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.

Charting cellular identity during human in vitro ß-cell differentiation.

In vitro differentiation of human stem cells can produce pancreatic ß-cells; the loss of this insulin-secreting cell type underlies type 1 diabetes. Here, as a step towards understanding this differentiation process, we report the transcriptional profiling of more than 100,000 human cells undergoing in vitro ß-cell differentiation, and describe the cells that emerged. We resolve populations that correspond to ß-cells, α-like poly-hormonal cells, non-endocrine cells that resemble pancreatic exocrine cells and a previously unreported population that resembles enterochromaffin cells. We show that endocrine cells maintain their identity in culture in the absence of exogenous growth factors, and that changes in gene expression associated with in vivo ß-cell maturation are recapitulated in vitro. We implement a scalable re-aggregation technique to deplete non-endocrine cells and identify CD49a (also known as ITGA1) as a surface marker of the ß-cell population, which allows magnetic sorting to a purity of 80%. Finally, we use a high-resolution sequencing time course to characterize gene-expression dynamics during the induction of human pancreatic endocrine cells, from which we develop a lineage model of in vitro ß-cell differentiation. This study provides a perspective on human stem-cell differentiation, and will guide future endeavours that focus on the differentiation of pancreatic islet cells, and their applications in regenerative medicine.

Engineering human stem cell-derived islets to evade immune rejection and promote localized immune tolerance.

Immunological protection of transplanted stem cell-derived islet (SC-islet) cells is yet to be achieved without chronic immunosuppression or encapsulation. Existing genetic engineering approaches to produce immune-evasive SC-islet cells have so far shown variable results. Here, we show that targeting human leukocyte antigens (HLAs) and PD-L1 alone does not sufficiently protect SC-islet cells from xenograft (xeno)- or allograft (allo)-rejection. As an addition to these approaches, we genetically engineer SC-islet cells to secrete the cytokines interleukin-10 (IL-10), transforming growth factor ß (TGF-ß), and modified IL-2 such that they promote a tolerogenic local microenvironment by recruiting regulatory T cells (Tregs) to the islet grafts. Cytokine-secreting human SC-ß cells resist xeno-rejection and correct diabetes for up to 8 weeks post-transplantation in non-obese diabetic (NOD) mice. Thus, genetically engineering human embryonic SCs (hESCs) to induce a tolerogenic local microenvironment represents a promising approach to provide SC-islet cells as a cell replacement therapy for diabetes without the requirement for encapsulation or immunosuppression.

A method for the generation of human stem cell-derived alpha cells.

The generation of pancreatic cell types from renewable cell sources holds promise for cell replacement therapies for diabetes. Although most effort has focused on generating pancreatic beta cells, considerable evidence indicates that glucagon secreting alpha cells are critically involved in disease progression and proper glucose control. Here we report on the generation of stem cell-derived human pancreatic alpha (SC-alpha) cells from pluripotent stem cells via a transient pre-alpha cell intermediate. These pre-alpha cells exhibit a transcriptional profile similar to mature alpha cells and although they produce proinsulin protein, they do not secrete significant amounts of processed insulin. Compound screening identified a protein kinase c activator that promotes maturation of pre-alpha cells into SC-alpha cells. The resulting SC-alpha cells do not express insulin, share an ultrastructure similar to cadaveric alpha cells, express and secrete glucagon in response to glucose and some glucagon secretagogues, and elevate blood glucose upon transplantation in mice.

Identifying gene expression programs of cell-type identity and cellular activity with single-cell RNA-Seq.

Identifying gene expression programs underlying both cell-type identity and cellular activities (e.g. life-cycle processes, responses to environmental cues) is crucial for understanding the organization of cells and tissues. Although single-cell RNA-Seq (scRNA-Seq) can quantify transcripts in individual cells, each cell's expression profile may be a mixture of both types of programs, making them difficult to disentangle. Here, we benchmark and enhance the use of matrix factorization to solve this problem. We show with simulations that a method we call consensus non-negative matrix factorization (cNMF) accurately infers identity and activity programs, including their relative contributions in each cell. To illustrate the insights this approach enables, we apply it to published brain organoid and visual cortex scRNA-Seq datasets; cNMF refines cell types and identifies both expected (e.g. cell cycle and hypoxia) and novel activity programs, including programs that may underlie a neurosecretory phenotype and synaptogenesis.

Single-cell barcoding and sequencing using droplet microfluidics.

Single-cell RNA sequencing has recently emerged as a powerful tool for mapping cellular heterogeneity in diseased and healthy tissues, yet high-throughput methods are needed for capturing the unbiased diversity of cells. Droplet microfluidics is among the most promising candidates for capturing and processing thousands of individual cells for whole-transcriptome or genomic analysis in a massively parallel manner with minimal reagent use. We recently established a method called inDrops, which has the capability to index >15,000 cells in an hour. A suspension of cells is first encapsulated into nanoliter droplets with hydrogel beads (HBs) bearing barcoding DNA primers. Cells are then lysed and mRNA is barcoded (indexed) by a reverse transcription (RT) reaction. Here we provide details for (i) establishing an inDrops platform (1 d); (ii) performing hydrogel bead synthesis (4 d); (iii) encapsulating and barcoding cells (1 d); and (iv) RNA-seq library preparation (2 d). inDrops is a robust and scalable platform, and it is unique in its ability to capture and profile >75% of cells in even very small samples, on a scale of thousands or tens of thousands of cells.

A Single-Cell Transcriptomic Map of the Human and Mouse Pancreas Reveals Inter- and Intra-cell Population Structure.

Although the function of the mammalian pancreas hinges on complex interactions of distinct cell types, gene expression profiles have primarily been described with bulk mixtures. Here we implemented a droplet-based, single-cell RNA-seq method to determine the transcriptomes of over 12,000 individual pancreatic cells from four human donors and two mouse strains. Cells could be divided into 15 clusters that matched previously characterized cell types: all endocrine cell types, including rare epsilon-cells; exocrine cell types; vascular cells; Schwann cells; quiescent and activated stellate cells; and four types of immune cells. We detected subpopulations of ductal cells with distinct expression profiles and validated their existence with immuno-histochemistry stains. Moreover, among human beta- cells, we detected heterogeneity in the regulation of genes relating to functional maturation and levels of ER stress. Finally, we deconvolved bulk gene expression samples using the single-cell data to detect disease-associated differential expression. Our dataset provides a resource for the discovery of novel cell type-specific transcription factors, signaling receptors, and medically relevant genes.

Delayed commitment to evolutionary fate in antibiotic resistance fitness landscapes.

Predicting evolutionary paths to antibiotic resistance is key for understanding and controlling drug resistance. When considering a single final resistant genotype, epistatic contingencies among mutations restrict evolution to a small number of adaptive paths. Less attention has been given to multi-peak landscapes, and while specific peaks can be favoured, it is unknown whether and how early a commitment to final fate is made. Here we characterize a multi-peaked adaptive landscape for trimethoprim resistance by constructing all combinatorial alleles of seven resistance-conferring mutations in dihydrofolate reductase. We observe that epistatic interactions increase rather than decrease the accessibility of each peak; while they restrict the number of direct paths, they generate more indirect paths, where mutations are adaptively gained and later adaptively lost or changed. This enhanced accessibility allows evolution to proceed through many adaptive steps while delaying commitment to genotypic fate, hindering our ability to predict or control evolutionary outcomes.

An augmented SMS intervention to improve access to antenatal CD4 testing and ART initiation in HIV-infected pregnant women: a cluster randomized trial.

BACKGROUND: Less than one-third of HIV-infected pregnant women eligible for combination antiretroviral therapy (ART) globally initiate treatment prior to delivery, with lack of access to timely CD4 results being a principal barrier. We evaluated the effectiveness of an SMS-based intervention to improve access to timely antenatal ART. METHODS: We conducted a stepped-wedge cluster randomized trial of a low-cost programmatic intervention in 20 antenatal clinics in Gaborone, Botswana. From July 2011-April 2012, 2 clinics were randomly selected every 4 weeks to receive an ongoing clinic-based educational intervention to improve CD4 collection and to receive CD4 results via an automated SMS platform with active patient tracing. CD4 testing before 26 weeks gestation and ART initiation before 30 weeks gestation were assessed. RESULTS: Three-hundred-sixty-six ART-naïve women were included, 189 registering for antenatal care under Intervention and 177 under Usual Care periods. Of CD4-eligible women, 100 (59.2%) women under Intervention and 79 (50.6%) women under Usual Care completed CD4 phlebotomy before 26 weeks gestation, adjusted odds ratio (aOR, adjusted for time that a clinic initiated Intervention) 0.87 (95% confidence interval [CI]0.47-1.63, P = 0.67). The SMS-based platform reduced time to clinic receipt of CD4 test result from median of 16 to 6 days (P<0.001), was appreciated by clinic staff, and was associated with reduced operational cost. However, rates of ART initiation remained low, with 56 (36.4%) women registering under Intervention versus 37 (24.2%) women under Usual Care initiating ART prior to 30 weeks gestation, aOR 1.06 (95%CI 0.53-2.13, P = 0.87). CONCLUSIONS: The augmented SMS-based intervention delivered CD4 results more rapidly and efficiently, and this type of SMS-based results delivery platform may be useful for a variety of tests and settings. However, the intervention did not appear to improve access to timely antenatal CD4 testing or ART initiation, as obstacles other than CD4 impeded ART initiation during pregnancy.

Low incidence of off-target mutations in individual CRISPR-Cas9 and TALEN targeted human stem cell clones detected by whole-genome sequencing.

Genome editing has attracted wide interest for the generation of cellular models of disease using human pluripotent stem cells and other cell types. CRISPR-Cas systems and TALENs can target desired genomic sites with high efficiency in human cells, but recent publications have led to concern about the extent to which these tools may cause off-target mutagenic effects that could potentially confound disease-modeling studies. Using CRISPR-Cas9 and TALEN targeted human pluripotent stem cell clones, we performed whole-genome sequencing at high coverage in order to assess the degree of mutagenesis across the entire genome. In both types of clones, we found that off-target mutations attributable to the nucleases were very rare. From this analysis, we suggest that, although some cell types may be at risk for off-target mutations, the incidence of such effects in human pluripotent stem cells may be sufficiently low and thus not a significant concern for disease modeling and other applications.

Building a morbidostat: an automated continuous-culture device for studying bacterial drug resistance under dynamically sustained drug inhibition.

We present a protocol for building and operating an automated fluidic system for continuous culture that we call the 'morbidostat'. The morbidostat is used to follow the evolution of microbial drug resistance in real time. Instead of exposing bacteria to predetermined drug environments, the morbidostat constantly measures the growth rates of evolving microbial populations and dynamically adjusts drug concentrations inside culture vials in order to maintain a constant drug-induced inhibition. The growth rate measurements are done using an optical detection system that is based on measuring the intensity of back-scattered light from bacterial cells suspended in the liquid culture. The morbidostat can additionally be used as a chemostat or a turbidostat. The whole system can be built from readily available components within 2-3 weeks by biologists with some electronics experience or engineers familiar with basic microbiology.

A TALEN genome-editing system for generating human stem cell-based disease models.

Transcription activator-like effector nucleases (TALENs) are a new class of engineered nucleases that are easier to design to cleave at desired sites in a genome than previous types of nucleases. We report here the use of TALENs to rapidly and efficiently generate mutant alleles of 15 genes in cultured somatic cells or human pluripotent stem cells, the latter for which we differentiated both the targeted lines and isogenic control lines into various metabolic cell types. We demonstrate cell-autonomous phenotypes directly linked to disease-dyslipidemia, insulin resistance, hypoglycemia, lipodystrophy, motor-neuron death, and hepatitis C infection. We found little evidence of TALEN off-target effects, but each clonal line nevertheless harbors a significant number of unique mutations. Given the speed and ease with which we were able to derive and characterize these cell lines, we anticipate TALEN-mediated genome editing of human cells becoming a mainstay for the investigation of human biology and disease.

Evolutionary paths to antibiotic resistance under dynamically sustained drug selection.

Antibiotic resistance can evolve through the sequential accumulation of multiple mutations. To study such gradual evolution, we developed a selection device, the 'morbidostat', that continuously monitors bacterial growth and dynamically regulates drug concentrations, such that the evolving population is constantly challenged. We analyzed the evolution of resistance in Escherichia coli under selection with single drugs, including chloramphenicol, doxycycline and trimethoprim. Over a period of ∼20 days, resistance levels increased dramatically, with parallel populations showing similar phenotypic trajectories. Whole-genome sequencing of the evolved strains identified mutations both specific to resistance to a particular drug and shared in resistance to multiple drugs. Chloramphenicol and doxycycline resistance evolved smoothly through diverse combinations of mutations in genes involved in translation, transcription and transport. In contrast, trimethoprim resistance evolved in a stepwise manner, through mutations restricted to the gene encoding the enzyme dihydrofolate reductase (DHFR). Sequencing of DHFR over the time course of the experiment showed that parallel populations evolved similar mutations and acquired them in a similar order.

Quantitative analysis of culture using millions of digitized books.

We constructed a corpus of digitized texts containing about 4% of all books ever printed. Analysis of this corpus enables us to investigate cultural trends quantitatively. We survey the vast terrain of 'culturomics,' focusing on linguistic and cultural phenomena that were reflected in the English language between 1800 and 2000. We show how this approach can provide insights about fields as diverse as lexicography, the evolution of grammar, collective memory, the adoption of technology, the pursuit of fame, censorship, and historical epidemiology. Culturomics extends the boundaries of rigorous quantitative inquiry to a wide array of new phenomena spanning the social sciences and the humanities.