Identification Of Gene Cluster Research Articles

Secondary metabolites and transcriptomic analysis of novel pulcherrimin producer Metschnikowia persimmonesis KIOM G15050: A potent and safe food biocontrol agent

Metschnikowia persimmonesis, a novel endophytic yeast strain isolated from Diospyros kaki calyx, possesses strong antimicrobial activity. We investigated its potential use as an environmentally safe food biocontrol agent through genomics, transcriptomics, and metabolomics. Secondary metabolites were isolated from M. persimmonesis, followed by chemical structure elucidation, PUL gene cluster identification, and RNA sequencing. Pulcherrimin was isolated using 2 M NaOH, its structure was confirmed, and the yield was quantified. Biocontrol efficacy of M. persimmonesis on persimmon fruits and calyx was evaluated by assessing lesion diameter and disease incidence. Following compounds were isolated from M. persimmonesis co-culture with Botrytis cinerea and Fusarium oxysporum: fusaric acid, benzoic acid, benzeneacetic acid, 4-hydroxybenzeneacetic acid, 4-(-2-hydoxyethyl)-benzoic acid, cyclo (Leu-Leu), benzenemethanol, 4-hydroxy-benzaldehide, 2-hydroxy-4-methoxy-benzoic acid, 4-hydroxy-benzoic acid, lumichrome, heptadecanoic acid, and nonadecanoic acid. Exposing M. persimmonesis to different growth media conditions (with or without sugar) resulted in the isolation of five compounds: Tyrosol, Cyclo (Pro-Val), cyclo(L-Pro-L-Tyr), cyclo(Leu-Leu), and cyclo(l-tyrosilylicine). Differentially expressed gene analysis revealed 3264 genes that were significantly expressed (fold change ≥2 and p-value ≤0.05) during M. persimmonesis growth in different media, of which only 270 (8.27%) showed altered expression in all sample combinations with Luria–Bertani Agar as control. Minimal media with ferric ions and tween-80 triggered the most gene expression changes, with the highest levels of PUL gene expression and pulcherrimin yield (262.166 mg/L) among all media treatments. M. persimmonesis also produced a higher amount of pulcherrimin (209.733 mg/L) than Metschnikowia pulcherrima (152.8 mg/L). M. persimmonesis inhibited the growth of Fusarium oxysporum in persimmon fruit and calyx. Toxicity evaluation of M. persimmonesis extracts showed no harmful effects on the liver and mitochondria of zebrafish, and no potential risk of cardiotoxicity in hERG-HEK293 cell lines. Thus, M. persimmonesis can be commercialized as a potent and safe biocontrol agent for preserving food products.

Spatial clustering based gene selection for gene expression analysis in microarray data classification

A typical application of categorization in data mining is to uncover interesting distributions and significant patterns in the information that underlies it using density-based spatial clustering for workloads with noise. In these conditions, it is anticipated that the classification of the microarray gene expression database will have the necessary clustering property that may be utilized to emphasize the effects of the alterations. The proposed method typically guarantees that the subsequent identification of gene clusters’ best global arrangement of genes. It provides an iterative method for figuring out the precise number of clusters needed for each data collection. The technique is based on practices frequently used in statistical tests. The key idea is to coordinate gene redistribution optimization across clusters with the search for the optimal number of groups. An experiment that finds the most effective number of genes over time was used to evaluate the effectiveness of the suggested strategy. It used this stringent statistical test to show that our technique accurately clusters more than 95% of the genes. Finally, since the basic principles of gene development and gene cluster assignment have been well characterized by earlier studies and the technique was verified using real gene expression information.

Identification of the Biosynthetic Gene Cluster of New Piperazic Acid-Containing Lipopeptides with Cytotoxic Activity in the Genome of Marine Streptomyces PHM034.

Three novel lipopeptides, PM130391 (1), PM130392 (2), and PM140293 (3) were obtained from cultures of Streptomyces tuirus PHM034 isolated from a marine sediment. Structural elucidation of the three compounds showed they belong to the nonribosomal peptides family, and they all contain an acylated alanine, three piperazic acids, a methylated glycine, and an N-hydroxylated alanine. The difference between the three compounds resides in the acyl chain bound to the alanine residue. All three compounds showed cytotoxic activity against human cancer cell lines. Genome sequence and bioinformatics analysis allowed the identification of the gene cluster responsible for the biosynthesis. Inactivation of a nonribosomal peptide synthase of this cluster abolished the biosynthesis of the three compounds, thus demonstrating the involvement of this cluster in the biosynthesis of these lipopeptides.

Fully automated annotation of mitochondrial genomes using a cluster-based approach with de Bruijn graphs.

A wide range of scientific fields, such as forensics, anthropology, medicine, and molecular evolution, benefits from the analysis of mitogenomic data. With the development of new sequencing technologies, the amount of mitochondrial sequence data to be analyzed has increased exponentially over the last few years. The accurate annotation of mitochondrial DNA is a prerequisite for any mitogenomic comparative analysis. To sustain with the growth of the available mitochondrial sequence data, highly efficient automatic computational methods are, hence, needed. Automatic annotation methods are typically based on databases that contain information about already annotated (and often pre-curated) mitogenomes of different species. However, the existing approaches have several shortcomings: 1) they do not scale well with the size of the database; 2) they do not allow for a fast (and easy) update of the database; and 3) they can only be applied to a relatively small taxonomic subset of all species. Here, we present a novel approach that does not have any of these aforementioned shortcomings, (1), (2), and (3). The reference database of mitogenomes is represented as a richly annotated de Bruijn graph. To generate gene predictions for a new user-supplied mitogenome, the method utilizes a clustering routine that uses the mapping information of the provided sequence to this graph. The method is implemented in a software package called DeGeCI (De Bruijn graph Gene Cluster Identification). For a large set of mitogenomes, for which expert-curated annotations are available, DeGeCI generates gene predictions of high conformity. In a comparative evaluation with MITOS2, a state-of-the-art annotation tool for mitochondrial genomes, DeGeCI shows better database scalability while still matching MITOS2 in terms of result quality and providing a fully automated means to update the underlying database. Moreover, unlike MITOS2, DeGeCI can be run in parallel on several processors to make use of modern multi-processor systems.

Navigating and expanding the roadmap of natural product genome mining tools.

Natural products are structurally highly diverse and exhibit a wide array of biological activities. As a result, they serve as an important source of new drug leads. Traditionally, natural products have been discovered by bioactivity-guided fractionation. The advent of genome sequencing technology has resulted in the introduction of an alternative approach towards novel natural product scaffolds: Genome mining. Genome mining is an in-silico natural product discovery strategy in which sequenced genomes are analyzed for the potential of the associated organism to produce natural products. Seemingly universal biosynthetic principles have been deciphered for most natural product classes that are used to detect natural product biosynthetic gene clusters using pathway-encoded conserved key enzymes, domains, or motifs as bait. Several generations of highly sophisticated tools have been developed for the biosynthetic rule-based identification of natural product gene clusters. Apart from these hard-coded algorithms, multiple tools that use machine learning-based approaches have been designed to complement the existing genome mining tool set and focus on natural product gene clusters that lack genes with conserved signature sequences. In this perspective, we take a closer look at state-of-the-art genome mining tools that are based on either hard-coded rules or machine learning algorithms, with an emphasis on the confidence of their predictions and potential to identify non-canonical natural product biosynthetic gene clusters. We highlight the genome mining pipelines' current strengths and limitations by contrasting their advantages and disadvantages. Moreover, we introduce two indirect biosynthetic gene cluster identification strategies that complement current workflows. The combination of all genome mining approaches will pave the way towards a more comprehensive understanding of the full biosynthetic repertoire encoded in microbial genome sequences.

Whole-Genome Sequence Data for the Holotype Strain of Diaporthe ilicicola, a Fungus Associated with Latent Fruit Rot in Deciduous Holly.

ABSTRACTDiaporthe ilicicola is a newly described fungal species that is associated with latent fruit rot in deciduous holly. This announcement provides a whole-genome assembly and annotation for this plant pathogen, which will inform research on its parasitism and identification of gene clusters involved in the production of bioactive metabolites.

Comparative analysis of assembly algorithms to optimize biosynthetic gene cluster identification in novel marine actinomycete genomes

Many marine sponges harbor dense communities of microbes that aid in the chemical defense of these nonmotile hosts. Metabolites that comprise this chemical arsenal can have pharmaceutically-relevant activities such as antibacterial, antiviral, antifungal and anticancer properties. Previous investigation of the Caribbean giant barrel sponge Xestospongia muta revealed a microbial community including novel Actinobacteria, a phylum well known for its production of antibiotic compounds. This novel assemblage was investigated for its ability to produce compounds that inhibit M. tuberculosis by using a bioinformatics approach. Microbial extracts were tested for their ability to inhibit growth of M. tb and genomes of the 11 strains that showed anti-M. tb activity including Micrococcus (n=2), Micromonospora (n=4), Streptomyces (n=3), and Brevibacterium spp. (n=2) were sequenced by using Illumina MiSeq. Three assembly algorithms/pipelines (SPAdes, A5-miseq and Shovill) were compared for their ability to construct contigs with minimal gaps to maximize the probability of identifying complete biosynthetic gene clusters (BGCs) present in the genomes. Although A5-miseq and Shovill usually assembled raw reads into the fewest contigs, after necessary post-assembly filtering, SPAdes generally produced the most complete genomes with the fewest contigs. This study revealed the strengths and weaknesses of the different assemblers based on their ease of use and ability to be manipulated based on output format. None of the assembly methods handle contamination well and high-quality DNA is a prerequisite. BGCs of compounds with known anti-TB activity were identified in all Micromonospora and Streptomyces strains (genomes > 5 Mb), while no such BGCs were identified in Micrococcus or Brevibacterium strains (genomes < 5 Mb). The majority of the putative BGCs identified were located on contig edges, emphasizing the inability of short-read assemblers to resolve repeat regions and supporting the need for long-read sequencing to fully resolve BGCs.

PyRSD-CoEv: A python package for selective sweep detection and co-evolutionary gene cluster identification.

Genes undergo distinct selective sweeps, and also interact and coevolve, forming the bases of complex phenotypic traits. Therefore, the identification of genes that coevolve or are under artificial selective sweeps is of great importance. However, previous computational methods have been designed for either populations of closely related breeds or individuals of distinct species. Approaches intended specifically for closely related individuals without replicate (i.e. each breed/strain is represented by only one individual) are long overdue. We present a free, powerful, open source package, pyRSD-CoEv, that allows the identification of genes undergoing coevolution and/or selection-based sweeps. pyRSD-CoEv includes two main analysis workflows for genomic variant data: (i) the identification of selective sweeps using relative homozygous single nucleotide variant density (RSD); and (ii) the identification of coevolutionary gene clusters based on correlated evolutionary rates. The python package pyRSD-CoEv is written using python 3.7 and is freely available from the github website at https://github.com/QianZiTang/pyRSD-CoEv. It runs on Linux.

Cell Wall Stress Stimulates the Activity of the Protein Kinase StkP of Streptococcus pneumoniae, Leading to Multiple Phosphorylation

Streptococcus pneumoniae is an opportunistic human pathogen that encodes a single eukaryotic-type Ser/Thr protein kinase StkP and its functional counterpart, the protein phosphatase PhpP. These signaling enzymes play critical roles in coordinating cell division and growth in pneumococci. In this study, we determined the proteome and phosphoproteome profiles of relevant mutants. Comparison of those with the wild-type provided a representative dataset of novel phosphoacceptor sites and StkP-dependent substrates. StkP phosphorylates key proteins involved in cell division and cell wall biosynthesis in both the unencapsulated laboratory strain Rx1 and the encapsulated virulent strain D39. Furthermore, we show that StkP plays an important role in triggering an adaptive response induced by a cell wall-directed antibiotic. Phosphorylation of the sensor histidine kinase WalK and downregulation of proteins of the WalRK core regulon suggest crosstalk between StkP and the WalRK two-component system. Analysis of proteomic profiles led to the identification of gene clusters regulated by catabolite control mechanisms, indicating a tight coupling of carbon metabolism and cell wall homeostasis. The imbalance of steady-state protein phosphorylation in the mutants as well as after antibiotic treatment is accompanied by an accumulation of the global Spx regulator, indicating a Spx-mediated envelope stress response. In summary, StkP relays the perceived signal of cell wall status to key cell division and regulatory proteins, controlling the cell cycle and cell wall homeostasis.

Applications and Restrictions of Integrated Genomic and Metabolomic Screening: An Accelerator for Drug Discovery from Actinomycetes?

Since the golden age of antibiotics in the 1950s and 1960s actinomycetes have been the most prolific source for bioactive natural products. However, the number of discoveries of new bioactive compounds decreases since decades. New procedures (e.g., activating strategies or innovative fermentation techniques) were developed to enhance the productivity of actinomycetes. Nevertheless, compound identification remains challenging among others due to high rediscovery rates. Rapid and cheap genome sequencing as well as the advent of bioinformatical analysis tools for biosynthetic gene cluster identification in combination with mass spectrometry-based molecular networking facilitated the tedious process of dereplication. In recent years several studies have been dedicated to accessing the biosynthetic potential of Actinomyces species, especially streptomycetes, by using integrated genomic and metabolomic screening in order to boost the discovery rate of new antibiotics. This review aims to present the various possible applications of this approach as well as the newly discovered molecules, covering studies between 2014 and 2021. Finally, the effectiveness of this approach with regard to find new bioactive agents from actinomycetes will be evaluated.

Discovery, Bioactivity Evaluation, Biosynthetic Gene Cluster Identification, and Heterologous Expression of Novel Albofungin Derivatives

The crude extract of Streptomyces chrestomyceticus exhibited strong and broad activities against most “ESKAPE pathogens.” We conducted a comprehensive chemical investigation for secondary metabolites from the S. chrestomyceticus strain and identified two novel albofungin (alb) derivatives, i.e., albofungins A (1) and B (2), along with two known compounds, i.e., albofungin (3) and chloroalbofungin (4). The chemical structures of the novel compounds were elucidated using HRMS, 1D and 2D NMR, and electronic circular dichroism spectroscopy. The draft genome of S. chrestomyceticus was sequenced, and a 72 kb albofungin (alb) gene cluster with 72 open reading frames encoding type II polyketide synthases (PKSs), regulators, and transporters, and tailoring enzymes were identified using bioinformatics analysis. The alb gene cluster was confirmed using the heterologous expression in Streptomyces coelicolor, which successfully produced the compounds 3 and 4. Furthermore, compounds 1–4 displayed remarkable activities against Gram-positive bacteria and antitumor activities toward various cancer cells. Notably, compounds 1 and 3 showed potent activities against Gram-negative pathogenic bacteria. The terminal deoxynucleotidyl transferase (dUTP) nick-end labeling and flow cytometry analysis verified that compound 1 inhibited cancer cell proliferation by inducing cellular apoptosis. These results indicated that albofungins might be potential candidates for the development of antibiotics and antitumor drugs.

Draft Genome Sequence and Secondary Metabolite Biosynthetic Potential of the Lysobacter niastensis Type Strain DSM 18481.

Lysobacter niastensis belongs to a group of bacterial predators that produce a number of bioactive small molecules endowed with lytic properties toward other microorganisms. Here, we report the draft genome sequence of the type strain DSM 18481 and the identification of gene clusters implicated in the biosynthesis of secondary metabolites.

The Integration of Genome Mining, Comparative Genomics, and Functional Genetics for Biosynthetic Gene Cluster Identification.

Antimicrobial resistance is a worldwide health crisis for which new antibiotics are needed. One strategy for antibiotic discovery is identifying unique antibiotic biosynthetic gene clusters that may produce novel compounds. The aim of this study was to demonstrate how an integrated approach that combines genome mining, comparative genomics, and functional genetics can be used to successfully identify novel biosynthetic gene clusters that produce antimicrobial natural products. Secondary metabolite clusters of an antibiotic producer are first predicted using genome mining tools, generating a list of candidates. Comparative genomic approaches are then used to identify gene suites present in the antibiotic producer that are absent in closely related non-producers. Gene sets that are common to the two lists represent leading candidates, which can then be confirmed using functional genetics approaches. To validate this strategy, we identified the genes responsible for antibiotic production in Pantoea agglomerans B025670, a strain identified in a large-scale bioactivity survey. The genome of B025670 was first mined with antiSMASH, which identified 24 candidate regions. We then used the comparative genomics platform, EDGAR, to identify genes unique to B025670 that were not present in closely related strains with contrasting antibiotic production profiles. The candidate lists generated by antiSMASH and EDGAR were compared with standalone BLAST. Among the common regions was a 14 kb cluster consisting of 14 genes with predicted enzymatic, transport, and unknown functions. Site-directed mutagenesis of the gene cluster resulted in a reduction in antimicrobial activity, suggesting involvement in antibiotic production. An integrated approach that combines genome mining, comparative genomics, and functional genetics yields a powerful, yet simple strategy for identifying potentially novel antibiotics.

Genome Mining, Microbial Interactions, and Molecular Networking Reveals New Dibromoalterochromides from Strains of Pseudoalteromonas of Coiba National Park-Panama.

The marine bacterial genus Pseudoalteromonas is known for their ability to produce antimicrobial compounds. The metabolite-producing capacity of Pseudoalteromonas has been associated with strain pigmentation; however, the genomic basis of their antimicrobial capacity remains to be explained. In this study, we sequenced the whole genome of six Pseudoalteromonas strains (three pigmented and three non-pigmented), with the purpose of identifying biosynthetic gene clusters (BGCs) associated to compounds we detected via microbial interactions along through MS-based molecular networking. The genomes were assembled and annotated using the SPAdes and RAST pipelines and mined for the identification of gene clusters involved in secondary metabolism using the antiSMASH database. Nineteen BGCs were detected for each non-pigmented strain, while more than thirty BGCs were found for two of the pigmented strains. Among these, the groups of genes of nonribosomal peptide synthetases (NRPS) that code for bromoalterochromides stand out the most. Our results show that all strains possess BGCs for the production of secondary metabolites, and a considerable number of distinct polyketide synthases (PKS) and NRPS clusters are present in pigmented strains. Furthermore, the molecular networking analyses revealed two new molecules produced during microbial interactions: the dibromoalterochromides D/D’ (11–12).

Biosynthetic gene cluster identification and biological activity of lucilactaene from Fusarium sp. RK97-94.

We identified the biosynthetic gene cluster for lucilactaene, a cell cycle inhibitor from a filamentous fungus Fusarium sp. RK 97-94. The luc1 knockout strain accumulated demethylated analogs, indicating the involvement of Luc1 methyltransferase in lucilactaene biosynthesis. Lucilactaene showed potent antimalarial activity. Our data suggested that methylation and ether ring formation are essential for its potent antimalarial activity.

Phylogenetic insight of Nonribosomal peptide synthetases (NRPS) Adenylate domain in Antibacterial potential Streptomyces BDUSMP 02 isolated from Pitchavaram Mangrove.

Identification of gene clusters in Streptomyces holds promise for the discovery of regulatory pathways linked to bioactive metabolites. We isolated a broad-spectrum antibacterial potential Streptomyces sp BDUSMP 02 from mangrove sediment. We further found a distinct of phylogeny pattern for NRPS A-domain in the Streptomyces sp BDUSMP 02. The result suggests that Streptomyces sp BDUSMP 02 has the potential to produce a new type of antibacterial compounds belonging to NRPS type.

Identification of Secondary Metabolite Gene Clusters in the Genome of Bacillus pumilus Strains 7P and 3-19

Members of Bacillus pumilus species are industrially important microorganisms able to secrete a wide range of hydrolytic enzymes and secondary metabolites. However, the traditional methods (based on phenotypes) used to identify such products are time-consuming and are not very specific. Currently, the availability of whole genome sequencing and bioinformatics tools has become a powerful approach for identification of gene clusters associated with the synthesis of substances useful for biotechnology. In order to estimate the potential industrial significance and application of B. pumilus, genome sequencing of two strains (7P and 3-19) and searching of secondary metabolite clusters were performed using antiSMASH program. These analyses revealed 11 potential gene clusters for the synthesis of bacilysin, lichenysin, bacteriocin, and other substances.

Identification of polyketide synthase gene clusters in a phage P1-derived artificial chromosome library of a Philippine strain of Streptomyces sp. PCS3-D2

A phage P1-derived artificial chromosome (PAC) library was constructed from genomic DNA of Streptomyces sp. PCS3-D2. Polymerase chain reaction (PCR) screening of the PAC library revealed two clones, PAC16D and P222O, which were positively identified to harbor polyketide synthase (PKS) Type I and PKS Type III gene clusters, respectively. Restriction enzyme digestion showed that PAC16D and PAC222O contained a 130 kb and a 140 kb insert, respectively. Results of sequencing and bioinformatics analyses revealed that PAC16D comprised of a full-length PKS type I bafilomycin gene cluster while PAC222O harbored truncated siderophore and putative gene clusters as well as a complete PKS III biosynthetic gene cluster. The PKS III gene cluster had three genes similar to alkyl resorcinol biosynthetic genes, however majority of the novel gene cluster had little similarity to known PKS Type III gene clusters. The successful cloning and identification of these gene clusters from Streptomyces sp. PCS3-D2 serve as the jump off point to further genetic manipulation in order to produce the insecticidal natural product in a heterologous host.

Discovery and Biosynthesis of the Antibiotic Bicyclomycin in Distantly Related Bacterial Classes.

ABSTRACTBicyclomycin (BCM) is a clinically promising antibiotic that is biosynthesized by Streptomyces cinnamoneus DSM 41675. BCM is structurally characterized by a core cyclo(l-Ile-l-Leu) 2,5-diketopiperazine (DKP) that is extensively oxidized. Here, we identify the BCM biosynthetic gene cluster, which shows that the core of BCM is biosynthesized by a cyclodipeptide synthase, and the oxidative modifications are introduced by five 2-oxoglutarate-dependent dioxygenases and one cytochrome P450 monooxygenase. The discovery of the gene cluster enabled the identification of BCM pathways encoded by the genomes of hundreds of Pseudomonas aeruginosa isolates distributed globally, and heterologous expression of the pathway from P. aeruginosa SCV20265 demonstrated that the product is chemically identical to BCM produced by S. cinnamoneus. Overall, putative BCM gene clusters have been found in at least seven genera spanning Actinobacteria and Proteobacteria (Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria). This represents a rare example of horizontal gene transfer of an intact biosynthetic gene cluster across such distantly related bacteria, and we show that these gene clusters are almost always associated with mobile genetic elements.IMPORTANCE Bicyclomycin is the only natural product antibiotic that selectively inhibits the transcription termination factor Rho. This mechanism of action, combined with its proven biological safety and its activity against clinically relevant Gram-negative bacterial pathogens, makes it a very promising antibiotic candidate. Here, we report the identification of the bicyclomycin biosynthetic gene cluster in the known bicyclomycin-producing organism Streptomyces cinnamoneus, which will enable the engineered production of new bicyclomycin derivatives. The identification of this gene cluster also led to the discovery of hundreds of bicyclomycin pathways encoded in highly diverse bacteria, including in the opportunistic pathogen Pseudomonas aeruginosa. This wide distribution of a complex biosynthetic pathway is very unusual and provides an insight into how a pathway for an antibiotic can be transferred between diverse bacteria.

Identification and Characterization of Mycemycin Biosynthetic Gene Clusters in Streptomyces olivaceus FXJ8.012 and Streptomyces sp. FXJ1.235.

Mycemycins A–E are new members of the dibenzoxazepinone (DBP) family, derived from the gntR gene-disrupted deep sea strain Streptomyces olivaceus FXJ8.012Δ1741 and the soil strain Streptomyces sp. FXJ1.235. In this paper, we report the identification of the gene clusters and pathways’ inference for mycemycin biosynthesis in the two strains. Bioinformatics analyses of the genome sequences of S. olivaceus FXJ8.012Δ1741 and S. sp. FXJ1.235 predicted two divergent mycemycin gene clusters, mym and mye, respectively. Heterologous expression of the key enzyme genes of mym and genetic manipulation of mye as well as a feeding study in S. sp. FXJ1.235 confirmed the gene clusters and led to the proposed biosynthetic pathways for mycemycins. To the best of our knowledge, this is the first report on DBP biosynthetic gene clusters and pathways.