Harnessing the Genetic Diversity and Metabolic Potential of Extremophilic Microorganisms through the Integration of Metagenomics and Single-Cell Genomics

Microorganisms thriving under extreme environments have proven to be an invaluable resource for metabolic products and processes. While studies carried out on microbial characterization of extremophilic environments during golden era of microbiology adapted a ‘reductionist approach’ and focused on isolation, purification and characterization of individual microbial isolates; the recent studies have implemented a holistic approach using both culture-dependent and culture-independent approaches for characterization of total microbial diversity of the extreme environments. Findings from these studies have unmistakably indicated that microbial diversity within extreme environments is much higher than anticipated. Consequently, unraveling the taxonomic and metabolic characteristics of microbial diversity in extreme environments has emerged as an imposing challenge in the field of microbiology and microbial biotechnology. To a great extent, this challenge has been addressed with inception and advancement of next-generation sequencing and computing methods for NGS data analyses. However, further it has been realized that in order to maximize the exploitation of genetic and metabolic diversity of extremophilic microbial diversity, the metagenomic approaches must be combined synergistically with single-cell genomics. A synergistic approach is expected to provide comprehensions into the biology of extremophilic microorganism, including their metabolic potential, molecular mechanisms of adaptations, unique genomic features including codon reassignments etc

A process optimization for bio-catalytic production of substituted catechols (3-nitrocatechol and 3-methylcatechol

<p>Abstract</p> <p>Background</p> <p>Substituted catechols are important precursors for large-scale synthesis of pharmaceuticals and other industrial products. Most of the reported chemical synthesis methods are expensive and insufficient at industrial level. However, biological processes for production of substituted catechols could be highly selective and suitable for industrial purposes.</p> <p>Results</p> <p>We have optimized a process for bio-catalytic production of 3-substituted catechols viz. 3-nitrocatechol (3-NC) and 3-methylcatechol (3-MC) at pilot scale. Amongst the screened strains, two strains viz. <it>Pseudomonas putida </it>strain (F1) and recombinant <it>Escherichia coli </it>expression clone (pDTG602) harboring first two genes of toluene degradation pathway were found to accumulate 3-NC and 3-MC respectively. Various parameters such as amount of nutrients, pH, temperature, substrate concentration, aeration, inoculums size, culture volume, toxicity of substrate and product, down stream extraction, single step and two-step biotransformation were optimized at laboratory scale to obtain high yields of 3-substituted catechols. Subsequently, pilot scale studies were performed in 2.5 liter bioreactor. The rate of product accumulation at pilot scale significantly increased up to ~90-95% with time and high yields of 3-NC (10 mM) and 3-MC (12 mM) were obtained.</p> <p>Conclusion</p> <p>The biocatalytic production of 3-substituted catechols viz. 3-NC and 3-MC depend on some crucial parameters to obtain maximum yields of the product at pilot scale. The process optimized for production of 3-substituted catechols by using the organisms <it>P. putida </it>(F1) and recombinant <it>E. coli </it>expression clone (pDTG602) may be useful for industrial application.</p

Genes involved in degradation of para-nitrophenol are differentially arranged in form of non-contiguous gene clusters in Burkholderia sp. strain SJ98.

Biodegradation of para-Nitrophenol (PNP) proceeds via two distinct pathways, having 1,2,3-benzenetriol (BT) and hydroquinone (HQ) as their respective terminal aromatic intermediates. Genes involved in these pathways have already been studied in different PNP degrading bacteria. Burkholderia sp. strain SJ98 degrades PNP via both the pathways. Earlier, we have sequenced and analyzed a ~41 kb fragment from the genomic library of strain SJ98. This DNA fragment was found to harbor all the lower pathway genes; however, genes responsible for the initial transformation of PNP could not be identified within this fragment. Now, we have sequenced and annotated the whole genome of strain SJ98 and found two ORFs (viz., pnpA and pnpB) showing maximum identity at amino acid level with p-nitrophenol 4-monooxygenase (PnpM) and p-benzoquinone reductase (BqR). Unlike the other PNP gene clusters reported earlier in different bacteria, these two ORFs in SJ98 genome are physically separated from the other genes of PNP degradation pathway. In order to ascertain the identity of ORFs pnpA and pnpB, we have performed in-vitro assays using recombinant proteins heterologously expressed and purified to homogeneity. Purified PnpA was found to be a functional PnpM and transformed PNP into benzoquinone (BQ), while PnpB was found to be a functional BqR which catalyzed the transformation of BQ into hydroquinone (HQ). Noticeably, PnpM from strain SJ98 could also transform a number of PNP analogues. Based on the above observations, we propose that the genes for PNP degradation in strain SJ98 are arranged differentially in form of non-contiguous gene clusters. This is the first report for such arrangement for gene clusters involved in PNP degradation. Therefore, we propose that PNP degradation in strain SJ98 could be an important model system for further studies on differential evolution of PNP degradation functions

Chemotaxis of <it>Burkholderia </it>sp. Strain SJ98 towards chloronitroaromatic compounds that it can metabolise

Abstract Background Burkholderia sp. strain SJ98 is known for its chemotaxis towards nitroaromatic compounds (NACs) that are either utilized as sole sources of carbon and energy or co-metabolized in the presence of alternative carbon sources. Here we test for the chemotaxis of this strain towards six chloro-nitroaromatic compounds (CNACs), namely 2-chloro-4-nitrophenol (2C4NP), 2-chloro-3-nitrophenol (2C3NP), 4-chloro-2-nitrophenol (4C2NP), 2-chloro-4-nitrobenzoate (2C4NB), 4-chloro-2-nitrobenzoate (4C2NB) and 5-chloro-2-nitrobenzoate (5C2NB), and examine its relationship to the degradation of such compounds. Results Strain SJ98 could mineralize 2C4NP, 4C2NB and 5C2NB, and co-metabolically transform 2C3NP and 2C4NB in the presence of an alternative carbon source, but was unable to transform 4C2NP under these conditions. Positive chemotaxis was only observed towards the five metabolically transformed CNACs. Moreover, the chemotaxis was induced by growth in the presence of the metabolisable CNAC. It was also competitively inhibited by the presence of nitroaromatic compounds (NACs) that it could metabolise but not by succinate or aspartate. Conclusions Burkholderia sp. strain SJ98 exhibits metabolic transformation of, and inducible chemotaxis towards CNACs. Its chemotactic responses towards these compounds are related to its previously demonstrated chemotaxis towards NACs that it can metabolise, but it is independently inducible from its chemotaxis towards succinate or aspartate.</p

Phylogenetic tree of amino acid sequences (A) <i>p</i>-nitrophenol 4-monooxygenase (PnpM), Benzenetriol dioxygenase (BtD) from stain SJ98 was taken as outgroup for the phylogenetic tree for PNP monooxygenases and (B) p-benzoquinone reductase (BqR), nitrite reductase from <i>E. coli</i> was taken as an outgroup to create the phylogenetic tree for the benzoquinone reductases.

<p>Neighbor joining method was applied at the bootstrap value of 1000. Accession number of the proteins is written in parentheses.</p

Comparison of <i>p</i>-nitrophenol (PNP) degradation gene clusters from different bacterial strains, schematic representation of the ORFs and distance between the gene clusters when arranged together as shown in <i>pnpAB</i> and <i>pnpCDE1E2F</i>

<div><p>(A) schematic representation of distance between Contig 11 (NZ_AJHK02000011.1) and contigs 12 (NZ_AJHK02000012.1) (B) if contigs 12 and then contigs 11 placed in series together then distance between the gene clusters and (C) PNP degradation gene clusters found in the other PNP degrading bacteria <i>Pseudomonas</i> sp. NyZ402 (GU123925.1), <i>Pseudomonas putida</i> DLLE-4 (FJ376608), <i>Pseudomonas</i> sp. 1-7 (FJ821777) and <i>Pseudomonas</i> sp. WBC-3 (EF577044).</p> <p>Similar genes have been assigned by the same colors.</p></div

Identification of gefitinib off-targets using a structure-based systems biology approach; their validation with reverse docking and retrospective data mining

Gefitinib, an EGFR tyrosine kinase inhibitor, is used as FDA approved drug in breast cancer and non-small cell lung cancer treatment. However, this drug has certain side effects and complications for which the underlying molecular mechanisms are not well understood. By systems biology based in silico analysis, we identified off-targets of gefitinib that might explain side effects of this drugs. The crystal structure of EGFR-gefitinib complex was used for binding pocket similarity searches on a druggable proteome database (Sc-PDB) by using IsoMIF Finder. The top 128 hits of putative off-targets were validated by reverse docking approach. The results showed that identified off-targets have efficient binding with gefitinib. The identified human specific off-targets were confirmed and further analyzed for their links with biological process and clinical disease pathways using retrospective studies and literature mining, respectively. Noticeably, many of the identified off-targets in this study were reported in previous high-throughput screenings. Interestingly, the present study reveals that gefitinib may have positive effects in reducing brain and bone metastasis, and may be useful in defining novel gefitinib based treatment regime. We propose that a system wide approach could be useful during new drug development and to minimize side effect of the prospective drug

Predicted positions for the activity of <i>pnpA</i> and <i>pnpB</i> in <i>p</i>-nitrophenol (PNP) degradation pathway of strain SJ98.

<p>Predicted positions for the activity of <i>pnpA</i> and <i>pnpB</i> in <i>p</i>-nitrophenol (PNP) degradation pathway of strain SJ98.</p