Inflorescences vs leaves: a distinct modulation of carbon metabolism process during Botrytis infection

Abstract

Plant growth and survival depends critically on photo assimilates. Pathogen infection leads to changes in carbohydrate metabolism of plants. In this study, we monitored changes in the carbohydrate metabolism in the grapevine inflorescence and leaves using Botrytis cinerea and Botrytis pseudo cinerea. Fluctuations in gas exchange were correlated with variations in chlorophyll a fluorescence. During infection, the inflorescences showed an increase in net photosynthesis (Pn) with a stomatal limitation. In leaves, photosynthesis decreased, with a non-stomatal limitation. A decrease in the effective photosystem II (PSII) quantum yield (ΦPSII) was accompanied by an increase in photochemical quenching (qP) and non-photochemical quenching (qN). The enhancement of qP and ΦPSII could explain the observed increase in Pn. In leaves, the significant decline in ΦPSII and qP, and increase in qN suggest that energy was mostly oriented toward heat dissipation instead of CO2 fixation. The accumulation of glucose and sucrose in inflorescences and glucose and fructose in the leaves during infection indicate that the plant's carbon metabolism is differently regulated in these two organs. While a strong accumulation of starch was observed at 24 and 48 hours post-inoculation (hpi) with both species of Botrytis in the inflorescences, a significant decrease with B. cinerea at 24 hpi and a significant increase with B. pseudo cinerea at 48 hpi were observed in the leaves. On the basis of these results, it can be said that during pathogen attack, the metabolism of grapevine inflorescence and leaf is modified suggesting distinct mechanisms modifying gas exchange, PSII activity and sugar contents in these two organs.

Genetic and molecular landscapes of the generalist phytopathogen Botrytis cinerea

“…These large collections of studies provide the ability to conduct a meta‐analysis of the factors influencing B. cinerea's extensive genetic diversity. To summarize findings of these studies, we performed a meta‐analysis by compiling the publicly available data for >10,000 strains across 58 publications (Abdel Wahab, 2015; Acosta Morel et al., 2018; Albertini & Leroux, 2004; Albertini et al., 2002; Aliaga, 2013; Amiri et al., 2018; Asadollahi et al., 2013; Beever & Parkes, 1993; Ben Ahmed & Hamada, 2005; Campia, 2014; Cettul et al., 2008; Ciliberti et al., 2016; DeLong et al., 2020; Diao et al., 2019; Emilda, 2015; Esterio et al., 2011; Fan et al., 2015; Fekete et al., 2012; Fournier et al., 2005, 2013; Giraud et al., 1997; Giraud et al., 1999; Hu et al., 2018; Isenegger et al., 2008; Johnston et al., 2013; Kecskeméti et al., 2014; Kumari et al., 2014; Kuzmanovska et al., 2012; Leyronas et al., 2014; Lorenzini & Zapparoli, 2014; Ma & Michailides, 2005; Makris et al., 2022; Martinez et al., 2003; Mercier et al., 2019; Moparthi et al., 2023; Muñoz & Campos, 2013; Muñoz et al., 2002, 2016; Naegele et al., 2021; Pei et al., 2019; Polat et al., 2018; Rajaguru & Shaw, 2010; Román Ramos, 2013; Tanović et al., 2009, 2014; Testempasis et al., 2020; Toffolatti et al., 2020; Topolovec‐Pintarić et al., 2004; Törün & Biyik, 2022; Vaczy et al., 2008; Vatsa‐Portugal et al., 2014; Vercesi et al., 2014…”