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At least 19 recordsLinked to original sources
PubMed2026

Upcycling Vegetable Waste Into Functional Food Ingredients via Synergistic Microbial Engineering and Artificial Intelligence.

The escalating generation of global vegetable waste represents a critical loss of bioactive resources, necessitating a paradigm shift from passive disposal to active nutrient upcycling. However, the industrial conversion of this heterogeneous biomass into standardized functional food ingredients is currently impeded by significant techno-economic barriers, primarily structural recalcitrance, compositional inconsistency, and the presence of toxic fermentation inhibitors. This review provides a comprehensive analysis of the synergistic application of microbial engineering and artificial intelligence (AI) to resolve these bioprocessing bottlenecks within a food-to-food closed-loop framework (as shown in the graphical abstract). We evaluate recent advances in engineering food-grade microbial chassis (e.g., Saccharomyces cerevisiae and Escherichia coli) to enhance lignocellulose degradation and stress tolerance. Concurrently, we examine the integration of AI across the entire value chain, covering deep learning-based rational enzyme design, genome-scale metabolic modeling, and intelligent process control for precision fermentation. Current evidence demonstrates that the hardware-software coupling of engineered strains and AI algorithms significantly enhances conversion efficiency and process robustness. Key findings highlight that AI-driven Design-Build-Test-Learn cycles facilitate the de novo creation of enzymes with superior kinetics and strains with adaptive stress response capabilities against toxins. Moreover, dynamic digital twin models effectively mitigate the impact of substrate variability, ensuring the batch-to-batch consistency required for food applications. We conclude that this data-driven synergistic paradigm is pivotal for establishing a resilient circular bioeconomy, enabling the reliable bioconversion of waste into high-value single-cell proteins, natural flavor additives, and sustainable packaging materials.

Artificial Intelligence↗
PubMed2025

Exploring genetic adaptation and microbial dynamics in engineered anaerobic ecosystems via strain-level metagenomics.

Genetic heterogeneity exists within all microbial populations, with sympatric cells of the same species often exhibiting single-nucleotide variations that influence phenotypic traits, including metabolic efficiency. However, the evolutionary dynamics of these strain-level differences in response to environmental stress remain poorly understood. Here, we present a first-of-its-kind study tracking the adaptive evolution of an anaerobic, carbon-fixing microbiota under a controlled engineered ecosystem focused on carbon dioxide bioconversion into methane. Leveraging strain-resolved metagenomics with an ad hoc variant calling and phasing approach, we mapped mutation trajectories and observed that the two dominant Methanothermobacter species maintained distinct sweeping haplotypes over time, most likely due to niche-specific metabolic roles. By combining population genetic statistics and peptide reconstruction, mer and mcrB genes emerged as potential drivers of archaeal strain-level competition. These findings pave the way for targeted engineering of microbial communities to enhance bioconversion efficiency, with significant implications for sustainable energy and carbon management in anaerobic systems.

Metagenomics↗
PubMed2025

Boolean matrix logic programming for active learning of gene functions in genome-scale metabolic network models.

Reasoning about hypotheses and updating knowledge through empirical observations are central to scientific discovery. In this work, we applied logic-based machine learning methods to drive biological discovery by guiding experimentation. Genome-scale metabolic network models (GEMs) - comprehensive representations of metabolic genes and reactions - are widely used to evaluate genetic engineering of biological systems. However, GEMs often fail to accurately predict the behaviour of genetically engineered cells, primarily due to incomplete annotations of gene interactions. The task of learning the intricate genetic interactions within GEMs presents computational and empirical challenges. To efficiently predict using GEM, we describe a novel approach called Boolean Matrix Logic Programming (BMLP) by leveraging Boolean matrices to evaluate large logic programs. We developed a new system, [Formula: see text], which guides cost-effective experimentation and uses interpretable logic programs to encode a state-of-the-art GEM of a model bacterial organism. Notably, [Formula: see text] successfully learned the interaction between a gene pair with fewer training examples than random experimentation, overcoming the increase in experimental design space. [Formula: see text] enables rapid optimisation of metabolic models to reliably engineer biological systems for producing useful compounds. It offers a realistic approach to creating a self-driving lab for biological discovery, which would then facilitate microbial engineering for practical applications.

Active learning↗
PubMed2026

Cross-Kingdom Siderophores: Biosynthesis, Ecology, and Biotechnological Applications.

Microbial siderophores are high-affinity iron-binding compounds which are produced by bacteria, fungi, and actinomycetes to obtain iron and survive and interact with different species in an iron-deficient environment. While the conventional research on siderophore systems deals mainly with the study within the same taxa, modern researchers have increased their inclination toward cross-kingdom integration of siderophore behavior and their impact on host-associated environments. This can be largely attributed to differences in biosynthetic gene clusters, receptor systems, and regulatory networks, which produce distinct genotype-to-phenotype results determining microbial cooperation and competition. Current advancements in genomic research, together with omics studies like transcriptomics, proteomics, and metabolomics, have created newer insights into how siderophores function. However, the present literature evidences multiple major gaps in multi-omics data because the link between genomes and metabolomes remains weak due to inconsistent regulatory data sets and failure in identifying producer-consumer relationships in polymicrobial systems. Additionally, major constraints like molecular instability, delivery system limitations, host toxicity, limitations in upscaling, and regulatory issues delimit the use of siderophores in medical treatment, agricultural practices, and environmental biotechnology. This review aims to bridge the existing knowledge about siderophore biochemistry, biosynthesis, ecological functions, and genetic regulation across kingdoms while integrating multi-omics outlook with translational considerations. Thus, by connecting molecular mechanisms with evolutionary cross-talk, this study aims to provide a system-level framework in the world of siderophore-mediated iron uptake and therefore shapes future directions in emerging fields of microbial engineering, precision therapies, and sustainable biotechnology.

Fur regulation↗
PubMed1992

Biological control of chestnut blight: an example of virus-mediated attenuation of fungal pathogenesis.

Environmental concerns have focused attention on natural forms of disease control as potentially safe and effective alternatives to chemical pesticides. This has led to increased efforts to develop control strategies that rely on natural predators and parasites or that involve genetically engineered microbial pest control agents. This review deals with a natural form of biological control in which the virulence of a fungal pathogen is attenuated by an endogenous viral RNA genetic element: the phenomenon of transmissible hypovirulence in the chestnut blight fungus, Cryphonectria parasitica. Recent progress in the molecular characterization of a hypovirulence-associated viral RNA has provided an emerging view of the genetic organization and basic expression strategy of this class of genetic elements. Several lines of evidence now suggest that specific hypovirulence-associated virus-encoded gene products selectively modulate the expression of subsets of fungal genes and the activity of specific regulatory pathways. The construction of an infectious cDNA clone of a hypovirulence-associated viral RNA represents a major advancement that provides exciting new opportunities for examining the molecular basis of transmissible hypovirulence and for engineering hypovirulent strains for improved biocontrol. These developments have significantly improved the prospects of using this system to identify molecular determinants of virulence and elucidate signal transduction pathways involved in pathogenic responses. In addition, novel approaches are now available for extending the application of transmissible hypovirulence for management of chestnut blight and possibly other fungal diseases.

Genes, Fungal↗
PubMed1985

Potential food safety problems in genetic engineering.

The rapid development of gene technology, exemplified by the recombinant DNA technique and the hybridoma technique, will heavily influence our food supply in the years to come. Fermentation products from genetic-engineered microbials, the microbials themselves and new plant products will create a number of questions concerning the possible pathogenicity, toxicity, and changed nutritional values of such foodstuffs. This is a great challenge not only to the development of new approaches in nutritional toxicology but also to international cooperation in the field because genetic-modified organisms are not expected to recognize human-made trade barriers or borders. Therefore the initiative of OECD establishing an ad hoc group on safety and regulations in biotechnology is greatly acknowledged.

DNA, Recombinant↗
PubMed1989

A sandwich CD7-ELISA for detection of solubilized CD7 from normal and leukemic T cells.

CD7 is a T differentiation antigen which is useful in the identification of precursor T cells as well as an important marker for the identification of leukemic T cells. It has proved to be useful as a target for immunotherapy by immunotoxins in several clinical settings. Most monoclonal antibodies to this antigen bind to the same or similar epitope. We have produced a monoclonal antibody, 69, which identifies a different epitope as that of the prototypic mAb to CD7, 3A1. Using mAB 69, we have devised a sandwich CD7-ELISA to detect solubilized CD7 antigen, with mAb 69 in the solid phase as the capturing mAb. This assay is sensitive and is able to detect antigen present on 2-5 x 10(4) activated T cells. This assay has been used to study the fate of CD7 on the membrane and in the cytosol of T cells during the process of mitogenesis. We have also utilized this assay to demonstrate the presence of free CD7 antigen in culture supernatant of activated T cells. This method will be useful to analyze antigen recovery from bulk cell cultures or from molecularly engineered microbial organisms. In addition, the sandwich CD7-ELISA may prove useful in monitoring the effects of immunotherapy in patients with leukemia.

Antibodies, Monoclonal↗
PubMed2026

Investigating cross-organism prediction of prokaryotic essential proteins using unsupervised language model and ensemble strategy.

Cross-organism prediction of essential proteins is a critical task for drug discovery and microbial engineering, yet the generalizability of existing machine learning models across diverse species remains a significant challenge. In this study, we propose DeepPEP, a large language model-based framework designed to reliably transfer essential protein annotations between distantly related organisms. Utilizing 66 curated prokaryotic datasets, we systematically evaluated DeepPEP's cross-organism performance under various conditions. Initial pairwise predictions revealed a correlation between performance and evolutionary distance; however, further investigation demonstrated that integrating training data from multiple organisms yields superior predictive power. In a benchmark scenario designed to simulate real-world applications, DeepPEP outperformed the state-of-the-art tool Geptop 2.0, showcasing a robust ability to identify species-specific essential proteins. Finally, a case study on novel genomes confirmed the model's practical effectiveness. Our results suggest that DeepPEP is a powerful strategy for prokaryotic essential protein prediction, and the rigorous evaluation framework established in this study provides a new benchmark for the field.

Large Language Models↗
PubMed2024

Strategies in engineering sustainable biochemical synthesis through microbial systems.

Growing environmental concerns and the urgency to address climate change have increased demand for the development of sustainable alternatives to fossil-derived fuels and chemicals. Microbial systems, possessing inherent biosynthetic capabilities, present a promising approach for achieving this goal. This review discusses the coupling of systems and synthetic biology to enable the elucidation and manipulation of microbial phenotypes for the production of chemicals that can substitute for petroleum-derived counterparts and contribute to advancing green biotechnology. The integration of artificial intelligence with metabolic engineering to facilitate precise and data-driven design of biosynthetic pathways is also discussed, along with the identification of current limitations and proposition of strategies for optimizing biosystems, thereby propelling the field of chemical biology towards sustainable chemical production.

Metabolic Engineering↗
PubMed1991

Ecologically significant effects of Pseudomonas putida PPO301(pRO103), genetically engineered to degrade 2,4-dichlorophenoxyacetate, on microbial populations and processes in soil.

Pseudomonas putida PPO301 (pRO103), genetically engineered to degrade 2,4-dichlorophenoxyacetate, affected microbial populations and processes in a nonsterile xeric soil. In soil amended with 2,4-dichlorophenoxyacetate (500 micrograms/g soil) and inoculated with PPO301 (pRO103), the rate of evolution of carbon dioxide was retarded for approximately 35 days; there was a transient increase in dehydrogenase activity; and the number of fungal propagules decreased below detection after 18 days. In unamended soil inoculated with PPO301(pRO103), the rate of evolution of carbon dioxide and the dehydrogenase activity were unaffected, and the numbers of fungal propagules were reduced by about two orders of magnitude. The numbers of total, spore-forming, and chitin-utilizing bacteria were reduced transiently in soil either amended or unamended with 2,4-dichlorophenoxyacetate and inoculated with PPO301(pRO103). The activities of arylsulfatases and phosphatases in soil were not affected by the presence of PPO301(pRO103), either in the presence or absence of 2,4-dichlorophenoxyacetate. In soil amended with 2,4-dichlorophenoxyacetate and inoculated with the parental strain (PPO301) or not inoculated, the evolution of carbon dioxide, the numbers of fungal propagules and of total, spore-forming, and chitin-utilizing bacteria, and the dehydrogenase activity were not affected as in soil inoculated with PPO301(pRO103). These results demonstrated that a genetically engineered microorganism, in the presence of the substrate on which its novel genes can function, is capable of inducing measurable ecological effects in soil.

2,4-Dichlorophenoxyacetic Acid↗
PubMed2024

Tapping the treasure trove of atypical phages.

With advancements in genomics technologies, a vast diversity of 'atypical' phages, that is, with single-stranded DNA or RNA genomes, are being uncovered from different ecosystems. Though these efforts have revealed the existence and prevalence of these nonmodel phages, computational approaches often fail to associate these phages with their specific bacterial host(s), while the lack of methods to isolate these phages has limited our ability to characterize infectivity pathways and new gene function. In this review, we call for the development of generalizable experimental methods to better capture this understudied viral diversity via isolation and study them through gene-level characterization and engineering. Establishing a diverse set of new 'atypical' phage model systems has the potential to provide many new biotechnologies, including potential uses of these atypical phages in halting the spread of antibiotic resistance and engineering of microbial communities for beneficial outcomes.

Bacteriophages↗
PubMed2025

Genomically integrated cassettes swapping: bringing modularity to the strain level in Saccharomyces cerevisiae.

A large variety of synthetic biology toolkits for the introduction of multiple expression cassettes is available for Saccharomyces cerevisiae. Unfortunately, none of these tools is designed to allow the modification - exchange or removal - of the cassettes already integrated into the genome in a standardized way. The application of the modularity principle therefore ends to the steps preceding the final host engineering, making microbial cell factories construction stiff and strictly sequential. In this work, we describe a system that easily allows CRISPR-mediated swapping or removal of previously integrated cassettes, thus bringing the modularity to the strain level, enhancing the possibility of modifying existing strains with a reduced number of steps. In the system, each cassette is tagged with specific barcodes, which can be used as targets for CRISPR nucleases (Cas9 and Cas12a), allowing the excision of the construct from the genome and its substitution with another expression cassette or the restoration of the wild type locus in one single standardized step. The system has been applied to the previously developed Easy-MISE toolkit and tested by swapping fluorescent protein expression cassettes with an efficiency of ∼90% quantified by PCR and flow cytometry.

Saccharomyces cerevisiae↗
PubMed1986

Production of new hybrid antibiotics, mederrhodins A and B, by a genetically engineered strain.

Hybrid antibiotics mederrhodins A and B were produced by a recombinant strain consisting of the medermycin-producing Streptomyces sp. strain AM7161 containing part of the gene clusters for actinorhodin biosynthesis of Streptomyces coelicolor A3(2). Mederrhodin A has a hydroxyl group at the C-6 position of the medermycin molecule, and mederrhodin B is dihydromederrhodin A. The antimicrobial activity of mederrhodin A resembled that of medermycin. Mederrhodin B was almost devoid of antimicrobial activity.

Anti-Bacterial Agents↗
PubMed1987

Problems and potential for in situ treatment of environmental pollutants by engineered microorganisms.

Molecular microbial ecology could provide tools for studying the structure and function of biodegradative microbial communities useful for in situ removal of environmental pollutants. Detection and monitoring of released organisms in the environment is required and DNA:DNA colony hybridization seems to be one of the highly sensitive and accurate technologies available for achieving this goal. A realistic and pragmatic view is required for analysis of the risks of environmental release of genetically-modified or engineered organisms.

Bacteria↗
PubMed2026

Optimizing eco-engineering pedogenesis of bauxite residues: Synergistic effects of humus and FeSO4/sulfur on microbial community and function.

Eco-engineered pedogenesis represents a promising approach for soil amelioration of bauxite residues (BRs) through exogenous organic matter. However, the role of humus in mediating this process remains poorly understood, significantly impeding the eco-engineering rehabilitation of BRs. In this study, we conducted pot experiments and subsequent microbial analysis to evaluate the individual improvement of humic acid (HA), fulvic acid (FA), and corn straw (SWZ) on the BRs' pedogenesis. High-throughput sequencing analysis revealed that both FA and SWZ were more effective than HA in steering microbial community assembly, as community diversity, dominant taxa enrichment, and species' interaction were all significantly higher (p < 0.05) in the FA/SWZ treatments than in HA treatments. Notably, the combination of FA with FeSO4 specifically enriched halophilic taxa, while FA coupled with sulfur (S) significantly improved the connectivity and complexity of the microbial network, as the average connection degree increasing from 1.008 to 1.113. Hydrolytic enzyme activity assays further indicated that FA, especially when combined with S, was the most effective treatment in restoring microbial function during BR pedogenesis. These findings highlight FA as a critical driver of microbial restructuring and functional recovery in BRs. Moreover, its efficacy can be enhanced by co-amendment with FeSO4 or S. This study provides important theoretical and practical insights for optimizing organic-inorganic amendment strategies to accelerate the eco-engineering pedogenesis of bauxite residues.

Humic Substances↗
PubMed2026

Enhancing the fiber degradation efficiency in dairy cattle rumen through engineered bacterial communities.

BACKGROUND: The rumen functions as an anaerobic fermentation chamber, housing microorganisms with cellulolytic and proteolytic capabilities that facilitate feed utilization. Fiber-degrading bacteria possess the capability to enhance the productivity of cellulolytic feed. The application of omics technologies has greatly improved our understanding of the rumen microbiome. Determining microbial composition and functional patterns in the rumen does not equate to a comprehensive exploration of rumen microbial resources and their mechanisms of action. This study seeks to integrate high throughput 16S rRNA data with information on culturomics, cellulolytic activities, nutrition, and synthetic microbial communities (SynCom) engineering. The objective is to evaluate the relationship between rumen microbial activity and fiber utilization efficiency in cattle, ultimately aiming to develop a more powerful intervention strategy for the ruminant industry. RESULTS: The enrichment culture with various carbon sources led to significant alterations in the composition and structure of rumen microbiota, particularly enhancing those associated with carbohydrate metabolism. Employing the culturomics methodology, 896 strains from 78 species (including 8 novel species) were isolated, resulting in a 10.1% isolation rate relative to the rumen bacterial community. Among them, 35 strains demonstrated boosted cellulose-degrading capability on plates, while 25 exhibited the ability to degrade hemicellulose as well. SynComs of these candidates were prepared based on the ratio observed in rumen microbiota exhibiting high cellulolytic performance. SynCom&#xa0;3 improved the neutral detergent fiber degradation (NDFD) by 20.39%&#xa0;averagely. Additionally, both in vitro and in situ assessments indicated that the optimization of dose/strain in SynCom&#xa0;3 significantly improved the in vitro NDFD by 20.56% and increased the in situ NDFD by 7.81%, along with the acidic detergent fiber (ADF,&#xa0;+&#x2009;11.47%). Genomic analysis revealed that the SynCom&#xa0;3 functioned well in fiber degradation through the synergistic action of key carbohydrate-active enzymes. CONCLUSIONS: This study strengthens rumen microbiome research by integrating omics and SynCom engineering within a microbiota-bacteria-enzymes-genes framework, revealing the significance of enzymatic synergy in carbohydrate metabolism. The findings establish a framework for utilizing low-abundance microbes and engineering functional consortia, which are crucial for improving ruminant feed utilization and biomass conversion. Future research should investigate the transcriptomic profiles and the metabolic cross-feeding mechanisms of fiber-degrading strains in the rumen. Video Abstract.

Animals↗
PubMed2026

Microbial diversity: the essential foundation for life on our planet.

The biological basis of life on Earth is microbial diversity that ensures human health, agricultural productivity, ecological balance, and ecosystem functioning. Microorganisms enable ecosystem restoration through bioremediation, maintain soil fertility, support plant growth, manage vital biogeochemical cycles, and contribute to climate resilience. Precision probiotics, postbiotics, faecal microbiota transplantation, and personalized microbiome medicine are the examples of emerging microbiome-based therapies that offer promising therapeutic opportunities. In humans, the gut microbial community is essential for immune regulation, metabolism, and disease prevention. In terrestrial ecological systems, interactions between plants, fungi, bacteria, and other soil microorganisms improve carbon sequestration, nutrient cycling, stress resilience, and sustainable agricultural productivity in the given effects of climate change. Emerging uses in agriculture, environmental restoration, and medicine are made possible by advancements in multi-omic techniques, synthetic microbial genomes, microbiome engineering, and artificial intelligence. Considering these developments, issues with ecological complexity, long-term validation, standardization, and field scale application still exist. Therefore, preserving microbial diversity is important for conserving ecological resilience and strengthening the One Health framework, which highlights the mutual dependance of health of animal, human, plant, and environment. This review summarizes what has been discovered about ecological and biomedical relevance of microbiome, identifies important research gaps, highlighting emerging technologies, and evaluates potential future directions for using microbiome to support planetary sustainability.

Bioremediation↗