Publications and Posters

Inhibition of the C5aR1 receptor with PMX205 reduces plaque load and gliosis while improving short-term memory in Alzheimer’s Disease (AD) mouse models. Using scRNA-Seq and snRNA-Seq, the authors found that PMX205 treatment enhanced cell growth and repair and decreased the inflammatory gene expression in microglia despite little alteration of the protein levels in reactive cells. The results highlight the attractiveness of a C5aR1 inhibition-based strategy.

Researchers used snRNA-Seq to compare gene expression in early and late-stage Alzheimer’s Disease (AD) and AD in Down Syndrome (DS), bridging the gap between genetic mouse models and sporadic AD. The study revealed a complex interaction between the extra chr21 and the genome, identified shared and unique pathways between late-stage AD and AD in DS, and discovered sex-related expression differences in AD in DS, enhancing our understanding of factors influencing AD progression.

In a multisite study to test the reproducibility of human cortical organoids (hCO) differentiation protocols, scRNA-Seq was used to characterize cross-site similarities and differences. The results showed reproducible key features, such as cell type proportions and structure, including neuroepithelial budding and cortical wall-like organization, as well as some differences that limit the utility of hCO models. Understanding how stem cell states influence early hCO cell types could lead to more reliable hCO protocols for studying neurodevelopmental disorders.

Using snRNA-Seq on chicken embryos, researchers profiled gene expression and chromatin accessibility associated with the chicken ocular lens development. They found three distinct populations representing major cell states (epithelial, intermediate, and fiber cell) and established a continuous trajectory from epithelial to fiber cell differentiation. The study confirmed known pathways and cataract-linked genes while uncovering new factors involved in lens development, homeostasis, and pathology.

Parse and 10X were compared using scRNA-seq on PBMC from 2 healthy donors. Parse demonstrated better data quality with lower multiplets rates but had lower cell recovery. Parse detected 1.2-fold more genes, had better clustering performance, and greater power in distinguishing cell types with specific gene signatures. Parse also excelled in detecting longer transcripts and rare cell types.

Alveolar epithelium regeneration and repair following injury is not completely understood. Evidence suggests that the Hippo-YAP/TAZ pathway is vital for AT2 to AT1 development and dysregulation of this pathway is a key feature of idiopathic pulmonary fibrosis. In a mouse model, AT2 cells lacking YAP/TAZ were injured with bleomycin. scRNA-Seq showed upregulated fibroblast activation markers, increased fibrillar collagen expression, and prolonged inflammation 28 days post-injury, ultimately resulting in lung fibrosis.

Spatial molecular imaging is combined with single-cell sequencing to characterize the tumor microenvironment of human pancreatic cancer. These multi-modal data lead to the generation of the SCOTIA model to better explain the emergence of treatment resistance.

Using an organoid and mouse model of SHH medulloblastoma (MB), scRNA-seq data shows tumor cells expressing the reoccurrence driver OLIG2, are disrupted by CT-179 with minimal off-target toxicity. Post-treatment, tumors up-regulate CDK4 mediating CT-179 resistance. However, combined therapy with a CDK4/6 inhibitor delayed cancer recurrence compared to either single agent.

Using scRNA-seq, researchers developed a scalable screening platform to establish a morphogen atlas of human neural cell fate. By applying 14 morphogen modulators to neural organoids, they identified distinct cellular and structural characteristics of brain regions and critical timing windows.

Using scRNA-seq data of CD4+ T cells from healthy individuals and autoimmune disease patients, clustering was performed through non-negative matrix factorization (NMF). Analysis of publicly available scRNA-seq datasets identified 12 transcriptional gene programs that characterized each autoimmune disease and predicted clinical status accurately.