Scaling by shrinking: empowering single-cell 'omics' with microfluidic devices.

Recent advances in cellular profiling have demonstrated substantial heterogeneity in the behaviour of cells once deemed 'identical', challenging fundamental notions of cell 'type' and 'state'. Not surprisingly, these findings have elicited substantial interest in deeply characterizing the diversity, interrelationships and plasticity among cellular phenotypes. To explore these questions, experimental platforms are needed that can extensively and controllably profile many individual cells. Here, microfluidic structures - whether valve-, droplet- or nanowell-based - have an important role because they can facilitate easy capture and processing of single cells and their components, reducing labour and costs relative to conventional plate-based methods while also improving consistency. In this article, we review the current state-of-the-art methodologies with respect to microfluidics for mammalian single-cell 'omics' and discuss challenges and future opportunities.

Optofluidic real-time cell sorter for longitudinal CTC studies in mouse models of cancer.

Circulating tumor cells (CTCs) play a fundamental role in cancer progression. However, in mice, limited blood volume and the rarity of CTCs in the bloodstream preclude longitudinal, in-depth studies of these cells using existing liquid biopsy techniques. Here, we present an optofluidic system that continuously collects fluorescently labeled CTCs from a genetically engineered mouse model (GEMM) for several hours per day over multiple days or weeks. The system is based on a microfluidic cell sorting chip connected serially to an unanesthetized mouse via an implanted arteriovenous shunt. Pneumatically controlled microfluidic valves capture CTCs as they flow through the device, and CTC-depleted blood is returned back to the mouse via the shunt. To demonstrate the utility of our system, we profile CTCs isolated longitudinally from animals over 4 days of treatment with the BET inhibitor JQ1 using single-cell RNA sequencing (scRNA-Seq) and show that our approach eliminates potential biases driven by intermouse heterogeneity that can occur when CTCs are collected across different mice. The CTC isolation and sorting technology presented here provides a research tool to help reveal details of how CTCs evolve over time, allowing studies to credential changes in CTCs as biomarkers of drug response and facilitating future studies to understand the role of CTCs in metastasis.

Chronic metabolic stress drives developmental programs and loss of tissue functions in non-transformed liver that mirror tumor states and stratify survival.

Under chronic stress, cells must balance competing demands between cellular survival and tissue function. In metabolic dysfunction-associated steatotic liver disease (MASLD, formerly NAFLD/NASH), hepatocytes cooperate with structural and immune cells to perform crucial metabolic, synthetic, and detoxification functions despite nutrient imbalances. While prior work has emphasized stress-induced drivers of cell death, the dynamic adaptations of surviving cells and their functional repercussions remain unclear. Namely, we do not know which pathways and programs define cellular responses, what regulatory factors mediate (mal)adaptations, and how this aberrant activity connects to tissue-scale dysfunction and long-term disease outcomes. Here, by applying longitudinal single-cell multi -omics to a mouse model of chronic metabolic stress and extending to human cohorts, we show that stress drives survival-linked tradeoffs and metabolic rewiring, manifesting as shifts towards development-associated states in non-transformed hepatocytes with accompanying decreases in their professional functionality. Diet-induced adaptations occur significantly prior to tumorigenesis but parallel tumorigenesis-induced phenotypes and predict worsened human cancer survival. Through the development of a multi -omic computational gene regulatory inference framework and human in vitro and mouse in vivo genetic perturbations, we validate transcriptional (RELB, SOX4) and metabolic (HMGCS2) mediators that co-regulate and couple the balance between developmental state and hepatocyte functional identity programming. Our work defines cellular features of liver adaptation to chronic stress as well as their links to long-term disease outcomes and cancer hallmarks, unifying diverse axes of cellular dysfunction around core causal mechanisms.

MR1-Restricted MAIT Cells From The Human Lung Mucosal Surface Have Distinct Phenotypic, Functional, and Transcriptomic Features That Are Preserved in HIV Infection.

Mucosal associated invariant T (MAIT) cells are a class of innate-like T cells that utilize a semi-invariant αß T cell receptor to recognize small molecule ligands produced by bacteria and fungi. Despite growing evidence that immune cells at mucosal surfaces are often phenotypically and functionally distinct from those in the peripheral circulation, knowledge about the characteristics of MAIT cells at the lung mucosal surface, the site of exposure to respiratory pathogens, is limited. HIV infection has been shown to have a profound effect on the number and function of MAIT cells in the peripheral blood, but its effect on lung mucosal MAIT cells is unknown. We examined the phenotypic, functional, and transcriptomic features of major histocompatibility complex (MHC) class I-related (MR1)-restricted MAIT cells from the peripheral blood and bronchoalveolar compartments of otherwise healthy individuals with latent Mycobacterium tuberculosis (Mtb) infection who were either HIV uninfected or HIV infected. Peripheral blood MAIT cells consistently co-expressed typical MAIT cell surface markers CD161 and CD26 in HIV-negative individuals, while paired bronchoalveolar MAIT cells displayed heterogenous expression of these markers. Bronchoalveolar MAIT cells produced lower levels of pro-inflammatory cytokine IFN-γ and expressed higher levels of co-inhibitory markers PD-1 and TIM-3 than peripheral MAIT cells. HIV infection resulted in decreased frequencies and pro-inflammatory function of peripheral blood MAIT cells, while in the bronchoalveolar compartment MAIT cell frequency was decreased but phenotype and function were not significantly altered. Single-cell transcriptomic analysis demonstrated greater heterogeneity among bronchoalveolar compared to peripheral blood MAIT cells and suggested a distinct subset in the bronchoalveolar compartment. The transcriptional features of this bronchoalveolar subset were associated with MAIT cell tissue repair functions. In summary, we found previously undescribed phenotypic and transcriptional heterogeneity of bronchoalveolar MAIT cells in HIV-negative people. In HIV infection, we found numeric depletion of MAIT cells in both anatomical compartments but preservation of the novel phenotypic and transcriptional features of bronchoalveolar MAIT cells.

Genomic and transcriptomic correlates of immunotherapy response within the tumor microenvironment of leptomeningeal metastases.

Leptomeningeal disease (LMD) is a devastating complication of solid tumor malignancies, with dire prognosis and no effective systemic treatment options. Over the past decade, the incidence of LMD has steadily increased due to therapeutics that have extended the survival of cancer patients, highlighting the need for new interventions. To examine the efficacy of immune checkpoint inhibitors (ICI) in patients with LMD, we completed two phase II clinical trials. Here, we investigate the cellular and molecular features underpinning observed patient trajectories in these trials by applying single-cell RNA and cell-free DNA profiling to longitudinal cerebrospinal fluid (CSF) draws from enrolled patients. We recover immune and malignant cell types in the CSF, characterize cell behavior changes following ICI, and identify genomic features associated with relevant clinical phenomena. Overall, our study describes the liquid LMD tumor microenvironment prior to and following ICI treatment and demonstrates clinical utility of cell-free and single-cell genomic measurements for LMD research.

Mechanisms of Lymphoma Clearance Induced by High-Dose Alkylating Agents.

The extraordinary activity of high-dose cyclophosphamide against some high-grade lymphomas was described nearly 60 years ago. Here we address mechanisms that mediate cyclophosphamide activity in bona fide human double-hit lymphoma. We show that antibody resistance within the bone marrow (BM) is not present upon early engraftment but develops during lymphoma progression. This resistance required a high tumor:macrophage ratio, was recapitulated in spleen by partial macrophage depletion, and was overcome by multiple, high-dose alkylating agents. Cyclophosphamide induced endoplasmic reticulum (ER) stress in BM-resident lymphoma cells in vivo that resulted in ATF4-mediated paracrine secretion of VEGFA, massive macrophage infiltration, and clearance of alemtuzumab-opsonized cells. BM macrophages isolated after cyclophosphamide treatment had increased phagocytic capacity that was reversed by VEGFA blockade or SYK inhibition. Single-cell RNA sequencing of these macrophages identified a "super-phagocytic" subset that expressed CD36/FCGR4. Together, these findings define a novel mechanism through which high-dose alkylating agents promote macrophage-dependent lymphoma clearance. SIGNIFICANCE: mAbs are effective against only a small subset of cancers. Herein, we recapitulate compartment-specific antibody resistance and define an ER stress-dependent mechanism induced by high-dose alkylating agents that promotes phagocytosis of opsonized tumor cells. This approach induces synergistic effects with mAbs and merits testing across additional tumor types.See related commentary by Duval and De Palma, p. 834.This article is highlighted in the In This Issue feature, p. 813.

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

Mass and growth rate are highly integrative measures of cell physiology not discernable via genomic measurements. Here, we introduce a microfluidic platform enabling direct measurement of single-cell mass and growth rate upstream of highly multiplexed single-cell profiling such as single-cell RNA sequencing. We resolve transcriptional signatures associated with single-cell mass and growth rate in L1210 and FL5.12 cell lines and activated CD8+ T cells. Further, we demonstrate a framework using these linked measurements to characterize biophysical heterogeneity in a patient-derived glioblastoma cell line with and without drug treatment. Our results highlight the value of coupled phenotypic metrics in guiding single-cell genomics.

Multiplexed, targeted profiling of single-cell proteomes and transcriptomes in a single reaction.

We present a scalable, integrated strategy for coupled protein and RNA detection from single cells. Our approach leverages the DNA polymerase activity of reverse transcriptase to simultaneously perform proximity extension assays and complementary DNA synthesis in the same reaction. Using the Fluidigm C1™ system, we profile the transcriptomic and proteomic response of a human breast adenocarcinoma cell line to a chemical perturbation, benchmarking against in situ hybridizations and immunofluorescence staining, as well as recombinant proteins, ERCC Spike-Ins, and population lysate dilutions. Through supervised and unsupervised analyses, we demonstrate synergies enabled by simultaneous measurement of single-cell protein and RNA abundances. Collectively, our generalizable approach highlights the potential for molecular metadata to inform highly-multiplexed single-cell analyses.

Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq.

To explore the distinct genotypic and phenotypic states of melanoma tumors, we applied single-cell RNA sequencing (RNA-seq) to 4645 single cells isolated from 19 patients, profiling malignant, immune, stromal, and endothelial cells. Malignant cells within the same tumor displayed transcriptional heterogeneity associated with the cell cycle, spatial context, and a drug-resistance program. In particular, all tumors harbored malignant cells from two distinct transcriptional cell states, such that tumors characterized by high levels of the MITF transcription factor also contained cells with low MITF and elevated levels of the AXL kinase. Single-cell analyses suggested distinct tumor microenvironmental patterns, including cell-to-cell interactions. Analysis of tumor-infiltrating T cells revealed exhaustion programs, their connection to T cell activation and clonal expansion, and their variability across patients. Overall, we begin to unravel the cellular ecosystem of tumors and how single-cell genomics offers insights with implications for both targeted and immune therapies.