Research Article Open Access Research Article Open Access Aiman et al., J Proteomics Bioinform 2018, 11:1 DOI: 10.4172/jpb.1000460 Journal of Proteomics & Bioinformatics J o u r n a l o f P r o t e o m i c s & B i o i n f o r m a t i c s ISSN: 0974-276X Volume 11(1) 001-007 (2018) - 1 J Proteomics Bioinform, an open access journal ISSN: 0974-276X *Corresponding author: Asifullah Khan, Assistant Professor, Department of Biochemistry, Abdul Wali Khan University Mardan, Mardan, Pakistan, Tel: +92- 937-929122; E-mail: asif@awkum.edu.pk Received December 07, 2017; Accepted January 10, 2018; Published January 17, 2018 Citation: Aiman S, Shehroz M, Munir M, Gul S, Shah M, et al. (2018) Species-Wide Genome Mining of Pseudomonas putida for Potential Secondary Metabolites and Drug-Like Natural Products Characterization. J Proteomics Bioinform 11: 001-007. doi: 10.4172/jpb.1000460 Copyright: © 2018 Aiman S, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Keywords: Biosynthetic gene cluster; Secondary metabolites; Pseudomonas putida; Bacterial genomics Introduction Microbial secondary metabolites are small organic compounds play important role in the survival of microbial culture and ecological interaction with other organisms [1]. Microbial natural products are used as agricultural, dietary and pharmaceutical agents. Tese include nonribosomal peptides (NRPs), polyketides (PKs), post- translationally modifed peptides (RiPPs), ribosomally synthesized compounds, saccharides, terpenoids and some hybrids natural products. Te biosynthesis of these secondary metabolites are directed by group of genes physically located within a single locus on microbial chromosomal and plasmid DNA termed as Biosynthetic Gene Clusters (BGCs). Tese clusters allow the concerted expression of necessary biosynthetic, regulatory enzymes and transporter proteins require for biosynthesis, mechanism of action and transport of secondary metabolites [2]. Te rich genetic diversity of microbial BGCs due to evolutionary basis eventually cause high chemical diversity in their underlie coding secondary metabolites [3,4]. Te P. putida is a gram-negative bacterium typically colonizes at soil and aquatic habitats. Te strains of this species exhibit wide metabolic versatility driving their adaptability to diverse habitats. Te P. putida strains are important for the biosynthesis of variety of biotechnological signifcant natural products by heterologous expression of diverse biosynthetic pathways [5]. P. putida ofer several particular advantages with respect to natural product biosynthesis, notably a versatile intrinsic metabolism with diverse enzymatic capacities and outstanding tolerance to xenobiotics. Terefore, P. putida strains are potential source of antimicrobial agents and implement in recombinant biosynthesis of valuable natural products [5,6]. Te decreasing cost of genome-level DNA sequencing due to technological advancement in the form of next- generation sequencing allowed to understand the ecological diversity and dynamic functionality of microbial communities with increase resolution. Nowadays, these fast genome sequencing along with advance bioinformatics resources transformed the secondary Species-Wide Genome Mining of Pseudomonas putida for Potential Secondary Metabolites and Drug-Like Natural Products Characterization Sara Aiman, Muhammad Shehroz, Mehwish Munir, Sahib Gul, Mohibullah Shah and Asifullah Khan * Department of Biochemistry, Abdul Wali Khan University Mardan, Mardan-23200, Pakistan Abstract The gram negative bacteria species of Pseudomonas putida (P. putida) are important for heterologous expression of diverse biosynthetic pathways and numerous secondary metabolites biosynthesis. The genes code for such secondary metabolites biosynthetic proteins are organized in microbial genomes as clusters to bring the concerted expression of entire biosynthetic machinery. The complete and whole genome sequences of more than ffty different strains available in public DNA sequences databases provide an excellent opportunity to investigate the genetically encoded secondary metabolites potential of ecologically diverse P. putida strains. We implement the advance bioinformatics resources to annotate the so far available P. putida strains genomes for biosynthetic gene clusters (BGCs) and underlie secondary metabolites chemical scaffolds. The P. puida strains are found to harbor genomic signatures coding the molecular machinery for diverse secondary metabolites biosynthesis. The corresponding BGCs of these metabolites are found to be uniquely distributed across different P. putida strains speculate their role toward strain's ecological competency acquirement. The chemoinformatics dereplication and DrugBank database searching revealed the chemical mimicry of one putative metabolite with 2, 3, Dihydroxybenzoylserine, that mediates an antibiotic iron depletion along with human neutrophil lipocalin during innate immune response. metabolites discovery approaches towards more rational and predictive directions [7]. Moreover, the organization of BGCs as single locus on bacterial chromosomal and plasmid DNA actually eased these genomic motifs confdent in silico predictions based on fundamental principles of bioinformatics [8]. However, still the genome-guided microbial secondary metabolites discovery and knowledge is limited compare to bioassay screening. In this study, we adopted multiple computational biology resources to mine all publically available whole genome sequences of P. putida strains to elucidate the secondary metabolites coding potential of this species. Te chemical scafolds of putative secondary metabolites as identifed are further evaluated for drug-like potential using chemoinformatics resources. Material and Methods Genome sequences retrieval Te complete and partial genomes assemblies of 58 diferent stains and isolates of P. putida are retrieved from NCBI Genbank [9] and Integrated Microbial Genome (IMG) databases [10]. Te data retrieval was made in March 2016. Secondary metabolites prediction Several prediction models are implemented in bioinformatics resources for putative identifcation of BGCs responsible for