Biology subjects

Hendrickson, T.

Publications and source records attributed to Hendrickson, T..

4 recordsLinked to original sources

bioRxiv2024

Polycystin-1 loss of function increases susceptibility to atrial fibrillation through impaired DNA damage response

BackgroundThe increasing prevalence of atrial fibrillation (AF) and chronic kidney diseases highlights the need for a deeper comprehension of the molecular mechanisms linking them. Mutations in PKD1, the gene encoding Polycystin-1 (PKD1 or PC1), account for 85% of autosomal dominant polycystic kidney disease (ADPKD) cases. This disease often includes cardiac complications such as AF. In cardiomyocytes, PC1 deletion reduces hypertrophic response to pressure overload but promotes baseline ventricular dysfunction, while deletion in fibroblasts ameliorates post-myocardial infarction fibrosis. Despite its known cardiac impact, the role of PC1 in atrial cardiomyocytes and arrhythmias is less understood. Here, we sought to investigate the role of PC1 in AF. MethodsWe used intracardiac programmed stimulation and optical mapping to evaluate AF inducibility in two mouse models, Pkd1 R3277C, which recapitulates human ADPKD progression, and cardiomyocyte-specific Pkd1 deletion, and their respective controls. Isolated adult mouse atrial cardiomyocytes, human iPSC-derived atrial cardiomyocytes (hiPSC-aCM), and HL-1 cells served as in vitro cellular models. Molecular mechanisms were evaluated using optical mapping and molecular and biochemical approaches. ResultsLoss-of-function PC1 mutations significantly increased AF susceptibility in vivo and facilitated local reentry in ex vivo left atrial appendages. Comprehensive in vitro experiments supported a direct effect of PC1 in atrial cardiomyocytes. PC1-deficient monolayers exhibited increased arrhythmic events, escalating into reentrant spiral waves post-tachypacing. Transcriptomics analysis revealed PC1-dependent regulation of DNA repair, with PC1 deficiency leading to increased DNA damage under stress. PARP1 inhibitors or nicotinamide riboside, which counteract DNA damage-related metabolic consequences, reduced in vitro arrhythmias PC1-deficient monolayers. Overexpression of the C-terminus of PC1 had the opposite effects in DNA repair genes, suggesting its regulatory effects in atrial cardiomyocytes through retinoblastoma/E2F. Analyses of human atrial tissue from non-ADPKD AF patients showed reduced levels of mature PC1, suggesting a broader relevance of impaired PC1 in AF. ConclusionsImpaired PC1 increases in vivo AF inducibility under programmed electrical stimulation and promotes in vitro arrhythmias in hiPSC-aCM and HL-1 cells. Our findings indicate that PC1 protects against DNA damage to reduce AF susceptibility.

pathology↗

bioRxiv2022

Curation of BIDS (CuBIDS): a workflow and software package for streamlining reproducible curation of large BIDS datasets

The Brain Imaging Data Structure (BIDS) is a specification accompanied by a software ecosystem that was designed to create reproducible and automated workflows for processing neuroimaging data. BIDS Apps flexibly build workflows based on the metadata detected in a dataset. However, even BIDS valid metadata can include incorrect values or omissions that result in inconsistent processing across sessions. Additionally, in large-scale, heterogeneous neuroimaging datasets, hidden variability in metadata is difficult to detect and classify. To address these challenges, we created a Python-based software package titled "Curation of BIDS" (CuBIDS), which provides an intuitive workflow that helps users validate and manage the curation of their neuroimaging datasets. CuBIDS includes a robust implementation of BIDS validation that scales to large samples and incorporates DataLad--a version control software package for data--to ensure reproducibility and provenance tracking throughout the entire curation process. CuBIDS provides tools to help users perform quality control on their images metadata and identify unique combinations of imaging parameters. Users can then execute BIDS Apps on a subset of participants that represent the full range of acquisition parameters that are present, accelerating pipeline testing on large datasets. HIGHLIGHTSO_LICuBIDS is a workflow and software package for curating BIDS data. C_LIO_LICuBIDS summarizes the heterogeneity in a BIDS dataset. C_LIO_LICuBIDS prepares BIDS data for successful preprocessing pipeline runs. C_LIO_LICuBIDS helps users perform metadata-based quality control. C_LI

neuroscience↗

bioRxiv2021

Structures of core eukaryotic protein complexes

Protein-protein interactions play critical roles in biology, but despite decades of effort, the structures of many eukaryotic protein complexes are unknown, and there are likely many interactions that have not yet been identified. Here, we take advantage of recent advances in proteome-wide amino acid coevolution analysis and deep-learning-based structure modeling to systematically identify and build accurate models of core eukaryotic protein complexes, as represented within the Saccharomyces cerevisiae proteome. We use a combination of RoseTTAFold and AlphaFold to screen through paired multiple sequence alignments for 8.3 million pairs of S. cerevisiae proteins and build models for strongly predicted protein assemblies with two to five components. Comparison to existing interaction and structural data suggests that these predictions are likely to be quite accurate. We provide structure models spanning almost all key processes in Eukaryotic cells for 104 protein assemblies which have not been previously identified, and 608 which have not been structurally characterized. One-sentence summaryWe take advantage of recent advances in proteome-wide amino acid coevolution analysis and deep-learning-based structure modeling to systematically identify and build accurate models of core eukaryotic protein complexes.

biochemistry↗

bioRxiv2021

Adolescent Brain Cognitive Development (ABCD) Community MRI Collection and Utilities

The Adolescent Brain Cognitive Development Study (ABCD), a 10 year longitudinal neuroimaging study of the largest population based and demographically distributed cohort of 9-10 year olds (N=11,877), was designed to overcome reproducibility limitations of prior child mental health studies. Besides the fantastic wealth of research opportunities, the extremely large size of the ABCD data set also creates enormous data storage, processing, and analysis challenges for researchers. To ensure data privacy and safety, researchers are not currently able to share neuroimaging data derivatives through the central repository at the National Data Archive (NDA). However, sharing derived data amongst researchers laterally can powerfully accelerate scientific progress, to ensure the maximum public benefit is derived from the ABCD study. To simultaneously promote collaboration and data safety, we developed the ABCD-BIDS Community Collection (ABCC), which includes both curated processed data and software utilities for further analyses. The ABCC also enables researchers to upload their own custom-processed versions of ABCD data and derivatives for sharing with the research community. This NeuroResource is meant to serve as the companion guide for the ABCC. In section we describe the ABCC. Section II highlights ABCC utilities that help researchers access, share, and analyze ABCD data, while section III provides two exemplar reproducibility analyses using ABCC utilities. We hope that adoption of the ABCCs data-safe, open-science framework will boost access and reproducibility, thus facilitating progress in child and adolescent mental health research.

neuroscience↗