Mild Hypoxia Accelerates Cerebral Cavernous Malformation Disease Through CX3CR1-CX3CL1 Signaling.

BACKGROUND: Heterogeneity in the severity of cerebral cavernous malformations (CCMs) disease, including brain bleedings and thrombosis that cause neurological disabilities in patients, suggests that environmental, genetic, or biological factors act as disease modifiers. Still, the underlying mechanisms are not entirely understood. Here, we report that mild hypoxia accelerates CCM disease by promoting angiogenesis, neuroinflammation, and vascular thrombosis in the brains of CCM mouse models. METHODS: We used genetic studies, RNA sequencing, spatial transcriptome, micro-computed tomography, fluorescence-activated cell sorting, multiplex immunofluorescence, coculture studies, and imaging techniques to reveal that sustained mild hypoxia via the CX3CR1-CX3CL1 (CX3C motif chemokine receptor 1/chemokine [CX3C motif] ligand 1) signaling pathway influences cell-specific neuroinflammatory interactions, contributing to heterogeneity in CCM severity. RESULTS: Histological and expression profiles of CCM neurovascular lesions (Slco1c1-iCreERT2;Pdcd10fl/fl; Pdcd10BECKO) in male and female mice found that sustained mild hypoxia (12% O2, 7 days) accelerates CCM disease. Our findings indicate that a small reduction in oxygen levels can significantly increase angiogenesis, neuroinflammation, and thrombosis in CCM disease by enhancing the interactions between endothelium, astrocytes, and immune cells. Our study indicates that the interactions between CX3CR1 and CX3CL1 are crucial in the maturation of CCM lesions and propensity to CCM immunothrombosis. In particular, this pathway regulates the recruitment and activation of microglia and other immune cells in CCM lesions, which leads to lesion growth and thrombosis. We found that human CX3CR1 variants are linked to lower lesion burden in familial CCMs, proving it is a genetic modifier in human disease and a potential marker for aggressiveness. Moreover, monoclonal blocking antibody against CX3CL1 or reducing 1 copy of the Cx3cr1 gene significantly reduces hypoxia-induced CCM immunothrombosis. CONCLUSIONS: Our study reveals that interactions between CX3CR1 and CX3CL1 can modify CCM neuropathology when lesions are accelerated by environmental hypoxia. Moreover, a hypoxic environment or hypoxia signaling caused by CCM disease influences the balance between neuroinflammation and neuroprotection mediated by CX3CR1-CX3CL1 signaling. These results establish CX3CR1 as a genetic marker for patient stratification and a potential predictor of CCM aggressiveness.

Refining empiric subgroups of pediatric sepsis using machine-learning techniques on observational data.

Sepsis contributes to 1 of every 5 deaths globally with 3 million per year occurring in children. To improve clinical outcomes in pediatric sepsis, it is critical to avoid "one-size-fits-all" approaches and to employ a precision medicine approach. To advance a precision medicine approach to pediatric sepsis treatments, this review provides a summary of two phenotyping strategies, empiric and machine-learning-based phenotyping based on multifaceted data underlying the complex pediatric sepsis pathobiology. Although empiric and machine-learning-based phenotypes help clinicians accelerate the diagnosis and treatments, neither empiric nor machine-learning-based phenotypes fully encapsulate all aspects of pediatric sepsis heterogeneity. To facilitate accurate delineations of pediatric sepsis phenotypes for precision medicine approach, methodological steps and challenges are further highlighted.

Genome wide identification of chilling responsive microRNAs in Prunus persica.

BACKGROUND: MicroRNAs (miRNAs) are small RNAs (sRNAs) approximately 21 nucleotides in length that negatively control gene expression by cleaving or inhibiting the translation of target gene transcripts. Within this context, miRNAs and siRNAs are coming to the forefront as molecular mediators of gene regulation in plant responses to annual temperature cycling and cold stress. For this reason, we chose to identify and characterize the conserved and non-conserved miRNA component of peach (Prunus persica (L.) Batsch) focusing our efforts on both the recently released whole genome sequence of peach and sRNA transcriptome sequences from two tissues representing non-dormant leaves and dormant leaf buds. Conserved and non-conserved miRNAs, and their targets were identified. These sRNA resources were used to identify cold-responsive miRNAs whose gene targets co-localize with previously described QTLs for chilling requirement (CR). RESULTS: Analysis of 21 million peach sRNA reads allowed us to identify 157 and 230 conserved and non-conserved miRNA sequences. Among the non-conserved miRNAs, we identified 205 that seem to be specific to peach. Comparative genome analysis between peach and Arabidopsis showed that conserved miRNA families, with the exception of miR5021, are similar in size. Sixteen of these conserved miRNA families are deeply rooted in land plant phylogeny as they are present in mosses and/or lycophytes. Within the other conserved miRNA families, five families (miR1446, miR473, miR479, miR3629, and miR3627) were reported only in tree species (Populustrichocarpa, Citrus trifolia, and Prunus persica). Expression analysis identified several up-regulated or down-regulated miRNAs in winter buds versus young leaves. A search of the peach proteome allowed the prediction of target genes for most of the conserved miRNAs and a large fraction of non-conserved miRNAs. A fraction of predicted targets in peach have not been previously reported in other species. Several conserved and non-conserved miRNAs and miRNA-regulated genes co-localize with Quantitative Trait Loci (QTLs) for chilling requirement (CR-QTL) and bloom date (BD-QTL). CONCLUSIONS: In this work, we identified a large set of conserved and non-conserved miRNAs and describe their evolutionary footprint in angiosperm lineages. Several of these miRNAs were induced in winter buds and co-localized with QTLs for chilling requirement and bloom date thus making their gene targets potential candidates for mediating plant responses to cold stress. Several peach homologs of genes participating in the regulation of vernalization in Arabidopsis were identified as differentially expressed miRNAs targets, potentially linking these gene activities to cold responses in peach dormant buds. The non-conserved miRNAs may regulate cellular, physiological or developmental processes specific to peach and/or other tree species.

Deep neural networks with knockoff features identify nonlinear causal relations and estimate effect sizes in complex biological systems.

BACKGROUND: Learning the causal structure helps identify risk factors, disease mechanisms, and candidate therapeutics for complex diseases. However, although complex biological systems are characterized by nonlinear associations, existing bioinformatic methods of causal inference cannot identify the nonlinear relationships and estimate their effect size. RESULTS: To overcome these limitations, we developed the first computational method that explicitly learns nonlinear causal relations and estimates the effect size using a deep neural network approach coupled with the knockoff framework, named causal directed acyclic graphs using deep learning variable selection (DAG-deepVASE). Using simulation data of diverse scenarios and identifying known and novel causal relations in molecular and clinical data of various diseases, we demonstrated that DAG-deepVASE consistently outperforms existing methods in identifying true and known causal relations. In the analyses, we also illustrate how identifying nonlinear causal relations and estimating their effect size help understand the complex disease pathobiology, which is not possible using other methods. CONCLUSIONS: With these advantages, the application of DAG-deepVASE can help identify driver genes and therapeutic agents in biomedical studies and clinical trials.

Distinct cold tolerance traits independently vary across genotypes in Drosophila melanogaster.

Cold tolerance, the ability to cope with low temperature stress, is a critical adaptation in thermally variable environments. An individual's cold tolerance comprises several traits including minimum temperatures for growth and activity, ability to survive severe cold, and ability to resume normal function after cold subsides. Across species, these traits are correlated, suggesting they were shaped by shared evolutionary processes or possibly share physiological mechanisms. However, the extent to which cold tolerance traits and their associated mechanisms covary within populations has not been assessed. We measured five cold tolerance traits-critical thermal minimum, chill coma recovery, short- and long-term cold tolerance, and cold-induced changes in locomotor behavior-along with cold-induced expression of two genes with possible roles in cold tolerance (heat shock protein 70 and frost)-across 12 lines of Drosophila melanogaster derived from a single population. We observed significant genetic variation in all traits, but few were correlated across genotypes, and these correlations were sex-specific. Further, cold-induced gene expression varied by genotype, but there was no evidence supporting our hypothesis that cold-hardy lines would have either higher baseline expression or induction of stress genes. These results suggest cold tolerance traits possess unique mechanisms and have the capacity to evolve independently.

Assessment of Autism Zebrafish Mutant Models Using a High-Throughput Larval Phenotyping Platform.

In recent years, zebrafish have become commonly used as a model for studying human traits and disorders. Their small size, high fecundity, and rapid development allow for more high-throughput experiments compared to other vertebrate models. Given that zebrafish share >70% gene homologs with humans and their genomes can be readily edited using highly efficient CRISPR methods, we are now able to rapidly generate mutations impacting practically any gene of interest. Unfortunately, our ability to phenotype mutant larvae has not kept pace. To address this challenge, we have developed a protocol that obtains multiple phenotypic measurements from individual zebrafish larvae in an automated and parallel fashion, including morphological features (i.e., body length, eye area, and head size) and movement/behavior. By assaying wild-type zebrafish in a variety of conditions, we determined optimal parameters that avoid significant developmental defects or physical damage; these include morphological imaging of larvae at two time points [3 days post fertilization (dpf) and 5 dpf] coupled with motion tracking of behavior at 5 dpf. As a proof-of-principle, we tested our approach on two novel CRISPR-generated mutant zebrafish lines carrying predicted null-alleles of syngap1b and slc7a5, orthologs to two human genes implicated in autism-spectrum disorder, intellectual disability, and epilepsy. Using our optimized high-throughput phenotyping protocol, we recapitulated previously published results from mouse and zebrafish models of these candidate genes. In summary, we describe a rapid parallel pipeline to characterize morphological and behavioral features of individual larvae in a robust and consistent fashion, thereby improving our ability to better identify genes important in human traits and disorders.