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Sbaraini N, Bellini R, Penteriche AB, Guedes RLM, Garcia AWA, Gerber AL, Vainstein MH, de Vasconcelos ATR, Schrank A, Staats CC. Genome-wide DNA methylation analysis of Metarhizium anisopliae during tick mimicked infection condition. BMC Genomics 2019; 20:836. [PMID: 31711419 PMCID: PMC6849299 DOI: 10.1186/s12864-019-6220-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Accepted: 10/24/2019] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND The Metarhizium genus harbors important entomopathogenic fungi. These species have been widely explored as biological control agents, and strategies to improve the fungal virulence are under investigation. Thus, the interaction between Metarhizium species and susceptible hosts have been explored employing different methods in order to characterize putative virulence determinants. However, the impact of epigenetic modulation on the infection cycle of Metarhizium is still an open topic. Among the different epigenetic modifications, DNA methylation of cytosine bases is an important mechanism to control gene expression in several organisms. To better understand if DNA methylation can govern Metarhizium-host interactions, the genome-wide DNA methylation profile of Metarhizium anisopliae was explored in two conditions: tick mimicked infection and a saprophytic-like control. RESULTS Using a genome wide DNA methylation profile based on bisulfite sequencing (BS-Seq), approximately 0.60% of the total cytosines were methylated in saprophytic-like condition, which was lower than the DNA methylation level (0.89%) in tick mimicked infection condition. A total of 670 mRNA genes were found to be putatively methylated, with 390 mRNA genes uniquely methylated in the tick mimicked infection condition. GO terms linked to response to stimuli, cell wall morphogenesis, cytoskeleton morphogenesis and secondary metabolism biosynthesis were over-represented in the tick mimicked infection condition, suggesting that energy metabolism is directed towards the regulation of genes associated with infection. However, recognized virulence determinants known to be expressed at distinct infection steps, such as the destruxin backbone gene and the collagen-like protein gene Mcl1, were found methylated, suggesting that a dynamic pattern of methylation could be found during the infectious process. These results were further endorsed employing RT-qPCR from cultures treated or not with the DNA methyltransferase inhibitor 5-Azacytidine. CONCLUSIONS The set of genes here analyzed focused on secondary metabolites associated genes, known to be involved in several processes, including virulence. The BS-Seq pipeline and RT-qPCR analysis employing 5-Azacytidine led to identification of methylated virulence genes in M. anisopliae. The results provided evidences that DNA methylation in M. anisopliae comprises another layer of gene expression regulation, suggesting a main role of DNA methylation regulating putative virulence determinants during M. anisopliae infection cycle.
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Affiliation(s)
- Nicolau Sbaraini
- Centro de Biotecnologia, UFRGS, Porto Alegre, RS, Brazil.,Rede Avançada em Biologia Computacional, RABICÓ, Petrópolis, RJ, Brazil
| | - Reinaldo Bellini
- Laboratório Nacional de Computação Científica, LNCC, Petrópolis, RJ, Brazil.,Rede Avançada em Biologia Computacional, RABICÓ, Petrópolis, RJ, Brazil
| | | | - Rafael Lucas Muniz Guedes
- Laboratório Nacional de Computação Científica, LNCC, Petrópolis, RJ, Brazil.,Rede Avançada em Biologia Computacional, RABICÓ, Petrópolis, RJ, Brazil
| | | | | | - Marilene Henning Vainstein
- Centro de Biotecnologia, UFRGS, Porto Alegre, RS, Brazil.,Rede Avançada em Biologia Computacional, RABICÓ, Petrópolis, RJ, Brazil
| | - Ana Tereza Ribeiro de Vasconcelos
- Laboratório Nacional de Computação Científica, LNCC, Petrópolis, RJ, Brazil.,Rede Avançada em Biologia Computacional, RABICÓ, Petrópolis, RJ, Brazil
| | - Augusto Schrank
- Centro de Biotecnologia, UFRGS, Porto Alegre, RS, Brazil.,Rede Avançada em Biologia Computacional, RABICÓ, Petrópolis, RJ, Brazil
| | - Charley Christian Staats
- Centro de Biotecnologia, UFRGS, Porto Alegre, RS, Brazil. .,Rede Avançada em Biologia Computacional, RABICÓ, Petrópolis, RJ, Brazil.
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