Biology subjects

Xiao, R.

Publications and source records attributed to Xiao, R..

At least 19 recordsLinked to original sources

bioRxiv2026

Structural and genetic dissection of RNA-guided gene repression by TnpB-derived transcription factors

TnpB nucleases, the evolutionary progenitors of CRISPR-associated Cas12 enzymes, are transposon-encoded, RNA-guided endonucleases found throughout bacteria. Independent of the trajectory towards adaptive immunity, TnpB nucleases have also recurrently given rise to TnpB-like nuclease-dead repressors (TldRs), a family of programmable RNA-guided transcription factors, though the physiological roles of most TldR clades remain unclear. Recently, we identified a TldR clade associated with bacterial ABC transporter operons, but this clade has not been characterized in any native host, leaving the biological significance of its predicted regulatory function unknown. Here, we demonstrate direct in vivo repression of the oligopeptide permease (opp) binding protein OppA in Enterococcus faecalis, implicating TldR in shaping the substrate repertoire of bacterial peptide import machinery. Phylogenetic and comparative genomic analyses reveal that bacterial genomes typically encode multiple, structurally conserved but functionally diversified OppA paralogs, suggesting that TldR-mediated repression could enable selective tuning of transporter composition. To define the structural basis of this regulatory specificity, we used cryo-electron microscopy to capture an oppF-associated TldR in multiple functional states, revealing a conserved bilobed architecture and a TAM recognition mechanism inherited from TnpB ancestors. Together, these findings define the structural, genetic, and evolutionary basis of a widespread RNA-guided regulatory system domesticated from mobile genetic elements to tune peptide transport in bacteria.

microbiology↗

bioRxiv2026

idTAG enables programmable and physiologically faithful control of endogenous protein degradation

Rapid and precise depletion of endogenous proteins is essential for dissecting gene function, yet existing degron technologies often require direct modification of endogenous coding sequences, which can compromise protein expression and limit their applicability. Here, we develop idTAG, an inducible degron platform that decouples protein expression from protein degradation by integrating Tet-On 3G-mediated transcriptional control with dTAG-mediated degradation. Systematic characterization reveals that conventional degron knock-in frequently causes unintended reduction of target protein expression at the mRNA level, representing an underappreciated limitation of current approaches. In contrast, idTAG enables efficient generation of degron cell lines while maintaining physiological protein abundance and allows programmable control of degradation kinetics through independent regulation of protein synthesis and degradation. Applying idTAG to RNA-binding proteins, we demonstrate that acute depletion of FUS has minimal effects on global RNA polymerase II transcription, whereas acute loss of SRSF5 selectively disrupts transcription termination at a subset of genes. Thus, idTAG provides a versatile platform for physiological and temporally controlled interrogation of endogenous protein functions.

molecular biology↗

bioRxiv2026

Characterizing Individual and Population-Level Heterogeneity in Infant BMI Trajectories Using Flexible and Functional Modeling Approaches

Infant body mass index (BMI) follows a rapid and nonlinear trajectory, yet substantial inter-individual variation complicates accurate characterization of growth dynamics. Here we systematically compared individual- and group-based approaches for modeling longitudinal BMI trajectories in 2,114 healthy infants. Among linear spline, natural cubic spline and fractional polynomial mixed-effects models and SITAR, natural cubic splines provided the best fit while preserving individual variation in trajectory shape. Across all models, males reached their BMI peak earlier than females. To characterize population-level heterogeneity, we further compared latent class mixed models with functional principal component analysis (FPCA) followed by Gaussian mixture clustering. Whereas latent class modeling produced numerous small classes, FPCA identified three interpretable trajectory groups in both sexes, including a rare subgroup characterized by higher BMI and delayed or unestimable peak timing. Maternal gestational diabetes was associated with earlier BMI peak timing in females and was enriched in the rare female trajectory subgroup. Together, these results support combining flexible mixed-effects modeling with functional trajectory analysis to characterize both individual growth dynamics and population-level heterogeneity during infancy.

developmental biology↗

bioRxiv2026

Ablation of a maternal Cryptosporidium mRNA-binding protein results in sterile sporozoites

Infection with Cryptosporidium is a leading cause of diarrheal disease and early childhood mortality. This apicomplexan parasite undergoes asexual and sexual replication within the same host and recent studies have shown an intrinsic developmental program of obligate transition to male and female gametes and sex. While factors were identified that control male fate and development, how female gene expression is orchestrated remains largely unknown. Here we use the Cryptosporidium Single Cell Atlas to discover an RNA binding protein (F-RBP) as one of the earliest markers of female identity. Reporter parasites engineered based on this gene allowed us to calibrate transcriptional pseudotime against the real time of female development revealing a significant window of transcriptional fate ambiguity. While F-RBP is an early transcript, the protein persists throughout female development and into the zygote. Conditional ablation of the F-RBP gene showed it to be dispensable for sex determination and early female development in vitro. However, the gene is essential in vivo and its loss results in rapid cure. Cell biological experiments link this loss to the production of sterile oocysts which release sporozoites incapable of host cell invasion. F-RBP binds transcripts highly expressed in the female gamete enriched for a YBOX primary sequence motif and forms mRNA protein complexes in late females akin to processing or P bodies. We propose F-RBPs essential role to be in the regulation of long-term homeostasis of maternally inherited RNA required for sporozoite infectivity.

microbiology↗

bioRxiv2026

Dichloroacetate improves animal survival, growth, neuromuscular activity, mitochondrial stress and physiology, and elevated lactate in C. elegans pdha-1 and dld-1 RNAi models of pyruvate dehydrogenase complex deficiency (PDCD)

Pyruvate dehydrogenase complex (PDHc) deficiency (PDCD) is a primary mitochondrial disorder characterized by neurodevelopmental disability, altered intermediary metabolism and early mortality. Dichloroacetate (DCA), a pyruvate analogue, is a well-described PDHc activator that remains under clinical investigation for treatment of PDCD. Here, we studied the in vivo efficacy of a 5-point log concentration range of DCA on animal health and metabolism in C. elegans with feeding RNA interference (RNAi) expression knockdown of either PDHA-1 or DLD-1 homologues at graded degrees to model variable disease severity. These worm models recapitulate phenotypic features of PDCD observed in human patients, including reduced survival, delayed growth, locomotor impairment, and elevated lactate and/or pyruvate tissue levels. DCA treatment appeared well-tolerated, with no gross morphologic toxicity seen at doses up to 25 mM. Significantly improved health, survival, tissue lactate levels, and mitochondrial physiology were observed at 25 mM in pdha-1(RNAi) knockdown animals. DCA treatment in dld-1(RNAi) C. elegans models (undiluted, 1:20 dilution, and 1:100 dilution) showed significant therapeutic benefits on survival, neuromuscular function and metabolic phenotypes primarily in the moderate (1:20) and/or mild (1:100) dld-1(RNAi) deficiency strains, but not in full-dose dld-1(RNAi). Importantly, linear growth, neuromuscular activity, and mitochondrial physiology were significantly improved with DCA treatment even in the most severe dld-1(RNAi) undiluted model. Overall, preclinical modeling provides objective evidence of DCA therapeutic efficacy in C. elegans expression knockdown strains for two well-conserved homologues of PDHA1 and DLD that represent distinct genetic etiologies of PDHc deficiency, with demonstrated beneficial effects on survival, healthspan, tissue lactate, and mitochondrial physiology. These data further confirm that DCAs therapeutic effect correlates with PDHc disease phenotype severity in dld-1(RNAi) animals. SYNOPSIS: Dichloroacetate (DCA) treatment demonstrated significant preclinical beneficial effect on survival, neuromuscular function, linear growth, tissue lactate, and mitochondrial metabolism in two C. elegans models with variable degrees of pyruvate dehydrogenase complex (PDHc) deficiency (PDCD), providing confirmatory evidence to support its therapeutic potential in human PDCD patients.

cell biology↗

bioRxiv2026

In vivo gene disruption and homology-directed repair in muscles and muscle stem cells using CRISPR/Cas9

Programmable endonucleases such as CRISPR/Cas9 provide powerful tools to edit mammalian genomes by engaging cellular mechanisms of DNA double-strand break (DSB) repair. CRISPR-catalysed homology-directed repair (CRISPR-HDR), though generally less efficient than other modes of DNA repair, holds particular promise to enable precise sequence replacement by targeted insertion of a homologous DNA template1,2. While recent studies have reported appreciable levels of HDR in cardiomyocytes in vivo3, skeletal muscle myofibres have historically been considered refractory to HDR-mediated genome editing4. Furthermore, how repair outcomes differ across tissues after systemic delivery of CRISPR/Cas9 editors, whether precise HDR editing can be achieved in regenerative tissue stem cells, and how developmental timing influences accessibility to CRISPR-induced repair remain unclear. Here, we use an adeno-associated virus (AAV)-delivered in vivo GFP-to-BFP colour-switching reporter system (AAV-GFP-to-BFP) to examine in vivo CRISPR-HDR with cellular- and tissue-level resolution. We find that postnatal cardiac muscle, skeletal muscle, and muscle stem cells undergo templated HDR at different rates across discrete developmental stages in mice. While HDR-edited muscle stem cells and myofibres were readily detectable after in vivo editing in juvenile mice, editing in neonatal mice yielded more efficient HDR in cardiac tissue. Based on these results, we adapted the CRISPR-HDR approach to rescue the therapeutically relevant Dmd mutation in mdx mice, demonstrating recoding to the wild-type protein sequence in both skeletal and cardiac muscles. These results provide a framework for advancing donor-templated DNA repair in living postnatal animals, and reveal unexpected cellular, developmental, and disease-related constraints on precise, therapeutic in vivo gene correction.

cell biology↗

bioRxiv2026

A colorectal cancer organoid-CAF co-culture chip for drug screening and personalized therapy

The tumor microenvironment (TME) plays a critical role in cancer progression and therapeutic response, with cancer-associated fibroblasts (CAFs) being a key stromal component. Conventional tumor organoid models lack TME elements, and existing co-culture systems have limitations in recapitulating dynamic, multidimensional interactions. Here, we developed a novel dynamic co-culture chip (BAC) to better model the TME and investigate CAF-tumor cell crosstalk. Using this platform, we established a non-contact co-culture model of patient-derived colorectal cancer cells and CAFs. The resulting model closely recapitulated the morphological and molecular characteristics of the original patient tumors. Compared with tumor organoids cultured alone, the co-culture system exhibited significantly higher resistance to the clinically common chemotherapeutics 5-fluorouracil and oxaliplatin. Moreover, the presence of CAFs promoted tumor recurrence. Notably, drug responses in the co-culture model showed superior concordance with clinical outcomes relative to both organoid-only and animal models. Transcriptomic profiling under different culture conditions provided further insights into the mechanisms driving CAF-mediated interactions. These findings demonstrate that the BAC-based tumor organoid-CAF co-culture model serves as a more accurate platform for predicting drug responses, investigating TME-dependent mechanisms, and guiding personalized cancer therapy.

Cell Biology↗

bioRxiv2026

A hybrid framework integrating structural machine learning and 3D liver-on-chip assay for drug-induced liver injury prediction

Drug-induced liver injury (DILI) remains a major cause of clinical attrition and postmarketing withdrawal, but structure only DILI predictors are difficult to compare because public benchmarks are vulnerable to compound overlap, scaffold similarity and shared label provenance. We present OakuloidTM, an open DILI prediction framework that pairs a leakage audited structure based model with an optional iBAC 3D primary human hepatocyte IC50/Cmax confirmation signal. The structural model integrates gradient boosted descriptor backbones, fingerprint random forests and LivTox proxy-DILI features through a logistic meta learner. Its evaluation is designed as part of the contribution: internal DILIrank, strict external TDC, scaffold disjoint TDC and independent Geci provenance checks are reported with released per compound predictions. Oakuloid reaches AUROC 0.811 on the strict external TDC benchmark and remains competitive under scaffold and fully clean TDC filtering. A channel attribution ablation shows that the external benchmark lead is driven by descriptor based gradient boosted trees rather than by DILIPredictor derived proxy features, reducing a potential circularity concern. The wet lab IC50/Cmax signal is largely orthogonal to structure and supports a confirmation mode that shifts the internal operating point toward higher specificity without claiming a universal AUROC gain. Oakuloid is released with code, model artifacts, calibration analysis, a 122 compound wet lab benchmark and a model card under the Apache License 2.0, supporting reproducible DILI screening and benchmark auditing.

biochemistry↗

bioRxiv2026

Application of a High-Biomimetic Tumor Organoid-CAF Co-Culture Model for the Efficacy Evaluation of CAR-T Drugs

The tumor microenvironment (TME) is a complex ecosystem composed of tumor cells, cancer-associated fibroblasts (CAFs), immune suppressive cells, and the extracellular matrix (ECM), playing a crucial role in tumor development and CAR-T cell therapy efficacy. CAR-T therapy has shown promise in hematological malignancies but faces challenges in solid tumors due to the TMEs ability to suppress CAR-T cell infiltration, proliferation, and cytotoxicity. Traditional drug evaluation models, such as 2D cell cultures and animal models, have significant limitations due to oversimplification of the in vivo environment or physiological differences between species. Organoid models offer a more biomimetic approach but often fail to fully recapitulate the TMEs complexity and heterogeneity. Our research developed a tumor organoid and CAF co-culture model using the IBAC co-culture chip, demonstrating that CAFs significantly impact CAR-T cell therapy efficacy by forming physical (e.g., fibronectin) and chemical (e.g., IL-10) barriers that prevent CAR-T cell infiltration and cytotoxicity. This model provides a high-biomimetic platform for investigating the TMEs effects on CAR-T therapy and highlights the importance of incorporating a comprehensive stromal component into in vitro models to enhance their predictive power for cancer treatment.

cell biology↗

bioRxiv2026

Reconstructing multi-scale tissue spatial architecture from single-cell RNA-seq with REMAP

Understanding spatial organization of cells is critical for deciphering tissue function and disease. Single-cell RNA-sequencing (scRNA-seq) profiles transcriptomes at scale but loses spatial context, while spatial transcriptomics (ST) preserves spatial information but is constrained by cost and gene coverage. Here, we present REMAP, a deep learning framework that integrates gene expression with neighborhood-level gene-gene covariance to reconstruct multi-scale spatial organization of scRNA-seq data using one or multiple ST references. Across 2D and 3D mouse brain, human fetal cortex, and seven human cancer types, REMAP consistently outperformed existing approaches. Applied to a human multiple sclerosis atlas, REMAP resolved microglial neighborhood heterogeneity, and identified a rare pro-inflammatory microglia-astrocyte subpopulation. Across diverse cancers, REMAP recovered conserved spatially-defined cancer-associated fibroblast subtypes with known prognostic significance. By transforming cost-efficient single-cell datasets into spatially interpretable tissue maps, REMAP enables spatial hypothesis generation, microenvironment discovery, and population-scale inference of conserved and perturbed architectural principles in human disease.

genomics↗

bioRxiv2026

Cognate amino acid therapies provide preclinical benefit in 19 C. elegans models of ARS2 deficiency

Mitochondrial aminoacyl-tRNA synthetases (mt-ARS) are essential mitochondrial translation machinery components that catalyze mitochondrial transfer RNAs (tRNAs) charging with their cognate amino acid. Although mt-ARS have a common biochemical function, patients with mt-ARS pathogenic variants commonly develop neurological disorders with varying phenotypes, severity spectrum, and age of onset. Cognate amino acid supplementation has shown reported benefits in select cases of both mt-ARS (ARS2) and cytosolic (ARS1) deficiencies, although the safety and potential benefits of this candidate therapy approach across the full spectrum of mt-ARS disorders remain unclear. Here, C. elegans models were systematically generated for all 19 mitochondrial mt-ARS genes by feeding RNAi knockdown for one or two generations. mt-ARS deficient animals at baseline and upon cognate amino acid treatment were studied at the level of linear growth, neuromuscular activity, lifespan, mitochondrial physiology, and fertility. Results demonstrated that cognate amino acid treatment in a dose-dependent fashion consistently improved worm linear growth and neuromuscular activity, and reduced mitochondrial unfolded protein response stress, in all 19 knockdown models. It further rescued impaired fertility of hars-1 and fars-2 knockdown strains. Collectively, these preclinical studies provide compelling evidence to warrant future cognate amino acid treatment study in rigorous clinical trials spanning all human mt-ARS deficiencies.

physiology↗

bioRxiv2025

Diverse infections transcriptionally reprogram the intestinal epithelium and epithelial-immune cell interactions

The distal small intestine plays vital roles in host physiology by regulating nutrient and fluid homeostasis. Despite being impacted in Crohns disease and a major target for a range of infections, we know relatively little about the complexity of cellular responses and cell-cell communication in the ileum during infection. Single cell and spatial transcriptomics have emerged as powerful technologies to study tissue heterogeneity in the gut, but these tools have focused on the large intestine, in part due to the accessibility of this tissue for biopsies and its importance in cancer. Here we present GutPath, an atlas of over 500,000 single cells with RNA and protein expression profiles for 91 cell states in the ileum across diverse infectious archetypes. We show that GutPath accurately captures established immune responses to infection while revealing pathogen-specific responses in enterocytes. To highlight the discovery potential of this atlas, we identify a novel enterocyte cell state present during Yersinia pseudotuberculosis infection that is spatially linked to bacterial load and tissue pathology. GutPath establishes a much-needed resource for the immunology community that will accelerate the study of the transcriptional diversity of cellular landscapes in the small intestine.

immunology↗

bioRxiv2025

Decoding the Glycan Signature: Unraveling N-Glycosylation Alterations in Glycogen Storage Disease Ia and Ib

Glycogen storage disease (GSD) types Ia and Ib are rare inherited metabolic disorders caused by pathogenic variants in G6PC or SLC37A4, respectively. These defects disrupt glucose homeostasis and may affect protein glycosylation. We systematically profiled sera N-glycomes from retrospectively collected GSD Ia (n=17), GSD Ib (n=8), and control (n=21) samples. Derived traits analyses revealed distinct, subtype-specific, and shared glycomic alterations, including shifts from 2,3-to 2,6-sialylation in both subtypes. GSD Ia showed enhanced branching and reduced fucosylation, whereas GSD Ib displayed elevated fucosylation, bisection, and reduced branching. In GSD Ia patients with hepatocellular adenoma/carcinoma (HCA/HCC), further enrichment of oligomannosidic and 2,3-sialylation was observed. Several individual N-glycans showed strong discriminatory performance, supporting their potential as biomarkers for GSD I subtyping and HCA/HCC surveillance. This study provides the first comprehensive characterization of systemic N-glycans in GSD Ia and Ib, revealing glycomic remodeling as a potential biomarker of disease subtypes and tumor progression. Take-home message (synopsis) of the articleSerum/plasma N-glycomic profiling reveals distinct glycosylation signatures in GSD Ia and GSD Ib, including tumor-associated shifts in GSD Ia, highlighting novel biomarkers for disease subtyping and surveillance of hepatic complications.

biochemistry↗

bioRxiv2025

Widespread genomic heterogeneity at the type II NAD(P)H dehydrogenase locus predisposes Cryptosporidium to clofazimine resistance

The parasite Cryptosporidium is a leading cause of life-threatening diarrheal disease, and effective treatment is not available. The discovery of potent anti-Cryptosporidium activity of clofazimine, offered the opportunity to repurpose a drug already used to treat leprosy and tuberculosis. However, clofazimine failed in a human trial, which was attributed to poor bioavailability. Here, we observed differential susceptibility among parasite isolates which we exploit to map the mode of action to type II NADH dehydrogenase (NDH2) in an unbiased genetic cross. Targeted genetic ablation of NDH2 resulted in profound clofazimine resistance, and biochemical studies demonstrated NDH2 mediated electron transfer to clofazimine. Through genomic analyses we uncovered heterogeneity at the NDH2 locus for C. parvum and C. hominis and widespread carriage of a conserved attenuated allele across multiple continents. This heterogeneity allows parasites genomically linked through frequent sexual recombination to adjust to changing NDH2 requirements and predisposes Cryptosporidium to evade clofazimine treatment.

microbiology↗

bioRxiv2025

Predicting Risk of Transfusion-Induced Red Blood Cell Alloimmunization Using Statistical and Machine Learning Approaches in the Recipient Epidemiology and Donor Evaluation Study (REDS-III) Database

Red blood cell (RBC) alloimmunization is a common complication from blood transfusion, often resulting in accelerated donor RBC destruction. Patients show substantial variation in their predisposition to RBC alloimmunization. Previous studies have identified several risk factors, but to our knowledge, there have been no studies that predict risk of RBC alloimmunization by modeling multiple potential risk factors simultaneously. Here, our study represents the first attempt to build prediction models for RBC alloimmunization using the large sample size and rich set of potential risk factors available in the Recipient Epidemiology and Donor Evaluation Study (REDS-III) recipient database. To develop the prediction models, we applied a range of approaches, including traditional statistical models (logistic regression), and modern machine learning (including gradient boosting, random forest, and XGBoost), deep learning (the multilayer perceptron method), and large language models (LLM). XGBoost demonstrates the overall best performance among models providing uncertainty quantification (F1= 0.672 and area under the ROC curve [AUC-ROC]=0.752). LLMs show promising results with the best F1 scores (0.677-0.687), though they are limited by their inability to provide uncertainty estimates, they hold the potential for use as an interactive chatbot for patients. Although there is ample room for performance improvement, limiting the analysis to patients predicted with >80% confidence by XGBoost resulted in a substantially improved AUC-ROC of 0.919, which can be of potential clinical significance.

immunology↗

bioRxiv2025

Proteomics profiling of serum and liver in GSD Ia and Ib patients: insights into complication mechanisms and circulation biomarkers

BackgroundGlycogen Storage Disease (GSD) Types Ia and Ib are rare metabolic diseases caused by gene variants in G6PC1 and SLC37A4, respectively. Although life-threatening fasting hypoglycemia can be controlled by a strict diet, patients often suffer from multiple metabolic abnormalities and severe long-term complications. However, the underlying mechanisms remain incompletely understood, and the lack of effective monitoring biomarkers makes it a challenge to treat patients. Therefore, the aims of this study are to investigate the pathological mechanisms of the disease and disease complications in GSD I and identify potential protein biomarkers. MethodsIn this study, we employed comprehensive untargeted proteomics on stored samples: 26 serum or plasma samples from 18 GSD Ia and 8 GSD Ib patients with 21 matched control sera, complemented by 4 liver samples from 2 GSD Ia patients who received liver transplantation (from the one patient with hepatocellular carcinoma we obtained tissue from both the carcinoma tissue and the adjacent non-carcinoma tissue), and 1 from a GSD Ib patient, compared to 10 donor liver samples. ResultsWe identified a total of 415 proteins in our analyses. Pathway analysis of the differentially regulated proteins revealed distinct changes in serum/plasma of GSD Ia and Ib. The coagulation pathway was the most significantly changed biological process in the GSD Ia patients. Immune response-associated proteins, especially a large number of immunoglobulins, were increased in GSD Ib specifically. Proteins related to liver injury, cholesterol, and amyloidosis were altered in two subtypes, though more pronounced in GSD Ia. Potential biomarkers with significant alterations both in the circulation as well as in the liver tissue were identified specifically for monitoring GSD I subtypes and prognosing liver deterioration, namely GSD Ia (COL163 and PROC), GSD Ib (F11 and CD163), and hepatocellular carcinoma (HCC) in GSD Ia patients (ALDOB and CFHR5). ConclusionsThese findings provide new insights into the differences between the two GSD I subtypes and the pathogenesis of GSD I-related complications, as well as highlighting the potential of protein circulating biomarkers for monitoring complication progression in GSD I and assessing HCC risk in GSD Ia patients. Trial registrationNot applicable. A concise 1 sentence take-home message (synopsis) of the articleThis comprehensive in-depth proteomics study on blood and liver GSD Ia and Ib patient samples provided novel insights into understanding of the disease subtypes as well as the the pathogenesis of GSD I-related complications, such as HCC risk in GSD Ia patients and identified potential biomarkers for the disease subtypes and complications.

systems biology↗

bioRxiv2025

Human wastewater contamination drives the emergence of novel multidrug resistant bacteria in the Galapagos marine ecosystem.

Since the publication of Charles Darwins On the Origin of Species in 1859, the Galapagos archipelago has become emblematic of natural selection and evolution. While the lens of evolution in the Galapagos has traditionally focused on iconic megafauna, including finches, marine iguanas, and giant tortoises, the marine environment is also home to diverse microbial ecosystems that are constantly evolving under selective pressure from environmental factors such as human activity. We focused on the second most populated island within the archipelago -- San Cristobal -- an island that has experienced rapid urbanization and intense international tourism pressure. Using a lab-free approach, we spatiotemporally mapped wastewater contamination around San Cristobal. On-site metagenomic sequencing revealed a stark shift in genera and a higher count of antimicrobial resistance genes at wastewater-associated sites. Over 40% of lactose-fermenting Enterobacteriaceae isolates collected from sewage and wastewater outfall exhibited multidrug resistance (MDR). Long-read sequencing and de novo assembly of bacterial genomes and plasmids from MDR Escherichia coli revealed frequent and rapid reassortment of antimicrobial resistance genes on plasmids, generating unique antimicrobial resistance profiles. This study not only provides a framework for conducting antimicrobial resistance research in low-resource settings but also underscores the impact of wastewater contamination on the environmental AMR landscape and highlights potential threats to human and animal health.

microbiology↗

bioRxiv2025

Exapted CRISPR-Cas12f homologs drive RNA-guided transcription

Bacterial transcription initiation is a tightly regulated process that canonically relies on sequence-specific promoter recognition by dedicated sigma ({sigma}) factors, leading to functional DNA engagement by RNA polymerase (RNAP)1. Although the seven {sigma} factors in E. coli have been extensively characterized2, Bacteroidetes species encode dozens of specialized, extracytoplasmic function {sigma} factors ({sigma}E) whose precise roles are unknown, pointing to additional layers of regulatory potential3. Here we uncover an unprecedented mechanism of RNA-guided gene activation involving the coordinated action of {sigma}E factor in complex with nuclease-dead Cas12f (dCas12f). We screened a large set of genetically-linked dCas12f and {sigma}E homologs in E. coli using RIP-seq and ChIP-seq experiments, revealing systems that exhibited robust guide RNA enrichment and DNA target binding with a minimal 5'-G target-adjacent motif (TAM). Recruitment of {sigma}E was dependent on dCas12f and guide RNA (gRNA), suggesting direct protein-protein interactions, and co-expression experiments demonstrated that the dCas12f-gRNA-{sigma}E ternary complex was competent for programmable recruitment of the RNAP holoenzyme. Remarkably, dCas12f-RNA-{sigma}E complexes drove potent gene expression in the absence of any requisite promoter motifs, with de novo transcription start sites defined exclusively by the relative distance from the dCas12f-mediated R-loop. Our findings highlight a new paradigm of RNA-guided transcription (RGT) that embodies natural features reminiscent of CRISPRa technology developed by humans4,5.

molecular biology↗