Transcriptomic dynamics in the transition from ground to space are revealed by Virgin Galactic human-tended suborbital spaceflight.
Robert J FerlMingqi ZhouHunter F StricklandNatasha J HavemanJordan B CallahamSirisha BandlaDaniel AmbrizAnna-Lisa PaulPublished in: NPJ microgravity (2023)
The Virgin Galactic Unity 22 mission conducted the first astronaut-manipulated suborbital spaceflight experiment. The experiment examined the operationalization of Kennedy Space Center Fixation Tubes (KFTs) as a generalizable approach to preserving biology at various phases of suborbital flight. The biology chosen for this experiment was Arabidopsis thaliana, ecotype Col-0, because of the plant history of spaceflight experimentation within KFTs and wealth of comparative data from orbital experiments. KFTs were deployed as a wearable device, a leg pouch attached to the astronaut, which proved to be operationally effective during the course of the flight. Data from the inflight samples indicated that the microgravity period of the flight elicited the strongest transcriptomic responses as measured by the number of genes showing differential expression. Genes related to reactive oxygen species and stress, as well as genes associated with orbital spaceflight, were highly represented among the suborbital gene expression profile. In addition, gene families largely unaffected in orbital spaceflight were diversely regulated in suborbital flight, including stress-responsive transcription factors. The human-tended suborbital experiment demonstrated the operational effectiveness of the KFTs in suborbital flight and suggests that rapid transcriptomic responses are a part of the temporal dynamics at the beginning of physiological adaptation to spaceflight.
Keyphrases
- genome wide identification
- genome wide
- transcription factor
- endothelial cells
- arabidopsis thaliana
- reactive oxygen species
- single cell
- electronic health record
- rna seq
- randomized controlled trial
- big data
- systematic review
- genome wide analysis
- gene expression
- cancer therapy
- heart rate
- blood pressure
- deep learning
- data analysis