Elicitation of natural products biosynthesis from endophytic microorganisms´ interactions

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(1)UNIVERSITY OF SÃO PAULO SCHOOL OF PHARMACEUTICAL SCIENCES OF RIBEIRÃO PRETO. Elicitation of natural products biosynthesis from endophytic microorganisms´ interactions. Andrés Mauricio Caraballo Rodríguez. Ribeirão Preto 2016.

(2) UNIVERSITY OF SÃO PAULO SCHOOL OF PHARMACEUTICAL SCIENCES OF RIBEIRÃO PRETO. Elicitation of natural products biosynthesis from endophytic microorganisms´ interactions. Tese de Doutorado apresentada ao Programa de Pós-Graduação em Ciências Farmacêuticas para obtenção do Título de Doutor em Ciências Área de Concentração: Produtos Naturais e Sintêticos Dissertation submitted to the Pharmaceutical Sciences Graduate Program in partial fulfillment of the requirements for the degree of Doctor in Philosophy.. Field of Study: Natural and synthetic products PhD candidate: Andrés Mauricio Caraballo Rodríguez Advisor: Mônica Tallarico Pupo, PhD.. Corrected version of the doctoral dissertation submitted to the Pharmaceutical Sciences Graduate Program 10/02/2017. The original version is available at the School of Pharmaceutical Sciences of Ribeirão Preto/USP. Ribeirão Preto 2016.

(3) TOTAL OR PARTIAL REPRODUCTION AND DISSEMINATION OF THIS WORK FOR STUDY OR RESEARCH PURPOSES, BY CONVENTIONAL OR DIGITAL SOURCES IS AUTHORIZED, SINCE THIS WORK IS PROPERLY REFERENCED.. Caraballo-Rodríguez, Andrés Mauricio. Elicitation of natural products biosynthesis from endophytic microorganisms´ interactions. Ribeirão Preto, 2016. 169 p.: il. ; 30 cm. Dissertation submitted to School of Pharmaceutical Sciences of Ribeirão Preto / USP – Field of Study: Natural and synthetic products. Advisor: Pupo, Mônica T. 1- Endophytes. 2 - Microbial interactions. 3 - Natural products. 4. Molecular networking. 5. Elicitation. 6. Amphotericin B..

(4) DISSERTATION APPROVAL SHEET Andrés Mauricio Caraballo Rodríguez Elicitation of natural products biosynthesis from endophytic microorganisms´ interactions. Dissertation submitted to the Pharmaceutical Sciences Graduate Program in partial fulfillment of the requirements for the degree of Doctor in Philosophy. Field of Study: Natural and synthetic products Advisor: Mônica Tallarico Pupo, PhD.. Date Approved: 10/02/2017. Committee Prof. Dr. ____________________________________________________________ Institution: _____________________________ Signature:____________________. Prof. Dr. ____________________________________________________________ Institution: _____________________________ Signature:____________________. Prof. Dr. ____________________________________________________________ Institution: _____________________________ Signature:____________________. Prof. Dr. ____________________________________________________________ Institution: _____________________________ Signature:____________________. Prof. Dr. ____________________________________________________________ Institution: _____________________________ Signature:____________________.

(5) In dedication to my beloved wife, Tatiana, who has been a fundamental support during my life, not just as a scientist; to my parents, Aurora and Alfonso, who have been my main inspiration of love, dedication and perseverance to reach a desired goal; to my brother, Hugo, my sister in law, Karen and my dear nephews, Sammuel and Diego, who have been a beautiful example of love and how to pursue a dream; to my darling sister, Angélica, because she knows it is worthy to do what you really want to do; to my father and mother in law, Guillermo and Nora, my sisters in law, Johana and Susana and my nephew, Miguel David, who have been a lovely support for me and my wife..

(6) ACKNOWLEDGMENTS. I would like to thank everybody, who directly or indirectly have influenced the building of my career as a scientist. Special thanks to my mentors, Prof. Mônica Tallarico Pupo (LQMo) and Prof. Pieter Dorrestein (Dorrestein lab) who encouraged me to do my best and look beyond, for giving me freedom for doing science. You have been fundamental and inspirational figures during my scientific career. To my dear labmates at the LQMo: Fernanda, Claudia, Cássia, Carla, Rita, Eduardo, Camila, Humberto, Weilan, Taíse, Bárbara, Andressa, Henrique, Camila F., Isabela, Ulysses, Larissa, Marília, Denise, Raphael, Adriana, Gisele, thank you all for the great time we spent at the lab, exchanging ideas and learning together about the chemistry of microorganisms. To Eduardo José Crevelin, Prof. Antônio Eduardo Miller, Prof. Luiz A. de Morais, Prof. Norberto Lopes, José Carlos Tomaz for their laboratory support and technical discussions. To Vinicius Palaretti for his support during NMR acquisitions. To the Dorrestein lab: Vanessa, Don, Laura S., Thomas, Amina, Neha, Mike, Dimitri, Alex, Cliff, Ming, Chen, Daniel, Rachel, Aurélie, Rianne, Jakob, Fernando, Andrew, Nobuhiro, Rob, Ricardo, Laura P., Kathleen, thank you all for our amazing time in San Diego, having fun while applying mass spec to our research. To the Faculdade de Ciências Farmacêuticas de Ribeirão Preto - Universidade de São Paulo (FCFRP - USP), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) for their support to this research. I would like to thank Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) for providing the financial support during my research in Brazil (2012/21803-1) as well as in United States (2014/01651-8) I am grateful to all of you..

(7) “Never pass up new experiences, Scarlett. They enrich the mind.” - Rhett Butler..

(8) i ABSTRACT. CARABALLO-RODRÍGUEZ, A. M. Elicitation of natural products biosynthesis from endophytic microorganisms´ interactions. 2016. 169 p. Doctoral Dissertation. School of Pharmaceutical Sciences of Ribeirão Preto - University of São Paulo, Ribeirão Preto, 2016. In order to continue with the study of natural products from previously isolated endophytes of the Brazilian medicinal plant Lychnophora ericoides, the main goal of this work focused on the metabolic exchange of endophytic microorganisms from this plant. As it has been demonstrated during the last years, elicitation of different molecules is consequence of microbial interactions, mainly due to the need to compete, survive and establish microbial communities in shared environments. Recent mass spectrometry related approaches, such as imaging and molecular networking, in combination with purification and structural elucidation were applied to the current study of the microbial interactions of endophytes. During this study, several chemical families were identified, such as polyene macrocycles, pyrroloindole alkaloids, leupeptins, angucyclines, siderophores, amongst others. Amongst the polyene macrocycles, the well-known antifungal amphotericin B was identified as a biosynthetic product of the endophytic actinobacteria Streptomyces albospinus RLe7. When S. albospinus RLe7 interacted with an endophytic fungus, Coniochaeta sp. FLe4, a red pigmentation was observed. A new fungal compound was detected from microbial interactions. Isolation and structure elucidation of this new compound enabled to demonstrate the elicitation of fungal secondary metabolites by amphotericin B, an actinobacterial metabolite. It was also demonstrated the elicitation of griseofulvin and its analogue dechlorogriseofulvin from another endophytic fungus, FLe9, as a consequence of exposition to amphotericin B. In addition, investigation of the chemical profile of another endophytic actinobacteria, S. mobaraensis RLe3, led to reveal this strain as angucycline-derivatives producer. Besides that, coculturing of this actinobacteria against Coniochaeta sp. FLe4 also demonstrated elicitation of angucycline analogues. In conclusion, this study demonstrated elicitation of natural products from microbial interactions as well as new compounds from endophytes from L. ericoides and contributed to the identification of microbial metabolites.. Keywords: Endophytes; microbial interactions; natural products; molecular networking; elicitation; amphotericin B..

(9) ii. RESUMO. CARABALLO-RODRÍGUEZ, A. M. Eliciação da biossíntese de produtos naturais a partir da interação de microorganismos endofíticos. 2016. 169 f. Tese de doutorado, Faculdade de Ciências Farmacêuticas de Ribeirão Preto - Universidade de São Paulo, Ribeirão Preto, 2016. Com o propósito de continuar com os estudos de produtos naturais de microorganismos endofíticos da planta medicinal Brasileira Lychnophora ericoides, o principal objetivo desse trabalho focou-se no estudo da troca metabólica de microorganismos endofíticos dessa planta. Como tem sido demonstrado durante os últimos anos, a elicitação de diferentes compostos é consequência das interações microbianas, principalmente devido à necessidade de competir, sobreviver e estabelecer comunidades microbianas em diversos ambientes naturais. Abordagens recentes de espectrometria de massas, tais como imageamento e molecular networking, junto com purificação e elucidação estrutural foram aplicadas durante o estudo de interações microbianas de endofíticos. Durante este estudo, várias classes químicas foram identificadas, tais como polienos macrocíclicos, alcaloides pirroloindólicos, leupeptinas, anguciclinas, sideróforos, entre outras. Da classe química de polienos macrocíclicos, foi identificada a anfotericina B como produto da biossíntese da actinobactéria endofítica Streptomyces albospinus RLe7. Durante a interação da S. albospinus RLe7 com o fungo endofítico Coniochaeta sp. FLe4, uma pigmentação vermelha foi observada. Um novo composto de origem fúngica foi detectado a partir de interações microbianas. O isolamento e posterior elucidação estrutural do novo composto permitiu demonstrar a eliciação de metabólitos secundários fúngicos pela anfotericina B, metabólito da actinobactéria S. albospinus RLe7. Foi também demonstrada a eliciação de griseofulvina e desclorogriseofulvina a partir de outro fungo endofítico, FLe9, como consequência da exposição à anfotericina B. Adicionalmente, a investigação do perfil químico de outra actinobactéria endofítica, S. mobaraensis RLe3, evidenciou essa linhagem como produtora de compostos da classe das anguciclinas. Além disso, o cocultivo dessa actinobacteria com o fungo endofítico Coniochaeta sp. FLe4 também eliciou análogos de anguciclinas. Em conclusão, neste estudo demonstrou-se a elicitação de produtos naturais a partir das interações microbianas assim como de novos compostos de endofíticos de L. ericoides e contribuiu-se com a identificação de metabólitos microbianos.. Palavras-chave: Endofíticos. Networking. Elicitação.. Interações. microbianas.. Produtos. naturais.. Molecular.

(10) iii. LIST OF FIGURES. Figure 1. Illustrative examples of natural products from endophytes. ...................................... 4 Figure 2. Illustrative examples of natural products from microbial interactions. ..................... 8 Figure 3. Illustrative examples of natural products discovered by MS approaches and molecular networking. .............................................................................................................. 12 Figure 4. Scheme for MIC assay for marangucycline A2 (compound 6) against Coniochaeta sp. FLe4. ................................................................................................................................... 23 Figure 5. Microbial interactions of endophytes from L. ericoides. ......................................... 24 Figure 6. HPLC-DAD profile of extracts from microbial interaction between S. mobaraensis RLe3 and Coniochaeta sp. FLe4 in liquid culture.................................................................... 25 Figure 7. HPLC-DAD of purified peak corresponding to compound (1)................................ 26 Figure 8. HPLC-DAD of purified peak corresponding to compound (2)................................ 27 Figure 9. HPLC-DAD of purified peak corresponding to compound (3)................................ 29 Figure 10. HPLC-DAD of purified peak corresponding to compound (4).............................. 30 Figure 11. HPLC-DAD of purified peak corresponding to compound (5).............................. 31 Figure 12. HPLC-DAD of purified peak corresponding to compound (6).............................. 33 Figure 13. HPLC-DAD of purified peak corresponding to compound (7).............................. 35 Figure 14. HPLC-DAD profile of extracts from microbial interaction between S. mobaraensis RLe3 and Coniochaeta sp. FLe4 in liquid culture.................................................................... 36 Figure 15. Comparison between MALDI-TOF IMS samples prepared and analyzed after 7 days and 4 days of culturing. .................................................................................................... 37 Figure 16. Colony-colony interaction of endophytic microorganisms from L. ericoides. ...... 38 Figure 17. MALDI-TOF IMS distribution for the ion of m/z 924 during time-course colonycolony interaction of S. albospinus RLe7 and Coniochaeta sp. FLe4. .................................... 39 Figure 18. Molecular network of microbial interactions amongst endophytic microorganisms from L. ericoides. ..................................................................................................................... 40 Figure 19. Parent ion distribution from molecular network of interactions amongst endophytic microorganisms from L. ericoides. ........................................................................ 41 Figure 20. Biosynthetic pathway of physostigmine (8). .......................................................... 43 Figure 21. MS/MS spectrum of detected physostigmine (8) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ...................................... 43 Figure 22. Physostigmine-cluster from molecular networking of interactions amongst endophytic microorganisms from L. ericoides. ........................................................................ 44.

(11) iv. Figure 23. MS/MS spectrum of detected TAN 1169A (9) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ...................................... 44 Figure 24. MS/MS spectrum of detected TAN 1169B (10) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ...................................... 45 Figure 25. Amphotericin-cluster from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ........................................................................ 46 Figure 26. Biosynthetic origin of amphotericin B (11). .......................................................... 47 Figure 27. MS/MS spectrum of detected amphotericin B (11) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ...................................... 47 Figure 28. MS/MS spectrum of detected amphotericin A (12) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ...................................... 48 Figure 29. MS/MS spectrum of putative amphotericin X or B2 (13) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ................... 48 Figure 30. MS/MS spectrum of putative deoxyamphotericin A (19) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ................... 49 Figure 31. MS/MS spectrum of putative deoxyamphotericin B (20) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ................... 49 Figure 32. Leupeptin-cluster from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ........................................................................................... 51 Figure 33. MS/MS spectrum of detected leupeptin (21) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ...................................... 51 Figure 34. MS/MS spectrum of detected leupeptin acetyl-(LVR or VLR) (22) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. .. 52 Figure 35. MS/MS spectrum of detected strepin P1 (23) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ...................................... 52 Figure 36. MS/MS spectrum of detected leupeptin Pr-LL (24) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ...................................... 53 Figure 37. Biosynthetic pathways of the typical benz[a]anthracene backbone of angucyclin/one/s. ...................................................................................................................... 54 Figure 38. MS/MS spectrum of detected aquayamycin (2) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ...................................... 55 Figure 39. Aquayamycin-cluster from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ........................................................................ 55.

(12) v. Figure 40. MS/MS spectrum of detected aquayamycin analogue m/z 713 (25) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. .. 56 Figure 41. MS/MS spectrum of detected aquayamycin analogue m/z 469 (26) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. .. 56 Figure 42. MS/MS spectrum of detected dehydroxyaquayamycin (5) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ................... 57 Figure 43. MS/MS spectrum of detected marangucycline A2 (6) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides.................................. 58 Figure 44. Urdamycinone B (2) and galtamycinone (3) cluster from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ...................................... 59 Figure 45. MS/MS spectrum of detected galtamycinone (3) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ...................................... 59 Figure 46. MS/MS spectrum of detected urdamycinone B (2) from the molecular network of interactions amongst endophytic microorganisms from L. ericoides. ...................................... 60 Figure 47. Cultures of Coniochaeta sp. FLe4 in presence of amphotericin B and S. albospinus RLe7. ........................................................................................................................................ 61 Figure 48. Cultures of Coniochaeta sp. FLe4 in presence of nystatin. ................................... 61 Figure 49. Biological assay of purified compounds against Coniochaeta sp. FLe4. .............. 62 Figure 50. Representative ions detected by MALDI-TOF IMS after 2 days culture of microbial interactions amongst endophytic actinobacteria of L. ericoides. ............................. 63 Figure 51. Molecular network of the 14-days five-colonies interactions of endophytic actinobacteria from L. ericoides. .............................................................................................. 64 Figure 52. Parent ion distribution from the molecular network of the 14-days five-colonies interactions of endophytic actinobacteria from L. ericoides. ................................................... 65 Figure 53. Leupeptin-cluster from the molecular network of the 14-days five-colonies interactions of endophytic actinobacteria from L. ericoides. ................................................... 66 Figure 54. Amphotericin-cluster from the molecular network of the 14-days five-colonies interactions of endophytic actinobacteria from L. ericoides. ................................................... 67 Figure 55. Physostigmine-cluster from the molecular network of the 14-days five-colonies interactions of endophytic actinobacteria from L. ericoides. ................................................... 68 Figure 56. Node and representative MS/MS spectrum of m/z 655, corresponding to coproporphyrin (32) from the 14-days five-colonies interactions of endophytic actinobacteria from L. ericoides. ..................................................................................................................... 69.

(13) vi. Figure 57. Siderophore-cluster from the molecular network of the 14-days five-colonies interactions of endophytic actinobacteria from L. ericoides. ................................................... 70 Figure 58. MS/MS spectrum of detected desferrioxamine B (33) from the molecular network of the 14-days five-colonies interactions of endophytic actinobacteria from L. ericoides....... 71 Figure 59. MS/MS spectrum of detected desferrioxamine E (34) from the molecular network of the 14-days five-colonies interactions of endophytic actinobacteria from L. ericoides....... 71 Figure 60. MS/MS spectrum of putative desferrioxamine m/z 518 (35) from the molecular network of the 14-days five-colonies interactions of endophytic actinobacteria from L. ericoides. .................................................................................................................................. 72 Figure 61. Angucycline-clusters from the molecular network of the 14-days five-colonies interactions of endophytic actinobacteria from L. ericoides. ................................................... 73 Figure 62. Impact of 14-days five-colonies interactions of endophytic actinobacteria from L. ericoides on colony sizes. ......................................................................................................... 74 Figure 63. MALDI-TOF IMS of S. albospinus RLe7 vs B. subtilis ATCC3610. ................... 76 Figure 64. Microbial interactions amongst endophytic actinobacteria with opportunistic pathogens B. subtilis 3610 and P. aeruginosa PAO1. .............................................................. 76 Figure 65. Molecular network of microbial interactions of endophytic microorganisms from L. ericoides with B. subtilis 3610 and P. aeruginosa PAO1. ................................................... 77 Figure 66. Parent ion distribution from molecular network of interactions endophytic microorganisms from L. ericoides with B. subtilis 3610 and P. aeruginosa PAO1. ............... 78 Figure 67. 2-Methoxyphenazine-cluster from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ................................................................. 79 Figure 68. MS/MS spectrum of detected 2-methoxyphenazine (36) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria.............. 79 Figure 69. Phenazine-1-carboxylic acid-cluster from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ................................................... 80 Figure 70. MS/MS spectrum of detected phenazine-1-carboxylic acid (37) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria.............. 80 Figure 71. Quinolones-clusters from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ................................................................. 82 Figure 72. MS/MS spectrum of detected HQNO (38) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ............................... 83 Figure 73. MS/MS spectrum of detected NHQ C9:db (39) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ............................... 83.

(14) vii. Figure 98. MS/MS spectrum of detected C8-HQNO (40) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ............................... 84 Figure 75. MS/MS spectrum of detected NQNO (41) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ............................... 84 Figure 76. MS/MS spectrum of detected UHQ (unknown double bond position) (42) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. .................................................................................................................................................. 85 Figure 77. MS/MS spectrum of detected TQNO (unknown double bond position) (43) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. .................................................................................................................................... 86 Figure 78. MS/MS spectrum of detected putative unknown quinolone (m/z 276) (44) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. .................................................................................................................................................. 86 Figure 79. MS/MS spectrum of detected NQNO C9:1 (45) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ............................... 87 Figure 80. MS/MS spectrum of detected C11-PQS (unknown double bond position) (46) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. .................................................................................................................................... 87 Figure 81. Rhamnolipids-cluster from molecular networking of interactions between endophytic actinobacteria and pathogenic bacteria. ................................................................. 88 Figure 82. MS/MS spectrum of detected Rha-C10-C12/ Rha-C12-C10 (47) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. .................................................................................................................................................. 89 Figure 83. MS/MS spectrum of detected Rha-C10-C10 (48) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ............................... 89 Figure 84. Rha-Rhamnolipids-cluster from molecular networking of interactions between endophytic actinobacteria and pathogenic bacteria. ................................................................. 90 Figure 85. MS/MS spectrum of detected Rha-Rha-C10-C10 (49) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ........................... 90 Figure 86. MS/MS spectrum of detected Rha-Rha-C10-C12 (unknown double bond position) (50) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. .................................................................................................................. 91 Figure 87. MS/MS spectrum of detected Rha-Rha-C10-C12 (51) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ........................... 92.

(15) viii. Figure 88. Phosphatidylethanolamine-cluster from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ................................................... 93 Figure 89. MS/MS spectrum of detected phosphatidylethanolamine (14:0/16:0) (52) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. .................................................................................................................................................. 93 Figure 90. MS/MS spectrum of detected phosphatidylethanolamine (15:0/16:0) (53) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. .................................................................................................................................................. 94 Figure 91. MS/MS spectrum of detected phosphatidylethanolamine (16:0) (54) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. .................................................................................................................................................. 95 Figure 92. Diglycosyldiacylglycerol-cluster from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ................................................... 96 Figure 93. MS/MS spectrum of detected diglycosyldiacylglycerol C30 (55) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. .................................................................................................................................................. 96 Figure 94. MS/MS spectrum of detected diglycosyldiacylglycerol C31 (56) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. .................................................................................................................................................. 97 Figure 95. MS/MS spectrum of detected diglycosyldiacylglycerol C32 (57) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. .................................................................................................................................................. 98 Figure 96. Surfactin-cluster from molecular networking of interactions between endophytic actinobacteria and pathogenic bacteria. .................................................................................... 99 Figure 97. MS/MS spectrum of detected surfactin analogue (m/z 994) (58) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. .................................................................................................................................................. 99 Figure 98. MS/MS spectrum of detected surfactin C14 (59) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ............................. 100 Figure 99. MS/MS spectrum of detected surfactin C14 (m/z 1022) (60) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria............ 100 Figure 100. MS/MS spectrum of detected surfactin C15 (m/z 1036) (61) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria............ 101.

(16) ix. Figure 101. Physostigmine-cluster from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ............................................................... 102 Figure 102. Leupeptin-cluster from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ............................................................... 103 Figure 103. Amphotericin-cluster from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ............................................................... 104 Figure 104. Aquayamycin-cluster and angucyclines nodes from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ............................. 105 Figure 105. MS/MS spectrum of detected aquayamycin analogue (m/z 601) (27) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ................................................................................................................................................ 105 Figure 106. MS/MS spectrum of detected aquayamycin analogue (m/z 715) (28) from the molecular network of interactions between endophytic actinobacteria and pathogenic bacteria. ................................................................................................................................................ 106 Figure 107. HPLC-DAD of purified peak corresponding to compound (64)........................ 108 Figure 108. Node and representative MS/MS spectrum of m/z 265 (compound 64) detected from interactions between Coniochaeta sp. FLe4 against S. cattleya RLe1, S. mobaraensis RLe3, S. albospinus RLe7 and K. cystarginea RLe10. .......................................................... 110 Figure 109. Culture of S. albospinus RLe7 over amphotericin B-induced red pigmentation from Coniochaeta sp. FLe4. ................................................................................................... 111 Figure 110. Effect of amphotericin B on Coniochaeta sp. FLe4 in liquid medium compared with solid medium. ................................................................................................................. 112 Figure 111. Culture of endophytic fungi from L. ericoides exposed or in absence to amphotericin B. ...................................................................................................................... 113 Figure 112. HPLC-DAD of purified griseofulvin (65) and UV spectrum ............................ 114 Figure 113. HPLC-DAD of purified dechlorogriseofulvin (66) and UV spectrum .............. 115 Figure 114. HPLC-DAD chromatogram showing the increased intensity of griseofulvin (65) and dechlorogriseofulvin (66) from the fungus FLe9 in presence of amphotericin B (11).... 116 Figure 115. HR-ESI-MS of exudate collected from fungus FLe9 in presence of amphotericin B (11) after 9 days of incubation. ........................................................................................... 117 Figure 116. Biosynthesis pathway of griseofulvin (65)......................................................... 119 Figure 117. Summary illustration of the effect of amphotericin B (11) on the fungus FLe 9. ................................................................................................................................................ 119.

(17) x. LIST OF TABLES. Table 1. Endophytic strains from the LQMo´s collection involved throughout this study. .... 15 Table 2. NMR Spectroscopic Data (500 MHz, MeOH-d4) for compound (1) ........................ 26 Table 3. NMR Spectroscopic Data (500 MHz, acetone-d6) for compound (2) ....................... 28 Table 4. NMR Spectroscopic Data (500 MHz, MeOH-d4) for compound (3) ........................ 29 Table 5. NMR Spectroscopic Data (500 MHz, CDCl3) for compound (5).............................. 32 Table 6. NMR Spectroscopic Data (500 MHz, CDCl3) for compound (6).............................. 34 Table 7. NMR Spectroscopic Data (500 MHz, MeOH-d4) for compound (64) .................... 108 Table 8. NMR Spectroscopic Data (500 MHz, MeOH-d4) for compound (65) .................... 114 Table 9. NMR Spectroscopic Data (500 MHz, MeOH-d4) for compound (66) .................... 115.

(18) xi. LIST OF SYMBOLS AND ABBREVIATIONS. AchE ACN ATCC br s o C CDCl3 CID δ d dd ddd DAD DHB DMSO DNP dquint D2O ELSD ESI-MS gCOSY gHSQC gHMBC GNPS Hax Heq HPLC HQNO HR-ESI-MS ISP-2 LB LC-MS/MS m MALDI-TOF IMS Mb MeOH MeOH-d4 MHz MIC µL µM MS/MS NHQ NMR NOE DIFF. Acetylcholinesterase Acetonitrile American type culture collection Broad singlet Celsius degree Deuterated chloroform Collision induced dissociation Chemical shift Doublet Doublet of doublets Doublet of doublet of doublets Diode array detector Dihydroxybenzoic acid Dimethyl sulfoxide Dictionary of Natural Products Double quintet Deuterium oxide Evaporative Light Scattering Detector Electrospray ionization mass spectrometry Gradient correlation spectroscopy Gradient heteronuclear single-quantum correlation Gradient heteronuclear multiple-bond correlation Global natural products social molecular networking Hydrogen in axial position Hydrogen in equatorial position High performance liquid chromatography 2-Heptyl-4-hydroxyquinoline N-oxide High resolution electrospray International Streptomyces Project Lysogeny broth medium Liquid chromatography-tandem mass spectrometry Multiplet Matrix-assisted laser desorption/ionization time-of-flight imaging mass spectrometry Megabases Methanol Deuterated methanol Megahertz Minimal inhibitory concentration Microliter Micromolar Tandem mass spectrometry 2-Nonyl-4-hydroxyquinoline Nuclear Magnetic Resonance Nuclear Overhauser effect differential.

(19) xii. NOESY NQNO OSMAC PDB PQS q quint Rhas sep SFM SPE t TOCSY TQNO UHPLC-TOF-MS UHQ UV. Homonuclear two-dimensional NOE spectroscopy 2-Nonyl-4-hydroxyquinoline N-oxide One strain-many compounds Potato dextrose broth Pseudomonas quinolone signals Quartet Quintuplet Rhamnose Singlet septet Soy Flour Mannitol Solid Phase Extraction Triplet Total correlation spectroscopy Tridecyl-4-hydroxyquinoline N-oxide Ultra-High Performance Liquid Chromatography 2-Undecyl-4-hydroxyquinoline Ultraviolet.

(20) xiii. LIST OF APPENDICES Appendix A - 1H NMR (500 MHz, MeOH-d4) spectrum of compound (1) ......................... 147 Appendix B - gCOSY (500 MHz, MeOH-d4) spectrum of compound (1) ........................... 147 Appendix C - gHSQC (500 MHz, MeOH-d4) spectrum of compound (1) ........................... 148 Appendix D - gHMBC (500 MHz, MeOH-d4) spectrum of compound (1).......................... 148 Appendix E - 1H NMR (500 MHz, acetone-d6) spectrum of compound (2) ........................ 149 Appendix F - gCOSY (500 MHz, acetone-d6) spectrum of compound (2) .......................... 149 Appendix G - gHSQC (500 MHz, acetone-d6) spectrum of compound (2) ......................... 150 Appendix H - gHMBC (500 MHz, acetone-d6) spectrum of compound (2) ........................ 150 Appendix I - 1H NMR (500 MHz, MeOH-d4) spectrum of compound (3) .......................... 151 Appendix J - gCOSY (500 MHz, MeOH-d4) spectrum of compound (3)............................ 151 Appendix K- gHSQC (500 MHz, MeOH-d4) spectrum of compound (3) ........................... 152 Appendix L - gHMBC (500 MHz, MeOH-d4) spectrum of compound (3) .......................... 152 Appendix M - HR-ESI-MS of purified compound (4) .......................................................... 153 Appendix N - 1H NMR (500 MHz, CDCl3) spectrum of compound (5) ............................... 154 Appendix O - gCOSY (500 MHz, CDCl3) spectrum of compound (5) ................................ 154 Appendix P - gHSQC (500 MHz, CDCl3) spectrum of compound (5) ................................. 155 Appendix Q - gHMBC (500 MHz, CDCl3) spectrum of compound (5) ............................... 155 Appendix R - 1H NMR (500 MHz, CDCl3) spectrum of compound (6) ............................... 156 Appendix S - gCOSY (500 MHz, CDCl3) spectrum of compound (6) ................................. 156 Appendix T - gHSQC (500 MHz, CDCl3) spectrum of compound (6) ................................. 157 Appendix U - gHMBC (500 MHz, CDCl3) spectrum of compound (6) ............................... 157 Appendix V - NOESY (500 MHz, CDCl3) spectrum of compound (6) ................................ 158 Appendix W - 1H NMR (500 MHz, CDCl3) spectrum of compound (7) .............................. 158 Appendix X - 1H NMR (500 MHz, MeOH-d4) spectrum of compound (64) ....................... 159 Appendix Y - COSY (500 MHz, MeOH-d4) spectrum of compound (64) ........................... 159 Appendix Z - gHSQC (500 MHz, MeOH-d4) spectrum of compound (64) ......................... 160 Appendix AA - gHMBC (500 MHz, JHC 8Hz, MeOH-d4) spectrum of compound (64) ...... 160 Appendix BB - gHMBC (500 MHz, JHC 4Hz, MeOH-d4) spectrum of compound (64) ...... 161 Appendix CC - NOE DIFF (500 MHz, MeOH-d4) spectrum of compound (64)................. 161 Appendix DD - NOESY (500 MHz, MeOH-d4) spectrum of compound (64) ..................... 162 Appendix EE - TOCSY 1D 1.12 ppm (600 MHz, MeOH-d4) spectrum of compound (64) 162 Appendix FF - TOCSY 1D 6.19 ppm (600 MHz, MeOH-d4) spectrum of compound (64) 163.

(21) xiv. Appendix GG - 1H NMR (500 MHz, MeOH-d4) spectrum of compound (65) .................... 163 Appendix HH - gCOSY (500 MHz, MeOH-d4) spectrum of compound (65) ..................... 164 Appendix II - gHSQC (500 MHz, MeOH-d4) spectrum of compound (65)......................... 164 Appendix JJ - gHMBC (500 MHz, MeOH-d4) spectrum of compound (65) ...................... 165 Appendix KK - HR-ESI-MS of purified griseofulvin (65) ................................................... 166 Appendix LL - 1H NMR (500 MHz, MeOH-d4) spectrum of compound (66)..................... 167 Appendix MM - gCOSY (500 MHz, MeOH-d4) spectrum of compound (66) .................... 167 Appendix NN - gHSQC (500 MHz, MeOH-d4) spectrum of compound (66) ...................... 168 Appendix OO - gHMBC (500 MHz, MeOH-d4) spectrum of compound (66) .................... 168 Appendix PP - HR-ESI-MS of purified dechlorogriseofulvin (66) ...................................... 169.

(22) xv. LIST OF CONTENT ABSTRACT ................................................................................................................................ i RESUMO ................................................................................................................................... ii LIST OF FIGURES ...................................................................................................................iii LIST OF TABLES ..................................................................................................................... x LIST OF SYMBOLS AND ABBREVIATIONS ...................................................................... xi LIST OF APPENDICES .........................................................................................................xiii 1. INTRODUCTION ............................................................................................................ 1 1.1. Relevance of endophytic microorganisms ................................................................... 1. 2. 3.. 4.. 1.2.. Natural products from microbial interactions approaches ........................................... 5. 1.3.. Mass spectrometry related tools for microbial natural products investigation .......... 10. AIM OF THIS STUDY .................................................................................................. 13 MATERIALS AND METHODS ................................................................................... 14 3.1. General instrumentation ............................................................................................. 14 3.2.. Reagents and general material ................................................................................... 14. 3.3.. Strains and culture conditions .................................................................................... 15. 3.4.. Sample preparation for MALDI-TOF IMS................................................................ 17. 3.5.. Sample preparation for MS/MS networking .............................................................. 18. 3.6.. LC-MS/MS experiments ............................................................................................ 18. 3.7.. Molecular networking and MALDI-TOF IMS .......................................................... 19. 3.8.. Extraction, fractionation and purification procedures ............................................... 20. 3.9.. Diffusion test with purified compounds against Coniochaeta sp. FLe4.................... 22. 3.10.. MIC assay with pure substance .............................................................................. 22. 3.11.. Measurement of colony areas................................................................................. 23. RESULTS AND DISCUSSION ..................................................................................... 24 4.1. Microbial interactions of endophytic microorganisms .............................................. 24 4.2.. Mass spectrometry approaches applied to microbial interactions ............................. 36. 4.2.1.. Interkingdom interactions amongst endophytic microorganisms ....................... 37. 4.2.2.. Five-strains interactions amongst actinobacteria influences colony size ........... 62. 4.2.3.. Microbial interactions between endophytes and opportunistic pathogens ......... 75. 4.3.. Amphotericin B as inducer of fungal responses ...................................................... 107. 4.3.1. Chemical investigation of the chemical response of Coniochaeta sp. FLe4 against amphotericin B ................................................................................................... 107 4.3.2. Chemical investigation of the chemical response of other endophytic fungi against amphotericin B ................................................................................................... 112 5. CONCLUSIONS ........................................................................................................... 120 6. REFERENCES ............................................................................................................. 121 APPENDICES....................................................................................................................... 147.

(23) 1. 1.. INTRODUCTION. 1.1.. Relevance of endophytic microorganisms. The first report of an endophytic fungus was published more than a century ago (Freeman, 1904), describing the presence of a non-spore forming fungus in the seeds of Lolium temulentum and suggesting a possible symbiotic relationship between the fungus and the host. The term “endophyte” was later clarified in the biological context by considering that many biological terms evolve over time (Wilson, 1995). The proposed definition considered not just the location but also the infection strategy by the microorganism. Therefore, endophytes were defined as fungi or bacteria that during all or part of their life cycle invade tissues of living plants without causing symptoms of disease (Wilson, 1995). Interestingly, in that paper was emphasized that, instead of being slaves of rules and definitions, the priority should be placed on the biological context of the situation. As the question regarding to why infection by endophytes does not trigger a defense response by the plant host (Wilson, 1995), a balanced antagonism was proposed as a consequence of endophyte-host interaction (Schulz & Boyle, 2005; Schulz, Rommert, Dammann, Aust, & Strack, 1999). By investigating endophytes and plant pathogens, it was found that a higher proportion of endophytes produced herbicidal metabolites when compared to microorganisms isolated from other sources (Schulz et al., 1999). Additionally, it was suggested that secondary metabolites produced by pathogens and endophytes inhabiting the same host may be directed against each other in order to decrease their competition (Schulz et al., 1999). This is a clear example of microbial metabolites as mediators of biological responses in ecological contexts, such as plant-microorganisms systems. Endophytes became interesting as bioactive compounds sources since the first report of an endophytic fungus, Taxomyces andreanae, producing the anticancer compound paclitaxel (Stierle, Strobel, & Stierle, 1993). Paclitaxel (Figure 1) was further investigated and still remains amongst one of the most effective chemotherapeutics currently used against cancer (Cragg, Grothaus, & Newman, 2014; Newman & Cragg, 2016). Paclitaxel has been reported from several endophytes (Somjaipeng, Medina, & Magan, 2016), including actinobacteria such as Kitasatospora sp. (Caruso et al., 2000), as part of the efforts to find sustainable sources for this compound (Liu, Gong, & Zhu, 2016). After several years of research focused on obtaining.

(24) 2. more amounts of this compound, the question about why endophytic microorganisms produced the same compound as their hosts kept unanswered (Talbot, 2015). A relatively recent study provided some answers and gave new insights into the fungi-host interaction, with paclitaxel as one of the mediators of this relationship (Soliman et al., 2015; Soliman & Raizada, 2013). Briefly, as paclitaxel acts as fungicide (Soliman, Trobacher, Tsao, Greenwood, & Raizada, 2013), yew tree formed a symbiotic relationship with taxol-producing endophytes to protect itself against pathogen invasion (Soliman, Tsao, & Raizada, 2011). The endophyte protects diving cells from paclitaxel phytotoxicity by storage in hydrophobic bodies. As a response to pathogen elicitors, the hydrophobic bodies containing the antifungal are released by exocytosis at the pathogen entry points. So, while plant-produced paclitaxel assists general immunity, endophytic-produced paclitaxel might target immunity where plant cells cannot, finally explaining why both organisms produce paclitaxel (Soliman et al., 2015). Maytansine (Figure 1), another important anticancer and cytotoxic compound, was discovered in 1970 from Putterlickia species and in other Celastraceae plants of the genus Maytenus (Kupchan et al., 1977; Kupchan et al., 1972). Interestingly, it was demonstrated a different localization of maytansine in plant tissues. While in Maytenus, it was localized in the above-ground tissues; in Putterlickia plants this compound was accumulated in the roots (Kupchan et al., 1977; Kupchan et al., 1972). Further investigation enabled to demonstrate that maytansine was produced by an endophytic microbial community within the roots of Putterlickia verrucosa and P. retrospinosa (Kusari, S. et al., 2014). Besides that, in Maytenus serrata, maytansine is produced jointly by the endophytic bacterial community with the host plant (Kusari, P. et al., 2016). Recent studies showed detection of new maytansinoids in P. pyracantha (Eckelmann, Kusari, & Spiteller, 2016), opening up further questions addressed to reveal the ecological relevance of maytansinoids in their plant-hosts. A large number of publications about endophytic microorganisms focused on natural products sources became available and several reviews highlight the importance of endophytic fungi for the pursuit of natural products (Aly, Debbab, Kjer, & Proksch, 2010; Borges, W., Borges, K., Bonato, Said, & Pupo, 2009; Gunatilaka, 2006; Kharwar, Mishra, Gond, Stierle, & Stierle, 2011; Schulz, Boyle, Draeger, Rommert, & Krohn, 2002; Suryanarayanan et al., 2009; Verma, Kharwar, & Strobel, 2009; Wang & Dai, 2011) as well as endophytic actinobacteria (Golinska et al., 2015; Qin, Xing, Jiang, Xu, & Li, 2011; Raja & Prabakarana, 2011) or endophytes in general as sources for therapeutic uses in various fields (Gouda, Das, Sen, Shin, & Patra, 2016). Endophytes can potentially be used for peptide based drugs (Abdalla & Matasyoh,. 2014). or. even. other. anticancer. compounds,. such. as. the. pro-drug.

(25) 3. deoxypodophyllotoxin (Kusari, S., Lamshoeft, & Spiteller, 2009), camptothecin (Venugopalan, Potunuru, Dixit, & Srivastava, 2016) or solamargine (El-Hawary et al., 2016) (Figure 1), amongst others. However, their use at industrial level will have to wait for further developments (Kusari, S., Pandey, & Spiteller, 2013; Kusari, S. & Spiteller, 2011). Currently, as illustrated with the paclitaxel investigations, the discussion about the real sources of several natural products have turned into what those metabolites are doing in nature (Davies, 2013; Davies & Ryan, 2012; Newman & Cragg, 2015; Talbot, 2015). An understanding of the chemical ecology behind microbial interactions of endophytes will lead to reveal their inexhaustible biosynthetic potential (Kusari, S., Hertweck, & Spitellert, 2012). The role natural products may play in the endophyte-host plant interaction is a matter of recent interest. Considering the wide range of biological activities already discovered for the reported microbial metabolites, their role in nature may be suggested. Since microorganisms use the chemical language to communicate and interact, one of the suggested roles may be the interference in quorum sensing by attenuating virulence factors of pathogens, which means quenching of pathogen quorum molecules (Kusari, P. et al., 2014). In nature, microbes and plants are in a close association, and the study of population dinamics, gene expression as well as metabolite production involving microbe-microbe and microbe-plant quorum sensing phenomena will give further directions to completely understand these ecosystems (Kusari, P., Kusari, S., Spiteller, & Kayser, 2015). One example where a tripartite interaction mediated by quorum sensing molecules illustrates the importance of chemical communication in ecological systems. Pantoea agglomerans (olive plant epiphyte) and Erwinia toletana (endophyte), nonpathogenic bacteria, are associated with olive knot disease. Both microorganisms release homoserine lactones analogues (Figure 1), signals that modulate the virulence of Pseudomonas savastanoi pv. Savastanoi, responsible pathogen for the disease (Hosni et al., 2011). The interference in quorum sensing is generally mediated mainly by two enzymes, lactonase and acylase, for quenching or degradating of homoserine lactone autoinducers (Hong, Koh, Sam, Yin, & Chan, 2012). Interestingly, homoserine lactone acylase has been reported from endophytic Streptomyces, which may be involved in suppressing the soft rot infection by Pectobacterium carotovorum spp. carotovorum on potato (Chankhamhaengdecha, Hongvijit, Srichaisupakit, Charnchai, & Panbangred, 2013). These findings show the complexity of chemical communication in ecological systems. Biotechnological applications of natural products for drug resistance can be fully exploited if factors such as autoinducer triggers, production/release signals or even degradation systems are considered (Kusari, P. et al., 2015)..

(26) 4. Figure 1. Illustrative examples of natural products from endophytes.. The role of endophytes in plant growth has been also investigated (Gaiero et al., 2013; Miliute et al., 2016). Plant promoting traits, such as production of indole-3-acetic acid (Figure 1), were observed in endophytes from apple phyllosphere (Miliute et al., 2016). Indole-3-acetic acid is a phytohormone that stimulates cell division as well as formation of plant roots (Davies, 2010). The effect of bacterial endophytes was also investigated in Trigonella foenum-graecum L. Four out of nine endophytic Bacillus sp., associated with that medicinal plant, showed a significant impact on plant growth and besides that, contributed to the increase in diosgenin biosynthesis, a steroid sapogenin (Jasim, Geethu, Mathew, & Radhakrishnan, 2015). In another medicinal plant, Euphorbia pekinensis, the effective growth promotion as a consequence of treatment with endophytic fungi was demonstrated. Interestingly, it was also proved that treatment of plants with non-endophytic fungi, was not as effective as the treatment with endophytes. These findings could be attributed to the production of phytohormones, such as indole-3 acetic acid (Dai, Yu, & Li, 2008). The mechanisms behind the plant-growth promotion by endophytic bacteria have been proposed as phytostimulation (through production of phytohormones), biofertilization (by increasing access to nutrients) and biocontrol (by protection against phytopathogens) (Bloemberg & Lugtenberg, 2001). A complete understanding of the microbial community composition of the plant system is necessary to predict the effectiveness of an endophyte to promote plant growth (Gaiero et al., 2013). Of.

(27) 5. course, more comprehensive tools, such as “omics” approaches, should be used to study endophytes and reveal their role in the plant host (Kaul, Sharma, & Dhar, 2016). Even more relevant for future research, after understanding the endophyte community dynamics, is how these populations will be affected in an environment influenced by climate change (Gaiero et al., 2013). As microorganisms are still underexplored reservoirs of natural products, endophytes from the Brazilian medicinal plant Lychnophora ericoides (falsa-arnica) were selected in this study for investigation of their natural products profile. L. ericoides has been used in traditional medicine for treatment of wounds, inflammation and pain and several studies focused on its chemistry have been carried out (Borella, Lopes, Vichnewski, Cunha, & Herz, 1998; dos Santos, Gobbo-Neto, Albarella, de Souza, & Lopes, 2005; Gobbo-Neto, L., dos Santos, et al., 2008; Gobbo-Neto, L., Gates, & Lopes, 2008; Gobbo-Neto, L. et al., 2010; Gobbo-Neto, L. & Lopes, 2008; Gobbo-Neto, L. et al., 2005; Sakamoto et al., 2003; Semir, Rezende, Monge, & Lopes, 2011). As part of the efforts of our research at the Laboratory of Chemistry of Microorganisms (LQMo) at the School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, coordinated by Prof. Dr. Mônica T. Pupo, endophytic microorganisms from L. ericoides were isolated and a first study including some of these actinobacteria strains was recently published by our group (Conti et al., 2016). In light of the described studies and the importance of endophytes for this research field, microbial interactions approaches were used in this PhD thesis in order to investigate natural products from endophytes of L. ericoides.. 1.2.. Natural products from microbial interactions approaches. As it was mentioned in the previous section, microorganisms inhabiting plant tissues are interacting with other microorganisms. One of the expected consequences of these interactions, which has been the focus of several studies, is the production of secondary metabolites. Several reviews have been published highlighting different strategies involving microbial interactions in order to increase the metabolite diversity (Bertrand et al., 2014; Bode, Bethe, Hofs, & Zeeck, 2002; Marmann, Aly, Lin, Wang, & Proksch, 2014; Pettit, 2009; Rutledge & Challis, 2015; Scherlach & Hertweck, 2009). These approaches are totally consistent with simulation of ecological contexts since microorganisms are in continuous interactions with other microorganisms and even macroorganisms (Suryanarayanan, T., 2013), as previously.

(28) 6. described. However, it is well known that microbes establish different kinds of interactions such as cooperative or competitive relationships (Abrudan et al., 2015; Ghoul & Mitri, 2016; Stubbendieck & Straight, 2016), and most of in vitro microbial interactions have not been tested in more natural settings (Hibbing, Fuqua, Parsek, & Peterson, 2010). Due to the lack of knowledge of the complex regulatory factors that may influence the microbial biosynthetic machinery, a random approach named OSMAC (One Strain – MAny Compounds) was proposed in the last decade (Bode et al., 2002). Briefly, the concept establishes that by modifying culture parameters such as culture vessels, culture media, fermentor size, pH, dissolved oxygen, or even microbial interaction, the chemical diversity can be expanded. By using the OSMAC approach, more than 100 compounds from 25 different structural classes from only 6 microorganisms were isolated (Bode et al., 2002). Microbial interactions approach, or coculture strategy, has been widely used to induce microbial compounds of interest, and plenty of examples can be found in literature. For instance, increased production of paclitaxel from Paraconiothyrium SSM001 when exposed to endophytes from the same host, Taxus (yew) tree (Soliman & Raizada, 2013) was observed. The induction of istamycins (Figure 2) in Streptomyces tenjimariensis up to twice-fold as a consequence of the interaction with twelve out of 53 tested bacteria was reported (Slattery, Rajbhandari, & Wesson, 2001). Microbial interactions between Pseudomonas aeruginosa and Enterobacter sp., isolated from a marine environment, enabled the isolation of a blue compound, identified as pyocyanin (Figure 2), as well as the correction of the structural characterization of this compound by NMR due to previous misreported data in the literature (Angell, Bench, Williams, & Watanabe, 2006). Cocultivation of marine fungi have resulted in isolation of new alkaloids, marinamide and its methyl ester (Zhu & Lin, 2006), which chemical structures were later revised and attributed to pyrrolyl 4-quinolone analogues (Figure 2) (Zhu, Chen, Wu, & Pan, 2013), as well as a new xanthone, 8-hydroxy-3-methyl-9-oxo-9H-xanthene1-carboxylic acid methyl ether (Figure 2) (Li, C. et al., 2011). Microbial interaction between Aspergillus fumigatus and Streptomyces peucetius led to the induction of the new metabolites, fumiformamide. and. N,N’-((1Z,. 3Z)-1,4-bis(4-methoxyphenyl)buta-1,3-diene-2,3-. diyl)diformamide (Figure 2), two known N-formyl derivatives and a xanthocillin analogue BU4704 (Zuck, Shipley, & Newman, 2011). The coculturing of the endophytic fungus Fusarium tricinctum with the bacterium Bacillus subtilis led to the production of three new compounds, macrocarpon C, 2-(carboxymethylamino)benzoic acid and (-)-citreoisocumarinol (Figure 2), as well as the increased levels of known compounds of the chemical classes of pyrones, cyclic depsipeptides and lipopeptides (Ola, Thomy, Lai, Broetz-Oesterhelt, & Prolcsch, 2013). Three.

(29) 7. new decalin-type tetramic acid analogues, N-demethyl-ophiosetin and pallidorosetins A/B, were produced when Fusarium pallidoroseum was cocultured with Saccharopolyspora erythraea (Figure 2) (Whitt, Shipley, Newman, & Zuck, 2014). Three novel macrolactams with unprecedented skeletons, niizalactams A-C, were isolated when Streptomyces sp. NZ-6 was cultured in presence of mycolic acid-containing bacterium Tsukamurella pulmonis TP-B0596 (Hoshino et al., 2015). Interestingly, the same strain T. pulmonis TP-B0596 induced the production of eight new 5-alkyl-1,2,3,4-tetrahydroquinolines (Figure 2) (Sugiyama et al., 2015) as well as a novel class of lipidic metabolites named streptoaminals (Figure 2) from Streptomyces nigrescens HEK616 (Sugiyama et al., 2016)..

(30) 8. Figure 2. Illustrative examples of natural products from microbial interactions..

(31) 9. A remarkable study supported the hypothesis that not only diffusible signals but also intimate physical interactions contribute to microbial communication (Schroeckh et al., 2009). In that study, it was demonstrated that the physical interaction of Aspergillus nidulans with Streptomyces hygroscopicus led to stimulate the fungal biosynthesis of aromatic polyketides, such as orsellinic acid, lecanoric acid, and cathepsin inhibitors F-9775A and F-9775B (Figure 2) (Schroeckh et al., 2009). Another outstanding study screened 657 coculture experiments involving fungal strains by using a high-throughput UHPLC-TOF-MS-based metabolomic approach. In this study, two types of inductions were observed, de novo biosynthesis and upregulation. Interestingly, most of the detected features (peaks) from monocultures (80%) matched at least one reported compound from the DNP database ("Dictionary of Natural Products,"), while the matches were zero when the induced features, corresponding to the induced metabolites from coculture, where searched. This results suggest that the features detected at the fungal interaction zones in cocultures may correspond to novel chemical compounds, not included in natural products databases (Bertrand et al., 2013). Taking into consideration that a single microbial compound may have an impact on the metabolism of microorganisms inhabiting the same environment (Kusari, S. et al., 2013), exposing microorganisms to simulated communities where chemical exchange occurs makes the previous examples coherent with what may happen in natural contexts. At this point it is necessary to highlight that the study of microbe-microbe interactions may provide valuable information to decipher chemical communication in nature, a necessary step before validate the findings in more complex microbial communities (Lareen, Burton, & Schafer, 2016) as it may occur in natural systems. Besides that, multispecies interactions should be studied since endophytes communities are diverse and complex, and consequently, may be more involved in interactions with microbial competitors than with the plant host itself (van Overbeek & Saikkonen, 2016). This is consistent, since microbes are part of essential consortia (Newman & Cragg, 2015), no matter what the environment they inhabit. Considering the genome size of 8 Mb in actinobacteria, up to 11 Mb in myxobacteria, and more than 30 Mb in fungi, the enormous potential of microorganisms for production of small molecules is big (Bode et al., 2002). This is consistent with recent genomic approaches, such as metagenomics, showing global microbial biosynthetic diversity holds enormous potential for natural products discovery (Charlop-Powers et al., 2015). The bottleneck lays in finding the triggers for biosynthesis of the cryptic metabolites, although the regulation of antibiotic production has been extensively investigated in microbial models such as S. coelicolor, but also.

(32) 10. in nonmodel streptomycetes (Liu, Chater, Chandra, Niu, & Tan, 2013), giving directions for regulation of secondary metabolites that can be extended perhaps in other actinobacteria. Due to the relevance of small molecules as mediators of chemical responses during microbial interactions, and the fact that the levels of those chemicals are very low for detection, the need for more sensitive techniques is required. For that reason, mass spectrometry related tools were applied to the current study of endophytes from L. ericoides.. 1.3.. Mass spectrometry related tools for microbial natural produ cts. investigation. The necessity for more sensitive techniques that enable to detect small quantities of microbial compounds can be illustrated with the yet-uncharacterized secondary metabolite produced by human gut bacteria, colibactin, involved in colorectal cancer (Nougayrede et al., 2006). After more than ten years of research, the chemical structure of this cryptic metabolite remains unsolved (Bode, 2015). However, several approaches, including NMR, MS, genomics and bioinformatics tools, have enabled to tentatively propose candidates for pre-colibactins (Figure 3) (Li, Z. R. et al., 2015; Vizcaino & Crawford, 2015). A recent example given by the identification of maytansinoids in plant tissues showed clearly the need for MS/MS data that enable future studies to identify natural products without the necessity for isolating (Eckelmann et al., 2016). For that reason, techniques that enable to obtain enough chemical information from small quantities of samples are relevant for the current research, including in the field of natural products. Recent developments have occurred in the detection of microbial small molecules by using mass spectrometry (MS) approaches. A first approach recently used, Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight Imaging Mass Spectrometry (MALDI-TOF IMS) for detecting microbial small molecules has been developed ad widely used (Yang et al., 2012). Basically, MALDI-TOF IMS offers the possibility to detect small molecules from agar pieces containing cultured microorganisms, and also allows to visualize their distribution in two or even three dimensions (Watrous et al., 2013). Several examples and even the discovery of novel natural products and biotransformation processes have been published in the past few years (Gonzalez et al., 2012; Moree et al., 2012). This technique has been also applied for monitoring suppression of quorum sensing signals by endophytic bacteria from Cannabis sativa L. (Kusari,.

(33) 11. P. et al., 2014). Besides that, it enabled to visualize the spatial distribution of metabolites in situ, as illustrated by maytansine in the roots of Putterlickia verrucosa and P. retrospinosa, enabling to prove the hypothesis of microbial endophytes as actual producers of the compound (Kusari, S. et al., 2014). Another MS-based approach is molecular networking. It consists in the comparison of fragmentation patterns amongst different MS/MS spectra in order to find similarities amongst them. This approach was initially applied for peptide identification (Guthals & Bandeira, 2012) and it was then developed for microbial small molecules analysis, since every single molecule can lead to a unique MS/MS spectra, such as a fingerprint and then similarities can be found in structurally related compounds (Watrous et al., 2012; Yang et al., 2013). Molecular networking has been important for detection and partial characterization of natural products, such as an antifungal lipopeptide from the syringomycin family, thanamycin (Figure 3) (Watrous et al., 2012). As manual analysis of large MS/MS datasets results inefficient, a free access platform for the automated analysis and cross correlation of natural products MS/MS data, named Global Natural Products Social Molecular Networking (Wang, M. et al., 2016) (GNPS, gnps.ucsd.edu) was recently developed. What can be done by using the GNPS workflow include storage and organization of MS/MS data, generation and visualization of molecular networking, dereplication of natural products, contribution to MS/MS natural products collection, sharing and curate data. For dereplication purposes, which means finding known or already identified natural products, based on comparison with MS/MS data the GNPS platform includes libraries such as MassBank, ReSpect and NIST, as well as collection of natural products and pharmacologically active compounds related to the National Institutes of Health (NIH) in the United States (Wang, M. et al., 2016). Currently, the GNPS libraries contains more than 200.000 MS/MS spectra representing more than 22.000 compounds (Wang, M. et al., 2016). However, the number of published natural products can be about 300.000 to 600.000 (Berdy, 2012), which means the total chemical space still remains to be covered. To demonstrate how GNPS platform can support natural products discovery, a set of five analogues of a broadspectrum antibiotic, stenothricin, were identified and named stenothricin-GNPS 1-5. The most abundant of these analogues was isolated successfully confirming its structural similarity (Figure 3) (Wang, M. et al., 2016). Computational methods for detection and investigation of small molecules using mass spectrometry data have been developed (Hufsky, Scheubert, & Bocker, 2014). Recently, in silico approaches that enable to search experimental MS/MS.

(34) 12. spectra have been proposed and successfully tested to compensate the lack of experimental data (Allard et al., 2016).. Figure 3. Illustrative examples of natural products discovered by MS approaches and molecular networking.. Structural elucidation of new compounds based only by mass spectrometry or even elucidate the fragmentation pathway for knowns compounds are challenging tasks even for experienced mass spectrometrists (Chai, Wang, & Wang, 2016). However, as previously mentioned, fragmentation patterns are fingerprints that help in finding structural relationship amongst chemical families, as it has been widely reported by using molecular networking (Covington, McLeanab, & Bachmann, 2016; Floros, Jensen, Dorrestein, & Koyama, 2016; Garg et al., 2015; Mascuch et al., 2015; Nguyen et al., 2013; Okada, Wu, Mao, Bushin, & Seyedsayamdost, 2016; Wang, M. et al., 2016; Watrous et al., 2012). Due to the extensive application of MS/MS, it is still necessary to investigate the mechanisms for specific fragmentation reactions (Chai et al., 2016) to fully support structural elucidation. At this point, it is important to keep in mind the relevance of analyzing mass differences instead of defining the specific reactions involved in each fragment formation, in order to use mass fragmentation as a useful tool for structural elucidation (Demarque, Crotti, Vessecchi, Lopes, & Lopes, 2016)..

(35) 13. 2.. AIM OF THIS STUDY. The aim of this study was concerned with natural products of endophytes from the Brazilian medicinal plant Lychnophora ericoides and their elicitation during microbial interactions, and extended to microbial interactions of endophytes against opportunistic pathogenic bacteria, such as Bacillus subtilis and Pseudomonas aeruginosa. In order to achieve this aim, mass spectrometry approaches, such as MALDI-TOF IMS (Yang et al., 2012) and molecular networking (Wang, M. et al., 2016; Watrous et al., 2012), were used for data analysis of microbial interactions. Chromatographic procedures for comparison of chemical profiles amongst samples as well as purification of microbial metabolites and posterior structural elucidation based on NMR, UV and/or MS data were carried out..

(36) 14. 3.. MATERIALS AND METHODS. 3.1.. General instrumentation. Analyses of extracts and purified compounds were carried out on a Shimadzu Prominence Nexera XR HPLC coupled to a DAD (SPD-M10AVP) and ELS detectors. Purification of described compounds were carried out on a Shimadzu Prominence Nexera XR HPLC coupled to a DAD (SPD-M10AVP) and fraction collector FRC10A Shimadzu (Shimadzu, Kyoto, Japan). LC-MS/MS analysis of crude extracts were carried out on an Agilent 1290 UHPLC coupled to a MicrOTOF-QII mass spectrometer (Bruker Daltonics) equipped with ESI source. MALDI-TOF IMS were carried out either at an Autoflex or Microflex (Bruker Daltonics). HRESI-MS also obtained on UltrO-TOF (Bruker-daltonics, Billerica, USA). Vertical sterilizer (Phoenix® AV 75). Analytical balance BP 121S (Sartorius). BOD incubator (biochemical oxygen demand - Tecnal). Vacuum pump (Micronal). Laminar flow biohood (Pachane® PA 320). VisiprepTM SPE Vacuum Manifold (Supelco). NMR spectrometers DRX-500MHz, DRX400MHz, DPX-300MHz (Bruker UK, Coventry, UK) at FFCLRP-USP, Ribeirão Preto, SP. Brazil, NMR Ascend III 600 MHz (Bruker UK, Coventry, UK) at UNESP-Araraquara, SP. Brazil. Rotatory evaporators (Büchi R-114). Millipore Milli-Q (Millipore) and Reverse Osmosis Water Purificator System OS10LX (Gehaka). Sonicator Branson1200 (Branson Ultrasonics Corporation).. 3.2.. Reagents and general material. Solvents: Organic solvents analytical grade (Synth), HPLC grade (Merck, JT Baker or Mallinckrodt), deuterated solvents (Acros and Sigma-Aldrich), LC-MS grade (J. T. Baker). Chromatography: Kinetex™ 1.7 µm x 50 mm x 2.1 mm C18 RP column, Phenomenex Gemini C18 110A semipreparative (5µm x 250 mm x 10 mm) column, Gemini Phe-C6 110A semipreparative (5µm x 250 mm x 10 mm) column. Ascentis® Express C18 (10 cm x 2.1 mm x 2.7 µm) Sigma-Aldrich®, Ascentis® Express Phe-Hex columns Sigma-Aldrich® (10 cm x.