Methods for in vitro DNA cleavage and molecular cloning remain unable to precisely cleave DNA directly adjacent to bases of interest. Restriction enzymes (REs) must bind specific motifs, whereas wild-type CRISPR-Cas9 or CRISPR-Cas12 nucleases require protospacer adjacent motifs (PAMs). Here we explore the utility of our previously reported near-PAMless SpCas9 variant, named SpRY, to serve as a universal DNA cleavage tool for various cloning applications. By performing SpRY DNA digests (SpRYgests) using more than 130 guide RNAs (gRNAs) sampling a wide diversity of PAMs, we discovered that SpRY is PAMless in vitro and can cleave DNA at practically any sequence, including sites refractory to cleavage with wild-type SpCas9. We illustrate the versatility and effectiveness of SpRYgests to improve the precision of several cloning workflows, including those not possible with REs or canonical CRISPR nucleases. We also optimize a rapid and simple one-pot gRNA synthesis protocol to streamline SpRYgest implementation. Together, SpRYgests can improve various DNA engineering applications that benefit from precise DNA breaks.

The goal when imaging bioprocesses with optical microscopy is to acquire the most spatiotemporal information with the least invasiveness. Deep neural networks have substantially improved optical microscopy, including image super-resolution and restoration, but still have substantial potential for artifacts. In this study, we developed rationalized deep learning (rDL) for structured illumination microscopy and lattice light sheet microscopy (LLSM) by incorporating prior knowledge of illumination patterns and, thereby, rationally guiding the network to denoise raw images. Here we demonstrate that rDL structured illumination microscopy eliminates spectral bias-induced resolution degradation and reduces model uncertainty by five-fold, improving the super-resolution information by more than ten-fold over other computational approaches. Moreover, rDL applied to LLSM enables self-supervised training by using the spatial or temporal continuity of noisy data itself, yielding results similar to those of supervised methods. We demonstrate the utility of rDL by imaging the rapid kinetics of motile cilia, nucleolar protein condensation during light-sensitive mitosis and long-term interactions between membranous and membrane-less organelles.

Post-translational modification (PTM) of antigens provides an additional source of specificities targeted by immune responses to tumors or pathogens, but identifying antigen PTMs and assessing their role in shaping the immunopeptidome is challenging. Here we describe the Protein Modification Integrated Search Engine (PROMISE), an antigen discovery pipeline that enables the analysis of 29 different PTM combinations from multiple clinical cohorts and cell lines. We expanded the antigen landscape, uncovering human leukocyte antigen class I binding motifs defined by specific PTMs with haplotype-specific binding preferences and revealing disease-specific modified targets, including thousands of new cancer-specific antigens that can be shared between patients and across cancer types. Furthermore, we uncovered a subset of modified peptides that are specific to cancer tissue and driven by post-translational changes that occurred in the tumor proteome. Our findings highlight principles of PTM-driven antigenicity, which may have broad implications for T cell-mediated therapies in cancer and beyond.

Erratum in Nat Biotechnol. 2022 Nov 23;:

Chromatin profiling at locus resolution uncovers gene regulatory features that define cell types and developmental trajectories, but it remains challenging to map and compare different chromatin-associated proteins in the same sample. Here we describe Multiple Target Identification by Tagmentation (MulTI-Tag), an antibody barcoding approach for profiling multiple chromatin features simultaneously in single cells. We optimized MulTI-Tag to retain high sensitivity and specificity, and we demonstrate detection of up to three histone modifications in the same cell: H3K27me3, H3K4me1/2 and H3K36me3. We apply MulTI-Tag to resolve distinct cell types and developmental trajectories; to distinguish unique, coordinated patterns of active and repressive element regulatory usage associated with differentiation outcomes; and to uncover associations between histone marks. Multifactorial epigenetic profiling holds promise for comprehensively characterizing cell-specific gene regulatory landscapes in development and disease.

The therapeutic potential of recombinant cytokines has been limited by the severe side effects of systemic administration. We describe a strategy to reduce the dose-limiting toxicities of monomeric cytokines by designing two components that require colocalization for activity and that can be independently targeted to restrict activity to cells expressing two surface markers. We demonstrate the approach with a previously designed mimetic of cytokines interleukin-2 and interleukin-15-Neoleukin-2/15 (Neo-2/15)-both for trans-activating immune cells surrounding targeted tumor cells and for cis-activating directly targeted immune cells. In trans-activation mode, tumor antigen targeting of the two components enhanced antitumor activity and attenuated toxicity compared with systemic treatment in syngeneic mouse melanoma models. In cis-activation mode, immune cell targeting of the two components selectively expanded CD8+ T cells in a syngeneic mouse melanoma model and promoted chimeric antigen receptor T cell activation in a lymphoma xenograft model, enhancing antitumor efficacy in both cases.

The formation and maintenance of tissue integrity requires complex, coordinated activities by thousands of genes and their encoded products. Until recently, transcript levels could only be quantified for a few genes in tissues, but advances in DNA sequencing, oligonucleotide synthesis and fluorescence microscopy have enabled the invention of a suite of spatial transcriptomics technologies capable of measuring the expression of many, or all, genes in situ. These technologies have evolved rapidly in sensitivity, multiplexing and throughput. As such, they have enabled the determination of the cell-type architecture of tissues, the querying of cell-cell interactions and the monitoring of molecular interactions between tissue components. The rapidly evolving spatial genomics landscape will enable generalized high-throughput genomic measurements and perturbations to be performed in the context of tissues. These advances will empower hypothesis generation and biological discovery and bridge the worlds of tissue biology and genomics.

Programmable approaches to sense and respond to the presence of specific RNAs in biological systems have broad applications in research, diagnostics, and therapeutics. Here we engineer a programmable RNA-sensing technology, reprogrammable ADAR sensors (RADARS), which harnesses RNA editing by adenosine deaminases acting on RNA (ADAR) to gate translation of a cargo protein by the presence of endogenous RNA transcripts. Introduction of a stop codon in a guide upstream of the cargo makes translation contingent on binding of an endogenous transcript to the guide, leading to ADAR editing of the stop codon and allowing translational readthrough. Through systematic sensor engineering, we achieve 277 fold improvement in sensor activation and engineer RADARS with diverse cargo proteins, including luciferases, fluorescent proteins, recombinases, and caspases, enabling detection sensitivity on endogenous transcripts expressed at levels as low as 13 transcripts per million. We show that RADARS are functional as either expressed DNA or synthetic mRNA and with either exogenous or endogenous ADAR. We apply RADARS in multiple contexts, including tracking transcriptional states, RNA-sensing-induced cell death, cell-type identification, and control of synthetic mRNA translation.

N6-methyladenosine (m6A) is the most abundant RNA modification in mammalian cells and the best-studied epitranscriptomic mark. Despite the development of various tools to map m6A, a transcriptome-wide method that enables absolute quantification of m6A at single-base resolution is lacking. Here we use glyoxal and nitrite-mediated deamination of unmethylated adenosines (GLORI) to develop an absolute m6A quantification method that is conceptually similar to bisulfite-sequencing-based quantification of DNA 5-methylcytosine. We apply GLORI to quantify the m6A methylomes of mouse and human cells and reveal clustered m6A modifications with differential distribution and stoichiometry. In addition, we characterize m6A dynamics under stress and examine the quantitative landscape of m6A modification in gene expression regulation. GLORI is an unbiased, convenient method for the absolute quantification of the m6A methylome.

Functional characterization of pseudouridine (Ψ) in mammalian mRNA has been hampered by the lack of a quantitative method that maps Ψ in the whole transcriptome. We report bisulfite-induced deletion sequencing (BID-seq), which uses a bisulfite-mediated reaction to convert pseudouridine stoichiometrically into deletion upon reverse transcription without cytosine deamination. BID-seq enables detection of abundant Ψ sites with stoichiometry information in several human cell lines and 12 different mouse tissues using 10-20 ng input RNA. We uncover consensus sequences for Ψ in mammalian mRNA and assign different 'writer' proteins to individual Ψ deposition. Our results reveal a transcript stabilization role of Ψ sites installed by TRUB1 in human cancer cells. We also detect the presence of Ψ within stop codons of mammalian mRNA and confirm the role of Ψ in promoting stop codon readthrough in vivo. BID-seq will enable future investigations of the roles of Ψ in diverse biological processes.

Despite unequivocal roles in disease, transcription factors (TFs) remain largely untapped as pharmacologic targets due to the challenges in targeting protein-protein and protein-DNA interactions. Here we report a chemical strategy to generate modular synthetic transcriptional repressors (STRs) derived from the bHLH domain of MAX. Our synthetic approach yields chemically stabilized tertiary domain mimetics that cooperatively bind the MYC/MAX consensus E-box motif with nanomolar affinity, exhibit specificity that is equivalent to or beyond that of full-length TFs and directly compete with MYC/MAX protein for DNA binding. A lead STR directly inhibits MYC binding in cells, downregulates MYC-dependent expression programs at the proteome level and inhibits MYC-dependent cell proliferation. Co-crystallization and structure determination of a STR:E-box DNA complex confirms retention of DNA recognition in a near identical manner as full-length bHLH TFs. We additionally demonstrate structure-blind design of STRs derived from alternative bHLH-TFs, confirming that STRs can be used to develop highly specific mimetics of TFs targeting other gene regulatory elements.

Models of intercellular communication in tissues are based on molecular profiles of dissociated cells, are limited to receptor-ligand signaling and ignore spatial proximity in situ. We present node-centric expression modeling, a method based on graph neural networks that estimates the effects of niche composition on gene expression in an unbiased manner from spatial molecular profiling data. We recover signatures of molecular processes known to underlie cell communication.

Bacterial toxin DddA-derived cytosine base editors (DdCBEs)-composed of split DddAtox (a cytosine deaminase specific to double-stranded DNA), custom-designed TALE (transcription activator-like effector) DNA-binding proteins, and a uracil glycosylase inhibitor-enable mitochondrial DNA (mtDNA) editing in human cells, which may pave the way for therapeutic correction of pathogenic mtDNA mutations in patients. The utility of DdCBEs has been limited by off-target activity, which is probably caused by spontaneous assembly of the split DddAtox deaminase enzyme, independent of DNA-binding interactions. We engineered high-fidelity DddA-derived cytosine base editors (HiFi-DdCBEs) with minimal off-target activity by substituting alanine for amino acid residues at the interface between the split DddAtox halves. The resulting domains cannot form a functional deaminase without binding of their linked TALE proteins at adjacent sites on DNA. Whole mitochondrial genome sequencing shows that, unlike conventional DdCBEs, which induce hundreds of unwanted off-target C-to-T conversions in human mtDNA, HiFi-DdCBEs are highly efficient and precise, avoiding collateral off-target mutations, and as such, they will probably be desirable for therapeutic applications.

Multi-omic single-cell datasets, in which multiple molecular modalities are profiled within the same cell, offer an opportunity to understand the temporal relationship between epigenome and transcriptome. To realize this potential, we developed MultiVelo, a differential equation model of gene expression that extends the RNA velocity framework to incorporate epigenomic data. MultiVelo uses a probabilistic latent variable model to estimate the switch time and rate parameters of chromatin accessibility and gene expression and improves the accuracy of cell fate prediction compared to velocity estimates from RNA only. Application to multi-omic single-cell datasets from brain, skin and blood cells reveals two distinct classes of genes distinguished by whether chromatin closes before or after transcription ceases. We also find four types of cell states: two states in which epigenome and transcriptome are coupled and two distinct decoupled states. Finally, we identify time lags between transcription factor expression and binding site accessibility and between disease-associated SNP accessibility and expression of the linked genes. MultiVelo is available on PyPI, Bioconda and GitHub ( https://github.com/welch-lab/MultiVelo ).

Large serine recombinases (LSRs) are DNA integrases that facilitate the site-specific integration of mobile genetic elements into bacterial genomes. Only a few LSRs, such as Bxb1 and PhiC31, have been characterized to date, with limited efficiency as tools for DNA integration in human cells. In this study, we developed a computational approach to identify thousands of LSRs and their DNA attachment sites, expanding known LSR diversity by >100-fold and enabling the prediction of their insertion site specificities. We tested their recombination activity in human cells, classifying them as landing pad, genome-targeting or multi-targeting LSRs. Overall, we achieved up to seven-fold higher recombination than Bxb1 and genome integration efficiencies of 40-75% with cargo sizes over 7 kb. We also demonstrate virus-free, direct integration of plasmid or amplicon libraries for improved functional genomics applications. This systematic discovery of recombinases directly from microbial sequencing data provides a resource of over 60 LSRs experimentally characterized in human cells for large-payload genome insertion without exposed DNA double-stranded breaks.

The formation of macromolecular complexes can be measured by detection of changes in rotational mobility using time-resolved fluorescence anisotropy. However, this method is limited to relatively small molecules (~0.1-30 kDa), excluding the majority of the human proteome and its complexes. We describe selective time-resolved anisotropy with reversibly switchable states (STARSS), which overcomes this limitation and extends the observable mass range by more than three orders of magnitude. STARSS is based on long-lived reversible molecular transitions of switchable fluorescent proteins to resolve the relatively slow rotational diffusivity of large complexes. We used STARSS to probe the rotational mobility of several molecular complexes in cells, including chromatin, the retroviral Gag lattice and activity-regulated cytoskeleton-associated protein oligomers. Because STARSS can probe arbitrarily large structures, it is generally applicable to the entire human proteome.