Diet, Microbiota and Gut-Lung Connection

The gut microbial community (Gut microbiota) is known to impact metabolic functions as well as immune responses in our body. Diet plays an important role in determining the composition of the gut microbiota. Gut microbes help in assimilating dietary nutrients which are indigestible by humans. The metabolites produced by them not only modulate gastro-intestinal immunity, but also impact distal organs like lung and brain. Micro-aspiration of gut bacteria or movement of sensitized immune cells through lymph or bloodstream can also influence immune response of other organs. Dysbiosis in gut microbiota has been implicated in several lung diseases, including allergy, asthma and cystic fibrosis. The bi-directional cross-talk between gut and lung (termed as Gut-Lung axis) is best exemplified by intestinal disturbances observed in lung diseases. Some of the existing probiotics show beneficial effects on lung health. A deeper understanding of the gut microbiome which comprises of all the genetic material within the gut microbiota and its role in respiratory disorders is likely to help in designing appropriate probiotic cocktails for therapeutic applications

FLIM-MAP: Gene Context Based Identification of Functional Modules in Bacterial Metabolic Pathways

Prediction of functional potential of bacteria can only be ascertained by the accurate annotation of its metabolic pathways. Homology based methods decipher metabolic gene content but ignore the fact that homologs of same protein can function in different pathways. Therefore, mere presence of all constituent genes in an organism is not sufficient to indicate a pathway. Contextual occurrence of genes belonging to a pathway on the bacterial genome can hence be exploited for an accurate estimation of functional potential of a bacterium. In this communication, we present a novel annotation resource to accurately identify pathway presence by using gene context. Our tool FLIM-MAP (Functionally Important Modules in bacterial Metabolic Pathways) predicts biologically relevant functional units called ‘GCMs’ (Gene Context based Modules) from a given metabolic reaction network. We benchmark the accuracy of our tool on amino acids and carbohydrate metabolism pathways

SBSPKS: structure based sequence analysis of polyketide synthases

Polyketide synthases (PKSs) catalyze biosynthesis of a diverse family of pharmaceutically important secondary metabolites. Bioinformatics analysis of sequence and structural features of PKS proteins plays a crucial role in discovery of new natural products by genome mining, as well as in design of novel secondary metabolites by biosynthetic engineering. The availability of the crystal structures of various PKS catalytic and docking domains, and mammalian fatty acid synthase module prompted us to develop SBSPKS software which consists of three major components. Model_3D_PKS can be used for modeling, visualization and analysis of 3D structure of individual PKS catalytic domains, dimeric structures for complete PKS modules and prediction of substrate specificity. Dock_Dom_Anal identifies the key interacting residue pairs in inter-subunit interfaces based on alignment of inter-polypeptide linker sequences to the docking domain structure. In case of modular PKS with multiple open reading frames (ORFs), it can predict the cognate order of substrate channeling based on combinatorial evaluation of all possible interface contacts. NRPS–PKS provides user friendly tools for identifying various catalytic domains in the sequence of a Type I PKS protein and comparing them with experimentally characterized PKS/NRPS clusters cataloged in the backend databases of SBSPKS. SBSPKS is available at http://www.nii.ac.in/sbspks.html

In silico methods for linking genes and secondary metabolites: The way forward

In silico methods for linking genomic space to chemical space have played a crucial role in genomics driven discovery of new natural products as well as biosynthesis of altered natural products by engineering of biosynthetic pathways. Here we give an overview of available computational tools and then briefly describe a novel computational framework, namely retro-biosynthetic enumeration of biosynthetic reactions, which can add to the repertoire of computational tools available for connecting natural products to their biosynthetic gene clusters. Most of the currently available bioinformatics tools for analysis of secondary metabolite biosynthetic gene clusters utilize the “Genes to Metabolites” approach. In contrast to the “Genes to Metabolites” approach, the “Metabolites to Genes” or retro-biosynthetic approach would involve enumerating the various biochemical transformations or enzymatic reactions which would generate the given chemical moiety starting from a set of precursor molecules and identifying enzymatic domains which can potentially catalyze the enumerated biochemical transformations. In this article, we first give a brief overview of the presently available in silico tools and approaches for analysis of secondary metabolite biosynthetic pathways. We also discuss our preliminary work on development of algorithms for retro-biosynthetic enumeration of biochemical transformations to formulate a novel computational method for identifying genes associated with biosynthesis of a given polyketide or nonribosomal peptide

Comparative In silico Analysis of Butyrate Production Pathways in Gut Commensals and Pathogens

Biosynthesis of butyrate by commensal bacteria plays a crucial role in maintenance of human gut health while dysbiosis in gut microbiome has been linked to several enteric disorders. Contrastingly, butyrate shows cytotoxic effects in patients with oral diseases like periodontal infections and oral cancer. In addition to these host associations, few syntrophic bacteria couple butyrate degradation with sulfate reduction and methane production. Thus, it becomes imperative to understand the distribution of butyrate metabolism pathways and delineate differences in substrate utilization between pathogens and commensals.The bacteria utilize four pathways for butyrate production with different initial substrates (Pyruvate, 4-aminobutyrate, Glutarate and Lysine) which follow a polyphyletic distribution. A comprehensive mining of complete/draft bacterial genomes indicated conserved juxtaposed genomic arrangement in all these pathways. This gene context information was utilized for an accurate annotation of butyrate production pathways in bacterial genomes. Interestingly, our analysis showed that inspite of a beneficial impact of butyrate in gut, not only commensals, but a few gut pathogens also possess butyrogenic pathways. The results further illustrated that all the gut commensal bacteria (Faecalibacterium, Roseburia, Butyrivibrio, commensal species of Clostridia etc) ferment pyruvate for butyrate production. On the contrary, the butyrogenic gut pathogen Fusobacterium utilizes different amino acid metabolism pathways like those for Glutamate (4-aminobutyrate and Glutarate) and Lysine for butyrogenesis which leads to a concomitant release of harmful by-products like ammonia in the process. The findings in this study indicate that commensals and pathogens in gut have divergently evolved to produce butyrate using distinct pathways. No such evolutionary selection was observed in oral pathogens (Porphyromonas and Filifactor) which showed presence of pyruvate as well as amino acid fermenting pathways which might be because the final product butyrate is itself known to be cytotoxic in oral diseases. This differential utilization of butyrogenic pathways in gut pathogens and commensals has an enormous ecological impact taking into consideration the immense influence of butyrate on different disorders in humans. The results of this study can potentially guide bioengineering experiments to design therapeutics/probiotics by manipulation of butyrate biosynthesis gene clusters in bacteria

Probing the amino acids critical for protein oligomerisation and protein–nucleotide interaction in Mycobacterium tuberculosis PII protein through integration of computational and experimental approaches

We investigated the interacting amino acids critical for the stability and ATP binding of Mycobacterium tuberculosis PII protein through a series of site specific mutagenesis experiments. We assessed the effect of mutants using glutaraldehyde crosslinking and size exclusion chromatography and isothermal titration calorimetry. Mutations in the amino acid pair R60–E62 affecting central electrostatic interaction resulted in insoluble proteins. Multiple sequence alignment of PII orthologs displayed a conserved pattern of charged residues at these positions. Mutation of amino acid D97 to a neutral residue was tolerated whereas positive charge was not acceptable. Mutation of R107 alone had no effect on trimer formation. However, the combination of neutral residues both at positions 97 and 107 was not acceptable even with the pair at 60–62 intact. Reversal of charge polarity could partially restore the interaction. The residues including K90, R101 and R103 with potential to form H-bonds to ATP are conserved throughout across numerous orthologs of PII but when mutated to Alanine, they did not show significant differences in the total free energy change of the interaction as examined through isothermal titration calorimetry. The ATP binding pattern showed anti-cooperativity using three-site binding model. We observed compensatory effect in enthalpy and entropy changes and these may represent structural adjustments to accommodate ATP in the cavity even in absence of some interactions to perform the requisite function. In this respect these small differences between the PII orthologs may have evolved to suite species specific physiological niches

Functional Potential of Bacterial Communities using Gene Context Information

Estimation of the functional potential of a bacterial genome can be determined by accurate annotation of its metabolic pathways. Existing homology based methods for pathway annotation fail to account for homologous genes that participate in multiple pathways, causing overestimation of gene copy number. Mere presence of constituent genes of a candidate pathway which are dispersed on a genome often results in incorrect annotation, thereby leading to erroneous gene abundance and pathway estimation. Clusters of evolutionarily conserved coregulated genes are characteristic features in bacterial genomes and their spatial arrangement in the genome is constrained by the pathway encoded by them. Thus, in order to improve the accuracy of pathway prediction, it is important to augment homology based annotation with gene organization information. In this communication, we present a methodology considering prioritization of gene context for improved pathway annotation. Extensive literature mining was performed to confirm conserved juxtaposed arrangement of gene components of various pathways. Our method was utilized to identify and analyse the functional potential of all available completely sequenced bacterial genomes. The accuracy of the predicted gene clusters and their importance in metabolic pathways will be demonstrated using a few case studies. One of such case study corresponds to butyrate production pathways in gut bacteria where it was observed that gut pathogens and commensals possess a distinct set of pathway components. In another example, we will demonstrate how our methodology improves the prediction accuracy of carbohydrate metabolic potential in human microbial communities. Applicability of our method for estimation of functional potential in bacterial communities present in diverse environments will also be illustrated

Novel intermolecular iterative mechanism for biosynthesis of mycoketide catalyzed by a bimodular polyketide synthase.

In recent years, remarkable versatility of polyketide synthases (PKSs) has been recognized; both in terms of their structural and functional organization as well as their ability to produce compounds other than typical secondary metabolites. Multifunctional Type I PKSs catalyze the biosynthesis of polyketide products by either using the same active sites repetitively (iterative) or by using these catalytic domains only once (modular) during the entire biosynthetic process. The largest open reading frame in Mycobacterium tuberculosis, pks12, was recently proposed to be involved in the biosynthesis of mannosyl-beta-1-phosphomycoketide (MPM). The PKS12 protein contains two complete sets of modules and has been suggested to synthesize mycoketide by five alternating condensations of methylmalonyl and malonyl units by using an iterative mode of catalysis. The bimodular iterative catalysis would require transfer of intermediate chains from acyl carrier protein domain of module 2 to ketosynthase domain of module 1. Such bimodular iterations during PKS biosynthesis have not been characterized and appear unlikely based on recent understanding of the three-dimensional organization of these proteins. Moreover, all known examples of iterative PKSs so far characterized involve unimodular iterations. Based on cell-free reconstitution of PKS12 enzymatic machinery, in this study, we provide the first evidence for a novel "modularly iterative" mechanism of biosynthesis. By combination of biochemical, computational, mutagenic, analytical ultracentrifugation and atomic force microscopy studies, we propose that PKS12 protein is organized as a large supramolecular assembly mediated through specific interactions between the C- and N-terminus linkers. PKS12 protein thus forms a modular assembly to perform repetitive condensations analogous to iterative proteins. This novel intermolecular iterative biosynthetic mechanism provides new perspective to our understanding of polyketide biosynthetic machinery and also suggests new ways to engineer polyketide metabolites. The characterization of novel molecular mechanisms involved in biosynthesis of mycobacterial virulent lipids has opened new avenues for drug discovery