Comparative secretome of white‐rot fungi reveals co‐regulated carbohydrate‐active enzymes associated with selective ligninolysis of ramie stalks

Abstract

In the present research, Phanerochaete chrysosporium and Irpex Lacteus simultaneously degraded lignin and cellulose in ramie stalks, whereas Pleurotus ostreatus and Pleurotus eryngii could depolymerize lignin but little cellulose. Comparative proteomic analysis of these four white-rot fungi was used to investigate the molecular mechanism of this selective ligninolysis. 292 proteins, including CAZymes, sugar transporters, cytochrome P450, proteases, phosphatases and proteins with other function, were successfully identified. A total of 58 CAZyme proteins were differentially expressed, and at the same time, oxidoreductases participated in lignin degradation were expressed at higher levels in P. eryngii and P. ostreatus. Enzyme activity results indicated that cellulase activities were higher in P. chrysosporium and I. lacteus, while the activities of lignin-degrading enzymes were higher in P. eryngii and P. ostreatus. In addition to the lignocellulosic degrading enzymes, several proteins including sugar transporters, cytochrome P450 monooxygenases, peptidases, proteinases, phosphatases and kinases were also found to be differentially expressed among these four species of white-rot fungi. In summary, the protein expression patterns of P. eryngii and P. ostreatus exhibit co-upregulated oxidoreductase potential and co-downregulated cellulolytic capability relative to those of P. chrysosporium and I. lacteus, providing a mechanism consistent with selective ligninolysis by P. eryngii and P. ostreatus.

Systems biology-guided understanding of white-rot fungi for biotechnological applications: A review

“…Due to challenges in protein separation, this approach only identified dozens of proteins per sample ( Abbas et al., 2005 ; Ravalason et al., 2008 ; Salvachúa et al., 2013a ; Vasina et al., 2016 ; Xiao et al., 2017 , 2019 ; Zorn et al., 2005 ). The utilization of liquid chromatography-tandem mass spectrometry (LC-MS/MS) for shotgun or bottom-up proteomic studies – which aim to identify proteins from the overall pool of peptides in one sample – as well as the recent release of many WRF genomes, has increased the throughput of proteomic analyses and expanded the number of identified proteins to hundreds per sample ( del Cerro et al., 2021 ; Fernández-Fueyo et al., 2012 ; Fernández-Fueyo et al., 2016 ; Floudas et al., 2012 ; Miyauchi et al., 2020a ; Miyauchi et al., 2017 ; Xie et al., 2021 ). Other modern proteomic approaches include quantitative and top-down proteomics – which provide additional information on exact protein abundances and post-translational modifications, respectively ( Toby et al., 2016 ) – and will further expand the breadth of proteomic research in WRF ( Alfaro et al., 2014 ).…”

“…However, comparative analysis of a diversity of WRF secretomes within the same study is a powerful approach to avoid experimental and technical variability and establish direct correlations among organisms and/or cultivations conditions. For instance, Xie et al. (2021) showed a correlation between WRF species and lignocellulose degradation patterns and showed that two selective lignin-degrading WRF, P. ostreatus and Pleurotus eryngii , secrete higher abundances of ligninolytic and lower abundances of cellulolytic enzymes compared to P. chrysosporium and I. lacteus, WRF that simultaneously degrade lignocellulose, in ramie stalks-containing cultivations.…”

“…In this review, we therefore conducted an additional analysis to identify trends of secreted enzymes across different types of substrates and WRF. We collected 92 secretomic datasets from 31 publications and spanning 19 WRF species, all of which have published genomes ( Couturier et al., 2015 ; del Cerro et al., 2021 ; Fernández-Fueyo et al., 2012 ; Fernández-Fueyo et al., 2016 ; Floudas et al., 2012 ; Hori et al., 2014a ; Hori et al., 2014b ; Iwata et al., 2021 ; Kuuskeri et al., 2016 ; Levasseur et al., 2014 ; Liu et al., 2020 ; Machado et al., 2020 ; Mahajan and Master, 2010 ; Manavalan et al., 2011 ; Miyauchi et al., 2020a ; Miyauchi et al., 2017 ; Miyauchi et al., 2018 ; Moody et al., 2018 ; Peña et al., 2021 ; Presley et al., 2018 ; Ravalason et al., 2008 ; Rytioja et al., 2017 ; Salvachúa et al., 2016 ; Salvachúa et al., 2013a ; Vanden Wymelenberg et al., 2009 ; Vanden Wymelenberg et al., 2010 ; Vanden Wymelenberg et al., 2011 ; Xiao et al., 2019 ; Xie et al., 2021 ; Yoav et al., 2018 ; Zhu et al., 2016 ). Metadata for each dataset can be found in Table S3 , and detailed analytical pipelines can be found in Transparent Methods Supplemental File .…”

“…Some others use peptide spectral count as a proxy for relative quantitation ( Fernández-Fueyo et al., 2012 , 2016 ; Peña et al., 2021 ; Presley et al., 2018 ). Few studies adopted more accurate quantitation such as emPAI calculation or iTRAQ labeling ( Alfaro et al., 2014 ; Liu et al., 2020 ; Manavalan et al., 2011 ; Xie et al., 2021 ), whereas several others used only qualitative presence-absence values. Standardizing analytical approaches will be crucial for comparison across studies and meta-analyses.…”

Improving saccharification of ramie stalks by synergistic effect of in-house cellulolytic enzymes consortium

“…The phloem of ramie is accounted for only about 15% of its biomass, and the stalks reach to more than 60% (Meng et al 2018 ). Ramie stalks composed of 44% cellulose, 31% hemicellulose and 18.1% lignin, making it a suitable substrate for biofuel production (Xie et al 2021 ). However, the lignin content of native lignocellulosic biomass is highly resistant to cellulase degradation for cellulose, resulting in low cellulose conversion (Guo et al 2018 ).…”