Each of us begins life as a single fertilized cell. Following a seemingly predetermined set of cell divisions, the single cell morphs into a rough mass, then a hollowed tube, and finally becomes a ...recognizable neonatal form. How the information contained within a single cell si- multaneously specifies an organism’s anatomy, the construction of its organs, and the ability to cogitate on this very question, remains one of biology’s open questions. Although centuries of careful experiments devoted to characterizing development have revealed many important genes and mechanisms, the results of these experiments span different model organisms, developmental stages, cell populations and measurement modalities. Integrating this knowledge base into coher- ent representation requires a cellular scaffold that charts an organism’s development over the axes of time and space. Preliminary unified representations of developing organisms (e.g. C. Elegans, Zebrafish and Mouse) have been created by large-scale single cell RNA sequencing (scRNA-seq) efforts. These efforts have characterized the set of intermediates through which differentiating cells transit and have profiled the large number of cell types present in a developing organism. Although scRNA-seq data have proven powerful in cataloging cellular states, they lack crucial context: i) the experimental context afforded by the comparison of multiple conditions (e.g. wild-type vs. perturbation) and ii) a cell’s spatial context, a crucial factor driving its behavior. To address these knowledge gaps, over the course of my PhD I have developed two scRNA-seq technologies: 1) sci- Plex, a generalizable strategy to label cell populations and 2) sci-Space, a methodology to record acell’s spatial position in conjunction with its single cell transcriptome.(1) First I developed the sci-Plex protocol, an inexpensive and efficient method to label singlecells through the chemical fixation of unmodified single stranded oligos to nuclei prior to scRNA- seq library preparation. To demonstrate proof-of-concept of the sci-Plex protocol, I performed a high-throughput, high-content drug screen at single cell resolution in 3 cancer cell lines; effectively conducting 4,500 independent scRNA-seq experiments at once. The resulting dataset enabled characterization of a drug’s potency, class, mechanism of action, and the heterogeneity of cellular responses induced upon drug treatment. For example, our scRNA-seq data showed that histone deacetylase inhibitors likely lead to cell death by trapping valuable acetyl molecules on chromatin.(2) Next, I extended the application of the sci-Plex protocol and developed the sci-Space method to capture spatial information from sectioned tissue. The fast and scalable sci-Space method uses patterned oligonucleotide barcodes in a regular array such that each spot contains a unique set of sequences. Then, to mark each nucleus’ coordinates on the grid, the barcodes are stamped onto a tissue section prior to disaggregation and library preparation. To showcase the power of sci-Space, I collected a dataset comprising over 120,000 cells originating from 14 sections of a single E14 mouse embryo. The resulting data uncovers the genes that drive the devel- oping organism’s body plan and reveals a widespread migration signature within neurons that form the developing brain. These data also provide a quantitative assessment of how cell state relates to spatial position within the developing embryo. Specifically, our estimates indicate that 25% of the variance in gene expression observed is attributable to spatial position. It is my hope that this technology will power the generation of a unified scaffold of development akin to the reference genome. I believe that such a unified representation will be instrumental in amassing data, accel- erating discovery and facilitating translation through the training of machine learning models of cellular state.
Abstract Antigen delivered within particulate materials leads to enhanced antigen-specific immunity compared to soluble administration of antigen. However, current delivery approaches for antigen ...encapsulated in synthetic particulate materials are limited by the complexity of particle production that affects stability and immunogenicity of the antigen. Herein, we describe a protein delivery system that utilizes plasma membrane vesicles (PMVs) derived from biological materials such as cultured cells or isolated tissues and a simple protein transfer technology. We show that these particulate PMVs can be easily modified within 4 h by a protein transfer process to stably incorporate a glycosylphosphatidylinositol (GPI)-anchored form of the breast cancer antigen HER-2 onto the PMV surface. Immunization of mice with GPI-HER-2-modified-PMVs induced strong HER-2-specific antibody responses and protection from tumor challenge in two different breast cancer models. Further incorporation of the immunostimulatory molecules IL-12 and B7-1 onto the PMVs by protein transfer enhanced tumor protection and induced beneficial Th1 and Th2-type HER-2-specific immune responses. Since protein antigens can be easily converted to GPI-anchored forms, these results demonstrate that isolated plasma membrane vesicles can be modified with desired antigens along with immunostimulatory molecules by protein transfer and used as a vaccine delivery vehicle to elicit potent antigen-specific immunity.
Cellular reprogramming through manipulation of defined factors holds great promise for large-scale production of cell types needed for use in therapy and for revealing principles of gene regulation. ...However, most reprogramming systems are inefficient, converting only a fraction of cells to the desired state. Here, we analyze MYOD-mediated reprogramming of human fibroblasts to myotubes, a well-characterized model system for direct conversion by defined factors, at pseudotemporal resolution using single-cell RNA-seq. To expose barriers to efficient conversion, we introduce a novel analytic technique, trajectory alignment, which enables quantitative comparison of gene expression kinetics across two biological processes. Reprogrammed cells navigate a trajectory with branch points that correspond to two alternative decision points, with cells that select incorrect branches terminating at aberrant or incomplete reprogramming outcomes. Analysis of these branch points revealed insulin and BMP signaling as crucial molecular determinants of reprogramming. Single-cell trajectory alignment enables rigorous quantitative comparisons between biological trajectories found in diverse processes in development, reprogramming, and other contexts.
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•Single-cell RNA-seq of myogenic reprogramming reveals barriers to conversion by MYOD•Reprogramming and differentiation can be aligned by dynamic time warping•Modulating insulin and BMP signaling greatly enhances myogenic conversion
Cellular reprogramming converts only a fraction of cells to the desired state. We analyze reprogramming of human fibroblasts to myotubes at pseudotemporal resolution using single-cell RNA-seq. We identified defects in BMP and insulin signaling as culprits using trajectory alignment, which enables quantitative comparison of gene expression kinetics across two biological processes.
Chemical genetic screens are a powerful tool for exploring how cancer cells’ response to drugs is shaped by their mutations, yet they lack a molecular view of the contribution of individual genes to ...the response to exposure. Here, we present sci-Plex-Gene-by-Environment (sci-Plex-GxE), a platform for combined single-cell genetic and chemical screening at scale. We highlight the advantages of large-scale, unbiased screening by defining the contribution of each of 522 human kinases to the response of glioblastoma to different drugs designed to abrogate signaling from the receptor tyrosine kinase pathway. In total, we probed 14,121 gene-by-environment combinations across 1,052,205 single-cell transcriptomes. We identify an expression signature characteristic of compensatory adaptive signaling regulated in a MEK/MAPK-dependent manner. Further analyses aimed at preventing adaptation revealed promising combination therapies, including dual MEK and CDC7/CDK9 or nuclear factor κB (NF-κB) inhibitors, as potent means of preventing transcriptional adaptation of glioblastoma to targeted therapy.
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•A platform for combined single-cell genetic and chemical screens at scale•Inferred transcriptional EC50 quantifies the effect of perturbation on drug response•Chemical transcriptomics defines a shared adaptive drug-resistance program•Kinome-wide sci-Plex-GxE prioritizes treatment combinations that block adaptation
Molecular maps of response to anti-cancer therapy can uncover genes that promote or resist treatment. McFaline-Figueroa et al. introduce sci-Plex-GxE to probe the vast interaction space between genetic perturbations and drug treatments. Applying it to a kinome-wide screen for regulators of drug-induced transcription identified kinases that induce an adaptive resistance program.
Therapeutic use and function of recombinant molecules can be studied by the expression of foreign genes in mice. In this study, we have expressed human Fcγ receptor-Ig fusion molecules (FcγR-Igs) in ...mice by administering FcγR-Ig plasmid DNAs hydrodynamically and compared their effectiveness with purified molecules in blocking immune-complex (IC)-mediated inflammation in mice. The concentration of hydrodynamically expressed FcγR-Igs (CD16A(F)-Ig, CD32A(R)-Ig and CD32A(H)-Ig) reached a maximum of 130 μg ml(-1) of blood within 24 h after plasmid DNA administration. The in vivo half-life of FcγR-Igs was found to be 9-16 days and western blot analysis showed that the FcγR-Igs were expressed as a homodimer. The hydrodynamically expressed FcγR-Igs blocked 50-80% of IC-mediated inflammation up to 3 days in a reverse passive Arthus reaction model. Comparative analysis with purified molecules showed that hydrodynamically expressed FcγR-Igs are more efficient than purified molecules in blocking IC-mediated inflammation and had a higher half-life. In summary, these results suggest that the administration of a plasmid vector with the FcγR-Ig gene can be used to study the consequences of blocking IC binding to FcγRs during the development of inflammatory diseases. This approach may have potential therapeutic value in treating IC-mediated inflammatory autoimmune diseases such as lupus, arthritis and autoimmune vasculitis.
Abstract
Background
We aimed to evaluate a testing program to facilitate control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission at a large university and measure spread ...in the university community using viral genome sequencing.
Methods
Our prospective longitudinal study used remote contactless enrollment, daily mobile symptom and exposure tracking, and self-swab sample collection. Individuals were tested if the participant was exposed to a known SARS-CoV-2-infected person, developed new symptoms, or reported high-risk behavior (such as attending an indoor gathering without masking or social distancing), if a member of a group experiencing an outbreak, or at enrollment. Study participants included students, staff, and faculty at an urban public university during the Autumn quarter of 2020.
Results
We enrolled 16 476 individuals, performed 29 783 SARS-CoV-2 tests, and detected 236 infections. Seventy-five percent of positive cases reported at least 1 of the following: symptoms (60.8%), exposure (34.7%), or high-risk behaviors (21.5%). Greek community affiliation was the strongest risk factor for testing positive, and molecular epidemiology results suggest that specific large gatherings were responsible for several outbreaks.
Conclusions
A testing program focused on individuals with symptoms and unvaccinated persons who participate in large campus gatherings may be effective as part of a comprehensive university-wide mitigation strategy to control the spread of SARS-CoV-2.
Single cell combinatorial indexing RNA sequencing (sci-RNA-seq) is a powerful method for recovering gene expression data from an exponentially scalable number of individual cells or nuclei. However, ...sci-RNA-seq is a complex protocol that has historically exhibited variable performance on different tissues, as well as lower sensitivity than alternative methods. Here we report a simplified, optimized version of the three-level sci-RNA-seq protocol that is faster, higher yield, more robust, and more sensitive, than the original sci-RNA-seq3 protocol, with reagent costs on the order of 1 cent per cell or less. We showcase the optimized protocol via whole organism analysis of an E16.5 mouse embryo, profiling ~380,000 nuclei in a single experiment. Finally, we introduce a "tiny sci-*" protocol for experiments where input is extremely limited.
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