(M1330-03-15) Extracellular Vesicle Transcriptomic Analysis for Understanding Muscle Aging under the Influence of Microgravity

Purpose: Extracellular vesicles (EVs) offer a non-invasive window into muscle cell stress and degeneration. This study leverages spaceflight and microgravity to accelerate aging phenotypes and reveal age-specific EV signatures.Through an interdisciplinary collaboration, cell culture media was collected in the final 24 hours of spaceflight from muscle-on-a-chips platform flown to the Internatonal Space Station (ISS). To validate and extend these findings, we collaborated with NASA’s KSC MSSF and replicated the experiment using two distinct microgravity simulators. We employed a high-throughput microfluidic platform to generate collagen-based muscle organoids derived from patient-specific iPSCs, enabling a scalable, human-relevant system for aging and therapeutic modeling. Our overarching goal is to leverage exosome-based transcriptomic insights to discover circulating biomarkers and therapeutic targets associated with degenerative muscle disease. By using microgravity as a novel model of accelerated aging, this platform holds promise for advancing precision medicine strategies to monitor and intervene in age-related muscle decline.

Methods: Muscle-tissue-chips derived from young active (YA) individuals and older sedentary (OS) individuals were flown to the ISS for 7 days in an autonomous CubeLabTM to study the molecular effects of spaceflight on muscle cells in SpaceX CRS-25 mission. Cell media was collected and  the sample preparation involved preclearing EV-containing media through sequential centrifugation steps to remove cellular debris. EVs were then isolated using ExCy¹ beads, which are functionalized magnetic nanoparticles. The beads were incubated with the media, subjected to pH changes for binding and elution, and washed before resuspending the purified EVs. RNA was extracted from purified EVs using a column-based method. For transcriptomic analysis, RNA sequencing libraries were prepared, sequenced using NovaSeq 6000, and processed using the FREYA pipeline for alignment, differential expression, and enrichment analysis. Statistical analyses were conducted using DESeq2 for transcriptomics (FDR < 0.05, p < 0.05). Research conducted at NASA’s KSC MSSF utilized two commercially available microgravity simulators: RPM and and the Gravite. This equipment simulate microgravity conditions using controlled rotation to minimize the gravity vector at the center of the device. To model the effects of spaceflight, patient-derived muscle organoids from young and old individuals were generated using our high-throughput microfluidic platform, which enables large-scale production of collagen-based 3D muscle cultures². The organoids were continuously exposed to simulated microgravity conditions for seven days, matching the duration of spaceflight exposure in our previous experiment. Conditioned media was collected and subjected to the same preclearing and isolation procedures previously described. To capture this subpopulation mitochondrial-derived vesicles (MDV) we employed Nanopom immunomagetic beads³ functionalized with CD9, CD63 and CD81 tetraspanins and mitochondrial specific antibodies.

Results: EV transcriptomic analysis revealed that spaceflight induces significant molecular changes associated with muscle wasting. Skeletal muscle chips from young  and old  individuals were cultured aboard the ISS, with ground controls for comparison. Across all samples, 8,546 EV-derived transcripts were detected. Differential expression analysis between spaceflight and ground control groups revealed 99 significantly differentially expressed transcripts (adjusted p < 0.05), including 73 downregulated and 26 upregulated genes in SP (Figure 1A).GO:BP enrichment analysis (Figure 1B) showed that downregulated transcripts were associated with proteostasis, gene expression, cell signaling, and tissue integrity, whereas upregulated genes reflected oxidative stress and metabolic adaptation. This suggests that EVs may selectively package transcripts reflecting both stress resilience and functional suppression under spaceflight conditions. A heatmap and Sankey analysis (Figure 1C) revealed distinct EV gene expression profiles in young vs. old groups under spaceflight, with key transcripts mapping to vesicle pathways and disease processes including mitochondrial dysfunction, neurodegeneration, and muscle degeneration. To further explore mitochondrial involvement, EV transcripts were mapped to MitoCarta 3.0. These revealed robust enrichment across mitochondrial compartments, particularly the inner/outer membrane, envelope, and matrix, with specific transcripts associated with MDV pathways (Figure 2A). In the KSC MSSF validation study, we used NanoPom magnetic bead isolation to capture canonical EVs and MDV via antibody targeting. Preeliminary data showed that both RPM and Gravite simulators revealed consistent enrichment of mitochondrial EV transcripts, with the Gravite system showing the strongest MDV signal (Figures 2B, 2C).

Conclusion: This ongoing study presents a novel, out-of-the-box framework that leverages spaceflight and simulated microgravity to model aging in human skeletal muscle. Transcriptomic profiling of these vesicles revealed distinct signatures of spaceflight and aging, most notably, the induction of aging-like molecular programs in young muscle samples, closely mirroring those observed in ground-based aged counterparts. Enrichment and pathway analyses indicate mitochondrial stress responses, telomere regulation, and protein homeostasis as key axes of muscle aging. These findings establish a scalable platform for age-related biomarker discovery and therapeutic screening. The detection of MDVs under both spaceflight and simulated microgravity conditions reveals a stress-adaptive EV pathway with potential as a source of mitochondrial biomarkers. Future work will include functional validation of MDV cargo through proteomic profiling and gain/loss-of-function assays in 3D muscle models. Altogether, this platform opens new translational avenues for vesicle-based diagnostics and personalized therapies targeting muscle atrophy in aging and beyond.

References: 1 Greenberg, Z. F. et al. Peptide-based capture-and-release purification of extracellular vesicles and statistical algorithm enabled quality assessment. bioRxiv (2024-02-08). https://doi.org/10.1101/2024.02.06.578050
2 Ali, S. et al. High-throughput Generation of Collagen Microbeads for 3D Cell Culture and Extracellular Vesicle Production. bioRxiv (2024-11-03). https://doi.org/10.1101/2024.11.03.621748
3 He, N. et al. Nano pom-poms prepared exosomes enable highly specific cancer biomarker detection. Communications Biology 2022 5:1 5 (2022-07-04). https://doi.org/10.1038/s42003-022-03598-0


Figure: Multi-omic profiling of extracellular vesicles (EVs) from young (YA) and old (OS) muscle organoids exposed to spaceflight (SP) reveals transcriptional signatures of aging and mitochondrial stress.
(A) Volcano plot showing differentially expressed transcripts in space-exposed (SP) vs. ground control (GC) samples, highlighting genes associated with mitochondrial function and immune modulation.
(B): Circos plot linking key EV transcripts to enriched pathways, including oxidative stress, metabolism, proteostasis, and telomere regulation.
(C): Heatmap of top EV-associated transcripts clustered by age and stimulation status, linked via Sankey flow to Gene Ontology terms and disease categories. Genes enriched in vesicle-mediated transport, mitochondrial dysfunction, and neurodegenerative disorders suggest candidate biomarkers for age-related muscle decline


Figure: Mitochondrial localization and pathway enrichment analysis of vesicle-associated transcripts from muscleunder simulated microgravity.
(A): Sankey diagram illustrating the sub-organelle localization of significantly enriched transcripts, highlighting specific associations with mitochondrial structures including the outer membrane, inner membrane, envelope, matrix, and mitochondrial-derived vesicles.
(B) bar graph of gravite simulator mitochondrial derived vesicles and CD9, CD81, CD63 derived EVs
(C) bar graph of RPM simulator mitochondrial derived vesicles and CD9, CD81, CD63 derived EVs