Biology subjects

Gootenberg, J. S.

Publications and source records attributed to Gootenberg, J. S..

12 recordsLinked to original sources

bioRxiv2026

flashscenic: Accelerated GRN Analysis with RegDiffusion for Large-Scale Single-Cell Data

Single-cell gene regulatory network (GRN) analysis via the SCENIC framework provides biologically interpretable cell-state representations through motif-validated transcription factor (TF) regulon activities. However, sequential, CPU-bound implementations (pySCENIC) constrain scalability to highly variable genes and make the repeated executions needed to resolve network stochasticity computationally prohibitive. Furthermore, while regulon activity is hypothesized to mitigate technical batch effects, its integration performance has never been quantitatively assessed against modern data integration benchmarks. We present flashscenic, an end-to-end GPU-accelerated framework that resolves these bottlenecks and expands the practical scope of single-cell regulatory genomics. By reformulating module construction, cisTarget motif pruning, and AUCell scoring into batched GPU tensor operations, flashscenic achieves a 12- to 27-fold downstream speedup over pySCENIC, while maintaining strict numerical equivalence (Pearson r = 0.9996). Leveraging this throughput, we conducted the first systematic benchmark of nine consensus aggregation strategies across multiple independent tissue cohorts, demonstrating that discrete post-pruning recurrence voting ([≥]50% recurrence, [≥]5 targets per regulon) maximizes biological fidelity. Finally, data integration benchmarking across a 116,043-cell acute myeloid leukemia (AML) atlas quantitatively demonstrates that uncorrected TF activity provides an intrinsic, unsupervised batch-integration benefit over raw PCA. Combining it with a standard batch integration method matches or outperforms canonical expression-based integration while accurately recovering lineage-defining and oncogenic regulators (CEBPA, HOXA9). flashscenic is available via pip install flashscenic, with source code and tutorials at https://github.com/haozhu233/flashscenic.

bioinformatics↗

bioRxiv2026

Programmable Lipid Nanoparticle Targeting via Corona Engineering

Lipid nanoparticles (LNPs) are a versatile platform for in vivo delivery of biomolecules, yet systemically administered LNPs predominantly accumulate in the liver, limiting extrahepatic applications. This tropism arises from LNP adsorption of serum proteins, particularly apolipoprotein E (ApoE), which binds to LDL receptors (LDLR) on hepatocytes. Here, we overcome this tropism with two compatible strategies. First, we engineer dead ApoE mutants (dApoE) with five receptor-binding domain substitutions that selectively disrupt the ApoE-LDLR interaction but retain lipid binding. In cultured cells, pre-coating with these dApoE markedly inhibited LDLR-mediated uptake. Second, we pretreat cells with hyperactive PCSK9 (haPCSK9) to internalize surface LDLR, similarly reducing the LDLR-mediate uptake of LNPs. In vivo, both strategies substantially reduced liver LNP transduction without inducing redistribution to other major organs. To retarget LNP to new cell types we combined antibody conjugation with dApoE or haPCSK9, effectively engineering tropism to T cells, brain and lung tissues in vivo with substantially reduced hepatic background. In pilot studies, this strategy enabled specific delivery of reporter mRNAs to additional tissues, including megakaryocytes, hematopoietic progenitor cells, and cardiac tissue, and in aged T cells, to deliver miRNA cargos that produced a sustained reduction in DNA damage markers following a single systemic dose. dApoE coated CD5-targeted LNPs generated CAR+ T cells that retained cytotoxicity against CD19+ targets, while simultaneously reducing hepatocyte transduction by 90%. These findings establish a modular framework that integrates dApoE and haPCSK9-mediated detargeting with antibody-based retargeting, allowing for improvements in LNP specificity and broadening the therapeutic scope of LNPs.

bioengineering↗

bioRxiv2025

T-PGI: an engineered STITCHR system for scarless, programmable genome integration

Scarless, programmable insertion of defined DNA remains a central goal for therapeutic genome editing. We introduce T-PGI (Transposon-mediated programmable genomic integration), an engineered implementation of STITCHR that preserves target-primed reverse transcription (TPRT) while substantially improving efficiency, specificity, and modularity. T-PGI uses R2Tocc, a low-background ortholog that we further engineered through defined deletions, rational point mutations, and modular domain insertions to enhance performance. The system employs paired nCas9 nicks flanking homology arms and bicistronic co-expression with dual NLSs, together with optimized RNA donor designs. Using combinatorial guide-template screening, T-PGI achieves robust integration across diverse cargos, including precise cassette insertion following multi-kilobase deletions. Short- and long-read sequencing confirm high-fidelity insertion with minimal local indels or structural variants. Collectively, these advances establish T-PGI as a practical and adaptable platform for accurate, scarless genome integration and provide concise design principles spanning enzyme architecture, donor configuration, and guide pairing for next-generation therapeutic editing.

bioengineering↗

bioRxiv2024

Rapid protein evolution by few-shot learning with a protein language model

Directed evolution of proteins is critical for applications in basic biological research, therapeutics, diagnostics, and sustainability. However, directed evolution methods are labor intensive, cannot efficiently optimize over multiple protein properties, and are often trapped by local maxima. In silico-directed evolution methods incorporating protein language models (PLMs) have the potential to accelerate this engineering process, but current approaches fail to generalize across diverse protein families. We introduce EVOLVEpro, a few-shot active learning framework to rapidly improve protein activity using a combination of PLMs and protein activity predictors, achieving improved activity with as few as four rounds of evolution. EVOLVEpro substantially enhances the efficiency and effectiveness of in silico protein evolution, surpassing current state-of-the-art methods and yielding proteins with up to 100-fold improvement of desired properties. We showcase EVOLVEpro for five proteins across three applications: T7 RNA polymerase for RNA production, a miniature CRISPR nuclease, a prime editor, and an integrase for genome editing, and a monoclonal antibody for epitope binding. These results demonstrate the advantages of few-shot active learning with small amounts of experimental data over zero-shot predictions. EVOLVEpro paves the way for broader applications of AI-guided protein engineering in biology and medicine.

bioengineering↗

bioRxiv2024

Programmable RNA writing with trans-splicing

RNA editing offers the opportunity to introduce either stable or transient modifications to nucleic acid sequence without permanent off-target effects, but installation of arbitrary edits into the transcriptome is currently infeasible. Here, we describe Programmable RNA Editing & Cleavage for Insertion, Substitution, and Erasure (PRECISE), a versatile RNA editing method for writing RNA of arbitrary length and sequence into existing pre-mRNAs via 5' or 3' trans-splicing. In trans-splicing, an exogenous template is introduced to compete with the endogenous pre-mRNA, allowing for replacement of upstream or downstream exon sequence. Using Cas7-11 cleavage of pre-mRNAs to bias towards editing outcomes, we boost the efficiency of RNA trans-splicing by 10-100 fold, achieving editing rates between 5-50% and 85% on endogenous and reporter transcripts, respectively, while maintaining high-fidelity. We demonstrate PRECISE editing across 11 distinct endogenous transcripts of widely varying expression levels, showcasing more than 50 types of edits, including all 12 possible transversions and transitions, insertions ranging from 1 to 1,863 nucleotides, and deletions. We show high efficiency replacement of exon 4 of MECP2, addressing most mutations that drive the Rett Syndrome; editing of SHANK3 transcripts, a gene involved in Autism; and replacement of exon 1 of HTT, removing the hallmark repeat expansions of Huntington's disease. Whole transcriptome sequencing reveals the high precision of PRECISE editing and lack of off-target trans-splicing activity. Furthermore, we combine payload engineering and ribozymes for protein-free, high-efficiency trans-splicing, with demonstrated efficiency in editing HTT exon 1 via AAV delivery. We show that the high activity of PRECISE editing enables editing in non-dividing neurons and patient-derived Huntingtons disease fibroblasts. PRECISE editing markedly broadens the scope of genetic editing, is straightforward to deliver over existing gene editing tools like prime editing, lacks permanent off-targets, and can enable any type of genetic edit large or small, including edits not otherwise possible with existing RNA base editors, widening the spectrum of addressable diseases.

molecular biology↗

bioRxiv2023

Programmable RNA-guided endonucleases are widespread in eukaryotes and their viruses

TnpB proteins are RNA-guided nucleases that are broadly associated with IS200/605 family transposons in prokaryotes. TnpB homologs, named Fanzors, have been detected in genomes of some eukaryotes and large viruses, but their activity and functions in eukaryotes remain unknown. We searched genomes of diverse eukaryotes and their viruses for TnpB homologs and identified numerous putative RNA-guided nucleases that are often associated with various transposases, suggesting they are encoded in mobile genetic elements. Reconstruction of the evolution of these nucleases, which we rename Horizontally-transferred Eukaryotic RNA-guided Mobile Element Systems (HERMES), revealed multiple acquisitions of TnpBs by eukaryotes and subsequent diversification. In their adaptation and spread in eukaryotes, HERMES proteins acquired nuclear localization signals, and genes captured introns, indicating extensive, long term adaptation to functioning in eukaryotic cells. Biochemical and cellular evidence show that HERMES employ non-coding RNAs encoded adjacent to the nuclease for RNA-guided cleavage of double-stranded DNA. HERMES nucleases contain a re-arranged catalytic site of the RuvC domain, similar to a distinct subset of TnpBs, and lack collateral cleavage activity. We demonstrate that HERMES can be harnessed for genome editing in human cells, highlighting the potential of these widespread eukaryotic RNA-guided nucleases for biotechnology applications.

molecular biology↗

bioRxiv2022

RNA-triggered protein cleavage and cell death by the RNA-guided type III-E CRISPR-Cas nuclease-protease complex

The type III-E Cas7-11 effector nuclease forms a complex with a CRISPR RNA (crRNA) and the putative caspase-like protease Csx29, catalyzes crRNA-guided target RNA cleavage, and has been used for RNA targeting in eukaryotic cells. Here, we report cryo-electron microscopy structures of the Cas7-11-crRNA-Csx29 complex with and without target RNA, and demonstrate that target RNA binding induces a conformational change in Csx29 and results in the protease activation. Biochemical analysis confirmed that Cas7-11-bound Csx29 cleaves Csx30 in a target RNA-dependent manner. Reconstitution of the system in bacteria uncovered Csx30-dependent cellular toxicity regulated by Csx31, and that Csx29-mediated cleavage produces toxic Csx30 fragments, promoting cell death. We find that Csx30 can bind both Csx31 and the associated sigma factor RpoE, suggesting Csx30 can inhibit RpoE and modulate cellular stress response towards infection. Overall, the RNA-guided nuclease-protease activities of the Cas7-11-Csx29 effector complex facilitate protease-based programmed cell death.

molecular biology↗

bioRxiv2022

Programmable eukaryotic protein expression with RNA sensors

The diversity of cell types and states can be scalably measured and defined by expressed RNA transcripts. However, approaches to programmably sense and respond to the presence of specific RNAs within living biological systems with high sensitivity are lacking. RNA sensors that gate expression of reporter or cargo genes would have diverse applications for basic biology, diagnostics and therapeutics by enabling cell-state specific control of transgene expression. Here, we engineer a novel programmable RNA-sensing technology, Reprogrammable ADAR Sensors (RADARS), which leverages RNA editing by adenosine deaminases acting on RNA (ADAR) to gate translation of a protein payload on the presence of endogenous RNA transcripts. In mammalian cells, we engineer RADARS with diverse payloads, including luciferase and fluorescent proteins, with up to 164-fold activation and quantitative detection in the presence of target RNAs. We show RADARS are functional either expressed from DNA or as synthetic mRNA. Importantly, RADARS can function with endogenous cellular ADAR. We apply RADARS to multiple contexts, including RNA-sensing induced cell death via caspases, cell type identification, and in vivo control of synthetic mRNA translation, demonstrating RADARS as a tool with significant potential for gene and cell therapy, synthetic biology, and biomedical research. One Sentence SummaryA new technology utilizing ADAR mediated RNA-editing enables robust reprogrammable protein expression based on target RNA transcripts in mammalian cells, leading to broad applications in basic science research, cell engineering, and gene therapy.

genomics↗

bioRxiv2021

Drag-and-drop genome insertion without DNA cleavage with CRISPR-directed integrases

Programmable and multiplexed genome integration of large, diverse DNA cargo independent of DNA repair remains an unsolved challenge of genome editing. Current gene integration approaches require double-strand breaks that evoke DNA damage responses and rely on repair pathways that are inactive in terminally differentiated cells. Furthermore, CRISPR-based approaches that bypass double stranded breaks, such as Prime editing, are limited to modification or insertion of short sequences. We present Programmable Addition via Site-specific Targeting Elements, or PASTE, which achieves efficient and versatile gene integration at diverse loci by directing insertion with a CRISPR-Cas9 nickase fused to both a reverse transcriptase and serine integrase. Without generating double stranded breaks, we demonstrate integration of sequences as large as [~]36 kb with rates between 10-50% at multiple genomic loci across three human cell lines, primary T cells, and quiescent non-dividing primary human hepatocytes. To further improve PASTE, we discover thousands of novel serine integrases and cognate attachment sites from metagenomes and engineer active orthologs for high-efficiency integration using PASTE. We apply PASTE to fluorescent tagging of proteins, integration of therapeutically relevant genes, and production and secretion of transgenes. Leveraging the orthogonality of serine integrases, we engineer PASTE for multiplexed gene integration, simultaneously integrating three different genes at three genomic loci. PASTE has editing efficiencies comparable to or better than those of homology directed repair or non-homologous end joining based integration, with activity in non-dividing cells and fewer detectable off-target events. For therapeutic applications, PASTE can be delivered as mRNA with synthetically modified guides to programmably direct insertion of DNA templates carried by AAV or adenoviral vectors. PASTE expands the capabilities of genome editing via drag-and-drop gene integration, offering a platform with wide applicability for research, cell engineering, and gene therapy. One Sentence SummaryA new technology combining CRISPR-mediated genome editing and site-specific integrases enables efficient programmable gene integration at any targeted genomic locus without double-strand DNA breaks, leading to broad applications in basic science research, cell engineering, and gene therapy.

bioengineering↗

bioRxiv2018

Pairwise library screen systematically interrogates Staphylococcus aureus Cas9 specificity in human cells

We report a high-throughput screening approach to measure Staphylococcus aureus Cas9 (SaCas9) genome editing variation in human cells across a large repertoire of 88,692 single guide RNAs (sgRNAs) paired with matched or mismatched target sites in a synthetic cassette. We incorporated randomized barcodes that enable whitelisting of correctly synthesized molecules for further downstream analysis, in order to circumvent the limitation of oligonucleotide synthesis errors. We find SaCas9 sgRNAs with a 21-nucleotide spacer are most active against off-targets with single and double mismatches, compared to shorter or longer sgRNAs. Using this dataset, we developed an SaCas9 specificity model that performs well in ranking off-target sites. The barcoded pairwise library screen enabled high-fidelity recovery of guide-target relationships, providing a scalable framework for the investigation of CRISPR enzyme properties and general nucleic acid interactions.

bioengineering↗

bioRxiv2017

A Survey of Genome Editing Activity for 16 Cpf1 orthologs

The recently discovered class 2 CRISPR-Cas endonuclease Cpf1 offers several advantages over Cas9, including the ability to process its own array and requirement for just a single RNA guide. These attributes make Cpf1 promising for many genome engineering applications. To further expand the suite of Cpf1 tools available, we tested 16 Cpf1 orthologs for activity in eukaryotic cells. Four of these new enzymes demonstrated targeted activity, one of which, from Moraxella bovoculi AAX11_00205 (Mb3Cpf1), exhibited robust indel formation. We also show that Mb3Cpf1 displays some tolerance for a shortened PAM (TTN versus the canonical Cpf1 PAM TTTV). The addition of these enzymes to the genome editing toolbox will further expand the utility of this powerful technology.

molecular biology↗

bioRxiv2016

Cas13b is a Type VI-B CRISPR-associated RNA-Guided RNase differentially regulated by accessory proteins Csx27 and Csx28

CRISPR-Cas adaptive immune systems defend microbes against foreign nucleic acids via RNA-guided endonucleases. Using a computational sequence database mining approach, we identify two Class 2 CRISPR-Cas systems (subtype VI-B) that lack Cas1 and Cas2 and encompass a single large effector protein, Cas13b, along with one of two previously uncharacterized associated proteins, Csx27 or Csx28. We establish that these CRISPR-Cas systems can achieve RNA interference when heterologously expressed. Through a combination of biochemical and genetic experiments, we show that Cas13b processes its own CRISPR array with short and long direct repeats, cleaves target RNA, and exhibits collateral RNase activity. Using an E. coli essential gene screen, we demonstrate that Cas13b has a double-sided protospacer-flanking sequence and elucidate RNA secondary structure requirements for targeting. We also find that Csx27 represses, whereas Csx28 enhances, Cas13b-mediated RNA interference. Characterization of these CRISPR systems creates opportunities to develop tools to manipulate and monitor cellular transcripts.

microbiology↗