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BioRxiv : the Preprint Server For... Jun 2024SARS-CoV-2 is a highly transmissible virus that causes COVID-19 disease. Mechanisms of viral pathogenesis include excessive inflammation and viral-induced cell death,...
SARS-CoV-2 is a highly transmissible virus that causes COVID-19 disease. Mechanisms of viral pathogenesis include excessive inflammation and viral-induced cell death, resulting in tissue damage. We identified the host E3-ubiquitin ligase TRIM7 as an inhibitor of apoptosis and SARS-CoV-2 replication via ubiquitination of the viral membrane (M) protein. mice exhibited increased pathology and virus titers associated with epithelial apoptosis and dysregulated immune responses. Mechanistically, TRIM7 ubiquitinates M on K14, which protects cells from cell death. Longitudinal SARS-CoV-2 sequence analysis from infected patients revealed that mutations on M-K14 appeared in circulating variants during the pandemic. The relevance of these mutations was tested in a mouse model. A recombinant M- K14/K15R virus showed reduced viral replication, consistent with the role of K15 in virus assembly, and increased levels of apoptosis associated with the loss of ubiquitination on K14. TRIM7 antiviral activity requires caspase-6 inhibition, linking apoptosis with viral replication and pathology.
PubMed: 38948778
DOI: 10.1101/2024.06.17.599107 -
BioRxiv : the Preprint Server For... Jun 2024CRISPR screens are powerful tools to identify key genes that underlie biological processes. One important type of screen uses fluorescence activated cell sorting (FACS)...
CRISPR screens are powerful tools to identify key genes that underlie biological processes. One important type of screen uses fluorescence activated cell sorting (FACS) to sort perturbed cells into bins based on the expression level of marker genes, followed by guide RNA (gRNA) sequencing. Analysis of these data presents several statistical challenges due to multiple factors including the discrete nature of the bins and typically small numbers of replicate experiments. To address these challenges, we developed a robust and powerful Bayesian random effects model and software package called Waterbear. Furthermore, we used Waterbear to explore how various experimental design parameters affect statistical power to establish principled guidelines for future screens. Finally, we experimentally validated our experimental design model findings that, when using Waterbear for analysis, high power is maintained even at low cell coverage and a high multiplicity of infection. We anticipate that Waterbear will be of broad utility for analyzing FACS-based CRISPR screens.
PubMed: 38948774
DOI: 10.1101/2024.06.17.599448 -
BioRxiv : the Preprint Server For... Jun 2024Social touch is critical for communication and to impart emotions and intentions. However, certain autistic individuals experience aversion to social touch, especially...
Social touch is critical for communication and to impart emotions and intentions. However, certain autistic individuals experience aversion to social touch, especially when it is unwanted. We used a novel social touch assay and Neuropixels probes to compare neural responses to social vs. non-social interactions in three relevant brain regions: vibrissal somatosensory cortex, tail of striatum, and basolateral amygdala. We find that wild type (WT) mice showed aversion to repeated presentations of an inanimate object but not of another mouse. Cortical neurons cared most about touch context (social vs. object) and showed a preference for social interactions, while striatal neurons changed their preference depending on whether mice could choose or not to interact. Amygdalar and striatal neurons were preferentially modulated by forced object touch, which was the most aversive. In contrast, the knockout (KO) model of autism found social and non-social interactions equally aversive and displayed more aversive facial expressions to social touch when it invaded their personal space. Importantly, when KO mice could choose to interact, neurons in all three regions did not discriminate social valence. Thus, a failure to differentially encode social from non-social stimuli at the circuit level may underlie social avoidance in autism.
PubMed: 38948773
DOI: 10.1101/2024.06.19.599778 -
BioRxiv : the Preprint Server For... Jun 2024Perineuronal nets (PNNs) are a condensed subtype of extracellular matrix that form a net-like coverings around certain neurons in the brain. PNNs are primarily composed...
Chondroitin sulfate glycan sulfation patterns influence histochemical labeling of perineuronal nets: a comparative study of interregional distribution in human and mouse brain.
Perineuronal nets (PNNs) are a condensed subtype of extracellular matrix that form a net-like coverings around certain neurons in the brain. PNNs are primarily composed of chondroitin sulfate (CS) proteoglycans from the lectican family that consist of CS-glycosaminoglycan (CS-GAG) side chains attached to a core protein. CS disaccharides can exist in various isoforms with different sulfation patterns. Literature suggests that CS disaccharide sulfation patterns can influence the function of PNNs as well as their labeling. This study was conducted to characterize such interregional CS disaccharide sulfation pattern differences in adult human (N = 81) and mouse (N = 19) brains. Liquid chromatography tandem mass spectrometry was used to quantify five different CS disaccharide sulfation patterns, which were then compared to immunolabeling of PNNs using (WFL) to identify CS-GAGs and anti-aggrecan to identify CS proteoglycans. In healthy brains, significant regional and species-specific differences in CS disaccharide sulfation and single versus double-labeling pattern were identified. A secondary analysis to investigate how early-life stress (ELS) impacts these PNN features discovered that although ELS increases WFL+ PNN density, the CS-GAG sulfation code and single versus double PNN-labeling distributions remained unaffected in both species. These results underscore PNN complexity in traditional research, emphasizing the need to consider their heterogeneity in future experiments.
PubMed: 38948769
DOI: 10.1101/2024.02.09.579711 -
BioRxiv : the Preprint Server For... Jun 2024Sjögren's disease (SjD) is a common exocrine disorder typified by chronic inflammation and dryness, but also profound fatigue, suggesting a pathological basis in...
OBJECTIVES
Sjögren's disease (SjD) is a common exocrine disorder typified by chronic inflammation and dryness, but also profound fatigue, suggesting a pathological basis in cellular bioenergetics. In healthy states, damaged or dysfunctional mitochondrial components are broken down and recycled by mitophagy, a specialized form of autophagy. In many autoimmune disorders, however, evidence suggests that dysfunctional mitophagy allows poorly functioning mitochondria to persist and contribute to a cellular milieu with elevated reactive oxygen species. We hypothesized that mitophagic processes are dysregulated in SjD and that dysfunctional mitochondria contribute to overall fatigue. We sought to link fatigue with mitochondrial dysfunction directly in SjD, heretofore unexamined, and further sought to assess the pathogenic extent and implications of dysregulated mitophagy in SjD.
METHODS
We isolated pan T cells via negative selection from the peripheral blood mononuclear cells of 17 SjD and 8 age-matched healthy subjects, all of whom completed fatigue questionnaires prior to phlebotomy. Isolated T cells were analyzed for mitochondrial oxygen consumption rate (OCR) and glycolysis using Seahorse, and linear correlations with fatigue measures were assessed. A mitophagy transcriptional signature in SjD was identified by reanalysis of whole-blood microarray data from 190 SjD and 32 healthy subjects. Differential expression analyses were performed by case/control and subgroup analyses comparing SjD patients by mitophagy transcriptional cluster against healthy subjects followed by bioinformatic interpretation using gene set enrichment analysis.
RESULTS
Basal OCR, ATP-linked respiration, maximal respiration, and reserve capacity were significantly lower in SjD compared to healthy subjects with no observed differences in non-mitochondrial respiration, basal glycolysis, or glycolytic stress. SjD lymphocytic mitochondria show structural alterations compared to healthy subjects. Fatigue scores related to pain/discomfort in SjD correlated with the altered OCR. Results from subgroup analyses by mitophagic SjD clusters revealed highly variable inter-cluster differentially expressed genes (DEGs) and expanded the number of SjD-associated gene targets by tenfold within the same dataset.
CONCLUSION
Mitochondrial dysfunction, associated with fatigue, is a significant problem in SjD and warrants further investigation.
PubMed: 38948768
DOI: 10.1101/2024.06.17.598269 -
BioRxiv : the Preprint Server For... Jun 2024is a prominent member of the human gut microbiota, playing crucial roles in maintaining gut homeostasis and host health. Although it primarily functions as a beneficial...
is a prominent member of the human gut microbiota, playing crucial roles in maintaining gut homeostasis and host health. Although it primarily functions as a beneficial commensal, can become pathogenic. To determine the genetic basis of its duality, we conducted a comparative genomic analysis of 813 strains, representing both commensal and pathogenic origins. Our findings reveal that pathogenic strains emerge across diverse phylogenetic lineages, due in part to rapid gene exchange and the adaptability of the accessory genome. We identified 16 phylogenetic groups, differentiated by genes associated with capsule composition, interspecies competition, and host interactions. A microbial genome-wide association study identified 44 genes linked to extra-intestinal survival and pathogenicity. These findings reveal how genomic diversity within commensal species can lead to the emergence of pathogenic traits, broadening our understanding of microbial evolution in the gut.
PubMed: 38948766
DOI: 10.1101/2024.06.19.599758 -
BioRxiv : the Preprint Server For... Jun 2024In this paper, we introduce a new, open-source software developed in Python for analyzing Auditory Brainstem Response (ABR) waveforms. ABRs are a far-field recording of...
In this paper, we introduce a new, open-source software developed in Python for analyzing Auditory Brainstem Response (ABR) waveforms. ABRs are a far-field recording of synchronous neural activity generated by the auditory fibers in the ear in response to sound, and used to study acoustic neural information traveling along the ascending auditory pathway. Common ABR data analysis practices are subject to human interpretation and are labor-intensive, requiring manual annotations and visual estimation of hearing thresholds. The proposed new Auditory Brainstem Response Analyzer (ABRA) software is designed to facilitate the analysis of ABRs by supporting batch data import/export, waveform visualization, and statistical analysis. Techniques implemented in this software include algorithmic peak finding, threshold estimation, latency estimation, time warping for curve alignment, and 3D plotting of ABR waveforms over stimulus frequencies and decibels. The excellent performance on a large dataset of ABR collected from three labs in the field of hearing research that use different experimental recording settings illustrates the efficacy, flexibility, and wide utility of ABRA.
PubMed: 38948763
DOI: 10.1101/2024.06.20.599815 -
BioRxiv : the Preprint Server For... Jun 2024Fully capturing cellular state requires examining genomic, epigenomic, transcriptomic, proteomic, and other assays for a biological sample and comprehensive...
Fully capturing cellular state requires examining genomic, epigenomic, transcriptomic, proteomic, and other assays for a biological sample and comprehensive computational modeling to reason with the complex and sometimes conflicting measurements. Modeling these so-called multi-omic data is especially beneficial in disease analysis, where observations across omic data types may reveal unexpected patient groupings and inform clinical outcomes and treatments. We present Multi-omic Pathway Analysis of Cancer (MPAC), a computational framework that interprets multi-omic data through prior knowledge from biological pathways. MPAC uses network relationships encoded in pathways using a factor graph to infer consensus activity levels for proteins and associated pathway entities from multi-omic data, runs permutation testing to eliminate spurious activity predictions, and groups biological samples by pathway activities to prioritize proteins with potential clinical relevance. Using DNA copy number alteration and RNA-seq data from head and neck squamous cell carcinoma patients from The Cancer Genome Atlas as an example, we demonstrate that MPAC predicts a patient subgroup related to immune responses not identified by analysis with either input omic data type alone. Key proteins identified via this subgroup have pathway activities related to clinical outcome as well as immune cell compositions. Our MPAC R package, available at https://bioconductor.org/packages/MPAC , enables similar multi-omic analyses on new datasets.
PubMed: 38948762
DOI: 10.1101/2024.06.15.599113 -
BioRxiv : the Preprint Server For... Jun 2024Serine protease cascades regulate key innate immune responses. In mosquitoes, these cascades involve clip-domain serine proteases and their non-catalytic homologs...
Serine protease cascades regulate key innate immune responses. In mosquitoes, these cascades involve clip-domain serine proteases and their non-catalytic homologs (CLIPs), forming a complex network whose make-up and structural organization is not fully understood. This study assessed the impact of 85 CLIPs on humoral immunity in . By coupling RNAi with assays measuring antimicrobial activity and melanization, we identified 27 CLIPs as immunoregulators that together form two distinct subnetworks. CLIPs regulating antimicrobial activity were found to control infection resistance, as knockdowns reduced bacterial load and improved survival. Furthermore, our analysis of CLIP gene expression unveiled a novel immunoregulatory mechanism reliant on protease baseline co-expression rather than infection-induced upregulation. These findings underscore that despite its complexity mosquito immune regulation may be targeted for malaria interventions.
PubMed: 38948760
DOI: 10.1101/2024.06.18.599423 -
BioRxiv : the Preprint Server For... Jun 20241Computational methods in biology can infer large molecular interaction networks from multiple data sources and at different resolutions, creating unprecedented...
1Computational methods in biology can infer large molecular interaction networks from multiple data sources and at different resolutions, creating unprecedented opportunities to explore the mechanisms driving complex biological phenomena. Networks can be built to represent distinct conditions and compared to uncover graph-level differences-such as when comparing patterns of gene-gene interactions that change between biological states. Given the importance of the graph comparison problem, there is a clear and growing need for robust and scalable methods that can identify meaningful differences. We introduce node2vec2rank (n2v2r), a method for graph differential analysis that ranks nodes according to the disparities of their representations in joint latent embedding spaces. Improving upon previous bag-of-features approaches, we take advantage of recent advances in machine learning and statistics to compare graphs in higher-order structures and in a data-driven manner. Formulated as a multi-layer spectral embedding algorithm, n2v2r is computationally efficient, incorporates stability as a key feature, and can provably identify the correct ranking of differences between graphs in an overall procedure that adheres to veridical data science principles. By better adapting to the data, node2vec2rank clearly outperformed the commonly used node degree in finding complex differences in simulated data. In the real-world applications of breast cancer subtype characterization, analysis of cell cycle in single-cell data, and searching for sex differences in lung adenocarcinoma, node2vec2rank found meaningful biological differences enabling the hypothesis generation for therapeutic candidates. Software and analysis pipelines implementing n2v2r and used for the analyses presented here are publicly available.
PubMed: 38948759
DOI: 10.1101/2024.06.16.599201