Integrative multi-omics approaches to explore immune cell functions: Challenges and opportunities

Abstract

As modern biological sciences evolve from investigation of individual molecules and pathways to growing emphasis on global and systems-based processes, increasing efforts have focused on combining the study of genomics with that of the other omics technologies, including epigenomics, transcriptomics, quantitative proteomics, global analyses of post-translational modifications (PTMs) and metabolomics, to characterize specific biological or pathological processes. In addition, emerging genome-wide functional screening technologies further help researchers identify key regulators of immune functions. Derived from these multi-omics technologies, single cell sequencing analysis on multiple layers offers an overview of intra-tissue or intra-organ immune cell heterogeneity. In this review, we summarize advances in multi-omics tools to explore immune cell functions and applications of these multi-omics approaches in the analysis of clinical immune disorders, aiming to provide an outlook on the potential opportunities and challenges that these technologies pose in future investigation in the field of immunology.

Keywords: Bioinformatics; Cell biology; Immunology.

Graphical abstract

Figure 1

Summary of the key molecules and associated approaches involved in each regulatory layer The process of information flowing from DNA to metabolites includes four parts and is placed in the Targeted molecules section. Typical approaches are divided into four levels according to different targeted molecules. Each group of molecules with similar chemical properties stands for one ‘omic’ layer, which constitutes multi-omics by connecting each other. scDNA-seq, single cell DNA sequencing; ATAC-seq, transposase-accessible chromatin sequencing; ChIP-seq, chromatin immunoprecipitation-sequencing; scRNA-seq, single cell RNA sequencing; snRNA-seq, single-nuclei RNA sequencing; SLAM-seq, thiol (SH)-linked alkylation for the metabolic sequencing of RNA; MS, massspectrometry; CyTOF, cytometry by time-of-flight; scTCR-seq, single cell T-cell receptor sequencing; scBCR-seq, single cell B-cell receptor sequencing; PTMs, post-translational modifications.

Figure 2

Combination of single cell sequencing, bulk sequencing and multi-omics analysis to dissect TME Tumor tissue is mixed with various types of cells including fibroblasts, cancer cells and different immune cells. Bulk sequencing of tumor tissue provides average information of genomics, transcriptomics, proteomics, and metabolomics. By analyzing average information, tumor antigen and immune cell ratio can be gained for developing tumor vaccine, immune-related scores, and immune response biomarkers. Single cell analysis helps identify new types of immune cells and further exploration can be conducted in the same type of immune cells through multi-omics analysis and genome-wide functional screening to identify key regulatory genes, proteins and metabolites, which could potentially become new biomarkers and treatment targets. The tumor tissue can also be replaced by other clinical samples including blood, urine, feces, exhaled air and other tissues in the multi-omics analysis. PTMs, post-translational modifications.

Figure 3

Summary of clinical applications of immune cell-based multi-omics analysis in the context of diseases Immune cells are involved in wide spectrum of diseases, and specific diseases have their own distinct immunological hallmarks. Hypersensitivity diseases can occur in various tissues and organs including the nasal mucosa, trachea and skin, and functions of mast cells are significant in hypersensitivity disease. Infection can be caused by invasion of pathogens, and each pathogen is related to specific immune cells. Different types of tumors, even different subtypes, have featured composition of infiltrating immune cells and immune checkpoint molecules in TME. Dysfunction of immune cells is the key pathogenic factor in autoimmune disease and chronic inflammation-related disease. Thus, analyzing immune cells involved in these diseases through multi-omics approaches can help find new diagnosis biomarker, therapeutic targets and monitoring index in the clinical setting.

Figure 4

The general illustration of how omics technologies are integrated to tackle complex biological problems in immunology (A). Complex biological activities of immune cells: various immune cells have their own states including active and inactive, functional and dysfunctional. Different states can be explained by different trajectories of transcription and translation. Regulative processes and products in intracellular activities can be measured by single cell multi-omics tools and associated data can be acquired in each immune cell. Combination of each single cell multi-omics data can reveal the interactions and communications in the same type immune cells with different states, different types of immune cells, and other types of cells like cancer cells and cancer-related fibroblasts. Microbe-immune interplay can also be decoded by integration of microbiomics and multi-omics data. In addition, degree of communication may depend on the relative distance between cells. (B) Integration of multi-omics approaches and associated data to understand the complexities of the human immune landscape.