Biology subjects

Konermann, S.

Publications and source records attributed to Konermann, S..

16 recordsLinked to original sources

bioRxiv2026

Systematic mapping of the prokaryotic noncoding sequence space with a genomic language model

Prokaryotic genomes encode a vast repertoire of noncoding elements such as ribozymes, riboswitches, and CRISPR RNAs. The sequence-level diversity of these intergenic elements precludes alignment-based clustering that would enable annotation and discovery of novel noncoding RNA families. Here, we show that a genomic language model fine-tuned on prokaryotic intergenic sequences learns representations of noncoding elements from DNA sequence. We used these embeddings to organize 376 million intergenic regions from 1.3 terabase pairs of prokaryotic genomes and metagenomes into 5.14 million clusters. This approach nominated 20,149 clusters of putative structured RNAs with a candidate protein partner. Periodicity in token entropies revealed internal architecture, recovering CRISPR, TIGR and VIPR arrays together with their cognate effector proteins from sequence alone. Targeted clustering of bridge recombinase-adjacent sequences identified bridge RNA variants with longer guide recognition sequences than any characterized ortholog. Finally, we directed teams of AI agents to mine the database under researcher-defined criteria, uncovering divergent riboswitches, ribozymes, and other structured RNAs with biological hypotheses for their function. We release a publicly available database that transforms the dark matter of prokaryotic genomes into an explorable resource for human-agent molecular discovery.

genomics↗

bioRxiv2026

Extracellular cGAMP transmission exacerbates neuroinflammation in aging and multiple sclerosis

Neuroinflammation drives neurodegeneration and cognitive decline in aging, but the signals that spread this inflammation across the CNS remain unclear. Here, we show in mice that advanced age and experimental autoimmune encephalomyelitis (EAE) both result in elevated cytosolic mtDNA in microglia, which stimulates the production and export of cGAMP from these cells. Meanwhile, ENPP1, the dominant cGAMP hydrolase in the brain and spinal cord, is downregulated in both EAE mice and MS patients, releasing the brake on extracellular cGAMP accumulation. In Enpp1H362A mice, which selectively lack cGAMP hydrolysis activity, unrestrained extracellular cGAMP worsens EAE-associated paralysis and drives premature aging phenotypes including impaired motor coordination (rotarod, pole test) and reduced exploration (open field test) in a manner dependent on STING. Single-cell RNA sequencing pinpoints microglia, astrocytes, and inhibitory neurons as the principal cGAMP responders that activate STING-dependent interferon-stimulated gene induction in response to elevated extracellular cGAMP. Mechanistically, microglia import cGAMP through the LRRC8A:C channel, while astrocytes and neurons import cGAMP via the glutamate antiporter system xc-, reinforced by SLC1A2-mediated glutamate uptake in astrocytes and SLC38A1/2-fueled glutamine-to-glutamate synthesis in neurons. In isolated primary astrocytes and neurons, high intracellular glutamate and system xc--driven redox demands favor cGAMP uptake, raising the possibility that neurotransmitter cycling and redox burden shape cellular vulnerability to cGAMP immunotransmission in vivo. Together, these findings position ENPP1 as a protective brake on neuroinflammation in aging and MS, nominating cGAS inhibition and CNS ENPP1 enhancement as therapeutic strategies.

cell biology↗

bioRxiv2026

Scalable probe-based single-cell transcriptional profiling for virtual cell perturbation mapping and synthetic biology phenotyping

Large-scale single-cell transcriptional phenotyping of genetic perturbations (perturb-seq) links genes to phenotypes and should enable virtual cell predictive modeling and cellular engineering. However, current perturb-seq single-cell methods are costly, information sparse and require barcodes for many applications. We developed ProPer-seq, a perturb-seq method that uses multiplexed custom DNA probe panels to measure and phenotype synthetic biology perturbations at single-cell resolution without barcodes, including multidomain proteins and sgRNAs. ProPer-seq faithfully reproduces gold-standard perturb-seq phenotypes while achieving 4-fold cost reduction and 50% increased gene detection per cell. As a scalable fixed-cell profiling method, ProPer-seq enables atlas-scale profiling for virtual-cell initiatives and demonstrates data quality suitable for training and validating predictive models. Lastly, ProPer-seqs targeted detection of modular transgenes enables library-on-library perturbation profiling of combinatorial synthetic protein design spaces. We applied this to 3,550 sgRNA x dCas9 effector combinations as well as 260 CAR x ORF combinations dynamically profiled in primary T cells, revealing principles of transcriptional control and cell state modulation by multidomain synthetic transgenes.

synthetic biology↗

bioRxiv2025

Predicting cellular responses to perturbation across diverse contexts with STATE

Cellular responses to perturbations are a cornerstone for understanding biological mechanisms and selecting drug targets. While machine learning models offer tremendous potential for predicting perturbation effects, they currently struggle to generalize to unobserved cellular contexts. Here, we introduce SO_SCPLOWTATEC_SCPLOW, a transformer model that predicts perturbation effects while accounting for cellular heterogeneity within and across experiments. SO_SCPLOWTATEC_SCPLOW predicts perturbation effects across sets of cells and is trained using gene expression data from over 100 million perturbed cells. SO_SCPLOWTATEC_SCPLOW improved discrimination of effects on large datasets by more than 30% and identified differentially expressed genes across genetic, signaling and chemical perturbations with significantly improved accuracy. Using its cell embedding trained on observational data from 167 million cells, SO_SCPLOWTATEC_SCPLOW identified strong perturbations in novel cellular contexts where no perturbations were observed during training. We further introduce Cell-Eval, a comprehensive evaluation framework that highlights SO_SCPLOWTATEC_SCPLOWs ability to detect cell type-specific perturbation responses, such as cell survival. Overall, the performance and flexibility of SO_SCPLOWTATEC_SCPLOW sets the stage for scaling the development of virtual cell models.

systems biology↗

bioRxiv2025

Megabase-scale human genome rearrangement with programmable bridge recombinases

Bridge recombinases are a class of naturally occurring RNA-guided DNA recombinases. We previously demonstrated they can programmably insert, excise, and invert DNA in vitro and in bacteria. Here, we report the discovery and engineering of IS622, a simple two-component system capable of universal DNA rearrangements of the human genome. We define strategies for the optimal application of bridge systems, leveraging mechanistic insights to improve their targeting specificity. Through rational engineering of the IS622 bridge RNA and deep mutational scanning of its recombinase, we achieve up to 20% insertion efficiency into the human genome and genome-wide specificity as high as 82%. We further demonstrate intra-chromosomal inversion and excision, mobilizing up to 0.93 megabases of DNA. Finally, we provide proof-of-concept for excision of a gene regulatory region or expanded repeats relevant for the treatment of genetic diseases.

bioengineering↗

bioRxiv2025

scBaseCamp: An AI agent-curated, uniformly processed, and continually expanding single cell data repository

Single-cell RNA sequencing has transformed cell biology by enabling precise transcriptomic measurements of individual cells. The Sequence Read Archive (SRA) is the largest public repository of sequencing reads, yet much of it remains underutilized due to unstandardized metadata and the cost of processing reads. Here, we introduce scBaseCount, a single-cell RNA sequencing database that leverages an AI agent to automate discovery and metadata extraction, and standardize data processing. Built by directly mining all 10x Genomics datasets from SRA, scBaseCount is the largest freely accessible public repository of single-cell gene expression data, comprising over 502 million cells across 27 organisms and 75 tissues, offering an unbiased view of the composition of data within SRA. Uniform processing enables measurement of both intronic and exonic reads, non-coding gene expression and improves alignment across experiments as well as the performance of AI models trained on this phenotypically diverse data. Moreover, scBaseCount provides a blueprint for how AI can be leveraged to curate and autonomously update large biological data repositories.

bioinformatics↗

bioRxiv2024

Site-specific DNA insertion into the human genome with engineered recombinases

Technologies for precisely inserting large DNA sequences into the genome are critical for diverse research and therapeutic applications. Large serine recombinases (LSRs) can mediate direct, site-specific genomic integration of multi-kilobase DNA sequences without a pre-installed landing pad, but current approaches suffer from low insertion rates and high off-target activity. Here, we present a comprehensive engineering roadmap for the joint optimization of DNA recombination efficiency and specificity. We combined directed evolution, structural analysis, and computational models to rapidly identify additive mutational combinations. We further enhanced performance through donor DNA optimization and dCas9 fusions, enabling simultaneous target and donor recruitment. Top engineered LSR variants achieved up to 53% integration efficiency and 97% genome-wide specificity at an endogenous human locus, and effectively integrated large DNA cargoes (up to 12 kb tested) for stable expression in challenging cell types, including non-dividing cells, human embryonic stem cells, and primary human T cells. This blueprint for rational engineering of DNA recombinases enables precise genome engineering without the generation of double-stranded breaks.

bioengineering↗

bioRxiv2024

A combinatorial domain screening platform reveals epigenetic effector interactions for transcriptional perturbation

Epigenetic regulation involves the coordinated interplay of diverse proteins. To systematically explore these combinations, we present COMBINE (combinatorial interaction exploration), a high-throughput platform that tests over 50,000 pairs of epigenetic effector domains up to 2,094 amino acids in length for their ability to modulate endogenous human gene transcription. COMBINE revealed diverse synergistic and antagonistic interactions between epigenetic protein domains, including a potent KRAB-L3MBTL3 fusion that enhanced gene silencing up to 34-fold in dose-limited conditions and enabled robust bidirectional CRISPR perturbation. Inducible screening showed DNA methylation modifiers are essential for epigenetic memory, with distinct combinations driving long-term silencing, repression, or activation. Notably, we identified TET1-based combinations that induce hit-and-run upregulation for over 50 days, demonstrating long-term transcriptional activation. This systematic analysis of pairwise domain interactions provides a rich resource for understanding epigenetic crosstalk and developing next-generation epigenome editing tools. More broadly, COMBINE offers a generalizable platform to functionally characterize combinatorial biological processes at scale.

bioengineering↗

bioRxiv2024

Rewriting endogenous human transcripts with trans-splicing

Splicing bridges the gap between static DNA sequence and the diverse and dynamic set of protein products that execute a genes biological functions. While exon skipping technologies enable influence over splice site selection, many desired perturbations to the transcriptome require replacement or addition of exogenous exons to target mRNAs: for example, to replace disease-causing exons, repair truncated proteins, or engineer protein fusions. Here, we report the development of RNA-guided trans-splicing with Cas editor (RESPLICE), inspired by the rare, natural process of trans-splicing that joins exons from two distinct primary transcripts. RESPLICE uses two orthogonal RNA-targeting CRISPR effectors to co-localize a trans-splicing pre-mRNA and to inhibit the cis-splicing reaction, respectively. We demonstrate efficient, specific, and programmable trans-splicing of multi-kilobase RNA cargo into nine endogenous transcripts across two human cell types, achieving up to 45% trans-splicing efficiency in bulk, or 90% when sorting for high effector expression. Our results present RESPLICE as a new mode of RNA editing for fine-tuned and transient control of cellular programs without permanent alterations to the genetic code.

molecular biology↗

bioRxiv2024

Bridge RNAs direct modular and programmable recombination of target and donor DNA

Genomic rearrangements, encompassing mutational changes in the genome such as insertions, deletions, or inversions, are essential for genetic diversity. These rearrangements are typically orchestrated by enzymes involved in fundamental DNA repair processes such as homologous recombination or in the transposition of foreign genetic material by viruses and mobile genetic elements (MGEs). We report that IS110 insertion sequences, a family of minimal and autonomous MGEs, express a structured non-coding RNA that binds specifically to their encoded recombinase. This bridge RNA contains two internal loops encoding nucleotide stretches that base-pair with the target DNA and donor DNA, which is the IS110 element itself. We demonstrate that the target-binding and donor-binding loops can be independently reprogrammed to direct sequence-specific recombination between two DNA molecules. This modularity enables DNA insertion into genomic target sites as well as programmable DNA excision and inversion. The IS110 bridge system expands the diversity of nucleic acid-guided systems beyond CRISPR and RNA interference, offering a unified mechanism for the three fundamental DNA rearrangements required for genome design.

genetics↗

bioRxiv2022

Kinase-independent activity of DYRK1A promotes viral entry of highly pathogenic human coronaviruses

Identifying host genes essential for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has the potential to reveal novel drug targets and further our understanding of coronavirus disease 2019 (COVID-19). We previously performed a genome-wide CRISPR/Cas9 screen to identify pro-viral host factors for highly pathogenic human coronaviruses. Very few host factors were required by diverse coronaviruses across multiple cell types, but DYRK1A was one such exception. Although its role in coronavirus infection was completely unknown, DYRK1A encodes Dual Specificity Tyrosine Phosphorylation Regulated Kinase 1A and regulates cell proliferation, and neuronal development, among other cellular processes. Interestingly, individuals with Down syndrome overexpress DYRK1A 1.5-fold and exhibit 5-10x higher hospitalization and mortality rates from COVID-19 infection. Here, we demonstrate that DYRK1A regulates ACE2 and DPP4 transcription independent of its catalytic kinase function to support SARS-CoV, SARS-CoV-2, and MERS-CoV entry. We show that DYRK1A promotes DNA accessibility at the ACE2 promoter and a putative distal enhancer, facilitating transcription and gene expression. Finally, we validate that the pro-viral activity of DYRK1A is conserved across species using cells of monkey and human origin and an in vivo mouse model. In summary, we report that DYRK1A is a novel regulator of ACE2 and DPP4 expression that may dictate susceptibility to multiple highly pathogenic human coronaviruses. Whether DYRK1A overexpression contributes to heightened COVID-19 severity in individuals with Down syndrome through ACE2 regulation warrants further future investigation.

microbiology↗

bioRxiv2021

Deep learning of Cas13 guide activity from high-throughput gene essentiality screening

Transcriptome engineering technologies that can effectively and precisely perturb mammalian RNAs are needed to accelerate biological discovery and RNA therapeutics. However, the broad utility of programmable CRISPR-Cas13 ribonucleases has been hampered by an incomplete understanding of the design rules governing guide RNA activity as well as cellular toxicity resulting from off-target or collateral RNA cleavage. Here, we sought to characterize and develop Cas13d systems for efficient and specific RNA knockdown with low cellular toxicity in human cells. We first quantified the performance of over 127,000 RfxCas13d (CasRx) guide RNAs in the largest-scale screen to date and systematically evaluated three linear, two ensemble, and two deep learning models to build a guide efficiency prediction algorithm validated across multiple human cell types in orthogonal validation experiments (https://www.RNAtargeting.org). Deep learning model interpretation revealed specific sequence motifs at spacer position 15-24 along with favored secondary features for highly efficient guides. We next identified 46 novel Cas13d orthologs through metagenomic mining for activity and cytotoxicity screening, discovering that the metagenome-derived DjCas13d ortholog achieves low cellular toxicity and high transcriptome-wide specificity when deployed against high abundance transcripts or in sensitive cell types, including human embryonic stem cells, neural progenitor cells, and neurons. Finally, our Cas13d guide efficiency model successfully generalized to DjCas13d, highlighting the utility of a comprehensive approach combining machine learning with ortholog discovery to advance RNA targeting in human cells.

bioengineering↗

bioRxiv2021

Genome-wide, bidirectional CRISPR screens identify mucins as critical host factors modulating SARS-CoV-2 infection

SARS-CoV-2 can cause a range of symptoms in infected individuals, from mild respiratory illness to acute respiratory distress syndrome. A systematic understanding of the host factors mediating viral infection or restriction is critical to elucidate SARS-CoV-2 host-pathogen interactions and the progression of COVID-19. To this end, we conducted genome-wide CRISPR knockout and activation screens in human lung epithelial cells with endogenous expression of the SARS-CoV-2 entry factors ACE2 and TMPRSS2. These screens uncovered proviral and antiviral host factors across highly interconnected host pathways, including components implicated in clathrin transport, inflammatory signaling, cell cycle regulation, and transcriptional and epigenetic regulation. We further identified mucins, a family of high-molecular weight glycoproteins, as a prominent viral restriction network. We demonstrate that multiple membrane-anchored mucins are critical inhibitors of SARS-CoV-2 entry and are upregulated in response to viral infection. This functional landscape of SARS-CoV-2 host factors provides a physiologically relevant starting point for new host-directed therapeutics and suggests interactions between SARS-CoV-2 and airway mucins of COVID-19 patients as a host defense mechanism.

genetics↗

bioRxiv2019

CloneRetriever: retrieval of rare clones from heterogeneous cell populations

BackgroundMany biological processes, such as cancer metastasis, organismal development, and development of resistance to cytotoxic therapy, rely on the emergence of rare sub-clones from a larger population. Understanding how the genetic and epigenetic features of diverse clones affect clonal fitness provides insight into molecular mechanisms underlying selective processes. However, identifying causal drivers of clonal fitness remains challenging. Population-level analysis has limited resolution to characterize clones prior to selection, while high-resolution single-cell methods are destructive and challenging to scale across large populations, limiting further functional analysis of relevant clones.\n\nResultsHere, we develop CloneRetriever, a methodology for tracking and retrieving rare clones throughout their response to selection. CloneRetriever utilizes a CRISPR sgRNA-barcode library that allows isolation of viable cells from specific clones within the barcoded population using a sequence-specific retrieval reporter. We demonstrated that CloneRetriever can measure clonal fitness of cancer cell models in vitro and retrieve targeted clones at abundance as low as 1 in 1,883 in a heterogeneous cell population.\n\nConclusionsCloneRetriever provides a means to track and access specific and rare clones of interest across dynamic changes in population structure to comprehensively explore the basis of these changes.

genomics↗

bioRxiv2019

Interaction between DNA damage response, translation and apoptosome determines cancer susceptibility to TOP2 poisons

Topoisomerase II poisons are one of the most common class of chemotherapeutics used in cancer. We show that glioblastoma (GBM), the most malignant of all primary brain tumors in adults is responsive to TOP2 poisons. To identify genes that confer susceptibility to this drug in gliomas, we performed a genome-scale CRISPR knockout screen with etoposide. Genes involved in protein synthesis and DNA damage were implicated in etoposide susceptibility. To define potential biomarkers for TOP2 poisons, CRISPR hits were overlapped with genes whose expression correlates with susceptibility to this drug across glioma cell lines, revealing ribosomal protein subunit RPS11, 16, 18 as putative biomarkers for response to TOP2 poisons. Loss of RPS11 impaired the induction of pro-apoptotic gene APAF1 following etoposide treatment, and led to resistance to this drug and doxorubicin. The expression of these ribosomal subunits was also associated with susceptibility to TOP2 poisons across cell lines from multiple cancers.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC=\"FIGDIR/small/614024v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (14K):\norg.highwire.dtl.DTLVardef@310f7org.highwire.dtl.DTLVardef@14ed578org.highwire.dtl.DTLVardef@a0d9c0org.highwire.dtl.DTLVardef@37f59a_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2018

Structural basis for the RNA-guided ribonuclease activity of CRISPR-Cas13d

CRISPR-Cas endonucleases directed against foreign nucleic acids mediate prokaryotic adaptive immunity and have been tailored for broad genetic engineering applications. Type VI-D CRISPR systems contain the smallest known family of single effector Cas enzymes, and their signature Cas13d ribonuclease employs guide RNAs to cleave matching target RNAs. To understand the molecular basis for Cas13d function, we resolved cryo-electron microscopy structures of Cas13d-guide RNA binary complex and Cas13d-guide-target RNA ternary complex to 3.4 and 3.3 [A] resolution, respectively. Furthermore, a 6.5 [A] reconstruction of apo Cas13d combined with hydrogen-deuterium exchange revealed conformational dynamics that have implications for RNA scanning. These structures, together with biochemical and cellular characterization, explain the compact molecular architecture of Cas13d and provide insights into the structural transitions required for enzyme activation. Our comprehensive analysis of Cas13d in diverse enzymatic states facilitated site-specific truncations for minimal size and delineates a blueprint for improving biomolecular applications of RNA targeting.

biochemistry↗