Massively parallel nanowell-based single-cell gene expression profiling.

BACKGROUND: Technological advances have enabled transcriptome characterization of cell types at the single-cell level providing new biological insights. New methods that enable simple yet high-throughput single-cell expression profiling are highly desirable. RESULTS: Here we report a novel nanowell-based single-cell RNA sequencing system, ICELL8, which enables processing of thousands of cells per sample. The system employs a 5,184-nanowell-containing microchip to capture ~1,300 single cells and process them. Each nanowell contains preprinted oligonucleotides encoding poly-d(T), a unique well barcode, and a unique molecular identifier. The ICELL8 system uses imaging software to identify nanowells containing viable single cells and only wells with single cells are processed into sequencing libraries. Here, we report the performance and utility of ICELL8 using samples of increasing complexity from cultured cells to mouse solid tissue samples. Our assessment of the system to discriminate between mixed human and mouse cells showed that ICELL8 has a low cell multiplet rate (< 3%) and low cross-cell contamination. We characterized single-cell transcriptomes of more than a thousand cultured human and mouse cells as well as 468 mouse pancreatic islets cells. We were able to identify distinct cell types in pancreatic islets, including alpha, beta, delta and gamma cells. CONCLUSIONS: Overall, ICELL8 provides efficient and cost-effective single-cell expression profiling of thousands of cells, allowing researchers to decipher single-cell transcriptomes within complex biological samples.

Assay-agnostic spatial profiling detects tumor microenvironment signatures: new diagnostic insights for triple-negative breast cancer.

The role of the tumor microenvironment (TME) in immuno-oncology has driven demand for technologies that deliver in situ, or spatial, molecular information. Compartmentalized heterogeneity that traditional methods miss is becoming key to predicting both acquired drug resistance to targeted therapies and patient response to immunotherapy. Here, we describe a novel method for assay-agnostic spatial profiling and demonstrate its ability to detect immune microenvironment signatures in breast cancer patients that are unresolved by the immunohistochemical (IHC) assessment of programmed cell death ligand-1 (PD-L1) on immune cells, which represents the only FDA microenvironment-based companion diagnostic test that has been approved for triple-negative breast cancer (TNBC). Two distinct physiological states were found that are uncorrelated to tumor mutational burden (TMB), microsatellite instability (MSI), PD-L1 expression, and intrinsic cancer subtypes.

Taking qPCR to a higher level: Analysis of CNV reveals the power of high throughput qPCR to enhance quantitative resolution.

This paper assesses the quantitative resolution of qPCR using copy number variation (CNV) as a paradigm. An error model is developed for real-time qPCR data showing how the precision of CNV determination varies with the number of replicates. Using samples with varying numbers of X chromosomes, experimental data demonstrates that real-time qPCR can readily distinguish four copes from five copies, which corresponds to a 1.25-fold difference in relative quantity. Digital PCR is considered as an alternative form of qPCR. For digital PCR, an error model is shown that relates the precision of CNV determination to the number of reaction chambers. The quantitative capability of digital PCR is illustrated with an experiment distinguishing four and five copies of the human gene MRGPRX1. For either real-time qPCR or digital PCR, practical application of these models to achieve enhanced quantitative resolution requires use of a high throughput PCR platform that can simultaneously perform thousands of reactions. Comparing the two methods, real-time qPCR has the advantage of throughput and digital PCR has the advantage of simplicity in terms of the assumptions made for data analysis.

A multicenter study benchmarking single-cell RNA sequencing technologies using reference samples.

Comparing diverse single-cell RNA sequencing (scRNA-seq) datasets generated by different technologies and in different laboratories remains a major challenge. Here we address the need for guidance in choosing algorithms leading to accurate biological interpretations of varied data types acquired with different platforms. Using two well-characterized cellular reference samples (breast cancer cells and B cells), captured either separately or in mixtures, we compared different scRNA-seq platforms and several preprocessing, normalization and batch-effect correction methods at multiple centers. Although preprocessing and normalization contributed to variability in gene detection and cell classification, batch-effect correction was by far the most important factor in correctly classifying the cells. Moreover, scRNA-seq dataset characteristics (for example, sample and cellular heterogeneity and platform used) were critical in determining the optimal bioinformatic method. However, reproducibility across centers and platforms was high when appropriate bioinformatic methods were applied. Our findings offer practical guidance for optimizing platform and software selection when designing an scRNA-seq study.

Extending and evaluating a warfarin dosing algorithm that includes CYP4F2 and pooled rare variants of CYP2C9.

OBJECTIVE: Warfarin dosing remains challenging because of its narrow therapeutic window and large variability in dose response. We sought to analyze new factors involved in its dosing and to evaluate eight dosing algorithms, including two developed by the International Warfarin Pharmacogenetics Consortium (IWPC). METHODS: we enrolled 108 patients on chronic warfarin therapy and obtained complete clinical and pharmacy records; we genotyped single nucleotide polymorphisms relevant to the VKORC1, CYP2C9, and CYP4F2 genes using integrated fluidic circuits made by Fluidigm. RESULTS: When applying the IWPC pharmacogenetic algorithm to our cohort of patients, the percentage of patients within 1 mg/d of the therapeutic warfarin dose increases from 54% to 63% using clinical factors only, or from 38% using a fixed-dose approach. CYP4F2 adds 4% to the fraction of the variability in dose (R) explained by the IWPC pharmacogenetic algorithm (P<0.05). Importantly, we show that pooling rare variants substantially increases the R for CYP2C9 (rare variants: P=0.0065, R=6%; common variants: P=0.0034, R=7%; rare and common variants: P=0.00018; R=12%), indicating that relatively rare variants not genotyped in genome-wide association studies may be important. In addition, the IWPC pharmacogenetic algorithm and the Gage (2008) algorithm perform best (IWPC: R=50%; Gage: R=49%), and all pharmacogenetic algorithms outperform the IWPC clinical equation (R=22%). VKORC1 and CYP2C9 genotypes did not affect long-term variability in dose. Finally, the Fluidigm platform, a novel warfarin genotyping method, showed 99.65% concordance between different operators and instruments. CONCLUSION: CYP4F2 and pooled rare variants of CYP2C9 significantly improve the ability to estimate warfarin dose.

An essential role for a MEK-C/EBP pathway during growth factor-regulated cortical neurogenesis.

Mammalian neurogenesis is determined by an interplay between intrinsic genetic mechanisms and extrinsic cues such as growth factors. Here we have defined a signaling cascade, a MEK-C/EBP pathway, that is essential for cortical progenitor cells to become postmitotic neurons. Inhibition of MEK or of the C/EBP family of transcription factors inhibits neurogenesis while expression of a C/EBPbeta mutant that is a phosphorylation-mimic at a MEK-Rsk site enhances neurogenesis. C/EBP mediates this positive effect by direct transcriptional activation of neuron-specific genes such as Talpha1 alpha-tubulin. Conversely, inhibition of C/EBP-dependent transcription enhances CNTF-mediated generation of astrocytes from the same progenitor cells. Thus, activation of a MEK-C/EBP pathway enhances neurogenesis and inhibits gliogenesis, thereby providing a mechanism whereby growth factors can selectively bias progenitors to become neurons during development.

High-throughput chromatin accessibility profiling at single-cell resolution.

Here we develop a high-throughput single-cell ATAC-seq (assay for transposition of accessible chromatin) method to measure physical access to DNA in whole cells. Our approach integrates fluorescence imaging and addressable reagent deposition across a massively parallel (5184) nano-well array, yielding a nearly 20-fold improvement in throughput (up to ~1800 cells/chip, 4-5 h on-chip processing time) and library preparation cost (~81¢ per cell) compared to prior microfluidic implementations. We apply this method to measure regulatory variation in peripheral blood mononuclear cells (PBMCs) and show robust, de novo clustering of single cells by hematopoietic cell type.

Magnesium is required for specific DNA binding of the CREB B-ZIP domain.

We have examined binding of the CREB B-ZIP protein domain to double-stranded DNA containing a consensus CRE sequence (5'-TGACGTCA-3'), the related PAR, C/EBP and AP-1 sequences and the unrelated SP1 sequence. DNA binding was assayed in the presence or absence of MgCl2 and/or KCl using two methods: circular dichroism (CD) spectroscopy and electrophoretic mobility shift assay (EMSA). The CD assay allows us to measure equilibrium binding in solution. Thermal denaturation in 150 mM KCl indicates that the CREB B-ZIP domain binds all the DNA sequences, with highest affinity for the CRE site, followed by the PAR (5'-TAACGTTA-3'), C/EBP (5'-TTGCGCAA-3') and AP-1 (5'-TGAGTCA-3') sites. The addition of 10 mM MgCl2 diminished DNA binding to the CRE and PAR DNA sequences and abolished binding to the C/EBP and AP-1 DNA sequences, resulting in more sequence-specific DNA binding. Using 'standard' EMSA conditions (0.25x TBE), CREB bound all the DNA sequences examined. The CREB-CRE complex had an apparent Kd of approximately 300 pM, PAR of approximately 1 nM, C/EBP and AP-1 of approximately 3 nM and SP1 of approximately 30 nM. The addition of 10 mM MgCl2 to the polyacrylamide gel dramatically altered sequence-specific DNA binding. CREB binding affinity for CRE DNA decreased 3-fold, but binding to the other DNA sequences decreased >1000-fold. In the EMSA, addition of 150 mM KCl to the gels had an effect similar to MgCl2. The magnesium concentration needed to prevent non-specific electrostatic interactions between CREB and DNA in solution is in the physiological range and thus changes in magnesium concentration may be a cellular signal that regulates gene expression.

High throughput microRNA profiling: optimized multiplex qRT-PCR at nanoliter scale on the fluidigm dynamic arrayTM IFCs.

The broad involvement of miRNAs in critical processes underlying development, tissue homoeostasis and disease has led to a surging interest among the research and pharmaceutical communities. To study miRNAs, it is essential that the quantification of microRNA levels is accurate and robust. By comparing wild-type to small RNA deficient mouse embryonic stem cells (mESC), we revealed a lack of accuracy and robustness in previous published multiplex qRT-PCR techniques. Here, we describe an optimized method, including purifying away excessive primers from previous multiplex steps before singleplex real time detection, which dramatically increases the accuracy and robustness of the technique. Furthermore, we explain how performing the technique on a microfluidic chip at nanoliter volumes significantly reduces reagent costs and permits time effective high throughput miRNA expression profiling.

IL-6 controls leukemic multipotent progenitor cell fate and contributes to chronic myelogenous leukemia development.

Using a mouse model recapitulating the main features of human chronic myelogenous leukemia (CML), we uncover the hierarchy of leukemic stem and progenitor cells contributing to disease pathogenesis. We refine the characterization of CML leukemic stem cells (LSCs) to the most immature long-term hematopoietic stem cells (LT-HSCs) and identify some important molecular deregulations underlying their aberrant behavior. We find that CML multipotent progenitors (MPPs) exhibit an aberrant B-lymphoid potential but are redirected toward the myeloid lineage by the action of the proinflammatory cytokine IL-6. We show that BCR/ABL activity controls Il-6 expression thereby establishing a paracrine feedback loop that sustains CML development. These results describe how proinflammatory tumor environment affects leukemic progenitor cell fate and contributes to CML pathogenesis.

Elovl3: a model gene to dissect homeostatic links between the circadian clock and nutritional status.

The ELOVL3 protein is a very long-chain fatty acid elongase found in liver, skin, and brown adipose tissues. Circadian expression of the Elovl3 gene in the liver is perturbed in mutant CLOCK mice but persists in mice with severe hepatic dysfunction. A reliance on an intact clock, combined with the refractoriness to liver decompensation and the finding of a robust sexually dimorphic pattern of expression, evince a particularly complex mode of transcriptional control. The Elovl3 gene upstream region was repressed by RevErbalpha and activated by sterol-regulatory element binding protein-1 (SREBP1) transcription factors. We propose that the temporal coordination of RevErbalpha and SREBP1 activities integrates clock and nutrition signals to drive a subset of oscillatory transcripts in the liver. Proteolytic activation of SREBP1 is circadian in the liver, and because the cycle of SREBP1 activation was reversed after restricting meals to the inactive phase of the day, this factor could serve as an acute sensor of nutritional state. SREBP1 regulates many known lipogenic and cholesterogenic circadian genes; hence, our results could explain how feeding can override brain-derived entraining signals in the liver. This mechanism would permit a rapid adjustment in the sequence of key aspects of the absorptive and postabsorptive phases in the liver.

Clustering of DNA sequences in human promoters.

We have determined the distribution of each of the 65,536 DNA sequences that are eight bases long (8-mer) in a set of 13,010 human genomic promoter sequences aligned relative to the putative transcription start site (TSS). A limited number of 8-mers have peaks in their distribution (cluster), and most cluster within 100 bp of the TSS. The 156 DNA sequences exhibiting the greatest statistically significant clustering near the TSS can be placed into nine groups of related sequences. Each group is defined by a consensus sequence, and seven of these consensus sequences are known binding sites for the transcription factors (TFs) SP1, NF-Y, ETS, CREB, TBP, USF, and NRF-1. One sequence, which we named Clus1, is not a known TF binding site. The ninth sequence group is composed of the strand-specific Kozak sequence that clusters downstream of the TSS. An examination of the co-occurrence of these TF consensus sequences indicates a positive correlation for most of them except for sequences bound by TBP (the TATA box). Human mRNA expression data from 29 tissues indicate that the ETS, NRF-1, and Clus1 sequences that cluster are predominantly found in the promoters of housekeeping genes (e.g., ribosomal genes). In contrast, TATA is more abundant in the promoters of tissue-specific genes. This analysis identified eight DNA sequences in 5082 promoters that we suggest are important for regulating gene expression.

A search for candidate genes for lipodystrophy, obesity and diabetes via gene expression analysis of A-ZIP/F-1 mice.

Genome scans for diabetes have identified many regions of the human genome that correlate with the disease state. To identify candidate genes for type 2 diabetes, we examined the transgenic A-ZIP/F-1 mouse. This mouse model has no white fat, resulting in abnormal levels of glucose, insulin, and leptin, making the A-ZIP/F-1 mice a good model for lipodystrophy and insulin resistance. We used cDNA-based microarrays to find differentially expressed genes in four tissues of these mice. We examined these results in the context of human linkage scans for lipodystrophy, obesity, and type 2 diabetes. We combined 199 known human orthologs of the misregulated mouse genes with 33 published human genome scans on a genome map. Integrating expression data with human linkage results permitted us to suggest and prioritize candidate genes for lipodystrophy and related disorders. These genes include a cluster of 3 S100A genes on chromosome 1 and SLPI1 on chromosome 20.