Gut-Microbiome Interactions: Characterization, Therapeutic Implications and Machine Learning

Abstract

The gut microbiome is vital in maintaining overall health, yet its complexity and dynamic interactions are still not fully understood. This diverse microbial community comprises bacteria, viruses, fungi, and archaea, contributing to metabolism, immune regulation, and disease susceptibility. However, imbalances in the gut microbiome (dysbiosis), have been linked to various diseases, underscoring the importance of understanding microbial interactions within the gut ecosystem. This review explores these interactions, focusing on biochemical and molecular mechanisms that shape microbial behavior and function. Additionally, it examines the therapeutic potential of the gut microbiome, particularly its involvement in disease progression, prevention, and treatment. The role of medicinal plants in influencing gut microbial composition is also discussed, given their potential to support microbiome health. Lastly, it highlights the integration of machine learning in microbiome research, offering new insights into microbial interactions, predictive disease modeling, and personalized medicine. By addressing these key areas, this review aims to deepen our understanding of gut-microbiome dynamics and their implications for human health and disease management.