Species-Independent Attraction to Biofilms through Electrical Signaling.

Bacteria residing within biofilm communities can coordinate their behavior through cell-to-cell signaling. However, it remains unclear if these signals can also influence the behavior of distant cells that are not part of the community. Using a microfluidic approach, we find that potassium ion channel-mediated electrical signaling generated by a Bacillus subtilis biofilm can attract distant cells. Integration of experiments and mathematical modeling indicates that extracellular potassium emitted from the biofilm alters the membrane potential of distant cells, thereby directing their motility. This electrically mediated attraction appears to be a generic mechanism that enables cross-species interactions, as Pseudomonas aeruginosa cells also become attracted to the electrical signal released by the B. subtilis biofilm. Cells within a biofilm community can thus not only coordinate their own behavior but also influence the behavior of diverse bacteria at a distance through long-range electrical signaling. PAPERCLIP.

Reverse Engineering Human Pathophysiology with Organs-on-Chips.

While studies of cultured cells have led to new insights into biological control, greater understanding of human pathophysiology requires the development of experimental systems that permit analysis of intercellular communications and tissue-tissue interactions in a more relevant organ context. Human organs-on-chips offer a potentially powerful new approach to confront this long-standing problem.

Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.

Cells, the basic units of biological structure and function, vary broadly in type and state. Single-cell genomics can characterize cell identity and function, but limitations of ease and scale have prevented its broad application. Here we describe Drop-seq, a strategy for quickly profiling thousands of individual cells by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell's RNAs, and sequencing them all together. Drop-seq analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts' cell of origin. We analyzed transcriptomes from 44,808 mouse retinal cells and identified 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes. Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution. VIDEO ABSTRACT.

Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells.

It has long been the dream of biologists to map gene expression at the single-cell level. With such data one might track heterogeneous cell sub-populations, and infer regulatory relationships between genes and pathways. Recently, RNA sequencing has achieved single-cell resolution. What is limiting is an effective way to routinely isolate and process large numbers of individual cells for quantitative in-depth sequencing. We have developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing. The method shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays. We analyzed mouse embryonic stem cells, revealing in detail the population structure and the heterogeneous onset of differentiation after leukemia inhibitory factor (LIF) withdrawal. The reproducibility of these high-throughput single-cell data allowed us to deconstruct cell populations and infer gene expression relationships. VIDEO ABSTRACT.

Noise facilitates transcriptional control under dynamic inputs.

Cells must respond sensitively to time-varying inputs in complex signaling environments. To understand how signaling networks process dynamic inputs into gene expression outputs and the role of noise in cellular information processing, we studied the immune pathway NF-κB under periodic cytokine inputs using microfluidic single-cell measurements and stochastic modeling. We find that NF-κB dynamics in fibroblasts synchronize with oscillating TNF signal and become entrained, leading to significantly increased NF-κB oscillation amplitude and mRNA output compared to non-entrained response. Simulations show that intrinsic biochemical noise in individual cells improves NF-κB oscillation and entrainment, whereas cell-to-cell variability in NF-κB natural frequency creates population robustness, together enabling entrainment over a wider range of dynamic inputs. This wide range is confirmed by experiments where entrained cells were measured under all input periods. These results indicate that synergy between oscillation and noise allows cells to achieve efficient gene expression in dynamically changing signaling environments.

Single-cell quantification of ribosome occupancy in early mouse development.

Translation regulation is critical for early mammalian embryonic development1. However, previous studies had been restricted to bulk measurements2, precluding precise determination of translation regulation including allele-specific analyses. Here, to address this challenge, we developed a novel microfluidic isotachophoresis (ITP) approach, named RIBOsome profiling via ITP (Ribo-ITP), and characterized translation in single oocytes and embryos during early mouse development. We identified differential translation efficiency as a key mechanism regulating genes involved in centrosome organization and N6-methyladenosine modification of RNAs. Our high-coverage measurements enabled, to our knowledge, the first analysis of allele-specific ribosome engagement in early development. These led to the discovery of stage-specific differential engagement of zygotic RNAs with ribosomes and reduced translation efficiency of transcripts exhibiting allele-biased expression. By integrating our measurements with proteomics data, we discovered that ribosome occupancy in germinal vesicle-stage oocytes is the predominant determinant of protein abundance in the zygote. The Ribo-ITP approach will enable numerous applications by providing high-coverage and high-resolution ribosome occupancy measurements from ultra-low input samples including single cells.

Microfluidic chain reaction of structurally programmed capillary flow events.

Chain reactions, characterized by initiation, propagation and termination, are stochastic at microscopic scales and underlie vital chemical (for example, combustion engines), nuclear and biotechnological (for example, polymerase chain reaction) applications1-5. At macroscopic scales, chain reactions are deterministic and limited to applications for entertainment and art such as falling dominoes and Rube Goldberg machines. On the other hand, the microfluidic lab-on-a-chip (also called a micro-total analysis system)6,7 was visualized as an integrated chip, akin to microelectronic integrated circuits, yet in practice remains dependent on cumbersome peripherals, connections and a computer for automation8-11. Capillary microfluidics integrate energy supply and flow control onto a single chip by using capillary phenomena, but programmability remains rudimentary with at most a handful (eight) operations possible12-19. Here we introduce the microfluidic chain reaction (MCR) as the conditional, structurally programmed propagation of capillary flow events. Monolithic chips integrating a MCR are three-dimensionally printed, and powered by the free energy of a paper pump, autonomously execute liquid handling algorithms step-by-step. With MCR, we automated (1) the sequential release of 300 aliquots across chained, interconnected chips, (2) a protocol for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) antibodies detection in saliva and (3) a thrombin generation assay by continuous subsampling and analysis of coagulation-activated plasma with parallel operations including timers, iterative cycles of synchronous flow and stop-flow operations. MCRs are untethered from and unencumbered by peripherals, encode programs structurally in situ and can form a frugal, versatile, bona fide lab-on-a-chip with wide-ranging applications in liquid handling and point-of-care diagnostics.

Microfluidics: reframing biological enquiry.

The underlying physical properties of microfluidic tools have led to new biological insights through the development of microsystems that can manipulate, mimic and measure biology at a resolution that has not been possible with macroscale tools. Microsystems readily handle sub-microlitre volumes, precisely route predictable laminar fluid flows and match both perturbations and measurements to the length scales and timescales of biological systems. The advent of fabrication techniques that do not require highly specialized engineering facilities is fuelling the broad dissemination of microfluidic systems and their adaptation to specific biological questions. We describe how our understanding of molecular and cell biology is being and will continue to be advanced by precision microfluidic approaches and posit that microfluidic tools - in conjunction with advanced imaging, bioinformatics and molecular biology approaches - will transform biology into a precision science.

Genome-wide single-cell analysis of recombination activity and de novo mutation rates in human sperm.

Meiotic recombination and de novo mutation are the two main contributions toward gamete genome diversity, and many questions remain about how an individual human's genome is edited by these two processes. Here, we describe a high-throughput method for single-cell whole-genome analysis that was used to measure the genomic diversity in one individual's gamete genomes. A microfluidic system was used for highly parallel sample processing and to minimize nonspecific amplification. High-density genotyping results from 91 single cells were used to create a personal recombination map, which was consistent with population-wide data at low resolution but revealed significant differences from pedigree data at higher resolution. We used the data to test for meiotic drive and found evidence for gene conversion. High-throughput sequencing on 31 single cells was used to measure the frequency of large-scale genome instability, and deeper sequencing of eight single cells revealed de novo mutation rates with distinct characteristics.

Single-cell expression analyses during cellular reprogramming reveal an early stochastic and a late hierarchic phase.

During cellular reprogramming, only a small fraction of cells become induced pluripotent stem cells (iPSCs). Previous analyses of gene expression during reprogramming were based on populations of cells, impeding single-cell level identification of reprogramming events. We utilized two gene expression technologies to profile 48 genes in single cells at various stages during the reprogramming process. Analysis of early stages revealed considerable variation in gene expression between cells in contrast to late stages. Expression of Esrrb, Utf1, Lin28, and Dppa2 is a better predictor for cells to progress into iPSCs than expression of the previously suggested reprogramming markers Fbxo15, Fgf4, and Oct4. Stochastic gene expression early in reprogramming is followed by a late hierarchical phase with Sox2 being the upstream factor in a gene expression hierarchy. Finally, downstream factors derived from the late phase, which do not include Oct4, Sox2, Klf4, c-Myc, and Nanog, can activate the pluripotency circuitry.

Comparative Analysis of Droplet-Based Ultra-High-Throughput Single-Cell RNA-Seq Systems.

Since its establishment in 2009, single-cell RNA sequencing (RNA-seq) has been a major driver behind progress in biomedical research. In developmental biology and stem cell studies, the ability to profile single cells confers particular benefits. Although most studies still focus on individual tissues or organs, the recent development of ultra-high-throughput single-cell RNA-seq has demonstrated potential power in characterizing more complex systems or even the entire body. However, although multiple ultra-high-throughput single-cell RNA-seq systems have attracted attention, no systematic comparison of these systems has been performed. Here, with the same cell line and bioinformatics pipeline, we developed directly comparable datasets for each of three widely used droplet-based ultra-high-throughput single-cell RNA-seq systems, inDrop, Drop-seq, and 10X Genomics Chromium. Although each system is capable of profiling single-cell transcriptomes, their detailed comparison revealed the distinguishing features and suitable applications for each system.

Genetic and phenotypic profiling of single living circulating tumor cells from patients with microfluidics.

Accurate prediction of the efficacy of immunotherapy for cancer patients through the characterization of both genetic and phenotypic heterogeneity in individual patient cells holds great promise in informing targeted treatments, and ultimately in improving care pathways and clinical outcomes. Here, we describe the nanoplatform for interrogating living cell host-gene and (micro-)environment (NICHE) relationships, that integrates micro- and nanofluidics to enable highly efficient capture of circulating tumor cells (CTCs) from blood samples. The platform uses a unique nanopore-enhanced electrodelivery system that efficiently and rapidly integrates stable multichannel fluorescence probes into living CTCs for in situ quantification of target gene expression, while on-chip coculturing of CTCs with immune cells allows for the real-time correlative quantification of their phenotypic heterogeneities in response to immune checkpoint inhibitors (ICI). The NICHE microfluidic device provides a unique ability to perform both gene expression and phenotypic analysis on the same single cells in situ, allowing us to generate a predictive index for screening patients who could benefit from ICI. This index, which simultaneously integrates the heterogeneity of single cellular responses for both gene expression and phenotype, was validated by clinically tracing 80 non-small cell lung cancer patients, demonstrating significantly higher AUC (area under the curve) (0.906) than current clinical reference for immunotherapy prediction.

Massively multiplexed nucleic acid detection with Cas13.

The great majority of globally circulating pathogens go undetected, undermining patient care and hindering outbreak preparedness and response. To enable routine surveillance and comprehensive diagnostic applications, there is a need for detection technologies that can scale to test many samples1-3 while simultaneously testing for many pathogens4-6. Here, we develop Combinatorial Arrayed Reactions for Multiplexed Evaluation of Nucleic acids (CARMEN), a platform for scalable, multiplexed pathogen detection. In the CARMEN platform, nanolitre droplets containing CRISPR-based nucleic acid detection reagents7 self-organize in a microwell array8 to pair with droplets of amplified samples, testing each sample against each CRISPR RNA (crRNA) in replicate. The combination of CARMEN and Cas13 detection (CARMEN-Cas13) enables robust testing of more than 4,500 crRNA-target pairs on a single array. Using CARMEN-Cas13, we developed a multiplexed assay that simultaneously differentiates all 169 human-associated viruses with at least 10 published genome sequences and rapidly incorporated an additional crRNA to detect the causative agent of the 2020 COVID-19 pandemic. CARMEN-Cas13 further enables comprehensive subtyping of influenza A strains and multiplexed identification of dozens of HIV drug-resistance mutations. The intrinsic multiplexing and throughput capabilities of CARMEN make it practical to scale, as miniaturization decreases reagent cost per test by more than 300-fold. Scalable, highly multiplexed CRISPR-based nucleic acid detection shifts diagnostic and surveillance efforts from targeted testing of high-priority samples to comprehensive testing of large sample sets, greatly benefiting patients and public health9-11.

Bioengineering methods for analysis of cells in vitro.

Efforts in the interdisciplinary field of bioengineering have led to innovative methods for investigating the complexities of cell responses in vitro. These approaches have emphasized the reduction of complex multicomponent cellular microenvironments into distinct individual signals as a means to both (a) better construct mimics of in vivo microenvironments and (b) better deconstruct microenvironments to study them. Microtechnology tools, together with advances in biomaterials, have been fundamental to this progress by enabling the tightly controlled presentation of environmental cues and the improved systematic analysis of cellular perturbations. In this review, we describe bioengineering approaches for controlling and measuring cell-environmental interactions in vitro, including strategies for high-throughput analysis. We also describe the mechanistic insights gained by the use of these novel tools, with associated applications ranging from fundamental biological studies, in vitro modeling of in vivo processes, and cell-based therapies.

Adaptation to DNA damage checkpoint in senescent telomerase-negative cells promotes genome instability.

In cells lacking telomerase, telomeres gradually shorten during each cell division to reach a critically short length, permanently activate the DNA damage checkpoint, and trigger replicative senescence. The increase in genome instability that occurs as a consequence may contribute to the early steps of tumorigenesis. However, because of the low frequency of mutations and the heterogeneity of telomere-induced senescence, the timing and mechanisms of genome instability increase remain elusive. Here, to capture early mutation events during replicative senescence, we used a combined microfluidic-based approach and live-cell imaging in yeast. We analyzed DNA damage checkpoint activation in consecutive cell divisions of individual cell lineages in telomerase-negative yeast cells and observed that prolonged checkpoint arrests occurred frequently in telomerase-negative lineages. Cells relied on the adaptation to the DNA damage pathway to bypass the prolonged checkpoint arrests, allowing further cell divisions despite the presence of unrepaired DNA damage. We demonstrate that the adaptation pathway is a major contributor to the genome instability induced during replicative senescence. Therefore, adaptation plays a critical role in shaping the dynamics of genome instability during replicative senescence.

Ultrahigh-Throughput Enzyme Engineering and Discovery in In Vitro Compartments.

Novel and improved biocatalysts are increasingly sourced from libraries via experimental screening. The success of such campaigns is crucially dependent on the number of candidates tested. Water-in-oil emulsion droplets can replace the classical test tube, to provide in vitro compartments as an alternative screening format, containing genotype and phenotype and enabling a readout of function. The scale-down to micrometer droplet diameters and picoliter volumes brings about a >107-fold volume reduction compared to 96-well-plate screening. Droplets made in automated microfluidic devices can be integrated into modular workflows to set up multistep screening protocols involving various detection modes to sort >107 variants a day with kHz frequencies. The repertoire of assays available for droplet screening covers all seven enzyme commission (EC) number classes, setting the stage for widespread use of droplet microfluidics in everyday biochemical experiments. We review the practicalities of adapting droplet screening for enzyme discovery and for detailed kinetic characterization. These new ways of working will not just accelerate discovery experiments currently limited by screening capacity but profoundly change the paradigms we can probe. By interfacing the results of ultrahigh-throughput droplet screening with next-generation sequencing and deep learning, strategies for directed evolution can be implemented, examined, and evaluated.

Dissecting Cell-Type Composition and Activity-Dependent Transcriptional State in Mammalian Brains by Massively Parallel Single-Nucleus RNA-Seq.

Massively parallel single-cell RNA sequencing can precisely resolve cellular diversity in a high-throughput manner at low cost, but unbiased isolation of intact single cells from complex tissues such as adult mammalian brains is challenging. Here, we integrate sucrose-gradient-assisted purification of nuclei with droplet microfluidics to develop a highly scalable single-nucleus RNA-seq approach (sNucDrop-seq), which is free of enzymatic dissociation and nucleus sorting. By profiling ∼18,000 nuclei isolated from cortical tissues of adult mice, we demonstrate that sNucDrop-seq not only accurately reveals neuronal and non-neuronal subtype composition with high sensitivity but also enables in-depth analysis of transient transcriptional states driven by neuronal activity, at single-cell resolution, in vivo.

Characterizing cell interactions at scale with made-to-order droplet ensembles (MODEs).

Cell-cell interactions are important to numerous biological systems, including tissue microenvironments, the immune system, and cancer. However, current methods for studying cell combinations and interactions are limited in scalability, allowing just hundreds to thousands of multicell assays per experiment; this limited throughput makes it difficult to characterize interactions at biologically relevant scales. Here, we describe a paradigm in cell interaction profiling that allows accurate grouping of cells and characterization of their interactions for tens to hundreds of thousands of combinations. Our approach leverages high-throughput droplet microfluidics to construct multicellular combinations in a deterministic process that allows inclusion of programmed reagent mixtures and beads. The combination droplets are compatible with common manipulation and measurement techniques, including imaging, barcode-based genomics, and sorting. We demonstrate the approach by using it to enrich for chimeric antigen receptor (CAR)-T cells that activate upon incubation with target cells, a bottleneck in the therapeutic T cell engineering pipeline. The speed and control of our approach should enable valuable cell interaction studies.

High-throughput selection of cells based on accumulated growth and division using PicoShell particles.

Production of high-energy lipids by microalgae may provide a sustainable energy source that can help tackle climate change. However, microalgae engineered to produce more lipids usually grow slowly, leading to reduced overall yields. Unfortunately, culture vessels used to select cells based on growth while maintaining high biomass production, such as well plates, water-in-oil droplet emulsions, and nanowell arrays, do not provide production-relevant environments that cells experience in scaled-up cultures (e.g., bioreactors or outdoor cultivation farms). As a result, strains that are developed in the laboratory may not exhibit the same beneficial phenotypic behavior when transferred to industrial production. Here, we introduce PicoShells, picoliter-scale porous hydrogel compartments, that enable >100,000 individual cells to be compartmentalized, cultured in production-relevant environments, and selected based on growth and bioproduct accumulation traits using standard flow cytometers. PicoShells consist of a hollow inner cavity where cells are encapsulated and a porous outer shell that allows for continuous solution exchange with the external environment. PicoShells allow for cell growth directly in culture environments, such as shaking flasks and bioreactors. We experimentally demonstrate that Chlorella sp., Saccharomyces cerevisiae, and Chinese hamster ovary cells, used for bioproduction, grow to significantly larger colony sizes in PicoShells than in water-in-oil droplet emulsions (P < 0.05). We also demonstrate that PicoShells containing faster dividing and growing Chlorella clonal colonies can be selected using a fluorescence-activated cell sorter and regrown. Using the PicoShell process, we select a Chlorella population that accumulates chlorophyll 8% faster than does an unselected population after a single selection cycle.

A Scalable Microfluidic Platform for Nanoparticle Formulation: For Exploratory- and Industrial-Level Scales.

Nanoparticle synthesis on microfluidic platforms provides excellent reproducibility and control over bulk synthesis. While there have been plenty of platforms for producing nanoparticles (NPs) with controlled physicochemical properties, such platforms often operate in a narrow range of predefined flow rates. The flow rate limitation restricts either up-scalability for industrial production or down-scalability for exploratory research use. Here, we present a universal flow rate platform that operates over a wide range of flow rates (0.1-75 mL/min) for small-scale exploratory research and industrial-level synthesis of NPs without compromising the mixing capabilities. The wide range of flow rate is obtained by using a coaxial flow with a triangular microstructure to create a vortex regardless of the flow regime (Reynolds number). The chip synthesizes several types of NPs for gene and protein delivery, including polyplex, lipid NPs, and solid polymer NPs via self-assembly and precipitation, and successfully expresses GFP plasmid DNA in human T cells.