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.

Widespread macromolecular interaction perturbations in human genetic disorders.

How disease-associated mutations impair protein activities in the context of biological networks remains mostly undetermined. Although a few renowned alleles are well characterized, functional information is missing for over 100,000 disease-associated variants. Here we functionally profile several thousand missense mutations across a spectrum of Mendelian disorders using various interaction assays. The majority of disease-associated alleles exhibit wild-type chaperone binding profiles, suggesting they preserve protein folding or stability. While common variants from healthy individuals rarely affect interactions, two-thirds of disease-associated alleles perturb protein-protein interactions, with half corresponding to "edgetic" alleles affecting only a subset of interactions while leaving most other interactions unperturbed. With transcription factors, many alleles that leave protein-protein interactions intact affect DNA binding. Different mutations in the same gene leading to different interaction profiles often result in distinct disease phenotypes. Thus disease-associated alleles that perturb distinct protein activities rather than grossly affecting folding and stability are relatively widespread.

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.

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.

Fast and global detection of periodic sequence repeats in large genomic resources.

Periodically repeating DNA and protein elements are involved in various important biological events including genomic evolution, gene regulation, protein complex formation, and immunity. Notably, the currently used genome editing tools such as ZFNs, TALENs, and CRISPRs are also all associated with periodically repeating biomolecules of natural organisms. Despite the biological importance of periodically repeating sequences and the expectation that new genome editing modules could be discovered from such periodical repeats, no software that globally detects such structured elements in large genomic resources in a high-throughput and unsupervised manner has been developed. We developed new software, SPADE (Search for Patterned DNA Elements), that exhaustively explores periodic DNA and protein repeats from large-scale genomic datasets based on k-mer periodicity evaluation. With a simple constraint, sequence periodicity, SPADE captured reported genome-editing-associated sequences and other protein families involving repeating domains such as tetratricopeptide, ankyrin and WD40 repeats with better performance than the other software designed for limited sets of repetitive biomolecular sequences, suggesting the high potential of this software to contribute to the discovery of new biological events and new genome editing modules.

Yeast genetic interaction screen of human genes associated with amyotrophic lateral sclerosis: identification of MAP2K5 kinase as a potential drug target.

To understand disease mechanisms, a large-scale analysis of human-yeast genetic interactions was performed. Of 1305 human disease genes assayed, 20 genes exhibited strong toxicity in yeast. Human-yeast genetic interactions were identified by en masse transformation of the human disease genes into a pool of 4653 homozygous diploid yeast deletion mutants with unique barcode sequences, followed by multiplexed barcode sequencing to identify yeast toxicity modifiers. Subsequent network analyses focusing on amyotrophic lateral sclerosis (ALS)-associated genes, such as optineurin (OPTN) and angiogenin (ANG), showed that the human orthologs of the yeast toxicity modifiers of these ALS genes are enriched for several biological processes, such as cell death, lipid metabolism, and molecular transport. When yeast genetic interaction partners held in common between human OPTN and ANG were validated in mammalian cells and zebrafish, MAP2K5 kinase emerged as a potential drug target for ALS therapy. The toxicity modifiers identified in this study may deepen our understanding of the pathogenic mechanisms of ALS and other devastating diseases.

Pooled-matrix protein interaction screens using Barcode Fusion Genetics.

High-throughput binary protein interaction mapping is continuing to extend our understanding of cellular function and disease mechanisms. However, we remain one or two orders of magnitude away from a complete interaction map for humans and other major model organisms. Completion will require screening at substantially larger scales with many complementary assays, requiring further efficiency gains in proteome-scale interaction mapping. Here, we report Barcode Fusion Genetics-Yeast Two-Hybrid (BFG-Y2H), by which a full matrix of protein pairs can be screened in a single multiplexed strain pool. BFG-Y2H uses Cre recombination to fuse DNA barcodes from distinct plasmids, generating chimeric protein-pair barcodes that can be quantified via next-generation sequencing. We applied BFG-Y2H to four different matrices ranging in scale from ~25 K to 2.5 M protein pairs. The results show that BFG-Y2H increases the efficiency of protein matrix screening, with quality that is on par with state-of-the-art Y2H methods.

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.

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."

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.

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.

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).

Integrative features of the yeast phosphoproteome and protein-protein interaction map.

Following recent advances in high-throughput mass spectrometry (MS)-based proteomics, the numbers of identified phosphoproteins and their phosphosites have greatly increased in a wide variety of organisms. Although a critical role of phosphorylation is control of protein signaling, our understanding of the phosphoproteome remains limited. Here, we report unexpected, large-scale connections revealed between the phosphoproteome and protein interactome by integrative data-mining of yeast multi-omics data. First, new phosphoproteome data on yeast cells were obtained by MS-based proteomics and unified with publicly available yeast phosphoproteome data. This revealed that nearly 60% of ∼6,000 yeast genes encode phosphoproteins. We mapped these unified phosphoproteome data on a yeast protein-protein interaction (PPI) network with other yeast multi-omics datasets containing information about proteome abundance, proteome disorders, literature-derived signaling reactomes, and in vitro substratomes of kinases. In the phospho-PPI, phosphoproteins had more interacting partners than nonphosphoproteins, implying that a large fraction of intracellular protein interaction patterns (including those of protein complex formation) is affected by reversible and alternative phosphorylation reactions. Although highly abundant or unstructured proteins have a high chance of both interacting with other proteins and being phosphorylated within cells, the difference between the number counts of interacting partners of phosphoproteins and nonphosphoproteins was significant independently of protein abundance and disorder level. Moreover, analysis of the phospho-PPI and yeast signaling reactome data suggested that co-phosphorylation of interacting proteins by single kinases is common within cells. These multi-omics analyses illuminate how wide-ranging intracellular phosphorylation events and the diversity of physical protein interactions are largely affected by each other.

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.

Molecular recorders to track cellular events.

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

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.

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.

Tight associations between transcription promoter type and epigenetic variation in histone positioning and modification.

BACKGROUND: Transcription promoters are fundamental genomic cis-elements controlling gene expression. They can be classified into two types by the degree of imprecision of their transcription start sites: peak promoters, which initiate transcription from a narrow genomic region; and broad promoters, which initiate transcription from a wide-ranging region. Eukaryotic transcription initiation is suggested to be associated with the genomic positions and modifications of nucleosomes. For instance, it has been recently shown that histone with H3K9 acetylation (H3K9ac) is more likely to be distributed around broad promoters rather than peak promoters; it can thus be inferred that there is an association between histone H3K9 and promoter architecture. RESULTS: Here, we performed a systematic analysis of transcription promoters and gene expression, as well as of epigenetic histone behaviors, including genomic position, stability within the chromatin, and several modifications. We found that, in humans, broad promoters, but not peak promoters, generally had significant associations with nucleosome positioning and modification. Specifically, around broad promoters histones were highly distributed and aligned in an orderly fashion. This feature was more evident with histones that were methylated or acetylated; moreover, the nucleosome positions around the broad promoters were more stable than those around the peak ones. More strikingly, the overall expression levels of genes associated with broad promoters (but not peak promoters) with modified histones were significantly higher than the levels of genes associated with broad promoters with unmodified histones. CONCLUSION: These results shed light on how epigenetic regulatory networks of histone modifications are associated with promoter architecture.

In silico analysis of phosphoproteome data suggests a rich-get-richer process of phosphosite accumulation over evolution.

Recent phosphoproteome analyses using mass spectrometry-based technologies have provided new insights into the extensive presence of protein phosphorylation in various species and have raised the interesting question of how this protein modification was gained evolutionarily on such a large scale. We investigated this issue by using human and mouse phosphoproteome data. We initially found that phosphoproteins followed a power-law distribution with regard to their number of phosphosites: most of the proteins included only a few phosphosites, but some included dozens of phosphosites. The power-law distribution, unlike more commonly observed distributions such as normal and log-normal distributions, is considered by the field of complex systems science to be produced by a specific rich-get-richer process called preferential attachment growth. Therefore, we explored the factors that may have promoted the rich-get-richer process during phosphosite evolution. We conducted a bioinformatics analysis to evaluate the relationship of amino acid sequences of phosphoproteins with the positions of phosphosites and found an overconcentration of phosphosites in specific regions of protein surfaces and implications that in many phosphoproteins these clusters of phosphosites are activated simultaneously. Multiple phosphosites concentrated in limited spaces on phosphoprotein surfaces may therefore function biologically as cooperative modules that are resistant to selective pressures during phosphoprotein evolution. We therefore proposed a hypothetical model by which the modularization of multiple phosphosites has been resistant to natural selection and has driven the rich-get-richer process of the evolutionary growth of phosphosite numbers.