Genomic alterations driving tumorigenesis in sinonasal malignancies remain largely unexplored. Here, we perform an in vivo loss-of-function screen using a pooled custom single-guide library delivered to the sinonasal cavity by adeno-associated virus vector to identify cancer driver genes across diverse sinonasal malignancies. This approach yielded sinonasal malignancies with diverse histologies, including sinonasal squamous cell carcinoma, adenocarcinoma, poorly differentiated sinonasal carcinoma, and sinonasal neuroendocrine tumors characteristic of olfactory neuroblastoma. Surprisingly, rather than observing distinct sgRNA profiles across sinonasal tumor subtypes, common recurrent mutations were identified in Nf1 (79%), Rasa1 (74%), and Trp53 (68%) across malignancies with distinct histologies. Utilizing an orthogonal approach, we confirmed that Nf1/Trp53 were required for sinonasal tumorigenesis. Given that loss-of-function in NF1 and RASA1 may lead to increased Ras activity and downstream MEK signaling, we tested small molecule targeting of the RAS-MAPK pathway in sinonasal malignancies. Indeed, both tumor cell lines derived from our loss-of-function approach as well as from human sinonasal malignancies displayed significant sensitivity to MEK inhibition in standard in vitro culture and organoid models. These findings demonstrate that loss of NF1 and RASA1-mediated Ras-GAP activity leads to Ras activation and downstream MEK signaling which is a potential common target throughout major sinonasal tumor subtypes.

The fatty acid elongase1 ( FAE1 ) genes of tetraploid Brassica juncea are the key determinant of high erucic acid (EA, C22:1) accumulation in its seed oil. While our previous work demonstrated near-zero EA content in mustard oil via CRISPR/Cas9 knockout of the two homeoalleles, BjFAE1.1 and BjFAE1.2 ; the contributory function of each isozymes towards EA biosynthesis remains elusive. This study investigated the heterologous expression of BjFAE1.1 and BjFAE1.2 from high EA B. juncea cultivar JD6 in two metabolically distinct eukaryotic microbial hosts: the green microalga Chlamydomonas reinhardtii and the budding yeast Saccharomyces cerevisiae . Despite confirmed protein expression, neither BjFAE1 isozyme produced detectable C20:1 or C22:1 very-long-chain fatty acids (VLCFAs) in transgenic lines of C. reinhardtii . In contrast, expression in S. cerevisiae resulted in significant de novo biosynthesis of VLCFAs, C20:1 (∼9-11%) and C22:1 (∼17-19%), confirming their enzymatic activity as functional β-ketoacyl-CoA synthase. Substrate feeding experiments in yeast further validated their capability to elongate oleoyl-CoA (C18:1-CoA) to erucoyl-CoA (C22:1-CoA) via eicosenoyl-CoA (C20:1-CoA), with BjFAE1.1 showing slightly higher activity, as indicated by the enhanced VLCFAs accumulation. These findings highlight the critical influence of the heterologous host’s cellular environment on the enzyme functionality of plant genes involved in lipid metabolism, underscoring challenges for VLCFA production in microalgal platform.

Papaya ( Carica papaya L.) is an economically important tropical crop that produces papain and highly nutritious fruit, which are used in the grocery, cosmetic, pharmaceutical, and food processing industries. However, various destructive pathogens severely threaten its production. Furthermore, limited natural genetic variation restricts breeding efforts for crop improvement. Therefore, we turned to gene editing as a tool to address these problems. We utilized two CRISPR systems (Cas9 and Cas12a) and two papaya genes, CpPDS (phytoene desaturase) and CpMLO6 (Mildew Locus O 6), to establish efficient genome editing systems of papaya. The systems were delivered by an optimized protocol of Agrobacterium -mediated transformation (AMT) of embryogenic callus suspension cultures derived from hypocotyls. Accordingly, we transformed papaya with five plasmid constructs, each of which expressed one or two guide RNAs (gRNAs) for gene editing using either Cas9 or Cas12a. All except two T0 transgenic plants tested produced mutations with the majority containing indels of over 90%. Furthermore, successful mutation of the CpPDS gene using both Cas9 and Cas12a produced albino phenotypes as expected for disrupting a gene for carotenoid biosynthesis. Successful mutagenesis was achieved with seven out of eight gRNAs. Homozygous and/or biallelic mutants were generated from transformation using all five constructs, suggesting the feasibility of obtaining transgene-free homozygous segregating mutants by selfing in the second generation. Taken together, a robust and reliable papaya genome editing system was established, which enables genetic modification in various genomic environments to meet the diverse needs of basic scientific research and tropical crop improvement.

Plants constantly monitor their environment to adapt to potential threats to their health and fitness. This involves cell-surface receptors that can detect conserved microbe-associated molecular patterns (MAMPs) or endogenous immunogenic signals, initiating signaling pathways to induce broad-spectrum disease resistance, known as pattern-triggered immunity (PTI). In Arabidopsis thaliana , the leucine-rich repeat receptor kinase (LRR-RK) MIK2 is an exceptionally versatile receptor involved in the perception of the vast family of Brassicales-specific endogenous SCOOP peptides as well as potential MAMPs derived from Fusarium and related fungi. Although only plant species belonging to the order of Brassicales encode genes for SCOOP peptides and show SCOOP-responsiveness, the Fusarium -derived elicitor fraction also induces PTI responses in plants from other lineages. In this study, we demonstrate that Fusarium elicitor-responsiveness and proteins belonging to the MIK2-clade are widely conserved among seed plants. We identified a MIK2-clade protein from tomato, which shares properties of At MIK2 in the perception of the Fusarium elicitor but not of SCOOP peptides. Tomato mutants lacking the receptor show compromised PTI responses to the fungal elicitor and enhanced susceptibility to infection by Fusarium oxysporum . Our data provide insights into the evolutionary trajectory of MIK2 as a multifunctional receptor involved in plant immunity.

Abstract Recent single-cell CRISPR screening experiments have combined the advances of genetic editing and single-cell technologies, leading to transcriptome-scale readouts of responses to perturbations at single-cell resolution. An outstanding question is how to efficiently identify heterogeneous effects of perturbations using these technologies. Here we present CausalPerturb, which leverages AI tools and causal analysis to dissect the heterogeneous landscape of perturbation effects. CausalPerturb disentangles transcriptome changes introduced by perturbations from those reflecting inherent cell-state variations. It provides nonparametric inferences of perturbation effects, enabling a range of downstream tasks including genetic interaction analysis, perturbation clustering and prioritization. We evaluated CausalPerturb through simulation studies and real datasets, and demonstrated its competence in characterizing latent confounding factors and discerning heterogeneous perturbation effects. The application of CausalPerturb unraveled novel genetic interactions between erythroid differentiation drivers. In particular, it pinpointed the role of the synergistic interaction between CBL and CNN1 in the S phase.

Abstract Insights from urochordates/tunicates can instruct on the evolutionary origins of key cell types or gene regulatory mechanisms such as for the ‘new head’ sensory placodes and neural crest. Taking advantage of their invariant lineage with reproducible binary cell fate switches, we decipher in Ciona intestinalis the unanswered question of how highly conserved and ongoing FGF/MAPK/ERK signalling gives rise to co-existing nuclear Ets activation and repression states to finely tune the neural fate and its diversification. Genetic interference shows that Erf and Elk repressors play successive roles at different transcriptional targets. We propose an Ets site occupancy model where activators and repressors compete to produce consecutive and opposite winning switches in adjacent territories. Such Ets factor network is relevant beyond the ascidian neuroectodermal lineage to produce palp placodal and neural plate progenitors. It may explain Ets factor effects in many metazoans including Elk in vertebrate neural crest and appeal to stem cell and cancer research.

Abstract Background. Metastatic breast cancer (MBC) remains a major clinical challenge, particularly in estrogen receptor α (ERα)-positive patients who develop resistance to endocrine therapy (ET). While hotspot mutations such as Y537S in the ligand-binding domain (LBD) are well-characterized drivers of resistance, other ERα variants remain poorly studied. Understanding the molecular mechanisms underlying resistance in these variants is crucial for identifying novel therapeutic strategies. Here, we investigated the functional role of the L370F and E471D ERα variants, which are spatially close in the ERα structure. Methods. Stable overexpressing HEK293 cells and CRISPR/CAS9 engineered MCF-7 cells were generated and treated with 17β-estradiol (E2), fulvestrant (Ful) and all-trans retinoic acid (ATRA) to measure ERα stability, transcriptional activity and gene expression analyses using different cellular assays and RNASeq techniques. Direct in vitro measurement of ligand binding affinity to ERα were performed using the purified full-length wild type (wt) as well as L370F and Y537S ERα. In silico structural simulations were also performed to predict the structure of the mutated L370F ERα. Senescent analyses of MCF-7 and Y537S MCF-7 cells were performed using direct measurement β-galactosidase activity in vitro and in cell lines. Results The L370F variant conferred resistance to Ful in terms of in vitro ERα binding, ERα transcriptional activity, receptor degradation and cell proliferation by modifying the folding of the receptor structure. Furthermore, L370F-expressing cells exhibited a hyperactive response to low doses of E2 and basally upregulated late estrogen responsive genes. Additionally, we found that both L370F and Y537S ERα variants displayed increased RARα expression, rendering them highly sensitive to ATRA. Notably, ATRA killed L370F-expressing cells and induced senescence in Y537S-expressing cells, highlighting mutation-specific responses. Conclusions Our findings expand the understanding of ERα mutations beyond known hotspots, identifying L370F as a novel mutation contributing to ET resistance and further indicate the necessity to characterize all the less-studied ERα variants found in MBC. Furthermore, we demonstrate that ATRA selectively targets MBC cells harboring L370F and Y537S mutations, suggesting its potential as a mutation-specific therapeutic agent. These results support further investigation of ATRA in clinical settings to improve treatment strategies for ERα-mutant MBC.

ABSTRACT TP53 mutations confer treatment resistance across multiple cancers. Mechanisms of therapy resistance, beyond affecting transactivation of BCL-2 family genes, remain a mystery. Here, we report that TP53 mutated AML, triple negative breast cancer, and colorectal cancer escape therapy-induced apoptosis due to inability to activate caspase-3/7, despite having normal mitochondrial outer membrane permeabilization (MOMP) induction. To identify post-MOMP determinants of therapy resistance in TP53 mutated AML, we applied a multiomics approach – whole-genome CRISPR screen, bulk/single-cell RNAseq, and high-throughput drug screen. BIRC5 , encoding survivin, was selectively upregulated in paired hematopoietic stem/multipotent progenitor cells from TP53 mutant AML patients, with further enrichment after venetoclax-azacitidine (VenAza) relapse. Critically, BIRC5 was also upregulated in 17 of 26 TP53 mutant TCGA cancers. Genetic ablation of BIRC5 resensitized TP53 mutated AML to standard therapy by restoring caspase activation, validating therapeutic relevance. Importantly, targeting IAPs and survivin using clinically relevant inhibitors overcame VenAza resistance of TP53 mutant tumors in vivo , achieving sustained AML suppression. Combination with survivin inhibitors also overcame chemotherapy resistance in TP53 deficient solid cancers. Together, we discovered that wild-type TP53 is required in post-MOMP signaling and that BIRC5 dependency is an effective therapeutic target for poor prognosis, TP53 mutated cancers.

Immune matching and rejection pose major hurdles in tissue transplantation. Here, we profile HLA-A , HLA-B , and HLA-C alleles in 3,496 Lithuanian donors genotyped at three-field resolution. The five most frequent alleles constitute 74.6% of HLA-A , 43.2% of HLA-B , and 59.2% of HLA-C , with HLA-A*02:01:01, HLA-B*07:02:01, and HLA-C*07:02:01 being the most common. Lithuanian allele frequencies closely resemble those of populations with pre-Neolithic hunter-gatherer ancestry, such as European-American and British groups. We identified 153 double homozygotes and 51 triple homozygotes for HLA-A , HLA-B , and HLA-C . Compatibility modeling showed triple homozygous profiles match 60.5% of Lithuanians (33.3% for double homozygotes), 13.4% of British population, and 7.4% of European-Americans. CRISPR-Cas9 guide RNA design yielded 54 candidates predicted to disrupt HLA-A or HLA-B , while preserving HLA-C , producing edited profiles matching over 98.1% of Lithuanians, 95.8% of European-Americans, and 95.6% of British population. Finally, we established 16 fibroblast lines from double and triple homozygotes, offering a resource for immune-compatibility studies and regenerative medicine applications.

RNA splicing is fundamental to cellular function, yet systematic investigation of its complex regulation has been limited by existing methods. Here, we present SPLiCR-seq ( SPL icing regulator identification through CR ISPR screening), a high-throughput CRISPR screening platform that enables direct measurement of RNA splicing outcomes for pooled genetic perturbations, overcoming limitations of traditional fluorescence-based approaches. Applying SPLiCR-seq to investigate XBP1 splicing during the unfolded protein response (UPR), we conducted targeted and genome-wide screens across diverse cellular contexts, revealing both common and cell-type specific regulators. Notably, we identified GADD34 ( PPP1R15A ) as a novel modulator of IRE1-XBP1 signaling, demonstrating that it directly interacts with IRE1 and functions independently of its canonical role in eIF2α dephosphorylation. Pharmacological inhibition of GADD34 using Sephin1 effectively suppressed XBP1 splicing and alleviated CAR-T cell exhaustion in an ex vivo model, leading to enhanced tumor-killing capacity across multiple cancer models. This work not only establishes a powerful new tool for systematically studying RNA splicing regulation but also uncovers a promising therapeutic strategy for improving CAR-T cell immunotherapy through modulation of the IRE1-XBP1 pathway.

Objective Genome-wide association studies (GWAS) have identified numerous single nucleotide polymorphisms (SNPs) associated with juvenile idiopathic arthritis (JIA), the majority of which are located in non-coding regions such as enhancers. This presents a challenge for pinpointing causal variants and their target genes. Interpreting these loci requires functional genomics data from disease-relevant tissues, which has been lacking for JIA. This study seeks to fill that gap and elucidate the biological mechanisms underlying JIA susceptibility. Methods We performed low-input whole genome promoter Capture Hi-C (PCHi-C) and ATAC-seq on CD4+ T cells from three JIA oligoarthritis patients. To link JIA-associated SNPs to potential causal genes, we integrated PCHi-C data with JIA GWAS summary statistics using our Bayesian prioritisation algorithm, Capture Hi-C Omnibus Gene Score (COGS). ATAC-seq was used to further annotate JIA GWAS loci in CD4+ T cells. We then employed CRISPR activation and interference (CRISPRa/i) in Jurkat cells to validate the prioritised SNPs and their corresponding genes. Results Chromatin interactions between JIA-associated SNPs and gene promoters were identified in 19 of 44 non-MHC JIA loci, linking 61 known and novel target genes to the disease. Through COGS, we prioritised seven putative causal genes for JIA: RGS14, ERAP2, HIPK1, CCR4, CCRL2, CCR2 , and CCR3 . SNPs within promoter-interacting regions (PIRs) of these genes were further validated using CRISPRa/i to confirm their roles in regulating gene expression. Conclusions This study provides insights into the genetic architecture of JIA by integrating genomic and epigenomic data, identifying disease-related genes, functionally validating risk SNPs, and highlighting candidate drugs for repurposing. Key messages What is already known on this topic Recent genome-wide association studies in JIA have identified genetic loci associated with disease risk. However, the precise mechanisms by which these variants contribute to disease pathology remain unclear, as most do not directly alter protein-coding genes. It has been proposed that non-coding SNPs can affect genes that are important in disease through disruption of enhancer-mediated regulatory mechanisms that control their expression, with enhancers exerting their effects through chromatin interactions. Functional characterisation of risk loci is essential to delineate causal SNPs and target genes in JIA. What this study adds This study is the first to utilise low-input Promoter Capture Hi-C to map long-range chromatin interactions in CD4+ T cells from JIA patients, alongside ATAC-seq to assess chromatin accessibility within the same samples. It identifies 61 potential target genes at JIA-associated loci and validates the regulatory roles of some of these through CRISPR activation and interference. This work enhances our understanding of how genetic variants modulate gene expression in immune cells, shedding light on key pathways involved in JIA pathogenesis. How this study might affect research, practice or policy Highlights new potential causal genes in JIA which can help understand the pathological mechanisms in JIA, and suggests the potential to repurpose CCR2/CCR5 inhibitors in JIA.

Metastasis remains the leading cause of cancer-related mortality, yet predicting future metastasis is a major clinical challenge due to the lack of validated biomarkers and effective assessment methods. Here, we present EmitGCL, a deep-learning framework that accurately predicts future metastasis and its corresponding biomarkers. Based on a comprehensive benchmarking comparison, EmitGCL outperformed other computational tools across six cancer types from seven cohorts of patients with superior sensitivity and specificity. It captured occult metastatic cells in a patient with a lymph node-negative breast cancer, who was declared to have no evidence of disease by conventional imaging methods but was later confirmed to have a metastatic disease. Notably, EmitGCL identified HSP90AA1 and HSP90AB1 as predictable biomarkers for future breast cancer metastasis, which was validated across five independent cohorts of patients (n=420). Furthermore, we demonstrated YY1 transcription factor as a key driver of breast cancer metastasis which was validated through in-silico and CRISPR-based migration assays, suggesting that YY1 is a potential therapeutic target for deterring metastasis.

Synthetic autotrophs are a promising platform for sustainable bioproduction using CO 2 as substrate. The methylotrophic yeast Komagataella phaffii has been engineered to use CO 2 as the sole carbon source by integration of the Calvin–Benson–Bassham (CBB) cycle, based on its native methanol assimilating xylulose monophosphate pathway (XuMP) cycle. Initial growth rates were low, but could be doubled by adaptive laboratory evolution (ALE). Beneficial mutations led to a decrease of CBB cycle reactions, indicating further limitations. During this study, temperature was identified as one of the key process parameters to improve autotrophic growth. For this reason, a new round of adaptive laboratory evolution was performed at the identified optimal cultivation temperature of 25°C, resulting in isolates growing up to 50 % faster compared to the control strain. Whole genome resequencing followed by reverse engineering helped to identify first key mutations of the evolved strains. In addition, targeted engineering was performed by increasing the copy number of the key gene of the CBB cycle RuBisCO, which is the bottleneck of carbon fixation. Combining this with the optimal cultivation temperature boosted maximum specific growth rates of the autotrophic K. phaffii strain. In comparison to ALE, the targeted engineering still is lagging behind a bit. Starting from the initial condition, growth was boosted more than 2.5-fold in this study to a maximum of 0.025 h -1 .

ABSTRACT Wnt signaling plays an essential role in organismal development and stem cell maintenance, and is frequently dysregulated in various human diseases. Wnt proteins are lipid-modified, secreted morphogens that activate biological programs in a concentration-dependent manner. Their secretion depends on specialized trafficking components, including the cargo receptor Evi/Wls, and often involves apical re- internalization and transcytosis. However, several critical steps in Wnt/Wg trafficking remain poorly understood. In this study, we conducted an in vivo CRISPR-Cas9 screen in the developing Drosophila wing imaginal disc to uncover novel regulators of Wg secretion. We identified Vps15, a regulatory subunit of the class III phosphatidylinositol 3-kinase (PI3K(III)) complex, as an essential factor for Wg trafficking at the apical membrane. Loss of Vps15 leads to pronounced apical accumulation of Wg in producing cells, elevated extracellular Wg levels, and reduced expression of Wg target genes. Our data indicate that PI3K(III) activity is required for efficient apical endocytosis of Wg, independent of Evi/Wls abundance. These findings reveal a previously unrecognized role for the PI3K(III) and lipid biogenesis in Wg secretion within polarized epithelia, enhancing our mechanistic understanding of Wnt trafficking. Summary statement We identify the PI3K(III) complex as a novel regulator of Wg endocytosis at the apical membrane, revealing a new mechanism controlling Wnt secretion in polarized epithelial tissue.

SUMMARY Animal models of human diseases are an essential component of understanding disease pathogenesis and serve as preclinical models for therapeutic evaluation. Recently human patient genome sequencing has defined unique patient variants that result in disease states with different phenotypes than those observed with null alleles. The UAB Center for Precision Animal Modeling (CPAM) serves to analyze patient variant pathogenicity and disease mechanisms through the generation of animal models. We have optimized a zebrafish gene editing platform to successfully generate 11 patient variants (first round: NF1 R1276Q, NF1 G484R, VMA21 G55V, SPOP D144N, SGO1 K23E, Pex10 H310D, and FKRP C318Y; second round: NF1 R681*, NF1 M992del, P53 R175H, and PKD2 L656W) and 1 research allele ( p53 K120R). We used CRISPR/Cas9 guide directed cleavage along with single-stranded oligodeoxynucleotide (ssODNs) repair templates to generate these models. We evaluated multiple oligo orientations and sizes, but did not find a unified consensus orientation or size that significantly impacted efficiency, emphasizing the need to empirically evaluate multiple variations for the best homology directed repair (HDR) rate. We determined PCR amplicon Next Generation Sequencing (NGS) evaluation of HDR efficiency at the F0 embryo level is best for determining the ideal guide and oligo combination. Further NGS evaluation of DNA from progeny from F0s (germline derived), not F0 biopsy DNA, is essential to identify germline transmitting founders. Surprisingly we find that most founders exhibit a jackpot effect in the germ line but not in the somatic tissue. We found NGS superior to using ICE (Inference of CRISPR Edits) for determining HDR frequency. When applicable, allelic-specific PCR or allelic specific restriction digestion can be used to genotype mutation carrying F1 generation animals, however we demonstrated that false positives occur. Further, we successfully used high resolution melting curve analysis (HRMA) to differentiate and identify F1 animals with patient variants.

Summary The zinc-finger associated domain (ZAD)-containing C2H2 zinc-finger proteins (ZAD-ZnFs) represent the most abundant class of transcription factors that emerged during insect evolution, yet their molecular diversity and biological functions remain largely unclear. Here, we established a systematic CRISPR-based protein-tagging approach that enables direct, unambiguous comparison of nuclear localization and genome-wide binding profiles of endogenous ZAD-ZnFs in developing Drosophila embryos. Evidence is provided that a subset of ZAD-ZnFs forms nuclear condensates through the stacking of the N-terminal ZAD dimerization surface. Disruption of condensation activity leads to misregulation of genome-wide binding profiles and lethality, underscoring its functional and physiological significance in development. Importantly, integrative ChIP-seq and Micro-C data analyses reveal that many ZAD-ZnFs colocalize with core insulator proteins such as CTCF and CP190 to strengthen the formation of topological boundaries. We suggest that the diverse molecular functions of ZAD-ZnFs have evolutionally arisen from their ancestral role as insulator-binding proteins.

Bioplastics represent promising alternatives to petroleum-based plastics, yet their biodegradation remains insufficiently understood. Identifying bacteria capable of degrading bioplastics extracellularly could enhance end-of-life management practices. To investigate Burkholderia ’s capacities for the degradation of medium-chain-length polyhydroxyalkanoate (mcl-PHA), we screened a panel of Burkholderia strains and identified such capacity in some strains of B. gladioli , B. multivorans, and B. vietnamiensis . To elucidate the genetic basis of this activity, we performed transposon mutagenesis followed by activity-based screening and Tn-seq on B. vietnamiensis LMG 16232. Transposon insertions with negative phenotype were identified in genes encoding a triacylglycerol lipase, a lipase chaperone, type II secretion system components, HTH-type transcriptional activators, and a polyhydroxyalkanoate synthesis repressor. To validate the involvement of these genetic elements in mcl-PHA degradation, we generated insertional mutants using a CRISPR-associated transposase system (CAST). Complete loss or reduced extracellular mcl-PHA depolymerase activity was observed in the CAST mutants, validating their involvement in mcl-PHA degradation. In addition, the interruption of these genetic elements showed a loss of lipase activity, suggesting that the enzymes responsible for mcl-PHA depolymerase are lipases with substrate ambiguity; moreover, docking experiments supported these findings. Together, we identify B. vietnamiensis as a source of enzymes capable of degrading extracellular mcl-PHA and demonstrate the power of combining activity-based screening, Tn-seq, and CAST to rapidly establish gene-to-function links. Importance Due to their versatile metabolism, Burkholderia strains play critical roles in degradation of multiple compounds in the environment. Here we show that several Burkholderia species can degrade medium-chain-length polyhydroxyalkanoates (mcl-PHAs), a promising class of bioplastics. By integrating transposon mutagenesis, Tn-seq, and CRISPR-associated transposase (CAST) technologies, we identify and validate key genetic determinants involved in mcl-PHA degradation in B. vietnamiensis. These genes encode a lipase, a secretion system component, and regulatory factors, underscoring the complexity and specificity of microbial bioplastic degradation pathways. The findings not only advance our understanding of PHA biodegradation but also identifies B. vietnamiensis as as a source of enzymes capable of degrading extracellular mcl-PHA.

Duchenne muscular dystrophy (DMD) is a progressive muscle wasting disease for which there is no cure. There is a critical need for additional therapeutics. Human genome-wide association studies (GWAS) have identified candidate DMD genetic modifiers that could serve as therapeutic targets. Because many GWAS-identified single nucleotide polymorphisms (SNPs) lie in noncoding, putative regulatory regions, it can be challenging to identify which gene(s) are regulated by these SNPs and how gene expression is altered to modify disease severity even with extensive in silico modeling. We analyzed expression of zebrafish orthologs of putative DMD modifiers and showed almost all are comparably expressed in wild-type and dmd mutant zebrafish at three different stages of disease. To model decreased expression of candidate modifiers, we pursued a zebrafish CRISPR-based screening approach, which we validated by testing zebrafish orthologs of two extensively studied DMD modifiers, LTBP4 and THBS1. We then tested candidates from the most recent GWAS and demonstrate that galntl6, man1a1, etaa1a;etaa1b, and adamts17 are bona fide DMD modifiers. Our findings demonstrate the utility of zebrafish for DMD genetic modifier screening and characterizing modifier function.

CRISPR base editors enable scalable targeted DNA mutagenesis and are a powerful tool for the interpretation of gene function, the study of variants of unknown significance, and disease modelling. Existing guide RNA (gRNA) design tools focus on engineering a small number of targeted variants in a given gene or lack comprehensive functional annotation of target sequences. Here we developed BEstimate, a flexible computational pipeline that systematically specifies base editor gRNA target sites, generates gRNA off-target predictions, and rich functional, structural and clinical annotations of targeted edits. BEstimate accommodates custom gRNA design against variant alleles, improving editing accuracy and facilitating the programmed reversion of disease variants. BEstimate is a freely available, versatile tool for designing gRNA libraries and analysing base editor screens.

Computational models have become essential tools for understanding signalling networks and their non-linear dynamics. However, these models are typically constructed manually using prior knowledge and can be over-reliant on study bias. These limitations hinder their ability to make accurate predictions and incorporate new evidence. Scaling up the construction of models to take advantage of increasingly abundant ‘omics data can bridge these gaps by providing a comprehensive view of signalling events and how they influence cellular phenotypes. In this study, we present MAGELLAN, a method leveraging message passing graph neural networks to build computational models directly from pathway data and discrete rules representing experimental results. We used this to construct a computational model of breast cancer signalling and re-parameterize a previously published non-small cell lung cancer (NSCLC) model, showing that MAGELLAN can predict genetic dependencies and achieve comparable model quality to expert-curated and manually trained models. Our approach enables the integration of prior knowledge networks and experimental data to build predictive models that are mechanistically interpretable. This approach simplifies model creation, making it more accessible and practical for experimentalists, and supports broader applications in drug discovery and biological research.

Abstract The developmentally dynamic stem cell-like subpopulation in cancers known as cancer stem cells (CSCs) metastasize efficiently, form new tumours, and are resistant to current therapeutics. Understanding the molecular mechanisms of the stem cell-like state could help eliminate CSCs via novel therapeutic applications in aggressive cancers such as pancreatic ductal adenocarcinoma (PDAC). Here, we performed a compound screen uncovering that inhibition of Hypoxia-inducible factor prolyl hydroxylase 2 (PHD2) supports CSCs, whereas a novel proline-uncompetitive glutamyl-prolyl-tRNA synthetase (GluProRS) inhibitor NCP26 eliminates CSCs. By using a multiomic strategy with transcriptomics and quantitative secretomic analyses, we uncovered that TGFβ/Activin signalling induces HIF1A-mediated pseudohypoxia via ɑ-Ketoglutarate depletion due to P4HA1 intracellular upregulation. In turn, HIF1A and SMAD2/3 form a transcriptional complex that regulates CSC self-renewal, invasiveness and chemoresistance. NCP26 has several anti-tumour effects, including direct activation of the Integrated Stress Response (ISR) and indirect inhibition of the pseudo-hypoxia circuitry mediated by SMAD2/3-HIF1A that deposits collagen in ECM. Furthermore, GluProRS is secreted from PDAC cells and elevated in PDAC patient blood compared to healthy and pancreatitis patients. Collectively, the secreted GluProRS protein could be a useful biomarker for early PDAC detection, and its inhibitor NCP26 is an attractive candidate for combined chemotherapeutic applications.

Abstract Background BRAT1 (BRCA1-associated ataxia telangiectasia mutated activator 1) plays a crucial role in several vital biological processes, including the DNA damage response and the maintenance of mitochondrial homeostasis. Dysfunction in BRAT1 leads to a range of clinical phenotypes, with the majority of affected individuals succumbing before reaching one year of age. Results Through an analysis of previous literature, the homozygous BRAT1 p.V62E mutation (GTG to GAG) was selected to construct a mouse model. Homozygous BRAT1 p.V62E knock-in mice with a C57BL/6J background were generated using CRISPR/Cas9 technology, and the point mutation was confirmed by Sanger sequencing. The results revealed no significant differences between the mutant mice and wild-type controls during low-intensity testing. However, the mutant mice exhibited enhanced endurance during high-intensity testing. RNA sequencing analysis identified ten differentially expressed genes in the gastrocnemius muscle and four differentially expressed genes in the brain tissue of the mutant mice. Conclusions This represents the first successful construction of a BRAT1 mutant mouse model. This achievement not only provides confidence for developing additional mouse models but also offers a valuable perspective for understanding the relationship between BRAT1 and mitochondrial function. The mouse model demonstrates a degree of consistency with the clinical phenotypes observed in patients and may serve as a predictive tool for patient prognosis.

ABSTRACT Phosphorylation, a crucial post-translational modification (PTM), plays a central role in cellular signaling and disease mechanisms. Mass spectrometry-based phosphoproteomics is widely used for system-wide characterization of phosphorylation events. However, traditional methods struggle with accurate phosphorylated site localization, complex search spaces, and detecting sequences outside the reference database. Advances in de novo peptide sequencing offer opportunities to address these limitations, but have yet to become integrated and adapted for phosphoproteomics datasets. Here, we present InstaNovo-P, a phosphorylation specific version of our transformer-based InstaNovo model, fine-tuned on extensive phosphoproteomics datasets. InstaNovo-P significantly surpasses existing methods in phosphorylated peptide detection and phosphorylated site localization accuracy across multiple datasets, including complex experimental scenarios. Our model robustly identifies peptides with single and multiple phosphorylated sites, effectively localizing phosphorylation events on serine, threonine, and tyrosine residues. We experimentally validate our model predictions by studying FGFR2 signaling, further demonstrating that InstaNovo-P uncovers phosphorylated sites previously missed by traditional database searches. These predictions align with critical biological processes, confirming the model’s capacity to yield valuable biological insights. InstaNovo-P adds value to phosphoproteomics experiments by effectively identifying biologically relevant phosphorylation events without prior information, providing a powerful analytical tool for the dissection of signaling pathways.

Classification of high-dimensional information is a ubiquitous computing paradigm across diverse biological systems, including organs such as the brain, down to signaling between individual cells. Inspired by the success of artificial neural networks in machine learning, the idea of engineering genetic circuits that operate as neural networks emerges as a strategy to expand the classification capabilities of living systems. In this work, we design these biomolecular neural networks (BNNs) based on the molecular sequestration reaction, and experimentally characterize their behavior as linear classifiers for increasing levels of complexity. Initially, we demonstrate that a static, DNA-based system can effectively prototype a linear classifier, though we also identify its limitations to easily tune the slope of the decision boundary it generates. We then propose and experimentally validate a BNN at the protein level using a cell-free transcription–translation (TXTL) system, which overcomes the DNA-based system’s limitation and behaves as a linear classifier even before it reaches its steady state (or, equivalently, out-of-equilibrium). Ultimately, we test a CRISPR-based design and its out-of-equilibrium behavior in a biological context by successfully constructing a linear classifier within mammalian cells. Overall, by leveraging mathematical modeling and experimental automation, we establish molecular sequestration as a universal scheme for implementing neural networks within living systems, paving the way for transformative advances in synthetic biology and programmable biocomputing systems.

Lipid nanoparticles (LNPs) have emerged as a transformative platform for mRNA delivery, enabling vaccines and gene editing with transient expression and high cargo capacity. However, their potential for ocular gene editing remains underexplored. In this study, we assessed the transduction efficiency, inflammatory response, and gene editing capability of LNP-encapsulated mRNA in murine eyes. Intravitreal delivery of LNPs achieved targeted mRNA expression in the trabecular meshwork (TM) with superior specificity and efficiency compared to adenoviral or adeno-associated viral vectors, while inducing minimal microglial activation in the retina. Using LNPs co-encapsulating SpCas9 mRNA and sgRNA, we demonstrated efficient CRISPR-mediated knockout (KO) of Matrix Gla Protein (Mgp), a key inhibitor of TM calcification. Mgp-KO eyes exhibited sustained intraocular pressure (IOP) elevation and anterior chamber deepening with normal anterior chamber angle, recapitulating key features of primary open-angle glaucoma (POAG). Chronic IOP elevation led to reactive Müller gliosis and ganglion cell complex thinning, reflecting retinal stress and progressive neurodegeneration. Our findings establish LNP-CRISPR as a safe and efficient system for TM-targeted gene editing, with broad applicability in glaucoma pathogenesis modelling and therapeutic discovery.