Cargando…

A glimpse into the fungal metabolomic abyss: Novel network analysis reveals relationships between exogenous compounds and their outputs

Fungal specialized metabolites are a major source of beneficial compounds that are routinely isolated, characterized, and manufactured as pharmaceuticals, agrochemical agents, and industrial chemicals. The production of these metabolites is encoded by biosynthetic gene clusters that are often silent...

Descripción completa

Detalles Bibliográficos
Autores principales: Gopalakrishnan Meena, Muralikrishnan, Lane, Matthew J, Tannous, Joanna, Carrell, Alyssa A, Abraham, Paul E, Giannone, Richard J, Ané, Jean-Michel, Keller, Nancy P, Labbé, Jesse L, Geiger, Armin G, Kainer, David, Jacobson, Daniel A, Rush, Tomás A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10581544/
https://www.ncbi.nlm.nih.gov/pubmed/37854706
http://dx.doi.org/10.1093/pnasnexus/pgad322
_version_ 1785122159780167680
author Gopalakrishnan Meena, Muralikrishnan
Lane, Matthew J
Tannous, Joanna
Carrell, Alyssa A
Abraham, Paul E
Giannone, Richard J
Ané, Jean-Michel
Keller, Nancy P
Labbé, Jesse L
Geiger, Armin G
Kainer, David
Jacobson, Daniel A
Rush, Tomás A
author_facet Gopalakrishnan Meena, Muralikrishnan
Lane, Matthew J
Tannous, Joanna
Carrell, Alyssa A
Abraham, Paul E
Giannone, Richard J
Ané, Jean-Michel
Keller, Nancy P
Labbé, Jesse L
Geiger, Armin G
Kainer, David
Jacobson, Daniel A
Rush, Tomás A
author_sort Gopalakrishnan Meena, Muralikrishnan
collection PubMed
description Fungal specialized metabolites are a major source of beneficial compounds that are routinely isolated, characterized, and manufactured as pharmaceuticals, agrochemical agents, and industrial chemicals. The production of these metabolites is encoded by biosynthetic gene clusters that are often silent under standard growth conditions. There are limited resources for characterizing the direct link between abiotic stimuli and metabolite production. Herein, we introduce a network analysis-based, data-driven algorithm comprising two routes to characterize the production of specialized fungal metabolites triggered by different exogenous compounds: the direct route and the auxiliary route. Both routes elucidate the influence of treatments on the production of specialized metabolites from experimental data. The direct route determines known and putative metabolites induced by treatments and provides additional insight over traditional comparison methods. The auxiliary route is specific for discovering unknown analytes, and further identification can be curated through online bioinformatic resources. We validated our algorithm by applying chitooligosaccharides and lipids at two different temperatures to the fungal pathogen Aspergillus fumigatus. After liquid chromatography–mass spectrometry quantification of significantly produced analytes, we used network centrality measures to rank the treatments’ ability to elucidate these analytes and confirmed their identity through fragmentation patterns or in silico spiking with commercially available standards. Later, we examined the transcriptional regulation of these metabolites through real-time quantitative polymerase chain reaction. Our data-driven techniques can complement existing metabolomic network analysis by providing an approach to track the influence of any exogenous stimuli on metabolite production. Our experimental-based algorithm can overcome the bottlenecks in elucidating novel fungal compounds used in drug discovery.
format Online
Article
Text
id pubmed-10581544
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-105815442023-10-18 A glimpse into the fungal metabolomic abyss: Novel network analysis reveals relationships between exogenous compounds and their outputs Gopalakrishnan Meena, Muralikrishnan Lane, Matthew J Tannous, Joanna Carrell, Alyssa A Abraham, Paul E Giannone, Richard J Ané, Jean-Michel Keller, Nancy P Labbé, Jesse L Geiger, Armin G Kainer, David Jacobson, Daniel A Rush, Tomás A PNAS Nexus Biological, Health, and Medical Sciences Fungal specialized metabolites are a major source of beneficial compounds that are routinely isolated, characterized, and manufactured as pharmaceuticals, agrochemical agents, and industrial chemicals. The production of these metabolites is encoded by biosynthetic gene clusters that are often silent under standard growth conditions. There are limited resources for characterizing the direct link between abiotic stimuli and metabolite production. Herein, we introduce a network analysis-based, data-driven algorithm comprising two routes to characterize the production of specialized fungal metabolites triggered by different exogenous compounds: the direct route and the auxiliary route. Both routes elucidate the influence of treatments on the production of specialized metabolites from experimental data. The direct route determines known and putative metabolites induced by treatments and provides additional insight over traditional comparison methods. The auxiliary route is specific for discovering unknown analytes, and further identification can be curated through online bioinformatic resources. We validated our algorithm by applying chitooligosaccharides and lipids at two different temperatures to the fungal pathogen Aspergillus fumigatus. After liquid chromatography–mass spectrometry quantification of significantly produced analytes, we used network centrality measures to rank the treatments’ ability to elucidate these analytes and confirmed their identity through fragmentation patterns or in silico spiking with commercially available standards. Later, we examined the transcriptional regulation of these metabolites through real-time quantitative polymerase chain reaction. Our data-driven techniques can complement existing metabolomic network analysis by providing an approach to track the influence of any exogenous stimuli on metabolite production. Our experimental-based algorithm can overcome the bottlenecks in elucidating novel fungal compounds used in drug discovery. Oxford University Press 2023-09-29 /pmc/articles/PMC10581544/ /pubmed/37854706 http://dx.doi.org/10.1093/pnasnexus/pgad322 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of National Academy of Sciences. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Biological, Health, and Medical Sciences
Gopalakrishnan Meena, Muralikrishnan
Lane, Matthew J
Tannous, Joanna
Carrell, Alyssa A
Abraham, Paul E
Giannone, Richard J
Ané, Jean-Michel
Keller, Nancy P
Labbé, Jesse L
Geiger, Armin G
Kainer, David
Jacobson, Daniel A
Rush, Tomás A
A glimpse into the fungal metabolomic abyss: Novel network analysis reveals relationships between exogenous compounds and their outputs
title A glimpse into the fungal metabolomic abyss: Novel network analysis reveals relationships between exogenous compounds and their outputs
title_full A glimpse into the fungal metabolomic abyss: Novel network analysis reveals relationships between exogenous compounds and their outputs
title_fullStr A glimpse into the fungal metabolomic abyss: Novel network analysis reveals relationships between exogenous compounds and their outputs
title_full_unstemmed A glimpse into the fungal metabolomic abyss: Novel network analysis reveals relationships between exogenous compounds and their outputs
title_short A glimpse into the fungal metabolomic abyss: Novel network analysis reveals relationships between exogenous compounds and their outputs
title_sort glimpse into the fungal metabolomic abyss: novel network analysis reveals relationships between exogenous compounds and their outputs
topic Biological, Health, and Medical Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10581544/
https://www.ncbi.nlm.nih.gov/pubmed/37854706
http://dx.doi.org/10.1093/pnasnexus/pgad322
work_keys_str_mv AT gopalakrishnanmeenamuralikrishnan aglimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT lanematthewj aglimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT tannousjoanna aglimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT carrellalyssaa aglimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT abrahampaule aglimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT giannonerichardj aglimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT anejeanmichel aglimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT kellernancyp aglimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT labbejessel aglimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT geigerarming aglimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT kainerdavid aglimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT jacobsondaniela aglimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT rushtomasa aglimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT gopalakrishnanmeenamuralikrishnan glimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT lanematthewj glimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT tannousjoanna glimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT carrellalyssaa glimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT abrahampaule glimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT giannonerichardj glimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT anejeanmichel glimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT kellernancyp glimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT labbejessel glimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT geigerarming glimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT kainerdavid glimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT jacobsondaniela glimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs
AT rushtomasa glimpseintothefungalmetabolomicabyssnovelnetworkanalysisrevealsrelationshipsbetweenexogenouscompoundsandtheiroutputs