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      Convergent evolution of [ D-Leucine 1] microcystin-LR in taxonomically disparate cyanobacteria

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          Abstract

          Background

          Many important toxins and antibiotics are produced by non-ribosomal biosynthetic pathways. Microcystins are a chemically diverse family of potent peptide toxins and the end-products of a hybrid NRPS and PKS secondary metabolic pathway. They are produced by a variety of cyanobacteria and are responsible for the poisoning of humans as well as the deaths of wild and domestic animals around the world. The chemical diversity of the microcystin family is attributed to a number of genetic events that have resulted in the diversification of the pathway for microcystin assembly.

          Results

          Here, we show that independent evolutionary events affecting the substrate specificity of the microcystin biosynthetic pathway have resulted in convergence on a rare [ D-Leu 1] microcystin-LR chemical variant. We detected this rare microcystin variant from strains of the distantly related genera Microcystis, Nostoc, and Phormidium. Phylogenetic analysis performed using sequences of the catalytic domains within the mcy gene cluster demonstrated a clear recombination pattern in the adenylation domain phylogenetic tree. We found evidence for conversion of the gene encoding the McyA 2 adenylation domain in strains of the genera Nostoc and Phormidium. However, point mutations affecting the substrate-binding sequence motifs of the McyA 2 adenylation domain were associated with the change in substrate specificity in two strains of Microcystis. In addition to the main [ D-Leu 1] microcystin-LR variant, these two strains produced a new microcystin that was identified as [Met 1] microcystin-LR.

          Conclusions

          Phylogenetic analysis demonstrated that both point mutations and gene conversion result in functional mcy gene clusters that produce the same rare [ D-Leu 1] variant of microcystin in strains of the genera Microcystis, Nostoc, and Phormidium. Engineering pathways to produce recombinant non-ribosomal peptides could provide new natural products or increase the activity of known compounds. Our results suggest that the replacement of entire adenylation domains could be a more successful strategy to obtain higher specificity in the modification of the non-ribosomal peptides than point mutations.

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          Most cited references50

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          A modified bootscan algorithm for automated identification of recombinant sequences and recombination breakpoints.

          We have developed a modified BOOTSCAN algorithm that may be used to screen nucleotide sequence alignments for evidence of recombination without prior identification of nonrecombinant reference sequences. The algorithm is fast and includes a Bonferroni corrected statistical test of recombination to circumvent the multiple testing problems encountered when using the BOOTSCAN method to explore alignments for evidence of recombination. Using both simulated and real datasets we demonstrate that the modified algorithm is more powerful than other phylogenetic recombination detection methods and performs almost as well as one of the best substitution distribution recombination detection methods.
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            An exact nonparametric method for inferring mosaic structure in sequence triplets.

            Statistical tests for detecting mosaic structure or recombination among nucleotide sequences usually rely on identifying a pattern or a signal that would be unlikely to appear under clonal reproduction. Dozens of such tests have been described, but many are hampered by long running times, confounding of selection and recombination, and/or inability to isolate the mosaic-producing event. We introduce a test that is exact, nonparametric, rapidly computable, free of the infinite-sites assumption, able to distinguish between recombination and variation in mutation/fixation rates, and able to identify the breakpoints and sequences involved in the mosaic-producing event. Our test considers three sequences at a time: two parent sequences that may have recombined, with one or two breakpoints, to form the third sequence (the child sequence). Excess similarity of the child sequence to a candidate recombinant of the parents is a sign of recombination; we take the maximum value of this excess similarity as our test statistic Delta(m,n,b). We present a method for rapidly calculating the distribution of Delta(m,n,b) and demonstrate that it has comparable power to and a much improved running time over previous methods, especially in detecting recombination in large data sets.
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              NRPSpredictor2—a web server for predicting NRPS adenylation domain specificity

              The products of many bacterial non-ribosomal peptide synthetases (NRPS) are highly important secondary metabolites, including vancomycin and other antibiotics. The ability to predict substrate specificity of newly detected NRPS Adenylation (A-) domains by genome sequencing efforts is of great importance to identify and annotate new gene clusters that produce secondary metabolites. Prediction of A-domain specificity based on the sequence alone can be achieved through sequence signatures or, more accurately, through machine learning methods. We present an improved predictor, based on previous work (NRPSpredictor), that predicts A-domain specificity using Support Vector Machines on four hierarchical levels, ranging from gross physicochemical properties of an A-domain’s substrates down to single amino acid substrates. The three more general levels are predicted with an F-measure better than 0.89 and the most detailed level with an average F-measure of 0.80. We also modeled the applicability domain of our predictor to estimate for new A-domains whether they lie in the applicability domain. Finally, since there are also NRPS that play an important role in natural products chemistry of fungi, such as peptaibols and cephalosporins, we added a predictor for fungal A-domains, which predicts gross physicochemical properties with an F-measure of 0.84. The service is available at http://nrps.informatik.uni-tuebingen.de/.
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                Author and article information

                Journal
                BMC Evol Biol
                BMC Evol. Biol
                BMC Evolutionary Biology
                BioMed Central
                1471-2148
                2013
                19 April 2013
                : 13
                : 86
                Affiliations
                [1 ]Department of Food and Environmental Sciences, Division of Microbiology and Biotechnology, University of Helsinki, Viikki Biocenter (Viikinkaari 9), P.O. Box 56, Helsinki, FIN-00014, Finland
                [2 ]Department of Biosciences, University of Helsinki, Viikki Biocenter (Viikinkaari 1), P.O. Box 65, Helsinki, FIN-00014, Finland
                [3 ]Center for Nuclear Energy in Agriculture, University of São Paulo, Avenida Centenário 303, Piracicaba, SP, 13400-970, Brazil
                [4 ]Unidade de Pesquisas em Cianobactérias, Federal University of Rio Grande, Av. Itália km 8 - Caixa Postal 474, Rio Grande, RS, 96.201-900, Brazil
                Article
                1471-2148-13-86
                10.1186/1471-2148-13-86
                3640908
                23601305
                9f7f7376-c172-4443-b391-d5d178b56491
                Copyright ©2013 Shishido et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 12 November 2012
                : 9 April 2013
                Categories
                Research Article

                Evolutionary Biology
                adenylation domain,phylogeny,substrate specificity,gene conversion,point mutations,recombination

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