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mhryu@live.com
Today, 1:01 AM
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Glycolate, an α-hydroxycarboxylic acid, is widely used in industries such as bioplastics, food, and pharmaceuticals. However, current microbial production methods are limited by the use of plasmids and chemical inducers, hindering their industrial scalability. In this study, a stable and efficient E. coli platform was developed for glycolate production. The glycolate biosynthetic pathway was reconstructed through the identification of a highly efficient glyoxylate reductase (GhrA) from Acetobacter aceti. Carbon flux toward glycolate synthesis was optimized through strategies including enhancing precursor supply, blocking competing pathways, and fine-tuning gene copy numbers. Cofactor engineering was employed by engineering GhrA cofactor preference from NADPH to NADH. Additionally, a non-auxotrophic strain (eliminating exogenous nutrient requirements) for glycolate production was engineered by implementing a growth-stage-dependent molecular switch to dynamically regulate the expression of isocitrate dehydrogenase. Through fermentation optimization, the engineered strain E. coli GA26 achieved a glycolate titer of 81.5 g/L, a yield of 0.49 g/g glucose, and a productivity of 1.9 g/L/h in a 5-L bioreactor, representing the highest reported glycolate titer from glucose to date. These results pave the way for sustainable and cost-effective industrial glycolate production.
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mhryu@live.com
Today, 12:45 AM
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Microalgae are natural and sustainable biological resources rich in high-value nutrients such as lipids, proteins, and functional pigments, which show great potential in the fields of functional foods, dietary supplements, and natural colorants. However, the yields of target components in natural microalgae are often insufficient to meet commercialization demands. The CRISPR-Cas9 gene editing system, a revolutionary technology, provides a precise and effective means for targeted improvement of microalgae to enhance their nutritional value and yields. This review first outlines the basic principles of the CRISPR/Cas9 system, including its core components and gene editing mechanism. It then summarizes the application of this technology in microalgae, focusing on successful cases of modifying metabolic pathways to enrich specific nutrients, such as increasing the unsaturated fatty acid content of lipids, increasing the proportion of edible proteins, and enriching natural pigments with antioxidant properties. In addition, this review discusses the main challenges faced when applying this technology to microalgae, including delivery difficulties due to strong cell walls, low efficiency of genetic transformation, and the risk of off-target effects. Finally, the paper describes cutting-edge strategies to address these challenges, such as the development of high-fidelity Cas9 enzymes and the optimization of a single-guide RNA (sgRNA) design. Continued advances in these technologies are propelling microalgae into efficient and sustainable “cell factories”, providing the food industry with more natural, healthy, and high-value functional ingredients.
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mhryu@live.com
Today, 12:37 AM
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Cysteine is a central metabolite in cellular redox regulation and iron-sulfur cluster assembly. Despite its critical role, monitoring cysteine dynamics in living systems has remained a challenge due to the lack of tools that avoid cysteine oxidation and/or do not destroy the cell in the process. Here, we report the development of Cystector (from Cysteine Detector), a genetically encoded, ratiometric green fluorescent biosensor for cysteine that exhibits an exceptional selectivity, minimal pH sensitivity in the physiological range, and a dynamic range of up to 4500%. Furthermore, the sensor retains functionality in the presence of physiological glutathione concentrations. We demonstrate the live-cell functionality of Cystector by monitoring intracellular and extracellular cysteine dynamics in different organisms. In E. coli, we show how cystine reduction in Escherichia coli is dependent on glutathione and glutaredoxins, and that the reduced cysteine is then exported into the extracellular environment. In yeast, we demonstrate how energy metabolism and oxidative stress determine cysteine homeostasis. In mammalian cells, we show how Cystector effectively monitors cysteine depletion in response to treatments such as H2O2, erastin2, and glutamate. Finally, we demonstrate, via a mitochondrially targeted variant, that Cystector can be used to monitor subcellular cysteine dynamics. These results together establish Cystector as a robust tool to unravel cysteine metabolism and transport in live cells across life domains.
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mhryu@live.com
Today, 12:19 AM
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As DNA sequencing technologies improve, it is becoming easier to sequence and assemble new genomes from non-model organisms. However, before a newly assembled genome sequence can be used as a reference, it must be annotated with genes and other features. This can be conducted by individual laboratories using publicly available software. Modern genome annotations integrate gene predictions from the assembled DNA sequence with gene homology information from other high-quality reference genomes and take into account functional evidence (e.g., protein sequences and RNA sequencing information). Many genome annotation pipelines exist but have varying accuracies, resource requirements and ease of use. This genome annotation Tutorial describes a streamlined genome annotation pipeline that can create high-quality genome annotations for animals in the laboratory. Our workflow integrates existing state-of-the-art genome annotation tools capable of annotating protein-coding and non-coding RNA genes. This Tutorial also guides the user on assigning gene symbols and annotating repeat regions. Finally, we describe additional tools to assess annotation quality and combine and format the results. This Tutorial integrates state-of-the-art tools into a streamlined workflow to create high-quality annotations for animal genomes, assigning gene symbols and annotating repeat regions for both protein-coding and non-coding RNA genes, before assessing annotation quality.
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mhryu@live.com
Today, 12:05 AM
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The in situ relevance of biosynthetic gene clusters (BGCs) remains poorly understood. We applied meta-omics to characterize BGC diversity and activity along a peatland redox gradient. From seven metagenomes, we recovered 9,694 BGCs spanning diverse taxa, most lacking close relatives in reference databases, indicating extensive novelty. Only 9-27% of this potential was expressed in situ, with Acidobacteriota, despite moderate repertoires, accounting for over half of all BGC transcription. Talented producers with up to 24 clusters were largely silent, and expression was inversely related to BGCs per genome. Acidobacteriota and other oligotrophic taxa expressed most of their BGCs, whereas copiotrophic Pseudomonadota expressed a few, suggesting that life-history and stress-responsive regulation govern activation. PKS and terpene BGCs expression was enriched in genomes expressing markers of aerobic respiration and stress, whereas RiPPs were associated with antimicrobial resistance, stationary phase and stress. Thus, although BGCs are widespread, environmental constraints determine which are realized.
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mhryu@live.com
January 28, 11:20 PM
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The role of microbial strains in regulating natural stresses and their impact on plant health is well-established. However, the role of microbial tolerance mechanisms in plant response to unnatural or anthropogenic stresses is less understood. Examination of these interactions impact our deeper understanding of plant-microbe interactions and our ability to enhance beneficial functions. In this study we use the model plant Brachypodium distachyon and its prominent root colonizer Paraburkholderia graminis OAS925 to investigate mechanisms of tolerance to alcohol and salt stress. We examined the ability of OAS925 to reduce root growth inhibition during exposure to short chain alcohols and salt. We also examined the tolerance mechanism for OAS925 towards these stresses using RB-TnSeq fitness assays. The most prominent tolerance systems in OAS925 are genes specifically involved in membrane transport (such as the Mla operon), efflux systems (e.g., RND efflux systems), signaling and regulation (PrtR/PrtI, NtrY/NtrX, and EnvZ/OmpR), and oxidative stress response (GshB). Our findings provide a model where bacterial membrane integrity, active solvent efflux, and stress signaling are crucial not only for bacterial survival but also for maintaining the root colonization and biofilm formation that confer protection to the host plant.
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mhryu@live.com
January 28, 10:59 PM
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Bacteriophages ("phage") are viruses that prey on bacteria in diverse environments, from biological tissues to soils. In many of these environments, bacterial hosts are constantly migrating, yet how bacterial migration is influenced by phage predation remains poorly understood. Using transparent granular hydrogels that mimic natural habitats, we directly visualize populations of motile E. coli encountering lytic T4 phage. Unexpectedly, we find that even in phage-rich environments, bacteria successfully form chemotactic fronts that enable them to migrate over large distances without needing to develop phage resistance. Higher phage concentrations delay front formation but not steady-state front speed or shape. By combining our experiments with biophysical modeling, we demonstrate that this phenomenon arises from the ability of cells to collectively outrun trailing phage bursts---as quantified by a dimensionless "escape parameter" comparing chemotactic and predation rates. This work thus reveals and provides mechanistic insight into the role of cell motility in shaping phage-bacteria interactions in spatially-extended environments.
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mhryu@live.com
January 28, 4:43 PM
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Plant diseases significantly impact crop yield and quality, while conventional pesticide treatments often disrupt beneficial plant microbiota essential for pathogen prevention and immune regulation. Although plant beneficial microorganisms (PBMs) show promise as disease control agents, their effectiveness is constrained by strain-dependent variations, survival challenges, and inconsistent immune responses. Recent advances in genetic engineering, particularly CRISPR-Cas systems combined with complementary technologies like RecE/T, enable precise modifications of PBMs to enhance their protective potential. Enhanced PBMs improve functionality via multiple mechanisms: targeted gene-expression-mediated colonization, specific antimicrobial activity, and immune regulation. Studies demonstrate that genetically modified PBMs can prevent and control plant diseases through competitive exclusion, antibiotic production, barrier reinforcement, and immune modulation. We analyzed the considerations for the environmental release of engineered PBMs to reduce risks. Future research should focus on optimizing PBMs for specific applications while addressing biosafety concerns, thereby unlocking their full potential in safeguarding plant health. pgpr
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mhryu@live.com
January 28, 4:33 PM
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Accurate recognition of promoter sequences in E. coli is fundamental for understanding gene regulation and engineering synthetic biological systems. However, existing computational methods struggle to simultaneously model long-range genomic dependencies and fine-grained local motifs, particularly the degenerate −10 and −35 elements of 𝜎70 promoters. To address this gap, we propose DNABERT2-CAMP, a novel hybrid deep learning framework designed to integrate global contextual understanding with high-resolution local motif detection for robust promoter identification. We constructed a balanced dataset of 8720 experimentally validated and negative 81-bp sequences from RegulonDB, literature, and the E. coli K-12 genome. Our model combines a pre-trained DNABERT-2 Transformer for global sequence encoding with a custom CAMP module (CNN-Attention-Mean Pooling) for local feature refinement. We evaluated performance using 5-fold cross-validation and an independent external test set, reporting standard metrics including accuracy, ROC AUC, and Matthews correlation coefficient (MCC). DNABERT2-CAMP achieved 93.10% accuracy and 97.28% ROC AUC in cross-validation, outperforming existing methods including DNABERT. On an independent test set, it maintained strong generalization (89.83% accuracy, 92.79% ROC AUC). Interpretability analyses confirmed biologically plausible attention over canonical promoter regions and CNN-identified AT-rich/-35-like motifs. Conclusions: DNABERT2-CAMP demonstrates that synergistically combining pre-trained Transformers with convolutional motif detection significantly improves promoter recognition accuracy and interpretability. This framework offers a powerful, generalizable tool for genomic annotation and synthetic biology applications.
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mhryu@live.com
January 28, 4:16 PM
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High-throughput screening (HTS) platforms and automated biofoundries have enabled large-scale experimentation in enzyme and microbial strain engineering. Central to HTS are biosensors and assays, which translate biochemical activities into measurable signals, enabling rapid evaluation of cellular and enzymatic performance. Yet despite advancements in high-throughput infrastructure, the limited availability of robust biosensors or assays and the difficulty of integrating them with HTS, particularly with ultra-HTS, remains a major bottleneck. This review highlights recent progress and challenges in applying biosensors- and assays-enabled HTS for enzyme and strain libraries. We discuss strategies for integrating diverse biosensor types, including transcription factors, G protein-coupled receptors, aptamers, fluorogenic RNAs, riboswitches, and colorimetric assays, with HTS to detect a broad range of metabolites and products. We also explore how biosensor-enabled HTS facilitates data generation for machine learning-guided biocatalyst engineering. Collectively, these advances accelerate biocatalyst discovery and drive the next generation of sustainable biomanufacturing.
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mhryu@live.com
January 28, 3:55 PM
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Human genetic variation influences all aspects of our biology, including the oral cavity, through which nutrients and microbes enter the body. Yet it is largely unknown which human genetic variants shape a person’s oral microbiome and potentially promote its dysbiosis. We characterized the oral microbiomes of 12,519 people by re-analysing whole-genome sequencing reads from previously sequenced saliva-derived DNA. Human genetic variation at 11 loci (10 new) associated with variation in oral microbiome composition. Several of these related to carbohydrate availability; the strongest association (P = 3.0 × 10−188) involved the common FUT2 W154X loss-of-function variant, which associated with the abundances of 58 bacterial species. Human host genetics also seemed to powerfully shape genetic variation in oral bacterial species: these 11 host genetic variants also associated with variation of gene dosages in 68 regions of bacterial genomes. Common, multi-allelic copy number variation of AMY1, which encodes salivary amylase, associated with oral microbiome composition (P = 1.5 × 10−53) and with dentures use in UK Biobank (P = 5.9 × 10−35, n = 418,039) but not with body mass index (P = 0.85), suggesting that salivary amylase abundance impacts health by influencing the oral microbiome. Two other microbiome composition-associated loci, FUT2 and PITX1, also significantly associated with dentures risk, collectively nominating numerous host–microbial interactions that contribute to tooth decay. Human genetic loci that associate with composition of the oral microbiome are identified using saliva-derived DNA, where the same host genetics also shapes oral health and genetic variation in oral bacteria.
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mhryu@live.com
January 28, 3:39 PM
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Cyanobacteria play a key role in the biomineralization of carbon dioxide into solid carbonates, a critical process in the global carbon biogeochemical cycle that links atmospheric CO2 to lithospheric carbonate reservoirs. While photosynthetic carbon fixation by these microorganisms has been extensively studied and is relatively well understood, the biomineralisation pathway remains much less explored, likely leading to an underestimation of its global relevance. This review summarises current findings and highlights the ecological and cellular factors that contribute to cyanobacterial biomineralisation. In particular, the need to cope with fluctuating environmental conditions has played a central role in enabling cyanobacteria to develop rapid metabolic adaptations together with the evolution of a complex cell wall architecture. Within this framework, biomineralisation emerged as a tangible and effective adaptive strategy. Particular attention is given to the metabolic processes and related ion trafficking mechanisms across the cell envelope, which are instrumental in facilitating mineral nucleation and growth.
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mhryu@live.com
January 28, 3:09 PM
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Serial multi-omic analysis of proteome, phosphoproteome, and glycoproteome is pivotal for elucidating drug mechanisms, discovering biomarkers, and identifying therapeutic targets. However, simultaneous multi-level post-translational modifications (PTM) analysis via parallel processing is hampered by laborious, time-consuming procedures and inconsistent reproducibility. We present an integrated Multi-level PTMs-Proteomic Enrichment platform (MuPPE), enabling sequential glycoproteome, phosphoproteome, and proteome analysis from single biological samples. It combines protein aggregation capture with on-bead digestion and tandem enrichment, achieving superior reproducibility (CV 12.3% vs 17.6% conventional methods) while reducing processing time by 87.5% (4 hours vs 32 hours). MuPPE also enhances coverage, identifying more serum glycopeptides and brain phosphopeptides than other platforms. Applied to aging mouse cohorts, the platform uncovers tissue-specific PTMs remodeling and brain barrier dysfunction. For arsenic mechanisms of action, MuPPE reveals drug-induced PTMs crosstalk between glycosylation and phosphorylation-driven pathway regulation. MuPPE offers a transformative tool for advancing multi-omics insights across precision medicine and disease research. Authors develop MuPPE, which enables integrated proteome, phosphoproteome, and glycoproteome profiling from a single sample, providing deeper biological insights into aging and drug-response mechanisms.
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Scooped by
mhryu@live.com
Today, 12:54 AM
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Metagenomic sequencing has revolutionised the field of microbial ecology, as it has led to cultivation-independent exploration of complicated microbial communities. The assembly of metagenome-assembled genomes has provided genome-scale information about uncultivated microorganisms, but issues such as sequencing errors, fragmented assemblies, residual redundancy, uneven coverage, recovery of low-abundance taxa, and highly diversified taxa continue to impair the quality of these genomes. The latest achievements in artificial intelligence, particularly in machine learning and deep learning, have played a significant role in overcoming these limitations by enhancing quality control, error correction, assembly, binning, refinement, and annotation procedures. It is demonstrated that representation learning and graph-based binning methods have high strain-level resolution and can reduce contamination in complex microbial communities, whereas artificial intelligence-based assemblers and polishing tools improve base-level precision and assembly contiguity. This review synthesizes traditional and artificial intelligence-based workflows involved in the reconstruction of metagenome-assembled genomes, encompassing quality control, assembly, binning, refinement, and annotation, as well as quantitative benchmarking of significant artificial intelligence-based pipelines. As future directions, the focus on emerging trends, such as explainable artificial intelligence, federated learning, cloud-native scalable pipelines, multimodal and multi-omics integration, and large language model-based annotation, is covered. In general, the incorporation of artificial intelligence represents a paradigm shift in the reconstruction of metagenome-assembled genomes, allowing for a more relevant, scalable, and biologically informative search of the microbial dark matter in various ecosystems.
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mhryu@live.com
Today, 12:41 AM
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Methane is one of the most prominent greenhouse gases contributing to global warming. It is also a valuable source of energy and a raw material for the production of chemicals. Gas-to-liquid technologies for its conversion into methanol are particularly interesting, methanol being considered as a platform molecule for the chemical industry and a prospective fuel for low-emission transport. Methane oxidation into methanol is up to day carried out industrially under energy-consuming conditions, associated to significant CO2 emissions. Methanotrophic catalysis has arisen as a promising greener alternative since methanotrophs are naturally-occurring microorganisms (bacteria and archaea) able to uptake methane under mild conditions. Methanotrophic bacteria express the Methane MonoOxygenase (MMO) enzyme, able to selectively hydroxylate methane. However, their large-scale implementation is currently hindered by both biological and process constraints. This review summarizes recent developments in bioprocesses for methanol production from methane, including methanotroph-based ones. Whole-cell methanotrophs, cell-free (enzymatic) processes and MMO heterologous expression have been covered.
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mhryu@live.com
Today, 12:34 AM
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Caves are unique among ecosystem types because of their physical structures and biological functions. Embedded in rocks, the geological setting defines the boundaries of caves and dictates how energy and matter move through them. General features of caves, compared to surface ecosystems, include absence of light, relatively stable temperature and humidity, and oligotrophic conditions. Despite these conditions, caves are highly diverse ecosystems whose environmental properties are shaped by geological, hydrological, and climatic factors. Cave microbiomes metabolize atmospheric trace gases, such as methane, nitrous oxide, and carbon dioxide, contributing to greenhouse gas (GHG) cycling dynamics. In some cases, these microbes also form biominerals, such as calcium carbonate, highlighting critical gaps in our understanding of subterranean biogeochemical processes. Some of these gaps include the limited genomic data and geographic bias in the literature. Herein, we review the current state of knowledge surrounding the potential of cave microorganisms, including those capable of biomineralizing calcium carbonate, as agents for sustainable GHG sequestration and climate change mitigation, with emerging strategies for developing novel sustainable biotechnological solutions. By revealing the hidden microbial activity beneath the Earth’s surface, this review proposes integrating subterranean ecosystems into global climate models, reframing caves as metabolically and functionally active contributors to the planet’s climate system rather than isolated geological features.
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mhryu@live.com
Today, 12:11 AM
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Environmental pollution from a wide range of compounds poses serious ecological and health risks. While bioremediation offers a promising solution, its application is limited by fragmented genomic resources and unsatisfactory understanding of microbial biodegradation pathways. Here, we developed the Microbial BioRemediation (MBR) database, freely accessible at https://probiogenomics.unipr.it/cmu, a comprehensive and manually curated repository comprising over 643,351 bacterial protein sequences associated with the degradation of 564 pollutant compounds across 25 chemical classes. Optimized for both genomic and metagenomic analyses, the database enables high-resolution functional and taxonomic profiling of microbial communities and individual bacterial strains. Validation using public genome and metagenome datasets from contaminated environments confirmed the database ability to detect both conserved and environment-specific biodegradation functions. Its application to host-associated microbiomes further confirmed the suitability of MBR for assessing how environmental exposures shape microbial catabolic potential across ecological contexts. The MBR atabase thus serves as a strategic tool for the early-stage identification and prioritization of microbial candidates for bioremediation. By enabling the in silico selection of key microbial taxa and enzymatic functions, it supports a rational pipeline that progresses toward targeted in vitro validation and experimental characterization. This integrative approach facilitates development of next-generation, tailored strategies for the remediation of complex polluted ecosystems.
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mhryu@live.com
January 28, 11:45 PM
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Microorganisms play essential roles in mediating biogeochemical cycling of carbon across Earth`s ecosystems. Understanding the processes and underlying mechanisms for microbially mediated carbon cycling is therefore critical for advancing global ecology and climate change research. To comprehensively depict these complex biogeochemical processes, we developed CCycDB, a knowledge-based functional gene database, to accurately fingerprint microbially-mediated carbon cycling pathways and gene families, particularly from shotgun metagenomes. The CCycDB database comprises 4,676 gene families classified into six major functional categories, further structured into 45 level-1 and 188 level-2 sub-categories, encompassing a total of 10,991,724 high-quality reference sequences. Validation using both synthetic and real-world datasets demonstrated that CCycDB outperforms existing orthology databases in terms of accuracy, coverage and specificity. By directly targeting carbon-cycling functional gene families, CCycDB provided promising routines to reconstruct both functional gene and taxonomic profiles associated with microbially mediated carbon cycling. Application of CCycDB to shotgun metagenomes from diverse and complex ecosystems revealed pronounced habitat-specific differences in carbon cycling processes and their associated microbial taxa. Collectively, CCycDB provides a powerful and reliable tool for profiling carbon cycling processes from both functional and taxonomic perspectives in complex ecosystems. CCycDB is accessible at https://ccycdb.github.io/.
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mhryu@live.com
January 28, 11:04 PM
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Mammalian cell lines are the preferred hosts for producing commercially relevant therapeutic proteins such as antibodies, multispecifics, and cytokine fusion proteins. Even though significant investment is made to optimize upstream and downstream processes, the optimal gene design parameters for heterologous recombinant protein expression remain poorly understood. We describe here a generic approach to gene optimization in which design features are systematically sampled and modulated iteratively using machine learning (ML). Synthetic genes encoding the Dasher fluorescent protein, differing only in synonymous codons, were used to interrogate the gene-sequence preferences of transient antibody-expressing HEK293 cells. Synonymous codon variations influenced expression by more than two orders of magnitude. This variation in protein yield was used to build ML models relating gene design features, which were then employed to design further-improved genes. The ML models were shown to be expression system-specific. Messenger RNA levels and ribosome occupancy were highly correlated with protein levels, suggesting that mRNA lifetime has a causal relationship with coding bias. Our results illustrate a novel, generally applicable method to improve gene expression via synonymous re-coding for any protein target or host cell.
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mhryu@live.com
January 28, 4:46 PM
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Designer cellulosomes are engineered multi-enzyme complexes inspired by natural cellulosomes, designed to improve lignocellulose breakdown. Their modular architecture enables the spatial colocalization of diverse catalytic activities, potentially enhancing depolymerization efficiency compared to free enzymes. Although conceptually promising, little is known about how they perform on complex lignocellulosic substrates. In this study, we developed a tetravalent designer cellulosome using a modular VersaTile assembly approach, incorporating endoglucanase, cellobiohydrolase, β-glucosidase, and endoxylanase activities. The process involved (i) delineating catalytic modules from Cellvibrio japonicus enzymes, (ii) generating docking enzyme variants via combinatorial cloning, and (iii) selecting optimal candidates based on expression, activity, and cohesin-dockerin binding before assembling them onto a scaffoldin with four cohesins and a cellulose-binding module. The resulting designer cellulosome was tested on two industrially relevant substrates: agro-industrial wheat fibers and genome-edited low-lignin poplar biomass under controlled laboratory conditions. It achieved cellulose-to-glucose conversion yields of 24.98% (150 pmol designer cellulosome/ml) and 0.82% (200 pmol designer cellulosome/ml), respectively, under the test conditions. By comparing the saccharification efficiencies of the enzymes in their free and complexed forms, we found that colocalization on a common scaffoldin significantly enhanced synergistic activity. This effect was most pronounced under low enzyme concentrations and when acting on complex lignocellulosic substrates, increasing glucose release compared to free enzymes. These observations highlight that the benefits of colocalization are substrate-dependent and occur under conditions that mimic the natural environment of biomass degradation, conditions that differ from typical industrial settings. This work advances our understanding of designer cellulosome behavior on real-world substrates, providing essential insights for evaluating their economic viability in industrial applications.
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mhryu@live.com
January 28, 4:41 PM
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Regions in intrinsic disordered proteins (IDPs) constitute important continuous aspects of protein function. While their existence on a structural continuum is widely accepted, most computational predictions have, nevertheless, focused on binary classifications. Existing datasets are severely limited in size and experimental evidence for continuous disorder. Building on recently released datasets of continuous protein disorder and flexibility, we introduce UdonPred, a lightweight neural network exclusively inputting embeddings from the protein Language Model (pLM) ProstT5 to predict per-residue protein disorder from sequence alone. Training and evaluating UdonPred on seven datasets with divergent definitions of disorder and flexibility suggests that not model capacity, but agreement and nuance of disorder annotations, remains the main driver of performance. Binary disorder annotations can be reliably predicted from a multitude of different disorder and flexibility datasets, but there is still room for improvement in predicting continuous disorder. https://github.com/davidwagemann/udonpred.
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mhryu@live.com
January 28, 4:22 PM
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Against the backdrop of the global protein crisis and the textural limitations of alternative proteins, microorganisms are increasingly recognized as versatile structural materials to address these challenges. This review systematically analyzes three key microbial strategies: employing mycelial solid-state fermentation to engineer fibrous meat analogues; utilizing bacterial cellulose scaffolds to enhance the texture of both cultured meat and plant-based products; and applying synthetic biology to design tailored functional proteins. Existing studies confirm that mycelial fermentation significantly improves product texture and production sustainability. In parallel, bacterial cellulose provides highly biocompatible nanoscaffolds, while synthetic biology enables the efficient production and nutritional enhancement of complex animal proteins. Although challenges in scaling production and optimizing flavor persist, advanced bioprocess optimization and genetic engineering offer promising solutions. Future breakthroughs are expected to transition from structural mimicry to true functional creation, establish decentralized production networks, and advance dynamic 4D-printed foods, which will collectively contribute to a more sustainable and resilient global food system.
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mhryu@live.com
January 28, 4:01 PM
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Most bacterial pathogens are polylysogens, harboring multiple vertically transmitted prophages. These prophages enhance bacterial pathogenicity and survival by encoding virulence factors and antiphage defence systems while retaining the capacity for horizontal transfer. Thus, prophage-encoded anti-phage defences must block propagation of external phages without inhibiting the spread of the prophages that encode them. Here we identify HepS—an abortive infection system encoded on the Gifsy-1 prophage constituted of a single HEPN domain protein—which restricts phages of the Siphoviridae family. We demonstrate that in its native host context of Salmonella enterica serovar Typhimurium, HepS both senses phage infection and enacts abortive infection. Structures of HepS reveal a tetrameric nuclease complex that undergoes allosteric activation upon recognition of Siphoviridae tail tip proteins during production of new phage particles. Once activated, HepS cleaves specific transfer RNA anticodon loops and arrests phage replication. Gifsy-1, a Siphoviridae itself, evades self-targeting by expressing a tail tip variant that does not trigger HepS, as do co-resident Siphoviridae prophages Gifsy-2 and Gifsy-3. This evasion permits Gifsy-1 to spread despite encoding HepS. These findings reveal a mechanism by which a prophage defends the host while maintaining its propagation abilities. A Gifsy-1 prophage–encoded higher eukaryotes and prokaryotes nucleotide-binding protein, HepS, senses Siphoviridae infection, activates abortive defence by cleaving host transfer RNAs, blocks rival phages and avoids self-targeting via tail-tip variation.
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mhryu@live.com
January 28, 3:53 PM
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Whole-genome duplication (WGD) has had profound macroevolutionary impacts on diverse lineages, preceding adaptive radiations in vertebrates, teleost fish, and angiosperms. In contrast to the many known ancient WGDs in animals, and especially plants, we are aware of evidence for only four WGDs in fungi. The oldest of these occurred ∼100 million years ago (mya) and is shared by ∼60 extant Saccharomycetales species, including the baker’s yeast Saccharomyces cerevisiae. Notably, this is the only known ancient WGD event in the yeast subphylum Saccharomycotina. The dearth of ancient WGD events in fungi remains a mystery. Some studies have suggested that fungal lineages that experience chromosome and genome duplication quickly go extinct, leaving no trace in the genomic record, while others contend that the lack of known WGDs is due to an absence of data. Under the second hypothesis, additional sampling and deeper sequencing of fungal genomes should lead to the discovery of more WGD events. Coupling hundreds of recently published genomes from nearly every described Saccharomycotina species, with three additional long-read assemblies, we discovered three novel WGD events. Although the functions of retained duplicate genes originating from these events are broad, they bear similarities to the well-known WGD that occurred in the Saccharomycetales. Our results suggest that WGD may be a more common evolutionary force in fungi than previously believed.
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mhryu@live.com
January 28, 3:20 PM
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De novo genes generally refer to genes that arise from previously non-coding sequences. This evolutionary path — when randomly expressed sequences become folded and active proteins — challenges our understanding of genetic innovation and has prompted studies to address the evolutionary and mechanistic knowledge gaps. More specifically, prior work has illuminated the mechanisms underlying the origin of de novo genes, their potential functional roles in the cell and the evolutionary processes that lead to these functions. Recent advances in both experimental and computational approaches have contributed to insights into the emergence of de novo genes and the broader implications for our understanding of biological complexity. In this Review, we place particular emphasis on efforts to quantify the likelihood of de novo gene emergence in eukaryotes given genomic characteristics, as well as the mechanisms by which de novo protein structures that are not actively selected against become amenable to selection-driven changes. De novo gene evolution entails the birth of new genes from previously non-coding DNA. In this Review, Bornberg-Bauer and Eicholt overview how protein-coding de novo genes are identified, the mechanistic and evolutionary processes underlying their emergence and evolution, and the patterns in their encoded protein structures.
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Bacteria inoculated at the left edge of a phage-rich environment (left) consume chemoattractant and establish a self-generated gradient (middle). Despite continuous phage infection and lysis of cells within the population, collective chemotactic migration up this gradient is fast enough to outrun the trailing burst of phage progeny, enabling the formation and propagation of a migrating chemotactic front (right). This mechanism allows bacterial populations to successfully traverse phage-rich terrain over large distances without requiring evolution of genetic resistance.