Multiscale Modeling and Systems Biology in Microgravity Investigations

Area of Science:

• Space biology
• Computational biology
• Genomics

Background:

• Spaceflight presents unique stressors: radiation, microgravity, isolation.
• These stressors impact biological systems, causing health issues like bone loss and neuroimmune dysfunction.
• Countermeasures developed for spaceflight have terrestrial health benefits.

Purpose of the Study:

• To systematically characterize spaceflight-induced biological changes.
• To describe computational pipelines for analyzing space-derived transcriptomic data.
• To support multiscale modeling for understanding space biology and developing countermeasures.

Main Methods:

• Utilizing omics techniques (transcriptomics, proteomics, metabolomics).
• Employing in silico modeling (molecular dynamics simulations).
• Conducting research in space and using terrestrial analogs (clinostats).
• Analyzing data using computational pipelines for quality control, alignment, and functional analysis.

Main Results:

• Established computational pipelines for processing spaceflight transcriptomic data.
• Facilitated data sharing and integrative analysis via platforms like NASA GeneLab.
• Enabled the construction of multiscale models linking molecular and physiological data.

Conclusions:

• Computational analysis of omics data is crucial for understanding space biology.
• These methods advance the development of countermeasures for spaceflight-induced health effects.
• Integrative analysis of multiomics datasets enhances our comprehension of biological responses to space.