-terminal ATP-binding site of Hsp90. Of several novobiocin analogs synthesized and tested for protection against amyloid beta (Aβ)-induced neuronal death, “KU-32” was the most potent in protecting primary neurons, but did not increase expression of other chaperones believed to help clear misfolded proteins. However, KU-32 reversed Aβ-induced superoxide formation, activated Complex I of the electron transfer chain in mitochondria, and blocked the Aβ-induced inhibition of Complex I in neuroblastoma cells. A mechanism for these effects of KU-32 on mitochondrial metabolism appeared to be the inhibition of pyruvate dehydrogenase kinase (PDHK), both in isolated brain mitochondria and in SH-SY5Y cells. PDHK inhibition by the classic enzyme inhibitor, dichloroacetate, led to neuroprotection from Aβ25-35-induced cell injury similarly to KU-32. Inhibition of PDHK in neurons would lead to activation of the PDH complex, increased acetyl-CoA generation, stimulation of the tricarboxylic acid cycle and Complex I in the electron transfer chain, and enhanced oxidative phosphorylation. A focus of future studies may be on the potential value of PDHK as a target in AD therapy
Antibody-directed evolution reveals a mechanism for enhanced neutralization at the HIV-1 fusion peptide site
No full textThe HIV-1 fusion peptide (FP) represents a promising vaccine target, but global FP sequence diversity among circulating strains has limited anti-FP antibodies to ~60% neutralization breadth. Here we evolve the FP-targeting antibody VRC34.01 in vitro to enhance FP-neutralization using site saturation mutagenesis and yeast display. Successive rounds of directed evolution by iterative selection of antibodies for binding to resistant HIV-1 strains establish a variant, VRC34.01_mm28, as a best-in-class antibody with 10-fold enhanced potency compared to the template antibody and ~80% breadth on a cross-clade 208-strain neutralization panel. Structural analyses demonstrate that the improved paratope expands the FP binding groove to accommodate diverse FP sequences of different lengths while also recognizing the HIV-1 Env backbone. These data reveal critical antibody features for enhanced neutralization breadth and potency against the FP site of vulnerability and accelerate clinical development of broad HIV-1 FP-targeting vaccines and therapeutics
Human Impacts on the Vegetation of the Juan Fernández (Robinson Crusoe) Archipelago
No full textThe human footprint on marine and terrestrial ecosystems of the planet has been substantial, largely due to the increase in the human population with associated activities and resource utilization. Oceanic islands have been particularly susceptible to such pressures, resulting in high levels of loss of biodiversity and reductions in the numbers and sizes of wild populations. One archipelago that has suffered from human impact has been the Juan Fernández (Robinson Crusoe) Archipelago, a Chilean national park located 667 km west of Valparaíso at 33° S. latitude. The park consists of three principal islands: Robinson Crusoe Island (48 km); Santa Clara Island (2.2 km); and Alejandro Selkirk Island (50 km). The latter island lies 181 kms further west into the Pacific Ocean. No indigenous peoples ever visited or lived on any of these islands; they were first discovered by the Spanish navigator, Juan Fernández, in 1574. From that point onward, a series of European visitors arrived, especially to Robinson Crusoe Island. They began to cut the forests, and such activity increased with the establishment of a permanent colony in 1750 that has persisted to the present day. Pressures on the native and endemic flora increased due to the introduction of animals, such as goats, rats, dogs, cats, pigs, and rabbits. Numerous invasive plants also arrived, some deliberately introduced and others arriving inadvertently. At present, more than three-quarters of the endemic and native vascular species of the flora are either threatened or endangered. The loss of vegetation has also resulted in a loss of genetic variability in some species as populations are reduced in size or go extinct. It is critical that the remaining genetic diversity be conserved, and genomic markers would provide guidelines for the conservation of the diversity of the endemic flora. To preserve the unique flora of these islands, further conservation measures are needed, especially in education and phytosanitary monitoring
Connecting livestock disease dynamics to human learning and biosecurity decisions
No full textThe acceleration of animal disease spread worldwide due to increased animal, feed, and human movement has driven a growing body of epidemiological research as well as a deeper interest in human behavioral studies aimed at understanding their interconnectedness. Biosecurity measures can reduce the risk of infection, but human risk tolerance can hinder biosecurity investments and compliance. Humans may learn from hardship and become more risk averse, but sometimes they instead become more risk tolerant because they forget negative experiences happened in the past or because they come to believe they are immune. We represent the complexity of the hog production system with disease threats, human decision making, and human risk attitude using an agent-based model. Our objective is to explore the role of risk tolerant behaviors and the consequences of delayed biosecurity investments. We set up experiment with Monte Carlo simulations of scenarios designed with different risk tolerance amongst the swine producers and we derive distributions and trends of biosecurity and porcine epidemic diarrhea virus (PEDv) incidence emerging in the system. The output data allowed us to examine interactions between modes of risk tolerance and timings of biosecurity response discussing consequences for disease protection in the production system. The results show that hasty and delayed biosecurity responses or slow shifts toward a biosecure culture do not guarantee control of contamination when the disease has already spread in the system. In an effort to support effective disease prevention, our model results can inform policy making to move toward more resilient and healthy production systems. The modeled dynamics of risk attitude have also the potential to improve communication strategies for nudging and establishing risk averse behaviors thereby equipping the production system in case of foreign disease incursions
Use of claims data to predict the inpatient length of stay among U.S. stroke patients
No full textA grant from the One-University Open Access Fund at the University of Kansas was used to defray the author's publication fees in this Open Access journal. The Open Access Fund, administered by librarians from the KU, KU Law, and KUMC libraries, is made possible by contributions from the offices of KU Provost, KU Vice Chancellor for Research & Graduate Studies, and KUMC Vice Chancellor for Research. For more information about the Open Access Fund, please see http://library.kumc.edu/authors-fund.xml.Background
The prediction of stroke inpatient length of stay (LOS) attracts much attention from researchers worldwide as it facilitates resource management and improves care. However, studies largely underutilized the claims data for predicting stroke LOS. The predictive models for the U.S. stroke population are understudied.
Purpose
To evaluate the feasibility of using claims data for stroke LOS prediction and to identify new important predictors of LOS in U.S. stroke patients.
Methods
Data preparation, analyses, and predictive modeling processes were conducted on a retrospective dataset, including claims and EHR data about acute care stroke admissions during 2010–2018. Two tree-based models (i.e., the eXtreme Gradient Boosting (XGBoost) model and Categorical Boosting (CatBoost) model) were trained through 10-fold cross-validation and compared with a baseline model that did not include any predictors. The predictive performance was evaluated on the holdout set using mean absolute error (MAE) and root mean squared error (RMSE). Importance plots and SHAP (SHapley Additive exPlanations) plots were used to identify the important predictors.
Results
A total of 6102 stroke patients were included, with an average LOS of 6.4 days. The predictive models built using claims data (RMSE: 1.627; MAE: 0.530) performed similarly well as those built on the entire dataset, including additional variables from EHR (RMSE: 1.622; MAE: 0.533). Important predictors were admission channel and type, comorbidities (e.g., acute respiratory failure), medical services used (e.g., critical care, ambulance), facility characteristics (e.g., type, size), patient demographics, and patient socioeconomic status. Among these important predictors, admission channel and type, medical services including critical care and ambulance, facility type, and patient socioeconomic status were newly identified predictors not studied before.
Conclusion
Claims data are suitable for stroke LOS prediction. The newly identified important predictors from this study could be integrated with other existing key predictors identified in previous research to improve the prediction, thereby aiding in better stroke care management
Endophenotype trait domains for advancing gene discovery in autism spectrum disorder
No full textAutism spectrum disorder (ASD) is associated with a diverse range of etiological processes, including both genetic and non-genetic causes. For a plurality of individuals with ASD, it is likely that the primary causes involve multiple common inherited variants that individually account for only small levels of variation in phenotypic outcomes. This genetic landscape creates a major challenge for detecting small but important pathogenic effects associated with ASD. To address similar challenges, separate fields of medicine have identified endophenotypes, or discrete, quantitative traits that reflect genetic likelihood for a particular clinical condition and leveraged the study of these traits to map polygenic mechanisms and advance more personalized therapeutic strategies for complex diseases. Endophenotypes represent a distinct class of biomarkers useful for understanding genetic contributions to psychiatric and developmental disorders because they are embedded within the causal chain between genotype and clinical phenotype, and they are more proximal to the action of the gene(s) than behavioral traits. Despite their demonstrated power for guiding new understanding of complex genetic structures of clinical conditions, few endophenotypes associated with ASD have been identified and integrated into family genetic studies. In this review, we argue that advancing knowledge of the complex pathogenic processes that contribute to ASD can be accelerated by refocusing attention toward identifying endophenotypic traits reflective of inherited mechanisms. This pivot requires renewed emphasis on study designs with measurement of familial co-variation including infant sibling studies, family trio and quad designs, and analysis of monozygotic and dizygotic twin concordance for select trait dimensions. We also emphasize that clarification of endophenotypic traits necessarily will involve integration of transdiagnostic approaches as candidate traits likely reflect liability for multiple clinical conditions and often are agnostic to diagnostic boundaries. Multiple candidate endophenotypes associated with ASD likelihood are described, and we propose a new focus on the analysis of “endophenotype trait domains” (ETDs), or traits measured across multiple levels (e.g., molecular, cellular, neural system, neuropsychological) along the causal pathway from genes to behavior. To inform our central argument for research efforts toward ETD discovery, we first provide a brief review of the concept of endophenotypes and their application to psychiatry. Next, we highlight key criteria for determining the value of candidate endophenotypes, including unique considerations for the study of ASD. Descriptions of different study designs for assessing endophenotypes in ASD research then are offered, including analysis of how select patterns of results may help prioritize candidate traits in future research. We also present multiple candidate ETDs that collectively cover a breadth of clinical phenomena associated with ASD, including social, language/communication, cognitive control, and sensorimotor processes. These ETDs are described because they represent promising targets for gene discovery related to clinical autistic traits, and they serve as models for analysis of separate candidate domains that may inform understanding of inherited etiological processes associated with ASD as well as overlapping neurodevelopmental disorders
Dilution of specialist pathogens drives productivity benefits from diversity in plant mixtures
No full textProductivity benefits from diversity can arise when compatible pathogen hosts are buffered by unrelated neighbors, diluting pathogen impacts. However, the generality of pathogen dilution has been controversial and rarely tested within biodiversity manipulations. Here, we test whether soil pathogen dilution generates diversity- productivity relationships using a field biodiversity-manipulation experiment, greenhouse assays, and feedback modeling. We find that the accumulation of specialist pathogens in monocultures decreases host plant yields and that pathogen dilution predicts plant productivity gains derived from diversity. Pathogen specialization predicts the strength of the negative feedback between plant species in greenhouse assays. These feedbacks significantly predict the overyielding measured in the field the following year. This relationship strengthens when accounting for the expected dilution of pathogens in mixtures. Using a feedback model, we corroborate that pathogen dilution drives overyielding. Combined empirical and theoretical evidence indicate that specialist pathogen dilution generates overyielding and suggests that the risk of losing productivity benefits from diversity may be highest where environmental change decouples plant-microbe interactions