Scalable genetic screening for regulatory circuits using compressed Perturb-seq.

Pooled CRISPR screens with single-cell RNA sequencing readout (Perturb-seq) have emerged as a key technique in functional genomics, but they are limited in scale by cost and combinatorial complexity. In this study, we modified the design of Perturb-seq by incorporating algorithms applied to random, low-dimensional observations. Compressed Perturb-seq measures multiple random perturbations per cell or multiple cells per droplet and computationally decompresses these measurements by leveraging the sparse structure of regulatory circuits. Applied to 598 genes in the immune response to bacterial lipopolysaccharide, compressed Perturb-seq achieves the same accuracy as conventional Perturb-seq with an order of magnitude cost reduction and greater power to learn genetic interactions. We identified known and novel regulators of immune responses and uncovered evolutionarily constrained genes with downstream targets enriched for immune disease heritability, including many missed by existing genome-wide association studies. Our framework enables new scales of interrogation for a foundational method in functional genomics.

Systematically characterizing the roles of E3-ligase family members in inflammatory responses with massively parallel Perturb-seq.

E3 ligases regulate key processes, but many of their roles remain unknown. Using Perturb-seq, we interrogated the function of 1,130 E3 ligases, partners and substrates in the inflammatory response in primary dendritic cells (DCs). Dozens impacted the balance of DC1, DC2, migratory DC and macrophage states and a gradient of DC maturation. Family members grouped into co-functional modules that were enriched for physical interactions and impacted specific programs through substrate transcription factors. E3s and their adaptors co-regulated the same processes, but partnered with different substrate recognition adaptors to impact distinct aspects of the DC life cycle. Genetic interactions were more prevalent within than between modules, and a deep learning model, comßVAE, predicts the outcome of new combinations by leveraging modularity. The E3 regulatory network was associated with heritable variation and aberrant gene expression in immune cells in human inflammatory diseases. Our study provides a general approach to dissect gene function.

Compressed Perturb-seq: highly efficient screens for regulatory circuits using random composite perturbations.

Pooled CRISPR screens with single-cell RNA-seq readout (Perturb-seq) have emerged as a key technique in functional genomics, but are limited in scale by cost and combinatorial complexity. Here, we reimagine Perturb-seq's design through the lens of algorithms applied to random, low-dimensional observations. We present compressed Perturb-seq, which measures multiple random perturbations per cell or multiple cells per droplet and computationally decompresses these measurements by leveraging the sparse structure of regulatory circuits. Applied to 598 genes in the immune response to bacterial lipopolysaccharide, compressed Perturb-seq achieves the same accuracy as conventional Perturb-seq at 4 to 20-fold reduced cost, with greater power to learn genetic interactions. We identify known and novel regulators of immune responses and uncover evolutionarily constrained genes with downstream targets enriched for immune disease heritability, including many missed by existing GWAS or trans-eQTL studies. Our framework enables new scales of interrogation for a foundational method in functional genomics.

A transcription factor atlas of directed differentiation.

Transcription factors (TFs) regulate gene programs, thereby controlling diverse cellular processes and cell states. To comprehensively understand TFs and the programs they control, we created a barcoded library of all annotated human TF splice isoforms (>3,500) and applied it to build a TF Atlas charting expression profiles of human embryonic stem cells (hESCs) overexpressing each TF at single-cell resolution. We mapped TF-induced expression profiles to reference cell types and validated candidate TFs for generation of diverse cell types, spanning all three germ layers and trophoblasts. Targeted screens with subsets of the library allowed us to create a tailored cellular disease model and integrate mRNA expression and chromatin accessibility data to identify downstream regulators. Finally, we characterized the effects of combinatorial TF overexpression by developing and validating a strategy for predicting combinations of TFs that produce target expression profiles matching reference cell types to accelerate cellular engineering efforts.

Mostly natural sequencing-by-synthesis for scRNA-seq using Ultima sequencing.

Here we introduce a mostly natural sequencing-by-synthesis (mnSBS) method for single-cell RNA sequencing (scRNA-seq), adapted to the Ultima genomics platform, and systematically benchmark it against current scRNA-seq technology. mnSBS uses mostly natural, unmodified nucleotides and only a low fraction of fluorescently labeled nucleotides, which allows for high polymerase processivity and lower costs. We demonstrate successful application in four scRNA-seq case studies of different technical and biological types, including 5' and 3' scRNA-seq, human peripheral blood mononuclear cells from a single individual and in multiplex, as well as Perturb-Seq. Benchmarking shows that results from mnSBS-based scRNA-seq are very similar to those using Illumina sequencing, with minor differences in results related to the position of reads relative to annotated gene boundaries, owing to single-end reads of Ultima being closer to gene ends than reads from Illumina. The method is thus compatible with state-of-the-art scRNA-seq libraries independent of the sequencing technology. We expect mnSBS to be of particular utility for cost-effective large-scale scRNA-seq projects.

Multimodal pooled Perturb-CITE-seq screens in patient models define mechanisms of cancer immune evasion.

Resistance to immune checkpoint inhibitors (ICIs) is a key challenge in cancer therapy. To elucidate underlying mechanisms, we developed Perturb-CITE-sequencing (Perturb-CITE-seq), enabling pooled clustered regularly interspaced short palindromic repeat (CRISPR)-Cas9 perturbations with single-cell transcriptome and protein readouts. In patient-derived melanoma cells and autologous tumor-infiltrating lymphocyte (TIL) co-cultures, we profiled transcriptomes and 20 proteins in ~218,000 cells under ~750 perturbations associated with cancer cell-intrinsic ICI resistance (ICR). We recover known mechanisms of resistance, including defects in the interferon-γ (IFN-γ)-JAK/STAT and antigen-presentation pathways in RNA, protein and perturbation space, and new ones, including loss/downregulation of CD58. Loss of CD58 conferred immune evasion in multiple co-culture models and was downregulated in tumors of melanoma patients with ICR. CD58 protein expression was not induced by IFN-γ signaling, and CD58 loss conferred immune evasion without compromising major histocompatibility complex (MHC) expression, suggesting that it acts orthogonally to known mechanisms of ICR. This work provides a framework for the deciphering of complex mechanisms by large-scale perturbation screens with multimodal, single-cell readouts, and discovers potentially clinically relevant mechanisms of immune evasion.

A collection of programs for one-dimensional Ising analysis of linear repeat proteins with point substitutions.

A collection of programs is presented to analyze the thermodynamics of folding of linear repeat proteins using a 1D Ising model to determine intrinsic folding and interfacial coupling free energies. Expressions for folding transitions are generated for a series of constructs with different repeat numbers and are globally fitted to transitions for these constructs. These programs are designed to analyze Ising parameters for capped homopolymeric consensus repeat constructs as well as heteropolymeric constructs that contain point substitutions, providing a rigorous framework for analysis of the effects of mutation on intrinsic and directional (i.e., N- vs. C-terminal) interfacial coupling free-energies. A bootstrap analysis is provided to estimate parameter uncertainty as well as correlations among fitted parameters. Rigorous statistical analysis is essential for interpreting fits using the complex models required for Ising analysis of repeat proteins, especially heteropolymeric repeat proteins. Programs described here are available at https://github.com/barricklab-at-jhu/Ising_programs.

Multiplexed single-cell transcriptional response profiling to define cancer vulnerabilities and therapeutic mechanism of action.

Assays to study cancer cell responses to pharmacologic or genetic perturbations are typically restricted to using simple phenotypic readouts such as proliferation rate. Information-rich assays, such as gene-expression profiling, have generally not permitted efficient profiling of a given perturbation across multiple cellular contexts. Here, we develop MIX-Seq, a method for multiplexed transcriptional profiling of post-perturbation responses across a mixture of samples with single-cell resolution, using SNP-based computational demultiplexing of single-cell RNA-sequencing data. We show that MIX-Seq can be used to profile responses to chemical or genetic perturbations across pools of 100 or more cancer cell lines. We combine it with Cell Hashing to further multiplex additional experimental conditions, such as post-treatment time points or drug doses. Analyzing the high-content readout of scRNA-seq reveals both shared and context-specific transcriptional response components that can identify drug mechanism of action and enable prediction of long-term cell viability from short-term transcriptional responses to treatment.

Functional instability allows access to DNA in longer transcription Activator-Like effector (TALE) arrays.

Transcription activator-like effectors (TALEs) bind DNA through an array of tandem 34-residue repeats. How TALE repeat domains wrap around DNA, often extending more than 1.5 helical turns, without using external energy is not well understood. Here, we examine the kinetics of DNA binding of TALE arrays with varying numbers of identical repeats. Single molecule fluorescence analysis and deterministic modeling reveal conformational heterogeneity in both the free- and DNA-bound TALE arrays. Our findings, combined with previously identified partly folded states, indicate a TALE instability that is functionally important for DNA binding. For TALEs forming less than one superhelical turn around DNA, partly folded states inhibit DNA binding. In contrast, for TALEs forming more than one turn, partly folded states facilitate DNA binding, demonstrating a mode of 'functional instability' that facilitates macromolecular assembly. Increasing repeat number slows down interconversion between the various DNA-free and DNA-bound states.

Extreme stability in de novo-designed repeat arrays is determined by unusually stable short-range interactions.

Designed helical repeats (DHRs) are modular helix-loop-helix-loop protein structures that are tandemly repeated to form a superhelical array. Structures combining tandem DHRs demonstrate a wide range of molecular geometries, many of which are not observed in nature. Understanding cooperativity of DHR proteins provides insight into the molecular origins of Rosetta-based protein design hyperstability and facilitates comparison of energy distributions in artificial and naturally occurring protein folds. Here, we use a nearest-neighbor Ising model to quantify the intrinsic and interfacial free energies of four different DHRs. We measure the folding free energies of constructs with varying numbers of internal and terminal capping repeats for four different DHR folds, using guanidine-HCl and glycerol as destabilizing and solubilizing cosolvents. One-dimensional Ising analysis of these series reveals that, although interrepeat coupling energies are within the range seen for naturally occurring repeat proteins, the individual repeats of DHR proteins are intrinsically stable. This favorable intrinsic stability, which has not been observed for naturally occurring repeat proteins, adds to stabilizing interfaces, resulting in extraordinarily high stability. Stable repeats also impart a downhill shape to the energy landscape for DHR folding. These intrinsic stability differences suggest that part of the success of Rosetta-based design results from capturing favorable local interactions.

Broken TALEs: Transcription Activator-like Effectors Populate Partly Folded States.

Transcription activator-like effector proteins (TALEs) contain large numbers of repeats that bind double-stranded DNA, wrapping around DNA to form a continuous superhelix. Since unbound TALEs retain superhelical structure, it seems likely that DNA binding requires a significant structural distortion or partial unfolding. In this study, we use nearest-neighbor "Ising" analysis of consensus TALE (cTALE) repeat unfolding to quantify intrinsic folding free energies, coupling energies between repeats, and the free energy distribution of partly unfolded states, and to determine how those energies depend on the sequence that determines DNA-specificity (called the "RVD"). We find a moderate level of cooperativity for both the HD and NS RVD sequences (stabilizing interfaces combined with unstable repeats), as has been seen in other linear repeat proteins. Surprisingly, RVD sequence identity influences both the overall stability and the balance of intrinsic repeat stability and interfacial coupling energy. Using parameters from the Ising analysis, we have analyzed the distribution of partly folded states as a function of cTALE length and RVD sequence. We find partly unfolded states where one or more repeats are unfolded to be energetically accessible. Mixing repeats with different RVD sequences increases the population of partially folded states. Local folding free energies plateau for central repeats, suggesting that TALEs access partially folded states where a single internal repeat is unfolded while adjacent repeats remain folded. This breakage should allow TALEs to access superhelically-broken states, and may facilitate DNA binding.

Role of a non-canonical surface of Rad6 in ubiquitin conjugating activity.

Rad6 is a yeast E2 ubiquitin conjugating enzyme that monoubiquitinates histone H2B in conjunction with the E3, Bre1, but can non-specifically modify histones on its own. We determined the crystal structure of a Rad6∼Ub thioester mimic, which revealed a network of interactions in the crystal in which the ubiquitin in one conjugate contacts Rad6 in another. The region of Rad6 contacted is located on the distal face of Rad6 opposite the active site, but differs from the canonical E2 backside that mediates free ubiquitin binding and polyubiquitination activity in other E2 enzymes. We find that free ubiquitin interacts weakly with both non-canonical and canonical backside residues of Rad6 and that mutations of non-canonical residues have deleterious effects on Rad6 activity comparable to those observed to mutations in the canonical E2 backside. The effect of non-canonical backside mutations is similar in the presence and absence of Bre1, indicating that contacts with non-canonical backside residues govern the intrinsic activity of Rad6. Our findings shed light on the determinants of intrinsic Rad6 activity and reveal new ways in which contacts with an E2 backside can regulate ubiquitin conjugating activity.