Casey, J. | bioRxiv Science

bioRxiv2024

Antithrombotic Efficacy and Bleeding Risks of Vaccine-Induced Immune Thrombotic Thrombocytopenia Treatments

Current guidelines for treating vaccine-induced immune thrombotic thrombocytopenia (VITT) recommend non-heparin anticoagulants and intravenous immunoglobulin (IVIg). However, the efficacy of these treatments remains uncertain due to a lack of comparative clinical trials or animal studies. A recent study proposed danaparoid and heparin as potential VITT therapies due to their ability to disrupt VITT IgG-PF4 binding. Here, we examined the effects of various anticoagulants (including unfractionated (UF) heparin, danaparoid, bivalirudin, fondaparinux, and argatroban), IVIg, and the Fc{gamma}RIIa receptor-blocking antibody, IV.3, in relation to VITT pathophysiology. Our investigation focused on VITT IgG-PF4 binding, platelet activation, thrombocytopenia, and thrombosis. Danaparoid, at therapeutic doses, was the sole anticoagulant that reduced VITT IgG-PF4 binding, verified by purified anti-PF4 specific VITT IgG. Low-dose UF heparin (< 2U/mL) augmented VITT IgG binding to PF4 on platelets. While danaparoid and high-dose UF heparin (10 U/mL) inhibited platelet activation, none of the anticoagulants significantly affected thrombocytopenia in our VITT animal model, and all prolonged bleeding time. IVIg and all anticoagulants, except UF heparin, protected VITT mice from thrombosis. Direct Fc{gamma}RIIa receptor inhibition with IV.3 antibody proved the most effective approach for managing both thrombosis and thrombocytopenia in VITT. Our results underscore the necessity of animal model investigations to inform patient treatment strategies. This study provides compelling evidence for developing Fc{gamma}RIIa receptor blockers to treat VITT and other Fc{gamma}RIIa-related thrombotic inflammatory disorders. Key pointsO_LINon-heparin anticoagulants and IVIg reduce thrombosis in vivo by varying degrees whereas heparin exacerbates thrombosis. C_LIO_LIDirect blocking of Fc{gamma}RIIa receptor is the most effective strategy to treating both thrombosis and thrombocytopenia in VITT. C_LI

immunology↗

bioRxiv2021

A flexible Bayesian approach to estimating size-structured matrix population models

The rates of cell growth, division, and carbon loss of microbial populations are key parameters for understanding how organisms interact with their environment and how they contribute to the carbon cycle. However, the invasive nature of current analytical methods has hindered efforts to reliably quantify these parameters. In recent years, size-structured matrix population models (MPMs) have gained popularity for estimating rate parameters of microbial populations by mechanistically describing changes in microbial cell size distributions over time. And yet, the construction, analysis, and biological interpretation of these models are underdeveloped, as current implementations do not adequately constrain or assess the biological feasibility of parameter values, leading to inference which may provide a good fit to observed size distributions but does not necessarily reflect realistic physiological dynamics. Here we present a flexible Bayesian extension of size-structured MPMs for testing underlying assumptions describing the dynamics of a marine phytoplankton population over the day-night cycle. Our Bayesian framework takes prior scientific knowledge into account and generates biologically interpretable results. Using data from an exponentially growing laboratory culture of the cyanobacterium Prochlorococcus, we herein demonstrate the performance improvements of our approach over current models and isolate previously ignored biological processes, such as respiratory and exudative carbon losses, as critical parameters for the modeling of microbial population dynamics. The results demonstrate that this modeling framework can provide deeper insights into microbial population dynamics provided by flow-cytometry time-series data. Author summaryIdentifying the growth and population dynamics of marine microorganisms in their natural habitat is crucial to understanding the flow of carbon in the oceans but remains a grand challenge due to the invasive nature of current measurement methods. As time-series observations of population size structure have become more commonplace in aquatic environments, matrix population models (MPMs), which aim to mechanistically describe the change in size structure of these populations over time, have gained in popularity over the last decade. However, the underlying assumptions and behavior of MPMs have not been adequately scrutinized, and parameter values are difficult to interpret biologically, leading to inference that may not reflect plausible physiological dynamics. Here, we develop a Bayesian extension of the MPM framework to examine biological assumptions, improve interpretability of model output, and account for additional biological processes. We evaluated the performance of our models on a publicly available dataset of laboratory experiment time-series measurements of the cyanobacterium Prochlorococcus, Earths most abundant photosynthetic organisms, demonstrated the performance improvements of our approach over current models, and isolated previously ignored respiratory and exudative carbon losses as critical parameters for the modeling of microbial population dynamics.

microbiology↗

bioRxiv2019

HyPo: Super Fast & Accurate Polisher for Long Read Genome Assemblies

Efforts towards making population-scale long read genome assemblies (especially human genomes) viable have intensified recently with the emergence of many fast assemblers. The reliance of these fast assemblers on polishing for the accuracy of assemblies makes it crucial. We present HyPo-a Hybrid Polisher-that utilises short as well as long reads within a single run to polish a long read assembly of small and large genomes. It exploits unique genomic kmers to selectively polish segments of contigs using partial order alignment of selective read-segments. As demonstrated on human genome assemblies, Hypo generates significantly more accurate polished assemblies in about one-third time with about half the memory requirements in comparison to Racon (the widely used polisher currently).

bioinformatics↗