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Sam Kimmey is a PhD candidate in the Bendall Lab. He grew up in Upstate New York and studied Biochemistry as an undergraduate at Stony Brook University.

Stanford Advisors

Research & Scholarship

Current Research and Scholarly Interests

Investigating early human development with single cell proteomics to understand how stem cells make developmental decisions at the molecular level. To accomplish this, protein expression of key regulators is quantified simultaneously in single, differentiating embryonic cells to produce a high-dimensional map of transcription factor expression along a developmental axis. The generated highly multiplexed data is used to infer function and relationships of key regulators.


All Publications

  • An Integrated Multi-omic Single-Cell Atlas of Human B Cell Identity. Immunity Glass, D. R., Tsai, A. G., Oliveria, J. P., Hartmann, F. J., Kimmey, S. C., Calderon, A. A., Borges, L. n., Glass, M. C., Wagar, L. E., Davis, M. M., Bendall, S. C. 2020; 53 (1): 217?32.e5


    B cells are capable of a wide range of effector functions including antibody secretion, antigen presentation, cytokine production, and generation of immunological memory. A consistent strategy for classifying human B cells by using surface molecules is essential to harness this functional diversity for clinical translation. We developed a highly multiplexed screen to quantify the co-expression of 351 surface molecules on millions of human B cells. We identified differentially expressed molecules and aligned their variance with isotype usage, VDJ sequence, metabolic profile, biosynthesis activity, and signaling response. Based on these analyses, we propose a classification scheme to segregate B cells from four lymphoid tissues into twelve unique subsets, including a CD45RB+CD27- early memory population, a class-switched CD39+ tonsil-resident population, and a CD19hiCD11c+ memory population that potently responds to immune activation. This classification framework and underlying datasets provide a resource for further investigations of human B cell identity and function.

    View details for DOI 10.1016/j.immuni.2020.06.013

    View details for PubMedID 32668225

  • TRAIL-induced variation of cell signaling states provides nonheritable resistance to apoptosis. Life science alliance Baskar, R., Fienberg, H. G., Khair, Z., Favaro, P., Kimmey, S., Green, D. R., Nolan, G. P., Plevritis, S., Bendall, S. C. 2019; 2 (6)


    TNFalpha-related apoptosis-inducing ligand (TRAIL), specifically initiates programmed cell death, but often fails to eradicate all cells, making it an ineffective therapy for cancer. This fractional killing is linked to cellular variation that bulk assays cannot capture. Here, we quantify the diversity in cellular signaling responses to TRAIL, linking it to apoptotic frequency across numerous cell systems with single-cell mass cytometry (CyTOF). Although all cells respond to TRAIL, a variable fraction persists without apoptotic progression. This cell-specific behavior is nonheritable where both the TRAIL-induced signaling responses and frequency of apoptotic resistance remain unaffected by prior exposure. The diversity of signaling states upon exposure is correlated to TRAIL resistance. Concomitantly, constricting the variation in signaling response with kinase inhibitors proportionally decreases TRAIL resistance. Simultaneously, TRAIL-induced de novo translation in resistant cells, when blocked by cycloheximide, abrogated all TRAIL resistance. This work highlights how cell signaling diversity, and subsequent translation response, relates to nonheritable fractional escape from TRAIL-induced apoptosis. This refined view of TRAIL resistance provides new avenues to study death ligands in general.

    View details for DOI 10.26508/lsa.201900554

    View details for PubMedID 31704709

  • Parallel analysis of tri-molecular biosynthesis with cell identity and function in single cells. Nature communications Kimmey, S. C., Borges, L., Baskar, R., Bendall, S. C. 2019; 10 (1): 1185


    Cellular products derived from the activity of DNA, RNA, and protein synthesis collectively control cell identity and function. Yet there is little information on how these three biosynthesis activities are coordinated during transient and sparse cellular processes, such as activation and differentiation. Here, we describe Simultaneous Overview of tri-Molecule Biosynthesis (SOM3B), a molecular labeling and simultaneous detection strategy to quantify DNA, RNA, and protein synthesis in individual cells. Comprehensive interrogation of biosynthesis activities during transient cell states, such as progression through cell cycle or cellular differentiation, is achieved by partnering SOM3B with parallel quantification of select biomolecules with conjugated antibody reagents. Here, we investigate differential de novo DNA, RNA, and protein synthesis dynamics in transformed human cell lines, primary activated human immune cells, and across the healthy human hematopoietic continuum, all at a single-cell resolution.

    View details for PubMedID 30862852

  • Mapping lung cancer epithelial-mesenchymal transition states and trajectories with single-cell resolution. Nature communications Karacosta, L. G., Anchang, B. n., Ignatiadis, N. n., Kimmey, S. C., Benson, J. A., Shrager, J. B., Tibshirani, R. n., Bendall, S. C., Plevritis, S. K. 2019; 10 (1): 5587


    Elucidating the spectrum of epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) states in clinical samples promises insights on cancer progression and drug resistance. Using mass cytometry time-course analysis, we resolve lung cancer EMT states through TGF?-treatment and identify, through TGF?-withdrawal, a distinct MET state. We demonstrate significant differences between EMT and MET trajectories using a computational tool (TRACER) for reconstructing trajectories between cell states. In addition, we construct a lung cancer reference map of EMT and MET states referred to as the EMT-MET PHENOtypic STAte MaP (PHENOSTAMP). Using a neural net algorithm, we project clinical samples onto the EMT-MET PHENOSTAMP to characterize their phenotypic profile with single-cell resolution in terms of our in vitro EMT-MET analysis. In summary, we provide a framework to phenotypically characterize clinical samples in the context of in vitro EMT-MET findings which could help assess clinical relevance of EMT in cancer in future studies.

    View details for DOI 10.1038/s41467-019-13441-6

    View details for PubMedID 31811131

  • FGF and canonical Wnt signaling cooperate to induce paraxial mesoderm from tailbud neuromesodermal progenitors through regulation of a two-step EMT. Development Goto, H., Kimmey, S. C., Row, R. H., Matus, D. Q., Martin, B. L. 2017


    Mesoderm induction begins during gastrulation. Recent evidence from several vertebrate species indicates that mesoderm induction continues after gastrulation in neuromesodermal progenitors (NMPs) within the posteriormost embryonic structure, the tailbud. It is unclear to what extent the molecular mechanisms of mesoderm induction are conserved between gastrula and post-gastrula stages of development. Fibroblast growth factor (FGF) signaling is required for mesoderm induction during gastrulation through positive transcriptional regulation of the T-box transcription factor brachyury We find in zebrafish that FGF is continuously required for paraxial mesoderm (PM) induction in post-gastrula NMPs. FGF signaling represses the NMP markers brachyury (ntla) and sox2 through regulation of tbx16 and msgn1, thereby committing cells to a PM fate. FGF-mediated PM induction in NMPs functions in tight coordination with canonical Wnt signaling during the epithelial to mesenchymal transition (EMT) from NMP to mesodermal progenitor. Wnt signaling initiates EMT, whereas FGF signaling terminates this event. Our results indicate that germ layer induction in the zebrafish tailbud is not a simple continuation of gastrulation events.

    View details for DOI 10.1242/dev.143578

    View details for PubMedID 28242612

    View details for PubMedCentralID PMC5399664

  • High-throughput precision measurement of subcellular localization in single cells. Cytometry. Part A : the journal of the International Society for Analytical Cytology Burns, T. J., Frei, A. P., Gherardini, P. F., Bava, F. A., Batchelder, J. E., Yoshiyasu, Y., Yu, J. M., Groziak, A. R., Kimmey, S. C., Gonzalez, V. D., Fantl, W. J., Nolan, G. P. 2017; 91 (2): 180-189


    To quantify visual and spatial information in single cells with a throughput of thousands of cells per second, we developed Subcellular Localization Assay (SLA). This adaptation of Proximity Ligation Assay expands the capabilities of flow cytometry to include data relating to localization of proteins to and within organelles. We used SLA to detect the nuclear import of transcription factors across cell subsets in complex samples. We further measured intranuclear re-localization of target proteins across the cell cycle and upon DNA damage induction. SLA combines multiple single-cell methods to bring about a new dimension of inquiry and analysis in complex cell populations. 2017 International Society for Advancement of Cytometry.

    View details for DOI 10.1002/cyto.a.23054

    View details for PubMedID 28094900

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