Diversity and Distribution of Biosynthetic Gene Clusters in the Halophilic Bacteria

doi:10.21203/rs.3.rs-4878965/v1

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Diversity and Distribution of Biosynthetic Gene Clusters in the Halophilic Bacteria

https://doi.org/10.21203/rs.3.rs-4878965/v1

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Halophilic bacteria have emerged as a promising source of bioactive compounds with potential therapeutic and biotechnological applications. In the present study, we conducted an in-silico analysis to investigate biosynthetic gene clusters (BGCs) of halophilic bacteria for which genomes are available in the public database. In the Halodom database, 670 halophilic bacterial genomes were identified. The genomic data were available for 454 of them. We used the antiSMASH database to identify potential BGCs. The presence of BGCs in 447 bacterial species was revealed, ranging from 1 to 44 per genome. More than 400 species showed the presence of 2 or more BGCs in their genome. Common BGCs were ectoine, terpene, betalactone, Type III polyketide synthases, and ribosomally synthesized and post-translationally modified peptides (RiPPs). We also observed a moderate positive correlation (R² = 0.40) between genome size and the number of BGCs in the genome. A diverse range of BGCs were found across different bacterial clades. However, the phylogenetic analysis revealed that certain clades such as the phylum Actinomycetota and subclades formed by the members of Cyanobacteriota, Myxococcota and Pseudomonadota were particularly rich in the multiple BGCs. The study highlights the potential of halophilic bacteria for bioactivity production.

Halophilic bacteria

secondary metabolites

genome mining

gene clusters

natural products

Natural products are small chemical compounds produced by plants, animals, and microorganisms and have been used for centuries in traditional medicine (Dias et al. 2012). These unique and structurally diverse compounds, including essential oils, alkaloids, flavonoids, terpenes, and phenolic compounds, are usually synthesized by the organism to defend themselves against various biotic and abiotic stressors, to communicate or to attract pollinators (Shivanna 2023; Anjali et al. 2023; Netzker et al. 2015; Atanasov et al. 2021). These compounds have diverse biological activities; hence they have been used in medicine, agriculture and other industries for centuries. These compounds have acquired much attention in recent years due to their bioactive potential (Atanasov et al. 2021).

Halophiles are one of the most fascinating organisms for the production of natural products. They usually thrive in hypersaline environments such as salt lakes, saltpans, and salted food products (Kanekar and Kanekar 2022). Halophiles include members of all three domains of life: bacteria, archaea, and eukarya (Ma et al. 2010). Besides salinity, halophiles often are exposed to various environmental stressors such as ultraviolet radiations, and fluctuating temperatures (John et al. 2019). To cope with these harsh conditions, halophiles synthesize several metabolites such as carotenoid pigments, retinal proteins, hydrolytic enzymes, and compatible solutes, many of which possess huge biotechnological applications (Dutta and Bandopadhyay 2022). Compatible solutes are small organic molecules that help to maintain the osmotic balance between the cell and the environment, e.g. ectoine, glycine betaine, and trehalose. These metabolites are widely used in the cosmetic industry (Roberts 2005). In addition, halophilic bacteria produce various anti-microbial peptides such as cyclic dipeptides, halocon H4, Microcin E492, Streptomonomicin (STM), and Nisin which have inhibitory effects towards plant- and human- pathogens (Dutta and Bandopadhyay 2022; Thompson and Gilmore 2024 and the reference therein). They are also proven sources for potential anticancer compounds (Corral et al. 2019 and the reference therein; Mohammadipanah et al. 2015).

The conventional way of isolating bioactive compounds involves biological screening of crude extracts to identify a bioactive hit extract, which is then further fractionated to isolate the active natural products. It involves a variety of techniques such as solvent extraction, chromatography and crystallization. This process is known as bioactivity-guided isolation (Bucar et al. 2013; Sasidharan et al. 2011). Though the majority of the bioactive compounds have been generated in this way, the limitation is that it is a laborious and time-consuming process to isolate compounds, purify them, and evaluate their bioactivity (Atanasov et al. 2021).

In recent years, there has been significant advancement in genome sequencing technology and bioinformatic data analysis. It has helped to generate millions of whole genome sequences, available in public databases. Genome mining is extremely helpful for nature-based bioactive compound discovery (Bauman et al. 2021). Genome-guided biodiscovery identified genes and gene clusters that are involved in the biosynthesis of natural products such as antibiotics and other bioactive compounds. In addition, regulatory elements essential for the production of natural products are also identified (Pham et al. 2019; Kautsar et al. 2021).

Biosynthetic gene clusters (BGCs) are clusters of non-homologous genes that are physically close to one another on the genome, are tightly linked and participate in the common metabolic pathway. Computational analysis of biosynthetic gene clusters has enhanced natural product discovery by enabling the rapid investigation of secondary metabolic potential within microbial genome sequences (Kautsar et al., 2020). This approach has the advantage of being faster and more efficient than traditional methods of isolating bioactive compounds (Bauman et al. 2021). Since the method involves genetic-level understanding, detailed information on biochemical processes in the synthesis of these compounds can be gained. Hence, one can optimize the production of bioactive molecules or produce novel analogues with improved properties (Atanasov et al. 2021).

One of the most commonly used tools for identifying BGCs in bacteria, fungi and plant genomes is antiSMASH (antibiotics & Secondary Metabolite Analysis Shell) (Medema et al. 2011). It uses a combination of algorithms to predict the structure and function of the biosynthetic gene clusters, as well as the potential bioactive molecules that they produce. In addition to antiSMASH, there are several other tools and bioinformatic pipelines that can be used to predict biosynthetic gene clusters (BGCs), including MIBiG (Minimum Information about a Biosynthetic Gene cluster) (Medema et al. 2015)and PRISM (Prediction Informatics for Secondary Metabolomes) (Skinnider et al. 2015).

Recently, whole genome sequence analysis has revealed the presence of BGCs in several halophilic bacteria (Lach et al. 2021; Athmika et al. 2021; Y. Liu and Ojika 2023). However, a thorough analysis of the diversity and distribution of BGCs for halophilic bacteria is yet not done. To fill the gap, in this study, we utilized the available genomic information for the halophilic bacteria in the public domain to identify the BGCs. We had two hypotheses: most of the halophilic bacteria possess BGCs which help them to survive in saline conditions, and different classes of BGCs are produced by phylogenetically diverse bacteria.

Halophilic bacterial species and genome mining

We used the HaloDom database (https://halodom.bio.auth.gr/) to assess information on halophilic organisms. HaloDom has data on halophilic organisms across the three domains: Bacteria, Archaea, and Eukarya. The database provides taxonomic information, halotolerance classification, and genomic information via NCBI and other primary databases (Loukas et al. 2018). It was created in June 2017 and maintained by the School of Biology, Aristotle University of Thessaloniki, Greece. This most comprehensive halophile database contains 1268 entries of halophiles including 282 Archaea, 670 Bacteria and 316 Eukarya currently registered in the database.

The available species data was imported into Microsoft Excel, 2021 (Microsoft Corporation). We then sorted and arranged the data to extract only information on halophilic bacteria. After obtaining a total of 670 bacterial entries, we further checked for their genome availability in the NCBI Genome (https://www.ncbi.nlm.nih.gov/genome). We found that out of the 670 halophilic bacteria, 454 species have genome sequences available in the public database. Three levels of genome completeness were found for different species: complete, scaffold, or contigs. All three types of genomes were included in our study to maximize the diversity of the dataset and ensure it covers a broad range of biosynthetic gene clusters from halophilic bacteria. The genomic information for 454 entries was obtained in the GenBank Flat File Format (.gbff) for further analysis.

Identification of BGCs

We utilized the antiSMASH 6.0 (Blin et al. 2021) pipeline to identify biosynthetic gene clusters (BGCs) in the halophilic bacterial genomes. AntiSMASH is an open-source tool that allows the rapid genome-wide identification, annotation, and analysis of secondary metabolite biosynthesis gene clusters in bacterial genomes. It is powered by several open-source tools: NCBI BLAST+, HMMer 3, Muscle 3, Glimmer 3, FastTree, TreeGraph 2, Indigo-depict, PySVG and JQuery SVG. It integrates and cross-links with a large number of available in-silico secondary metabolite analysis tools. All the extra features such as KnownClusterBlast, ClusterBlast, SubClusterBlast, MIBiG cluster comparison, ActiveSiteFinder, RREFinder, Cluster Pfam analysis, Pfam-based GO term annotation, TIGRFam analysis and TFBS analysis, were on to detect additional genes that may play a role in the biosynthesis, regulation, or modification of secondary metabolites.

After obtaining the results of the antiSMASH analysis, we manually curated the data by categorizing and organizing the detected biosynthetic gene clusters in the spreadsheet. This process involved reviewing and sorting through the results to ensure that only the relevant data were included in the analysis. We removed any duplicate entries, corrected any errors or inconsistencies in the data, and standardized the format of the entries to facilitate analysis. Once the data were curated, we performed statistical analysis to identify trends and patterns in the biosynthetic gene clusters. Specifically, we examined the frequency and distribution of the different types of gene clusters detected in the halophilic bacterial genomes, as well as their functional properties. We did regression analysis for BGCs and genome size to identify significant trends and relationships in the data.

Phylogenetic diversity using 16S rRNA gene sequence

We obtained 16S rRNA gene sequences for 454 halophilic bacterial species from NCBI GenBank (https://www.ncbi.nlm.nih.gov/genbank/). The gene sequences were aligned using ClustalW (Thompson et al. 1994) integrated within BioEdit (Hall 1999). The aligned file was then edited to remove any ambiguous bases and primer ends were trimmed to improve the alignment. We then used the sequences for phylogenetic tree construction based on the neighbour-joining method in MEGA 11 (Tamura et al. 2021). A bootstrap value of 1000 was used to estimate the reliability of branches in the tree. The 16S rRNA gene sequence of extreme halophilic archaea Haloarcula sebkhae was used as an outgroup.

Distribution of BGCs in Halophilic Bacteria

After inferring the evolutionary relationships between halophilic bacteria based on their 16S rRNA gene sequences, we analysed, if the diversity and distribution of BGCs follow a pattern of phylogenetic diversity. To visualize the distribution of BGC classes across the phylogenetic tree of the 454 halophilic bacterial genomes, we used the Interactive Tree of Life, iTOL v5 (https://itol.embl.de/) (Letunic and Bork 2021). The 16S rRNA gene phylogeny in the Newick format was visualized in iTOL. A BGCs dataset was created to map the BGCs distribution onto the phylogenetic tree for 454 halophilic bacterial genomes. We then uploaded this BGC dataset to iTOL and used its annotation features to map the BGC classes onto the phylogenetic tree. This enabled us to visualize the distribution of different BGC classes across the phylogenetic tree and investigate the evolutionary relationship between the genomes and their potential to produce certain types of natural products.

Halophilic Bacterial Genomic Information

In this study, we conducted a systematic investigation of the biosynthetic potential of 454 halophilic bacterial species using their genome sequences. Among 454, 64 complete genomes, 203 scaffold genomes, and 167 contig genomes were identified (Supplementary Fig. 1). To maximize the diversity of our dataset and capture a broad range of biosynthetic gene clusters (BGCs) from halophilic bacteria, we included genomes at all 3-assembly levels in the study. Based on the halotolerance classification of halophilic bacteria, out of 454, 55 were extreme halophiles, 350 were moderate halophiles, and 49 were slight halophiles (Supplementary Fig. 2). We also wanted to understand the distribution of the three halotolerant categories (extreme, moderate, and slight) within our dataset and the level of their genome assembly. We found that 14%, 13% and 22% of the complete genome were available for the species belonging to slight, moderate and extreme halotolerance respectively. While 33%, 48%, and 36% of genomes were at scaffold level in slight, moderate and extreme halotolerant bacteria respectively. 53%, 39%, and 42% of genomes were assembled at the level of contigs in slight, moderate and extreme halo bacteria, respectively (Supplementary Fig. 3). These findings suggest that the completeness of the genomes varied across the halotolerance categories.

Halophilic Bacteria harbours diverse BGCs

Subsequently, we employed the antiSMASH 6.0 bacterial version to extract the biosynthetic gene clusters (BGCs) encoding for natural products from the 454 halophilic bacterial species. Similar to recent research reports (Qiu et al. 2023; Galal et al. 2023; Abdel-Mageed et al. 2020), our analysis also showed that the halophilic bacteria possessed a wide range of BGCs that have the potential to produce various natural products. We identified a total of 58 different BGC classes, including acyl_amino_acids, amglyccycl, arylpolyene, betalactone, butyrolactone, CDPS, cyanobactin, cyclic-lactone-autoinducer, ectoine, furan, hserlactone, glycocin, guanidinotides, HgIE-KS, indole, ladderane, lanthipeptide-class-i, lanthipeptide-class-ii, lanthipeptide-class-iii, lanthipeptide-class-iv, lanthipeptide-class-v, LAP, lassopeptide, linaridin, melanin, microviridin, NAGGN, NAPAA, NRPS, NRPS-like, nucleoside, oligosaccharide, phenazine, phosphonate, PKS-like, proteusin, prodigiosin, ranthipeptide, redox-cofactor, resorcinol, RiPP-like, RRE containing, sactipeptide, siderophore, spliceotide, terpene, thioamides, thiopeptide, thioamide-NRP, transAT-PKS, transAT-PKS-like, T1PKS, T2PKS, T3PKS, PBDE, PUFA, and tropodithietic-acid. (Fig. 1).

Interestingly, we observed a variable class of BGCs among the species. The number of BGCs varied between 0 to 44 per genome with a mean of 6.11 and a standard deviation of 5.59. Only 7 species namely Desulfovibrio gracilis, Mycoplasma marinum, Mycoplasma todarodis, Salinicoccus carnicancrihas, Salinicoccus halodurans, Salinimonas chungwhensis, and Salinimonas iocasae has the genome with no BGCs. Five of these species were moderate halotolerant and 2 slight halotolerant. We found contig level genome assembly for 4 species, a complete genome for 2 species and a scaffold for 1 species (Suppl Table 1). A total of 447 species out of 454 show the presence of BGCs in their genome indicating their potential for bioactive compound production. At least 2 BGCs were found in the genome of more than 400 species. These results validate our first hypothesis that most halophilic bacteria possess BGCs and can be utilized for various biotechnological applications for the betterment of human beings. A complete table of halobacteria with the number of BGC classes is given in Supplementary Table 2.

The most common BGCs were ectoine found in 291 genomes, terpene in 268 genomes, betalactone in 171 genomes, T3PKS in 170 genomes, and RiPP-like in 149 genomes. These BGCs were present across the diverse bacterial taxa, emphasizing the need for these secondary metabolites for survival in the dynamic environment. In general, high occurrences of terpene-, NRP-, and PK-encoding gene clusters have been reported in marine systems (Yi et al. 2024). The common occurrence of ectoine gene clusters suggests that a large number of halophilic bacteria can be utilized for ectoine production in the cosmetic and medical sectors (Lach et al. 2021). We also found that a few species carry multiple copies of the same or different BGC classes. For instance, Streptomyces chilikensis was found to carry a diverse array of BGCs including 1 amglyccyl, 4 butyrolactone, 1 indole, 1 melanin, 1 ectoine, 5 NRPS, 4 NRPS-like, 3 RiPP-like, 2 siderophore, 6 terpene, 1 trans-AT-PKS, 13 T1PKS, 1 T3PKS. However, the presence of a large number of BGCs in the members of phylum Actinomycetota was not surprising, as most of them have proven bioactivity potentials (Belknap et al. 2020; Z. Liu et al. 2021; Bruna et al. 2024; Seshadri et al. 2022; Parra et al. 2023). Some BGCs were uncommon and found only in a few genomes (Table 1).

Table 1

Uncommon BGCs observed in the genome of less than 5 halotolerant bacterial species
BGCs	Number of genomes	Species
CDPS	5	Nocardiopsis halotolerans, Nocardiopsis xinjiangensis, Salinivibrio costicola, Actinopolyspora erythraea
Cyanobactin	2	Nodularia spumigena, Microcoleus chthonoplastes
Furan	3	Actinopolyspora erythraea, Nocardiopsis halotolerans, Zhihengliuella salsuginis
Glycocin	2	Bacillus salaries, Bacillus oshimensis
Guanidinotides	2	Saccharopolyspora lacisalsi, Streptomonospora alba
Lanthipeptide-class-iv	2	Aliicoccus persicus, Halomonas cerina
Lanthipeptide-class-v	4	Nodularia spumigena, Chlorogloea fritschii, Nocardiopsis halotolerans Microcoleus chthonoplastes
Melanin	1	Streptomyces chilikensis
Microviridin	1	Nodularia spumigena
Nucleoside	2	Actinopolyspora erythraea Nocardiopsis kunsanensis
Spliceotide	1	Nodularia spumigena
Thioamide-NRP	4	Cellulosimicrobium cellulans, Streptomonospora litoralis, Cyclobacterium plantarum, Paracoccus halophilus
PBDE	1	Microbulbifer rhizosphaerae
Tropodithietic-acid	1	Halomonas zhaodongensis

Further, the correlation analysis between genome size and the number of BGCs revealed a moderate positive correlation with an R-squared value of 0.4038. (Fig. 2). Earlier studies have also reported a mild positive correlation (R2 = 0.29) between the number of BGCs and genome size of Streptomyces (Belknap et al. 2020), Actinobacteria (Seshadri et al. 2022), members of the phylum Bacteroidetes (Brinkmann et al. 2021) and several bacterial species (Cimermancic et al. 2014).

BGCs-rich bacteria form separate clades in 16S rRNA gene phylogeny

The halophilic bacteria belonged to the ten different phyla, namely Actinomycetota, Bacteroidota, Balneolota, Cyanobacteriota, Bacillota, Pseudomonadota, Rhodothermota, Synergistota, Mycoplasmatota, and Thermotogota. The phylogenetic tree based on the 16S rRNA gene sequence showed distinct clusters of related taxa and provided a framework for further analysis of the distribution of BGCs among the different lineages. The phylogenetic tree analysis conducted in this study revealed the presence of six well-defined clades, each of which was represented by a distinct colour in the phylogenetic tree (Fig. 3). These clades belong to different phyla, highlighting the diversity of halophilic bacterial species and their evolutionary relationships. The integration of BGCs and the phylogenetic tree revealed that even though most of the species have BGCs, the distribution of BGCs is not evenly distributed among the different clades. The genomes of a few particular taxa were rich in the BGCs highlighting certain taxa may have a greater potential for producing bioactive compounds than others (Supplementary Table 3).

Clade 1 (highlighted as a red clade in Fig. 3) consisted of a single member of the phylum Thermotogota, Synergistota, and 17 members belong to the order Halanaerobiales of phylum Bacillota. The unique BGCs ranged from 1 to 5 among different species, which is relatively lower compared to other clades. The most common BGCs found in clade 1 were RiPP-like, Cyclic lactone-autoinducer, and terpene.

Clade 2 was particularly interesting as it consisted of members of the phylum Actinomycetota. These species were found to carry between 2 and 44 BGCs per genome. Among the identified BGCs, Terpene, ectoine, siderophore, T1PKS, T3PKS, NRPS, and RiPP-like were found to be the most common BGCs. The other BGCs found in clade 2 were RRE containing, Lanthipeptide-class-I, Lassopeptide, Butyrolactone, Betalactone, LAP, T2PKS, Arylpolyene, PKS-like, HgIE-KS, Ladderane, Linaridin, Lanthipeptide-class-iii, NAPAA, Oligosaccharide, Redox-cofactor, Thiopeptide, Indole, Ranthipeptide, CDPS, Phenazine, Amglyccycl, Furan, NAGGN, transAT-PKS, transAT-PKS-like, Guanidinotides, Lanthipeptide-class-ii, Nucleoside, Phosphonate, Resorcinol, Thioamitides, Thioamide-NRP, Hserlactone, Lanthipeptide-class-v, Melanin and Prodigiosin. Upon further investigation, we found that Nocardiopsis halotolerans had the highest number of 20 unique BGCs, followed by Actinopolyspora erythraea with 19 BGCs, Nocardiopsis terrae with 17 BGCs, and Actinopolyspora mortivallis with 16 BGCs. This clade was found to carry a higher number of BGCs compared to other classes of halophilic bacteria. Some of the uncommon BGCs such as melanin and furan were produced only by the members of this phylum. The high number of BGCs in this phylum was expected as we know that most members are promising strains for the bioactive compounds (Belknap et al. 2020; Z. Liu et al. 2021; Bruna et al. 2024; Seshadri et al. 2022; Parra et al. 2023). Nocardiopsis halophila, the halophilic actinomycete that was isolated from soil, has been identified as a potential source of bioactive compounds. Studies have reported that Nocardiopsis species produce a variety of bioactive compounds, including antimicrobial agents (Bennur et al., 2015). A recent study reported the identification and characterization of a fluorinase from Actinopolyspora mzabensis (Sooklal et al., 2020).

Clade 3, which is composed of 139 species, mostly belonging to the phylum Bacillota, exhibited up to 13 BGCs per genome. Notably, two genomes in this clade, Salinicoccus carnicancri and Salinicoccus halodurans, contained no BGCs. The most commonly found BGCs in clade 3 were Terpene, T3PKS, and Ectoine, with 100, 97, and 94 genomes containing these BGCs, respectively. A recent study has shown Terpene, NRPS, and PKS BGCs found to be widespread in the marine environment (Yi et al. 2024). The other BGCs found in clade 3 species were Betalactone, siderophore, RiPP-like, Lassopeptide, NRPS, LAP, RRE containing, Cyclic-lactone-autoinducer, Lanthipeptide-ii, NRPS-like, Ranthipeptide, Phosphonate, T1PKS, Thiopeptide, Glycocin, Lanthipeptide-class-iii, transAT-PKS, hserlactone, lanthipeptide-class-i, lanthipeptide-class-iv, Redox-cofactor, sactipeptide, and transAT-PKS-like. These results suggest that species in clade 3 have a diverse range of biosynthetic capabilities, with some species producing a relatively small number of BGCs and others producing a much larger number. The presence of a wide variety of BGCs in clade 3 suggests that these species may be a valuable resource for the discovery of novel bioactive compounds. However, further research is needed to investigate the bioactivity of these compounds and their potential for drug discovery.

Clade 4, consisting of 6 species belonging to the Phylum Cyanobacteriota, has been found to carry a considerable number of biosynthetic gene clusters (BGCs) per genome, ranging from 3 to 25. The finding is in line with previous studies where a phylum-wide investigation of genetic diversification of the cyanobacterial NRPS and PKS pathways for the production of bioactive compounds revealed 452 NRPS and PKS gene clusters from 89 cyanobacterial genomes (Calteau et al. 2014). The presence of BGCs in Aphanothece halophytica suggests its potential for bioactivity. Indeed, earlier studies have shown the compounds isolated and purified from this bacterium are antibacterial and cytotoxic (Vishwakarma, 2013; Vishwakarma & Rai, 2013). Further, presence of the uncommon BGCs such as cyanobactin, microviridin, and spliceotide in the genome of Nodularia spumigena, makes it a suitable candidate for bioprospection.

Clade 5 was composed of 32 species belonging to three different phyla: Bacteroidota, Rhodothermota, and Balneolota. Our analysis reveals that these species carry a relatively low number of biosynthetic gene clusters (BGCs), ranging from 1 to 5 per genome.

Clade 6 contains the highest number of halophilic bacteria. A few species namely, Desulfovibrio gracilis, Salinimonas chungwhensis, Salinimonas iocasae, Mycoplasma marinum, and Mycoplasma todarodis, have no BGCs in their genomes. The highest number of 33 BGCs was found in the genome of Haliangium ochraceum. This is the only representative of the class Myxococcales of Deltaproteobacteria. The second-highest 30 BGCs in this clade were found in the genome of Gynuella sunshinyii, belonging to the class Gammaproteobacteria. These findings suggest that these species may have a greater potential for producing bioactive compounds and could be promising candidates for further investigation in natural product discovery. Indeed, earlier studies have reported that the biosynthetic gene cluster of haliamide, a new PKS-NRPS hybrid metabolite, and Haliangicin was characterized in the marine myxobacterium Haliangium ochraceum (Gemperlein et al. 2018; Sun et al. 2016). Earlier reports have also suggested unexplored biosynthetic potential of the members of the Myxococcales based on genomic studies (Gregory et al. 2019). Gynuella sunshinyii is a plant-associated marine bacterium belonging to the order Oceanospirillales that has been identified as a chemically unexplored bacterial taxon with high numbers of biosynthetic gene clusters. This species was first isolated from a halophyte, Carex scabrifolia Steud having an antifungal activity (Chung et al. 2015). In silico, chemical prediction of a non-canonical polyketide synthase cluster led to the discovery of janustatins, structurally unprecedented cytotoxins from G. sunshinyii (Ueoka et al. 2022).

Other members of Gammaproteobacteria have an average of 5 BGCs in their genome. The most common BGCs found in Clade 6 were ectoine (166 genomes), betalactone (105 genomes), terpene (86 genomes), RiPP-like (82 genomes), siderophore (77 genomes), redox-cofactor (73 genomes), and arylpolyene (61 genomes). Other BGCs found in Clade 6 include NRPS-like, T1PKS, hserlactone, NRPS, RRE containing, T3PKS, Lassopeptide, Ranthipeptide, resorcinol, thiopeptide, LAP, NAGGN, acyl amino acids, butryolactone, HgIE-KS, phosphonate, PUFA, proteusin, prodigiosin, thioamitides, ladderane, CDPS, Lanthipeptide-class-iv, Lanthipeptide-class-i, NAPAA, oligosaccharide, phenazine, PKS-like, Thioamide-NRP, transAT-PKS, and PBDE.

The presence of BGCs in most halophilic bacteria supports the hypothesis that bacteria need secondary metabolites to survive and grow in the harsh conditions of the hypersaline environment. These metabolites can be used as a potential bioactive compound for the betterment of human mankind. Some of the BGCs such as ectoine, terpenes etc were common among the majority of the species. While a few species in a particular clade have a high number of BGCs making them a potential target for the biosynthetic potentials. The findings of this study will also guide future research to focus on specific taxa for specific biosynthetic compounds from the halophilic conditions.

Author contribution

Amit Kumar supervised the study, analysed the results, wrote the first draft, and subsequent revision of the manuscript. Nivetha R conducted the genome mining, prepared the results and analysis.

Funding

No extramural funding is received for this study.

Declaration

The authors declare no competing interests.

Acknowledgments and Funding Information

We would like to thank the management of the Sathyabama Institute of Science and Technology for providing necessary facilities to carry out this research work. No external funding was received for this study.

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No competing interests reported.

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Diversity and Distribution of Biosynthetic Gene Clusters in the Halophilic Bacteria

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Abstract

Figures

Introduction

Materials and methods

Halophilic bacterial species and genome mining

Identification of BGCs

Phylogenetic diversity using 16S rRNA gene sequence

Distribution of BGCs in Halophilic Bacteria

Results and Discussion

Halophilic Bacterial Genomic Information

Halophilic Bacteria harbours diverse BGCs

BGCs-rich bacteria form separate clades in 16S rRNA gene phylogeny

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

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