Imidazoquinolines (IMDs), such as resiquimod (R848), are of great interest as potential cancer immunotherapies because of their ability to activate Toll-like receptor 7 (TLR7) and/or TLR8 on innate immune cells. Nevertheless, intravenous administration of IMDs causes severe immune-related toxicities, and attempts to improve their tissue-selective exposure while minimizing acute systemic inflammation have proven difficult. Here, using a library of R848 “bottlebrush prodrugs” (BPDs) that differ only by their R848 release kinetics, we explore how the timing of R848 exposure affects immune stimulation in vitro and in vivo. These studies led to the discovery of R848-BPDs that exhibit optimal activation kinetics to achieve potent stimulation of myeloid cells in tumors and substantial reductions in tumor growth following systemic administration in mouse syngeneic tumor models without any observable systemic toxicity. These results suggest that release kinetics can be tuned at the molecular level to provide safe yet effective systemically administered immunostimulant prodrugs for next-generation cancer immunotherapies.

High-throughput phenotypic screens leveraging biochemical perturbations, high-content readouts, and complex multicellular models could advance therapeutic discovery yet remain constrained by limitations of scale. To address this, we establish a method for compressing screens by pooling perturbations followed by computational deconvolution. Conducting controlled benchmarks with a highly bioactive small molecule library and a high-content imaging readout, we demonstrate increased efficiency for compressed experimental designs compared to conventional approaches. To prove generalizability, we apply compressed screening to examine transcriptional responses of patient-derived pancreatic cancer organoids to a library of tumor-microenvironment (TME)-nominated recombinant protein ligands. Using single-cell RNA-seq as a readout, we uncover reproducible phenotypic shifts induced by ligands that correlate with clinical features in larger datasets and are distinct from reference signatures available in public databases. In sum, our approach enables phenotypic screens that interrogate complex multicellular models with rich phenotypic readouts to advance translatable drug discovery as well as basic biology.

Protocol for integrating CITE-seq with well-based scRNA-seq protocols.

High-throughput single-cell RNA-sequencing (scRNA-seq) methodologies enable characterization of complex biological samples by increasing the number of cells that can be profiled contemporaneously. Nevertheless, these approaches recover less information per cell than low-throughput strategies. To accurately report the expression of key phenotypic features of cells, scRNA-seq platforms are needed that are both high fidelity and high throughput. To address this need, we created Seq-Well S3 (“Second-Strand Synthesis”), a massively parallel scRNA-seq protocol that uses a randomly primed second-strand synthesis to recover complementary DNA (cDNA) molecules that were successfully reverse transcribed but to which a second oligonucleotide handle, necessary for subsequent whole transcriptome amplification, was not appended due to inefficient template switching. Seq-Well Sincreased the efficiency of transcript capture and gene detection compared with that of previous iterations by up to 10- and 5-fold, respectively. We used Seq-Well S3 to chart the transcriptional landscape of five human inflammatory skin diseases, thus providing a resource for the further study of human skin inflammation.

Whether cultured in vitro or part of a complex tissue in vivo, a cell’s phenotype and function are significantly influenced by dynamic interactions with its microenvironment. To explicitly examine how a cell’s spatiotemporal activity impacts its behavior, we developed and validated a strategy termed SPACECAT – Spatially PhotoActivatable Color Encoded Cell Address Tags – to annotate, track, and isolate specific cells in a non-destructive, viability-preserving manner. In SPACECAT, a biological sample is immersed in a photocaged fluorescent molecule, and cells within a location of interest are labeled for further study by uncaging that molecule with user-patterned near-UV light. SPACECAT offers high spatial precision and temporal stability across diverse cell and tissue types, and is compatible with common downstream assays, including flow cytometry and single-cell RNA-Seq. Illustratively, we leveraged this approach in patient-derived intestinal organoids, a spatially complex system less amenable to genetic manipulations, to select for crypt-like regions enriched in stem-like and actively mitotic cells. Moreover, we demonstrate its applicability and utility on ex vivo tissue sections from four healthy organs and an autochthonous lung tumor model, uncovering spatially-biased gene expression patterns among immune cell subsets and identifying rare myeloid phenotypes enriched around tumor/healthy border regions. In sum, our method provides a minimally invasive and broadly applicable approach to link cellular spatiotemporal features and/or behavioral phenotypes with diverse downstream assays, enabling fundamental insights into the connections between tissue microenvironments and biological (dys)function.

We 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-ofprinciple, 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

We develop single-cell transcriptomic approaches to comprehensively profile human tissues and model systems. Previously, we focused on establishingvalidating, scaling, and simplifying single-cell RNA-seq, often through the development of microdevices, to enable genome-wide identification of the cell types/states contained within complex biological samples. More recently, we helped both enhance the detection of phenotype-defining transcripts using these methods and simplify their on-site processing for clinical applications. In parallel, we have also worked to democratize these techniques, providing open access to resources and protocols, training thousands locally and abroad, and establishing infrastructure and on-site collaborations spanning across 6 continents and 26+ countries.

As many factors define cellular phenotype and influence disease beyond mRNA, we develop complementary methods for co-assaying other cellular attributes to enrich our understanding of the drivers of cellular behaviors. Examples including the abundance of additional ‘-omes’, the sequence and amount of important transcripts, cellular history, biophysical properties, spatial position, and functional output. Recently, we have worked to: 1. detect pathogens in cells and potentially actionable associated host factors; 2. query for specific mutations to identify cancer cells; and, 3. extract T cell receptor sequences to examine clonality. We have also formulated computational methods to derive deeper insights from these data (e.g., to examine viral dynamic in infected cells, reproducible features hidden by inter-individual variability, multicellular immune dynamics, intercellular communication, or alteration in cellular ecosystems associated with pathology).

We explore how the extracellular milieu influences cellular decision-making. Here, we have employed controlled culture conditions with cells and organoids, chemical and genetic perturbations, and constant microfluidic perfusion. We also have leveraged natural microenvironmental variation within and across tissues via microdissection and by using photoactivatable probes that retain spatial information through dissociation. In each instance, we aim to understand the degree to which extracellular environments modulate, and can be used to rationally control, the responses of individual cells or the overall distribution thereof, with an eye toward engineering tissue responses.

We examine the impact of intercellular interactions on cellular function. We have used coculture, imaging and perturbation strategies, as well as matched computational methods, to reinforce findings from dissociated samples, validate inferred cell-cell communication in vivo (e.g., between sensory neurons and lymph node resident cells), and manipulate multicellular systems (e.g., organoids). We are currently working on building arrayed, synthetically-designed cellular ensembles to examine how ‘tissue’ structure impacts functional response. Our overall goal is to understand cellular co-dependencies that influence niche- and tissue-level response dynamics.

Seq-Well is a portable, low-cost platform for single-cell RNA sequencing designed to be compatible with low-input, clinical biopsies. We have recently published a manuscript detailing the development and validation of the Seq-Well plaftorm. Here, we provide an in-depth protocol and videos describing how to perform Seq-Well experiments.

We hope that you will use Seq-Well and apply it in your work.

Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput
  • Gierahn et al.,
  • Nature Methods,
  • 2017
  • R&D
  • Chemistry
  • Technology
  • Travel
  • Genomics
  • Marc Wadsworth II
  • Travis Hughes
  • Alex K. Shalek

 

 

 

CAD Files: 

CAD files for Seq-well devices and molds are provided here: CAD Files

Note: These files are made available under the “Attribution-NonCommercial-NoDerivatives 4.0 International” creative commons license.

Copyright 2017, Massachusetts Institute of Technology and the Broad Institute.

Single-cell RNA-seq can precisely resolve cellular states, but applying this method to low-input samples is challenging. Here, we present Seq-Well, a portable, low-cost platform for massively parallel single-cell RNA-seq. Barcoded mRNA capture beads and single cells are sealed in an array of subnanoliter wells using a semipermeable membrane, enabling efficient cell lysis and transcript capture. We use Seq-Well to profile thousands of primary human macrophages exposed to Mycobacterium tuberculosis.

 

We are exposed to a constant flux of external biochemical and physical stimuli as we age. Despite variability in our overall experiences and exact constitutions, our individual tissues typically manage to maintain functionality, though each can differ in its resilience to distinct stressors.

We have characterized how differences in cellular composition and communication impact tissue fitness and have identified responses and subsequent adaptations that drive chronic dysfunction. For example, although aberrant immune activity can precipitate allergic inflammatory diseases, therapies targeting immune cells and signaling are only successful in some, suggesting chronicity may involve alternative mechanisms. Previously, we helped demonstrate that dysregulated type-2 immune signaling, driven by environmental allergens, can impact tissue health in the upper airway through generating dysfunctional basal epithelial stem cells. These stem cells can then contribute to persistence by serving as repositories for allergic inflammatory memories, altering the integrity and functional output of the nasal epithelium. Our work, with that of others, suggests generalizable principles for cellular memory, and informs where and how tissues should be targeted to support health or restore function. We have since further investigated how tissue-resident cellular subsets participate in, and are shaped by, environmental exposures at barrier tissues and the functional consequences of these experiences.

We are now working to develop a more holistic appreciation for how different intra- and extracellular factors (e.g., genetics and integrated exposure history, respectively) influence barrier tissue function.

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 C1TM 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.

The orchestrated action of genes controls complex biological phenotypes, yet the systematic discovery of gene and drug combinations that modulate these phenotypes in human cells is labor intensive and challenging to scale. Here, we created a platform for the massively parallel screening of barcoded combinatorial gene perturbations in human cells and translated these hits into effective drug combinations. This technology leverages the simplicity of the CRISPR-Cas9 system for multiplexed targeting of specific genomic loci and the versatility of combinatorial genetics en masse (CombiGEM) to rapidly assemble barcoded combinatorial genetic libraries that can be tracked with high-throughput sequencing. We applied CombiGEM-CRISPR to create a library of 23,409 barcoded dual guide-RNA (gRNA) combinations and then perform a high-throughput pooled screen to identify gene pairs that inhibited ovarian cancer cell growth when they were targeted. We validated the growth-inhibiting effects of specific gene sets, including epigenetic regulators KDM4C/BRD4 and KDM6B/BRD4, via individual assays with CRISPR-Cas–based knockouts and RNA-interference–based knockdowns. We also tested small-molecule drug pairs directed against our pairwise hits and showed that they exerted synergistic antiproliferative effects against ovarian cancer cells. We envision that the CombiGEM-CRISPR platform will be applicable to a broad range of biological settings and will accelerate the systematic identification of genetic combinations and their translation into novel drug combinations that modulate complex human disease phenotypes.

Developing a detailed understanding of enzyme function in the context of an intracellular signal transduction pathway requires minimally invasive methods for probing enzyme activity in situ. Here, we describe a new method for monitoring enzyme activity in living cells by sandwiching live cells between two vertical silicon nanowire (NW) arrays. Specifically, we use the first NW array to immobilize the cells and then present enzymatic substrates intracellularly via the second NW array by utilizing the NWs’ ability to penetrate cellular membranes without affecting cells’ viability or function. This strategy, when coupled with fluorescence microscopy and mass spectrometry, enables intracellular examination of protease, phosphatase, and protein kinase activities, demonstrating the assay’s potential in uncovering the physiological roles of various enzymes.

Deciphering the neuronal code—the rules by which neuronal circuits store and process information—is a major scientific challenge. Currently, these efforts are impeded by a lack of experimental tools that are sensitive enough to quantify the strength of individual synaptic connections and also scalable enough to simultaneously measure and control a large number of mammalian neurons with single-cell resolution. Here, we report a scalable intracellular electrode platform based on vertical nanowires that allows parallel electrical interfacing to multiple mammalian neurons. Specifically, we show that our vertical nanowire electrode arrays can intracellularly record and stimulate neuronal activity in dissociated cultures of rat cortical neurons and can also be used to map multiple individual synaptic connections. The scalability of this platform, combined with its compatibility with silicon nanofabrication techniques, provides a clear path towards simultaneous, highfidelity interfacing with hundreds of individual neurons.

A generalized platform for introducing a diverse range of biomolecules into living cells in high-throughput could transform how complex cellular processes are probed and analyzed. Here, we demonstrate spatially localized, efficient, and universal delivery of biomolecules into immortalized and primary mammalian cells using surface-modified vertical silicon nanowires. The method relies on the ability of the silicon nanowires to penetrate a cell’s membrane and subsequently release surface-bound molecules directly into the cell’s cytosol, thus allowing highly efficient delivery of biomolecules without chemical modification or viral packaging. This modality enables one to assess the phenotypic consequences of introducing a broad range of biological effectors (DNAs, RNAs, peptides, proteins, and small molecules) into almost any cell type. We show that this platform can be used to guide neuronal progenitor growth with small molecules, knock down transcript levels by delivering siRNAs, inhibit apoptosis using peptides, and introduce targeted proteins to specific organelles. We further demonstrate codelivery of siRNAs and proteins on a single substrate in a microarray format, highlighting this technology’s potential as a robust, monolithic platform for high-throughput, miniaturized bioassays.

Abstract

Electrostatic force microscopy shows that the electric field gradients above pentacene monolayer islands on 2-nm SiO2/Si substrates, in a dark, dry nitrogen environment, display a wide distribution of signs and magnitude that is dependent on sample history. Under 12 mW/cm2 green (532 nm) illumination, pentacene islands accumulate positive charge because of photoexcited electron transfer across the oxide to the Si substrate. At a strong illumination of 60 mW/cm2, pentacene islands reform into small spherical particles, apparently because the positive charge Coulomb repulsion energy becomes comparable to the cohesive energy of the pentacene monolayer.