The disease burden from non-small cell lung cancer (NSCLC) adenocarcinoma is substantial, with around a million new cases diagnosed globally each year, and a 5-year survival rate of less than 20%. A lack of therapeutic options personalized to individual patient genetics, and the targeted therapies that exist quickly succumbing to resistance, leads to high variation in survival. Patient stratification combined with greater personalisation of therapies have the potential to improve outcomes, however, the wide variation in mutations found in NSCLC adenocarcinoma patients mean that experimentally determining suitable treatment combinations is time-consuming and expensive. Here we present an in silico model encompassing tumour intrinsic key oncogenic signalling pathways, including EGFR, AKT, JAK/STAT and WNT for efficiently predicting rational drug-drug and drug-radiotherapy combination therapies in NSCLC. Using this model, we simulate diverse genetic profiles and test over 10,000 therapeutic combinations to identify optimal strategies to overcome resistance mechanisms specific to genetic profiles and p53 status. Our in silico model reproduces drug additivity experiments, predicts radio-sensitising genes validated in a CRISPR screen and identifies 53BP1 as a potential drug target that improves the therapeutic window during radiotherapy, as well as potential to use ATM inhibitors to overcome p53 loss-of-function driven radiotherapy resistance. We further use the in silico model to identify a 19-gene signature to stratify patients most likely to benefit from radiotherapy and validated this using TCGA data. These results further demonstrate the utility of in silico mechanistic modelling and present a bespoke computational resource for large-scale screening of personalised therapies applied to NSCLC.

ABSTRACT The underlying cause for renal and uterine agenesis remains unknown in many cases, whereas recurrence in some families strongly suggests the involvement of genetic factors. Here, we identify 5 affected individuals from 3 families with phenotypes including bilateral or unilateral renal agenesis/hypoplasia, along with variable congenital uterine anomalies and costovertebral defects associated with heterozygous deleterious variants in NR6A1 . The variant spectrum includes both inherited missense as well as de novo loss of function, with the latter associated with a perinatal lethal phenotype characterized by bilateral renal agenesis. In vitro studies demonstrated partial loss-of-function for both missense variants. To investigate the role of NR6A1 in development, CRISPR-Cas9 knockout zebrafish models targeting the orthologues nr6a1a and nr6a1b were generated. Mutants recapitulate the human phenotype, exhibiting impaired kidney development, including pronephros segmentation defects and adult kidney hypoplasia, along with axial skeletal abnormalities, cloacal anomalies, and disrupted anteroposterior expression of posterior hox genes. This study provides strong evidence linking NR6A1 heterozygous loss-of-function variants to renal, uterine and costovertebral defects in humans.

Gene networks encapsulate biological knowledge, often linked to polygenic diseases. While model system experiments generate many plausible gene networks, validating their role in human phenotypes requires evidence from human genetics. Rare variants provide the most straightforward path for such validation. While single-gene analyses often lack power due to rare variant sparsity, expanding the unit of association to networks offers a powerful alternative, provided it integrates network connections. Here, we introduce NERINE, a hierarchical model-based association test that integrates gene interactions that integrates gene interactions while remaining robust to network inaccuracies. Applied to biobanks, NERINE uncovers compelling network associations for breast cancer, cardiovascular diseases, and type II diabetes, undetected by single-gene tests. For Parkinson’s disease (PD), NERINE newly substantiates several GWAS candidate loci with rare variant signal and synergizes human genetics with experimental screens targeting cardinal PD pathologies: dopaminergic neuron survival and alpha-synuclein pathobiology. CRISPRi-screening in human neurons and NERINE converge on PRL , revealing an intraneuronal α-synuclein/prolactin stress response that may impact resilience to PD pathologies.

Abstract Mutations in DJ-1 cause autosomal recessive Parkinson’s disease. Several functions have been attributed to DJ-1, including a key role in the protection from oxidative stress, however how this protein contributes to PD pathogenesis is still unclear. Recently, DJ-1 has been identified at higher concentration in extracellular vesicles (EV) from biological fluids of PD patients, providing a link between EV and a protein associated with PD. EV were isolated from the medium of control and rotenone-treated wild-type and DJ-1 KO differentiated SH-SY5Y cells, their number was evaluated by flow cytometry and the proteomic signature of their cargo was investigated by mass spectrometry analysis. Migration of THP-1 derived macrophages was used a read out for functional EV. The results obtained were validated in iPSC-derived neuronal cells. We identified an altered EV response to rotenone in DJ-1 KO cells compared to wild-type. Mass spectrometry analysis identified 116 proteins with significantly different concentrations between the two genotypes, suggesting a link between DJ-1 and EV cargo in response to oxidative stress. Additionally, we showed that DJ-1 KO alters the ability of EV to stimulate macrophage migration, thus implying functional consequences for DJ-1 absence in the EV mediated response to oxidative stress. The altered EV response to rotenone was confirmed in iPSC-derived neurons lacking DJ-1 compared to isogenic controls. Our results indicate a clear DJ-1 role in intercellular communication in oxidative stress, underlying a new EV mediated DJ-1 function that may be relevant to PD pathogenesis.

Candida auris is an emergent fungal pathogen of significant interest for molecular research because of its unique nosocomial persistence, high stress tolerance and common multidrug resistance. To investigate the molecular mechanisms of these or other phenotypes, a handful of CRISPR-Cas9 based allele editing tools have been optimized for C. auris . Nonetheless, allele editing in this species remains a significant challenge, and different systems have different advantages and disadvantages. In this work, we compare four systems to introduce the genetic elements necessary for the production of Cas9 and the guide RNA molecule in the genome of C. auris, replacing the ENO1 , LEU2 and HIS1 loci respectively, while the fourth system makes use of an episomal plasmid. We observed that the editing efficiency of all four systems was significantly different and strain dependent. Alarmingly, we did not detect correct integration of linear CRISPR cassette constructs in integration-based systems, in over 4,900 screened transformants. Still, all transformants, whether correctly edited or not, grew on selective nourseothricin media, suggesting common random ectopic integration of the CRISPR cassette. Although the plasmid-based system showed a low transformation success compared to the other systems, it has the highest editing efficiency with 41.9% correct transformants on average. In an attempt to improve editing efficiencies of integration-based systems by silencing the non-homologous end joining (NHEJ) DNA repair pathway, we deleted two main NHEJ factors, KU70 and LIG4 . However, no improved editing or targeting efficiencies were detected in ku7011, lig411, or ku7011/lig411 backgrounds. Our research highlights important challenges in precise genome editing of C. auris and sheds light on the advantages and limitations of several methods with the aim to guide scientists in selecting the most appropriate tool for molecular work in this enigmatic fungal pathogen. Author summary Candida auris is a rapidly emerging fungal pathogen that poses serious challenges to global healthcare. Understanding the genetic mechanisms that underlie its nosocomial persistence, virulence, multidrug resistance and other traits is essential for developing new treatments and preventing the spread and burden of C. auris infections. However, precise genetic manipulation in C. auris has proven difficult due to inefficient genome editing tools. This study compares four different CRISPR-based allele editing systems in C. auris , identifying their strengths and limitations. The findings provide crucial insights into selecting the best tools for genetic research in C. auris , guiding future efforts to combat this formidable pathogen.

The 5’-3’ exonuclease phospholipase D3 (PLD3) is a single-pass transmembrane protein undergoing sequential post-translational modifications (PTM) by N -glycosylation, AMPylation and proteolytic cleavage. The substrates of PLD3 5’-3’ exonuclease activity are single-stranded DNAs and RNAs, which act as ligands for Toll-like receptors (TLRs) and trigger a downstream pro-inflammatory response. Although PLD3 has primarily been studied in immune cells, recent findings indicate its enrichment in neurons, where it plays a role in regulating axonal fitness in Alzheimer’s disease (AD). However, the regulatory mechanisms governing the proteolytic processing of PLD3 into its catalytically active soluble form and its functional roles in both immune and neuronal cells remain unclear. Here, we describe the functional implications of PLD3 AMPylation, its direct interaction with the protein adenylyltransferase FICD, and changes in PLD3 processing in Parkinson’s disease (PD) patient-derived neurons. We identified PLD3 AMPylation sites within the proteins’ soluble region and show that mutation of these sites lead to loss of PLD3 exonuclease catalytic activity. FICD AMP-transferase accelerates PLD3 degradation and induces cellular stress response. Furthermore, depletion of the two human AMP-transferases FICD and SelO point towards a complex regulatory network governing PLD3 AMPylation. Together, our findings demonstrate a critical role of AMPylation in PLD3 processing and regulation of its catalytic activity and provide new insights into the protein’s transport and localization to lysosomes. The observation that PLD3 regulation in PD-derived neurons is altered compared to healthy neurons further highlights its role in neurodegenerative diseases.

Abstract Background Due to its ability to grow fast on CO 2 , CO and H 2 at high temperatures and with high energy efficiency, the thermophilic acetogen Thermoanaerobacter kivui could become an attractive host for industrial biotechnology. In a circular carbon economy, diversification and upgrading of C1 platform feedstocks into value-added products (e. g. ethanol, acetone and isopropanol) could become crucial. To that end, genetic and bioprocess engineering tools are required to facilitate development of bioproduction scenarios. Currently, the genome editing tools available for T. kivui present some limitations in speed and efficiency, thus restricting the development of a powerful strain chassis for industrial applications. Results In this study, we developed the versatile genome editing tool Hi-TARGET, based on the endogenous CRISPR Type I-B system of T. kivui . Hi-TARGET demonstrated 100% efficiency for gene knock-out (from both purified plasmid and cloning mixture) and knock-in, and 49% efficiency for creating point mutations. Furthermore, we optimized the transformation and plating protocol and increased transformation efficiency by 245-fold to 1.96 x 10 4 ± 8.7 x 10 3 CFU µg − 1 . Subsequently, Hi-TARGET was used to demonstrate gene knock-outs ( pyrE , rexA , hrcA ), a knock-in ( ldh ::pFAST), a single nucleotide mutation corresponding to PolC C629Y , and knock-down of the fluorescent protein pFAST. Analysis of the ∆ rexA deletion mutant created with Hi-TARGET revealed that the transcriptional repressor rexA is likely involved in the regulation of the expression of lactate dehydrogenase ( ldh ). Following genome engineering, an optimized curing procedure for edited strains was devised. In total, the time required from DNA to a clean, edited strain is 12 days, rendering Hi-TARGET a fast, robust and complete method for engineering T. kivui . Conclusions The CRISPR-based genome editing tool Hi-TARGET developed for T. kivui can be used for scarless deletion, insertion, point mutation and gene knock-down assays, thus fast-tracking the generation of industrially-relevant strains for the production of carbon-negative chemicals and fuels as well as facilitating studies of acetogen metabolism and physiology.

Despite the liver’s recognized regenerative potential, the role of the hepatic ductal cells (a.k.a. biliary epithelial cells), its heterogeneity, and functionality remain incompletely understood in this process. This study provides a comprehensive examination of the molecular and cellular mechanisms underpinning liver ductal development and liver regeneration in zebrafish, with a spotlight on the functional roles of her family genes in these processes. Using state-of-the-art knock-in zebrafish models and single-cell transcriptomics we reveal the differential expression patterns of the different her genes, of which her2 , her6 , and her9 , were identified as specific molecular signatures for distinguishing different ductal cell types with unique morphology and spatial distribution. Particularly, her9 serves as a pan-ductal marker and shows responsiveness to the synergistic effect of Notch and BMP signaling. By analyzing multiple single-cell RNA-seq datasets, we identify numerous ductal markers which are functional proteins for ductal integrity, and most notably CRISPR mutagenesis demonstrates that her9 is essential for hepatocyte recovery. Using multiple transgenic and knock-in zebrafish lines and genetic fate mapping, we provide a detailed characterization of the ductal remodeling process under development and extreme loss of intra-hepatic duct, highlighting the remarkable ductal cell plasticity. Single-cell transcriptomics of lineage-traced her9 -expressing liver ducts in static and regenerative states uncover distinct cell clusters with unique molecular signatures and morphology, reflecting the liver’s regenerative dynamics and highlight relevant key biological processes that could be leveraged to expedite liver regeneration.

Abstract Fonio ( Digitaria exilis ), known as the "grain of life," is a vital food security crop grown by smallholder farmers across West Africa. Renowned for its short maturity period of 6-8 weeks, fonio provides essential harvests during periods of food scarcity. Its nutritional value, drought resilience, and ability to thrive on marginal soils make it a crucial staple in the region. However, fonio’s yield, averaging less than 0.5 metric tons per hectare, remains significantly lower than major cereals, due to minimal breeding efforts aimed at enhancing agronomic traits. In this study, we generated a high-quality chromosome-resolved, tetraploid (2n=4x=36) genome of a fonio line (PI 349688) available through the United States Germplasm Resource Information Network (GRIN). Time-of-day (TOD) expression profiling revealed sub-genome dominance in pathways associated with key agronomic traits that were also identified in a selective sweep analysis across a panel of 90 fonio accessions that originated from 21 different villages over five regions of Senegal representing eight distinct ethnic groups. Leveraging phenotyping across 14 key agronomic traits, we identified genotype-trait associations for plant height, tillering and panicle yield with genes involved in the circadian clock, light signaling and plant architecture. We demonstrated that fonio is amenable to transformation and gene editing, as evidenced by successful CRISPR-Cas9 modification of the Green Revolution gene REDUCED HEIGHT 1 ( RHT1 ), resulting in lines with increased height, vegetative area, and enhanced tillering. Collectively, the genomic resources developed here pave new avenues for molecular breeding and trait discovery, laying a robust foundation for accelerating fonio improvement to bolster food security, climate resilience, and sustainable agriculture in West Africa.

Cardiometabolic diseases, including ischemic heart disease, hypertensive heart disease, and associated vascular conditions, have experienced a sharp global increase in prevalence and mortality over recent decades. According to the World Heart Federation, the global death toll from cardiovascular diseases grew from 12 million in 1990 to 20.5 million in 2021. The development of cardiometabolic diseases such as hypertension, type 2 diabetes, obesity, and vascular disorders is driven by a complex interplay of risk factors. These include oxidative stress, chronic inflammation, imbalances in blood glucose and lipid levels, formation of lipid peroxides, increased intima-media thickness (IMT), subclinical atherosclerosis, coronary artery calcification, arterial narrowing, the formation of vulnerable plaques, and activation of platelet and coagulation pathways. These risk factors contribute to metabolic disorders by promoting insulin resistance, endothelial dysfunction, and the progression of atherosclerosis. Despite this understanding, routine annual checkups often fail to prioritize early risk detection or the development of preventive and management strategies. Instead, these checkups typically focus on diagnosing existing metabolic conditions and managing them to prevent acute vascular events. However, the South Asian Society on Atherosclerosis and Thrombosis has been actively promoting global education and the development of preventive strategies. Recent research advances underscore the importance of addressing oxidative stress, inflammation, and lipid oxidation to slow disease progression. Innovative therapeutic approaches, including statins, small-interfering RNA (siRNA), non-coding RNA (ncRNA) therapies, and gene-editing tools like CRISPR/Cas9, have shown considerable promise in lowering cholesterol and lipoprotein(a) levels, lowering risks associated with type-2 diabetes, stabilizing arterial plaques, and reducing overall cardiovascular risk. Additionally, breakthroughs in mRNA vaccines and computational genomics emphasize the potential of precision medicine in tackling chronic diseases. This overview highlights key findings on the roles of oxidative stress, inflammation, atherosclerosis, platelet-vessel wall interactions, and acute vascular occlusion in the development and progress of cardiometabolic diseases. Major clinical trials indicate that addressing a few modifiable risk factors can significantly reduce premature deaths from cardiovascular diseases. Nevertheless, managing cardiometabolic diseases on a population scale remains a formidable challenge. Enhanced preventive measures, better diagnostic tools, and widespread education are critical. Collaborative efforts involving governments, healthcare systems, professional organizations, and communities are essential to alleviating the societal burden of these conditions and improving health outcomes globally. This, in turn, can improve health outcomes, particularly in low-and middle-income countries where healthcare infrastructure and resources are often limited.

The translation of mRNA into proteins in multicellular organisms needs to be carefully tuned to changing proteome demands in development and differentiation, and defects in translation often have a disproportionate impact in distinct cell types. Here we used inducible CRISPR interference screens to compare the essentiality of genes with functions in mRNA translation in human induced pluripotent stem cells (hiPSC) and hiPSC-derived neural and cardiac cells. We find that core components of the mRNA translation machinery are broadly essential, but the consequences of perturbing translation-coupled quality control factors are highly cell type-dependent. Human stem cells critically depend on pathways that detect and rescue slow or stalled ribosomes, and on the E3 ligase ZNF598 to resolve a novel type of ribosome collisions at translation start sites on endogenous mRNAs with highly efficient initiation. Our findings underscore the importance of cell identity for deciphering the molecular mechanisms of translational control in metazoans.

Reactive oxygen species (ROS) have been implicated repeatedly in multiple signaling processes in plants but the underlying mechanisms and roles remain enigmatic. Here, we developed live imaging of apoplastic ROS at the root surface. Different signals, including auxin, extracellular ATP and RALF1 peptide, all induce cytosolic calcium transients and apoplastic ROS bursts. Genetic and optogenetic manipulations identified calcium transients as necessary and sufficient for ROS bursts via activation of NADPH oxidases RBOHC and RBOHF. Apoplastic ROS bursts are not required but rather limit the gravity-induced root bending. Root bending is sensed by stretch-activated calcium channel MCA1 leading to NADPH oxidase activation at the stretched side. The resulting ROS production stiffens cell wall for better soil penetration. Apoplastic ROS thus provides a means to balance tissue flexibility and stiffness to efficiently navigate soil.

ABSTRACT Background Megalencephalic leukoencephalopathy with subcortical cysts (MLC), a rare and progressive neurodegenerative disorder involving the white matter, is not adequately recapitulated by current disease models. Somatic cell reprogramming, along with advancements in genome engineering, may allow the establishment of in-vitro human models of MLC for disease modeling and drug screening. In this study, we utilized cellular reprogramming and gene-editing techniques to develop induced pluripotent stem cell (iPSC) models of MLC to recapitulate the cellular context of the classical MLC-impacted nervous system. Methods Somatic cell reprogramming of peripheral patient-derived blood mononuclear cells (PBMCs) was used to develop iPSC models of MLC. CRISPR-Cas9 system-based genome engineering was also utilized to create the MLC1 knockout model of the disease. Directed differentiation of iPSCs to neural stem cells (NSCs) and astrocytes was performed in a 2D cell culture format, followed by various cellular and molecular biology approaches, to characterize the disease model. Results MLC iPSCs established by somatic cell reprogramming and genome engineering were well characterized for pluripotency. iPSCs were subsequently differentiated to disease-relevant cell types: neural stem cells (NSCs) and astrocytes. RNA sequencing profiling of MLC NSCs revealed a set of differentially expressed genes related to neurological disorders and epilepsy, a common clinical finding within MLC disease. This gene set can serve as a target for drug screening for the development of a potential therapeutic for this disease. Upon differentiation to the more disease relevant cell type-astrocytes, MLC-characteristic vacuoles were clearly observed, which were distinctly absent from controls. This emergence recapitulated a distinguishing phenotypic marker of the disease. Conclusion Through the creation and analyses of iPSC models of MLC, our work addresses a critical need for relevant cellular models of MLC for use in both disease modeling and drug screening assays. Further investigation can utilize MLC iPSC models, as well as generated transcriptomic data sets and analyses, to identify potential therapeutic interventions for this debilitating disease.

In many cells, cell polarity depends on the asymmetric distribution of the conserved PAR proteins, maintained by a balanced activity between kinases and phosphatases. The C. elegans one-cell embryo is polarized along the anterior-posterior axis, with the atypical protein kinase C PKC-3 enriched in the anterior, and the ring finger protein PAR-2 in the posterior. PAR-2 localization is regulated by PKC-3 and the PP1 phosphatases GSP-1/-2. Here, we find that, like GSP-2 depletion, depletion of the conserved PP1 interactor SDS-22 results in the rescue of the polarity defects of a pkc-3 temperature-sensitive mutant. Consistent with the rescue, SDS-22 depletion or mutation results in reduced GSP - 1/ - 2 protein levels and activity. The decreased levels of GSP-1/-2 can be rescued by reducing proteasomal activity. Our data suggest that SDS-22 regulates polarity not by directly regulating the localization or activity of GSP-1/-2, but by protecting these PP1 catalytic subunits from proteasome-mediated degradation, supporting recent data in human cells showing the SDS22 is required to stabilize nascent PP1.

Background Multicellular organisms develop from a single cell by repeated rounds of cell division, differentiation and apoptosis, which can be displayed in a single-cell phylogenetic tree. Genetic lineage tracing allows us to investigate this development by tracking the ancestry of individual cells as populations grow and change over time. However, accurate reconstruction of the cell phylogeny and quantification of the corresponding phylodynamic parameters - division, differentiation and apoptosis rate - from this tracking data remains challenging and needs to be systematically evaluated. Results We perform simulations and assess, using the Bayesian framework, the joint inference of time-scaled cell phylogenies and phylodynamic parameters from CRISPR lineage recordings with random or sequential edits. Principally, we characterize the inference improvement as the recorder capacity increases. Further, we characterize the increase of accuracy of phylogenetic reconstruction when using sequential compared to random recordings, i.e. when using the additional information contained in the order of edits. Moreover, we find that CRISPR lineage recordings carry a strong signal on the rates of cell division. When the phylodynamic parameters are inferred under models that match the true dynamics and when sufficiently many cells of each type are sampled, also cell death and differentiation rates can be estimated from the data. Conclusion In this study, we evaluate how much information on cellular development can be extracted from genetic lineage tracing data using phylogenetic and phylodynamic methodology. We identify important experimental, conceptual, and computational limitations for the inference which can guide future advancements in the field.

Cancer cells, immune cells, and stromal cells within the tumor microenvironment (TME) collaboratively influence disease progression and therapeutic responses. The nutrient-limited conditions of the TME, particularly the scarcity of glucose, amino acids, and lipids, challenge cancer cell survival 1–4 . However, the metabolic constraints faced by immune and stromal cells in comparison to cancer cells, and how these limitations affect therapeutic outcomes, remain poorly understood. Here, we introduce Dual Ribosome Profiling (DualRP), a method that allows for simultaneous analysis of translation and identification of ribosome stalling, revealing amino acid shortages in different cell types within tumors. Using DualRP, we uncover that interactions between cancer cells and fibroblasts trigger an inflammatory response, mitigating amino acid limitations during glucose starvation. In immunocompetent mouse models, we observe that immune checkpoint blockade therapy induces serine and glycine restrictions specifically in T cells, but not in cancer cells. We further demonstrate that these amino acids are essential for optimal T cell function both in vitro and in vivo , highlighting their critical role in effective immunotherapy. Our findings show that therapeutic interventions create distinct metabolic demands across different tumor cell types, with nutrient availability significantly influencing the success of immunotherapy. DualRP’s ability to explore cell type-specific metabolic vulnerabilities offers a promising tool for advancing our understanding of tumor biology and improving therapeutic strategies.

ABSTRACT Chemotherapy often kills a large fraction of cancer cells but leaves behind a small population of drug- tolerant persister cells. These persister cells survive drug treatments through reversible, non-genetic mechanisms and cause tumour recurrence upon cessation of therapy. Here, we report a drug tolerance mechanism regulated by the germ-cell-specific H3K4 methyltransferase PRDM9. Through histone proteomic, transcriptomic, lipidomic, and ChIP-sequencing studies combined with CRISPR knockout and phenotypic drug screen, we identified that chemotherapy-induced PRDM9 upregulation promotes metabolic rewiring in glioblastoma stem cells, leading to chemotherapy tolerance. Mechanistically, PRDM9-dependent H3K4me3 at cholesterol biosynthesis genes enhances cholesterol biosynthesis, which persister cells rely on to maintain homeostasis under chemotherapy- induced oxidative stress and lipid peroxidation. PRDM9 inhibition, combined with chemotherapy, resulted in strong anti-cancer efficacy in preclinical glioblastoma models, significantly enhancing the magnitude and duration of the antitumor response by eliminating persisters. These findings demonstrate a previously unknown role of PRDM9 in promoting metabolic reprogramming that enables the survival of drug-tolerant persister cells.

Anti-phage defense systems protect bacteria from viruses. Studying defense systems has begun to reveal the evolutionary roots of eukaryotic innate immunity and produced important biotechnologies such as CRISPR-Cas9. Dozens of new systems have been discovered by looking for systems that co-localize in genomes, but this approach cannot identify systems outside defense islands. Here, we present DefensePredictor, a machine-learning model that leverages embeddings from a protein language model to classify proteins as defensive. We applied DefensePredictor to 69 diverse E. coli strains and validated 45 previously unknown systems, with >750 additional unique proteins receiving high confidence predictions. Our model, provided as open-source software, will help comprehensively map the anti-phage defense landscape of bacteria, further reveal connections between prokaryotic and eukaryotic immunity, and accelerate biotechnology development.

ABSTRACT The rapid growth that occurs during Drosophila larval development requires a dramatic rewiring of central carbon metabolism to support biosynthesis. Larvae achieve this metabolic state, in part, by coordinately up-regulating the expression of genes involved in carbohydrate metabolism. The resulting metabolic program exhibits hallmark characteristics of aerobic glycolysis and establishes a physiological state that supports growth. To date, the only factor known to activate the larval glycolytic program is the Drosophila Estrogen-Related Receptor (dERR). However, dERR is dynamically regulated during the onset of this metabolic switch, indicating that other factors must be involved. Here we discover that Sima, the Drosophila ortholog of Hif1α, is also essential for establishing the larval glycolytic program. Using a multi-omics approach, we demonstrate that sima mutants fail to properly activate aerobic glycolysis and die during larval development with metabolic defects that phenocopy dERR mutants. Moreover, we demonstrate that dERR and Sima/Hif1α protein accumulation is mutually dependent, as loss of either transcription factor results in decreased abundance of the other protein. Considering that the mammalian homologs of ERR and Hif1α also cooperatively regulate aerobic glycolysis in cancer cells, our findings establish the fly as a powerful genetic model for studying the interaction between these two key metabolic regulators. STRUCTURED ABSTRACT Objectives The rapid growth that occurs during Drosophila larval development requires a dramatic rewiring of central carbon metabolism to support biosynthesis. Larvae achieve this metabolic state, in part, by coordinately up-regulating the expression of genes involved in carbohydrate metabolism. The resulting metabolic program exhibits hallmark characteristics of aerobic glycolysis and establishes a physiological state that supports growth. To date, the only factor known to activate the larval glycolytic program is the Drosophila Estrogen-Related Receptor (dERR). However, dERR is dynamically regulated during the onset of this metabolic switch, indicating that other factors must be involved. Here we examine the possibility the Drosophila ortholog of Hypoxia inducible factor 1α (Hif1α) is also required to activate the larval glycolytic program. Methods CRISPR/Cas9 was used to generate new loss-of-function alleles in the Drosophila gene similar ( sima ), which encodes the sole fly ortholog of Hif1α. The resulting mutant strains were analyzed using a combination of metabolomics and RNAseq for defects in carbohydrate metabolism. Results Our studies reveal that sima mutants fail to activate aerobic glycolysis and die during larval development with metabolic phenotypes that mimic those displayed by dERR mutants. Moreover, we demonstrate that dERR and Sima/Hif1α protein accumulation is mutually dependent, as loss of either transcription factor results in decreased abundance the other protein. Conclusions These findings demonstrate that Sima/HIF1α is required during embryogenesis to coordinately up-regulate carbohydrate metabolism in preparation for larval growth. Notably, our study also reveals that the Sima-dependent gene expression profile shares considerable overlap with that observed in dERR mutant, suggesting that Sima/HIF1α and dERR cooperatively regulate embryonic and larval glycolytic gene expression. HIGHLIGHTS The Drosophila melanogaster gene similar ( sima ), which encodes the sole fly ortholog of Hif1α, is required to up-regulate glycolysis in preparation for larval growth. sima mutant larvae exhibit severe defects in carbohydrate metabolism and die during the second larval instar. sima mutant larvae exhibit the same metabolic phenotypes as Drosophila Estrogen Related Receptor ( dERR ) mutants, suggesting that these two transcription factors coordinately regulate the larval glycolytic program. Sima/Hif1α and dERR accumulation is mutually dependent, as loss of either transcription factor results in decreased abundance of the other.

CRISPR (clustered regularly interspaced short palindromic repeats) technology has revolutionized both fundamental research and genomic medicine. The need for precise control of SpCas9-based CRISPR genome editing has resulted in a number of methods to control the function and activity of Cas9 proteins to minimize off-target editing effects. Proteolysis-targeting chimeras (PROTACs) are an emerging technology using the ubiquitin-proteasome system to selectively degrade the target proteins. Here, we developed CASPROTAC 6, a reversible and cell-permeable degrader directly targeting SpCas9 proteins for degradation. The warhead of CASPROTACs was derived by bridging a known SpCas9 binder BRD7087 with an S-substituted Lenalidomide cereblon (CRBN) ligand via the 6-carbon alkyl linker. Our data showed that CASPROTAC 6 is a broad-spectrum degrader of SpCas9 and SpCas9 variants such as dCas9 and Cas9 nickases. The CASPROTAC 6 degraded SpCas9 and the SpCas9-guide-RNA complex via the proteasome system by ∼50%. As a result, the CASPROTAC 6 molecule can reduce the CRISPR/Ca9-mediated genome editing by 30%. The CASPROTAC 6 molecules could be used to regulate the CRISPR/SpCas9-associated nucleases for precise genome editing to reduce off-target effects and strengthen biosafety.

Bacterial genomic mutations in Staphylococcus aureus (S. aureus) have been detected in isolated resistant clinical strains, yet their mechanistic effect on the development of antimicrobial resistance remains unclear. The resistance-associated regulatory systems acquire adaptive mutations under stress conditions that may lead to a gain of function effect and contribute to the resistance phenotype. Here, we investigate the effect of a single-point mutation (T331I) in VraS histidine kinase, part of the VraSR two-component system in S. aureus. VraSR senses and responds to environmental stress signals by upregulating gene expression for cell wall synthesis. A combination of enzyme kinetics, microbiological, and transcriptomic analysis revealed the mechanistic effect of the mutation on VraS and S. aureus . Michaelis Menten’s kinetics show that the VraS mutation caused an increase in the autophosphorylation rate of VraS and enhanced its catalytic efficiency. The introduction of the mutation through recombineering coupled with CRISPR-Cas9 counterselection to the Newman strain wild-type (WT) genome doubled the minimum inhibitory concentration of three cell wall-targeting antibiotics. The mutation caused an enhanced S. aureus growth rate at sub-lethal doses of the antibiotics, confirming the causative effect of mutation on bacterial persistence. Transcriptomic analysis showed a genome-wide alteration in gene expression levels and protein-protein interaction network of the mutant compared to the WT strain after exposure to vancomycin. The results suggest that vraS mutation causes several mechanistic changes at the protein and cellular levels that favor bacterial survival under antibiotic stress and cause the mutation-harboring strains to become the dominant population during infection. Importance Rising antimicrobial resistance (AMR) is a global health problem. Mutations in the two- component system have been linked to drug- resistance in Staphylococcus aureus , yet the exact mechanism through which these mutations work is understudied. We investigated the T331I mutation in the vraS gene linked to sensing and responding to cell wall stress. The mutation caused changes at the protein level by increasing the catalytic efficiency of VraS kinase activity. Introducing the mutation to the genome of an S. aureus strain resulted in changes in the phenotypic antibiotic susceptibility, growth kinetics, and genome-wide transcriptomic alterations. By a combination of enzyme kinetics, microbiological, and transcriptomic approaches, we highlight how small genetic changes can significantly impact bacterial physiology and survival under antibiotic stress. Understanding the mechanistic basis of antibiotic resistance is crucial to guide the development of novel therapeutic agents to combat AMR.

ABSTRACT In the malaria parasite Plasmodium falciparum, the expression of many genes is regulated by heterochromatin (HC) based on the histone mark tri-methylation of histone H3 lysine 9 (H3K9me3). HC assembly involves three distinct steps: de novo nucleation, spreading and maintenance. Nucleation, which consists in formation of HC in a previously euchromatic region, determines at which specific regions of the genome HC occurs. This process is not well understood in malaria parasites. Here we investigated the DNA sequence cis determinants of HC nucleation in P. falciparum , using a screening approach based on integration of fragments from different heterochromatic genes into an euchromatic locus, followed by H3K9me3 chromatin immunoprecipitation (ChIP) analysis. We found that fragments of var gene upstream regions nucleated HC efficiently, whereas fragments from the pfap2-g upstream region or from the mspdbl2 locus did not nucleate HC. Fragments from the beginning of the coding sequence (CDS) of pfap2-g nucleated HC with low efficiency, as evidenced by nucleation requiring long fragments of ∼2 Kb and occurring only in a fraction of the parasites. These results demonstrate that the primary DNA sequence is a main determinant of HC nucleation in P. falciparum . We also studied HC maintenance at the pfap2-g locus, which demonstrated that specific parts of the upstream region, different from the regions competent for HC nucleation, are required for maintenance. Together, our results provide initial insight into how HC is directed to specific loci and maintained in P. falciparum .

Abstract Dengue Virus (DENV) is a severe life-threatening virus to human, which is the major cause for dengue fever. However, the efficiency of traditional detection methods unable to meet the additional requirements in clinic practice, including the virus isolation method, ELISA, RT-PCR and qRT-PCR and so on. Therefore, a rapid, simple, and accurate diagnostic for DENV is highly desired. In the current study, we developed a novel method for universal DENV detection via introducing recombinase polymerase amplification (RPA) assay and Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR) and associated (Cas) protein 12a (CRISPR/Cas12a) system in one-pot, achieving the extremely sensitivity and specificity for DENV. The whole detection assay can be finished within 40 min without the requirement for sophisticated equipment. The limit of detection (LoD) was 91.7 copies per test. All the recombinant plasmid of these four serotypes of DENV (I to IV) were successfully identified by using present one-pot DENV universal RT-RPA CRISPR/Cas12a detection system. As for specificity, a total of 22 DENV positive samples were successfully identified, and no-cross reactions were observed in 4 other interferes nuclear acid samples. Moreover, we also established the universal DENV RT-RPA-CRISPR/Cas12a- lateral flow dipstick (LFD) platform and all the four serotypes of DENV (I to IV) were successfully identified, reaching the sensitivity of about 250 copies/test. Together, our present method not only provided an alternative approach for universal DENV detection but also gained a novel insight for other virus identification.

ABSTRACT CRISPR/Cas is a revolutionary technology for genome editing. Although hailed as a potential cure for a wide range of genetic disorders, CRISPR/Cas translation faces severe challenges due to unintended off-target editing. Predicting these off-targets are difficult and necessitates trade-offs between speed and sensitivity, and we show that some tools fail to recover even those they claim to be able to find Here, we develop the original concept of symbolic alignments to efficiently identify off-targets without sacrificing sensitivity. We also introduce data structures that allow near-instant alignment-free probabilistic ranking of guides based on their off-target counts. Implemented in the tool CHOPOFF, these innovations support mismatches, bulges and genomic sequence variation for personalized genomes while outperforming state-of-the-art methods in both speed and accuracy. Availability The CHOPOFF is available at https://github.com/JokingHero/CHOPOFF.jl

CRISPR-Cas enzymes must recognize a protospacer-adjacent motif (PAM) to edit a genomic site, significantly limiting the range of targetable sequences in a genome. Machine learning-based protein engineering provides a powerful solution to efficiently generate Cas protein variants tailored to recognize specific PAMs. Here, we present Protein2PAM, an evolution-informed deep learning model trained on a dataset of over 45,000 CRISPR-Cas PAMs. Protein2PAM rapidly and accurately predicts PAM specificity directly from Cas proteins across Type I, II, and V CRISPR-Cas systems. Using in silico deep mutational scanning, we demonstrate that the model can identify residues critical for PAM recognition in Cas9 without utilizing structural information. As a proof of concept for protein engineering, we employ Protein2PAM to computationally evolve Nme1Cas9, generating variants with broadened PAM recognition and up to a 50-fold increase in PAM cleavage rates compared to the wild-type under in vitro conditions. This work represents the first successful application of machine learning to achieve customization of Cas enzymes for alternate PAM recognition, paving the way for personalized genome editing.