Heart failure promotes multimorbidity through innate immune memory.

Patients with heart failure (HF) often experience repeated acute decompensation and develop comorbidities such as chronic kidney disease and frailty syndrome. Although this suggests pathological interaction among comorbidities, the mechanisms linking them are poorly understood. Here, we identified alterations in hematopoietic stem cells (HSCs) as a critical driver of recurrent HF and associated comorbidities. Bone marrow transplantation from HF-experienced mice resulted in spontaneous cardiac dysfunction and fibrosis in recipient mice, as well as increased vulnerability to kidney and skeletal muscle insults. HF enhanced the capacity of HSCs to generate proinflammatory macrophages. In HF mice, global chromatin accessibility analysis and single-cell RNA-seq showed that transforming growth factor-ß (TGF-ß) signaling was suppressed in HSCs, which corresponded with repressed sympathetic nervous activity in bone marrow. Transplantation of bone marrow from mice in which TGF-ß signaling was inhibited similarly exacerbated cardiac dysfunction. Collectively, these results suggest that cardiac stress modulates the epigenome of HSCs, which in turn alters their capacity to generate cardiac macrophage subpopulations. This change in HSCs may be a common driver of repeated HF events and comorbidity by serving as a key carrier of "stress memory."

Pooled CRISPR screening of high-content cellular phenotypes using ghost cytometry.

Recent advancements in image-based pooled CRISPR screening have facilitated the mapping of diverse genotype-phenotype associations within mammalian cells. However, the rapid enrichment of cells based on morphological information continues to pose a challenge, constraining the capacity for large-scale gene perturbation screening across diverse high-content cellular phenotypes. In this study, we demonstrate the applicability of multimodal ghost cytometry-based cell sorting, including both fluorescent and label-free high-content phenotypes, for rapid pooled CRISPR screening within vast cell populations. Using the high-content cell sorter operating in fluorescence mode, we successfully executed kinase-specific CRISPR screening targeting genes influencing the nuclear translocation of RelA. Furthermore, using the multiparametric, label-free mode, we performed large-scale screening to identify genes involved in macrophage polarization. Notably, the label-free platform can enrich target phenotypes without requiring invasive staining, preserving untouched cells for downstream assays and expanding the potential for screening cellular phenotypes even when suitable markers are absent.

DNA-GPS: A theoretical framework for optics-free spatial genomics and synthesis of current methods.

While single-cell sequencing technologies provide unprecedented insights into genomic profiles at the cellular level, they lose the spatial context of cells. Over the past decade, diverse spatial transcriptomics and multi-omics technologies have been developed to analyze molecular profiles of tissues. In this article, we categorize current spatial genomics technologies into three classes: optical imaging, positional indexing, and mathematical cartography. We discuss trade-offs in resolution and scale, identify limitations, and highlight synergies between existing single-cell and spatial genomics methods. Further, we propose DNA-GPS (global positioning system), a theoretical framework for large-scale optics-free spatial genomics that combines ideas from mathematical cartography and positional indexing. DNA-GPS has the potential to achieve scalable spatial genomics for multiple measurement modalities, and by eliminating the need for optical measurement, it has the potential to position cells in three-dimensions (3D).

An AsCas12f-based compact genome-editing tool derived by deep mutational scanning and structural analysis.

SpCas9 and AsCas12a are widely utilized as genome-editing tools in human cells. However, their relatively large size poses a limitation for delivery by cargo-size-limited adeno-associated virus (AAV) vectors. The type V-F Cas12f from Acidibacillus sulfuroxidans is exceptionally compact (422 amino acids) and has been harnessed as a compact genome-editing tool. Here, we developed an approach, combining deep mutational scanning and structure-informed design, to successfully generate two AsCas12f activity-enhanced (enAsCas12f) variants. Remarkably, the enAsCas12f variants exhibited genome-editing activities in human cells comparable with those of SpCas9 and AsCas12a. The cryoelectron microscopy (cryo-EM) structures revealed that the mutations stabilize the dimer formation and reinforce interactions with nucleic acids to enhance their DNA cleavage activities. Moreover, enAsCas12f packaged with partner genes in an all-in-one AAV vector exhibited efficient knock-in/knock-out activities and transcriptional activation in mice. Taken together, enAsCas12f variants could offer a minimal genome-editing platform for in vivo gene therapy.

Comprehensive behavioral analyses of mice with a glycine receptor alpha 4 deficiency.

Glycine receptors (GlyRs) are ligand-gated chloride channels comprising alpha (α1-4) and ß subunits. The GlyR subunits play major roles in the mammalian central nervous system, ranging from regulating simple sensory information to modulating higher-order brain function. Unlike the other GlyR subunits, GlyR α4 receives relatively little attention because the human ortholog lacks a transmembrane domain and is thus considered a pseudogene. A recent genetic study reported that the GLRA4 pseudogene locus on the X chromosome is potentially involved in cognitive impairment, motor delay and craniofacial anomalies in humans. The physiologic roles of GlyR α4 in mammal behavior and its involvement in disease, however, are not known. Here we examined the temporal and spatial expression profile of GlyR α4 in the mouse brain and subjected Glra4 mutant mice to a comprehensive behavioral analysis to elucidate the role of GlyR α4 in behavior. The GlyR α4 subunit was mainly enriched in the hindbrain and midbrain, and had relatively lower expression in the thalamus, cerebellum, hypothalamus, and olfactory bulb. In addition, expression of the GlyR α4 subunit gradually increased during brain development. Glra4 mutant mice exhibited a decreased amplitude and delayed onset of the startle response compared with wild-type littermates, and increased social interaction in the home cage during the dark period. Glra4 mutants also had a low percentage of entries into open arms in the elevated plus-maze test. Although mice with GlyR α4 deficiency did not show motor and learning abnormalities reported to be associated in human genomics studies, they exhibited behavioral changes in startle response and social and anxiety-like behavior. Our data clarify the spatiotemporal expression pattern of the GlyR α4 subunit and suggest that glycinergic signaling modulates social, startle, and anxiety-like behaviors in mice.

A universal sequencing read interpreter.

Massively parallel DNA sequencing has led to the rapid growth of highly multiplexed experiments in biology. These experiments produce unique sequencing results that require specific analysis pipelines to decode highly structured reads. However, no versatile framework that interprets sequencing reads to extract their encoded information for downstream biological analysis has been developed. Here, we report INTERSTELLAR (interpretation, scalable transformation, and emulation of large-scale sequencing reads) that decodes data values encoded in theoretically any type of sequencing read and translates them into sequencing reads of another structure of choice. We demonstrated that INTERSTELLAR successfully extracted information from a range of short- and long-read sequencing reads and translated those of single-cell (sc)RNA-seq, scATAC-seq, and spatial transcriptomics to be analyzed by different software tools that have been developed for conceptually the same types of experiments. INTERSTELLAR will greatly facilitate the development of sequencing-based experiments and sharing of data analysis pipelines.

Molecular recorders to track cellular events.

DNA tapes could be used to record dynamic molecular and cellular events in animals.

A framework to efficiently describe and share reproducible DNA materials and construction protocols.

DNA constructs and their annotated sequence maps have been rapidly accumulating with the advancement of DNA cloning, synthesis, and assembly methods. Such resources have also been utilized in designing and building new DNA materials. However, as commonly seen in the life sciences, no framework exists to describe reproducible DNA construction processes. Furthermore, the use of previously developed DNA materials and building protocols is usually not appropriately credited. Here, we report a framework QUEEN (framework to generate quinable and efficiently editable nucleotide sequence resources) to resolve these issues and accelerate the building of DNA. QUEEN enables the flexible design of new DNA by using existing DNA material resource files and recording its construction process in an output file (GenBank file format). A GenBank file generated by QUEEN can regenerate the process code such that it perfectly clones itself and bequeaths the same process code to its successive GenBank files, recycling its partial DNA resources. QUEEN-generated GenBank files are compatible with existing DNA repository services and software. We propose QUEEN as a solution to start significantly advancing the material and protocol sharing of DNA resources.

High-Throughput Gene Mutagenesis Screening Using Base Editing.

Base editing is a CRISPR-Cas9 genome engineering tool that allows programmable mutagenesis without the creation of double-stranded breaks. Here, we describe the design and execution of large-scale base editing screens using the Target-AID base editor in yeast. Using this approach, thousands of sites can be mutated simultaneously. The effects of these mutations on fitness can be measured using a pooled growth competition assay followed by DNA sequencing of gRNAs as barcodes.

Engineered Campylobacter jejuni Cas9 variant with enhanced activity and broader targeting range.

The RNA-guided DNA endonuclease Cas9 is a versatile genome-editing tool. However, the molecular weight of the commonly used Streptococcus pyogenes Cas9 is relatively large. Consequently, its gene cannot be efficiently packaged into an adeno-associated virus vector, thereby limiting its applications for therapeutic genome editing. Here, we biochemically characterized the compact Cas9 from Campylobacter jejuni (CjCas9) and found that CjCas9 has a previously unrecognized preference for the N3VRYAC protospacer adjacent motif. We thus rationally engineered a CjCas9 variant (enCjCas9), which exhibits enhanced cleavage activity and a broader targeting range both in vitro and in human cells, as compared with CjCas9. Furthermore, a nickase version of enCjCas9, but not CjCas9, fused with a cytosine deaminase mediated C-to-T conversions in human cells. Overall, our findings expand the CRISPR-Cas toolbox for therapeutic genome engineering.

Barcode fusion genetics-protein-fragment complementation assay (BFG-PCA): tools and resources that expand the potential for binary protein interaction discovery.

Barcode fusion genetics (BFG) utilizes deep sequencing to improve the throughput of protein-protein interaction (PPI) screening in pools. BFG has been implemented in Yeast two-hybrid (Y2H) screens (BFG-Y2H). While Y2H requires test protein pairs to localize in the nucleus for reporter reconstruction, dihydrofolate reductase protein-fragment complementation assay (DHFR-PCA) allows proteins to localize in broader subcellular contexts and proves to be largely orthogonal to Y2H. Here, we implemented BFG to DHFR-PCA (BFG-PCA). This plasmid-based system can leverage ORF collections across model organisms to perform comparative analysis, unlike the original DHFR-PCA that requires yeast genomic integration. The scalability and quality of BFG-PCA were demonstrated by screening human and yeast interactions for >11 000 bait-prey pairs. BFG-PCA showed high-sensitivity and high-specificity for capturing known interactions for both species. BFG-Y2H and BFG-PCA capture distinct sets of PPIs, which can partially be explained based on the domain orientation of the reporter tags. BFG-PCA is a high-throughput protein interaction technology to interrogate binary PPIs that exploits clone collections from any species of interest, expanding the scope of PPI assays.

Deep distributed computing to reconstruct extremely large lineage trees.

Phylogeny estimation (the reconstruction of evolutionary trees) has recently been applied to CRISPR-based cell lineage tracing, allowing the developmental history of an individual tissue or organism to be inferred from a large number of mutated sequences in somatic cells. However, current computational methods are not able to construct phylogenetic trees from extremely large numbers of input sequences. Here, we present a deep distributed computing framework to comprehensively trace accurate large lineages (FRACTAL) that substantially enhances the scalability of current lineage estimation software tools. FRACTAL first reconstructs only an upstream lineage of the input sequences and recursively iterates the same produce for its downstream lineages using independent computing nodes. We demonstrate the utility of FRACTAL by reconstructing lineages from >235 million simulated sequences and from >16 million cells from a simulated experiment with a CRISPR system that accumulates mutations during cell proliferation. We also successfully applied FRACTAL to evolutionary tree reconstructions and to an experiment using error-prone PCR (EP-PCR) for large-scale sequence diversification.

CRISPR/Cas9-mediated base-editing enables a chain reaction through sequential repair of sgRNA scaffold mutations.

Cell behavior is controlled by complex gene regulatory networks. Although studies have uncovered diverse roles of individual genes, it has been challenging to record or control sequential genetic events in living cells. In this study, we designed two cellular chain reaction systems that enable sequential sgRNA activation in mammalian cells using a nickase Cas9 tethering of a cytosine nucleotide deaminase (nCas9-CDA). In these systems, thymidine (T)-to-cytosine (C) substitutions in the scaffold region of the sgRNA or the TATA box-containing loxP sequence (TATAloxP) are corrected by the nCas9-CDA, leading to activation of the next sgRNA. These reactions can occur multiple times, resulting in cellular chain reactions. As a proof of concept, we established a chain reaction by repairing sgRNA scaffold mutations in 293 T cells. Importantly, the results obtained in yeast or in vitro did not match those obtained in mammalian cells, suggesting that in vivo chain reactions need to be optimized in appropriate cellular contexts. Our system may lay the foundation for building cellular chain reaction systems that have a broad utility in the future biomedical research.

Highly Multiplexed Analysis of CRISPR Genome Editing Outcomes in Mammalian Cells.

CRISPR-Cas-based genome editing has enabled efficient genetic engineering of a range of organisms and sparked revolutions in many fields of biology. After Streptococcus pyogenes Cas9 was first demonstrated for mammalian genome editing, many CRISPR-associated (Cas) protein variants have been isolated from different species and adopted for genome editing. Furthermore, various effector domains have been fused to these Cas proteins to expand their genome-editing abilities. Although the number of genome-editing tools has been rapidly increasing, the throughput of cell-based characterization of new genome-editing tools remains limited. Here we describe a highly multiplexed genome editing and sequencing library preparation protocol that allows high-resolution analysis of mutation outcomes and frequencies induced by hundreds to thousands of different genome-editing reagents in mammalian cells. We have successful experiences of developing several key genome-editing tools using this protocol. The protocol also is designed to be compatible with robotic liquid handling systems for further scalability.

Machine learning approach for discrimination of genotypes based on bright-field cellular images.

Morphological profiling is a combination of established optical microscopes and cutting-edge machine vision technologies, which stacks up successful applications in high-throughput phenotyping. One major question is how much information can be extracted from an image to identify genetic differences between cells. While fluorescent microscopy images of specific organelles have been broadly used for single-cell profiling, the potential ability of bright-field (BF) microscopy images of label-free cells remains to be tested. Here, we examine whether single-gene perturbation can be discriminated based on BF images of label-free cells using a machine learning approach. We acquired hundreds of BF images of single-gene mutant cells, quantified single-cell profiles consisting of texture features of cellular regions, and constructed a machine learning model to discriminate mutant cells from wild-type cells. Interestingly, the mutants were successfully discriminated from the wild type (area under the receiver operating characteristic curve = 0.773). The features that contributed to the discrimination were identified, and they included those related to the morphology of structures that appeared within cellular regions. Furthermore, functionally close gene pairs showed similar feature profiles of the mutant cells. Our study reveals that single-gene mutant cells can be discriminated from wild-type cells based on BF images, suggesting the potential as a useful tool for mutant cell profiling.

Interrogation of kinase genetic interactions provides a global view of PAK1-mediated signal transduction pathways.

Kinases are critical components of intracellular signaling pathways and have been extensively investigated with regard to their roles in cancer. p21-activated kinase-1 (PAK1) is a serine/threonine kinase that has been previously implicated in numerous biological processes, such as cell migration, cell cycle progression, cell motility, invasion, and angiogenesis, in glioma and other cancers. However, the signaling network linked to PAK1 is not fully defined. We previously reported a large-scale yeast genetic interaction screen using toxicity as a readout to identify candidate PAK1 genetic interactions. En masse transformation of the PAK1 gene into 4,653 homozygous diploid Saccharomyces cerevisiae yeast deletion mutants identified ∼400 candidates that suppressed yeast toxicity. Here we selected 19 candidate PAK1 genetic interactions that had human orthologs and were expressed in glioma for further examination in mammalian cells, brain slice cultures, and orthotopic glioma models. RNAi and pharmacological inhibition of potential PAK1 interactors confirmed that DPP4, KIF11, mTOR, PKM2, SGPP1, TTK, and YWHAE regulate PAK1-induced cell migration and revealed the importance of genes related to the mitotic spindle, proteolysis, autophagy, and metabolism in PAK1-mediated glioma cell migration, drug resistance, and proliferation. AKT1 was further identified as a downstream mediator of the PAK1-TTK genetic interaction. Taken together, these data provide a global view of PAK1-mediated signal transduction pathways and point to potential new drug targets for glioma therapy.

Publisher Correction: Base editors for simultaneous introduction of C-to-T and A-to-G mutations.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Base editors for simultaneous introduction of C-to-T and A-to-G mutations.

We describe base editors that combine both cytosine and adenine base-editing functions. A codon-optimized fusion of the cytosine deaminase PmCDA1, the adenosine deaminase TadA and a Cas9 nickase (Target-ACEmax) showed a high median simultaneous C-to-T and A-to-G editing activity at 47 genomic targets. On-target as well as DNA and RNA off-target activities of Target-ACEmax were similar to those of existing single-function base editors.

Yeast-Based Genetic Interaction Analysis of Human Kinome.

Kinases are critical intracellular signaling proteins. To better understand kinase-mediated signal transduction, a large-scale human-yeast genetic interaction screen was performed. Among 597 human kinase genes tested, 28 displayed strong toxicity in yeast when overexpressed. En masse transformation of these toxic kinase genes into 4653 homozygous diploid yeast deletion mutants followed by barcode sequencing identified yeast toxicity modifiers and thus their human orthologs. Subsequent network analyses and functional grouping revealed that the 28 kinases and their 676 interaction partners (corresponding to a total of 969 genetic interactions) are enriched in cell death and survival (34%), small-molecule biochemistry (18%) and molecular transport (11%), among others. In the subnetwork analyses, a few kinases were commonly associated with glioma, cell migration and cell death/survival. Our analysis enabled the creation of a first draft of the kinase genetic interactome network and identified multiple drug targets for inflammatory diseases and cancer, in which deregulated kinase signaling plays a pathogenic role.