Literature DB >> 34818109

Genotyping and Multivariate Regression Trees Reveal Ecological Diversification within the Microcystis aeruginosa Complex along a Wide Environmental Gradient.

Gabriela Martínez de la Escalera1, Angel M Segura2, Carla Kruk2,3, Badih Ghattas4, Frederick M Cohan5, Andrés Iriarte6, Claudia Piccini1.   

Abstract

Addressing the ecological and evolutionary processes underlying biodiversity patterns is essential to identify the mechanisms shaping community structure and function. In bacteria, the formation of new ecologically distinct populations (ecotypes) is proposed as one of the main drivers of diversification. New ecotypes arise when mutations in key functional genes or acquisition of new metabolic pathways by horizontal gene transfer allow the population to exploit new resources, permitting their coexistence with the parental population. We previously reported the presence of microcystin-producing organisms of the Microcystis aeruginosa complex (toxic MAC) through an 800-km environmental gradient ranging from freshwater to estuarine-marine waters in South America. We hypothesize that the success of toxic MAC in such a gradient is due to the existence of very closely related populations that are ecologically distinct (ecotypes), each specialized to a specific arrangement of environmental variables. Here, we analyzed toxic MAC genetic diversity through quantitative PCR (qPCR) and high-resolution melting analysis (HRMA) of a functional gene (mcyJ, microcystin synthetase cluster). We explored the variability of the mcyJ gene along the environmental gradient by multivariate classification and regression trees (mCART). Six groups of mcyJ genotypes were distinguished and associated with different combinations of water temperature, conductivity, and turbidity. We propose that each mcyJ variant associated with a defined environmental condition is an ecotype (or species) whose relative abundances vary according to their fitness in the local environment. This mechanism would explain the success of toxic MAC in such a wide array of environmental conditions. IMPORTANCE Organisms of the Microcystis aeruginosa complex form harmful algal blooms (HABs) in nutrient-rich water bodies worldwide. MAC HABs are difficult to manage owing to the production of potent toxins (microcystins) that resist water treatment. In addition, the role of microcystins in the ecology of MAC organisms is still elusive, meaning that the environmental conditions driving the toxicity of the bloom are not clear. Furthermore, the lack of coherence between morphology-based and genomic-based species classification makes it difficult to draw sound conclusions about when and where each member species of the MAC will dominate the bloom. Here, we propose that the diversification process and success of toxic MAC in a wide range of water bodies involves the generation of ecotypes, each specialized in a particular niche, whose relative abundance varies according to its fitness in the local environment. This knowledge can improve the generation of accurate prediction models of MAC growth and toxicity, helping to prevent human and animal intoxication.

Entities:  

Keywords:  HRMA; Microcystis aeruginosa complex; ecotypes; mcyJ; multivariate CART

Mesh:

Substances:

Year:  2021        PMID: 34818109      PMCID: PMC8824264          DOI: 10.1128/AEM.01475-21

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   5.005


  70 in total

1.  Natural variation in the microcystin synthetase operon mcyABC and impact on microcystin production in Microcystis strains.

Authors:  Bjørg Mikalsen; Gudrun Boison; Olav M Skulberg; Jutta Fastner; William Davies; Tove M Gabrielsen; Knut Rudi; Kjetill S Jakobsen
Journal:  J Bacteriol       Date:  2003-05       Impact factor: 3.490

2.  Microcystis genotype succession and related environmental factors in Lake Taihu during cyanobacterial blooms.

Authors:  Xingyu Wang; Mengjia Sun; Jinmei Wang; Letian Yang; Lan Luo; Pengfu Li; Fanxiang Kong
Journal:  Microb Ecol       Date:  2012-07-04       Impact factor: 4.552

3.  Different versions of the Dayhoff rate matrix.

Authors:  Carolin Kosiol; Nick Goldman
Journal:  Mol Biol Evol       Date:  2004-10-13       Impact factor: 16.240

4.  Towards a conceptual and operational union of bacterial systematics, ecology, and evolution.

Authors:  Frederick M Cohan
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2006-11-29       Impact factor: 6.237

5.  High-resolution melt analysis for rapid comparison of bacterial community compositions.

Authors:  Mathis Hjort Hjelmsø; Lars Hestbjerg Hansen; Jacob Baelum; Louise Feld; William E Holben; Carsten Suhr Jacobsen
Journal:  Appl Environ Microbiol       Date:  2014-06       Impact factor: 4.792

6.  Application of ancient DNA to the reconstruction of past microbial assemblages and for the detection of toxic cyanobacteria in subtropical freshwater ecosystems.

Authors:  Gabriela Martínez de la Escalera; Dermot Antoniades; Sylvia Bonilla; Claudia Piccini
Journal:  Mol Ecol       Date:  2014-11-21       Impact factor: 6.185

7.  Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: approximate methods.

Authors:  Z Yang
Journal:  J Mol Evol       Date:  1994-09       Impact factor: 2.395

8.  The role of microcystins in maintaining colonies of bloom-forming Microcystis spp.

Authors:  Nanqin Gan; Yan Xiao; Lin Zhu; Zhongxing Wu; Jin Liu; Chenlin Hu; Lirong Song
Journal:  Environ Microbiol       Date:  2011-10-31       Impact factor: 5.491

9.  Rapid freshwater discharge on the coastal ocean as a mean of long distance spreading of an unprecedented toxic cyanobacteria bloom.

Authors:  Carla Kruk; Ana Martínez; Gabriela Martínez de la Escalera; Romina Trinchin; Gastón Manta; Angel M Segura; Claudia Piccini; Beatriz Brena; Beatriz Yannicelli; Graciela Fabiano; Danilo Calliari
Journal:  Sci Total Environ       Date:  2020-09-16       Impact factor: 7.963

10.  High-resolution melting analysis of cDNA-derived PCR amplicons for rapid and cost-effective identification of novel alleles in barley.

Authors:  Bernhard J Hofinger; Hai-Chun Jing; Kim E Hammond-Kosack; Kostya Kanyuka
Journal:  Theor Appl Genet       Date:  2009-07-04       Impact factor: 5.699

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