Time-course human urine proteomics in space-flight simulation experiments.

Area of Science:

• Space exploration
• Human physiology
• Proteomics

Background:

• Long-term space travel simulations offer insights into human metabolism and salt balance.
• The Mars105 isolation experiment generated detailed proteomics data to understand molecular processes.

Purpose of the Study:

• To analyze temporal changes in urine protein abundance during a 105-day isolation study.
• To investigate the impact of reduced salt consumption on human physiological responses.
• To apply machine learning for personalized analysis of complex proteomics data.

Main Methods:

• Collected weekly urine samples from six volunteers over 105 days under controlled diets.
• Utilized Self-Organizing Maps (SOM) machine learning for time-series protein abundance analysis.
• Applied enrichment and pathway flow analysis for functional annotation of protein regulatory modes.

Main Results:

• Over half of approximately two thousand measured proteins showed significant abundance changes.
• Protein trajectories indicated three distinct phases: early (weeks 1-6), intermediate (weeks 7-11), and late (weeks 12-15).
• Early changes linked to immune/inflammatory responses, intermediate to developmental processes, and late to stress/chemical responses.

Conclusions:

• Protein profiles support alternative salt storage mechanisms.
• Reduced salt intake (approx. 6 g/day) may mitigate early inflammatory responses during isolation.
• SOM machine learning facilitates analysis of complex mass spectrometry-derived proteomics data.