Biology subjects

Mason, C. E.

Publications and source records attributed to Mason, C. E..

At least 19 recordsLinked to original sources

bioRxiv2026

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↗

bioRxiv2026

BIOTIA-DX RESISTANCE Achieved the Best Antimicrobial Resistance Phenotype Prediction Accuracy at CAMDA 2026

We present BIOTIA-DX RESISTANCE (BDXR), our submission to the CAMDA 2026 AMR Challenge. This work extends our CAMDA 2025 submission [1] to a new set of six species-drug pairs and adds k-mer-based feature engineering (both targeted and whole-genome) for pairs where the 2025 gene-presence base model underperforms. BDXR achieved a mean accuracy of 86.1% across the six pairs on the CAMDA 2026 test set, ranking first on four pairs, tied for first on Streptococcus pneumoniae (penicillin), and second on Campylobacter jejuni (nalidixic acid); per-pair test accuracy ranged from 69.9% (C. jejuni, nalidixic acid) to 98.8% (S. pneumoniae, penicillin). We refer the reader to our 2025 preprint [1] for the underlying workflow, dataset curation, and clinical motivation; this preprint focuses on the results and methodological changes that are new in 2026.

microbiology↗

bioRxiv2026

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↗

bioRxiv2026

Diverse high-fat diets drive multi-omic reprogramming that persists after dietary reversal

Dietary fat composition modulates host physiology and the gut microbiome, but the long-term effects of specific fat sources and the extent to which these changes resolve after dietary reversal remain incompletely defined. Here, we present a longitudinal multi-omic resource of mice maintained for one year on a purified control diet, seven high-fat diets differing in predominant fat source, or reversal regimens in which animals were switched from high-fat to control diet after 4 or 9 months. We further incorporated two cohorts with distinct pre-existing microbiome configurations to determine how baseline community structure shapes diet-induced remodeling of the gut microbiome ecosystem. By integrating longitudinal phenotyping, fecal metagenomics, fecal metabolomics, plasma metabolomics and lipidomics, and intestinal single-cell RNA sequencing, we defined the shared and dietary fat-specific responses across host and microbiome compartments. Baseline microbiome composition strongly influenced microbial responses to diet, indicating that pre-existing community structure is a major determinant of dietary ecosystem remodeling. Although many altered features shifted toward baseline after dietary reversal, only approximately half of diet-associated microbial changes recovered within the study window. A subset of taxa exhibited persistent alterations, including sustained depletion of Lactobacillus johnsonii and Bifidobacterium pseudolongum and sustained enrichment of Alistipes finegoldii, consistent with a "microbiome memory" of prior high-fat diet exposure. This memory effect is mirrored in the host, by sustained suppression of major histocompatibility complex class II (MHC-II) gene expression in intestinal epithelial cells after dietary reversal. These findings indicate that dietary fats leave a lasting imprint on the host-microbiome interactome that survives dietary intervention. Together, these data establish a resource for defining how dietary fat source, baseline microbiome composition, and dietary history shape host-microbiome states. The entire resource is available online as an RShiny app.

systems biology↗

bioRxiv2026

Leveraging a hybrid cross-disciplinary training model to accelerate global bioinformatics capacity

Disparities in formal bioinformatics training exacerbate the global skills gap, impeding the democratized application of advanced genomic technologies. To bridge this divide, we introduce a scalable, hybrid training framework designed to rapidly accelerate regional bioinformatics capacity. We exemplify this approach through the Eastern European Bioinformatics and Genomics (EEBG) workshop series -- a cross-disciplinary initiative that pairs international faculty with local institutions to deliver modular, hands-on curricula. Functioning as a structured knowledge-transfer pipeline, the series has catalyzed a sustainable educational ecosystem, evidenced by the establishment of multiple independent summer schools across the region. The assessment of the 2025 EEBG workshop in Krakow, Poland, validates the models viability; participant metrics confirm high efficacy in skill acquisition (mean satisfaction: 4.4/5.0) and community building. Crucially, the hybrid delivery mode dismantled geographic barriers, serving as a vital mechanism for maintaining scientific continuity for researchers facing displacement and crisis. Synthesizing these outcomes, we define the core features of a replicable blueprint for scientific readiness in resource-constrained environments. We conclude by presenting a strategic roadmap -- organized around infrastructure standardization, governance sustainability, and geographical expansion -- for adapting this regional proof-of-concept into a global export-ready model, offering a critical path toward ensuring universal access to genomic innovation.

scientific communication and education↗

bioRxiv2025

Signaling induced biophysical disruption of repressed chromatin domains drives immune cell fate

Cell fate transitions require signal-induced chromatin derepression, yet mechanisms governing transitions from repressed to active chromatin states are poorly understood. We discover, at fate-defining genes across immune cell types, a signal-induced histone code, and describe domains of H3 serine 28 phosphorylation (H3S28ph) spanning architectural features, often coincident with repressive H3 lysine 27 trimethylation (H3K27me3). Employing biophysical, single cell, and functional approaches to study signal-induced cell differentiation in the immune system, we uncover epigenomic transitions and cell fate choices precipitated by histone phosphorylation (H3ph). Mechanistically, H3ph overrides Polycomb Repressive Complex 2 (PRC2) chromatin repression, biophysically disrupts polynucleosome compaction, and promotes loss of H3K27me3, while increasing activating H3K27 acetylation and H3K36 dimethylation to drive domain interactivity and stabilize transcription. We demonstrate the activity of H3ph in several cell fate transitions and illuminate biophysical mechanisms enabling rapid signal-activated chromatin derepression, processes with general relevance for cellular differentiation and activation.

immunology↗

bioRxiv2025

BIOTIA-DX RESISTANCE Achieved the Best Antimicrobial Resistance Phenotype Prediction Accuracy at CAMDA 2025

We have developed BIOTIA-DX RESISTANCE (BDXR), a bioinformatic tool for predicting antimicrobial resistance (AMR) from whole genome sequencing of microbial isolates. BDXR achieved the best accuracy of any submission to the CAMDA 2025 AMR Challenge. This years challenge focused on predicting AMR phenotype which is a more complex problem than the detection of AMR marker genes, the focus of some prior years. BDXR achieved an overall F1 score of 89% on the training set and 84.1% on the challenge test set. Accuracy varied across the 9 species and drug pairs in the competition from an F1 score of 98.4% (Campylobacter jejuni, tetracycline) to 78.5% (Pseudomonas aeruginosa, cefatzidime). BDXR is based on curation of global datasets, machine learning-based predictions from input data, and highly stringent prepreprocessing of input data and databases.

microbiology↗

bioRxiv2025

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↗

bioRxiv2025

On the ancestry and evolution of the extinct dire wolf

Dire wolves (Aenocyon dirus) are extinct predators of Pleistocene North America. Although phenotypically similar to living wolves (Canis lupus), dire wolves have yet to be placed confidently in the canid family tree. We generated 3.4x and 12.8x paleogenomes from two well-preserved dire wolves dating to > 13,000 and > 72,000 years ago, and estimated consensus species trees for these and 10 canid species. Our results revealed that [~]2/3 of dire wolf ancestry is derived from a lineage sister to the clade comprising the gray wolf, coyote, and dhole, and the remaining [~]1/3 from a lineage near the base of Canini diversity. We identified 80 genes evolving under diversifying selection in dire wolves. Our results underscore the power of paleogenomes to resolve long-standing taxonomic questions and contribute to growing evidence of the role of post-speciation gene flow as an evolutionary force.

evolutionary biology↗

bioRxiv2024

A robust benchmark for detecting low-frequency variants in the HG002 Genome In A Bottle NIST reference material.

Somatic mosaicism is an important cause of disease, but mosaic and somatic variants are often challenging to detect because they exist in only a fraction of cells. To address the need for benchmarking subclonal variants in normal cell populations, we developed a benchmark containing mosaic variants in the Genome in a Bottle Consortium (GIAB) HG002 reference material DNA from a large batch of a normal lymphoblastoid cell line. First, we used a somatic variant caller with high coverage (300x) Illumina whole genome sequencing data from the Ashkenazi Jewish trio to detect variants in HG002 not detected in at least 5% of cells from the combined parental data. These candidate mosaic variants were subsequently evaluated using >100x BGI, Element, and PacBio HiFi data. High confidence candidate SNVs with variant allele fractions above 5% were included in the HG002 draft mosaic variant benchmark, with 13/85 occurring in medically relevant gene regions. We also delineated a 2.45 Gbp subset of the previously defined germline autosomal benchmark regions for HG002 in which no additional mosaic variants >2% exist, enabling robust assessment of false positives. The variant allele fraction of some mosaic variants is different between batches of cells, so using data from the homogeneous batch of reference material DNA is critical for benchmarking these variants. External validation of this mosaic benchmark showed it can be used to reliably identify both false negatives and false positives for a variety of technologies and detection algorithms, demonstrating its utility for optimization and validation. By adding our characterization of mosaic variants in this widely-used cell line, we support extensive benchmarking efforts using it in simulation, spike-in, and mixture studies.

bioinformatics↗

bioRxiv2024

A familial, telomere-to-telomere reference for human de novo mutation and recombination from a four-generation pedigree

Using five complementary short- and long-read sequencing technologies, we phased and assembled >95% of each diploid human genome in a four-generation, 28-member family (CEPH 1463) allowing us to systematically assess de novo mutations (DNMs) and recombination. From this family, we estimate an average of 192 DNMs per generation, including 75.5 de novo single-nucleotide variants (SNVs), 7.4 non-tandem repeat indels, 79.6 de novo indels or structural variants (SVs) originating from tandem repeats, 7.7 centromeric de novo SVs and SNVs, and 12.4 de novo Y chromosome events per generation. STRs and VNTRs are the most mutable with 32 loci exhibiting recurrent mutation through the generations. We accurately assemble 288 centromeres and six Y chromosomes across the generations, documenting de novo SVs, and demonstrate that the DNM rate varies by an order of magnitude depending on repeat content, length, and sequence identity. We show a strong paternal bias (75-81%) for all forms of germline DNM, yet we estimate that 17% of de novo SNVs are postzygotic in origin with no paternal bias. We place all this variation in the context of a high-resolution recombination map ([~]3.5 kbp breakpoint resolution). We observe a strong maternal recombination bias (1.36 maternal:paternal ratio) with a consistent reduction in the number of crossovers with increasing paternal (r=0.85) and maternal (r=0.65) age. However, we observe no correlation between meiotic crossover locations and de novo SVs, arguing against non-allelic homologous recombination as a predominant mechanism. The use of multiple orthogonal technologies, near-telomere-to-telomere phased genome assemblies, and a multi-generation family to assess transmission has created the most comprehensive, publicly available "truth set" of all classes of genomic variants. The resource can be used to test and benchmark new algorithms and technologies to understand the most fundamental processes underlying human genetic variation.

genomics↗

bioRxiv2024

Forecasting Dengue Fever in Brazil Using Multimodal Data, Including Climate Data

Dengue fever is a major tropical disease transmitted by Aedes mosquitoes. Dengue affects more than 120 countries with highly variable year to year infection rates. Despite high variability, dengue has a clear relationship to climate factors and human demography. Global trends to higher temperatures and greater disorderly urban development are increasing the scale and scope of dengue risk. Dengue has complex human immunity with 4 known serotypes that make multiple infections possible. Accurate forecasting of dengue fever would allow for appropriate interventions and improved public health outcomes. We demonstrate, GeoSeeq Dengue, a forecasting model for dengue fever in Brazil. GeoSeeq Dengue predicts dengue outbreaks monthly in 5,570 Brazilian municipalities at 1, 3, and 6 months ahead of the outbreak. Model accuracy compares favorably to a historical baseline model, making it a promising model for informing public health response. We evaluate how different types of input variables effect model accuracy and explore how this model could be adapted to other countries. This model could inform public health responses to dengue including targeting vector control programs, public health education messaging, and the newly launched dengue vaccine rollout.

bioinformatics↗

bioRxiv2024

DERIVATION OF ELEPHANT INDUCED PLURIPOTENT STEM CELLS

The crisis of biodiversity loss in the anthropogenic era requires new tools for studying non-model organisms. Elephants, for example, are both an endangered species and excellent models studying complex phenotypes like size, social behavior, and longevity, but they remain severely understudied. Here we report the first derivation of elephant (Elephas maximus) induced pluripotent stem cells (emiPSCs) achieved via a two-step process of chemical-media induction and colony selection, followed by overexpression of elephant transcription factors OCT4, SOX2, KLF4, MYC {+/-} NANOG and LIN28A, and modulation of the TP53 pathway. Since the seminal discovery of reprogramming by Shinya Yamanaka, iPSCs from many species including the functionally extinct northern white rhinocerous have been reported, but emiPSCs have remained elusive. While for multiple species the reprogramming protocol was adopted with little changes compared to model organisms like mouse and human, our emiPSC protocol requires a longer timeline and inhibition of TP53 expansion genes that are hypothesized to confer unique cancer resistance in elephants. iPSCs unlock tremendous potential to explore cell fate determination, cell and tissue development, cell therapies, drug screening, disease modeling, cancer development, gametogenesis and beyond to further our understanding of this iconic megafauna. This study opens new frontiers in advanced non-model organism cellular models for genetic rescue and conservation.

cell biology↗

bioRxiv2024

Pharmacogenomics Guided Spaceflight: the intersection between space-flown drugs and space genes

Ten years ago, it was predicted that the multi-omics revolution would also revolutionize space pharmacogenomics. Current barriers related to the findable, accessible, interoperable, and reproducible use of space-flown pharmaceutical data have contributed to a lack of progress beyond application of earth-based principles. To directly tackle these challenges, we have produced a novel database of all the drugs flown into space, compiled from publicly available ontological and spaceflight-related datasets, to exemplify analyses for describing significant spaceflight-related targets. By focusing on mechanisms perturbed by spaceflight, we have provided a novel avenue for identifying the most relevant changes within the drug absorption, distribution, metabolism, and excretion pathways. We suggest a set of space genes, by necessity limited to available tissue types, that can be expanded and modified based on future tissue-specific and mechanistic-specific high-throughput assays. In sum, we provide the justification and a definitive starting point for pharmacogenomics guided spaceflight as a foundation of precision medicine, which will enable long-term human habitation of the Moon, Mars, and beyond. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=147 SRC="FIGDIR/small/575951v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@48f739org.highwire.dtl.DTLVardef@5ecdb0org.highwire.dtl.DTLVardef@121c93org.highwire.dtl.DTLVardef@1122b3f_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2023

The impact of PCR duplication on RNA-seq data generated using NovaSeq 6000, NovaSeq X, AVITI and G4 sequencers.

RNA sequencing (RNA-seq) is a powerful technology for gene expression and functional genomics profiling. Expression profiles generated using this approach can be impacted by the methods utilised for cDNA library generation. Selection of the optimal parameters for each step during the protocol are crucial for acquisition of high-quality data. Polymerase chain reaction (PCR) amplification of transcripts is a common step in many RNA-seq protocols and, if not optimised, high PCR duplicate proportions can be generated, resulting in the inflation of transcript counts and introduction of bias. In this study, we investigate the impact of input amount and PCR cycle number on the PCR duplication rate and on the RNA-seq data quality using a broad range of inputs (1 ng -1,000 ng) for RNA-seq library preparation with unique molecular identifiers (UMIs) and sequencing the data on four different short-read sequencing platforms: Illumina NovaSeq 6000, Illumina NovaSeq X, Element Biosciences AVITI, and Singular Genomics G4. Across all platforms, samples of input amounts greater than 125 ng had a negligible PCR duplication rate and the number of PCR cycles did not have a significant effect on data quality. However, for input amounts lower than 125ng we observed a strong negative correlation between input amount and the proportion of PCR duplicates; between 34% and 96% of reads were discarded via deduplication. Fortunately, UMIs were effective for removing in silico PCR duplicates without removing valuable biological information. Removal of PCR duplicates resulted in more comparable gene expression obtained from the different PCR cycles. Data generated with each of the four sequencing platforms presented similar associations between starting material amount and the number of PCR cycles on PCR duplicates, a similar number of genes detected, and comparable gene expression profiles. However, the sequencers using conversion kits for Illumina libraries (AVITI, G4) exhibited lower adapter dimer abundance across all input amounts, but also a higher PCR duplication rate in very low input amounts (<15ng). Overall, this study showed that the choice of input amount and number of PCR cycles are important parameters for obtaining high-quality RNA-seq data across all sequencing platforms. UMI deduplication is an effective way to remove PCR duplicates, improving the data quality and removing any variation caused by the conversion kits.

genomics↗

bioRxiv2023

Cyanobacteria newly isolated from marine volcanic seeps display rapid sinking and robust, high density growth

Cyanobacteria are photosynthetic organisms that play important roles in carbon cycling as well as promising bioproduction chassis. Here, we isolate two novel cyanobacteria, UTEX 3221 and UTEX 3222, from a unique marine environment with naturally elevated CO2. We describe complete genome sequences for both isolates and, focusing on UTEX 3222 due to its planktonic growth in liquid, characterize biotechnologically-relevant growth and biomass characteristics. UTEX 3222 outpaces other fast-growing model strains on solid medium. It can double every 2.35 hours in a liquid medium and grows to high density (>31g/L biomass dry weight) in batch culture, nearly double that of Synechococcus sp. PCC 11901, whose high-density growth was recently reported. In addition, UTEX 3222 sinks readily, settling more quickly than other fast-growing strains, suggesting improved de-watering of UTEX 3222 biomass. This settling behavior can be explained in part by larger cell volume. These traits may make UTEX 3222 a compelling choice for photosynthetic bioproduction from CO2. Overall, we find that bio-prospecting in environments with naturally elevated CO2 may uncover novel CO2-metabolizing organisms with unique characteristics.

microbiology↗

bioRxiv2023

Intra-host variation in the spike S1/S2 region of a feline coronavirus type-1 in a cat with persistent infection

Feline coronavirus type 1 (FCoV-1) is widely known for causing feline infectious peritonitis (FIP), a systemic infection that is often fatal, with the virus known as the FIPV biotype. However, subclinical disease also occurs, in which cats may not show signs and intermittently shed the virus, including in feces, possibly for long periods of time. This virus is known as the FECV biotype. Progression of FECV to FIPV has been linked to several genomic changes, however a specific region of the viral spike protein at the interface of the spike S1 and S2 domains has been especially implicated. In this study, we followed a cat (#576) for six years from 2017, at which time FCoV-1 was detected in feces and conjunctival swabs, until 2022, when the animal was euthanized based on a diagnosis of alimentary small cell lymphoma. Over this time period, the cat was clinically diagnosed with inflammatory bowel disease and chronic rhinitis, and cardiac problems were also suspected. Using hybridization capture targeting the spike (S) gene of FCoV followed by next-generation sequencing, we screened 27 clinical samples. We detected FCoV-1 in 4 samples taken in 2017 (intestine and nasal tissue, feces, and conjunctiva), and 3 samples taken in 2022 (feces, and intestinal and heart tissue), but not in fecal samples taken in 2019 and 2020. Next, we focused on the S1/S2 region within S, which contains the furin cleavage site (FCS), a key regulator of viral transmission and pathogenesis. We show that the FCoV-1 variants obtained from feces in 2017 and 2022 were identical, while the ones from conjunctiva (2017), heart (2022), and intestine (2017 and 2022) were distinct. Sequence comparison of all the variants obtained showed that most of the non-synonymous changes in the S1/S2 region occur within the FCS. In the heart, we found two variants that differed by a single nucleotide, resulting in distinct FCS motifs that differ in one amino acid. It is predicted that one of these FCS motifs will down-regulate spike cleavability. The variant from the conjunctiva (2017) had a 6-nucleotide in-frame insertion that resulted in a longer and more exposed S1/S2 loop, which is predicted to be more accessible to the furin protease. Our studies indicate that FCoV-1 can independently persist in the gastrointestinal tract and heart of a cat over a long period of time without evidence of typical FIP signs, with intermittent viral shedding from the gastrointestinal and respiratory tracts.

molecular biology↗

bioRxiv2023

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↗