About this Research Topic
The field of Artificial Intelligence (AI) in modelling microbial communities and space stressors is rapidly evolving, driven by advancements in machine learning (ML) and OMICs technologies. The unique environment of space introduces stress factors that lead to distinct molecular changes in microbes, affecting their behavior and interactions with other microbial species and humans. These changes often result in increased virulence compared to terrestrial microbes, posing significant challenges for long-duration space missions.
Current research utilizes Earth-analog systems to simulate space conditions, providing a platform to study these microbial behaviors. Despite these efforts, there remains a gap in understanding the full extent of microbial interactions and their implications for human health in space. Recent studies have begun to address these issues by employing human-derived cell lines and animal models under simulated space conditions, yet comprehensive insights into the predictable impacts of microbes on human health are still needed. As space exploration advances, there is a pressing need for more in-depth investigations into microbial communities to ensure the success and sustainability of life support systems in space.
This Research Topic aims to explore the intersection of AI, ~omics, and microbiome research, with a focus on modelling the molecular and phenotypic signatures of microbial communities under various environmental conditions, including spaceflight and simulated space environments. Our objectives include understanding how AI and ML can be leveraged to predict and model microbial functions such as virulence, biofilm formation, resistance, and their implications for human health both in space and on Earth. By addressing these questions, the research seeks to enhance the feasibility and safety of future space missions and drive innovations in biotechnology and healthcare.
We welcome all accepted articles types addressing, but not limited to, the following themes:
• AI-driven ML models for planetary protection and space medicine, focusing on microbial dynamics and responses to space stressors;
• Biotechnological applications in space, including waste recycling, food production, and space medicine innovations;
• Data integration and interdisciplinary approaches utilizing multi-omics data for a holistic understanding of microbial interactions;
• Ethical considerations and biosecurity concerns related to AI and microbial systems in space missions.
This multidisciplinary Research Topic is hosted in Frontiers in Microbiology, Frontiers in Astronomy and Space Sciences, Frontiers in Space Technologies, Frontiers in Artificial Intelligence and Frontiers in Big Data. Please submit to your preferred journal.
This Research Topic has been coordinated and developed by Dr. Atul Munish Chander.
Current research utilizes Earth-analog systems to simulate space conditions, providing a platform to study these microbial behaviors. Despite these efforts, there remains a gap in understanding the full extent of microbial interactions and their implications for human health in space. Recent studies have begun to address these issues by employing human-derived cell lines and animal models under simulated space conditions, yet comprehensive insights into the predictable impacts of microbes on human health are still needed. As space exploration advances, there is a pressing need for more in-depth investigations into microbial communities to ensure the success and sustainability of life support systems in space.
This Research Topic aims to explore the intersection of AI, ~omics, and microbiome research, with a focus on modelling the molecular and phenotypic signatures of microbial communities under various environmental conditions, including spaceflight and simulated space environments. Our objectives include understanding how AI and ML can be leveraged to predict and model microbial functions such as virulence, biofilm formation, resistance, and their implications for human health both in space and on Earth. By addressing these questions, the research seeks to enhance the feasibility and safety of future space missions and drive innovations in biotechnology and healthcare.
We welcome all accepted articles types addressing, but not limited to, the following themes:
• AI-driven ML models for planetary protection and space medicine, focusing on microbial dynamics and responses to space stressors;
• Biotechnological applications in space, including waste recycling, food production, and space medicine innovations;
• Data integration and interdisciplinary approaches utilizing multi-omics data for a holistic understanding of microbial interactions;
• Ethical considerations and biosecurity concerns related to AI and microbial systems in space missions.
This multidisciplinary Research Topic is hosted in Frontiers in Microbiology, Frontiers in Astronomy and Space Sciences, Frontiers in Space Technologies, Frontiers in Artificial Intelligence and Frontiers in Big Data. Please submit to your preferred journal.
This Research Topic has been coordinated and developed by Dr. Atul Munish Chander.
Keywords: Machine Learning, Space Radiation, Microgravity, Artificial Intelligence, Life Support Systems, Sustainable Space Exploration, Microbial Systems in Space, Space Microbiology
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
