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Today, 11:36 PM
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Environmental sustainability is seriously threatened by the discharge of wastewater containing hazardous heavy metals (such as Cr, Cd, As, Hg, etc.). The utilization of microalgae has recently come to light as a viable, environmentally acceptable method for removing heavy metals from contaminated sites. Certain small biomolecules that resemble phytohormones can be beneficial in microalgal biotechnology as they control biological processes and signal transduction to increase stress tolerance and simultaneously upregulate the production of beneficial metabolites. As a result, they make good candidates for bioremediation and an effective vector for removing heavy metal pollutants from the environment. Melatonin, γ-aminobutyric acid (GABA), polyamines, and glycine-betaine are small biomolecules that act as signaling molecules or regulators in microalgae. They play crucial roles in controlling cell development, metabolism, stress resistance, heavy metal accumulation, and redox homeostasis. The potential of phytohormone-like small biomolecules and their incorporation into microalgal systems has been immensely explored by researchers across the globe. However, most studies have reported compromised photosynthetic efficiency in the targeted microalgae and repressed metabolite accumulation. There is then the need for developing cultivation methods without compromising cell viability and photosynthetic efficiency. Therefore, there is a greater need to understand the underlying mechanisms controlling cell proliferation and heavy metal bioaccumulation through the application of phytohormone-like small biomolecules. The current review aims to explore the efficacy of phytohormone-like small biomolecules in the context of microalgal bioremediation of heavy metals alongside the enhancement of various algal metabolites.
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Today, 11:24 PM
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α1,2-Fucosyltransferase (α1,2-FucT) catalyzes the constitution of 2′-fucosyllactose (2′-FL) via transferring the L-fucose from the donor GDP-L-fucose to the lactose acceptor, thus playing an essential role in the microbial biosynthesis of 2′-FL. However, the performance of natural α1,2-FucT catalytic activity is limited, and lack of efficient screening platforms is hampering its engineering. This study presents a whole-cell biosensor-based high-throughput screening platform to obtain α1,2-FucT with high catalytic activity. First, a whole-cell biosensor was designed to translate 2′-fucosyllactose, the catalytic product of α1,2-FucT, to a positively correlated fluorescence signal. Meanwhile, a thermosensitive lactose-degradation pathway was introduced to resolve the concern of lactose interference. Then, a cross-scale leap from microliter to picoliter was achieved through characterization and optimization, which allowed sorting of α1,2-FucT high-throughput droplets. We selected most widely utilized Helicobacter pylori α1,2-FucT and constructed a library of 0.1 million mutants, identifying V93I as the most optimal mutant. Its catalytic efficiency (kcat/Km) was 5.024 ± 0.702 min−1 mM−1, 2.31 times that of the wild-type α1,2-FucT. As far as we know, this study is the first to illustrate the high-throughput screening platform based on a 2′-FL whole-cell biosensor and droplet microfluidics, and this strategy can be extended to similar glycosyltransferase-screening applications.
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Today, 10:40 PM
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Biorefinery is an innovative concept for resource utilization. To further increase its efficiency, the integration of different biomass conversion technologies (integrated biorefinery) is essential. Biodiesel, a traditional biofuel, generates glycerol as an inevitable byproduct; making it an attractive carbon source for biorefineries due to its abundance, low price, and high degree of reduction. In this work, we propose an integrated two-step process of dark fermentation with Escherichia coli to produce L-malate from glycerol and photofermentation by Rhodobacter capsulatus to convert this L-malate into hydrogen, a clean and sustainable energy carrier. To this end, we optimized an E. coli L-malate-producing strain by overexpressing GlpK in the M4-Δiclr/pBAD-pck strain and scale up the process from shake flask to bioreactor using waste crude glycerol from a biodiesel biorefinery instead of pure glycerol. Under the optimized conditions, E. coli produced up to 11 g/L L-malate in 24 h. The culture medium from this dark fermentation was used to formulate an L-malate enriched medium for Rhodobacter that led to the production of 58.0 ± 6 mM H2 in 90 h.
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Today, 6:45 PM
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Post-translational modifications (PTM) are critical regulators of protein function, yet confidently identifying and localizing PTM sites across proteomes remains a challenging task. Integrating peptide property predictions into spectrum interpretation improves identification performance, but training data enabling zero-shot prediction across diverse PTMs are scarce. Here, we present a major expansion of the ProteomeTools dataset, comprising over 977,000 synthetic peptides, covering 22 PTM-residue combinations. Furthermore, we developed Prosit-PTM, a model with chemically-informed encoding and amino acid substitution-based augmentation trained with our novel ground-truth dataset, that achieves accurate zero-shot predictions. Applied to modified peptides, Prosit-PTM enhances PTM-site localization in phosphoproteomics, increases identification of multiply modified peptides in histones, and enables data-driven rescoring for unseen modifications such as HLA peptides. Furthermore, the learned embeddings of amino acids and modifications capture physicochemical relationships underlying PTM-driven HLA presentation. Prosit-PTM is integrated into multiple open-source tools, enabling PTM-aware rescoring, site localization, spectral library generation, and beyond.
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Today, 6:27 PM
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Overlapping genes allow multiple proteins to be encoded from a single DNA sequence, including convergent (antisense; tail-to-tail) orientations across three reading frames (phases 0, 1, and 2), with phase 1 most frequently observed in nature. Designing such overlaps is challenging due to codon degeneracy, phase-specific biases, and the need to preserve structural integrity for both proteins. Here, a purpose-built transformer encoder is introduced, trained on a balanced synthetic dataset of convergent overlaps spanning diverse prokaryotic genomes and GC contents. Controlled amino acid substitutions were incorporated during training to enhance model generalization, particularly for phase 1 overlaps. At inference, Monte Carlo dropout enabled uncertainty-aware sampling of synonymous codon solutions, which were iteratively refined using a windowed, multi-objective optimization framework. Candidate overlaps were scored using composite weighting across secondary structure preservation, substitution similarity, alignment identity, and ESM-2 contact map similarity, with SSIM applied as a rapid proxy for structural fidelity. This approach generated convergent overlaps across all phases, with phase 1 showing the highest success rates. Optimization trajectories revealed distinct dynamics, with secondary structure preservation steadily increasing despite its lower weight. External validation using SwissProt proteins stratified by AlphaFold2 pLDDT confidence supported generalization to proteins with differing rigidity, yielding high secondary structure preservation in silico. These results demonstrate that transformer models trained directly at the nucleotide level, when coupled with uncertainty-aware inference and lightweight structural proxies, can support the computational design of synthetic overlapping genes without requiring full structural prediction. This framework offers a scalable path for phase-specific, codon-aware overlap design under realistic constraints.
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Today, 3:33 PM
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Synthetic riboswitches have undergone great development in the past decade, evolving into valuable regulatory tools. Operating entirely at the RNA level and independently of auxiliary proteins, they offer a promising alternative to protein-based systems such as TetON/OFF or CRISPR-Cas. As compact, modular RNA elements they unite sensing and regulatory functions within a single molecule, giving them the advantages of high modularity, portability and low metabolic burden. Here, we explore the unique features of synthetic riboswitches, highlight key applications, assess current bottlenecks and limitations and put them in context with emerging solutions, to emphasise the potential of synthetic riboswitches. Synthetic riboswitches are a burgeoning regulatory tool in the field of molecular biology. Here, the authors explore the unique features of synthetic riboswitches, highlight key applications, assess current bottlenecks and limitations and put them in context with emerging solutions.
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Today, 3:22 PM
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Bacteria have been generally greatly overlooked in the aspect of intra- and extra-cellular homeostasis, and yet, since they have evolved intricate processes and mechanisms allowing them not only to stay alive but also thrive in favorable and unfavorable environments alike, they should be considered as a close-to-ideal example of single-cell homeostasis. The bacterial responses aimed at maintaining homeostasis, while adjusting and reacting smoothly and swiftly to any changes inside and outside the cell, involve complex transcriptional networks regulated by second messengers and DNA topology, but also influenced by the presence of prophages and toxin-antitoxin systems. Their adjustment to nutrient availability also involves homeostasis in energy-related processes, such as central carbon metabolism, and crucial ion acquisition, e.g., iron. The genome stability, which is indispensable to maintain a given organisms’ functions, is achieved by control of DNA replication and repair. Furthermore, bacteria can form multicellular structures (biofilms), where homeostasis is achieved at several different levels and provides bacteria with higher chances of survival and colonization of new niches and locations. Precise correlation between the above-mentioned cellular processes makes bacteria highly intriguing objects of studies. Homeostasis is the most important basis of their life-style flexibility, thus understanding of these processes is indispensable for both: the basic and applied sciences. For example, understanding how chromosomal architecture and DNA topology coordinate global gene expression is essential for optimizing strain engineering and synthetic biology applications. Moreover, bacterial homeostasis regulatory processes can be employed as targets for antibacterial agents and prospective therapies.
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Today, 2:16 PM
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Lactoferrin (LF) is a heat-sensitive, iron-binding globular glycoprotein. Glycosylation and glycation can significantly alter its three-dimensional structure, spatial conformation, and functional properties, thereby affecting its thermal stability. This study compared the thermal stability of glycosylated LF from caprine colostrum (CLF) and mature milk (MLF) with that of glycated LF from lactosylated LF (LFL). During the heating process, both CLF and MLF exhibited heat-induced aggregation in SDS-PAGE, the holo-peak of CLF was higher than that of MLF after heat treatment, and the thermal transition temperature of CLF (95 °C) was higher than that of MLF (85 °C), suggesting glycosylation plays a role in the heat stability of LF. Compared to MLF, LFL exhibited less thermal aggregation and greater retention of secondary structure. In addition, the LFL showed more rod-shaped proteins in SEM, indicating that the LFL had improved thermal stability. This study reveals the potential effects of glycosylation and glycation in enhancing the thermal stability of LF.
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Today, 1:49 PM
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mariner is a transposable element of the Tc1/mariner superfamily that is widely distributed in various species. It was discovered in Drosophila mauritiana owing to a white-peach eye color mutation, and since then it has been used as a research tool in many systems and species. mariner element mobilization consists of cut-and-paste transposon excision and insertion. Here, apart from giving a historical overview of the discovery, distribution, and classification of mariner elements, we address the factors responsible for their particularly high somatic mobilization activity, with a focus on stress responses. We also address the usage of mariner transposases as research tools and how somatic mobilization can currently be detected.
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Today, 1:35 PM
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Ribonuclease P (RNase P), a ribozyme conserved across all domains of life, is involved in the tRNA 5′ maturation. RNase P recognizes precursor tRNA based on its structure, not the tRNA sequence. This feature had been exploited to engineer RNase P to selectively target and cleave any RNA as a gene inactivation strategy. Of these, a strategy called M1GS involves tethering an Escherichia coli M1 RNA to a short stretch of guide sequence (GS), which is complementary to the RNA targeted for cleavage. Despite its simplicity and versatility, M1GS tool appears to be underutilized compared to other gene inactivation strategies. Perhaps one of the reasons is that employment of the M1GS strategy requires prior knowledge about the requirements of the M1GS target sites. To facilitate its broader use, we have developed a Python script-based user-friendly bioinformatic tool built based on the requirements of M1GS to predict its target sites for any given RNA (using either DNA or RNA sequence as an input). In this study, we first demonstrate the utility of the bioinformatic tool in predicting M1GS target sites for human 28S rRNA and then we show that the customized M1GS-mediated downregulation of 28S rRNA in a human cancer cell line. We further validate the bioinformatic tool by predicting M1GS target sites for two previously targeted RNAs. Lastly, we discuss the utility of M1GS ribozyme-mediated rRNA downregulation as a potential anticancer modality in cancers where rRNAs are upregulated.
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Today, 11:00 AM
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Heavy metal (HM) contamination in agricultural soils threatens food security, soil health, and human well-being. While phytoremediation offers a sustainable alternative to conventional remediation methods, its efficiency remains limited. Recent advances in artificial intelligence (AI), machine learning (ML), and multiomics technologies (genomics, proteomics, metabolomics) provide transformative opportunities to overcome these limitations. This review highlights the integration of AI-driven models with multiomics data to optimize phytoremediation strategies. AI enables the prediction of plant–microbe interactions, selection of plant growth-promoting bacteria (PGPB), and modeling of metal transporter dynamics, thereby enhancing crop tolerance and metal accumulation. By mining large-scale omics datasets, AI can also identify critical pathways for detoxification and guide precision engineering of plants and microbes. The convergence of AI, ML, and multi-omics technologies represents a transformative approach to solving the challenge of heavy metal pollution in soils. This integrated framework not only accelerates the development of metal-resistant crops but also paves the way for a new era of precision remediation, where tailored, data-driven solutions could revolutionize soil decontamination and lead to more sustainable and resilient agricultural practices.
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Today, 10:42 AM
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The global rise of antibiotic-resistant pathogens has intensified the search for alternative therapeutics. Bacteriophage-derived endolysins are emerging as promising candidates. They exhibit strong potential due to their target specificity, rapid bactericidal action, and low tendency to induce bacterial resistance. This study presents a comprehensive metagenomic analysis of the human skin phageome using 1564 samples from 10 metagenomic projects. Our analysis led to the classification of 696 phage genomes into clusters and singletons. These genomes displayed considerable variation in size, GC content (average 56%), and coding efficiency (72%). A total of 968 endolysins were identified, including 75 SAR variants, with diverse domain architectures such as CHAP, Amidase, and SH3, suggesting host-specific adaptations. Notably, we identified 37 previously unreported endolysin-derived antimicrobial peptides (AMPs), several of which exhibited nontoxic, antifungal, and antiviral properties. Molecular dynamics and docking studies revealed strong binding affinity and stability of peptides EP-464 and EP-519 to key virulence factors, including Staphylococcus epidermidis autolysin (PDB: 4EPC), beta-lactamase VIM-2 (PDB: 5O7N), and AHL synthase LasI (PDB: 1RO5). These interactions suggest potential for disrupting bacterial virulence, resistance mechanisms, and quorum sensing. This study provides the first large-scale functional characterization of the human skin phageome focused on therapeutic endolysins and their novel AMP derivatives, offering promising candidates for the development of next-generation antimicrobial agents. However, further experimental validation is essential to assess their clinical efficacy in treating skin-related infections.
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Today, 10:33 AM
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Recombinant protein production in prokaryotic systems remains a major topic in biotechnology because of their rapid growth, cost-effectiveness, and ease of genetic manipulation. However, the production of functionally active proteins still faces significant challenges due to folding failures, insolubility, and the lack of the capability of most prokaryotes for complex post-translational processing. This review dwells into both traditional and emerging strategies for optimizing recombinant protein expression in various prokaryotic systems. It also highlights recent advances in genetic engineering and synthetic biology for expanding the toolkit available for protein production, which include refined expression vectors, engineered hosts with improved folding capabilities, and high-throughput screening platforms. Additionally, it provides a thorough discussion of how to optimize heterologous expression using fusion tag approaches, codon bias elimination, promoter and ribosome binding site (RBS) engineering, and chaperone-assisted folding. This review explores diverse prokaryotic expression systems that offer unique advantages for heterologous expression that extend far beyond the limitations of traditional hosts. Additionally, this review also emphasizes the need for the selection of the right expression system and optimizing conditions to fulfill the increasing demands for recombinant protein production in various fields.
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Today, 11:30 PM
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The current state of agriculture heavily relies on chemical fertilizers and pesticides, which can negatively impact plant nutritional quality, plant health, and productivity. Additionally, abiotic stresses pose significant challenges to global agricultural productivity, threatening food security and crop sustainability. Therefore, developing and implementing sustainable alternatives to chemical fertilizers and pesticides is crucial to enhance agricultural productivity and resilience. Recent research highlights the potential of microorganisms, such as plant growth-promoting rhizobacteria (PGPR), mycorrhizal fungi, and endophytes, as sustainable solutions to improve plant resilience under abiotic stress conditions. However, challenges including scalability, ecological impacts, and the need for standardized application methods persist. This review explores novel microbial approaches to improving crop resilience against abiotic stress, focusing on how microorganisms interact with plants to mitigate stress impacts. Key mechanisms include the production of stress-alleviating compounds, enhanced nutrient uptake, and modulation of plant stress response pathways. We also examine advanced strategies in plant breeding, emphasizing CRISPR/Cas-mediated genome editing technologies as powerful tools for elucidating plant-microbe interactions. A thorough understanding of these interactions is essential for effectively applying genome editing to enhance the functional capacities of plants or associated microbes, ultimately improving key agronomic traits. This review provides a comprehensive overview of these innovative microbial approaches and their practical applications in sustainable agriculture, offering insights into future research directions, such as developing novel microbial strains and optimizing field applications.
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Today, 11:05 PM
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Modeling the conformational heterogeneity of protein–small molecule interactions is important for understanding natural systems and evaluating designed systems but remains an outstanding challenge. We reasoned that while residue-level descriptions of biomolecules are efficient for de novo structure prediction, for probing heterogeneity of interactions with small molecules in the folded state, an entirely atomic-level description could have advantages in speed and generality. We developed a graph neural network called PLACER (protein-ligand atomistic conformational ensemble resolver) trained to recapitulate correct atomic positions from partially corrupted input structures from the Cambridge Structural Database and the Protein Data Bank; the nodes of the graph are the atoms in the system. PLACER accurately generates structures of diverse organic small molecules given knowledge of their atom composition and bonding. When given a description of the larger protein context, it builds up structures of small molecules and protein side chains for protein–small molecule docking. Because PLACER is rapid and stochastic, ensembles of predictions can be readily generated to map conformational heterogeneity. In enzyme design efforts described here and elsewhere, we find that using PLACER to assess the accuracy and preorganization of the designed active sites results in higher success rates and higher activities; we obtain a preorganized retroaldolase with a kcat/KM of 11,000 M−1min−1, considerably higher than any pre–deep learning design for this reaction. We anticipate that PLACER will be widely useful for rapidly generating conformational ensembles of small molecule and small molecule–protein systems and for designing higher activity preorganized enzymes.
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Today, 6:52 PM
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Antimicrobial resistance (AMR) is a global healthcare emergency, directly causing 1.3 million deaths per year and predicted to increase dramatically over the coming decades. Understanding the molecular mechanisms underpinning antibiotic resistance is central to approaches for AMR surveillance and diagnosis in a clinical laboratory. Current antibiotic susceptibility tests are designed to detect canonical mechanisms of AMR that are functional on standard laboratory media. However, increasing evidence suggests that host and environmental factors can influence antibiotic susceptibility. In this perspective, we review known condition-dependent mechanisms of AMR and define them into four mechanistic classes: (1) Regulation of canonical AMR mechanisms by the host environment; (2) Changes to cellular respiration; (3) Increased metabolic capability; and (4) Metabolic control of tolerance and persistence. We further explore how these noncanonical AMR mechanisms can impact antibiotic susceptibility test results, and how increased mechanistic understanding might be used to optimize antibiotic therapy.
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Today, 6:39 PM
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Livestock feces contribute to approximately 32% of global methane emissions. Although ruminants are generally believed to have a higher methane production potential than non-ruminants, the dominant pathways and key regulatory processes underlying methane generation in ruminants remain poorly understood, impeding effective manure management and accurate livestock emission assessments. In this study, metagenomic and carbon isotope techniques were employed to investigate methane production potential and key pathways in sheep, pig, chicken, and duck feces. Methane production potential of ruminant sheep feces was significantly higher (approximately threefold) compared to that of non-ruminants. Isotopic analysis of methane sources revealed that sheep feces primarily produce methane through the acetoclastic pathway, whereas the other three likely rely on CO2 reduction. Metagenomic analysis of methanogenic pathways further indicated that the abundance of functional genes associated with acetoclastic methanogenesis is significantly higher in sheep feces compared to the other three. Moreover, the co-occurrence network analysis highlighted a tightly coordinated, cross-species partnership between fermentative acetogenic bacteria and methanogenic archaea in the sheep fecal microbiome. Together, our findings provide insights into some key methanogenic pathways, such as acetoclastic methanogenesis, contributing to high methane production from ruminant feces.
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Today, 3:40 PM
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Polyethylene terephthalate (PET)-hydrolyzing enzymes (PETases) are a recently discovered enzyme class capable of plastic degradation. PETases are commonly identified in bacteria; however, pipelines for discovery are often biased to recover highly similar enzymes. Here, we searched metagenomic data from hydrothermally impacted deep sea sediments in the Guaymas Basin (Gulf of California) for PETases. A broad diversity of potential proteins were identified and 22 were selected based on their potential thermal stability and phylogenetic novelty. Heterologous expression and functional analysis of these candidate PETases revealed three candidates capable of depolymerizing PET or its byproducts. One is a PETase from a Bathyarchaeia archaeon (dubbed GuaPA, for Guaymas PETase Archaeal) and two bishydroxyethylene terephthalate-hydrolyzing enzymes (BHETases) from uncultured bacteria, Poribacteria, and Thermotogota. GuaPA is the first archaeal PETase discovered that is able to depolymerize PET films and originates from a specific enzyme class which has endowed it with predicted novel structural features. Within 48 h, GuaPA released ~3–5 mM of terephthalic acid and mono-(2-hydroxyethyl) terephthalate from low crystallinity PET. PET co-hydrolysis containing GuaPA and one of the newly discovered BHETases further improves the hydrolysis of untreated PET film by 68%. Genomic analysis of the PETase- and BHETase-encoding microorganisms reveals that they likely metabolize the products of enzymatic PET depolymerization, suggesting an ecological role in utilizing anthropogenic carbon sources. Our analysis reveals a previously uncharacterized ability of these uncultured microorganisms to catabolize PET, suggesting that the deep ocean is a potential reservoir of biocatalysts for the depolymerization of plastic waste.
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Today, 3:28 PM
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The predatory bacterium Bdellovibrio bacteriovorus kills and consumes other bacteria, thrives in diverse environments and holds great potential to address major challenges in medicine, agriculture, and biotechnology. As a bacterial predator it represents an alternative to traditional antimicrobial strategies to combat multidrug-resistant bacterial pathogens and prevent food waste, while the multitude of predatory enzymes it produces have potential for biotechnological applications. However, while a limited set of genetic tools exist, the lack of secretion assays and fine-tuning of secretion constrain both fundamental studies and bioengineering of B. bacteriovorus. Here, we present a molecular toolbox for B. bacteriovorus by systematically tuning gene expression and secretion of a reporter protein. Building on functional native and synthetic promoters from the Anderson library with varying expression levels of fluorescent reporter protein mScarletI3, we evaluated different ribosomal binding sites (RBS) to fine-tune gene expression. To examine secretion, we established a novel protocol to quantify extracellular release of a Nanoluc luciferase reporter protein in B. bacteriovorus using different native Sec-dependent signal sequences. We anticipate that the newly developed genetic toolkit and techniques will advance research on this fundamental predator-prey system, laying the foundation for its broader application and future bioengineering efforts. This work will pave the way for tailored applications of B. bacteriovorus in microbial ecology, agriculture, biotechnology, and medicine.
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Today, 3:17 PM
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Major bacterial pathogens manipulate eukaryotic target cells by injecting effector proteins through type III secretion systems (T3SS). Recent in situ observations revealed that these large molecular machines, often referred to as injectisomes, are remarkably dynamic and adaptive entities, with the cytosolic T3SS components forming a mobile network that recruits effectors to the export machinery. In contrast to these soluble components, the transmembrane rings anchoring the injectisome are stably associated – with one exception. Using functional assays, live cell microscopy, and photobleaching experiments, we found that SctD, which constitutes the inner membrane ring of the T3SS, exchanges subunits in secreting injectisomes in Yersinia enterocolitica. To elucidate the biological significance of this unexpected dynamic behavior of a key structural component, we investigated its role in the assembly and function of the T3SS. Using engineered SctD variants whose exchange rate can be modulated, we found that exchange supports the integration of export apparatus components into assembled membrane rings and efficient secretion of effectors. Our findings uncover a new aspect of the molecular function and regulation of the T3SS, which may apply to other secretion systems and molecular machines. Bacteria use the type III secretion system (T3SS) to inject proteins into target cells. Here, Brianceau et al. show that a core structural component, SctD, exchanges between a T3SS-bound and a freely diffusing state in Yersinia bacteria, and that this exchange is required for assembly and function of the T3SS.
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Today, 2:05 PM
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Pan-genome analysis is a crucial method for studying genomic dynamics. By creating pan-genome maps for prokaryotic organisms, we can gain valuable insights into their genetic diversity and ecological adaptability. However, current analytical methods often struggle to balance accuracy and computational efficiency, and they tend to provide primarily qualitative results. This study introduces PGAP2, an integrated software package that simplifies various processes, including data quality control, pan-genome analysis, and result visualization. PGAP2 facilitates the rapid and accurate identification of orthologous and paralogous genes by employing fine-grained feature analysis within constrained regions. Our systematic evaluation with simulated and gold-standard datasets demonstrates that PGAP2 is more precise, robust, and scalable than state-of-the-art tools for large-scale pan-genome data. Furthermore, PGAP2 introduces four quantitative parameters derived from the distances between or within clusters, enabling detailed characterization of homology clusters. Finally, we validate our quantitative findings by applying PGAP2 to construct a pan-genomic profile of 2794 zoonotic Streptococcus suis strains. This analysis offers new insights into the genetic diversity of S. suis, thereby enhancing our understanding of its genomic structure. PGAP2 is freely available at https://github.com/bucongfan/PGAP2 . Prokaryotic pan-genome analysis is crucial for understanding microbial diversity, however current analytical methods often struggle to balance accuracy and computational efficiency. Here the authors present a more precise, robust and scalable toolkit for large-scale pan genome analysis.
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Today, 1:40 PM
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Antibiotic susceptibility tests (ASTs) often fail to predict treatment outcomes because they do not account for biofilm-specific tolerance mechanisms. In the present study, we explored alternative approaches to predict tobramycin susceptibility of Pseudomonas aeruginosa biofilms that were experimentally evolved in physiologically relevant conditions. To this end, we used four analytical methods – whole-genome sequencing (WGS), matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS), isothermal microcalorimetry (IMC) and multi-excitation Raman spectroscopy (MX-Raman). Machine learning models were trained on data outputs from these methods to predict tobramycin susceptibility of our evolved strains and validated with a collection of clinical isolates. For minimal inhibitory concentration (MIC) predictions of the evolved strains, the highest accuracy was achieved with MALDI-TOF MS (97.83%), while for biofilm prevention concentration (BPC) predictions, Raman spectroscopy performed best with an accuracy of 80.43%. Overall, all analytical methods demonstrated comparable predictive performance, showing their potential for improving biofilm AST.
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Today, 12:48 PM
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Deep learning has revolutionized biomolecular modeling, enabling the prediction of diverse structures with atomic accuracy. However, leveraging the atomic-level precision of the structure prediction model for de novo design remains challenging. Here, we present HalluDesign, a general all-atom framework for protein optimization and de novo design, which iteratively update protein structure and sequence. HalluDesign harnesses the inherent hallucination capabilities of AlphaFold3-style structure prediction models and enables fine-tune free, forward-pass only sequence-structure co-optimization. Structure conditioning at different noise level in the structure prediction stage allows precise control over the sampling space, facilitating tasks from local and global protein optimization to de novo design. We demonstrate the versatility of this approach by optimizing suboptimal structures, rescuing previously unsuccessful designs, designing new biomolecular interactions and generating new protein structures from scratch. Experimental characterization of binder design spanning small molecule, metal ion, protein, and antibody design of phosphorylation-specific peptide revealed high design success rates and excellent structural accuracy. Together, our comprehensive computational and experimental results highlight the broad utility of this framework. We anticipate that HalluDesign will further unlock the modeling and design potential of AlphaFold3-like models, enabling the systematic creation of complex proteins for a wide range of biotechnological applications.
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Today, 10:52 AM
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Nature has spent billions of years evolving the most efficient and effective solutions to complex problems, from navigation and energy harvesting to visual processing and biodegradation. Bioinspired engineering draws on these strategies to design adaptive, efficient and sustainable technologies, particularly in fields such as robotics, materials science and medical device engineering. robots typically have difficulty transversing uneven or unstable terrain, and even the most efficient bipedal robots fall behind humans in terms of energy usage. In a Review in this issue, Barbara Mazzolai and team analyse the cost of transport for different animals, plants and robotic systems to identify energy-efficient movement strategies that can inform robot design. In a Comment in this issue, Weimin Zhang and colleagues outline the design of robots that mimic these behaviours by integrating multiple sensors and using neuromorphic chips or algorithms trained on animal patterns to process sensory information for efficient navigation.
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Today, 10:38 AM
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Seaweed microbiomes are diverse and frequently species-specific. By actively attracting and repelling settling bacteria through exuded metabolites, seaweeds are thought to exert a strong selective pressure on their microbiomes. However, to what degree seaweed-associated bacteria are adapted to their host has received little attention. Here, we retrieve cultivable seaweed bacterial communities from Palmaria palmata (Dulse) and Fucus serratus (Serrated Wrack) and use reciprocal transplant experiments to test whether bacterial isolates have the greatest fitness on their host seaweed species. We used agar derived from host seaweed extracts for bacterial isolation, which was found to be superior to a generic marine agar formulation based on both 16S rRNA gene amplicon alpha- and beta-diversity comparisons to uncultured samples. We then demonstrate that bacterial isolates from both seaweed species exhibit higher fitness in media derived from their native host compared to a non-native host. Although epibacterial fitness varied between hosts, bacterial isolates on average outperformed non-native counterparts in their native environment. By integrating amplicon sequencing with laboratory experiments, we demonstrate that bacteria are locally adapted to their seaweed host species. These findings contribute to the growing body of research exploring the evolutionary and ecological drivers that shape bacterial communities, with implications for ecosystem management, disease control and microbial biotechnology.
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wonder how this luciferase works in microbes and plants. What is the minimum conc. of AkaLumine (substrate) for luminescence?