What is Metabolomics and Single Cell RNA Sequencing

Bulk RNA-seq operates under the presumption of sample homogeneity, applying a comprehensive sequencing technique to all mRNA within the sample. It is widely used to investigate transcriptome variations among distinct tissues/cells or other sample types. Yet, this method yields an average or representative gene expression level of a specific tissue/cell assemblage, often obscuring information on cell-specific individuality due to the innate heterogeneity among single cells within the same tissue. This approach may cause the oversight of critical data.

However, with the rapid advancements in sequencing technology, single-cell sequencing has emerged, owing its swift rise to its comprehensive display of cell heterogeneity. As its name suggests, the single-cell sequencing technology refers to a novel method of conducting transcriptome sequencing at the level of individual cells. In addition to fully illustrating cellular heterogeneity within samples, it also provides insights into the developmental trajectory of specific cells and explicates how intercellular interactions mediate corresponding molecular mechanisms.

Moreover, single-cell sequencing technology allows for the identification of a substantial number of differentially expressed genes at the cellular level or key genes at developmental nodes. It thus aids in interrogating their regulatory metabolic pathways, providing considerable avenues for subsequent research.

Metabolomics, a paramount integral field of systemic biology, has swiftly emerged as a fervently researched hotspot in the genomics sphere, following in the footsteps of genomics, transcriptomics, and proteomics. While genomics and proteomics elucidate life's dynamics from the genetic and protein perspectives respectively, it's manifest that numerous cellular activities are intimately entwined with metabolites, such as cellular signaling and energy transmission, which are indeed governed by these metabolites. Metabolomics, hence, commits to the scrutiny of the collective metabolites within a cell at a given moment, thereby vividly portraying events already transpired in the organism. Key methodologies in metabonomics include gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and nuclear magnetic resonance (NMR) for both qualitative and quantitative analysis of small molecule metabolites in the sample (metabolites with molecular weight within 1000Da).

Why to Integrated Analyze Metabolomics and Single Cell RNA Sequencing

Apart from the heterogeneity in gene expression, different cell types or states also display considerable metabolic variability. Metabolomics at the single-cell level is an area currently under development and exploration. Single-cell transcriptomics can elucidate differences in gene expression at both the cellular population and individual cell levels. This approach frequently culminates in the analysis of metabolic pathways. By integrating single-cell transcriptomics and Metabolomics, the identity of a cell and the environment it resides in can be described more comprehensively, thereby linking the two 'omics' and two levels of analysis. Therefore, the joint analysis based on single-cell sequencing and metabolomics can serve as an effective research strategy for characterizing the transcriptional landscape and metabolic regulation network within biological organisms at the single-cell level.

How to Integrated Analysis of Metabolomics and Single Cell RNA Sequencing

Building on transcriptome and metabolome correlation analysis, the integration of single-cell transcriptomics and metabolomics can likewise be linked via metabolic pathways, thereby interpreting cell-type-specific metabolic routes. With the aid of metabolomic technology, distinct metabolomic expression profiles within samples can be constructed. This elucidates how differential metabolites within the same sample mediate the onset and progression of a particular disease or a specific molecular mechanism.

Single-cell sequencing technology, on the other hand, unveils the expression patterns within individual cells. It enables the dissection of key factors or points in the progression of a disease or a molecular mechanism issue at the cellular level, primarily emphasizing cellular heterogeneity and gene variations cell-by-cell.

By co-analyzing single-cell and metabolomic data, the pathways of interest could be validated at disparate levels. Moreover, metabolomics findings could also complement single-cell clustering results. The combination of single-cell and metabolomic analysis might facilitate the screening of potential biological markers.

The integrated analysis of metabolomics and single-cell RNA sequencing typically falls into three categories:

1) Identification of key metabolic pathways in specific cellular subtypes through single-cell transcriptomics, with verification conducted via metabolomic techniques to detect changes in relevant metabolites.

2) Utilization of metabolomics to screen for potential biomarkers, thus allowing for a quick pinpointing of metabolic pathways of interest, related genes, and corresponding cell types within single-cell transcription profiles to narrow down the research scope.

3) Investigation of how metabolic profiles respond across different cellular populations and examination of metabolic heterogeneity. This approach aids in the classification of cells and elucidates disease mechanisms at the cellular level.

Integrative Approach of Metabolomics and Single-Cell Transcriptomics

Case of Integrated Analysis of Metabolomics and Single Cell RNA Sequencing

Multiomics analyses reveal a critical role of selenium in controlling T cell differentiation in Crohn's disease

Journal: Immunity (IF=43.474)
Published: August 2021
Sample Type: CD45+ Mucosal Immune Cells
Method: Single-cell transcriptomics and untargeted metabolomics

Inflammatory Bowel Disease (IBD), principally characterized by Crohn's Disease (CD) and Ulcerative Colitis (UC), involves significant immunological implications. While the role of the immune response is intrinsic to the pathogenesis of both types of IBD, a clear understanding of the dysregulated immune microenvironment in the colon and consequently the underpinning mechanisms remain elusive.

In this context, the authors engage in a comprehensive multi-omics study to assess the immune characteristics and the metabolic microenvironment of individuals diagnosed with untreated IBD. They identify a role for changes in CD-specific metabolites, especially a reduction in selenium, in substantially driving Th1 cell differentiation, which features prominently in CD pathogenesis.

Interestingly, selenium supplementation appears to ameliorate symptoms and the disease onset of CD, promoting Th1 cell differentiation. This effect is thought to be mediated by selenoprotein W (SELW), which facilitates the scavenging of reactive oxygen species. This mechanism involves SELW recruiting an E3 ubiquitin ligase, protein with ankyrin repeats 21 (ANKRD21), to enhance purine salvage pathway, whilst suppressing tumour metabolism. This interaction contributes to the stabilization of serine hydroxymethyltransferase 2.

This work underscores the significance of selenium as a vital modulator of T cell responses and a potential therapeutic target for steatorrhea, hence contributing to our understanding of metabolic interventions in IBD.

Obesity shapes metabolism in the tumor microenvironment to suppress anti-tumor immunity

Journal: Cell (IF=66.85)
Published: December 2020
Sample Types: Plasma, GFP+MC38 tumor cells, tumor interstitial fluid (TIF)
Research Methods: Single-cell transcriptomics, Metabolomics, proteomics

Obesity is a major risk factor for cancer, yet it remains unclear how systemic metabolic differences alter the tumor microenvironment (TME) and impact anti-tumor immunity. In this study, the authors demonstrate that diet-induced obesity impairs the functionality of CD8+ T cells within the TME in mice, accelerating tumor growth. They generated a single-cell resolution metabolic atlas of the TME and detailed how it changes with diet-induced obesity. The authors reveal distinct metabolic adaptations in response to obesity between tumor cells and CD8+ T cells. Tumor cells increased lipid uptake with a high-fat diet (HFD), while tumor-infiltrating CD8+ T cells did not. These differential adaptations led to alterations in fatty acid distribution within HFD tumors, compromising the infiltration and functionality of CD8+ T cells. In obese mice, blocking the metabolic reprogramming of tumor cells can enhance anti-tumor immune capacity. The analysis of human cancers revealed similar transcriptional alterations in CD8+ T cell markers, suggesting that metabolic interventions may be utilized to improve cancer immunotherapies.

Integrated analysis of plasma and single immune cells uncovers metabolic changes in individuals with COVID-19

Journal: Nature Biotechnology (IF=68.164)
Published: September 2022
Sample Types: Plasma and peripheral blood mononuclear cells (PBMC)
Research Methods: Single-cell transcriptomics, Metabolomics

A comprehensive understanding of the metabolic changes in immune cells during SARS-CoV-2 infection could aid in elucidating the wide-ranging clinical manifestations in COVID-19 patients. Herein, the authors report metabolic alterations associated with the peripheral immune response in 198 COVID-19 patients, as analyzed through an integrated investigation of plasma metabolites and protein levels in sequential blood draws collected in the first week following clinical diagnosis, coupled with single-cell multi-omics analysis. The authors documented the emergence of rare but metabolically distinct T cell subgroups, and found that an increase in disease severity was associated with monocyte differentiation into two metabolically different subpopulations. This integrative analysis unveils robust interrelations between plasma metabolites and cell-type-specific metabolic reprogramming networks that are linked to disease severity and can predict survival.

References

1. Huang LJ, Mao XT, Li YY, et al. Multiomics analyses reveal a critical role of selenium in controlling T cell differentiation in Crohn's disease. Immunity. 2021 Aug 10;54(8):1728-1744.e7.
2. Ringel AE, Drijvers JM, Baker GJ, et al. Obesity Shapes Metabolism in the Tumor Microenvironment to Suppress Anti-Tumor Immunity. Cell. 2020 Dec 23;183(7):1848-1866.e26.
3. Lee JW, Su Y, Baloni P, et al. Integrated analysis of plasma and single immune cells uncovers metabolic changes in individuals with COVID-19. Nat Biotechnol. 2022 Jan;40(1):110-120.