Integration of Phenomics and Metabolomics Datasets Reveals Different Mode of Action of Biostimulants Based on Protein Hydrolysates in Lactuca sativa L. and Solanum lycopersicum L. Under Salinity
Plant phenomics is becoming a common tool employed to characterize the mode of action of biostimulants. A combination of this technique with other omics such as metabolomics can offer a deeper understanding of a biostimulant effect in planta. However, the most challenging part then is the data analy...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-02-01
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| Series: | Frontiers in Plant Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpls.2021.808711/full |
| _version_ | 1818322733025460224 |
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| author | Mirella Sorrentino Mirella Sorrentino Klára Panzarová Ioannis Spyroglou Lukáš Spíchal Valentina Buffagni Paola Ganugi Youssef Rouphael Giuseppe Colla Luigi Lucini Nuria De Diego |
| author_facet | Mirella Sorrentino Mirella Sorrentino Klára Panzarová Ioannis Spyroglou Lukáš Spíchal Valentina Buffagni Paola Ganugi Youssef Rouphael Giuseppe Colla Luigi Lucini Nuria De Diego |
| author_sort | Mirella Sorrentino |
| collection | DOAJ |
| description | Plant phenomics is becoming a common tool employed to characterize the mode of action of biostimulants. A combination of this technique with other omics such as metabolomics can offer a deeper understanding of a biostimulant effect in planta. However, the most challenging part then is the data analysis and the interpretation of the omics datasets. In this work, we present an example of how different tools, based on multivariate statistical analysis, can help to simplify the omics data and extract the relevant information. We demonstrate this by studying the effect of protein hydrolysate (PH)-based biostimulants derived from different natural sources in lettuce and tomato plants grown in controlled conditions and under salinity. The biostimulants induced different phenotypic and metabolomic responses in both crops. In general, they improved growth and photosynthesis performance under control and salt stress conditions, with better performance in lettuce. To identify the most significant traits for each treatment, a random forest classifier was used. Using this approach, we found out that, in lettuce, biomass-related parameters were the most relevant traits to evaluate the biostimulant mode of action, with a better response mainly connected to plant hormone regulation. However, in tomatoes, the relevant traits were related to chlorophyll fluorescence parameters in combination with certain antistress metabolites that benefit the electron transport chain, such as 4-hydroxycoumarin and vitamin K1 (phylloquinone). Altogether, we show that to go further in the understanding of the use of biostimulants as plant growth promotors and/or stress alleviators, it is highly beneficial to integrate more advanced statistical tools to deal with the huge datasets obtained from the -omics to extract the relevant information. |
| first_indexed | 2024-12-13T11:01:29Z |
| format | Article |
| id | doaj.art-4872aaa907874eff9a8e3a351dd3ce2e |
| institution | Directory Open Access Journal |
| issn | 1664-462X |
| language | English |
| last_indexed | 2024-12-13T11:01:29Z |
| publishDate | 2022-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Plant Science |
| spelling | doaj.art-4872aaa907874eff9a8e3a351dd3ce2e2022-12-21T23:49:15ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2022-02-011210.3389/fpls.2021.808711808711Integration of Phenomics and Metabolomics Datasets Reveals Different Mode of Action of Biostimulants Based on Protein Hydrolysates in Lactuca sativa L. and Solanum lycopersicum L. Under SalinityMirella Sorrentino0Mirella Sorrentino1Klára Panzarová2Ioannis Spyroglou3Lukáš Spíchal4Valentina Buffagni5Paola Ganugi6Youssef Rouphael7Giuseppe Colla8Luigi Lucini9Nuria De Diego10Photon Systems Instruments (PSI), spol. S.r.o., Drásov, CzechiaDepartment of Agricultural Sciences, University of Naples Federico II, Portici, ItalyPhoton Systems Instruments (PSI), spol. S.r.o., Drásov, CzechiaPlant Sciences Core Facility, Central European Institute of Technology, Masaryk University, Brno, CzechiaCentre of the Region Haná for Biotechnological and Agricultural Research, Czech Advanced Technology and Research Institute, Palacký University, Olomouc, CzechiaDepartment for Sustainable Food Process, DiSTAS, Università Cattolica del Sacro Cuore, Piacenza, ItalyDepartment for Sustainable Food Process, DiSTAS, Università Cattolica del Sacro Cuore, Piacenza, ItalyDepartment of Agricultural Sciences, University of Naples Federico II, Portici, ItalyDepartment of Agriculture and Forest Sciences, University of Tuscia, Viterbo, ItalyDepartment for Sustainable Food Process, DiSTAS, Università Cattolica del Sacro Cuore, Piacenza, ItalyCentre of the Region Haná for Biotechnological and Agricultural Research, Czech Advanced Technology and Research Institute, Palacký University, Olomouc, CzechiaPlant phenomics is becoming a common tool employed to characterize the mode of action of biostimulants. A combination of this technique with other omics such as metabolomics can offer a deeper understanding of a biostimulant effect in planta. However, the most challenging part then is the data analysis and the interpretation of the omics datasets. In this work, we present an example of how different tools, based on multivariate statistical analysis, can help to simplify the omics data and extract the relevant information. We demonstrate this by studying the effect of protein hydrolysate (PH)-based biostimulants derived from different natural sources in lettuce and tomato plants grown in controlled conditions and under salinity. The biostimulants induced different phenotypic and metabolomic responses in both crops. In general, they improved growth and photosynthesis performance under control and salt stress conditions, with better performance in lettuce. To identify the most significant traits for each treatment, a random forest classifier was used. Using this approach, we found out that, in lettuce, biomass-related parameters were the most relevant traits to evaluate the biostimulant mode of action, with a better response mainly connected to plant hormone regulation. However, in tomatoes, the relevant traits were related to chlorophyll fluorescence parameters in combination with certain antistress metabolites that benefit the electron transport chain, such as 4-hydroxycoumarin and vitamin K1 (phylloquinone). Altogether, we show that to go further in the understanding of the use of biostimulants as plant growth promotors and/or stress alleviators, it is highly beneficial to integrate more advanced statistical tools to deal with the huge datasets obtained from the -omics to extract the relevant information.https://www.frontiersin.org/articles/10.3389/fpls.2021.808711/fullvegetal-based protein hydrolysatesmultivariate statistical analysismetabolomicssecondary metabolismsalt stressLactuca sativa L. |
| spellingShingle | Mirella Sorrentino Mirella Sorrentino Klára Panzarová Ioannis Spyroglou Lukáš Spíchal Valentina Buffagni Paola Ganugi Youssef Rouphael Giuseppe Colla Luigi Lucini Nuria De Diego Integration of Phenomics and Metabolomics Datasets Reveals Different Mode of Action of Biostimulants Based on Protein Hydrolysates in Lactuca sativa L. and Solanum lycopersicum L. Under Salinity Frontiers in Plant Science vegetal-based protein hydrolysates multivariate statistical analysis metabolomics secondary metabolism salt stress Lactuca sativa L. |
| title | Integration of Phenomics and Metabolomics Datasets Reveals Different Mode of Action of Biostimulants Based on Protein Hydrolysates in Lactuca sativa L. and Solanum lycopersicum L. Under Salinity |
| title_full | Integration of Phenomics and Metabolomics Datasets Reveals Different Mode of Action of Biostimulants Based on Protein Hydrolysates in Lactuca sativa L. and Solanum lycopersicum L. Under Salinity |
| title_fullStr | Integration of Phenomics and Metabolomics Datasets Reveals Different Mode of Action of Biostimulants Based on Protein Hydrolysates in Lactuca sativa L. and Solanum lycopersicum L. Under Salinity |
| title_full_unstemmed | Integration of Phenomics and Metabolomics Datasets Reveals Different Mode of Action of Biostimulants Based on Protein Hydrolysates in Lactuca sativa L. and Solanum lycopersicum L. Under Salinity |
| title_short | Integration of Phenomics and Metabolomics Datasets Reveals Different Mode of Action of Biostimulants Based on Protein Hydrolysates in Lactuca sativa L. and Solanum lycopersicum L. Under Salinity |
| title_sort | integration of phenomics and metabolomics datasets reveals different mode of action of biostimulants based on protein hydrolysates in lactuca sativa l and solanum lycopersicum l under salinity |
| topic | vegetal-based protein hydrolysates multivariate statistical analysis metabolomics secondary metabolism salt stress Lactuca sativa L. |
| url | https://www.frontiersin.org/articles/10.3389/fpls.2021.808711/full |
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