Automated human induced pluripotent stem cell culture and sample preparation for 3D live-cell microscopy.

To produce abundant cell culture samples to generate large, standardized image datasets of human induced pluripotent stem (hiPS) cells, we developed an automated workflow on a Hamilton STAR liquid handler system. This was developed specifically for culturing hiPS cell lines expressing fluorescently tagged proteins, which we have used to study the principles by which cells establish and maintain robust dynamic localization of cellular structures. This protocol includes all details for the maintenance, passage and seeding of cells, as well as Matrigel coating of 6-well plastic plates and 96-well optical-grade, glass plates. We also developed an automated image-based hiPS cell colony segmentation and feature extraction pipeline to streamline the process of predicting cell count and selecting wells with consistent morphology for high-resolution three-dimensional (3D) microscopy. The imaging samples produced with this protocol have been used to study the integrated intracellular organization and cell-to-cell variability of hiPS cells to train and develop deep learning-based label-free predictions from transmitted-light microscopy images and to develop deep learning-based generative models of single-cell organization. This protocol requires some experience with robotic equipment. However, we provide details and source code to facilitate implementation by biologists less experienced with robotics. The protocol is completed in less than 10 h with minimal human interaction. Overall, automation of our cell culture procedures increased our imaging samples' standardization, reproducibility, scalability and consistency. It also reduced the need for stringent culturist training and eliminated culturist-to-culturist variability, both of which were previous pain points of our original manual pipeline workflow.

Integrated intracellular organization and its variations in human iPS cells.

Understanding how a subset of expressed genes dictates cellular phenotype is a considerable challenge owing to the large numbers of molecules involved, their combinatorics and the plethora of cellular behaviours that they determine1,2. Here we reduced this complexity by focusing on cellular organization-a key readout and driver of cell behaviour3,4-at the level of major cellular structures that represent distinct organelles and functional machines, and generated the WTC-11 hiPSC Single-Cell Image Dataset v1, which contains more than 200,000 live cells in 3D, spanning 25 key cellular structures. The scale and quality of this dataset permitted the creation of a generalizable analysis framework to convert raw image data of cells and their structures into dimensionally reduced, quantitative measurements that can be interpreted by humans, and to facilitate data exploration. This framework embraces the vast cell-to-cell variability that is observed within a normal population, facilitates the integration of cell-by-cell structural data and allows quantitative analyses of distinct, separable aspects of organization within and across different cell populations. We found that the integrated intracellular organization of interphase cells was robust to the wide range of variation in cell shape in the population; that the average locations of some structures became polarized in cells at the edges of colonies while maintaining the 'wiring' of their interactions with other structures; and that, by contrast, changes in the location of structures during early mitotic reorganization were accompanied by changes in their wiring.

Fluorescent Gene Tagging of Transcriptionally Silent Genes in hiPSCs.

We describe a multistep method for endogenous tagging of transcriptionally silent genes in human induced pluripotent stem cells (hiPSCs). A monomeric EGFP (mEGFP) fusion tag and a constitutively expressed mCherry fluorescence selection cassette were delivered in tandem via homology-directed repair to five genes not expressed in hiPSCs but important for cardiomyocyte sarcomere function: TTN, MYL7, MYL2, TNNI1, and ACTN2. CRISPR/Cas9 was used to deliver the selection cassette and subsequently mediate its excision via microhomology-mediated end-joining and non-homologous end-joining. Most excised clones were effectively tagged, and all properly tagged clones expressed the mEGFP fusion protein upon differentiation into cardiomyocytes, allowing live visualization of these cardiac proteins at the sarcomere. This methodology provides a broadly applicable strategy for endogenously tagging transcriptionally silent genes in hiPSCs, potentially enabling their systematic and dynamic study during differentiation and morphogenesis.

Endogenous Protein Tagging in Human Induced Pluripotent Stem Cells Using CRISPR/Cas9.

A protocol is presented for generating human induced pluripotent stem cells (hiPSCs) that express endogenous proteins fused to in-frame N- or C-terminal fluorescent tags. The prokaryotic CRISPR/Cas9 system (clustered regularly interspaced short palindromic repeats/CRISPR-associated 9) may be used to introduce large exogenous sequences into genomic loci via homology directed repair (HDR). To achieve the desired knock-in, this protocol employs the ribonucleoprotein (RNP)-based approach where wild type Streptococcus pyogenes Cas9 protein, synthetic 2-part guide RNA (gRNA), and a donor template plasmid are delivered to the cells via electroporation. Putatively edited cells expressing the fluorescently tagged proteins are enriched by fluorescence activated cell sorting (FACS). Clonal lines are then generated and can be analyzed for precise editing outcomes. By introducing the fluorescent tag at the genomic locus of the gene of interest, the resulting subcellular localization and dynamics of the fusion protein can be studied under endogenous regulatory control, a key improvement over conventional overexpression systems. The use of hiPSCs as a model system for gene tagging provides the opportunity to study the tagged proteins in diploid, nontransformed cells. Since hiPSCs can be differentiated into multiple cell types, this approach provides the opportunity to create and study tagged proteins in a variety of isogenic cellular contexts.

Systematic gene tagging using CRISPR/Cas9 in human stem cells to illuminate cell organization.

We present a CRISPR/Cas9 genome-editing strategy to systematically tag endogenous proteins with fluorescent tags in human induced pluripotent stem cells (hiPSC). To date, we have generated multiple hiPSC lines with monoallelic green fluorescent protein tags labeling 10 proteins representing major cellular structures. The tagged proteins include alpha tubulin, beta actin, desmoplakin, fibrillarin, nuclear lamin B1, nonmuscle myosin heavy chain IIB, paxillin, Sec61 beta, tight junction protein ZO1, and Tom20. Our genome-editing methodology using Cas9/crRNA ribonuclear protein and donor plasmid coelectroporation, followed by fluorescence-based enrichment of edited cells, typically resulted in <0.1-4% homology-directed repair (HDR). Twenty-five percent of clones generated from each edited population were precisely edited. Furthermore, 92% (36/39) of expanded clonal lines displayed robust morphology, genomic stability, expression and localization of the tagged protein to the appropriate subcellular structure, pluripotency-marker expression, and multilineage differentiation. It is our conclusion that, if cell lines are confirmed to harbor an appropriate gene edit, pluripotency, differentiation potential, and genomic stability are typically maintained during the clonal line-generation process. The data described here reveal general trends that emerged from this systematic gene-tagging approach. Final clonal lines corresponding to each of the 10 cellular structures are now available to the research community.

A Single-Cell Roadmap of Lineage Bifurcation in Human ESC Models of Embryonic Brain Development.

During human brain development, multiple signaling pathways generate diverse cell types with varied regional identities. Here, we integrate single-cell RNA sequencing and clonal analyses to reveal lineage trees and molecular signals underlying early forebrain and mid/hindbrain cell differentiation from human embryonic stem cells (hESCs). Clustering single-cell transcriptomic data identified 41 distinct populations of progenitor, neuronal, and non-neural cells across our differentiation time course. Comparisons with primary mouse and human gene expression data demonstrated rostral and caudal progenitor and neuronal identities from early brain development. Bayesian analyses inferred a unified cell-type lineage tree that bifurcates between cortical and mid/hindbrain cell types. Two methods of clonal analyses confirmed these findings and further revealed the importance of Wnt/ß-catenin signaling in controlling this lineage decision. Together, these findings provide a rich transcriptome-based lineage map for studying human brain development and modeling developmental disorders.