Biology subjects

Kimmey, S. C.

Publications and source records attributed to Kimmey, S. C..

4 recordsLinked to original sources

bioRxiv2022

Supervised dimensionality reduction for exploration of single-cell data by Hybrid Subset Selection - Linear Discriminant Analysis

Single-cell technologies generate large, high-dimensional datasets encompassing a diversity of omics. Dimensionality reduction enables visualization of data by representing cells in two-dimensional plots that capture the structure and heterogeneity of the original dataset. Visualizations contribute to human understanding of data and are useful for guiding both quantitative and qualitative analysis of cellular relationships. Existing algorithms are typically unsupervised, utilizing only measured features to generate manifolds, disregarding known biological labels such as cell type or experimental timepoint. Here, we repurpose the classification algorithm, linear discriminant analysis (LDA), for supervised dimensionality reduction of single-cell data. LDA identifies linear combinations of predictors that optimally separate a priori classes, enabling users to tailor visualizations to separate specific aspects of cellular heterogeneity. We implement feature selection by hybrid subset selection (HSS) and demonstrate that this flexible, computationally-efficient approach generates non-stochastic, interpretable axes amenable to diverse biological processes, such as differentiation over time and cell cycle. We benchmark HSS-LDA against several popular dimensionality reduction algorithms and illustrate its utility and versatility for exploration of single-cell mass cytometry, transcriptomics and chromatin accessibility data.

bioinformatics↗

bioRxiv2021

mSWI/SNF interacts with the ribosome and its inhibition/mutations alter translation and sensitize to mTOR/PI3K inhibitors

The chromatin remodelers mammalian SWItch/Sucrose Non-Fermentable (mSWI/SNF) subunits are mutated, deleted or amplified in more than 40% of cancers. Understanding their functions in normal cells and the consequences of cancers alterations will lead to path toward new targeted therapies. Canonically, mSWI/SNF complexes regulate the structure of chromatin, however they likely have additional functions which could be relevant in carcinogenesis. Here, we highlight the substantial alteration of mSWI/SNF subunits expression in both the nucleus and cytoplasm in breast cancer cases. We demonstrate mSWI/SNF cytoplasmic localization and interaction with the translation initiation machinery. Short-term inhibition and depletion of specific subunits alter protein synthesis, implicating a direct role for these factors in translation. Inhibition and depletion of specific subunits increase sensitivity to mTOR-PI3K inhibitors, suggesting a potential therapeutic opportunity for diseases harboring mutations in these complexes. Indeed, SMARCA4 pathogenic mutations decrease protein synthesis. Furthermore, taking advantage of the DepMap studies, we demonstrate cancer cells harboring mutations of specific mSWI/SNF subunits exhibit a genetic dependency on translation factors and are particularly sensitive to translation pathway inhibitors. In conclusion, we report an unexpected cytoplasmic role for mSWI/SNF in protein synthesis, suggesting potential new therapeutic opportunities for patients afflicted by cancers demonstrating alterations in its subunits. Statement of significanceThis study establishes direct functions for mSWI/SNF in protein synthesis. mSWI/SNF inhibition, depletion and cancer mutations alter translation and increase sensitivity to translation pathway inhibitors, illustrating the potential for new therapeutic strategies.

cancer biology↗

bioRxiv2019

An integrated multi-omic single cell atlas to redefine human B cell memory

To evaluate the impact of heterogeneous B cells in health and disease, comprehensive profiling is needed at a single cell resolution. We developed a highly-multiplexed screen to quantify the co-expression of 351 surface molecules on low numbers of primary cells. We identified dozens of differentially expressed molecules and aligned their variance with B cell isotype usage, metabolism, biosynthesis activity, and signaling response. Here, we propose a new classification scheme to segregate peripheral blood B cells into ten unique subsets, including a CD45RB+ CD27- early memory population and a CD19hi CD11c+ memory population that is a potent responder to immune activation. Furthermore, we quantify the contributions of antibody isotype and cell surface phenotype to various cell processes and find that phenotype largely drives B cell function. Taken together, these findings provide an extensive profile of human B cell diversity that can serve as a resource for further immunological investigations.

immunology↗

bioRxiv2019

Mapping Lung Cancer Epithelial-Mesenchymal Transition States and Trajectories with Single-Cell Resolution

Elucidating a continuum of epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) states in clinical samples promises new insights in cancer progression and drug response. Using mass cytometry time-course analysis, we resolve lung cancer EMT states through TGF{beta}-treatment and identify through TGF{beta}-withdrawal, an MET state previously unrealized. We demonstrate significant differences between EMT and MET trajectories using a novel computational tool (TRACER) for reconstructing trajectories between cell states. Additionally, we construct a lung cancer reference map of EMT and MET states referred to as the EMT-MET STAte MaP (STAMP). Using a neural net algorithm, we project clinical samples onto the EMT-MET STAMP to characterize their phenotypic profile with single-cell resolution in terms of our in vitro EMT-MET analysis. In summary, we provide a framework that can be extended to phenotypically characterize clinical samples in the context of in vitro studies showing differential EMT-MET traits related to metastasis and drug sensitivity.

systems biology↗