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Proszynski, J.

Publications and source records attributed to Proszynski, J..

4 recordsLinked to original sources

Modulator Resolves Transcript-, Allele-, and Condition-associated RNA Modification Differences from Direct RNA Sequencing

Nanopore direct-RNA sequencing (DRS) reports RNA modifications on single molecules, but there is no comprehensive algorithm for processing, aligning, and differentiating base modifications across reads that are often 5'-truncated. Here we present Modulator, which assigns every read, truncated or not, to a fragmentform, defined by a shared transcript 3'-end and the splice-junctions upstream of it. Of note, Modulator builds fragmentforms from genomic alignments without a reference transcriptome, estimates per-base modification stoichiometry within each fragmentform, and classifies each stoichiometry difference as transcript-, allele-, or condition-dependent. In the control HG002 transcriptome, Modulator built 23,746 fragmentforms, with 15,620 candidate novel isoforms that carried poly(A) signals as often as previously annotated transcripts. Also, assigning 5'-truncated reads to fragmentforms nearly doubled the number of testable and differentially modified sites. m6A sites within 100 nucleotides (nt) of a splice junction or within 1 kb of a poly(A) site were less modified in fragmentforms that use that junction or poly(A) site, indicating that local transcript context shapes where m6A is deposited. From the same reads, Modulator called SNPs with 93% precision and no phasing errors against the Genome in a Bottle benchmark. It identified 131 SNPs that create or remove a modifiable nucleotide and 1,358 allele-specific modification differences, most involving SNPs more than 50 nt from the modified site. In cells infected with Zika virus, which remodels gene expression relative to uninfected cells, Modulator identified 1,253 transcript-independent modification stoichiometry changes. Of the m6A changes at sites measured by GLORI, 96% agreed in direction with single-nucleotide-resolution GLORI maps of the same samples. Thus, Modulator accurately separates changes in RNA modification from transcript-associated and allele-associated differences and can improve the utility of nanopore DRS. Availability and Implementation: Modulator is free and open source: https://github.com/Theo-Nelson/Modulator. It is written in Python and runs on Linux OS.

bioinformatics↗

Alternative polyadenylation drives isoform-dependent m6A remodeling during Zika virus infection

Alternative RNA processing generates extensive transcript diversity, yet how transcript architecture influences selective m6A deposition is incompletely understood. Exon-junction-based models explain where m6A is excluded, but a positive determinant of m6A accumulation remains undefined. Here, we leverage Zika virus-induced changes in m6A deposition to uncover determinants of transcript-selective methylation. By integrating GLORI-seq, native METTL3 RNA immunoprecipitation, and nanopore direct RNA sequencing, we generate a single-nucleotide, isoform-resolved map of m6A dynamics during infection. We identify over 2,000 dynamic m6A sites, many arising from changes in transcript architecture, and pinpoint proximal polyadenylation sites as positive determinants of m6A accumulation. The cleavage stimulation factors CSTF2 and CSTF2T drive this remodeling through two routes: redundant induction of intronic polyadenylation, which converts internal exons into terminal exons that expose DRACH motifs to METTL3, and non-redundant, cleavage-independent recruitment of METTL3 near proximal polyadenylation sites, establishing alternative polyadenylation as a key architectural determinant of the m6A landscape.

molecular biology↗

The Spatial Atlas of Human Anatomy (SAHA): A Multimodal Subcellular-Resolution Reference Across Human Organs

The Spatial Atlas of Human Anatomy (SAHA) represents the first multimodal, subcellular- resolution reference of healthy adult human tissues across multiple organ systems. Integrating spatial transcriptomics, proteomics, and histological features across over 15 million cells from more than 100 donors, SAHA maps conserved and organ-specific cellular niches in gastrointestinal and immune tissues. High-resolution profiling using CosMx SMI, 10x Xenium, RNAscope, GeoMx DSP, and single-nucleus RNA-seq reveals spatially organized cell states, rare adaptive immune populations, and tissue-specific cell-cell interactions and ligand-receptor pairs. Comparative analyses with colorectal cancer and inflammatory bowel disease demonstrate the power of SAHA to detect disease-associated spatial disruptions, including crypt dedifferentiation, perineural invasion, and therapy-resistant immune remodeling. All data are openly accessible through a FAIR-compliant interactive portal to support exploration, benchmarking, and machine learning model training. Through SAHA, we provide a foundational framework for spatial diagnostics and next-generation precision medicine grounded in a comprehensive human tissue atlas, enabling the development of context-aware models that simulate tissue behavior, decode complex pathologies, and accelerate therapeutic innovation at unprecedented scale.

systems biology↗

Collection of Biospecimens from the Inspiration4 Mission Establishes the Standards for the Space Omics and Medical Atlas (SOMA)

The SpaceX Inspiration4 mission provided a unique opportunity to study the impact of spaceflight on the human body. Biospecimen samples were collected from the crew at different stages of the mission, including before (L-92, L-44, L-3 days), during (FD1, FD2, FD3), and after (R+1, R+45, R+82, R+194 days) spaceflight, creating a longitudinal sample set. The collection process included samples such as venous blood, capillary dried blood spot cards, saliva, urine, stool, body swabs, capsule swabs, SpaceX Dragon capsule HEPA filter, and skin biopsies, which were processed to obtain aliquots of serum, plasma, extracellular vesicles, and peripheral blood mononuclear cells. All samples were then processed in clinical and research laboratories for optimal isolation and testing of DNA, RNA, proteins, metabolites, and other biomolecules. This paper describes the complete set of collected biospecimens, their processing steps, and long-term biobanking methods, which enable future molecular assays and testing. As such, this study details a robust framework for obtaining and preserving high-quality human, microbial, and environmental samples for aerospace medicine in the Space Omics and Medical Atlas (SOMA) initiative, which can also aid future experiments in human spaceflight and space biology.

molecular biology↗