The Space Omics and Medical Atlas (SOMA) and international astronaut biobank.

Spaceflight induces molecular, cellular and physiological shifts in astronauts and poses myriad biomedical challenges to the human body, which are becoming increasingly relevant as more humans venture into space1-6. Yet current frameworks for aerospace medicine are nascent and lag far behind advancements in precision medicine on Earth, underscoring the need for rapid development of space medicine databases, tools and protocols. Here we present the Space Omics and Medical Atlas (SOMA), an integrated data and sample repository for clinical, cellular and multi-omic research profiles from a diverse range of missions, including the NASA Twins Study7, JAXA CFE study8,9, SpaceX Inspiration4 crew10-12, Axiom and Polaris. The SOMA resource represents a more than tenfold increase in publicly available human space omics data, with matched samples available from the Cornell Aerospace Medicine Biobank. The Atlas includes extensive molecular and physiological profiles encompassing genomics, epigenomics, transcriptomics, proteomics, metabolomics and microbiome datasets, which reveal some consistent features across missions, including cytokine shifts, telomere elongation and gene expression changes, as well as mission-specific molecular responses and links to orthologous, tissue-specific mouse datasets. Leveraging the datasets, tools and resources in SOMA can help to accelerate precision aerospace medicine, bringing needed health monitoring, risk mitigation and countermeasure data for upcoming lunar, Mars and exploration-class missions.

Genomic analyses of the metastasis-derived prostate cancer cell lines LNCaP, VCaP, and PC3-AR.

BACKGROUND: The lymph node metastasis-derived LNCaP, the bone metastasis-derived PC3 (skull), and VCaP (vertebral) cell lines are widely used as preclinical models of human prostate cancer (CaP) and have been described in more than 19,000 publications. Here, we report on short-read whole-genome sequencing and genomic analyses of LNCaP, VCaP, and PC3 cells stably transduced with WT AR (PC3-AR). METHODS: LNCaP, VCaP, and PC3-AR cell lines were sequenced to an average depth of more than 30-fold using Illumina short-read sequencing. Using various computational methods, we identified and compared the single-nucleotide variants, copy-number profiles, and the structural variants observed in the three cell lines. RESULTS: LNCaP cells are composed of multiple subpopulations, which results in nonintegral copy number states and a high mutational load when the data is analyzed in bulk. All three cell lines contain pathogenic mutations and homozygous deletions in genes involved in DNA mismatch repair, along with deleterious mutations in cell-cycle, Wnt signaling, and other critical cellular processes. PC3-AR cells have a truncating mutation in TP53 and do not express the p53 protein. The VCaP cells contain a homozygous gain-of-function mutation in TP53 (p.R248W) that promotes cancer invasion, metastasis, and progression and has also been observed in prostate adenocarcinomas. In addition, we detect the signatures of chromothripsis of the q arms of chromosome 5 in both PC3-AR and VCaP cells, strengthening the association of TP53 inactivation with chromothripsis reported in other systems. CONCLUSIONS: Our work provides a resource for genetic, genomic, and biological studies employing these commonly-used prostate cancer cell lines.

Genome and clonal hematopoiesis stability contrasts with immune, cfDNA, mitochondrial, and telomere length changes during short duration spaceflight.

Background: The Inspiration4 (I4) mission, the first all-civilian orbital flight mission, investigated the physiological effects of short-duration spaceflight through a multi-omic approach. Despite advances, there remains much to learn about human adaptation to spaceflight's unique challenges, including microgravity, immune system perturbations, and radiation exposure. Methods: To provide a detailed genetics analysis of the mission, we collected dried blood spots pre-, during, and post-flight for DNA extraction. Telomere length was measured by quantitative PCR, while whole genome and cfDNA sequencing provided insight into genomic stability and immune adaptations. A robust bioinformatic pipeline was used for data analysis, including variant calling to assess mutational burden. Result: Telomere elongation occurred during spaceflight and shortened after return to Earth. Cell-free DNA analysis revealed increased immune cell signatures post-flight. No significant clonal hematopoiesis of indeterminate potential (CHIP) or whole-genome instability was observed. The long-term gene expression changes across immune cells suggested cellular adaptations to the space environment persisting months post-flight. Conclusion: Our findings provide valuable insights into the physiological consequences of short-duration spaceflight, with telomere dynamics and immune cell gene expression adapting to spaceflight and persisting after return to Earth. CHIP sequencing data will serve as a reference point for studying the early development of CHIP in astronauts, an understudied phenomenon as previous studies have focused on career astronauts. This study will serve as a reference point for future commercial and non-commercial spaceflight, low Earth orbit (LEO) missions, and deep-space exploration.

Protocol for integrative subtyping of lower-grade gliomas using the SUMO pipeline.

Grouping patients into subtypes with homogeneous molecular features can guide diagnosis and therapeutic interventions. SUMO is a computational pipeline that uses nonnegative matrix factorization of patient-similarity networks to integrate continuous multi-omic datasets for molecular subtyping of a disease. Here, we present a detailed protocol to demonstrate its use in determining subtypes of lower-grade gliomas by integrating gene expression, DNA methylation, and miRNA expression data from the TCGA-LGG cohort. For complete details on the use and execution of this profile, please refer to Sienkiewicz et al. (2022).

Detecting molecular subtypes from multi-omics datasets using SUMO.

We present a data integration framework that uses non-negative matrix factorization of patient-similarity networks to integrate continuous multi-omics datasets for molecular subtyping. It is demonstrated to have the capability to handle missing data without using imputation and to be consistently among the best in detecting subtypes with differential prognosis and enrichment of clinical associations in a large number of cancers. When applying the approach to data from individuals with lower-grade gliomas, we identify a subtype with a significantly worse prognosis. Tumors assigned to this subtype are hypomethylated genome wide with a gain of AP-1 occupancy in demethylated distal enhancers. The tumors are also enriched for somatic chromosome 7 (chr7) gain, chr10 loss, and other molecular events that have been suggested as diagnostic markers for "IDH wild type, with molecular features of glioblastoma" by the cIMPACT-NOW consortium but have yet to be included in the World Health Organization (WHO) guidelines.

Mapping chromatin accessibility and active regulatory elements reveals pathological mechanisms in human gliomas.

Chromatin structure and accessibility, and combinatorial binding of transcription factors to regulatory elements in genomic DNA control transcription. Genetic variations in genes encoding histones, epigenetics-related enzymes or modifiers affect chromatin structure/dynamics and result in alterations in gene expression contributing to cancer development or progression. Gliomas are brain tumors frequently associated with epigenetics-related gene deregulation. We perform whole-genome mapping of chromatin accessibility, histone modifications, DNA methylation patterns and transcriptome analysis simultaneously in multiple tumor samples to unravel epigenetic dysfunctions driving gliomagenesis. Based on the results of the integrative analysis of the acquired profiles, we create an atlas of active enhancers and promoters in benign and malignant gliomas. We explore these elements and intersect with Hi-C data to uncover molecular mechanisms instructing gene expression in gliomas.

Genome Sequence of the Yeast Saprochaete ingens CBS 517.90.

Chromosome-scale genome assembly of the yeast Saprochaete ingens CBS 517.90 was determined by a combination of technologies producing short (HiSeq X; Illumina) and long (MinION; Oxford Nanopore Technologies) reads. The 21.2-Mbp genome sequence has a GC content of 36.9% and codes for 6,475 predicted proteins.

Genome Sequence of Flavor-Producing Yeast Saprochaete suaveolens NRRL Y-17571.

Saprochaete suaveolens is an ascomycetous yeast that produces a range of fruity flavors and fragrances. Here, we report the high-contiguity genome sequence of the ex-holotype strain, NRRL Y-17571 (CBS 152.25). The nuclear genome sequence contains 24.4 Mbp and codes for 8,119 predicted proteins.