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Today, 1:21 AM
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Metabolic engineering employs microbial cell factories to produce high-value products from low-cost feedstocks. Designing, optimizing, and evaluating biosynthetic pathways in microbial cell factories is essential, yet these processes remain time- and labor-intensive. Biosensors help metabolic engineers address this challenge by converting target metabolite concentrations into observable outputs, enabling efficient assessment of microbial production. Whole-cell biosensors, which operate within living microorganisms, and cell-free biosensors, which function independently of cell growth using transcription–translation machinery, have contributed to microbial biosynthesis optimization through distinct approaches. This review summarizes recent advances in biosensor-driven metabolic engineering facilitated by whole-cell and cell-free biosensors.
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Today, 1:15 AM
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Escherichia coli Nissle 1917 (EcN) is a well-characterized Gram-negative probiotic distinguished by its unique, strain-specific physiology. Genome-scale metabolic models (GEMs) are powerful tools for elucidating metabolic traits and predicting genotype-phenotype relationships. Although several EcN GEMs have been published, none have explicitly represented its probiotic physiology. Here, we present a manually curated GEM of EcN that, for the first time, incorporates the energetic costs associated with its cryptic plasmids. Inclusion of a plasmid-specific module improved biomass yield predictions and overall model accuracy, providing a more physiologically realistic representation of EcN metabolism. Using COBRA methodologies and possibilistic metabolic flux analysis, this model and previous EcN reconstructions were systematically compared to evaluate the trade-off between model complexity and predictive performance. The analysis revealed that increased structural detail does not necessarily enhance quantitative accuracy and that predictive reliability depends on both computational methodology and model context. Metabolomic profiling under gut-like anaerobic conditions further showed that EcN exhibits a distinctive metabolic phenotype, characterized by elevated amino acid consumption and enhanced short-chain fatty acid production. These findings highlight the unique probiotic physiology of EcN and demonstrate the utility of metabolic modeling for reproducing and exploring such traits. Overall, this study provides a quantitatively reliable and physiologically relevant framework for modeling E. coli Nissle 1917 and related commensal bacteria, supporting advances in probiotic engineering, synthetic biology, and bioprocess design.
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Today, 1:03 AM
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Heme is an essential molecule required for critical biochemical processes in most vertebrates and bacteria. During infections, vertebrate hosts sequester heme away from invading pathogens, a process known as nutritional immunity, driving bacteria to evolve diverse mechanisms to evade this immunity and cause diseases. This review explores the functions of heme at the host–pathogen interface. We discuss the multifaceted roles of heme in bacterial pathogenesis and the potential for heme-targeting antimicrobial therapies. Beyond serving as a source of iron in the host environment, where iron bioavailability is limited, heme contributes to the structural stability and enzymatic functions of hemoproteins. We examine the regulatory mechanisms governing bacterial heme homeostasis in the host environment including sensing, detoxification, acquisition, utilization, and degradation pathways. Understanding how heme influences bacterial survival and virulence can lead to the development of novel therapeutic strategies that target the various essential and conserved mechanisms of heme homeostasis in bacterial pathogens. Given the rising challenge of antibiotic resistance, heme-based therapeutic interventions are promising strategies for the treatment of bacterial infections.
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Today, 12:53 AM
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Cell separation and purification techniques are crucial in modern biomedical research and clinical applications. Endogenous RNA, which reflects a cell’s genetic and physiological characteristics, provides a new way to determine cell identity at the transcriptional level. Here, we utilize RNA editing technology based on adenosine deaminase acting on RNA (ADAR) to design a dual-switch genetic circuit capable of detecting unique RNA biomarkers for cell separation and purification. The circuit incorporates a kill switch driven by barnase, which selectively eliminates nontarget cells, and a recognition switch, precisely regulated by ADAR editing, to control the expression of the MS2 bacteriophage coat protein (MCP) and barstar that inhibit barnase expression and activity. By temporally regulating these switches, our approach achieves purification efficiencies of 93–97% for HepG2, A549, and HER2-overexpressing SK-BR-3 cells in mixed populations, surpassing traditional methods. Furthermore, utilizing standard cell culture protocols, our approach simplifies cell identification and purification without interfering with the normal gene expression of target cells, ensuring robustness and safety. We believe that this ADAR-assisted genetic circuit holds great potential for applications in cell therapy and biopharmaceutical manufacturing.
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Today, 12:21 AM
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Pseudomonas putida is a gram-negative bacterial species increasingly utilized in biotechnology due to its robust growth, ability to degrade aromatic compounds, solvent tolerance, and genetic tractability. In this study, we report a comprehensive multi-strain analysis of 164 P. putida strains. We performed whole-genome sequencing and hybrid assembly for 40 strains, contributing a ~8% increase to the available genomic data for P. putida. Furthermore, high-throughput phenotypic profiling using the Biolog phenotype microarray system for 24 strains on 190 unique carbon sources, along with 15 aromatic compounds not present on Biolog plates, yielded 4,920 unique strain-phenotype measurements. These data were leveraged to curate GEMs for 24 representative strains, including a refined model for strain KT2440, which comprised 1,480 genes and 2,191 metabolites, achieving a prediction accuracy of 91.2% in carbon utilization. Systematic comparison of genomes and GEMs revealed both conserved core pathways and significant allelic and functional divergence across strains, highlighting strain-specific variation in aromatic degradation. While pathways for protocatechuate and phenylacetate degradation were widely conserved, metabolic capabilities for compounds such as ferulate, phenol, and cresols varied markedly, suggesting adaptation to distinct ecological niches. Alleleome analysis of enzymes such as PcaI and PcaJ revealed distinct, functionally similar clades, indicating possible convergent evolution or horizontal gene transfer. These results provide computable resources and models for selecting P. putida strains with desired traits for biomanufacturing and bioremediation and offer insights into the evolution and phylogeny of the P. putida species.
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November 18, 11:47 PM
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RNA’s regulatory and catalytic roles affect gene expression, with circular RNAs (circRNAs) emerging as a unique subclass with broad therapeutic potential. Among circRNA production methods, ribozyme-mediated circularization, especially through group I intron-based systems such as the T4 td-PIE (where PIE indicates permuted intron–exon), offers efficient in vitro synthesis. However, detailed structural insights of the T4 td intron are limited, particularly regarding circularization mechanisms. Here we use cryo-electron microscopy to resolve high-resolution structures of both linear and circular T4 td intron forms. Comparative structural analysis reveals key conformational shifts in the catalytic core, including P1ext domain loss and realignment of critical base pairs in the circular form. Additionally, we identify critical sites and interactions optimizing RNA circularization. Structure-guided mutations enhance circularization efficiency, as validated in the T4 td-PIE system and benchmarked against alternative platforms. These findings enhance our understanding of RNA circularization mechanisms and inform optimizations for large-scale circRNA production, with important implications for RNA-based therapeutics and synthetic biology. The T4 td-PIE system is a promising platform for circular RNA synthesis, but the dynamic mechanism of the T4 td group I intron during circularization remains unclear. Now, cryo-EM structures of both the linear and circular forms of the T4 td intron are solved, revealing key conformational shifts essential for RNA circularization.
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November 18, 11:17 PM
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Pseudomonas putida strains are prized biocatalysts, renowned for their versatility in degrading diverse chemicals, tolerating organic solvents, and withstanding environmental stressors. Central to their adaptive success is the precise regulation of primary carbon metabolism, with HexR emerging as a key regulator. While previous research has explored HexR binding through in vitro assays and comparative transcriptomics, the in vivo binding sites and genome-scale regulon remain uncharted. This study presents a comparative analysis of P. putida KT2440, comparing expression profiles of wild-type and hexR deletion mutant strains across distinct growth substrates: glucose (glycolytic), acetate, succinate (gluconeogenic), and glycerol (inducing both metabolic responses). Our findings revealed an extensive regulatory role of HexR in acetate metabolism, simultaneously suppressing the glycolytic pathway while enhancing pyruvate metabolism, glyoxylate shunt, and gluconeogenesis to support growth. Integration of ChIP-exo data identified 29 HexR binding locations in the KT2440 strain grown on acetate, directly regulating 75 genes. Complementing these findings, model-based in silico simulations provided contextual insight into metabolic flux states, deepening our understanding of carbon metabolism orchestrated by this transcription factor. This study thus offers a holistic view of the HexR regulatory landscape, highlighting its relevance in P. putida KT2440 metabolism and laying the groundwork for future metabolic engineering efforts in this versatile organism.
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November 18, 11:12 PM
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Since 2007, the SILVA database (https://www.arb-silva.de/) has served as a comprehensive resource providing quality-checked, aligned, and classified ribosomal RNA sequences for the scientific community worldwide. The database provides manually curated taxonomic classifications for the three domains of life, standardized reference datasets, and tools for classifying microbial diversity. SILVA’s impact has been recognized in its designation as ELIXIR Core Data Resource and Global Core Biodata Resource. The integration of SILVA into the DSMZ Digital Diversity consortium (D3; https://hub.dsmz.de) in 2023 marked a significant update, ensuring the long-term sustainability and continued development of the resource. Apart from moving to a new hosting institution, this integration facilitates data interoperability and standardization among SILVA, LPSN, StrainInfo, and other D3 databases. New developments this year include a redesigned website consistent with the DSMZ corporate identity, DOI assignments for all SILVA releases to enhance data citation and support the FAIR data principles, and the provisioning of QIIME2, DADA2, and KRAKEN2 classifiers. Additionally, the EukMap application has been redeveloped as a curation and visualization tool called TaxMap. In anticipation of the next data release, we outline recent developments and the current state of the database, its relation with other D3 resources, and its future directions.
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November 18, 10:58 PM
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Specialized metabolites produced by microorganisms are frequently used in the development of drugs and crop protection agents. Genome mining is a widely used approach to access this potential, and antiSMASH is often the tool of choice for this task. Here, we present version 5 of the antiSMASH database, with biosynthetic gene cluster predictions provided by antiSMASH 8.1 available in an easy-to-use web interface. Version 5 of the database contains 833 archaeal, 54 800 bacterial, and 421 fungal genomes and is available from https://antismash-db.secondarymetabolites.org/.
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November 18, 10:27 PM
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We conducted a clinical trial (ClinicalTrials.gov: NCT06165354; 8/12/2023) to evaluate the effectiveness of the vaginal-spray probiotic LiveSpo X-Secret, containing Bacillus subtilis, B. clausii, and B. coagulans spores (≥1 billion CFU/mL). A total of 120 women were randomized equally into Control and X-Secret groups at Bac Ninh CDC. Outcomes were assessed at day 7 (end of standard treatment) for symptom resolution and day 28 (21 days post-treatment) for recurrence. Both Per-Protocol and Intention-to-Treat analyses were performed to assess efficacy and account for attrition.
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November 18, 10:18 PM
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One CRISPR-Cas enzyme’s recognized protospacer adjacent motif (PAM) profile always shows intrinsic differences between assays with different working environments, such as in vitro, in bacterial cells, or in mammalian cells. The developed methods in mammalian cells are technically complex and not readily amenable to be broadly adopted, highlighting the urgent need for a well-established PAM-determining method in mammalian cells. In this study, we construct a rapid, simple, and accurate method for determining the PAM recognition profile of CRISPR-Cas nucleases in mammalian cells. The developed method is termed PAM-readID, PAM REcognition-profile-determining Achieved by Double-stranded oligodeoxynucleotides Integration in DNA double-stranded breaks. Using PAM-readID, the PAM recognition profiles of SaCas9, SaHyCas9, Nme1Cas9, SpCas9, SpG, SpRY, and AsCas12a in mammalian cells are well produced. An accurate PAM preference for SpCas9 can be identified by analysis with extremely low sequence depth (500 reads). PAM-readID can also define a PAM recognition profile of Cas9 based on Sanger sequencing with a significantly lower cost of time and price than that of high-throughput sequencing. We present an easy-to-use method for comprehensively revealing functional PAM of CRISPR-Cas nucleases in mammalian cells, which can contribute towards accelerating the advancement of exploiting novel genome editing nucleases. Rapid, simple, and accurate PAM determination assay in mammalian cells facilitates the advancement of CRISPR/Cas nucleases, especially for gene therapy and medical research.
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November 18, 10:00 PM
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Hydrogen bonds are fundamental chemical interactions that stabilize protein structures, particularly in β sheets, enabling resistance to mechanical stress and environmental extremes. Here, inspired by natural mechanostable proteins with shearing hydrogen bonds, such as titin and silk fibroin, we de novo designed superstable proteins by maximizing hydrogen-bond networks within force-bearing β strands. Using a computational framework combining artificial intelligence-guided structure and sequence design with all-atom molecular dynamics MD simulations, we systematically expanded protein architecture, increasing the number of backbone hydrogen bonds from 4 to 33. The resulting proteins exhibited unfolding forces exceeding 1,000 pN, about 400% stronger than the natural titin immunoglobulin domain, and retained structural integrity after exposure to 150 °C. This molecular-level stability translated directly to macroscopic properties, as demonstrated by the formation of thermally stable hydrogels. Our work introduces a scalable and efficient computational strategy for engineering robust proteins, offering a generalizable approach for the rational design of resilient protein systems for extreme environments. Nature contains a variety of mechanostable proteins, which all bear extensive hydrogen-bond networks within their β-sheet architectures to sustain high stability under stress. Now through integrating AI-guided design alongside MD simulations and by maximizing hydrogen bonds in β strands, SuperMyo proteins with nanonewton mechanical stability and thermal resilience up to 150 °C were created.
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November 18, 5:16 PM
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Antibiotic 2,4-diacetylphloroglucinol (DAPG) is produced by many plant-associated beneficial bacteria of the Pseudomonas genus and plays an important role in plant disease control due to its broad antimicrobial activity against different pathogens. DAPG biosynthesis is activated by the conserved GacA/GacS two-component regulatory system. Here, we report that a ΔgacA mutant of Pseudomonas protegens Pf-5, lacking both DAPG production and pathogen inhibition in culture, controlled pea Aphanomyces root rot in a DAPG-dependent manner in the greenhouse. DAPG production of the ΔgacA mutant could be restored by exogenous phloroglucinol (PG), the first intermediate in DAPG biosynthesis, by culturing the ΔgacA mutant with either PG or PG-producing bacteria. We identified a new Gac-dependent promoter of phlD. Gene expression assays demonstrated that GacA is required to activate the phlD promoter. In vitro binding assays showed that the RNA-binding protein RsmE bound directly to the leader mRNA of phlA, another DAPG biosynthetic gene converting PG into DAPG, indicating that GacA regulates phlA expression post-transcriptionally. No detectable binding activity was observed between RsmE and the phlD leader mRNA. These results show that GacA regulates DAPG biosynthesis at multiple steps via different mechanisms and elucidate a novel layer of Gac-Rsm regulation in secondary metabolism. Targeted PG supplementation and/or partner microbe interactions may help to enhance the disease control efficacy and stability of the DAPG-producing bacteria.
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Today, 1:19 AM
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Filamentous cyanobacteria of the Nostocaceae family can differentiate into multicellular forms to adapt to environmental stresses, and members can establish symbiosis with various embryophytes. Representative laboratory strains are typically grown under continuous light to maintain stable metabolic conditions; however, this departure from a natural diel cycle can result in extended stress. Early genomic examination of Nostoc punctiforme suggests the genetic potential for a circadian clock, but we lack insight into global cellular dynamics through the natural diel cycle for this model organism. Here, we comprehensively assess changes in expression of core cellular processes and the mobilome of accessory genetic elements during diel growth of N. punctiforme PCC 73102. The primary transcriptome confirmed that multicellular cyanobacteria precisely coordinate photosynthesis and carbon assimilation for cell division during the day, while control of DNA recombination and repair appeared to be sequestered to darkness. Moreover, we expanded the known repertoire of light-sensing proteins to uncover a putative regulator of circadian rhythm that itself exhibits striking oscillation between day-night expression. This was in sharp contrast to the arrhythmic pattern observed for a homolog of the canonical circadian input kinase in unicellular cyanobacteria. Looking beyond cellular coordination of diel growth, we uncovered dynamic mobile elements and, notably, targeted hypermutation by retroelements that are likely maintained for conflict mitigation, which is crucial for a multicellular lifestyle.
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Today, 1:11 AM
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Agrobacterium-mediated transformation (AMT) is the primary means of genetic engineering in plants and many fungi, but the factors that control transformation outcomes - efficiency, transgene insertion number, and transgene integrity - remain poorly characterized. Although transformation outcomes dictate an event's potential utility in both industrial and academic contexts, AMT remains largely unoptimized for these metrics. Here, we systematically analyze the impact of the transgene-harboring binary vector on transformation outcomes across plant and fungal species. Through a comparison of different plasmid origin of replication (ORI) families and engineered copy number variants, our results reveal that the ORI family - not plasmid copy number - dictates T-DNA insertion number, backbone inclusion, and transformation efficiency, while plasmid copy-number tuning alters efficiency without changing ORI family-specific signatures. Independent of plasmid copy number across kingdoms, the most widely used pVS1 ORI-based vectors (e.g. pCambia) result in significantly more insertions per transformant and high levels of transgene silencing compared to the less-utilized pSa ORI family, which enriches for more uniform single insertion events. Furthermore, we demonstrate that ORI-dependent transformation outcomes in yeast predictably reflect those in Arabidopsis. Together, these results lay the foundation for future binary vector design aimed at achieving more predictable, controllable, and optimized transformation outcomes across diverse eukaryotic hosts.
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Today, 12:58 AM
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Iron is a critical micronutrient for both plants and humans, yet its declining availability across agricultural systems threatens global food security and health. Biofortification of food crops has emerged as a promising strategy to combat iron deficiency and anemia, leveraging both crop breeding and microbiome-based approaches to enhance iron mobilization and uptake. Advances in plant and bacterial synthetic biology could enable the precise programming of iron homeostasis and acquisition mechanisms, offering tailored solutions across diverse species and environments. Here, we outline key biomolecules, genes, and biosynthetic and transport pathways that represent underexplored synthetic biology targets for improving crop iron acquisition. We highlight opportunities to tune expression strength, tissue specificity, and cross-host pathway transfer to enhance chelation- and reduction-mediated solubilization of soil iron and augment plant uptake. Finally, we emphasize the broader importance of developing plant–microbe–metal actuators as modular components in genetic circuit design and discuss how their deployment across diverse plant and microbial chassis could accelerate agricultural biofortification and improve global nutrition.
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Today, 12:24 AM
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Omics technologies can uncover the complex regulatory mechanisms of living systems at multiple levels, including genes, transcripts, proteins, metabolites and immune networks. They also provide an integrative framework to study how cells interact with their environment. In materiobiology, cellular responses to materials involve diverse processes. This review summarizes the applications of single-cell transcriptomics, transcriptomics, RNomics, genomics, proteomics, metabolomics, lipidomics, glycomics and immunomics in materiobiology. We highlight how these approaches reveal cell heterogeneity, transcriptional and epigenetic regulation, genetic determinants, protein and metabolic pathways, lipid and glycan remodeling and immune networks in the context of biomaterial interactions. In addition, we discuss how multi-omics strategies support the construction of bone organoids, which serve as physiologically relevant models to investigate bone development, disease mechanisms and material-driven repair. Together, these advances provide a theoretical foundation and methodology for the rational design of next-generation biomaterials with improved functionality and precision in regenerative medicine. This review outlines how multi-omics technologies drive materiobiology, bridging molecular insights with material innovation for precision and regenerative medicine.
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November 18, 11:51 PM
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Degeneracy in the genetic code has been shown to play a major role in yeast mRNA stability; differences in optimality (charged tRNA supply vs demand) among synonymous codons were revealed as a determinant of mRNA decay rates. However, whether and how much this mechanism determines mRNA decay rates in plants is unsettled. Furthermore, whether factors other than charged tRNA abundance influence codon optimality remains unexplored. Here, biased codon usage in Arabidopsis correlated with mRNA decay rates. A codon-optimality model of mRNA decay rate based on codon frequencies was tested using synonymously recoded genes. mRNA decay rates of these alleles in transgenic plants was consistent with the model predictions. Arabidopsis appears to use the same mechanism for sensing low optimality codons as yeast and humans because the N-terminal sensor domain of NOT3 is conserved. However, decay rates were also affected by codon context. Neighboring codons adjacent nucleotides consistently shifted codon correlations with decay rate in Arabidopsis, which was also observed in other published datasets revealing an influence of codon sequence on translation that is independent of charged tRNA concentrations. Codons frequencies explained 21% of decay rate variance, suggesting codon optimality-mediated decay is one of multiple mechanisms that determine decay rates in plants. Our study also found codon context as an additional factor that affects mRNA stability and establishes a paradigm of selection among synonymous codons decoded through wobble base pairing.
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November 18, 11:37 PM
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Google DeepMind is throwing its resources at several problems for which it thinks AI could speed development, and which could have “transformative impact”, says Kohli. These include weather forecasting5 and nuclear fusion, which has the potential to become a clean, abundant energy source. The company picks projects through a strict selection process, but individual researchers can choose which to work on and how to tackle a problem, he says. AI models that work on such problems often require specialized data and researchers to program knowledge into them. One project that shows promise, says Kohli, is AlphaGenome, which launched in June as an attempt to decipher long stretches of human non-coding DNA and predict their possible functions6. But the challenge is harder than for AlphaFold, because each sequence yields multiple valid functions. Materials science is another area in which the company hopes that AI could be revolutionary. Materials are hard to model because the complex interactions of atomic nuclei and electrons can only be approximated. Learning from a database of simulated structures, DeepMind developed its GNoME model, which in 2023 predicted 400,000 potential new substances7. Now, Kohli says, the team is using machine learning to develop better ways to simulate electron behavior, ones that are learnt from example interactions rather than by relying on the principles of physics. The end goal is to predict materials with specific properties, such as magnetism or superconductivity, he says. “We want to see the era where AI can basically design any material with any sort of magical property that you want, if it is possible,” he says.
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November 18, 11:14 PM
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Now in its 25th year of operation, the UCSC Genome Browser (https://genome.ucsc.edu) provides a central location for researchers around the world to display and compare annotations on assembled genomes. Highlighted updates include a positional heatmap display, used to show data on functional consequences of mutation from MaveDB; QuickLift, a tool to copy annotation data seen on one assembly for display on another related assembly; and HubSpace, an initiative to simplify the process of creating and using track hubs by providing each user account with dedicated storage on UCSC’s infrastructure.
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November 18, 11:08 PM
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DisProt (https://disprot.org/) is an open database integrating experimental evidence on intrinsically disordered proteins (IDPs), intrinsically disordered regions (IDRs), and their functions. Over the past two years, the database has grown over 20%, now comprising 3201 IDPs and 13 347 pieces of evidence, including over 1500 new structural state annotations and >1300 new function annotations. DisProt has systematically adopted the Minimum Information About Disorder Experiments (MIADE) guidelines, more than doubling annotations with experimental details and improving the interpretability of disorder-related experiments. The website has evolved into a hybrid knowledgebase and deposition system, introducing a Deposition Page that allows direct submissions by external users. Through BLAST-based homology propagation in MobiDB, DisProt disorder regions and linear interacting peptides have been extended from hundreds to hundreds of thousands of proteins across >11 000 organisms. This new release marks a paradigm shift by integrating computational predictions as valid evidence and introducing major updates and restructuring of the IDP Ontology, enhancing accuracy, interoperability, and semantic clarity. DisProt continues to support community engagement through training resources together with DisTriage, an AI-based literature triage tool, providing curators with regularly updated lists of prioritized publications.
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November 18, 10:55 PM
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The Bacterial and Viral Bioinformatics Resource Center (BV-BRC; https://www.bv-brc.org) is a comprehensive resource supporting research on bacterial and viral pathogens. It currently hosts over 14 million publicly available genomes and 33 high-throughput bioinformatic analysis services with numerous visual analytic tools allowing researchers to analyze their private data, generate comparisons with public data, and share data and results with colleagues. In recent years, the BV-BRC has added several new analysis services to support rapid comparative genomics and epidemiological analysis, viral genome assembly and annotation, viral subspecies classification, wastewater analysis, and molecular docking. In addition, several existing services have been updated to incorporate state-of-the-art tools, including assembly, annotation, taxonomic classification, metagenomic read mapping, and RNA-seq analysis. A new tool, called BV-BRC Copilot, provides an AI-powered natural-language interface that combines large language models with retrieval-augmented generation to guide users through data exploration, analysis workflows, and knowledge integration. With expanded outbreak tracking pages, training and educator engagement, and continued development of novel AI-driven analytics, BV-BRC continues to provide a unified resource to meet the evolving needs of the global research community.
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November 18, 10:20 PM
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CRISPR-based genome editing technologies, including nuclease-based editing, base editing and prime editing, have revolutionized biological research and modern medicine by enabling precise, programmable modification of the genome and offering new therapeutic strategies for a wide range of genetic diseases. Artificial intelligence (AI), including machine learning and deep learning models, is now further advancing the field by accelerating the optimization of gene editors for diverse targets, guiding the engineering of existing tools and supporting the discovery of novel genome-editing enzymes. In this Review, we summarize key AI methodologies underlying these advances and discuss their recent noteworthy applications to genome editing technologies. We also discuss emerging opportunities, such as AI-powered virtual cell models, which can guide genome editing through target selection or prediction of functional outcomes. Finally, we identify key directions where the integration of AI methods is poised to have a substantial impact going forward. CRISPR-based genome editing has revolutionized biotechnology, enabling precise DNA modifications for research and therapy. The authors review how artificial intelligence, including deep learning, is advancing genome editing by improving guide RNA design, editor protein engineering, novel effector discovery and predicting editing outcomes.
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November 18, 10:07 PM
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Plant guard cells perceive pathogens and close stomata to prevent their invasion. Biomolecular condensates are membraneless organelles essential for life processes. However, guard cell biomolecular condensates mediating stomatal immunity remain unknown. Here we identify a guard-cell-preferential RNA-recognition-motif-type RNA-BINDING PROTEIN, STOMATAL IMMUNE RNA-BINDING PROTEIN 1 (SAIR1), that forms pathogen-responsive guard cell condensates via phase separation. Upon perception of the pathogen molecular pattern flg22, the activated kinases MPK3 and MPK6 phosphorylate SAIR1 and trigger its condensation in guard cells for stomatal immunity. SAIR1 condensates recruit translational regulators such as POLYADENYLATE-BINDING PROTEINs and eIFiso4G, and sequester defence-related mRNAs, including key components of the salicylic acid pathway. Through these interactions, SAIR1 condensates enhance the translation of defence mRNAs, ultimately promoting stomatal closure. Our findings reveal phosphorylation-regulated SAIR1 condensates as a critical hub that links flg22–MPK3/6 signalling to stomatal immunity. The RNA-binding protein SAIR1 forms phosphorylation-regulated condensates in guard cells, which link PAMP–MPK3/6 signalling to stomatal immunity. This finding reveals how biomolecular condensates regulate spatially specific immune responses in plants.
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November 18, 9:56 PM
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Quorum sensing (QS) is a form of microbial communication that enables each cell in a population to sense the total population density, so that gene expression can be modified accordingly. Quorum quenching (QQ) is the antagonistic disruption of this communication by competing organisms, with potential use in the ongoing human effort to control microbial populations. Previous studies have taken advantage of functional metagenomics to retrieve new QS/QQ genes, but the frequency of obtaining positive clones remained very low, suggesting the need for increased screening efficiency. Here, a new ultrahigh-throughput screening method was developed to search for genes encoding novel QQ genes based on functional metagenomics, microfluidics, and the development of an Escherichia coli reporter strain whose fluorescence is repressed in the presence of AHLs but restored by the expression of any gene that interferes with the QS system. This strain was transformed with a metagenomic short-insert library collected from Antarctic plant rhizospheres; an understudied extreme environment. The library was encapsulated in droplets containing single clones and sorted using fluorescence-activated cell sorting (FACS). After screening approximately 7,000,000 clones, around 200 were recovered and one positive hit was confirmed, showing a previously unreported mode of action that would have been difficult to detect using rational computational methods. These findings underline the potential of microfluidics to dramatically increase screening efficiency, while reducing costs and processing time, and they act as a proof of concept for the discovery of more genes involved in QS and other molecular mechanisms of interest in microbial ecology.
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palsson bo, 2st, interesting, we focused on glucose-6-phosphate isomerase (GPI) and glucose-6-phosphate dehydrogenase (G6PD), which are associated with the most common human hereditary enzymopathies. As the growth rate of E. coli is contingent upon glycolytic flux11, it serves as a surrogate measure for the activity of heterologously expressed human enzymes.