Identifying niche‐mediated regulatory factors of stem cell phenotypic state: a systems biology approach

Abstract

Understanding how the cellular niche controls the stem cell phenotype is often hampered due to the complexity of variegated niche composition, its dynamics, and nonlinear stem cell–niche interactions. Here, we propose a systems biology view that considers stem cell–niche interactions as a many‐body problem amenable to simplification by the concept of mean field approximation. This enables approximation of the niche effect on stem cells as a constant field that induces sustained activation/inhibition of specific stem cell signaling pathways in all stem cells within heterogeneous populations exhibiting the same phenotype (niche determinants). This view offers a new basis for the development of single cell‐based computational approaches for identifying niche determinants, which has potential applications in regenerative medicine and tissue engineering.

Computational modelling of stem cell–niche interactions facilitates discovery of strategies to enhance tissue regeneration and counteract ageing

“…NicheHotSpotter is a general tool that can be readily applied to delineate paths towards stem cell rejuvenation in other tissues. In this regard, the tool has already been successfully applied to neural [ 2 , 10 ], embryonic, haematopoietic and hair‐follicle stem cells, as well as oligodendrocyte progenitor cells [ 9 ]. We also note that NicheHotSpotter's potential scope of use can be extended to other tissues as it only requires gene expression data in two conditions.…”

“…The stem cells of an adult organism are located in special microenvironments that enable them to effectively respond to the tissue renewal needs in case of injury and disease. These microenvironments, also known as stem cell niches, provide for the maintenance of the stem cell pool and for the control of the cellular fates during regeneration of an organ or tissue [ 1 , 2 ]. The stem cell niche interacts with its stem cells through signalling cues that change depending on the regeneration status.…”

Integrative Computational Network Analysis Reveals Site-Specific Mediators of Inflammation in Alzheimer's Disease

“…This is because, although we considered inflammation to be one of the predominant cause of sustained signaling activities, our computational approach infers constantly activated/inhibited signaling pathways irrespective of whether these pathways are induced by inflammation or any other cellular processes. Although this aspect could represent a limitation of our approach, it rather demonstrates that it can be applied in cases where sustained signaling pathways need to be identified (Ravichandran et al, 2016 ; Ravichandran and Del Sol, 2017 ). Further, certain classical inflammatory mediators, such as FAS- and IL6-related pathways, were not identified.…”

“…Consequently, certain signaling pathways that were upregulated under normal homeostatic conditions can get downregulated or inhibited under chronic inflammatory conditions, and certain pathways originally inhibited or downregulated under normal conditions can be activated due to chronic inflammation (Figure 1A ). In order to infer such constantly activated/inhibited signaling pathways/subnetworks possibly mediated by chronic inflammatory conditions in AD, we adapted a method that we originally developed to identify constantly activated/inhibited signaling subnetworks due to sustained effect of the niche or microenvironment on stem cell state (Ravichandran et al, 2016 ; Ravichandran and Del Sol, 2017 ). Briefly, the methodology combines gene expression data with signaling interactome, and identifies sparsest signaling sub-networks by connecting the receptors/ligands with the transcription factors (TFs) that best explain the differential gene expression pattern.…”