scholarly journals Linking single-cell measurements of mass, growth rate, and gene expression

2018 ◽  
Author(s):  
Robert J. Kimmerling ◽  
Sanjay M. Prakadan ◽  
Alejandro J. Gupta ◽  
Nicholas L. Calistri ◽  
Mark M. Stevens ◽  
...  

AbstractWe introduce a microfluidic platform that enables single-cell mass and growth rate measurements upstream of single-cell RNA-sequencing (scRNA-seq) to generate paired single-cell biophysical and transcriptional data sets. Biophysical measurements are collected with a serial suspended microchannel resonator platform (sSMR) that utilizes automated fluidic state switching to load individual cells at fixed intervals, achieving a throughput of 120 cells per hour. Each single-cell is subsequently captured downstream for linked molecular analysis using an automated collection system. From linked measurements of a murine leukemia (L1210) and pro-B cell line (FL5.12), we identify gene expression signatures that correlate significantly with cell mass and growth rate. In particular, we find that both cell lines display a cell-cycle signature that correlates with cell mass, with early and late cell-cycle signatures significantly enriched amongst genes with negative and positive correlations with mass, respectively. FL5.12 cells also show a significant correlation between single-cell growth efficiency and a G1-S transition signature, providing additional transcriptional evidence for a phenomenon previously observed through biophysical measurements alone. Importantly, the throughput and speed of our platform allows for the characterization of phenotypes in dynamic cellular systems. As a proof-of-principle, we apply our system to characterize activated murine CD8+ T cells and uncover two unique features of CD8+ T cells as they become proliferative in response to activation: i) the level of coordination between cell cycle gene expression and cell mass increases, and ii) translation-related gene expression increases and shows a correlation with single-cell growth efficiency. Overall, our approach provides a new means of characterizing the transcriptional mechanisms of normal and dysfunctional cellular mass and growth rate regulation across a range of biological contexts.

2019 ◽  
Vol 200 ◽  
pp. 24-30 ◽  
Author(s):  
Min Sun Shin ◽  
Kristina Yim ◽  
Kevin Moon ◽  
Hong-Jai Park ◽  
Subhasis Mohanty ◽  
...  

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 326-326
Author(s):  
David T. Melnekoff ◽  
Yogita Ghodke-Puranik ◽  
Oliver Van Oekelen ◽  
Adolfo Aleman ◽  
Bhaskar Upadhyaya ◽  
...  

Abstract Background: BCMA CAR-T cell therapy has shown great promise in relapsed/refractory multiple myeloma (RRMM) patients, even though there is unpredictable variability in the duration and depth of response. The mechanisms behind these divergent outcomes and relapse are not well understood and heterogeneity of MM patients at the level of both tumor genomics and tumor microenvironment (TME) likely contributes to this important knowledge gap. To explore this question, we performed a longitudinal high resolution single cell genomic and proteomic analysis of bone marrow (BM) and peripheral blood (PB) samples in MM patients treated with BCMA CAR-T. Methods: Longitudinal comprehensive immune phenotyping of 3.5 million peripheral blood mononuclear cells (PBMC, CD45+CD66b-) from 11 BCMA CAR-T (idecabtagene vicleucel, ide-cel) patients was achieved via mass cytometry (CyTOF) with a panel of 39 markers. In addition, a total of 45,161 bone marrow mononuclear cells (BMMC) were analyzed from 6 patients before initiation of ide-cel therapy and at relapse by unbiased mRNA profiling via single-cell RNA-seq (scRNA-seq) using the GemCode system (10x Genomics). Downstream analysis was performed using the CATALYST and Seurat R packages, respectively. Immune cell populations are reported as % of PBMC and CD138- BMMC respectively, unless noted otherwise. Reported p values correspond to non-parametric tests or paired t test where applicable. Results: We compared baseline immune cell populations in the PB and the TME (BM) with regards to depth of CAR-T response. In PB, good responders (≥VGPR) had a higher proportion of CD8+ T cells (37% in good vs 11% in poor responders (<VGPR), p=0.08) and a lower proportion of CD14+ monocytes (30% vs 61%, p=0.28) and NK cells (2% vs 6%, p=0.08). In the TME, a similar trend was confirmed for CD8+ T cells and CD14+ monocytes. (Fig. 1A) Longitudinal analysis of PBMCs revealed phenotypic changes coinciding with CAR-T expansion; CD14+ monocytes declined from week 0 to week 4 after CAR-T infusion (40% vs 13%, p=0.04), while (non-CAR) CD8+ T cells expanded from week 0 to week 4 (32% vs 43%, p=0.15). The non-CAR CD8+ T cell expansion is characterized by differentiation towards a CD8+ effector-memory phenotype (EM, CCR7-CD45RA-) (73% vs 92% of CD8+ T cells, p=0.005). (Fig. 1B) BM samples at CAR-T relapse showed reversal of this shift: CD14+ monocyte levels remain constant or are slightly elevated, while non-CAR CD8+ T cells decrease at relapse. scRNA-seq of BMMC revealed significant gene expression changes between screening and relapse tumor samples, suggesting tumor-intrinsic factors of CAR-T response. For example, when comparing the pre and post tumor samples of a patient with durable response (PFS 652 days), we observed a significant upregulation of gene expression of pro-inflammatory chemokines (CCL3, CCL4), anti-apoptotic genes (MCL-1, FOSB, JUND), and NF-kB signaling genes (NFKBIA) in post tumor. Gene Set Enrichment Analysis (GSEA) of differentially expressed genes showed significant enrichment for TNFA signaling via NF-kB Hallmark Pathway (p.adj = 0.04). We observed similar statistically significant findings between other screening and relapse samples within our cohort, as well as upon comparison of baseline samples of poor vs good responders. (Fig. 1C, D) Thus, our data suggest that anti-apoptotic gene expression could be one of the tumor intrinsic mechanisms of CAR-T therapy resistance. Notably, we did not observe loss of BCMA expression in any tumor samples. Conclusion: Single cell immune profiling and transcriptomic sequencing highlights changes in the PB, TME and within the tumor, which in concert may influence CAR-T efficacy. Our integrated data analysis indicates general immune activation after CAR-T cell infusion that returns to baseline levels at relapse. Specifically, the expansion of non-CAR cytotoxic CD8+ EM T cells provides a rationale for co-administration of IMiDs to enhance CAR-T efficacy. Significant up-regulation of anti-apoptotic genes at baseline in poor responders, and at relapse in good responders, suggest a novel tumor-mediated escape mechanism. Targeting the MCL-1/BCL-2 axis may augment CAR-T efficacy by sensitizing tumor cells and enhancing the effect of CAR-T killing. We will confirm these findings in a longitudinal cohort of BMMC/PBMC CITE-seq patients (n=23) and will present results at the conference. Figure 1 Figure 1. Disclosures Sebra: Sema4: Current Employment. Parekh: Foundation Medicine Inc: Consultancy; Amgen: Research Funding; PFIZER: Research Funding; CELGENE: Research Funding; Karyopharm Inv: Research Funding.


2011 ◽  
Vol 108 (14) ◽  
pp. 5724-5729 ◽  
Author(s):  
L. Flatz ◽  
R. Roychoudhuri ◽  
M. Honda ◽  
A. Filali-Mouhim ◽  
J.-P. Goulet ◽  
...  

2019 ◽  
Author(s):  
Xili Liu ◽  
Seungeun Oh ◽  
Leonid Peshkin ◽  
Marc W. Kirschner

AbstractThe fine balance of growth and division is a fundamental property of the physiology of cells and one of the least understood. Its study has been thwarted by difficulties in the accurate measurement of cell size and the even greater challenges of measuring growth of a single-cell over time. We address these limitations by demonstrating a new computationally enhanced methodology for Quantitative Phase Microscopy (ceQPM) for adherent cells, using improved image processing algorithms and automated cell tracking software. Accuracy has been improved more than two-fold and this improvement is sufficient to establish the dynamics of cell growth and adherence to simple growth laws. It is also sufficient to reveal unknown features of cell growth previously unmeasurable. With these methodological and analytical improvements, we document a remarkable oscillation in growth rate in several different cell lines, occurring throughout the cell cycle, coupled to cell division or birth, and yet independent of cell cycle progression. We expect that further exploration with this improved tool will provide a better understanding of growth rate regulation in mammalian cells.Significance StatementIt has been a long-standing question in cell growth studies that whether the mass of individual cell grows linearly or exponentially. The two models imply fundamentally distinct mechanisms, and the discrimination of the two requires great measurement accuracy. Here, we develop a new method of computationally enhanced Quantitative Phase Microscopy (ceQPM), which greatly improves the accuracy and throughput of single-cell growth measurement in adherent mammalian cells. The measurements of several cell lines indicate that the growth dynamics of individual cells cannot be explained by either of the simple models but rather present an unanticipated and remarkable oscillatory behavior, suggesting more complex regulation and feedbacks.


2017 ◽  
Author(s):  
Clotilde Cadart ◽  
Sylvain Monnier ◽  
Jacopo Grilli ◽  
Rafaele Attia ◽  
Emmanuel Terriac ◽  
...  

SummaryDespite decades of research, it remains unclear how mammalian cell growth varies with cell size and across the cell division cycle to maintain size control. Answers have been limited by the difficulty of directly measuring growth at the single cell level. Here we report direct measurement of single cell volumes over complete cell division cycles. The volume added across the cell cycle was independent of cell birth size, a size homeostasis behavior called “adder”. Single-cell growth curves revealed that the homeostatic behavior relied on adaptation of G1 duration as well as growth rate modulations. We developed a general mathematical framework that characterizes size homeostasis behaviors. Applying it on datasets ranging from bacteria to mammalian cells revealed that a near-adder is the most common type of size control, but only mammalian cells achieve it using modulation of both cell growth rate and cell-cycle progression.


2019 ◽  
Vol 10 ◽  
Author(s):  
Yannick F. Fuchs ◽  
Virag Sharma ◽  
Anne Eugster ◽  
Gloria Kraus ◽  
Robert Morgenstern ◽  
...  

2019 ◽  
Author(s):  
Suzanne N. Martos ◽  
Michelle R. Campbell ◽  
Oswaldo A. Lozoya ◽  
Brian D. Bennett ◽  
Isabel J.B. Thompson ◽  
...  

SUMMARYTobacco smoke exposure has been found to impact immune response, leukocyte subtypes, DNA methylation, and gene expression in human whole blood. Analysis with single cell technologies will resolve smoking associated (sub)population compositions, gene expression differences, and identification of rare subtypes masked by bulk fraction data. To characterize smoking-related gene expression changes in primary immune cells, we performed single-cell RNA sequencing (scRNAseq) on >45,000 human peripheral blood mononuclear cells (PBMCs) from smokers (n=4) and nonsmokers (n=4). Major cell type population frequencies showed strong correlation between scRNAseq and mass cytometry. Transcriptomes revealed an altered subpopulation of Natural Killer (NK)-like T lymphocytes in smokers, which expressed elevated levels of FCGR3A (gene encoding CD16) compared to other CD8 T cell subpopulations. Relatively rare in nonsmokers (median: 1.8%), the transcriptionally unique subset of CD8 T cells comprised 7.3% of PBMCs in smokers. Mass cytometry confirmed a significant increase (p = 0.03) in the frequency of CD16+ CD8 T cells in smokers. The majority of CD16+ CD8 T cells were CD45RA positive, indicating an effector memory re-expressing CD45RA T cell (TEMRA) phenotype. We expect that cigarette smoke alters CD8 T cell composition by shifting CD8 T cells toward differentiated functional states. Pseudotemporal ordering of CD8 T cell clusters revealed that smokers’ cells were biased toward later pseudotimes, and characterization of established markers in CD8 T cell subsets indicates a higher frequency of terminally differentiated cells in smokers than in nonsmokers, which corresponded with a lower frequency in naïve CD8 T cells. Consistent with an end-stage TEMRA phenotype, FCGR3A-expressing CD8 T cells were inferred as the most differentiated cluster by pseudotime analysis and expressed markers linked to senescence. Examination of differentially expressed genes in other PBMCs uncovered additional senescence-associated genes in CD4 T cells, NKT cells, NK cells, and monocytes. We also observed elevated Tregs, inducers of T cell senescence, in smokers. Taken together, our results suggest smoking-induced, senescence-associated immune cell dysregulation contributes to smoking-mediated pathologies.


2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi101-vi101
Author(s):  
Alexander Lee ◽  
Lu Sun ◽  
Aaron Mochizuki ◽  
Jeremy Reynoso ◽  
Joey Orpilla ◽  
...  

Abstract In a small phase I clinical trial, neoadjuvant anti-PD-1 (neo-aPD1) improved survival in glioblastoma patients (GBM) and was associated with increased interferon-γ-related gene expression and an associated decrease in cell cycle-related gene expression in the tumor. Despite this, neo-aPD1 was not curative. To better understand how neo-aPD1 alters the GBM tumor microenvironment and to discover new therapeutic axes, we used CyTOF and single-cell RNAsequencing to analyze the tumor-infiltrating immune populations of 70 GBM patients, 20 of whom had received neo-aPD1. In patients treated with neo-aPD1 the proportion and number of tumor-infiltrating T cells increased and these T cells had increased expression of the cytokines CCL5 and XCL1, which promote dendritic cell migration. Among the infiltrating T cells was a population of progenitor exhausted CD8+ T cells expressing the genes TCF, SLAM6, CCR7, IL7R, and GZMB. Single-cell TCR analysis revealed that these CD8+ T cells arose from a population of early activated, cytotoxic T cells that had expanded in the peripheral blood and trafficked into the tumor. Within the tumor-infiltrating myeloid cells, we found that neo-aPD1 upregulated genes in the interferon-γ response pathways; namely genes related to T cell trafficking and immune suppression, such as CD274 (PD-L1), TREM2, GPNMB, and IL10, indicating a maladaptive response by some myeloid cells to the immune response triggered by neo-aPD1. Finally, we identified a new migratory and interferon-γ activated tumor-infiltrating conventional dendritic cell population that was increased with neo-aPD1 and that notably expressed XCR1, the receptor for XCL1. Additionally, our results provide future basis to study if modalities that enhance the T cell:DC axis or that inhibit the inhibitory myeloid populations may improve survival in patients with GBM when used in conjunction with neo-aPD1. In sum, we characterized the immune landscape in GBM and how it changes with neo-aPD1 at single cell resolution.


2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A822-A822
Author(s):  
Sri Krishna ◽  
Frank Lowery ◽  
Amy Copeland ◽  
Stephanie Goff ◽  
Grégoire Altan-Bonnet ◽  
...  

BackgroundAdoptive T cell therapy (ACT) utilizing ex vivo-expanded autologous tumor infiltrating lymphocytes (TILs) can result in complete regression of human cancers.1 Successful immunotherapy is influenced by several tumor-intrinsic factors.2 3 Recently, T cell-intrinsic factors have been associated with immunotherapy response in murine and human studies.4 5 Analyses of tumor-reactive TILs have concluded that anti-tumor neoantigen-specific TILs are enriched in subsets defined by the expression of PD-1 or CD39.6 7 Thus, there is a lack of consensus regarding the tumor-reactive TIL subset that is directly responsible for successful immunotherapies such as ICB and ACT. In this study, we attempted to define the fitness landscape of TIL-enriched infusion products to specifically understand its phenotypic impact on human immunotherapy responses.MethodsWe compared the phenotypic differences that could distinguish bulk ACT infusion products (I.P.) administered to patients who had complete response to therapy (complete responders, CRs, N = 24) from those whose disease progressed following ACT (non-responders, NRs, N = 30) by high dimensional single cell protein and RNA analysis of the I.P. We further analyzed the phenotypic states of anti-tumor neoantigen specific TILs from patient I.P (N = 26) by flow cytometry and single cell transcriptomics.ResultsWe identified two CD8+ TIL populations associated with clinical outcomes: a memory-progenitor CD39-negative stem-like TIL (CD39-CD69-) in the I.P. associated with complete cancer regression (overall survival, P < 0.0001, HR = 0.217, 95% CI 0.101 to 0.463) and TIL persistence, and a terminally differentiated CD39-positive TIL (CD39+CD69+) population associated with poor TIL persistence post-treatment. Although the majority (>65%) of neoantigen-reactive TILs in both responders and non-responders to ACT were found in the differentiated CD39+ state, CR infusion products also contained a pool of CD39- stem-like neoantigen-specific TILs (median = 8.8%) that was lacking in NR infusion products (median = 23.6%, P = 1.86 x 10-5). Tumor-reactive stem-like T cells were capable of self-renewal, expansion, and persistence, and mediated superior anti-tumor response in vivo.ConclusionsOur results support the hypothesis that responders to ACT received infusion products containing a pool of stem-like neoantigen-specific TILs that are able to undergo prolific expansion, give rise to differentiated subsets, and mediate long-term tumor control and T cell persistence, in line with recent murine ICB studies mediated by TCF+ progenitor T cells.4 5 Our data also suggest that TIL subsets mediating ACT-response (stem-like CD39-) might be distinct from TIL subsets enriched for anti-tumor-reactivity (terminally differentiated CD39+) in human TIL.6 7AcknowledgementsWe thank Don White for curating the melanoma patient cohort, and J. Panopoulos (Flowjo) for helpful discussions on high-dimensional analysis, and NCI Surgery Branch members for helpful insights and suggestions. S. Krishna acknowledges funding support from NCI Director’s Innovation Award from the National Cancer Institute.Trial RegistrationNAEthics ApprovalThe study was approved by NCI’s IRB ethics board.ReferencesGoff SL, et al. Randomized, prospective evaluation comparing intensity of lymphodepletion before adoptive transfer of tumor-infiltrating lymphocytes for patients with metastatic melanoma. J Clin Oncol 2016;34:2389–2397.Snyder A, et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med 2014;371:2189–2199.McGranahan N, et al. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science 2016;351:1463–1469.Sade-Feldman M, et al. Defining T cell states associated with response to checkpoint immunotherapy in melanoma. Cell 2019;176:404.Miller BC, et al. Subsets of exhausted CD8 T cells differentially mediate tumor control and respond to checkpoint blockade. Nat. Immunol 2019;20:326–336.Simoni Y, et al. Bystander CD8 T cells are abundant and phenotypically distinct in human tumour infiltrates. Nature 2018;557:575–579.Gros A, et al. PD-1 identifies the patient-specific CD8+ tumor-reactive repertoire infiltrating human tumors. J Clin Invest 2014;124:2246–2259.


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