Microfluidics-free single-cell genomics with templated emulsification

Single-cell RNA sequencing is now a standard method used to reveal the molecular details of cellular heterogeneity, but current approaches have limitations on speed, scale, and ease of use that stem from the complex microfluidic devices or fluid handling steps required for sample processing. We, therefore, developed a method that does not require specialized microfluidic devices, expertise, or hardware. Our approach is based on particle-templated emulsification, which allows single-cell encapsulation and barcoding of cDNA in uniform droplet emulsions with only a vortexer. PIP-seq accommodates a wide range of emulsification formats, including microwell plates and large-volume conical tubes, enabling thousands of samples or millions of cells to be processed in minutes. We demonstrate that PIP-seq produces high-purity transcriptomes in mouse-human mixing studies, is compatible with multi-omics measurements, and can accurately characterize cell types in human breast tissue when compared to a commercial microfluidic platform. Single-cell transcriptional profiling of mixed phenotype acute leukemia using PIP-seq revealed the emergence of heterogeneity within chemotherapy-resistant cell subsets that were hidden by standard immunophenotyping. PIP-seq is a simple, flexible, and scalable next-generation workflow that extends single-cell sequencing to new applications, including screening, diagnostics, and disease monitoring.

[1]  R. J. Weber,et al.  Mapping hormone-regulated cell-cell interaction networks in the human breast at single-cell resolution. , 2022, Cell systems.

[2]  S. Quake The Tabula Sapiens: a multiple organ single cell transcriptomic atlas of humans , 2021, bioRxiv.

[3]  Paul J. Hoffman,et al.  Dictionary learning for integrative, multimodal and scalable single-cell analysis , 2022, bioRxiv.

[4]  J. Marioni,et al.  StabMap: Mosaic single cell data integration using non-overlapping features , 2022, bioRxiv.

[5]  S. Aerts,et al.  Hydrop enables droplet-based single-cell ATAC-seq and single-cell RNA-seq using dissolvable hydrogel beads , 2022, eLife.

[6]  Thomas M. Norman,et al.  Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq , 2021, Cell.

[7]  R. Pearson,et al.  Ribosomal proteins and human diseases: molecular mechanisms and targeted therapy , 2021, Signal Transduction and Targeted Therapy.

[8]  S. Picelli,et al.  Lightning Fast and Highly Sensitive Full-Length Single-cell sequencing using FLASH-Seq , 2021, bioRxiv.

[9]  P. Neufer,et al.  Intrinsic OXPHOS limitations underlie cellular bioenergetics in leukemia , 2021, eLife.

[10]  André F. Rendeiro,et al.  Ultra-high-throughput single-cell RNA sequencing and perturbation screening with combinatorial fluidic indexing , 2021, Nature Methods.

[11]  Deanne M. Taylor,et al.  A roadmap for the Human Developmental Cell Atlas , 2021, Nature.

[12]  André F. Rendeiro,et al.  A molecular single-cell lung atlas of lethal COVID-19 , 2021, Nature.

[13]  Ariel J. Levine,et al.  Confronting false discoveries in single-cell differential expression , 2021, Nature Communications.

[14]  Zhigang Lu,et al.  Oxidative phosphorylation enhances the leukemogenic capacity and resistance to chemotherapy of B cell acute lymphoblastic leukemia , 2021, Science Advances.

[15]  Raphael Gottardo,et al.  Integrated analysis of multimodal single-cell data , 2020, Cell.

[16]  A. Abate,et al.  Modular barcode beads for microfluidic single cell genomics , 2020, Scientific Reports.

[17]  A. Abate,et al.  Joint profiling of DNA and proteins in single cells to dissect genotype-phenotype associations in leukemia , 2020, Nature Communications.

[18]  J. C. Love,et al.  Second-Strand Synthesis-Based Massively Parallel scRNA-Seq Reveals Cellular States and Molecular Features of Human Inflammatory Skin Pathologies , 2020, Immunity.

[19]  Aviv Regev,et al.  Chromatin Potential Identified by Shared Single-Cell Profiling of RNA and Chromatin , 2020, Cell.

[20]  Monika S. Kowalczyk,et al.  Systematic comparison of single-cell and single-nucleus RNA-sequencing methods , 2020, Nature Biotechnology.

[21]  Thomas M. Norman,et al.  Combinatorial single-cell CRISPR screens by direct guide RNA capture and targeted sequencing , 2020, Nature Biotechnology.

[22]  Dan Zhang,et al.  Construction of a human cell landscape at single-cell level , 2020, Nature.

[23]  Ben S. Wittner,et al.  Deregulation of ribosomal protein expression and translation promotes breast cancer metastasis , 2020, Science.

[24]  Thomas M. Norman,et al.  Titrating gene expression using libraries of systematically attenuated CRISPR guide RNAs , 2019, Nature Biotechnology.

[25]  Thomas M. Norman,et al.  Titrating gene expression using libraries of systematically attenuated CRISPR guide RNAs , 2019, Nature Biotechnology.

[26]  R. Sandberg,et al.  Single-cell RNA counting at allele and isoform resolution using Smart-seq3 , 2019, Nature Biotechnology.

[27]  Howard Y. Chang,et al.  Single-cell multiomic analysis identifies regulatory programs in mixed-phenotype acute leukemia , 2019, Nature Biotechnology.

[28]  Sergey O. Sulima,et al.  Hallmarks of ribosomopathies , 2019, Nucleic acids research.

[29]  Jennifer L Hu,et al.  MULTI-seq: sample multiplexing for single-cell RNA sequencing using lipid-tagged indices , 2019, Nature Methods.

[30]  Martin J. Aryee,et al.  Epigenetic evolution and lineage histories of chronic lymphocytic leukemia , 2019, Nature.

[31]  R. Pearson,et al.  First-in-Human RNA Polymerase I Transcription Inhibitor CX-5461 in Patients with Advanced Hematological Cancers: Results of a Phase I Dose Escalation Study. , 2019, Cancer discovery.

[32]  Rafael C. Schulman,et al.  Epigenetic evolution and lineage histories of chronic lymphocytic leukemia , 2019, Nature.

[33]  Samantha Riesenfeld,et al.  EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data , 2019, Genome Biology.

[34]  Andrew J. Hill,et al.  The single cell transcriptional landscape of mammalian organogenesis , 2019, Nature.

[35]  Todd M. Gierahn,et al.  Seq-Well: A Sample-Efficient, Portable Picowell Platform for Massively Parallel Single-Cell RNA Sequencing. , 2019, Methods in molecular biology.

[36]  Bertrand Z. Yeung,et al.  Cell Hashing with barcoded antibodies enables multiplexing and doublet detection for single cell genomics , 2018, Genome Biology.

[37]  A. Abate,et al.  Microfluidic bead encapsulation above 20 kHz with triggered drop formation† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c8lc00514a , 2018, Lab on a chip.

[38]  R. J. Weber,et al.  Changes in epithelial proportions and transcriptional state underlie major premenopausal breast cancer risks , 2018, bioRxiv.

[39]  Steven J. M. Jones,et al.  The genetic basis and cell of origin of mixed phenotype acute leukaemia , 2018, Nature.

[40]  P. A. Futreal,et al.  Integrative genomic analysis of adult mixed phenotype acute leukemia delineates lineage associated molecular subtypes , 2018, Nature Communications.

[41]  Avi Srivastava,et al.  Alevin efficiently estimates accurate gene abundances from dscRNA-seq data , 2018, Genome Biology.

[42]  A. Abate,et al.  Particle-Templated Emulsification for Microfluidics-Free Digital Biology , 2018, bioRxiv.

[43]  Richard A. Muscat,et al.  Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding , 2018, Science.

[44]  H. Swerdlow,et al.  Large-scale simultaneous measurement of epitopes and transcriptomes in single cells , 2017, Nature Methods.

[45]  John R. Haliburton,et al.  Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding , 2017, Scientific Reports.

[46]  Geet Duggal,et al.  Salmon: fast and bias-aware quantification of transcript expression using dual-phase inference , 2017, Nature Methods.

[47]  Rob Patro,et al.  Salmon provides fast and bias-aware quantification of transcript expression , 2017, Nature Methods.

[48]  I. Hellmann,et al.  Comparative Analysis of Single-Cell RNA Sequencing Methods , 2016, bioRxiv.

[49]  Andrew C. Adey,et al.  Single-Cell Transcriptional Profiling of a Multicellular Organism , 2017 .

[50]  J. C. Love,et al.  Seq-Well: A Portable, Low-Cost Platform for High-Throughput Single-Cell RNA-Seq of Low-Input Samples , 2017, Nature Methods.

[51]  Laura Fancello,et al.  The ribosomal protein gene RPL5 is a haploinsufficient tumor suppressor in multiple cancer types , 2017, Oncotarget.

[52]  Allon M. Klein,et al.  Single-cell barcoding and sequencing using droplet microfluidics , 2016, Nature Protocols.

[53]  André F. Rendeiro,et al.  Pooled CRISPR screening with single-cell transcriptome read-out , 2017, Nature Methods.

[54]  Thomas M. Norman,et al.  Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens , 2016, Cell.

[55]  E. Mejstrikova,et al.  Distinct bilineal leukemia immunophenotypes are not genetically determined. , 2016, Blood.

[56]  M. Malumbres CDK4/6 Inhibitors resTORe Therapeutic Sensitivity in HER²⁺ Breast Cancer. , 2016, Cancer cell.

[57]  Antoni Ribas,et al.  Single-cell analysis tools for drug discovery and development , 2015, Nature Reviews Drug Discovery.

[58]  Andrew C. Adey,et al.  Multiplex single-cell profiling of chromatin accessibility by combinatorial cellular indexing , 2015, Science.

[59]  Evan Z. Macosko,et al.  Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets , 2015, Cell.

[60]  Andrew C. Adey,et al.  Haplotype-resolved whole-genome sequencing by contiguity-preserving transposition and combinatorial indexing , 2014, Nature Genetics.

[61]  Åsa K. Björklund,et al.  Full-length RNA-seq from single cells using Smart-seq2 , 2014, Nature Protocols.

[62]  Xiangpeng Li,et al.  Creating biocompatible oil-water interfaces without synthesis: direct interactions between primary amines and carboxylated perfluorocarbon surfactants. , 2013, Analytical chemistry.

[63]  Åsa K. Björklund,et al.  Smart-seq2 for sensitive full-length transcriptome profiling in single cells , 2013, Nature Methods.

[64]  M. Stampfer,et al.  Processing of Human Reduction Mammoplasty and Mastectomy Tissues for Cell Culture , 2013, Journal of visualized experiments : JoVE.

[65]  Stein Aerts,et al.  Exome sequencing identifies mutation in CNOT3 and ribosomal genes RPL5 and RPL10 in T-cell acute lymphoblastic leukemia , 2012, Nature Genetics.

[66]  A. Look,et al.  Inactivation of ribosomal protein L22 promotes transformation by induction of the stemness factor, Lin28B. , 2012, Blood.

[67]  Yih-Leong Chang,et al.  TROP2 is epigenetically inactivated and modulates IGF-1R signalling in lung adenocarcinoma , 2012, EMBO molecular medicine.

[68]  T. Kalina,et al.  Prognosis of children with mixed phenotype acute leukemia treated on the basis of consistent immunophenotypic criteria , 2010, Haematologica.

[69]  Catalin C. Barbacioru,et al.  mRNA-Seq whole-transcriptome analysis of a single cell , 2009, Nature Methods.

[70]  Davide Ruggero,et al.  Suppression of Myc oncogenic activity by ribosomal protein haploinsufficiency , 2008, Nature.

[71]  B. Ducommun,et al.  G2/M checkpoint stringency is a key parameter in the sensitivity of AML cells to genotoxic stress , 2008, Oncogene.

[72]  P. Jeggo,et al.  The impact of a negligent G2/M checkpoint on genomic instability and cancer induction , 2007, Nature Reviews Cancer.

[73]  D. Weitz,et al.  Dripping to jetting transitions in coflowing liquid streams. , 2007, Physical review letters.

[74]  J. Eberwine,et al.  Analysis of gene expression in single live neurons. , 1992, Proceedings of the National Academy of Sciences of the United States of America.