Biology subjects

Rodriguez, A. A.

Publications and source records attributed to Rodriguez, A. A..

9 recordsLinked to original sources

bioRxiv2026

ARCHER-LD: Rapid Long-Range Linkage Disequilibrium Calculations at Biobank Scale using GPU Acceleration

Linkage disequilibrium (LD) information from one's own dataset is considered optimal for downstream analyses such as statistical fine-mapping. However, the computational complexity ({approx}N2 / 2 computations for N variants) lead most studies to use external reference panels, such as from 1000 Genomes. To capture LD across all variant pairs in biobank-scale whole-genome sequencing (WGS) datasets with hundreds of millions of variants, new computational strategies are essential. We present a novel approach that uses multi-GPU distributed computing to compute R2 for every variant pair in a dataset. On chromosome 22 (1.8 million variants) of the 30x WGS 1000 Genomes dataset, our method using eight consumer-level 12GB GPUs (NVIDIA RTX 2080TIs) takes <10 minutes, while the same calculation with PLINK using a high-end 64-threaded CPU (Intel Xeon Gold 6338) takes >80 minutes, corresponding to a {approx}8x speedup. We further demonstrate true biobank-scale performance in the Penn Medicine Biobank (PMBB; 57,170 samples), computing chromosome 1 LD ({approx}1.38 million variants) in 49 minutes versus 22.7 hours for PLINK, a {approx}28x speedup. With this method, we successfully computed on the aforementioned 30x WGS 1000 Genomes dataset ({approx}120 million variants and {approx}2500 samples) the entire LD matrix (>1e16, or 10 quadrillion elements) in under 6 hours using 512 NVIDIA 40GB A100 GPUs on the Department of Energy Argonne Leadership Computing Facility Polaris Supercomputer. We make this tool, coded in Python using CuPy, publicly available. Using this tool, researchers can leverage the full extent of their genomic data without relying on external LD reference panels and acquire more accurate, population-specific findings, particularly for groups underrepresented in existing databases.

bioinformatics↗

bioRxiv2026

Delivery of small interfering RNA and antisense oligonucleotides across the blood-brain barrier with monovalent transferrin receptor 1 binding VHH-Fc fusion proteins

The blood-brain barrier (BBB) is a highly selective cell layer that restricts the diffusion of diverse chemical entities into the central nervous system (CNS) from systemic circulation. Macromolecular therapeutics including oligonucleotides, peptides, and monoclonal antibodies exhibit only minimal brain distribution after systemic dosing due to exclusion by the BBB. Receptor-mediated transcytosis (RMT) has evolved to transport vital cargo across the BBB through a specialized vesicular transport pathway. Transferrin receptor 1 (TfR1) shuttles transferrin, its natural ligand, across the BBB, as well as TfR1-binding IgG antibodies and conjugates. Here, we describe a novel monovalent TfR1-binding VHH-Fc for the delivery of oligonucleotide cargo, including antisense oligonucleotides (ASOs) and small interfering RNAs (siRNAs) across the BBB in rodents and non-human primates (NHPs), supporting the translational potential of the VHH-antisense RMT platform for the treatment of neurological disorders. We explore the role of binding affinity, conjugation site, drug-antibody ratio (DAR), and conjugation chemistry, and determine that binding affinity, DAR and conjugation site are major determinants of RMT capacity and brain activity of siRNAs delivered across the BBB. Graphical Abstract / Highlights O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/744307v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@d1d648org.highwire.dtl.DTLVardef@4b22d3org.highwire.dtl.DTLVardef@db8b6borg.highwire.dtl.DTLVardef@19e5ac3_HPS_FORMAT_FIGEXP M_FIG C_FIG - Anti-TfR1 (-TfR1) VHH ligands formatted as heterodimeric, 2-chain monovalent VHH-Fc were engineered for conjugation to siRNA and ASO. - Systematic in vivo evaluation of VHH clones spanning a range of TfR1 binding affinities revealed a relationship between TfR1 binding affinity and the CNS activity of intravenously dosed VHH-Fc-siRNA conjugates. - By optimizing TfR1 binding affinity, conjugation site, and conjugation chemistry, we identified VHH-Fc-siRNA molecules that efficiently cross the BBB via receptor-mediated transcytosis and reduce target mRNA across CNS tissues, including deeper brain regions, after intravenous (IV) or subcutaneous (SC) dosing in mice and non-human primates (NHPs).

neuroscience↗

bioRxiv2025

A chromatin-associated pool of Aurora A controls kinetochore-microtubule attachments to ensure chromosome biorientation

Accurate chromosome segregation requires dynamic kinetochore-microtubule attachments that, under the regulation of Aurora family kinases, biorient and align replicated chromosomes. In C. elegans, Aurora A acts with the TPX2-related activator TPXL-1 to regulate these attachments and control spindle length. We show that, in addition to prominent spindle pole localization, TPXL-1-AurA has a chromatin-associated pool positioned between the sister kinetochores. Structural modeling and biochemical analysis support TPXL-1 directly recognizing the nucleosome acidic patch via an arginine anchor. Disrupting this interaction selectively removed chromatin-bound TPXL-1-AurA and caused chromosome missegregation, whereas elevation of the chromatin pool disrupted chromosome alignment. These opposing perturbations inversely affected kinetochore recruitment of the microtubule-binding Ska complex. These results support spatially distinct TPXL-1-AurA populations acting sequentially, with the spindle pole pool controlling spindle length by switching kinetochores out of a depolymerization-coupled state, and the chromatin pool controlling attachment stabilization to ensure biorientation prior to anaphase.

cell biology↗

bioRxiv2025

Development of a Clinically Relevant Rabbit Model of Acute Laryngeal Injury

ObjectivesAcute Laryngeal Injury (ALgI) is created as a result of endotracheal tube pressure ulcer formation leading to fibrosis and inflammation. This condition often leads to airway obstruction and voice and swallowing dysfunction. This study demonstrates a reliable animal model of ALgI to reproduce the acute wound process seen clinically, to explore the pathophysiology of this disease process, and serve as a reproducible injury suitable for the evaluation of therapeutic interventions. MethodsAn ALgI model was developed in New Zealand White rabbits using precise mucosal stripping of the posterior larynx, followed by intubation with an oversized 4.0 endotracheal tube for one hour to mimic intubation-associated trauma and pressure ischemia. Laryngoscopy and laryngeal harvest were performed two weeks post-injury for histologic and immunofluorescent evaluation. ResultsInjured rabbits demonstrated an eight-fold increase in posterior glottic thickness (1.57mm vs. 0.19mm in controls; p=0.0004) and eleven-fold increase in collagen content (1.93mm2 vs. 0.17mm2; p=0.005). Collagen subtype analysis revealed a shift toward active collagen within the injured larynx compared to the uninjured, with increased type III collagen (69.0%% vs. 26.1%; p<0.0001) and reduced type I collagen (27.2% vs. 73.9%; p<0.0001) in the posterior glottis, consistent with the proliferative phase of wound healing. Collagen fiber alignment analysis demonstrated increased coherency in injured tissues (0.36 vs. 0.21; p=0.023), indicating early organized collagen formation consistent with scar formation within the posterior glottis. ConclusionsThe model offers a robust platform for studying the acute pathogenesis of laryngeal injury and for testing the treatment options in the management of ALgI. Level of EvidenceLevel III

bioengineering↗

bioRxiv2025

Bipartite chromatin recognition by Hop1 from two diverged holozoa

In meiosis, ploidy reduction is driven by a complex series of DNA breakage and recombination events between homologous chromosomes, orchestrated by meiotic HORMA domain proteins (HORMADs). Meiotic HORMADs possess a central chromatin binding region (CBR) whose architecture varies across eukaryotic groups. Here, we determine high-resolution crystal structures of the meiotic HORMAD CBR from two diverged aquatic holozoa, Schistosoma mansoni and Patiria miniata, which reveal tightly-associated PHD and winged helix-turn-helix (wHTH) domains. We show that PHD-wHTH CBRs bind duplex DNA through their wHTH domains, and identify key residues that disrupt this interaction. Combining experimental and predicted structures, we show that the CBRs PHD domains likely interact with the tail of histone H3, and may discriminate between unmethylated and trimethylated H3 lysine 4. Finally, we show that holozoa Hop1 CBRs bind nucleosomes in vitro in a bipartite manner involving both the PHD and wHTH domains. Our data reveal how meiotic HORMADs with PHD-wHTH CBRs can bind chromatin and potentially discriminate between chromatin states to drive meiotic recombination to specific chromosomal regions.

biochemistry↗

bioRxiv2024

Accelerating Genome- and Phenome-Wide Association Studies using GPUs - A case study using data from the Million Veteran Program

The expansion of biobanks has significantly propelled genomic discoveries yet the sheer scale of data within these repositories poses formidable computational hurdles, particularly in handling extensive matrix operations required by prevailing statistical frameworks. In this work, we introduce computational optimizations to the SAIGE (Scalable and Accurate Implementation of Generalized Mixed Model) algorithm, notably employing a GPU-based distributed computing approach to tackle these challenges. We applied these optimizations to conduct a large-scale genome-wide association study (GWAS) across 2,068 phenotypes derived from electronic health records of 635,969 diverse participants from the Veterans Affairs (VA) Million Veteran Program (MVP). Our strategies enabled scaling up the analysis to over 6,000 nodes on the Department of Energy (DOE) Oak Ridge Leadership Computing Facility (OLCF) Summit High-Performance Computer (HPC), resulting in a 20-fold acceleration compared to the baseline model. We also provide a Docker container with our optimizations that was successfully used on multiple cloud infrastructures on UK Biobank and All of Us datasets where we showed significant time and cost benefits over the baseline SAIGE model.

genetics↗

bioRxiv2023

Isolation and quantification of bacterial membrane vesicles for quantitative metabolic studies using mammalian cell cultures

Bacterial membrane vesicles (BMVs) are produced by most bacteria and participate in various cellular processes, such as intercellular communication, nutrient exchange, and pathogenesis. Notably, these vesicles can contain virulence factors, including toxic proteins, DNA, and RNA. Such factors can contribute to the harmful effects of bacterial pathogens on host cells and tissues. Although the general effects of BMVs on host cellular physiology are well known, the underlying molecular mechanisms are less understood. In this study, we introduce a vesicle quantification method, leveraging the membrane dye FM4-64. We utilize a linear regression model to analyze the fluorescence emitted by stained vesicle membranes to ensure consistent and reproducible vesicle-host interaction studies using cultured cells. This method is particularly valuable for identifying host cellular processes impacted by vesicles and their specific cargo. Moreover, it outcompetes clearly unreliable protein concentration-based methods. We (1) show a linear correlation between the quantity of vesicles and the fluorescence signal emitted from the FM4-64 dye, (2) introduce the "vesicle load" as a new semi-quantitative unit, facilitating more reproducible vesicle-cell culture interaction experiments (3) show that a stable vesicle load yields consistent host responses when studying vesicles from Pseudomonas aeruginosa mutants (4) demonstrate that typical vesicle isolation contaminants, such as flagella, do not significantly skew the metabolic response of lung epithelial cells to P. aeruginosa vesicles, and (5) identify inositol-1-monophosphatase (SuhB) as a pivotal regulator in the vesicle-mediated pathogenesis of P. aeruginosa.

cell biology↗

bioRxiv2023

The Enderstruder: An accessible open-source syringe extruder compatible with Ender series 3D printers

Bioprinting has enabled the precise spatiotemporal deposition of cells and biomaterials, opening new avenues of research in tissue engineering and regenerative medicine. Although several open-source syringe extruder adaptations for bioprinters have been published and adopted by end users, only one has been specifically adapted for the Ender series, an affordable and open-source line of thermoplastic 3D printers. Here, we introduce the Enderstruder, a cost-effective extruder attachment that uses a standard 10 mL BD syringe, positions the stepper motor at the level of the gantry, enhances x-axis stability with a linear rail, and uses the originally included stepper motor, resulting in reduced cost and simplified assembly. Furthermore, we present an iterative process to fine-tune printing profiles for high-viscosity biomaterial inks. To facilitate the implementation of our work by other researchers, we provide fully editable Cura profiles for five commonly used biomaterials. Using these five materials to validate and characterize our design, we employ the Enderstruder to print established calibration patterns and complex shapes. By presenting the Enderstruder and its iterative development process, this study contributes to the growing repository of open-source bioprinting solutions, fostering greater accessibility and affordability for researchers in tissue engineering. Specifications table O_TBL View this table: org.highwire.dtl.DTLVardef@52fe1aorg.highwire.dtl.DTLVardef@a874b8org.highwire.dtl.DTLVardef@1870252org.highwire.dtl.DTLVardef@a993d3org.highwire.dtl.DTLVardef@128092a_HPS_FORMAT_FIGEXP M_TBL C_TBL

bioengineering↗

bioRxiv2020

Genetic structure of Photosystem II functionality in rice unraveled by GWAS analysis

Rice production is a particularly important crop for the half-world population. Therefore, knowledge about which genes are implicated in the functionality of the Photosystem II, that are still poorly explored could collaborate in the assisted selection of rice improving. In the present study, we applied Genome wide Association Studies of PSII chlorophyll fluorescence under two contrasting environmental conditions in 283 rice accessions highly diverse. A total of 110 significant association SNP-phenotype were observed, and 69 quantitative trait loci identified with a total of 157 genes, of which 38 were highly significant, mapped spread out through rice genome. These underlying regions are enriched in genes related to biotic and abiotic stresses, transcription factors, Calvin cycle, senescence, and grain characters. The correlations analyses PSII chlorophyll fluorescence parameters and some panicle characteristics found here suggest the possibility of developing molecular markers to assist the breeding programs that improve photosynthesis and yield in rice. HighlightThe genetic structure of the Photosystem II functionality in rice was studied by using genome-wide association through chlorophyll fluorescence.

plant biology↗