Multiomic Analysis of the Hepatic Fibrotic Niche to Define New Therapeutic Targets for Liver Scarring

据估计，全球每年有200万人死于肝病。晚期肝病的一个特征是肝瘢痕（纤维化），这与临床预后差有关。目前还没有有效的抗纤维化治疗方法，因此迫切需要在这一领域开发新的治疗策略。Ramachandran实验室最近的工作使用单细胞RNA测序（scRNA-seq）鉴定了肝脏中存在于特定空间环境中的致病性细胞亚群，称为纤维化生态位。这种纤维化生态位的发现提供了一个机会，可以在不干扰非病变区域的情况下靶向组织的更多病变区域，因此这种基于精确医学的策略可能用于肝纤维化患者。然而，纤维化生态位内的细胞组成和细胞间相互作用尚未被评估。为了研究这一点，空间转录组学可以用来确定哪些转录本在疤痕的特定区域富集，随后在治疗策略方面允许更有针对性的方法。在这个项目中，我们将利用空间转录组学来确定患病人类肝脏中纤维化生态位的组成。我们的目标是整合空间转录组学和单细胞RNA测序数据，这样我们就可以询问参与纤维化过程的细胞-细胞相互作用。此外，我们的目标是研究小鼠模型中的生态位，以确定人类和小鼠之间的任何保守的促纤维化途径，使我们能够确定潜在的治疗靶点。空间转录组学方法将使用10X基因组学可视化平台。scRNA-seq数据和空间转录组数据的分析将使用R和Python语言中的各种软件包，包括Seurat、Harmony、Giotto、BayesSpace和scanpy。将对该生态位进行多组学分析，以比较人类和小鼠肝纤维化，从而确定保守的细胞类型和途径。感兴趣的分子将使用遗传方法和体内小鼠模型以及体外细胞培养模型的组合进行操作。

Liver disease accounts for an estimated 2 million deaths per year globally. One feature of advanced liver disease is liver scarring (fibrosis), which is associated with poor clinical outcome. There are, at present, no effective anti-fibrotic therapies thus highlighting an important need to develop novel therapeutic strategies in this area. Recent work in the Ramachandran lab has used single-cell RNA sequencing (scRNA-seq) to identify a pathogenic subpopulation of cells in the liver which reside in a distinct spatial environment, named the fibrotic niche. Discovery of this fibrotic niche provides an opportunity to target the more diseased areas of tissue without perturbing non-diseased regions, and as such this precision-medicine based strategy may be used for patients with liver fibrosis. However, the cellular composition and cell-to-cell interactions within the fibrotic niche have not yet been assessed. To investigate this, spatial transcriptomics can be used to identify which transcripts are enriched within specific areas of scarring, subsequently allowing for a more targeted approach in terms of therapeutic strategies. Within this project, we will utilise spatial transcriptomics to determine the composition of the fibrotic niche within diseased human liver. We aim to integrate spatial transcriptomic and single-cell RNA sequencing data, such that we can interrogate the cell-cell interactions involved in the fibrotic process. Furthermore, we aim to investigate the niche in mouse models to determine any conserved pro-fibrogenic pathways between human and mouse, allowing us to identify potential therapeutic targets. Spatial transcriptomics approach will use the 10X genomics visium platform. Analysis of scRNA-seq data and spatial transcriptomic data will be done using a variety of packages in the R and Python languages including Seurat, Harmony, Giotto, BayesSpace and scanpy. Multiomic analysis of the niche will be performed to compare human and mouse liver fibrosis, such that conserved cell types and pathways can be defined. Molecules of interest will be manipulated using a combination of genetic approaches and in vivo mouse models and in vitro cell culture models.