Cargando…
Advanced identification of global bioactivity hotspots via screening of the metabolic fingerprint of entire ecosystems
Natural products (NP) are a valuable drug resource. However, NP-inspired drug leads are declining, among other reasons due to high re-discovery rates. We developed a conceptual framework using the metabolic fingerprint of entire ecosystems (MeE) to facilitate the discovery of global bioactivity hots...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6987164/ https://www.ncbi.nlm.nih.gov/pubmed/31992728 http://dx.doi.org/10.1038/s41598-020-57709-0 |
_version_ | 1783492090538229760 |
---|---|
author | Mueller, Constanze Kremb, Stephan Gonsior, Michael Brack-Werner, Ruth Voolstra, Christian R. Schmitt-Kopplin, Philippe |
author_facet | Mueller, Constanze Kremb, Stephan Gonsior, Michael Brack-Werner, Ruth Voolstra, Christian R. Schmitt-Kopplin, Philippe |
author_sort | Mueller, Constanze |
collection | PubMed |
description | Natural products (NP) are a valuable drug resource. However, NP-inspired drug leads are declining, among other reasons due to high re-discovery rates. We developed a conceptual framework using the metabolic fingerprint of entire ecosystems (MeE) to facilitate the discovery of global bioactivity hotspots. We assessed the MeE of 305 sites of diverse aquatic ecosystems, worldwide. All samples were tested for antiviral effects against the human immunodeficiency virus (HIV), followed by a comprehensive screening for cell-modulatory activity by High-Content Screening (HCS). We discovered a very strong HIV-1 inhibition mainly in samples taken from fjords with a strong terrestrial input. Multivariate data integration demonstrated an association of a set of polyphenols with specific biological alterations (endoplasmic reticulum, lysosomes, and NFkB) caused by these samples. Moreover, we found strong HIV-1 inhibition in one unrelated oceanic sample closely matching to HIV-1-inhibitory drugs on a cytological and a chemical level. Taken together, we demonstrate that even without physical purification, a sophisticated strategy of differential filtering, correlation analysis, and multivariate statistics can be employed to guide chemical analysis, to improve de-replication, and to identify ecosystems with promising characteristics as sources for NP discovery. |
format | Online Article Text |
id | pubmed-6987164 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-69871642020-02-03 Advanced identification of global bioactivity hotspots via screening of the metabolic fingerprint of entire ecosystems Mueller, Constanze Kremb, Stephan Gonsior, Michael Brack-Werner, Ruth Voolstra, Christian R. Schmitt-Kopplin, Philippe Sci Rep Article Natural products (NP) are a valuable drug resource. However, NP-inspired drug leads are declining, among other reasons due to high re-discovery rates. We developed a conceptual framework using the metabolic fingerprint of entire ecosystems (MeE) to facilitate the discovery of global bioactivity hotspots. We assessed the MeE of 305 sites of diverse aquatic ecosystems, worldwide. All samples were tested for antiviral effects against the human immunodeficiency virus (HIV), followed by a comprehensive screening for cell-modulatory activity by High-Content Screening (HCS). We discovered a very strong HIV-1 inhibition mainly in samples taken from fjords with a strong terrestrial input. Multivariate data integration demonstrated an association of a set of polyphenols with specific biological alterations (endoplasmic reticulum, lysosomes, and NFkB) caused by these samples. Moreover, we found strong HIV-1 inhibition in one unrelated oceanic sample closely matching to HIV-1-inhibitory drugs on a cytological and a chemical level. Taken together, we demonstrate that even without physical purification, a sophisticated strategy of differential filtering, correlation analysis, and multivariate statistics can be employed to guide chemical analysis, to improve de-replication, and to identify ecosystems with promising characteristics as sources for NP discovery. Nature Publishing Group UK 2020-01-28 /pmc/articles/PMC6987164/ /pubmed/31992728 http://dx.doi.org/10.1038/s41598-020-57709-0 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Mueller, Constanze Kremb, Stephan Gonsior, Michael Brack-Werner, Ruth Voolstra, Christian R. Schmitt-Kopplin, Philippe Advanced identification of global bioactivity hotspots via screening of the metabolic fingerprint of entire ecosystems |
title | Advanced identification of global bioactivity hotspots via screening of the metabolic fingerprint of entire ecosystems |
title_full | Advanced identification of global bioactivity hotspots via screening of the metabolic fingerprint of entire ecosystems |
title_fullStr | Advanced identification of global bioactivity hotspots via screening of the metabolic fingerprint of entire ecosystems |
title_full_unstemmed | Advanced identification of global bioactivity hotspots via screening of the metabolic fingerprint of entire ecosystems |
title_short | Advanced identification of global bioactivity hotspots via screening of the metabolic fingerprint of entire ecosystems |
title_sort | advanced identification of global bioactivity hotspots via screening of the metabolic fingerprint of entire ecosystems |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6987164/ https://www.ncbi.nlm.nih.gov/pubmed/31992728 http://dx.doi.org/10.1038/s41598-020-57709-0 |
work_keys_str_mv | AT muellerconstanze advancedidentificationofglobalbioactivityhotspotsviascreeningofthemetabolicfingerprintofentireecosystems AT krembstephan advancedidentificationofglobalbioactivityhotspotsviascreeningofthemetabolicfingerprintofentireecosystems AT gonsiormichael advancedidentificationofglobalbioactivityhotspotsviascreeningofthemetabolicfingerprintofentireecosystems AT brackwernerruth advancedidentificationofglobalbioactivityhotspotsviascreeningofthemetabolicfingerprintofentireecosystems AT voolstrachristianr advancedidentificationofglobalbioactivityhotspotsviascreeningofthemetabolicfingerprintofentireecosystems AT schmittkopplinphilippe advancedidentificationofglobalbioactivityhotspotsviascreeningofthemetabolicfingerprintofentireecosystems |