Author: Douglas Sweeney
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Streptomyces bacteria have a remarkable capacity to biosynthesize natural products. The discovery of streptothricin in 1942 led to a wave of Streptomyces pharmaceutical research. Though reisolation and declining structural novelty eventually led to an industrial exit, decreases in the cost of genomic sequencing have reinvigorated microbial natural products. The expansion of genetic data has shown that bacteria have a genetic biosynthetic capacity larger than has been reported chemically. Biosynthetic genes often form Biosynthetic Gene Clusters (BGCs) within bacterial genomes allowing bioinformatic-based biosynthetic predictions. Despite this, efforts to classify identified BGCs have shown that most relate to unknown chemistry. However, recent advances in bio- and chem-informatics tools have given the ability to collect and analyze large datasets of complex genomic and metabolomic data to elucidate this biochemical "Dark Matter". Bioinformatics tools have simplified the identification and classification of BGCs. Similar advances in cheminformatic analyses such as molecular networking and open-source software have simplified the analysis of metabolomics datasets. Though connecting these disparate datasets can be difficult, pattern-based genome mining allows the classification of BGCs by comparing presence, absence patterns between BGCs and metabolites. This dissertation consists of six chapters for which the goal was to explore the biosynthetic capacity of marine actinomycetes using novel tools and methodologies. Chapter 2 is a meta-analysis of existing publications and public genetic data relating to the predominantly marine clade of Streptomyces, MAR4, with an emphasis on natural products from this clade. For chapter 3, 42 new MAR4 genomes were generated with paired metabolomics data. The diversity of MAR4 vanadium haloperoxidase and prenyltransferase genes was explored using bio- and chem-informatics tools with an emphasis on their role in biosynthesis. Chapter 4 describes the discovery of a novel bioactive metabolite from the MAR4 clade, indanopyrrole. In this work the indanopyrrole BGC is described and its distribution amongst known bacteria explored. Chapter 5 is a metabolomic survey of marine sediment actinomycetes and their response to hypoxia. In this work it is shown that Streptomyces Strain CNB-091 reduces extracellular iron using a small molecule electron shuttle. Chapter 6 is a conclusion chapter and explores the impact of this dissertation.
Author: Deepa Deepta Acharya
Publisher:
ISBN:
Category :
Languages : en
Pages : 156
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Book Description
The 'omics' era of the past decade resulted in a paradigm shift in the field of natural products. Recent genomics studies of different Actinobacteria, a class of prolific producers of therapeutic natural products, showed that they contain numerous 'cryptic' or 'silent' biosynthetic gene clusters (BGCs) that remain inactive under standard laboratory growth conditions. Therefore, triggering these silent BGCs could be the key to further exploit this untapped bacterial natural resource. Co-culture has proven to be a remarkable tactic to elicit the production of novel secondary metabolites in various Actinobacteria. Research in our laboratory found that a Rhodococcus sp. induces a Micromonospora sp. to produce an antibiotic, keyicin when co-cultured together. In this dissertation, the mechanism of interspecies interaction in bacteria was studied to understand how bacteria regulate their BGC activation. Differences in the transcription and translation of keyicin producing Micromonospora sp. in monoculture and co-culture were evaluated to determine the regulatory bottleneck for the corresponding BGC, kyc. Increase in transcription was found not only for kyc but also several other BGCs within the organism. Moreover, small molecule signaling was found to be key for keyicin production. Quorum sensing regulators like exogenously added acyl homoserine lactones and diketopiperizines isolated from the inducing Rhodococcus sp., led to keyicin production. Additional co-culture combinations were found to produce secondary metabolites that neither participating species produced in monoculture, using LCMS based metabolomics. The isolation and structure elucidation of these co-culture specific compounds were reported. Biosynthetic analyses also helped determine the producing organism in these cases. The amalgamation of several omics techniques was powerful in tracking the process of biosynthesis of keyicin from the genome to the metabolite. These interdisciplinary approaches can be utilized to systematically study interspecies interaction, which will equip us with the knowledge to activate other similarly regulated BGCs.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 13
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Book Description
Background: Considerable advances have been made in our understanding of the molecular genetics of secondary metabolite biosynthesis. Coupled with increased access to genome sequence data, new insight can be gained into the diversity and distributions of secondary metabolite biosynthetic gene clusters and the evolutionary processes that generate them. Here we examine the distribution of gene clusters predicted to encode the biosynthesis of a structurally diverse class of molecules called hybrid isoprenoids (HIs) in the genus Streptomyces. These compounds are derived from a mixed biosynthetic origin that is characterized by the incorporation of a terpene moiety onto a variety of chemical scaffolds and include many potent antibiotic and cytotoxic agents. Results: One hundred and twenty Streptomyces genomes were searched for HI biosynthetic gene clusters using ABBA prenyltransferases (PTases) as queries. These enzymes are responsible for a key step in HI biosynthesis. The strains included 12 that belong to the 'MAR4' clade, a largely marine-derived lineage linked to the production of diverse HI secondary metabolites. We found ABBA PTase homologs in all of the MAR4 genomes, which averaged five copies per strain, compared with 21 % of the non-MAR4 genomes, which averaged one copy per strain. Phylogenetic analyses suggest that MAR4 PTase diversity has arisen by a combination of horizontal gene transfer and gene duplication. Furthermore, there is evidence that HI gene cluster diversity is generated by the horizontal exchange of orthologous PTases among clusters. Many putative HI gene clusters have not been linked to their secondary metabolic products, suggesting that MAR4 strains will yield additional new compounds in this structure class. Finally, we confirm that the mevalonate pathway is not always present in genomes that contain HI gene clusters and thus is not a reliable query for identifying strains with the potential to produce HI secondary metabolites. In conclusion: We found that marine-derived MAR4 streptomycetes possess a relatively high genetic potential for HI biosynthesis. The combination of horizontal gene transfer, duplication, and rearrangement indicate that complex evolutionary processes account for the high level of HI gene cluster diversity in these bacteria, the products of which may provide a yet to be defined adaptation to the marine environment.
Author: Paul Zierep
Publisher:
ISBN:
Category : Biosynthesis
Languages : en
Pages :
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Book Description
Abstract: Natural products represent a valuable source for novel drugs and therapeutics. Rapid pro- gresses in computer technology, allow for the generation of knowledge about natural product biosynthesis and activity by investigation of large biological datasets. In this thesis bioinfor- matic know-how and machine learning algorithms were applied to develop methods for the prediction of secondary metabolite scaffolds based on their encoding biosynthetic gene clus- ter. Furthermore, the potential to predict the B cell and T cell epitope activity of non-peptidic molecules was explored. In order to connect biosynthetic gene clusters with their produced secondary metabolites the Secondary Metabolite Prediction and Identification pipeline (SeMPI) was developed. SeMPI v1 could predict polyketides (PK) of type I modular. The predicted scaffolds were screened in the StreptomeDB v2 in order to identify similar known secondary metabolites. Therefore, a novel algorithm was designed which allowed for the extraction of the putative initially biosynthesized carbon-chain of a secondary metabolite. In a benchmark based on the ranking power of annotated natural products, SeMPI v1 could outperform state-of-the-art biosynthetic gene cluster scaffold prediction software. The update SeMPI v2 was extended by nonribosomal peptide (NRP) and PK-NRP hy- brid predictions. The bottleneck in NRP scaffold generation is given by the prediction of the correct adenylation (A) domain substrate. To increase the prediction performance, a large selection of annotated A domains with known substrates was collected. The database scope was increased by 7 publicly available natural compound related libraries, which allows for the screening of almost 190,000 compounds. Additionally, SeMPI v2 includes the predic- tion of post-synthetic modifications, which were added to the screening process. Furthermore, the database screening was optimized using a benchmark, based on 559 biosynthetic gene clusters with annotated secondary metabolites. The same benchmark was applied to compare SeMPI v2 to the secondary metabolite scaffold prediction server antiSMASH v5. SeMPI v2 performed similar or better in all compared categories. SeMPI v2 provides a so- phisticated web server, including a genome browser, a molecular workbench and a prepro- cessed database. The genome browser allows for the observation of biosynthetic domains, modules and clusters in a visual overview. The molecular workbench enables the modifi- cation of predicted scaffolds before submission to the database screening. The molecular workbench can also be used to submit scaffolds to the screening without prior processing of a biosynthetic gene cluster. The preprocessed database includes biosynthetic gene clusters from the Minimum Information about a Biosynthetic Gene Cluster (MIBiG) database as well as a selection of streptomyces genomes. In order to identify novel A domain specificities based on the production of so far un- characterized A domains a cooperation project with the group of Prof. Dr. Helge Bode at the university of Frankfurt was initiated. Bode et al. developed a novel NRP production system, with the potential to rapidly identify the substrate specificities of A domains for the genera photorhabdus and xenorhabdus. In order to use this system to identify so far un- characterized A domain specificities, the available space of photorhabdus and xenorhabdus A domains was collected. The sequences were phylogenetically investigated and promising domains, with a high potential to encode for novel specificities, were selected. The results of the production experiments are pending. Different functionalities of protein subfamilies, such as the substrate specificity of A and acyltransferase (AT) domains, are associated with subfamily specific residues (SSRs). In order to allow researches a thorough analysis of protein subfamilies the Subfamily Spe- cific Residue vizualization toolbox (SSR-viz) was developed. SSR-viz uses a novel algo- rithm, which allows for the detection of SSRs based on different detection strategies. The performance of the tool was benchmarked using a dataset of 20 protein subfamilies with experimental validated SSRs. SSR-viz performed comparable to state-of-the-art software and could outperform all other tools in 4 cases. The graphical user interface of SSR-viz combines various features for the detection and visualization of SSRs. The expertise in cheminformatics and machine learning collected during the work on the aforementioned projects could be applied in a methodically related cooperation project con- ducted in the work group of Prof. Dr. Björn Peters at the La Jolla Institute of Immunology (LJI) in California. The adaptive immune system relies on the identification of pathogens based on the recognition of epitopes by T cell receptors, B cell receptors and antibodies. Apart from peptidic epitopes, various non-peptidic epitopes have been described. In order to analyze the potential of non-peptidic molecules to induce an immune response, a tool was developed which allows for the prediction of non-peptidic epitopes. The built machine learning models were thoroughly benchmarked and the prediction logic was investigated in an immunological context
Author: Trevor C. Charles
Publisher: Springer
ISBN: 3319615106
Category : Science
Languages : en
Pages : 256
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Book Description
In this book, the latest tools available for functional metagenomics research are described.This research enables scientists to directly access the genomes from diverse microbial genomes at one time and study these “metagenomes”. Using the modern tools of genome sequencing and cloning, researchers have now been able to harness this astounding metagenomic diversity to understand and exploit the diverse functions of microorganisms. Leading scientists from around the world demonstrate how these approaches have been applied in many different settings, including aquatic and terrestrial habitats, microbiomes, and many more environments. This is a highly informative and carefully presented book, providing microbiologists with a summary of the latest functional metagenomics literature on all specific habitats.
Author: American Chemical Society. Meeting
Publisher:
ISBN:
Category : Medical
Languages : en
Pages : 304
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Book Description
This book provides an overview of new discoveries in the field of polyketide research. It will benefit scientists and other sectors interested in the chemistry, molecular biology, and biotechnological aspects of this area of investigation.
Author: Yanyan Li
Publisher: Springer
ISBN: 1493910108
Category : Medical
Languages : en
Pages : 113
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Book Description
Lasso peptides form a growing family of fascinating ribosomally-synthesized and post-translationally modified peptides produced by bacteria. They contain 15 to 24 residues and share a unique interlocked topology that involves an N-terminal 7 to 9-residue macrolactam ring where the C-terminal tail is threaded and irreversibly trapped. The ring results from the condensation of the N-terminal amino group with a side-chain carboxylate of a glutamate at position 8 or 9, or an aspartate at position 7, 8 or 9. The trapping of the tail involves bulky amino acids located in the tail below and above the ring and/or disulfide bridges connecting the ring and the tail. Lasso peptides are subdivided into three subtypes depending on the absence (class II) or presence of one (class III) or two (class I) disulfide bridges. The lasso topology results in highly compact structures that give to lasso peptides an extraordinary stability towards both protease degradation and denaturing conditions. Lasso peptides are generally receptor antagonists, enzyme inhibitors and/or antibacterial or antiviral (anti-HIV) agents. The lasso scaffold and the associated biological activities shown by lasso peptides on different key targets make them promising molecules with high therapeutic potential. Their application in drug design has been exemplified by the development of an integrin antagonist based on a lasso peptide scaffold. The biosynthesis machinery of lasso peptides is therefore of high biotechnological interest, especially since such highly compact and stable structures have to date revealed inaccessible by peptide synthesis. Lasso peptides are produced from a linear precursor LasA, which undergoes a maturation process involving several steps, in particular cleavage of the leader peptide and cyclization. The post-translational modifications are ensured by a dedicated enzymatic machinery, which is composed of an ATP-dependent cysteine protease (LasB) and a lactam synthetase (LasC) that form an enzymatic complex called lasso synthetase. Microcin J25, produced by Escherichia coli AY25, is the archetype of lasso peptides and the most extensively studied. To date only around forty lasso peptides have been isolated, but genome mining approaches have revealed that they are widely distributed among Proteobacteria and Actinobacteria, particularly in Streptomyces, making available a rich resource of novel lasso peptides and enzyme machineries towards lasso topologies.
Author: Debmalya Barh
Publisher: Academic Press
ISBN: 0128047496
Category : Technology & Engineering
Languages : en
Pages : 645
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Book Description
Omics Technologies and Bio-Engineering: Towards Improving Quality of Life, Volume 1 is a unique reference that brings together multiple perspectives on omics research, providing in-depth analysis and insights from an international team of authors. The book delivers pivotal information that will inform and improve medical and biological research by helping readers gain more direct access to analytic data, an increased understanding on data evaluation, and a comprehensive picture on how to use omics data in molecular biology, biotechnology and human health care. - Covers various aspects of biotechnology and bio-engineering using omics technologies - Focuses on the latest developments in the field, including biofuel technologies - Provides key insights into omics approaches in personalized and precision medicine - Provides a complete picture on how one can utilize omics data in molecular biology, biotechnology and human health care
Author: Christopher T. Walsh
Publisher: Royal Society of Chemistry
ISBN: 1788010760
Category : Science
Languages : en
Pages : 787
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Book Description
This textbook describes the types of natural products, the biosynthetic pathways that enable the production of these molecules, and an update on the discovery of novel products in the post-genomic era.
Author: Michael Hamacher
Publisher: Humana Press
ISBN: 9781493958030
Category : Science
Languages : en
Pages : 461
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Book Description
Through the rapid development of proteomics methods and technologies, an enormous amount of data was created, leading to a wide-spread rethinking of strategy design and data interpretation. In Data Mining in Proteomics: From Standards to Applications, experts in the field present these new insights within the proteomics community, taking the historical evolution as well as the most important international standardization projects into account. Along with basic and sophisticated overviews of proteomics technologies, standard data formats, and databases, the volume features chapters on data interpretation strategies including statistics, spectra interpretation, and analysis environments as well as specialized tasks such as data annotation, peak picking, phosphoproteomics, spectrum libraries, LC/MS imaging, and splice isoforms. As a part of the highly successful Methods in Molecular BiologyTM series, this work provides the kind of detailed description and implementation advice that is crucial for getting optimal results. Authoritative and cutting-edge, Data Mining in Proteomics: From Standards to Applications is a well-balanced compendium for beginners and experts, offering a broad scope of data mining topics but always focusing on the current state-of-the-art and beyond.
