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PubMed2024

Accessing and exploring the unusual chemistry by radical SAM-RiPP enzymes.

Radical SAM enzymes involved in the biosynthesis of ribosomally synthesized and post-translationally modified peptides catalyze unusual transformations that lead to unique peptide scaffolds and building blocks. Several natural products from these pathways show encouraging antimicrobial activities and represent next-generation therapeutics for infectious diseases. These systems are uniquely configured to benefit from genome-mining approaches because minimal substrate and cognate modifying enzyme expression can reveal unique, chemically complex transformations that outperform late-stage chemical reactions. This report highlights the main strategies used to reveal these enzymatic transformations, which have relied mainly on genome mining using enzyme-first approaches. We describe the general biosynthetic components for rSAM enzymes and highlight emerging approaches that may broaden the discovery and study of rSAM-RiPP enzymes. The large number of uncharacterized rSAM proteins, coupled with their unpredictable transformations, will continue to be an essential and exciting resource for enzyme discovery.

S-Adenosylmethionine↗
PubMed2025

Logical Exploration of Cinnamoyl-Containing Nonribosomal Peptides via Metabologenomic Targeting and Regulator Overexpression.

A targeted method for discovering cinnamoyl-containing nonribosomal peptides (CCNPs), a unique class of bioactive compounds, was devised by using cinnamoyl isomerase, a key enzyme in the biosynthesis of the cinnamoyl moiety, as a genome mining probe. A total of 39 hit strains were obtained, including 35 from polymerase chain reaction-based screening of the in-house bacterial library (2.5% of 1400 strains) targeting the cinnamoyl isomerase-encoding gene and 4 from the genome mining of online databases. Sequence similarity networking and phylogenetic analyses of the isomerase amplicons (∼530 bp) classified the CCNPs into three major substructure-based groups (Z-, E-, and M-type CCNPs) and revealed distinct clade-structure relationships (13 clades). To overcome the challenge of silent biosynthetic gene clusters, we activated these clusters by overexpressing conserved cluster-situated LuxR regulators combined with extensive culture optimization. CCNP production was metabolomically detected in the bacterial extracts by using the characteristic UV absorption and MS/MS fragments of cinnamoyl moieties. CCNP production was observed in 20 of the 39 hit strains, resulting in the isolation of 6 new CCNPs, including oxy-skyllamycin B (2), gwanacinnamycin (3), and luxocinnamycins A-D (4-7), with high structural novelty. Their structures were elucidated using comprehensive spectroscopic analyses and multiple-step chemical derivatizations, and the putative biosynthetic pathways were bioinformatically proposed. Gwanacinnamycin (3) exhibited significant antimycobacterial activity, whereas luxocinnamycin A (4) displayed moderate antiproliferative activity against stomach cancer cells. Our findings highlight a targeted metabologenomic approach combined with transcriptional regulator overexpression as a logical and efficient platform for the discovery of bioactive compounds from nature.

Peptides↗
PubMed2026

Accessing Underexplored Biosynthetic Potential by Initiation Unit Engineering of Nonribosomal Peptide Synthetases in Proteobacteria.

Nonribosomal peptide synthetases (NRPSs) represent a valuable yet underexplored resource for producing bioactive natural products. However, most NRPSs remain silenced potentially due to factors such as dysfunction of the initiation unit. The starter condensation (Cs) domain of the initiation unit catalyzes the lipoinitiation of nonribosomal peptides via the incorporation of an N-terminal fatty acyl chain. The concept of initiation unit engineering introduced herein encompasses the replacement of the native initiation unit of NRPSs with a foreign and well-characterized Cs domain-containing initiation unit to activate the NRPS and optimize its expression. This strategy was employed herein to successfully access three of the six previously silent NRPS pathways in Mycetohabitans rhizoxinica HKI 454, a bacterium of the class β-proteobacteria, resulting in the identification of three classes of lipopeptides. This strategy was then extended to access two NRPS pathways in Pseudomonas syringae (γ-proteobacteria) and obtain novel lipopeptides, thereby establishing a feasible complement to existing genome mining strategies for natural product discovery. Furthermore, change of the initiation regions of biosynthetic pathways of nonlipidated chitinimide (β-proteobacteria) and pseudotetraivprolide (γ-proteobacteria) with heterologous Cs-containing initiation units enabled the successful incorporation of fatty acyl chains into the N-terminus of both peptide backbones, launching a workable approach to create artificial lipopeptides. Overall, this study provides a practical strategy for the rational recovery of silent BGCs and introduction of fatty acyl chains into nonribosomal peptides, at least in Proteobacteria, thereby enriching genome mining and combinatorial biosynthesis approaches for accessing the underexplored biosynthetic potential of NRPSs from various bacteria.

Proteobacteria↗
PubMed2026

Nerpa 2: probabilistic linking of biosynthetic gene clusters to nonribosomal peptides.

MOTIVATION: Nonribosomal peptides (NRPs) are bioactive microbial metabolites with high pharmaceutical potential. Although genome mining enables large-scale detection of biosynthetic gene clusters (BGCs) predicted to encode NRPs, reliably linking these clusters to their chemical products remains challenging due to the flexible and heterogeneous organization of NRP assembly pathways. RESULTS: We present Nerpa 2, a probabilistic framework for accurate and scalable linking of NRP BGCs to candidate chemical structures. The method represents assembly lines as hidden Markov models (HMMs) that capture uncertainty and alternative biosynthetic routes. On curated datasets of experimentally validated BGC-product pairs, our tool outperforms existing methods in linking accuracy and pathway reconstruction. When applied to large genome mining datasets, Nerpa 2 efficiently identifies BGCs likely associated with known compounds and highlights potential producers of novel chemistry. AVAILABILITY AND IMPLEMENTATION: Nerpa 2 is freely available at https://github.com/gurevichlab/nerpa.

Multigene Family↗
PubMed2025

Genome-Wide Mining of lncRNAs Reveals Their Potential Regulatory Role in the Evolution of Viviparity.

Reproduction in vertebrates usually involves egg-laying (oviparity) or live-bearing (viviparity). Oviparity is the ancestral trait from which viviparity has independently evolved more than 100 times in squamate reptiles. This transition involves a series of physiological and structural changes, including the degeneration of eggshell and the evolution of a placenta and differences in the temporal and spatial expression patterns of some functional genes that drive the structural transformation. Long non-coding RNAs (lncRNAs) play important roles in the regulation of gene expression, yet it remains unclear whether they participate in gene expression shifts during the transition from oviparity to viviparity, and if so how. Therefore, we employ deep mining to identify novel lncRNAs of a closely related oviparous-viviparous pair of lizards (Phrynocephalus przewalskii and P. vlangalii). We construct cis- and trans-regulatory networks between lncRNAs and target genes using the transcriptomic data of oviduct or uteri tissues across reproductive periods. Results show that lncRNAs that regulate eggshell gland developmental genes in the oviparous lizard are lost or less expressed in the viviparous lizard. A number of lncRNAs involved in the regulation of placental development and embryo attachment in viviparous species have no orthologs in oviparous species, and others show little or no expression. Accordingly, lncRNAs may play important regulatory roles in the physiological and structural changes in the transition from oviparity to viviparity. These results open doors to the further elucidation of genetic regulatory networks.

Animals↗
PubMed2026

The Computational Revolution in Natural Product Research: A Data-Driven Roadmap for Next-Generation Drug Development.

Natural products (NPs) have historically provided the foundational scaffolds for drug development, yet traditional bioprospecting faces critical limitations: high rediscovery rates, laborious isolation workflows, and substantial attrition during clinical translation. The emergence of big data technologies is fundamentally transforming this landscape, enabling a shift from serendipity-based discovery toward systematic, data-driven approaches. This review examines how the integration of artificial intelligence (AI), machine learning (ML), and multi-omics datasets is accelerating natural product research across three key domains: (1) genome mining for biosynthetic gene cluster identification using platforms such as antiSMASH, (2) cheminformatics-driven prediction of structure-activity relationships and ADMET properties, and (3) metabolomics-guided dereplication to prioritize novel bioactive scaffolds. We evaluate the convergence of genomics, metabolomics, and computational chemistry in enabling in silico lead optimization and the discovery of cryptic metabolites from previously inaccessible microbial taxa. While challenges in data standardization and scalability persist, the synergy between big data and NP research is accelerating clinical translation. Despite persistent challenges in data standardization, scalability, and equitable benefit-sharing, the convergence of big data and NP research is poised to redefine drug development. These advances position computational NP research as a cornerstone of next-generation drug development.

big data analytics↗
PubMed2025

South African Myxococcota: an untapped resource for microbial ecolo gy and biotechnology.

An extraordinary multicellular life cycle, ecological versatility, and prolific production of bioactive secondary metabolites characterise the phylum Myxococcota. While research has predominantly focused on Myxococcota in Asia, Europe, and North America, their potential occurrence in Sub-Saharan Africa remains largely unexplored. To date, only one study has isolated Myxococcota in South Africa, with additional findings limited to incidental detection through metagenomic studies. Considering South Africa's ecological diversity, its biomes may represent promising but under-examined environments for systematic bioprospecting aimed at discovering novel Myxococcota with ecological or biotechnological potential. The recent reclassification of Myxococcota from the former Deltaproteobacteria has provided a more coherent taxonomic framework to guide future ecological and systematic studies. This review presents an overview of the taxonomic revision and explores the potential occurrence of Myxococcota in South African biomes. It covers the challenges associated with conventional culture-based isolation methods and highlights potential genome- and metagenome-based approaches, including the use of metagenome-assembled genomes (MAGs) to identify cryptic biosynthetic gene clusters (BGCs), while acknowledging current limitations. Considering the increasing resistance to chemical fungicides in South African agriculture, this review further explores the potential of Myxococcota-derived secondary metabolites as candidate bioprotective alternatives. By identifying current research gaps, it aims to support future efforts towards systematic bioprospecting to investigate the ecological and biotechnological potential of Myxococcota in South Africa. KEY POINTS: • South African biomes may harbour novel Myxococcota with biosynthetic potential. • Genome mining could reveal cryptic biosynthetic gene clusters (BGCs). • Myxococcota metabolites may help control resistant fungal phytopathogens.

South Africa↗
PubMed2026

Molecular biology and integrated strategies for activating cryptic biosynthetic gene clusters toward next-generation antibiotic discovery.

Antimicrobial resistance (AMR) has been identified as one of the 21st century's severest global public health crises. AMR led to an estimated 4.95 million deaths in 2019 and will claim 10 million lives a year by 2050 in the absence of targeted interventions. During the same period, the number of novel antibiotics discovered has decreased drastically as many researchers are rediscovering known antibiotics, non-model microorganisms are poorly understood or difficult to culture and antibiotic research and development investment has declined drastically. However, high-throughput whole genome sequencing and the subsequent application of bioinformatics in bacterial and fungal genomes have shown that a numerous of cryptic or silent biosynthetic gene clusters (BGCs) remain latent at ambient laboratory conditions since their genes are transcriptionally inactive. Cryptic BGCs represent a vast source of unique secondary metabolites, many of which may yield novel antibacterial, antifungal, anti-cancer and other potentially valuable natural products. This review discusses the biological relevance of cryptic BGCs, the major limiting factors that restricts their activation and novel strategies that have been employed to activate them and exploit their potential to produce novel natural products. The review focuses on biological approaches including CRISPR-Cas mediation for the activation of cryptic BGCs, promoter engineering, pathway refactoring, and heterologous expression; biochemical strategies such as Osman, OsMAC, Precursor Feeding, Chemical Elicitation, Epigenetic Regulation and Co-cultivation and technology-based strategies such as Genome mining, Microfluidic Cultivation systems, High-Throughput Screening, Metabolomics, Molecular Networking and Artificial Intelligence and Machine Learning based prediction of BGCs and their metabolites. The use of multi-omics technologies combined with synthetic biology to achieve better discovery, characterization and large-scale production of novel natural products is also discussed herein. Finally, we will talk about the ecological significance and evolutionary advantage of cryptic BGCs' role in interactions between microorganisms, such as competition, communication, symbiosis and environmental adaptability, so as to provide a useful background for accelerating next-generation antibiotics.

CRISPR-Cas activation↗
PubMed2026

Unveiling Aziridine-Containing Natural Products by Genomic and Spectroscopic Approaches.

Aziridine-containing natural products are prized for their potent bioactivities, yet their scarcity and poorly understood biosynthesis have limited systematic exploration. Here, we address this by integrating genome mining with a 1H-13C coupled HSQC metabolomic approach that exploits the distinctive NMR signatures of aziridines, enabling their direct detection from complex extracts. This strategy unveiled the desertolides, the first macrolides incorporating a rare terminal 2-methyl-aziridine-2-carboxylate moiety. Genetic and isotopic studies identified a dedicated biosynthetic subcluster (desA-desN) that assembles and installs this unit from glutamate, and heterologous expression confirmed the self-sufficiency of this subcluster. Direct MS evidence reveals the aziridine moiety covalently bound to the active-site Cys113 of DesN, establishing this KAS III homolog as the first dedicated aziridine-transferase and a promising tool for polyketide engineering. Bioinformatic analysis uncovered over 50 biosynthetic gene clusters, suggesting that this aziridine-associated biosynthetic logic may be more widespread than currently appreciated. This work establishes a tractable platform for the targeted discovery and engineered biosynthesis of aziridine-containing natural products, opening this underexplored pharmacophore to systematic interrogation.

Aziridines↗
PubMed2024

Activity, structure, and diversity of Type II proline-rich antimicrobial peptides from insects.

Apidaecin 1b (Api), the first characterized Type II Proline-rich antimicrobial peptide (PrAMP), is encoded in the honey bee genome. It inhibits bacterial growth by binding in the nascent peptide exit tunnel of the ribosome after the release of the completed protein and trapping the release factors. By genome mining, we have identified 71 PrAMPs encoded in insect genomes as pre-pro-polyproteins. Having chemically synthesized and tested the activity of 26 peptides, we demonstrate that despite significant sequence variation in the N-terminal sequence, the majority of the PrAMPs that retain the conserved C-terminal sequence of Api are able to trap the ribosome at the stop codons and induce stop codon readthrough-all hallmarks of Type II PrAMP mode of action. Some of the characterized PrAMPs exhibit superior antibacterial activity in comparison with Api. The newly solved crystallographic structures of the ribosome complexed with Api and with the more active peptide Fva1 from the stingless bee demonstrate the universal placement of the PrAMPs' C-terminal pharmacophore in the post-release ribosome despite variations in their N-terminal sequence.

Animals↗
PubMed2025

Genomes of 211 Actinomycete Strains from Diverse Environments.

Actinomycetes are a highly diverse group of microorganisms that have long been recognized as a valuable source of antibiotics and other bioactive metabolites. Recent advances in genome mining have revealed a wealth of previously unexplored silent secondary metabolite biosynthetic gene clusters (smBGCs) in actinomycete genomes, underscoring their untapped bioactivity potential. Here, we present the genome sequences of 211 actinomycete strains isolated from various environmental sources, generated through high-throughput sequencing. The resulting genome assemblies exhibit high completeness and accuracy, offering high-quality data for downstream analyses and biological resource exploration.

Actinobacteria↗
PubMed2024

Neobacillus driksii sp. nov. isolated from a Mars 2020 spacecraft assembly facility and genomic potential for lasso peptide production in Neobacillus.

UNLABELLED: During microbial surveillance of the Mars 2020 spacecraft assembly facility, two novel bacterial strains, potentially capable of producing lasso peptides, were identified. Characterization using a polyphasic taxonomic approach, whole-genome sequencing and phylogenomic analyses revealed a close genetic relationship among two strains from Mars 2020 cleanroom floors (179-C4-2-HS, 179-J1A1-HS), one strain from the Agave plant (AT2.8), and another strain from wheat-associated soil (V4I25). All four strains exhibited high 16S rRNA gene sequence similarity (>99.2%) and low average nucleotide identity (ANI) with Neobacillus niacini NBRC 15566T, delineating new phylogenetic branches within the genus. Detailed molecular analyses, including gyrB (90.2%), ANI (86.4%), average amino acid identity (87.8%) phylogenies, digital DNA-DNA hybridization (32.6%), and percentage of conserved proteins (77.7%) indicated significant divergence from N. niacini NBRC 15566T. Consequently, these strains have been designated Neobacillus driksii sp. nov., with the type strain 179-C4-2-HST (DSM 115941T = NRRL B-65665T). N. driksii grew at 4°C to 45°C, pH range of 6.0 to 9.5, and 0.5% to 5% NaCl. The major cellular fatty acids are iso-C15:0 and anteiso-C15:0. The dominant polar lipids include diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, and an unidentified aminolipid. Metagenomic analysis within NASA cleanrooms revealed that N. driksii is scarce (17 out of 236 samples). Genes encoding the biosynthesis pathway for lasso peptides were identified in all N. driksii strains and are not commonly found in other Neobacillus species, except in 7 out of 26 recognized species. This study highlights the unique metabolic capabilities of N. driksii, underscoring their potential in antimicrobial research and biotechnology. IMPORTANCE: The microbial surveillance of the Mars 2020 assembly cleanroom led to the isolation of novel N. driksii with potential applications in cleanroom environments, such as hospitals, pharmaceuticals, semiconductors, and aeronautical industries. N. driksii genomes were found to possess genes responsible for producing lasso peptides, which are crucial for antimicrobial defense, communication, and enzyme inhibition. Isolation of N. driksii from cleanrooms, Agave plants, and dryland wheat soils, suggested niche-specific ecology and resilience under various environmentally challenging conditions. The discovery of potent antimicrobial agents from novel N. driksii underscores the importance of genome mining and the isolation of rare microorganisms. Bioactive gene clusters potentially producing nicotianamine-like siderophores were found in N. driksii genomes. These siderophores can be used for bioremediation to remove heavy metals from contaminated environments, promote plant growth by aiding iron uptake in agriculture, and treat iron overload conditions in medical applications.

Phylogeny↗
PubMed2026

Secondary metabolite profiling of rare Micromonospora spp. from cold desert of NW Himalayas via multi-omics analysis.

INTRODUCTION: The genus Micromonospora is a prolific producer of specialized metabolites with pharmacological and agronomic relevance. Natural products derived from the genus Micromonospora have a distinctive chemical diversity and enormous therapeutic potential, thus represent a potential source for drugs and drug leads. OBJECTIVE: To explore the biosynthetic potential of four Micromonospora strains isolated from cold desert of NW Himalayas through genome mining and to correlate predicted biosynthetic gene clusters with chemical features detected by untargeted LC-HRMS metabolomics. METHOD: High-quality genomes were annotated for BGCs and matched against untargeted LC-HRMS features (peak picking, alignment, and annotation to chemical classes). Each isolate was grown in triplicate, and fermented broth was pooled for further metabolomic studies. RESULTS: By integrating genomic and metabolomic approaches, specialized biosynthetic gene clusters and strain-based putative metabolite classes were identified. LRS1 showed elevated xanthines (RiPP/siderophore), LRS3 had phenolic glycosides (hybrid PKS/NRPS), LRS4 showed 70-fold hydroxycinnamate enrichment (Type II PKS), and LRS5 displayed p-benzoquinone enrichment (Type III PKS). The metabolite profile of each strain aligned with its predicted biosynthetic gene cluster composition. CONCLUSION: Under a single growth regime, each Micromonospora strain exhibits a distinct metabolomic profile. This metabologenomics workflow can be further explored to isolate specialized metabolites with potential therapeutic and agricultural value.

Micromonospora↗
PubMed2026

Genome sequence data of the chitinase-producing bacterium Paenibacillus mucilaginosus YWY-5.1.

Paenibacillus mucilaginosus is a beneficial bacterium widely applied as a biofertilizer in agriculture. To date, genomic information on this species remains limited; however, no genome assemblies from Vietnam have been reported. This work presented the draft genome of P. mucilaginosus YWY-5.1, a promising strain with strong chitin-degrading capability and agricultural potential, isolated from Yok Don National Park, Vietnam, using Illumina technology. Results showed that the assembled genome comprised 48 contigs with 4,076,146 bp and 73.8% GC-content. Genome annotation identified 3,611 protein-coding genes, 2 rRNA genes, and 53 tRNA genes. A total of 150 carbohydrate-active enzyme-related genes were predicted from the genome; among them, seven putative chitinolytic genes were identified, including 4 genes related to family 18 chitinase, 2 genes to family 20 β-N-acetylglucosaminidase, and one gene to auxiliary activity family 10. In addition, at least 32 genes related to plant growth-promoting functions were identified, including those associated with indole-3-acetic acid production, phosphate and potassium solubilization, siderophore biosynthesis, iron uptake, ACC metabolism, and nitrate transport and reduction. Furthermore, genome mining identified 4 biosynthetic gene clusters probably involved in secondary metabolite production, of which 3 displayed no similarity to previously reported clusters, indicating potential for novel bioactive compounds. These genomic data improved our understanding of the biodegradation capacity and agricultural potential of P. mucilaginosus YWY-5.1 isolated from Vietnam, and provided a valuable genomic resource for future functional and biotechnological investigations toward crop production and related fields.

Chitinases↗
PubMed2026

Programmable enzymes for targeted gene insertion.

Genome editing technologies have advanced from nuclease-based reagents that generate programmed DNA double-strand breaks, which can cause deleterious effects, to next-generation reagents that perform controlled DNA modification through double-strand break-independent mechanisms, such as base editing and prime editing. Although these approaches enable precise small-scale sequence changes, methods for programmable insertion of large DNA cargos have been limited. The ability to write entire genes or large regions into the genome could transform the treatment of genetically heterogeneous disorders, for which numerous pathogenic variants underlie a common disease and mutation-specific editing strategies are impractical. Recent advances in computational genome mining have accelerated the discovery of naturally occurring enzymes with novel biochemical and functional properties, including recombinases and transposases capable of large-scale modifications. Moreover, directed evolution, rational engineering and expanded homologue discovery are enabling the repurposing and optimization of these systems for genome engineering. Here we review recent technology development efforts that harness diverse enzymes for kilobase-scale genome engineering, with a particular focus on CRISPR-associated transposase systems.

Journal Article↗
PubMed2026

Genomic Insights Into Multidrug-Resistant Foodborne Serratia liquefaciens Strains Carrying mcr-9 and Comparative Genomic Analysis of Novel Biosynthetic Gene Clusters.

Serratia liquefaciens is an opportunistic nosocomial pathogen with a wide range of antibiotic resistance patterns. This study reports the characterization of the first mcr-9-positive S. liquefaciens strains, 35E-19E1 and CST-066, isolated from meat products in Japan. The strains were screened for the presence of β-lactamases, plasmid-mediated mobile colistin resistance (mcr) genes, and carbapenemase-encoding genes using PCR. Antimicrobial susceptibility was tested using the broth microdilution method. The strains exhibited multidrug resistance (MDR) phenotypes to third-generation cephalosporins, cephamycin, fosfomycin, and other clinically important antimicrobials. Genomic DNA sequencing showed that the genome sizes of CST-066 and 35E-19E1 are 5,529,704 and 5,261,506 bps, respectively. mcr-9 was identified on a chromosome within a genetic environment that included the two-component system qseBC, which plays a key role in the signaling network that triggers colistin resistance in Enterobacterales. Downstream genome analysis revealed a 1695-bp eptB-like kdo2-lipid phosphoethanolamine transferase, which is involved in intrinsic polymyxin resistance mechanisms in Serratia spp. The strain 35E-19E1 carries five CRISPR-Cas enzymes that are essential for adaptive immunity in bacteria, allowing defense against invading elements. Functional analysis using subsystem technology revealed that both strains possess subsystem features responsible for invasion and adhesion within the host biomes. Genome mining using antiSMASH and BAGL4 revealed various biosynthetic gene clusters, responsible for secondary metabolite synthesis. Notably, we identified novel gene clusters, mainly nonribosomal peptide synthetases, in both the strains, indicating their potential to produce bioactive compounds. Although the presence of mcr-9 in Serratia may not be of clinical significance because of natural resistance of the strain to polymyxins, we shed light on the genomic characteristics of this MDR pathogen and the potential spread of mcr-9 among other bacterial species. The emergence of mcr-9 in drug-resistant S. liquefaciens provides significant insights, underscoring the need for increased surveillance of this pathogen.

biosynthetic gene cluster↗
PubMed2026

Tryptophan-driven metabolomic shift in Acidobacteriaceae reveals phytohormones and antifungal metabolites.

UNLABELLED: Acidobacteriota is one of the most abundant phyla in soils and has recently attracted attention for its potential role in promoting phytosanitary benefits. The metabolomic capabilities of this phylum remain poorly characterized, with few experimentally confirmed metabolites described. To address these gaps, we combined untargeted metabolomic profiling with comparative genomic analyses to explore the functional potential of newly isolated Acidobacteriaceae strains. Genome mining across the Acidobacteriota phylum revealed the presence and taxon-specific enrichment of genes associated with plant-related traits, including phytohormone biosynthesis. In parallel, metabolomic analyses of OSMAC-derived extracts uncovered pronounced condition-dependent metabolic variation. Tryptophan supplementation was associated with marked metabolomic reprogramming, including changes in indole-derived metabolites, such as indole-3-acetic acid. Subsequent analyses linked these metabolic shifts to the suppression of phytopathogenic fungi and enabled the identification of malassezindoles and pityriacitrins as active compounds, confirmed by structure elucidation using NMR spectroscopy. Overall, these findings shed light on the previously unexplored metabolic potential of the Acidobacteriota phylum, emphasizing its ecological importance for phytosanitary applications. IMPORTANCE: Despite their ubiquity and genomic diversity, the functional metabolism of members of the Acidobacteriota has largely remained uncharacterized. This study links genomic predictions to experimentally verified metabolomic outputs of Acidobacteriaceae, demonstrating tryptophan-responsive metabolic shifts translating to phytohormones and metabolites suppressing fungal growth. Our work underscores the emerging role of Acidobacteriota as important contributors to soil ecosystem functioning and plant-microbe interactions.

Acidobacteriota↗
PubMed2026

Chemotactic sensing of extracellular antibiotic resistance genes enables their efficient removal by Stutzerimonas stutzeri.

The dissemination of antibiotic resistance genes (ARGs) in wastewater environments poses a severe threat to public health. Extracellular ARGs (eARGs) persist as free DNA fragments that are refractory to efficient removal by conventional physicochemical treatment technologies. Here, we isolated Stutzerimonas stutzeri CHY07 from municipal sewage and demonstrated that extracellular DNA fragments, including eARGs, can serve as chemoattractants for environmental bacteria. Through genomic mining, molecular docking, surface plasmon resonance (SPR), isothermal titration calorimetry (ITC) and protein-ligand interaction profiling, we identified the chemoreceptor Mcp16 as the primary sensor of extracellular DNA and revealed that it achieves sequence-independent recognition of the DNA phosphate backbone. We further established the endogenous pentapeptide VRSVR as a methylation substrate for CheR and constructed the engineered strain CHY07-2 (mcp16::VRSVR) using an SSB/CRISPR-Cas9 ribonucleoprotein (RNP) system. This strain exhibited significantly enhanced chemotactic responsiveness, achieving 72-h removal efficiencies of 96.56% and 91.60% for low- and high-molecular-weight eARGs in non-sterile WWTP secondary effluent; conversely, mcp16 deletion markedly attenuated both chemotaxis and removal, whereas in situ complementation restored them. These findings reveal a "chemotaxis-contact-removal" cascade - with a proposed self-reinforcing loop - in eARG-removing bacteria, providing both a theoretical framework and a technical paradigm for enhancing pollutant removal through targeted amplification of microbial chemotaxis.

Chemotaxis↗