Reprogramming Macrophages Employing Gene Regulatory Networks

Macrophages are able to coordinate immune responses to inflammatory conditions, tumors and degenerative disorders. Although major polarization regulatory elements have been identified, macrophages in vivo may present more complex transcriptional signatures. To study macrophage polarization comprehensively, gene regulatory networks provide a powerful framework. Gene regulatory network is a good source for the discovery of key regulators for macrophage reprogramming. Combining deep, industry-leading expertise with an innovative Macrophage Therapeutics Development Platform, Creative Biolabs has constructed a logical model of gene regulatory networks to understand how they affect macrophage polarization, and we offer high-quality macrophage reprogramming services.

Gene Regulatory Network Facilitate Macrophage Reprogramming

Macrophages are cells of the innate immune system that play a central role in tissue homeostasis, orchestration of inflammation, and host defense against pathogens. They show plasticity with great phenotypical and functional diversity can have the ability to polarize into two main activated states, classically activated M1 and alternatively activated M2 macrophages, which exert opposing effects to inflammation and possess different metabolic profiles. M1 macrophages are typically generated by proinflammatory factors like interferon (IFN) or Toll-like receptor activation, and secrete inflammatory cytokine and chemokines promoting inflammatory responses. On the other side, M2 polarization is induced by interleukin (IL)-4 and IL-13, and is linked to an anti-inflammatory phenotype. Multiple M2-like subtypes with different gene expression profiles have been described such as M2a, M2b, M2c, and M2d, which are determined by distinct inducing stimuli.

Computational models of gene regulatory networks are good approaches to study how cells integrate several signals driving the cell phenotypic changes, especially for their ability to quantitatively and qualitatively describe a great variety of poorly characterized biological situations. Computational models are used to describe immunological phenomena, to provide a better understanding of aspects of the immune response, and to produce outcomes coherent with available data, thus unraveling basic mechanisms of immunology. In recent years, gene regulatory network is of particular interest in macrophages.

Fig.1 Macrophage reprogramming as a potential target between tumor associated macrophages (TAMs) and CD8-positive (CD8⁺) T cells.^1,2

Employing Gene Regulatory Networks for Macrophage Reprogramming at Creative Biolabs

To obtain a broader overview of the gene regulatory networks that drive macrophage polarization and the heterogeneous single-cell subpopulations in the process, bulk RNA-seq/single-cell RNA-seq and ATAC-seq assays are usually performed to obtain a comprehensive macrophage transcription profile. Our seasoned scientists integrate all the data to construct a logical network model for the gene regulation driving macrophage polarization to the M1, M2a, M2b, and M2c phenotypes.

The transcription profiles of M1-like and M2-like polarized macrophages will be compared. Then, differentially expressed gene analysis and gene set enrichment analysis are conducted. Previous studies have shown that M1-like macrophages activate inflammatory processes, including inflammation, cell death, proinflammatory cytokine expression, and TNF signaling, while M2-like macrophages upregulate metabolic and cellular maintenance processes. Key regulators at the core of the regulatory pathways that control polarization into M1 and M2 states and M2 to M1 repolarization could also be identified. Those regulators are key for macrophage polarization. Our gene regulatory networks provide a powerful framework for macrophage reprogramming.

With an experienced team of in-house macrophage reprogramming experts, Creative Biolabs is proud to share our experience in developing highly customizable solutions for our customers. For more detailed information, please feel free to contact us and further discuss with our scientists.

References

1. Tu, Sheng, et al. "Crosstalk between tumor-associated microglia/macrophages and CD8-positive T cells plays a key role in glioblastoma." Frontiers in Immunology 12 (2021): 650105.
2. 2. Under Open Access license CC BY 4.0, without modification.