Computational Molecular Biology 2024, Vol.14, No.5, 211-219 http://bioscipublisher.com/index.php/cmb 215 5.2 Multi-omics in plant-microbe interactions Plants interact with a diverse array of microorganisms in their environment, and these interactions can significantly influence plant health and productivity. Multi-omics approaches have been pivotal in deciphering the complex interactions between plants and their associated microbiomes (Han, 2024). By integrating genomics, transcriptomics, proteomics, and metabolomics data, researchers can gain a comprehensive understanding of the microbial diversity associated with plants and the specific gene-by-gene interactions that occur. This knowledge can be applied to promote healthy plant growth with minimal agrochemical use, enhance nutrient acquisition, and improve stress resilience. The integration of host and microbial omics datasets has led to improved models of crop microbial community structure and function, which are crucial for sustainable agriculture (Kimotho and Maina, 2023; Kumar et al., 2023). 5.3 Multi-omics in food quality and safety The application of multi-omics technologies extends beyond crop breeding and plant-microbe interactions to include food quality and safety. High-throughput omics approaches such as genomics, proteomics, and metabolomics provide detailed insights into the molecular composition of food products, enabling the identification of key factors that influence food quality and safety. For instance, the integration of omics data can help in understanding the metabolic pathways and functional gene patterns that contribute to the nutritional value and safety of food crops. This holistic approach ensures the development of nutrient-sufficient and safe food products that can meet the growing global demand (Pazhamala et al., 2021; Dikobe et al., 2023). 6 Case Studies: Multi-Omics Integration Across Different Fields 6.1 Multi-omics integration in cancer research Multi-omics integration has revolutionized cancer research by providing a comprehensive understanding of the molecular complexity and heterogeneity of tumors. The integration of genomics, transcriptomics, proteomics, and metabolomics has enabled the classification of cancers beyond traditional histopathological methods, leading to the identification of novel biomarkers and therapeutic targets. For instance, multi-omics approaches have facilitated the pan-cancer molecular classification, which offers new therapeutic opportunities for precision medicine (Raufaste-Cazavieille et al., 2022). Tools like IOBR have been developed to decode the tumor microenvironment and signatures, enhancing our understanding of oncogenesis and immunotherapeutic sensitivity (Zeng et al., 2020). These advancements underscore the potential of multi-omics integration in improving cancer diagnosis, prognosis, and treatment. 6.2 Multi-omics in metabolic disorder research In the realm of metabolic disorders, multi-omics integration has provided significant insights into the complex biochemical and physiological interactions underlying these conditions. For example, genome-scale metabolic modeling has been used to identify metabolic footprints of diseases and guide the design of personalized treatments. A notable finding from multi-omics studies is the identification of increased plasma mannose levels as a potential biomarker of early insulin resistance, highlighting the utility of these approaches in metabolic disorder research (Figure 2) (Son et al., 2020). Furthermore, the integration of various omics data, including genomics, transcriptomics, and metabolomics, has been instrumental in understanding the molecular underpinnings of metabolic disorders and developing targeted therapeutic strategies (Pinu et al., 2019; Wörheide et al., 2021). 6.3 Microbiome and host interactions The interplay between the microbiome and host physiology is a burgeoning area of research that has greatly benefited from multi-omics integration. The holo-omic approach, which combines multi-omic data from both hosts and microbes, has been pivotal in untangling the bidirectional interactions between the two. This approach has applications across various fields, including biomedicine, biotechnology, and ecology, and has the potential to open new research avenues and discoveries (Nyholm et al., 2020). Multi-omics strategies have been employed to uncover host-pathogen interactions, providing insights into the genetic, immunologic, and metabolic mechanisms underlying infection and immune response (Khan et al., 2019). These studies underscore the importance of multi-omics integration in advancing our understanding of microbiome-host interactions and their implications for health and disease.
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