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Significance Cell size is believed to influence cell growth through limited transport efficiency in larger cells. However, this has not been experimentally investigated due to a lack of noninvasive, high-precision growth quantification methods suitable for measuring large cells. Here, we have engineered large versions of microfluidic mass sensors called suspended microchannel resonators in order to study the growth of single mammalian cells that range 100-fold in mass. Our measurements, which decouple growth effects caused by cell cycle and cell size, revealed that absolute cell size does not impose strict transport or other limitations that would inhibit growth and that cell cycle has a large influence on growth., Cell size is believed to influence cell growth and metabolism. Consistently, several studies have revealed that large cells have lower mass accumulation rates per unit mass (i.e., growth efficiency) than intermediate-sized cells in the same population. Size-dependent growth is commonly attributed to transport limitations, such as increased diffusion timescales and decreased surface-to-volume ratio. However, separating cell size- and cell cycle-dependent growth is challenging. To address this, we monitored growth efficiency of pseudodiploid mouse lymphocytic leukemia cells during normal proliferation and polyploidization. This was enabled by the development of large-channel suspended microchannel resonators that allow us to monitor buoyant mass of single cells ranging from 40 pg (small pseudodiploid cell) to over 4,000 pg, with a resolution ranging from ∼1% to ∼0.05%. We find that cell growth efficiency increases, plateaus, and then decreases as cell cycle proceeds. This growth behavior repeats with every endomitotic cycle as cells grow into polyploidy. Overall, growth efficiency changes 33% throughout the cell cycle. In contrast, increasing cell mass by over 100-fold during polyploidization did not change growth efficiency, indicating exponential growth. Consistently, growth efficiency remained constant when cell cycle was arrested in G2. Thus, cell cycle is a primary determinant of growth efficiency. As growth remains exponential over large size scales, our work finds no evidence for transport limitations that would decrease growth efficiency.

Mutation data reveal the dynamic equilibrium between DNA damage and repair processes in cells and are indispensable to the understanding of age-related diseases, tumor evolution, and the acquisition of drug resistance. However, available genome-wide methods have a limited ability to resolve rare somatic variants and the relationships between these variants. Here, we present lineage sequencing, a new genome sequencing approach that enables somatic event reconstruction by providing quality somatic mutation call sets with resolution as high as the single-cell level in subject lineages. Lineage sequencing entails sampling single cells from a population and sequencing subclonal sample sets derived from these cells such that knowledge of relationships among the cells can be used to jointly call variants across the sample set. This approach integrates data from multiple sequence libraries to support each variant and precisely assigns mutations to lineage segments. We applied lineage sequencing to a human colon cancer cell line with a DNA polymerase epsilon (POLE) proofreading deficiency (HT115) and a human retinal epithelial cell line immortalized by constitutive telomerase expression (RPE1). Cells were cultured under continuous observation to link observed single-cell phenotypes with single-cell mutation data. The high sensitivity, specificity, and resolution of the data provide a unique opportunity for quantitative analysis of variation in mutation rate, spectrum, and correlations among variants. Our data show that mutations arrive with nonuniform probability across sublineages and that DNA lesion dynamics may cause strong correlations between certain mutations.

Cell size is believed to influence cell growth and metabolism. Consistently, several studies have revealed that large cells have lower mass accumulation rates per unit mass (i.e. growth efficiency) than intermediate sized cells in the same population. Size-dependent growth is commonly attributed to transport limitations, such as increased diffusion timescales and decreased surface-to-volume ratio. However, separating cell size and cell cycle dependent growth is challenging. To decouple and quantify cell size and cell cycle dependent growth effects we monitor growth efficiency of freely proliferating and cycling polyploid mouse lymphocytes with high resolution. To achieve this, we develop large-channel suspended microchannel resonators that allow us to monitor mass of single cells ranging from 40 pg (small diploid lymphocyte) to over 4000 pg, with a resolution ranging from ~1% to ~0.05%. We find that mass increases exponentially with respect to time in early cell cycle but transitions to linear dependence during late S and G2 stages. This growth behavior repeats with every endomitotic cycle as cells grow in to polyploidy. Overall, growth efficiency changes 29% due to cell cycle. In contrast, growth efficiency did not change due to cell size over a 100-fold increase in cell mass during polyploidization. Consistently, growth efficiency remained constant when cell cycle was arrested in G2. Thus, cell cycle is a primary determinant of growth efficiency and increasing cell size does not impose transport limitations that decrease growth efficiency in cultured mammalian cells.Significance statementCell size is believed to influence cell behavior through limited transport efficiency in larger cells, which could decrease the growth rate of large cells. However, this has not been experimentally investigated due to a lack of non-invasive, high-precision growth quantification methods suitable for measuring large cells. Here, we have engineered large versions of microfluidic mass sensors called suspended microchannel resonators in order to study the growth of single mammalian cells that range 100-fold in mass. This revealed that the absolute size of a cell does not impose strict transport or other limitations that would inhibit growth. In contrast to cell size, however, cell cycle has a relatively large influence on growth and our measurements allow us to decouple and quantify the growth effects caused by cell cycle and cell size.

Measuring the size of micron-scale particles plays a central role in the biological sciences and in a wide range of industrial processes. A variety of size parameters, such as particle diameter, volume, and mass, can be measured using electrical and optical techniques. Suspended microchannel resonators (SMRs) are microfluidic devices that directly measure particle mass by detecting a shift in resonance frequency as particles flow through a resonating microcantilever beam. While these devices offer high precision for sizing particles by mass, throughput is fundamentally limited by the small dimensions of the resonator and the limited bandwidth with which changes in resonance frequency can be tracked. Here, we introduce two complementary technical advancements that vastly increase the throughput of SMRs. First, we describe a deconvolution-based approach for extracting mass measurements from resonance frequency data, which allows an SMR to accurately measure a particle’s mass approximately 16-fold faster than previously possible, increasing throughput from 120 particles/min to 2000 particles/min for our devices. Second, we describe the design and operation of new devices containing up to 16 SMRs connected fluidically in parallel and operated simultaneously on the same chip, increasing throughput to approximately 6800 particles/min without significantly degrading precision. Finally, we estimate that future systems designed to combine both of these techniques could increase throughput by nearly 200-fold compared to previously described SMR devices, with throughput potentially as high as 24 000 particles/min. We envision that increasing the throughput of SMRs will broaden the range of applications for which mass-based particle sizing can be employed.

Methods to rapidly assess cell growth would be useful for many applications, including drug susceptibility testing, but current technologies have limited sensitivity or throughput. Here we present an approach to precisely and rapidly measure growth rates of many individual cells simultaneously. We flow cells in suspension through a microfluidic channel with 10-12 resonant mass sensors distributed along its length, weighing each cell repeatedly over the 4-20 min it spends in the channel. Because multiple cells traverse the channel at the same time, we obtain growth rates for >60 cells/h with a resolution of 0.2 pg/h for mammalian cells and 0.02 pg/h for bacteria. We measure the growth of single lymphocytic cells, mouse and human T cells, primary human leukemia cells, yeast, Escherichia coli and Enterococcus faecalis. Our system reveals subpopulations of cells with divergent growth kinetics and enables assessment of cellular responses to antibiotics and antimicrobial peptides within minutes., United States. Army Research Office (Grant W911NF-09-D-0001), National Science Foundation (U.S.) (Grant 1129359), National Cancer Institute (U.S.) (Grant U54CA143874), National Cancer Institute (U.S.) (Grant P30-CA14051), National Cancer Institute (U.S.) (Grant R33-CA191143), National Institutes of Health (U.S.) (Grant T32-GM008334), National Institute of General Medical Sciences (U.S.) (Grant T32-GM008334)

Targeted inhibitors of essential oncogenic kinases induce high rates of clinical response but cure few patients due to the persistence of minimal residual disease (MRD). BCR-ABL mutant leukemias are a classic example of this paradigm where patients usually achieve deep remissions followed by near inevitable relapses. Multiple factors have been shown to influence how an individual patient’s leukemic cells will navigate treatment including differentiation state, mutational background, and communication with the microenvironment. Here, we use BCR-ABL-rearranged acute lymphoblastic leukemia (BCR-ABL ALL) to interrogate cell-autonomous features leading to therapeutic resistance using low-input single-cell assays. Specifically, we use a combination of primary samples and PDX models to dissect aberrant developmental hierarchies and monitor leukemic cell transcriptional and biophysical phenotype at pretreatment, MRD, and relapse. Using machine learning, we relate malignant B cells to normal development, allowing us to define leukemic developmental programs and demonstrate that these have consequences for the time to progression as well as the genetic alterations seen at relapse. Further, we determine that there are unique biophysical features tied to leukemic developmental states and that these integrative properties co-evolve with transcriptional state over the course of treatment. Finally, we demonstrate in PDX studies that it may be possible to intercept relapse by targeting specific features of MRD cells. Together, these data suggest that significant developmental hierarchies exist in ALL, tumor subpopulations can be identified directly within MRD, and their phenotypic and molecular characterization can be exploited to therapeutic effect. Citation Format: Peter S. Winter, Andrew Navia, Haley Strouf, Mahnoor Mirza, Jennyfer Galvez-Reyes, Nolawit Mulugeta, Laura Bilal, Nezha Senhaji, Peter Dennis, Catharine S. Leahy, Kay Shigemori, Foster Powers, Alejandro Gupta, Nicholas Calistri, Alex Van Scoyk, Kristen Jones, Huiyun Liu, Kristen E. Stevenson, Robert Kimmerling, Mark Stevens, David M. Weinstock, Scott R. Manalis, Mark A. Murakami, Alex K. Shalek. Aberrant leukemic developmental hierarchies and MRD-specific targeting informed by single-cell biophysical and molecular profiling [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr IA20.

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. Keywords: Single-cell RNA-Seq, Mass, Growth, Serial suspended microchannel resonator, Multi-omics, Single cell, T cell activation, Glioblastoma, GBM, Drug response, Microfluidics, Biophysical properties

Multiple myeloma (MM) has benefited from significant advancements in treatment that have improved outcomes and reduced morbidity. However, the disease remains incurable and is characterized by high rates of drug resistance and relapse. Consequently, methods to select the most efficacious therapy are of great interest. Here we utilize a functional assay to assess the ex vivo drug sensitivity of single multiple myeloma cells based on measuring their mass accumulation rate (MAR). We show that MAR accurately and rapidly defines therapeutic susceptibility across human multiple myeloma cell lines to a gamut of standard-of-care therapies. Finally, we demonstrate that our MAR assay, without the need for extended culture ex vivo, correctly defines the response of nine patients to standard-of-care drugs according to their clinical diagnoses. This data highlights the MAR assay in both research and clinical applications as a promising tool for predicting therapeutic response using clinical samples., Multiple myeloma is characterized by high rates of drug resistance and relapse. Here the authors utilize a functional assay to assess the ex vivo drug sensitivity of single multiple myeloma cells based on measuring the mass accumulation rate of individual cells.

Assays that can determine the response of tumor cells to cancer therapeutics could greatly aid the selection of drug regimens for individual patients. However, the utility of current functional assays is limited, and predictive genetic biomarkers are available for only a small fraction of cancer therapies. We found that the single-cell mass accumulation rate (MAR), profiled over many hours with a suspended microchannel resonator, accurately defined the drug sensitivity or resistance of glioblastoma and B-cell acute lymphocytic leukemia cells. MAR revealed heterogeneity in drug sensitivity not only between different tumors, but also within individual tumors and tumor-derived cell lines. MAR measurement predicted drug response using samples as small as 25 μl of peripheral blood while maintaining cell viability and compatibility with downstream characterization. MAR measurement is a promising approach for directly assaying single-cell therapeutic responses and for identifying cellular subpopulations with phenotypic resistance in heterogeneous tumors., United States. National Institutes of Health (R01 CA170592), United States. National Institutes of Health (R33 CA191143), National Cancer Institute (U.S.) (U54 CA143874), United States. National Institutes of Health (NIH/NIGMS T32 GM008334)

Changes to the biophysical properties of lymphocytes are identified as an adaptive response to acute nutrient stress that occurs before the induction of autophagy., Cytokine regulation of lymphocyte growth and proliferation is essential for matching nutrient consumption with cell state. Here, we examine how cellular biophysical changes that occur immediately after growth factor depletion promote adaptation to reduced nutrient uptake. After growth factor withdrawal, nutrient uptake decreases, leading to apoptosis. Bcl-xL expression prevents cell death, with autophagy facilitating long-term cell survival. However, autophagy induction is slow relative to the reduction of nutrient uptake, suggesting that cells must engage additional adaptive mechanisms to respond initially to growth factor depletion. We describe an acute biophysical response to growth factor withdrawal, characterized by a simultaneous decrease in cell volume and increase in cell density, which occurs before autophagy initiation and is observed in both FL5.12 Bcl-xL cells depleted of IL-3 and primary CD8+ T cells depleted of IL-2 that are differentiating toward memory cells. The response reduces cell surface area to minimize energy expenditure while conserving biomass, suggesting that the biophysical properties of cells can be regulated to promote survival under conditions of nutrient stress.

We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multi-generational lineage tracking under controlled culture conditions. We use this platform to generate whole-transcriptome profiles of primary, activated murine CD8+ T-cell and lymphocytic leukemia cell line lineages. Here we report that both cell types have greater intra- than inter-lineage transcriptional similarity. For CD8+ T-cells, genes with functional annotation relating to lymphocyte differentiation and function—including Granzyme B—are enriched among the genes that demonstrate greater intra-lineage expression level similarity. Analysis of gene expression covariance with matched measurements of time since division reveals cell type-specific transcriptional signatures that correspond with cell cycle progression. We believe that the ability to directly measure the effects of lineage and cell cycle-dependent transcriptional profiles of single cells will be broadly useful to fields where heterogeneous populations of cells display distinct clonal trajectories, including immunology, cancer, and developmental biology., National Institutes of Health (U.S.) (Contract R21AI110787), National Cancer Institute (U.S.). Physical Sciences Oncology Center (U54CA143874), National Cancer Institute (U.S.) (Koch Institute Support (Core) Grant P30-CA14051), National Science Foundation (U.S.). Graduate Research Fellowship, National Institutes of Health (U.S.) (Ruth L. Kirschstein National Research Service Award F32CA1800586), Kinship Foundation. Searle Scholars Program, Beckman Young Investigator Program, National Institutes of Health (U.S.) (New Innovator Award DP2 OD020839)

The physical characteristics of the T cell receptor (TCR)–peptide-major histocompatibility complex (pMHC) interaction are known to play a central role in determining T cell function in the initial stages of the adaptive immune response. State-of-the-art assays can probe the kinetics of this interaction with single-molecular-bond resolution, but this precision typically comes at the cost of low throughput, since the complexity of these measurements largely precludes “scaling up.” Here, we explore the feasibility of detecting specific TCR–pMHC interactions by flowing T cells past immobilized pMHC and measuring the reduction in cell speed due to the mechanical force of the receptor-ligand interaction. To test this new fluidic measurement modality, we fabricated a microfluidic device in which pMHC-coated beads are immobilized in hydrodynamic traps along the length of a serpentine channel. As T cells flow past the immobilized beads, their change in speed is tracked via microscopy. We validated this approach using two model systems: primary CD8+ T cells from an OT-1 TCR transgenic mouse with beads conjugated with H-2Kb:SIINFEKL, and Jurkat T cells with beads conjugated with anti-CD3 and anti-CD28 antibodies.

We present a droplet microfluidic method to extract molecules of interest from a droplet in a rapid and continuous fashion. We accomplish this by first marginalizing functionalized super-paramagnetic beads within the droplet using a magnetic field, and then splitting the droplet into one droplet containing the majority of magnetic beads and one droplet containing the minority fraction. We quantitatively analysed the factors which affect the efficiency of marginalization and droplet splitting to optimize the enrichment of magnetic beads. We first characterized the interplay between the droplet velocity and the strength of the magnetic field and its effect on marginalization. We found that marginalization is optimal at the midline of the magnet and that marginalization is a good predictor of bead enrichment through splitting at low to moderate droplet velocities. Finally, we focused our efforts on manipulating the splitting profile to improve the enrichment provided by asymmetric splitting. We designed asymmetric splitting forks that employ capillary effects to preferentially extract the bead-rich regions of the droplets. Our strategy represents a framework to optimize magnetic bead enrichment methods tailored to the requirements of specific droplet-based applications. We anticipate that our separation technology is well suited for applications in single-cell genomics and proteomics. In particular, our method could be used to separate mRNA bound to poly-dT functionalized magnetic microparticles from single cell lysates to prepare single-cell cDNA libraries.