Vibrio gazogenes inhibits aflatoxin production through downregulation of aflatoxin biosynthetic genes in Aspergillus flavus

Aspergillus flavus is an opportunistic pathogen of oilseed crops such as maize, peanut, cottonseed, and tree nuts and produces carcinogenic secondary metabolites known as aflatoxins during seed colonization. Aflatoxin contamination not only reduces the value of the produce but also is a health hazard to humans and animals. Previously, we observed inhibition of A. flavus aflatoxin biosynthesis upon exposure to the marine bacterium, Vibrio gazogenes (Vg). In this study, we used RNA sequencing to examine the transcriptional profiles of A. flavus treated with both live and heat-inactivated dead Vg and control samples. Fungal biomass, total accumulated aflatoxins, and expression profiles of genes constituting secondary metabolite biosynthetic gene clusters were determined at 24, 30, and 40 h after treatment. Statistically significant reductions in total aflatoxins were detected in Vg-treated samples as compared to control samples at 40 h. But no statistical difference in fungal biomass was observed upon these treatments. The Vg treatments were most effective on aflatoxin biosynthesis as was reflected in significant downregulation of majority of the genes in the aflatoxin gene cluster including the aflatoxin pathway regulator gene, aflR. Along with aflatoxin genes, we also observed significant downregulation in some other secondary metabolite gene clusters including cyclopiazonic acid and aflavarin, suggesting that the treatment may inhibit other secondary metabolites as well. Finally, a weighted gene correlation network analysis identified an upregulation of ten genes that were most strongly associated with Vg-dependent aflatoxin inhibition and provide a novel start-point in understanding the mechanisms that result in this phenomenon.

Perception of Biocontrol Potential of Bacillusinaquosorum KR2-7 against Tomato Fusarium Wilt through Merging Genome Mining with Chemical Analysis

Tomato Fusarium wilt, caused by Fusarium oxysporum f. sp. lycopersici (Fol), is a destructive disease that threatens the agricultural production of tomatoes. In the present study, the biocontrol potential of strain KR2-7 against Fol was investigated through integrated genome mining and chemical analysis. Strain KR2-7 was identified as B. inaquosorum based on phylogenetic analysis. Through the genome mining of strain KR2-7, we identified nine antifungal and antibacterial compound biosynthetic gene clusters (BGCs) including fengycin, surfactin and Bacillomycin F, bacillaene, macrolactin, sporulation killing factor (skf), subtilosin A, bacilysin, and bacillibactin. The corresponding compounds were confirmed through MALDI-TOF-MS chemical analysis. The gene/gene clusters involved in plant colonization, plant growth promotion, and induced systemic resistance were also identified in the KR2-7 genome, and their related secondary metabolites were detected. In light of these results, the biocontrol potential of strain KR2-7 against tomato Fusarium wilt was identified. This study highlights the potential to use strain KR2-7 as a plant-growth promotion agent.

Mining for novel cyclomaltodextrin glucanotransferases unravels the carbohydrate metabolism pathway via cyclodextrins in Thermoanaerobacterales

Carbohydrate metabolism via cyclodextrins (CM-CD) is an uncommon starch-converting pathway that thoroughly depends on extracellular cyclomaltodextrin glucanotransferases (CGTases) to transform the surrounding starch substrate to α-(1,4)-linked oligosaccharides and cyclodextrins (CDs). The CM-CD pathway has emerged as a convenient microbial adaptation to thrive under extreme temperatures, as CDs are functional amphipathic toroids with higher heat-resistant values than linear dextrins. Nevertheless, although the CM-CD pathway has been described in a few mesophilic bacteria and archaea, it remains obscure in extremely thermophilic prokaryotes (Topt ≥ 70 °C). Here, a new monophyletic group of CGTases with an exceptional three-domain ABC architecture was detected by (meta)genome mining of extremely thermophilic Thermoanaerobacterales living in a wide variety of hot starch-poor environments on Earth. Functional studies of a representative member, CldA, showed a maximum activity in a thermoacidophilic range (pH 4.0 and 80 °C) with remarkable product diversification that yielded a mixture of α:β:γ-CDs (34:62:4) from soluble starch, as well as G3–G7 linear dextrins and fermentable sugars as the primary products. Together, comparative genomics and predictive functional analysis, combined with data of the functionally characterized key proteins of the gene clusters encoding CGTases, revealed the CM-CD pathway in Thermoanaerobacterales and showed that it is involved in the synthesis, transportation, degradation, and metabolic assimilation of CDs.

Complete Genome Sequences of Five Burkholderia Strains with Biocontrol Activity against Various Lettuce Pathogens

Numerous bacterial strains from the Burkholderia cepacia complex display biocontrol activity. Here, we report the complete genome sequences of five Burkholderia strains isolated from soil. Biosynthetic gene clusters responsible for the production of antimicrobial compounds were found in the genome of these strains, which display biocontrol activity against various lettuce pathogens.

Targeted Genome Mining Reveals the Psychrophilic Clostridium estertheticum Complex as a Potential Source for Novel Bacteriocins, Including Cesin A and Estercticin A

Antimicrobial resistance in pathogenic bacteria is considered a major public health issue necessitating the discovery of alternative antimicrobial compounds. In this regard, targeted genome mining in bacteria occupying under-explored ecological niches has the potential to reveal such compounds, including bacteriocins. In this study, we determined the bacteriocin biosynthetic potential of the psychrophilic Clostridium estertheticum complex (CEC) through a combination of genome mining and phenotypic screening assays. The genome mining was performed in 40 CEC genomes using antiSMASH. The production of bacteriocin-like compounds was phenotypically validated through agar well (primary screening) and disk diffusion (secondary screening) assays using cell free supernatants (CFS) and partially purified extracts, respectively. Stability of four selected CFS against proteolytic enzymes, temperature and pH was determined while one CFS was analyzed by HRMS and MS/MS to identify potential bacteriocins. Twenty novel bacteriocin biosynthetic gene clusters (BBGC), which were classified into eight (six lantibiotics and two sactipeptides) distinct groups, were discovered in 18 genomes belonging to C. estertheticum (n = 12), C. tagluense (n = 3) and genomospecies2 (n = 3). Primary screening linked six BBGC with narrow antimicrobial activity against closely related clostridia species. All four preselected CFS retained activity after exposure to different proteolytic, temperature and pH conditions. Secondary screening linked BBGC1 and BBGC7 encoding a lantibiotic and sactipeptide, respectively, with activity against Bacillus cereus while lantibiotic-encoding BBGC2 and BBGC3 were linked with activity against B. cereus, Staphylococcus aureus (methicillin-resistant), Escherichia coli and Pseudomonas aeruginosa. MS/MS analysis revealed that C. estertheticum CF004 produces cesin A, a short natural variant of nisin, and HRMS indicated the production of a novel sactipeptide named estercticin A. Therefore, we have shown the CEC, in particular C. estertheticum, is a source of novel and stable bacteriocins that have activities against clinically relevant pathogens.

MagCluster: a Tool for Identification, Annotation, and Visualization of Magnetosome Gene Clusters

Magnetosome gene clusters (MGCs), which are responsible for magnetosome biosynthesis and organization in magnetotactic bacteria (MTB), are the key to deciphering the mechanisms and evolutionary origin of magnetoreception, organelle biogenesis, and intracellular biomineralization in bacteria. Here, we report the development of MagCluster, a Python stand-alone tool for efficient exploration of MGCs from large-scale (meta)genomic data.

Taxonomic and Functional Diversity of Rhizosphere Microbiome Recruited From Compost Synergistically Determined by Plant Species and Compost

Compost is frequently served as the first reservoir for plants to recruit rhizosphere microbiome when used as growing substrate in the seedling nursery. In the present study, recruitment of rhizosphere microbiome from two composts by tomato, pepper, or maize was addressed by shotgun metagenomics and 16S rRNA amplicon sequencing. The 16S rRNA amplicon sequencing analysis showed that 41% of variation in the rhizosphere bacterial community was explained by compost, in contrast to 23% by plant species. Proteobacterial genera were commonly recruited by all three plant species with specific selections for Ralstonia by tomato and Enterobacteria by maize. These findings were confirmed by analysis of 16S rRNA retrieved from the shotgun metagenomics library. Approximately 70% of functional gene clusters differed more than sevenfold in abundance between rhizosphere and compost. Functional groups associated with the sensing and up-taking of C3 and C4 carboxylic acids, amino acids, monosaccharide, production of antimicrobial substances, and antibiotic resistance were over-represented in the rhizosphere. In summary, compost and plant species synergistically shaped the composition of the rhizosphere microbiome and selected for functional traits associated with the competition on root exudates.

Horizontal Transfers Lead to the Birth of Momilactone Biosynthetic Gene Clusters in Grass

Momilactone A, an important plant labdane-related diterpenoid, functions as a phytoalexin against pathogens and an allelochemical against neighboring plants. The genes involved in biosynthesis of momilactone A are found in clusters, i.e., MABGCs (Momilactone A biosynthetic gene clusters), in the rice and barnyardgrass genomes. How MABGCs originate and evolve is still not clear. Here, we integrated results from comprehensive phylogeny and comparative genomic analyses of the core genes of MABGC-like clusters and MABGCs in 40 monocot plant genomes, providing convincing evidence for the birth and evolution of MABGCs in grass species. The MABGCs found in the PACMAD clade of the core grass lineage (including Panicoideae and Chloridoideae) originated from a MABGC-like cluster in Triticeae (BOP clade) via horizontal gene transfer (HGT) and followed by recruitment of MAS and CYP76L1 genes. The MABGCs in Oryzoideae originated from PACMAD through another HGT event and lost CYP76L1 afterwards. The Oryza MABGC and another Oryza diterpenoid cluster c2BGC are two distinct clusters, with the latter being originated from gene duplication and relocation within Oryzoideae. Further comparison of the expression patterns of the MABGC genes between rice and barnyardgrass in response to pathogen infection and allelopathy provides novel insights into the functional innovation of MABGCs in plants. Our results demonstrate HGT-mediated origination of MABGCs in grass and shed lights into the evolutionary innovation and optimization of plant biosynthetic pathways.

Induction of Isochromanones by Co-Cultivation of the Marine Fungus Cosmospora sp. and the Phytopathogen Magnaporthe oryzae

Microbial co-cultivation is a promising approach for the activation of biosynthetic gene clusters (BGCs) that remain transcriptionally silent under artificial culture conditions. As part of our project aiming at the discovery of marine-derived fungal agrochemicals, we previously used four phytopathogens as model competitors in the co-cultivation of 21 marine fungal strains. Based on comparative untargeted metabolomics analyses and anti-phytopathogenic activities of the co-cultures, we selected the co-culture of marine Cosmospora sp. with the phytopathogen Magnaporthe oryzae for in-depth chemical studies. UPLC-MS/MS-based molecular networking (MN) of the co-culture extract revealed an enhanced diversity of compounds in several molecular families, including isochromanones, specifically induced in the co-culture. Large scale co-cultivation of Cosmospora sp. and M. oryzae resulted in the isolation of five isochromanones from the whole co-culture extract, namely the known soudanones A, E, D (1-3) and their two new derivatives, soudanones H-I (4-5), the known isochromans, pseudoanguillosporins A and B (6, 7), naphtho-γ-pyrones, cephalochromin and ustilaginoidin G (8, 9), and ergosterol (10). Their structures were established by NMR, HR-ESIMS, FT-IR, electronic circular dichroism (ECD) spectroscopy, polarimetry ([α]D), and Mosher’s ester reaction. Bioactivity assays revealed antimicrobial activity of compounds 2 and 3 against the phytopathogens M. oryzae and Phytophthora infestans, while pseudoanguillosporin A (6) showed the broadest and strongest anti-phytopathogenic activity against Pseudomonas syringae, Xanthomonas campestris, M. oryzae and P. infestans. This is the first study assessing the anti-phytopathogenic activities of soudanones.

FunOrder 2.0 – a fully automated method for the identification of co-evolved genes

Coevolution is an important biological process that shapes interacting species or even proteins – may it be physically interacting proteins or consecutive enzymes in a metabolic pathway. The detection of co-evolved proteins will contribute to a better understanding of biological systems. Previously, we developed a semi-automated method, termed FunOrder, for the detection of co-evolved genes from an input gene or protein set. We demonstrated the usability and applicability of FunOrder by identifying essential genes in biosynthetic gene clusters from different ascomycetes. A major drawback of this original method was the need for a manual assessment, which may create a user bias and prevents a high-throughput application. Here we present a fully automated version of this method termed FunOrder 2.0. To fully automatize the method, we used several mathematical indices to determine the optimal number of clusters in the FunOrder output, and a subsequent k-means clustering based on the first three principal components of a principal component analysis of the FunOrder output. Further, we replaced the BLAST with the DIAMOND tool, which enhanced speed and allows the future integration of larger proteome databases. The introduced changes slightly decreased the sensitivity of this method, which is outweighed by enhanced overall speed and specificity. Additionally, the changes lay the foundation for future high-throughput applications of FunOrder 2.0 in different phyla to solve different biological problems.