Cytosine base editors (CBEs) enable programmable genomic C·G-to-T·A transition mutations and typically comprise a modified CRISPR-Cas enzyme, a naturally occurring cytidine deaminase, and an inhibitor of uracil repair. Previous studies have shown that CBEs utilizing naturally occurring cytidine deaminases may cause unguided, genome-wide cytosine deamination. While improved CBEs that decrease stochastic genome-wide off-targets have subsequently been reported, these editors can suffer from suboptimal on-target performance. Here, we report the generation and characterization of CBEs that use engineered variants of TadA (CBE-T) that enable high on-target C·G to T·A across a sequence-diverse set of genomic loci, demonstrate robust activity in primary cells and cause no detectable elevation in genome-wide mutation. Additionally, we report cytosine and adenine base editors (CABEs) catalyzing both A-to-I and C-to-U editing (CABE-Ts). Together with ABEs, CBE-Ts and CABE-Ts enable the programmable installation of all transition mutations using laboratory-evolved TadA variants with improved properties relative to previously reported CBEs.

The electrical current blockade of a peptide or protein threading through a nanopore can be used as a fingerprint of the molecule in biosensor applications. However, threading of full-length proteins has only been achieved using enzymatic unfolding and translocation. Here we describe an enzyme-free approach for unidirectional, slow transport of full-length proteins through nanopores. We show that the combination of a chemically resistant biological nanopore, α-hemolysin (narrowest part is ~1.4 nm in diameter), and a high concentration guanidinium chloride buffer enables unidirectional, single-file protein transport propelled by an electroosmotic effect. We show that the mean protein translocation velocity depends linearly on the applied voltage and translocation times depend linearly on length, resembling the translocation dynamics of ssDNA. Using a supervised machine-learning classifier, we demonstrate that single-translocation events contain sufficient information to distinguish their threading orientation and identity with accuracies larger than 90%. Capture rates of protein are increased substantially when either a genetically encoded charged peptide tail or a DNA tag is added to a protein.

Investigating how chromatin organization determines cell-type-specific gene expression remains challenging. Experimental methods for measuring three-dimensional chromatin organization, such as Hi-C, are costly and have technical limitations, restricting their broad application particularly in high-throughput genetic perturbations. We present C.Origami, a multimodal deep neural network that performs de novo prediction of cell-type-specific chromatin organization using DNA sequence and two cell-type-specific genomic features-CTCF binding and chromatin accessibility. C.Origami enables in silico experiments to examine the impact of genetic changes on chromatin interactions. We further developed an in silico genetic screening approach to assess how individual DNA elements may contribute to chromatin organization and to identify putative cell-type-specific trans-acting regulators that collectively determine chromatin architecture. Applying this approach to leukemia cells and normal T cells, we demonstrate that cell-type-specific in silico genetic screening, enabled by C.Origami, can be used to systematically discover novel chromatin regulation circuits in both normal and disease-related biological systems.

Here we developed an adenine transversion base editor, AYBE, for A-to-C and A-to-T transversion editing in mammalian cells by fusing an adenine base editor (ABE) with hypoxanthine excision protein N-methylpurine DNA glycosylase (MPG). We also engineered AYBE variants enabling targeted editing at genomic loci with higher transversion editing activity (up to 72% for A-to-C or A-to-T editing).

Capturing an individual cell's transcriptional history is a challenge exacerbated by the functional heterogeneity of cellular communities. Here, we leverage reprogrammed tracrRNAs (Rptrs) to record selected cellular transcripts as stored DNA edits in single living bacterial cells. Rptrs are designed to base pair with sensed transcripts, converting them into guide RNAs. The guide RNAs then direct a Cas9 base editor to target an introduced DNA target. The extent of base editing can then be read in the future by sequencing. We use this approach, called TIGER (transcribed RNAs inferred by genetically encoded records), to record heterologous and endogenous transcripts in individual bacterial cells. TIGER can quantify relative expression, distinguish single-nucleotide differences, record multiple transcripts simultaneously and read out single-cell phenomena. We further apply TIGER to record metabolic bet hedging and antibiotic resistance mobilization in Escherichia coli as well as host cell invasion by Salmonella. Through RNA recording, TIGER connects current cellular states with past transcriptional states to decipher complex cellular responses in single cells.

Current methods for epigenomic profiling are limited in their ability to obtain genome-wide information with spatial resolution. We introduce spatial ATAC, a method that integrates transposase-accessible chromatin profiling in tissue sections with barcoded solid-phase capture to perform spatially resolved epigenomics. We show that spatial ATAC enables the discovery of the regulatory programs underlying spatial gene expression during mouse organogenesis, lineage differentiation and in human pathology.

The efficiency of targeted knock-in for cell therapeutic applications is generally low, and the scale is limited. In this study, we developed CLASH, a system that enables high-efficiency, high-throughput knock-in engineering. In CLASH, Cas12a/Cpf1 mRNA combined with pooled adeno-associated viruses mediate simultaneous gene editing and precise transgene knock-in using massively parallel homology-directed repair, thereby producing a pool of stably integrated mutant variants each with targeted gene editing. We applied this technology in primary human T cells and performed time-coursed CLASH experiments in blood cancer and solid tumor models using CD3, CD8 and CD4 T cells, enabling pooled generation and unbiased selection of favorable CAR-T variants. Emerging from CLASH experiments, a unique CRISPR RNA (crRNA) generates an exon3 skip mutant of PRDM1 in CAR-Ts, which leads to increased proliferation, stem-like properties, central memory and longevity in these cells, resulting in higher efficacy in vivo across multiple cancer models, including a solid tumor model. The versatility of CLASH makes it broadly applicable to diverse cellular and therapeutic engineering applications.

The axial resolution of three-dimensional structured illumination microscopy (3D SIM) is limited to ∼300 nm. Here we present two distinct, complementary methods to improve axial resolution in 3D SIM with minimal or no modification to the optical system. We show that placing a mirror directly opposite the sample enables four-beam interference with higher spatial frequency content than 3D SIM illumination, offering near-isotropic imaging with ∼120-nm lateral and 160-nm axial resolution. We also developed a deep learning method achieving ∼120-nm isotropic resolution. This method can be combined with denoising to facilitate volumetric imaging spanning dozens of timepoints. We demonstrate the potential of these advances by imaging a variety of cellular samples, delineating the nanoscale distribution of vimentin and microtubule filaments, observing the relative positions of caveolar coat proteins and lysosomal markers and visualizing cytoskeletal dynamics within T cells in the early stages of immune synapse formation.

Deep-learning language models have shown promise in various biotechnological applications, including protein design and engineering. Here we describe ProGen, a language model that can generate protein sequences with a predictable function across large protein families, akin to generating grammatically and semantically correct natural language sentences on diverse topics. The model was trained on 280 million protein sequences from >19,000 families and is augmented with control tags specifying protein properties. ProGen can be further fine-tuned to curated sequences and tags to improve controllable generation performance of proteins from families with sufficient homologous samples. Artificial proteins fine-tuned to five distinct lysozyme families showed similar catalytic efficiencies as natural lysozymes, with sequence identity to natural proteins as low as 31.4%. ProGen is readily adapted to diverse protein families, as we demonstrate with chorismate mutase and malate dehydrogenase.

A barrier to advancing engineered adeno-associated viral vectors (AAVs) for precision access to cell subtypes is a lack of high-throughput, high-resolution assays to characterize in vivo transduction profiles. In this study, we developed an ultrasensitive, sequential fluorescence in situ hybridization (USeqFISH) method for spatial transcriptomic profiling of endogenous and viral RNA with a short barcode in intact tissue volumes by integrating hydrogel-based tissue clearing, enhanced signal amplification and multiplexing using sequential labeling. Using USeqFISH, we investigated the transduction and cell subtype tropisms across mouse brain regions of six systemic AAVs, including AAV-PHP.AX, a new variant that transduces robustly and efficiently across neurons and astrocytes. Here we reveal distinct cell subtype biases of each AAV variant, including a bias of AAV-PHP.N toward excitatory neurons. USeqFISH also enables profiling of pooled regulatory cargos, as we show for a 13-variant pool of microRNA target sites in AAV genomes. Lastly, we demonstrate potential applications of USeqFISH for in situ AAV profiling and multimodal single-cell analysis in non-human primates.

Human intestinal organoids (HIOs) derived from pluripotent stem cells provide a valuable model for investigating human intestinal organogenesis and physiology, but they lack the immune components required to fully recapitulate the complexity of human intestinal biology and diseases. To address this issue and to begin to decipher human intestinal-immune crosstalk during development, we generated HIOs containing immune cells by transplanting HIOs under the kidney capsule of mice with a humanized immune system. We found that human immune cells temporally migrate to the mucosa and form cellular aggregates that resemble human intestinal lymphoid follicles. Moreover, after microbial exposure, epithelial microfold cells are increased in number, leading to immune cell activation determined by the secretion of IgA antibodies in the HIO lumen. This in vivo HIO system with human immune cells provides a framework for future studies on infection- or allergen-driven intestinal diseases.

Cys2His2 zinc finger (ZF) domains engineered to bind specific target sequences in the genome provide an effective strategy for programmable regulation of gene expression, with many potential therapeutic applications. However, the structurally intricate engagement of ZF domains with DNA has made their design challenging. Here we describe the screening of 49 billion protein-DNA interactions and the development of a deep-learning model, ZFDesign, that solves ZF design for any genomic target. ZFDesign is a modern machine learning method that models global and target-specific differences induced by a range of library environments and specifically takes into account compatibility of neighboring fingers using a novel hierarchical transformer architecture. We demonstrate the versatility of designed ZFs as nucleases as well as activators and repressors by seamless reprogramming of human transcription factors. These factors could be used to upregulate an allele of haploinsufficiency, downregulate a gain-of-function mutation or test the consequence of regulation of a single gene as opposed to the many genes that a transcription factor would normally influence.

Robust and precise transcript targeting in mammalian cells remains a difficult challenge using existing approaches due to inefficiency, imprecision and subcellular compartmentalization. Here we show that the clustered regularly interspaced short palindromic repeats (CRISPR)-Csm complex, a multiprotein effector from type III CRISPR immune systems in prokaryotes, provides surgical RNA ablation of both nuclear and cytoplasmic transcripts. As part of the most widely occurring CRISPR adaptive immune pathway, CRISPR-Csm uses a programmable RNA-guided mechanism to find and degrade target RNA molecules without inducing indiscriminate trans-cleavage of cellular RNAs, giving it an important advantage over the CRISPR-Cas13 family of enzymes. Using single-vector delivery of the Streptococcus thermophilus Csm complex, we observe high-efficiency RNA knockdown (90-99%) and minimal off-target effects in human cells, outperforming existing technologies including short hairpin RNA- and Cas13-mediated knockdown. We also find that catalytically inactivated Csm achieves specific and durable RNA binding, a property we harness for live-cell RNA imaging. These results establish the feasibility and efficacy of multiprotein CRISPR-Cas effector complexes as RNA-targeting tools in eukaryotes.

Characterizing drug-target engagement is essential to understand how small molecules influence cellular functions. Here we present Chem-map for in situ mapping of small molecules that interact with DNA or chromatin-associated proteins, utilizing small-molecule-directed transposase Tn5 tagmentation. We demonstrate Chem-map for three distinct drug-binding modalities as follows: molecules that target a chromatin protein, a DNA secondary structure or that intercalate in DNA. We map the BET bromodomain protein-binding inhibitor JQ1 and provide interaction maps for DNA G-quadruplex structure-binding molecules PDS and PhenDC3. Moreover, we determine the binding sites of the widely used anticancer drug doxorubicin in human leukemia cells; using the Chem-map of doxorubicin in cells exposed to the histone deacetylase inhibitor tucidinostat reveals the potential clinical advantages of this combination therapy. In situ mapping with Chem-map of small-molecule interactions with DNA and chromatin proteins provides insights that will enhance understanding of genome and chromatin function and therapeutic interventions.

Defining the cellular response to pharmacological agents is critical for understanding the mechanism of action of small molecule perturbagens. Here, we developed a 96-well-plate-based high-throughput screening infrastructure for quantitative proteomics and profiled 875 compounds in a human cancer cell line with near-comprehensive proteome coverage. Examining the 24-h proteome changes revealed ligand-induced changes in protein expression and uncovered rules by which compounds regulate their protein targets while identifying putative dihydrofolate reductase and tankyrase inhibitors. We used protein-protein and compound-compound correlation networks to uncover mechanisms of action for several compounds, including the adrenergic receptor antagonist JP1302, which we show disrupts the FACT complex and degrades histone H1. By profiling many compounds with overlapping targets covering a broad chemical space, we linked compound structure to mechanisms of action and highlighted off-target polypharmacology for molecules within the library.

Monoclonal antibodies (Abs) that recognize major histocompatability complex (MHC)-presented tumor antigens in a manner similar to T cell receptors (TCRs) have great potential as cancer immunotherapeutics. However, isolation of 'TCR-mimic' (TCRm) Abs is laborious because Abs have not evolved the structurally nuanced peptide-MHC restriction of αβ-TCRs. Here, we present a strategy for rapid isolation of highly peptide-specific and 'MHC-restricted' Abs by re-engineering preselected Abs that engage peptide-MHC in a manner structurally similar to that of conventional αβ-TCRs. We created structure-based libraries focused on the peptide-interacting residues of TCRm Ab complementarity-determining region (CDR) loops, and rapidly generated MHC-restricted Abs to both mouse and human tumor antigens that specifically killed target cells when formatted as IgG, bispecific T cell engager (BiTE) and chimeric antigen receptor-T (CAR-T). Crystallographic analysis of one selected pMHC-restricted Ab revealed highly peptide-specific recognition, validating the engineering strategy. This approach can yield tumor antigen-specific antibodies in several weeks, potentially enabling rapid clinical translation.

Recording transcriptional histories of a cell would enable deeper understanding of cellular developmental trajectories and responses to external perturbations. Here we describe an engineered protein fiber that incorporates diverse fluorescent marks during its growth to store a ticker tape-like history. An embedded HaloTag reporter incorporates user-supplied dyes, leading to colored stripes that map the growth of each individual fiber to wall clock time. A co-expressed eGFP tag driven by a promoter of interest records a history of transcriptional activation. High-resolution multi-spectral imaging on fixed samples reads the cellular histories, and interpolation of eGFP marks relative to HaloTag timestamps provides accurate absolute timing. We demonstrate recordings of doxycycline-induced transcription in HEK cells and cFos promoter activation in cultured neurons, with a single-cell absolute accuracy of 30-40 minutes over a 12-hour recording. The protein-based ticker tape design we present here could be generalized to achieve massively parallel single-cell recordings of diverse physiological modalities.

Annotating newly sequenced genomes and determining alternative isoforms from long-read RNA data are complex and incompletely solved problems. Here we present IsoQuant-a computational tool using intron graphs that accurately reconstructs transcripts both with and without reference genome annotation. For novel transcript discovery, IsoQuant reduces the false-positive rate fivefold and 2.5-fold for Oxford Nanopore reference-based or reference-free mode, respectively. IsoQuant also improves performance for Pacific Biosciences data.

Spatial transcriptomics and proteomics provide complementary information that independently transformed our understanding of complex biological processes. However, experimental integration of these modalities is limited. To overcome this, we developed Spatial PrOtein and Transcriptome Sequencing (SPOTS) for high-throughput simultaneous spatial transcriptomics and protein profiling. Compared with unimodal measurements, SPOTS substantially improves signal resolution and cell clustering and enhances the discovery power in differential gene expression analysis across tissue regions.

Author information: (1)Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA. xiy010@health.ucsd.edu. (2)Rady Children's Institute for Genomic Medicine, San Diego, CA, USA. xiy010@health.ucsd.edu. (3)Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA. (4)Rady Children's Institute for Genomic Medicine, San Diego, CA, USA. (5)Department of Pediatrics, Section of Genetics and Metabolism, University of Colorado School of Medicine, Aurora, CO, USA. (6)Department of Quantitative Health Sciences, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA. (7)Department of Cellular and Molecular Medicine, UC San Diego, La Jolla, CA, USA. (8)Department of Bioengineering, UC San Diego, La Jolla, CA, USA. (9)Moores Cancer Center, UC San Diego, La Jolla, CA, USA. (10)Center for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, China. (11)Beyster Center for Genomics of Psychiatric Diseases, University of California, San Diego, La Jolla, CA, USA. (12)Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA. (13)Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA. (14)Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA. (15)Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA. jogleeson@health.ucsd.edu. (16)Rady Children's Institute for Genomic Medicine, San Diego, CA, USA. jogleeson@health.ucsd.edu. (#)Contributed equally

N6-methyladenosine (m6A), the most abundant internal messenger RNA modification in higher eukaryotes, serves myriad roles in regulating cellular processes. Functional dissection of m6A is, however, hampered in part by the lack of high-resolution and quantitative detection methods. Here we present evolved TadA-assisted N6-methyladenosine sequencing (eTAM-seq), an enzyme-assisted sequencing technology that detects and quantifies m6A by global adenosine deamination. With eTAM-seq, we analyze the transcriptome-wide distribution of m6A in HeLa and mouse embryonic stem cells. The enzymatic deamination route employed by eTAM-seq preserves RNA integrity, facilitating m6A detection from limited input samples. In addition to transcriptome-wide m6A profiling, we demonstrate site-specific, deep-sequencing-free m6A quantification with as few as ten cells, an input demand orders of magnitude lower than existing quantitative profiling methods. We envision that eTAM-seq will enable researchers to not only survey the m6A landscape at unprecedented resolution, but also detect m6A at user-specified loci with a simple workflow.

Observing cellular physiological histories is key to understanding normal and disease-related processes. Here we describe expression recording islands-a fully genetically encoded approach that enables both continual digital recording of biological information within cells and subsequent high-throughput readout in fixed cells. The information is stored in growing intracellular protein chains made of self-assembling subunits, human-designed filament-forming proteins bearing different epitope tags that each correspond to a different cellular state or function (for example, gene expression downstream of neural activity or pharmacological exposure), allowing the physiological history to be read out along the ordered subunits of protein chains with conventional optical microscopy. We use expression recording islands to record gene expression timecourse downstream of specific pharmacological and physiological stimuli in cultured neurons and in living mouse brain, with a time resolution of a fraction of a day, over periods of days to weeks.

CRISPR-associated transposases (CASTs) enable recombination-independent, multi-kilobase DNA insertions at RNA-programmed genomic locations. However, the utility of type V-K CASTs is hindered by high off-target integration and a transposition mechanism that results in a mixture of desired simple cargo insertions and undesired plasmid cointegrate products. Here we overcome both limitations by engineering new CASTs with improved integration product purity and genome-wide specificity. To do so, we engineered a nicking homing endonuclease fusion to TnsB (named HELIX) to restore the 5' nicking capability needed for cargo excision on the DNA donor. HELIX enables cut-and-paste DNA insertion with up to 99.4% simple insertion product purity, while retaining robust integration efficiencies on genomic targets. HELIX has substantially higher on-target specificity than canonical CASTs, and we identify several novel factors that further regulate targeted and genome-wide integration. Finally, we extend HELIX to other type V-K orthologs and demonstrate the feasibility of HELIX-mediated integration in human cell contexts.

Expansion microscopy enables nanoimaging with conventional microscopes by physically and isotropically magnifying preserved biological specimens embedded in a crosslinked water-swellable hydrogel. Current expansion microscopy protocols require prior treatment with reactive anchoring chemicals to link specific labels and biomolecule classes to the gel. We describe a strategy called Magnify, which uses a mechanically sturdy gel that retains nucleic acids, proteins and lipids without the need for a separate anchoring step. Magnify expands biological specimens up to 11 times and facilitates imaging of cells and tissues with effectively around 25-nm resolution using a diffraction-limited objective lens of about 280 nm on conventional optical microscopes or with around 15 nm effective resolution if combined with super-resolution optical fluctuation imaging. We demonstrate Magnify on a broad range of biological specimens, providing insight into nanoscopic subcellular structures, including synaptic proteins from mouse brain, podocyte foot processes in formalin-fixed paraffin-embedded human kidney and defects in cilia and basal bodies in drug-treated human lung organoids.

Allogeneic cell therapeutics for cancer therapy or regenerative medicine are susceptible to antibody-mediated killing, which diminishes their efficacy. Here we report a strategy to protect cells from antibody-mediated killing that relies on engineered overexpression of the IgG receptor CD64. We show that human and mouse iPSC-derived endothelial cells (iECs) overexpressing CD64 escape antibody-dependent cellular cytotoxicity (ADCC) and complement-dependent cytotoxicity from IgG antibodies in vitro and in ADCC-enabled mice. When CD64 expression was combined with hypoimmune genetic modifications known to protect against cellular immunity, B2M-/-CIITA-/- CD47/CD64-transgenic iECs were resistant to both IgG antibody-mediated and cellular immune killing in vitro and in humanized mice. Mechanistic studies demonstrated that CD64 or its intracellularly truncated analog CD64t effectively capture monomeric IgG and occupy their Fc, and the IgG bind and occupy their target antigens. In three applications of the approach, human CD64t-engineered thyroid epithelial cells, pancreatic beta cells and CAR T cells withstood clinically relevant levels of graft-directed antibodies and fully evaded antibody-mediated killing.

Nanopore sequencers can select which DNA molecules to sequence, rejecting a molecule after analysis of a small initial part. Currently, selection is based on predetermined regions of interest that remain constant throughout an experiment. Sequencing efforts, thus, cannot be re-focused on molecules likely contributing most to experimental success. Here we present BOSS-RUNS, an algorithmic framework and software to generate dynamically updated decision strategies. We quantify uncertainty at each genome position with real-time updates from data already observed. For each DNA fragment, we decide whether the expected decrease in uncertainty that it would provide warrants fully sequencing it, thus optimizing information gain. BOSS-RUNS mitigates coverage bias between and within members of a microbial community, leading to improved variant calling; for example, low-coverage sites of a species at 1% abundance were reduced by 87.5%, with 12.5% more single-nucleotide polymorphisms detected. Such data-driven updates to molecule selection are applicable to many sequencing scenarios, such as enriching for regions with increased divergence or low coverage, reducing time-to-answer.

Regulation of chromatin states involves the dynamic interplay between different histone modifications to control gene expression. Recent advances have enabled mapping of histone marks in single cells, but most methods are constrained to profile only one histone mark per cell. Here, we present an integrated experimental and computational framework, scChIX-seq (single-cell chromatin immunocleavage and unmixing sequencing), to map several histone marks in single cells. scChIX-seq multiplexes two histone marks together in single cells, then computationally deconvolves the signal using training data from respective histone mark profiles. This framework learns the cell-type-specific correlation structure between histone marks, and therefore does not require a priori assumptions of their genomic distributions. Using scChIX-seq, we demonstrate multimodal analysis of histone marks in single cells across a range of mark combinations. Modeling dynamics of in vitro macrophage differentiation enables integrated analysis of chromatin velocity. Overall, scChIX-seq unlocks systematic interrogation of the interplay between histone modifications in single cells.

Cancer neoantigens that arise from tumor mutations are drivers of tumor-specific T cell responses, but identification of T cell-recognized neoantigens in individual patients is challenging. Previous methods have restricted antigen discovery to selected HLA alleles, thereby limiting the breadth of neoantigen repertoires that can be uncovered. Here, we develop a genetic neoantigen screening system that allows sensitive identification of CD4+ and CD8+ T cell-recognized neoantigens across patients' complete HLA genotypes.

Ionizing radiation acoustic imaging (iRAI) allows online monitoring of radiation's interactions with tissues during radiation therapy, providing real-time, adaptive feedback for cancer treatments. We describe an iRAI volumetric imaging system that enables mapping of the three-dimensional (3D) radiation dose distribution in a complex clinical radiotherapy treatment. The method relies on a two-dimensional matrix array transducer and a matching multi-channel preamplifier board. The feasibility of imaging temporal 3D dose accumulation was first validated in a tissue-mimicking phantom. Next, semiquantitative iRAI relative dose measurements were verified in vivo in a rabbit model. Finally, real-time visualization of the 3D radiation dose delivered to a patient with liver metastases was accomplished with a clinical linear accelerator. These studies demonstrate the potential of iRAI to monitor and quantify the 3D radiation dose deposition during treatment, potentially improving radiotherapy treatment efficacy using real-time adaptive treatment.

Author information: (1)Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. (2)Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark. (3)Copenhagen Research Centre for Mental Health, Mental Health Centre Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark. (4)Department of Immunology and Microbiology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. (5)C.N.R. Institute of Neuroscience, Padova, Italy. (6)Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK. (7)Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland. (8)Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, UK. (9)Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, Germany. (10)Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, Germany. (11)Chair of Food Chemistry and Molecular and Sensory Science, Technical University of Munich, Freising, Germany. (12)Metabolomics and Proteomics Core, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Neuherberg, Germany. (13)Affinity Proteomics, Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden. (14)Research and Development Global Development, Translational Medicine and Clinical Pharmacology, Sanofi-Aventis Deutschland, Frankfurt, Germany. (15)Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. (16)University of Exeter Medical School, Exeter, UK. (17)The Immunoassay Biomarker Core Laboratory, School of Medicine, University of Dundee, Dundee, UK. (18)Research Centre for Optimal Health, Department of Life Sciences, University of Westminster, London, UK. (19)Section for Nutrition Research, Faculty of Medicine, Imperial College London, London, UK. (20)Department of Radiology, Copenhagen University Hospital Herlev-Gentofte, Herlev, Denmark. (21)Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands. (22)Department of General Practice, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands. (23)Department of Biomedical Data Science, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands. (24)Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands. (25)Inserm, Univ Lille, CHU Lille, Lille Pasteur Institute, EGID, Lille, France. (26)MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK. (27)Department of Medicine, University of Eastern Finland, Kuopio, Finland. (28)Institute of Cellular Medicine, Newcastle University, Newcastle, UK. (29)Diabetes Research Network, Royal Victoria Infirmary, Newcastle, UK. (30)Centre for Health, Law and Emerging Technologies (HeLEX), Faculty of Law, University of Oxford, Oxford, UK. (31)Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Malmö, Sweden. (32)Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, UK. (33)Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK. (34)Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, CRC, Lund University, SUS, Malmö, Sweden. (35)Eli Lilly Regional Operations, Vienna, Austria. (36)Harvard T.H. Chan School of Public Health, Boston, MA, USA. (37)OCDEM, Radcliffe Department of Medicine, University of Oxford, Oxford, UK. (38)Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. (39)Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. (40)Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia. (41)Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK. (42)Genentech, South San Francisco, CA, USA. (43)Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. simon.rasmussen@cpr.ku.dk. (44)Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. soren.brunak@cpr.ku.dk. (45)Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark. soren.brunak@cpr.ku.dk.

Identification of CD8+ T cell epitopes is critical for the development of immunotherapeutics. Existing methods for major histocompatibility complex class I (MHC class I) ligand discovery are time intensive, specialized and unable to interrogate specific proteins on a large scale. Here, we present EpiScan, which uses surface MHC class I levels as a readout for whether a genetically encoded peptide is an MHC class I ligand. Predetermined starting pools composed of >100,000 peptides can be designed using oligonucleotide synthesis, permitting large-scale MHC class I screening. We exploit this programmability of EpiScan to uncover an unappreciated role for cysteine that increases the number of predicted ligands by 9-21%, reveal affinity hierarchies by analysis of biased anchor peptide libraries and screen viral proteomes for MHC class I ligands. Using these data, we generate and iteratively refine peptide binding predictions to create EpiScan Predictor. EpiScan Predictor performs comparably to other state-of-the-art MHC class I peptide binding prediction algorithms without suffering from underrepresentation of cysteine-containing peptides. Thus, targeted immunopeptidomics using EpiScan will accelerate CD8+ T cell epitope discovery toward the goal of individual-specific immunotherapeutics.

Erratum in Nat Biotechnol. 2023 Jan 16;:

Generation of stable gene-edited plant lines using clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9) requires a lengthy process of outcrossing to eliminate CRISPR-Cas9-associated sequences and produce transgene-free lines. We have addressed this issue by designing fusions of Cas9 and guide RNA transcripts to tRNA-like sequence motifs that move RNAs from transgenic rootstocks to grafted wild-type shoots (scions) and achieve heritable gene editing, as demonstrated in wild-type Arabidopsis thaliana and Brassica rapa. The graft-mobile gene editing system enables the production of transgene-free offspring in one generation without the need for transgene elimination, culture recovery and selection, or use of viral editing vectors. We anticipate that using graft-mobile editing systems for transgene-free plant production may be applied to a wide range of breeding programs and crop plants.

Ultrasound allows imaging at a much greater depth than optical methods, but existing genetically encoded acoustic reporters for in vivo cellular imaging have been limited by poor sensitivity, specificity and in vivo expression. Here we describe two acoustic reporter genes (ARGs)-one for use in bacteria and one for use in mammalian cells-identified through a phylogenetic screen of candidate gas vesicle gene clusters from diverse bacteria and archaea that provide stronger ultrasound contrast, produce non-linear signals distinguishable from background tissue and have stable long-term expression. Compared to their first-generation counterparts, these improved bacterial and mammalian ARGs produce 9-fold and 38-fold stronger non-linear contrast, respectively. Using these new ARGs, we non-invasively imaged in situ tumor colonization and gene expression in tumor-homing therapeutic bacteria, tracked the progression of tumor gene expression and growth in a mouse model of breast cancer, and performed gene-expression-guided needle biopsies of a genetically mosaic tumor, demonstrating non-invasive access to dynamic biological processes at centimeter depth.

Oxytocin (OT), a peptide hormone and neuromodulator, is involved in diverse physiological and pathophysiological processes in the central nervous system and the periphery. However, the regulation and functional sequences of spatial OT release in the brain remain poorly understood. We describe a genetically encoded G-protein-coupled receptor activation-based (GRAB) OT sensor called GRABOT1.0. In contrast to previous methods, GRABOT1.0 enables imaging of OT release ex vivo and in vivo with suitable sensitivity, specificity and spatiotemporal resolution. Using this sensor, we visualize stimulation-induced OT release from specific neuronal compartments in mouse brain slices and discover that N-type calcium channels predominantly mediate axonal OT release, whereas L-type calcium channels mediate somatodendritic OT release. We identify differences in the fusion machinery of OT release for axon terminals versus somata and dendrites. Finally, we measure OT dynamics in various brain regions in mice during male courtship behavior. Thus, GRABOT1.0 provides insights into the role of compartmental OT release in physiological and behavioral functions.

The human microbiome influences the efficacy and safety of a wide variety of commonly prescribed drugs. Designing precision medicine approaches that incorporate microbial metabolism would require strain- and molecule-resolved, scalable computational modeling. Here, we extend our previous resource of genome-scale metabolic reconstructions of human gut microorganisms with a greatly expanded version. AGORA2 (assembly of gut organisms through reconstruction and analysis, version 2) accounts for 7,302 strains, includes strain-resolved drug degradation and biotransformation capabilities for 98 drugs, and was extensively curated based on comparative genomics and literature searches. The microbial reconstructions performed very well against three independently assembled experimental datasets with an accuracy of 0.72 to 0.84, surpassing other reconstruction resources and predicted known microbial drug transformations with an accuracy of 0.81. We demonstrate that AGORA2 enables personalized, strain-resolved modeling by predicting the drug conversion potential of the gut microbiomes from 616 patients with colorectal cancer and controls, which greatly varied between individuals and correlated with age, sex, body mass index and disease stages. AGORA2 serves as a knowledge base for the human microbiome and paves the way to personalized, predictive analysis of host-microbiome metabolic interactions.

Engineered live bacteria could provide a new modality for treating lung infections, a major cause of mortality worldwide. In the present study, we engineered a genome-reduced human lung bacterium, Mycoplasma pneumoniae, to treat ventilator-associated pneumonia, a disease with high hospital mortality when associated with Pseudomonas aeruginosa biofilms. After validating the biosafety of an attenuated M. pneumoniae chassis in mice, we introduced four transgenes into the chromosome by transposition to implement bactericidal and biofilm degradation activities. We show that this engineered strain has high efficacy against an acute P. aeruginosa lung infection in a mouse model. In addition, we demonstrated that the engineered strain could dissolve biofilms formed in endotracheal tubes of patients with ventilator-associated pneumonia and be combined with antibiotics targeting the peptidoglycan layer to increase efficacy against Gram-positive and Gram-negative bacteria. We expect our M. pneumoniae-engineered strain to be able to treat biofilm-associated infections in the respiratory tract.

Muscle-specific tyrosine kinase myasthenia gravis (MuSK MG) is an autoimmune disease that causes life-threatening muscle weakness due to anti-MuSK autoantibodies that disrupt neuromuscular junction signaling. To avoid chronic immunosuppression from current therapies, we engineered T cells to express a MuSK chimeric autoantibody receptor with CD137-CD3ζ signaling domains (MuSK-CAART) for precision targeting of B cells expressing anti-MuSK autoantibodies. MuSK-CAART demonstrated similar efficacy as anti-CD19 chimeric antigen receptor T cells for depletion of anti-MuSK B cells and retained cytolytic activity in the presence of soluble anti-MuSK antibodies. In an experimental autoimmune MG mouse model, MuSK-CAART reduced anti-MuSK IgG without decreasing B cells or total IgG levels, reflecting MuSK-specific B cell depletion. Specific off-target interactions of MuSK-CAART were not identified in vivo, in primary human cell screens or by high-throughput human membrane proteome array. These data contributed to an investigational new drug application and phase 1 clinical study design for MuSK-CAART for the treatment of MuSK autoantibody-positive MG.

Synapses are crucial structures that mediate signal transmission between neurons in complex neural circuits and display considerable morphological and electrophysiological heterogeneity. So far we still lack a high-throughput method to profile the molecular heterogeneity among individual synapses. In the present study, we develop a droplet-based single-cell (sc) total-RNA-sequencing platform, called Multiple-Annealing-and-Tailing-based Quantitative scRNA-seq in Droplets, for transcriptome profiling of individual neurites, primarily composed of synaptosomes. In the synaptosome transcriptome, or 'synaptome', profiling of both mouse and human brain samples, we detect subclusters among synaptosomes that are associated with neuronal subtypes and characterize the landscape of transcript splicing that occurs within synapses. We extend synaptome profiling to synaptopathy in an Alzheimer's disease (AD) mouse model and discover AD-associated synaptic gene expression changes that cannot be detected by single-nucleus transcriptome profiling. Overall, our results show that this platform provides a high-throughput, single-synaptosome transcriptome profiling tool that will facilitate future discoveries in neuroscience.

Cells interpret mechanical stimuli from their environments and neighbors, but the ability to engineer customized mechanosensing capabilities has remained a synthetic and mechanobiology challenge. Here we introduce tension-tuned synthetic Notch (SynNotch) receptors to convert extracellular and intercellular forces into specifiable gene expression changes. By elevating the tension requirements of SynNotch activation, in combination with structure-guided mutagenesis, we designed a set of receptors with mechanical sensitivities spanning the physiologically relevant picoNewton range. Cells expressing these receptors can distinguish between varying tensile forces and respond by enacting customizable transcriptional programs. We applied these tools to design a decision-making circuit, through which fibroblasts differentiate into myoblasts upon stimulation with distinct tension magnitudes. We also characterize cell-generated forces transmitted between cells during Notch signaling. Overall, this work provides insight into how mechanically induced changes in protein structure can be used to transduce physical forces into biochemical signals. The system should facilitate the further programming and dissection of force-related phenomena in biological systems.

Prime editing is a versatile genome editing tool but requires experimental optimization of the prime editing guide RNA (pegRNA) to achieve high editing efficiency. Here we conducted a high-throughput screen to analyze prime editing outcomes of 92,423 pegRNAs on a highly diverse set of 13,349 human pathogenic mutations that include base substitutions, insertions and deletions. Based on this dataset, we identified sequence context features that influence prime editing and trained PRIDICT (prime editing guide prediction), an attention-based bidirectional recurrent neural network. PRIDICT reliably predicts editing rates for all small-sized genetic changes with a Spearman's R of 0.85 and 0.78 for intended and unintended edits, respectively. We validated PRIDICT on endogenous editing sites as well as an external dataset and showed that pegRNAs with high (>70) versus low (<70) PRIDICT scores showed substantially increased prime editing efficiencies in different cell types in vitro (12-fold) and in hepatocytes in vivo (tenfold), highlighting the value of PRIDICT for basic and for translational research applications.

CD123, the alpha chain of the IL-3 receptor, is an attractive target for acute myeloid leukemia (AML) treatment. However, cytotoxic antibodies or T cell engagers targeting CD123 had insufficient efficacy or safety in clinical trials. We show that expression of CD64, the high-affinity receptor for human IgG, on AML blasts confers resistance to anti-CD123 antibody-dependent cell cytotoxicity (ADCC) in vitro. We engineer a trifunctional natural killer cell engager (NKCE) that targets CD123 on AML blasts and NKp46 and CD16a on NK cells (CD123-NKCE). CD123-NKCE has potent antitumor activity against primary AML blasts regardless of CD64 expression and induces NK cell activation and cytokine secretion only in the presence of AML cells. Its antitumor activity in a mouse CD123+ tumor model exceeds that of the benchmark ADCC-enhanced antibody. In nonhuman primates, it had prolonged pharmacodynamic effects, depleting CD123+ cells for more than 10 days with no signs of toxicity and very low inflammatory cytokine induction over a large dose range. These results support clinical development of CD123-NKCE.