Biology subjects

Marshall, J. C.

Publications and source records attributed to Marshall, J. C..

4 recordsLinked to original sources

bioRxiv2025

Lipid Nanoparticle Delivery of Mesenchymal Stromal Cell-Derived microRNA 187-3p as a First-in-Class Therapy for Myocardial Dysfunction in Sepsis

BackgroundSepsis-induced myocardial dysfunction is a common and critical complication of sepsis. Extracellular vesicles (EVs) from clonally expanded immortalized mesenchymal stromal cells (ciMSCs) contain microRNAs that may be exploited as therapy. MethodsIn mouse models of septic cardiomyopathy induced by caecum ligation and puncture, cardiac function was determined by invasive and echocardiographic assessment. Primary cardiomyocytes derived from foetal murine and human adult ventricular tissue, as well as murine hearts were used for mechanistic studies. Studies using post-mortem human hearts or patient plasma, and clinical and echocardiographic measurements were used to establish translational relevance. ResultsIn preclinical models of sepsis, intravenous administration of either MSCs or ciMSC-EVs, given after the induction of sepsis, prevented a decrease in myocardial ejection fraction, ventricular inflammation, and mortality compared to placebo or platelet-derived control EVs. EV-microRNA sequencing identified enrichment for microRNA-187a-3p (miR-187) in ciMSC-EVs. miR-187 is anti-inflammatory; with interleukin-6 (IL-6) as its major target. Intravenous delivery of lipid nanoparticle (LNP) encapsulated miR-187 improved cardiac function, reduced inflammation, and enhanced survival of septic mice. In cardiomyocytes and in murine hearts, LNP-miR-187 reduces inflammation and expression of myocardial transcription factors linked to fetal gene reactivation in failing septic hearts. In human septic hearts, low circulating miR-187 levels correlate with reduced cardiac function and high sequential organ failure assessment (SOFA) scores. ConclusionThese findings support the development of first-in-class, cell-free, miRNA-based therapy as a novel approach to treat sepsis-induced cardiomyopathy to address a critical gap in sepsis care. One Sentence SummarymiR-based therapy for sepsis The Clinical PerspectiveA. What is NEW? Sepsis accounts for 1 in 5 deaths worldwide. Here, we demonstrate that sepsis-induced myocardial dysfunction represents a discrete, targetable sepsis-trait -- a distinct biological abnormality characterized by cardiomyocyte inflammation and fetal gene reactivation. This component contributes to the propagation of organ dysfunction and overall mortality and may respond to focused epigenetic-based interventions. B. What are the Clinical implications? Currently, there are no effective treatments to reduce, limit, or reverse the immune dysfunction component of sepsis that contributes to multiorgan failure, such as sepsis-induced cardiomyopathy. We identify miR-187 as a clinically relevant post-transcriptional regulator of cardiac inflammation and cardiomyocyte gene expression. Intravenous delivery of miR-187 encapsulated in a lipid nanoparticle (LNP) represents a fundamentally distinct, effective and pathogen-agnostic approach to correcting sepsis-induced cardiac dysfunction through modulation of cardiomyocyte inflammatory and metabolic pathways.

molecular biology↗

bioRxiv2024

Spatial risk of disease transmission between wild bovids and livestock in Thailand

The livestock-wildlife interface is one of the most essential issues threatening wildlife conservation and public health. Identifying interface areas can help to prioritise disease surveillance and implement mitigation measures and control programs for targeting threatened wildlife. We predicted interface areas which were assumed to be areas at risk of infectious disease transmission based on the spatial overlap between three Thai wild bovids (including gaur, banteng and wild water buffalo) habitat suitability and domestic cattle. We assumed that domestic cattle are the reservoir of bovine infectious disease, and that high cattle density is a proxy for a higher risk of disease transmission. Our study indicated that the highest risk areas for the native species are at the forest edges where overlap exists between high habitat suitability and high cattle density. Wild water buffalo showed the largest proportion of high-risk areas (8%), while gaur and banteng showed similar risk areas (4%) in Thailand. The largest proportion of risk areas overlapping with protected areas was Namtok Sam Lan PAs at 89% for gaur, 84% for banteng and 65% for wild water buffalo. Kuiburi NP has the largest risk area around 274 km2 (around 28% of the total protected area) for gaur and banteng, whereas wild water buffalo has the largest risk area overlapping with Huai Thabthan-Had Samran around 126 km2 (10% of the PA). Kaengkrachan Forest Complex showed the second largest risk area from 249 km2 for gaur and 273 km2 for banteng (8-9% of the PA). Our results address how habitat suitability might be helpful for infectious disease prevention and control strategies focused on native fauna and One Health. Furthermore, this work may also support the wild bovid habitat conservation initiatives and land use planning by informing decision-making about balancing wildlife habitats and livestock farming.

ecology↗

bioRxiv2022

Lost In The Forest

Levels of a predictor variable that are absent when a classification tree is grown can not be subject to an explicit splitting rule. This is an issue if these absent levels then present in a new observation for prediction. To date, there remains no satisfactory solution for absent levels in random forest models. Unlike missing data, absent levels are fully observed and known. Ordinal encoding of predictors allows absent levels to be integrated and used for prediction. Using a case study on source attribution of Campylobacter species using whole genome sequencing (WGS) data as predictors, we examine how target-agnostic versus target-based encoding of predictor variables with absent levels affects the accuracy of random forest models. We show that a target-based encoding approach using class probabilities, with absent levels designated the highest rank, is systematically biased, and that this bias is resolved by encoding absent levels according to the a priori hypothesis of equal class probability. We present a novel method of ordinal encoding predictors via principal coordinates analysis (PCO) which capitalizes on the similarity between pairs of predictor levels. Absent levels are encoded according to their similarity to each of the other levels in the training data. We show that the PCO-encoding method performs at least as well as the target-based approach and is not biased.

bioinformatics↗

bioRxiv2019

Data driven analysis reveals shared transcriptome response and immune cell composition across aetiologies of critical illness.

Sepsis and trauma are frequent and challenging health problems in critical care. The diversity of patient response to these conditions complicates both disease management and outcome prediction. Whole blood transcriptomics allows the analysis of response in the critically ill at a molecular level. Prior results in this field demonstrate robust and diverse genomic response in the acute phase and others have shown shared biological mechanisms across wide disease aetiologies. We hypothesize that specific biological mechanisms, particularly those related to immune processes, are shared between sepsis and trauma cohorts. These may serve as universal markers for patients vulnerable to a complicated clinical course and/or mortality. We present a systems level analysis of gene expression for a total of 317 patients with abdominal sepsis (51), pulmonary sepsis (108) or trauma (158) and compare them to healthy controls (68). Our results confirm that immune processes are shared across disease aetiologies in critical illnesses. We identify two consistent and distinct subgroups of critical illness: 1) increased dendritic cell and CD4 T helper fractions but suppressed neutrophils and 2) high neutrophils and otherwise suppressed leukocyte fractions. These subgroups validate in an independent cohort of 181 paediatric patients suffering from septic shock of diverse aetiologies. Furthermore, we found immune and inflammatory processes derived from gene co-expression networks were downregulated in subgroup 1. This paralleled prior results which find similar leukocyte configuration by deconvolving whole blood transcriptomics, and this leukocyte configuration associates with greater susceptibility to multi organ failure. We are the first to identify a patient subgroup with a preserved leukocyte configuration across aetiologies of critical illness, which may serve as a universal predictor of complicated clinical course/poor outcome.

immunology↗