Transcriptome and proteome analyses reveal the regulatory networks and metabolite biosynthesis pathways during the development of Tolypocladium guangdongense

Abstract

Graphical abstract Workflows of transcriptome and proteome analyses across the differentially developmental stages of C. guangdongensis . My, Mycelial stages; P, Primordial stage; YFB, Young fruiting body stage; DFB, Developed fruiting body stage; MFB, Mature fruiting body stage.

Biosynthetic Pathway and the Potential Role of Melatonin at Different Abiotic Stressors and Developmental Stages in Tolypocladium guangdongense

“…These results indicate that T. guangdongense has the potential as an important economic fungus and can be applied in the functional food and healthcare industries. In addition, in our recent study, tryptophan and tryptamine levels peaked at the primordial (P) stage (Wang et al, 2020a), and we detected melatonin and several intermediates when performing the metabolome analysis of T. guangdongense fruiting bodies (unpublished data), suggesting that the levels of melatonin and the associated intermediates notably differ during the growth and development process of T. guangdongense.…”

“…Mycelia cultured at 23°C for 4 days were subjected to 14 days 30°C or 14°C treatment as heat treatment (HT) and cold treatment (CT), respectively. In addition, the samples of mycelium (My), P, and young fruiting body (FB) were collected as described previously (Wang et al, 2020a). All the samples were immediately frozen in liquid nitrogen and then were preserved at −80°C until metabolite, and RNA isolation were performed.…”

“…The indolic compounds tryptophan, tryptamine, 5HTryp, NAT, serotonin, NAS, and 5MT were purchased from Sigma-Aldrich (Madrid, Spain) and Shanghai Yuanye Bio-Technology Co., Ltd (China). These indolic compounds were extracted using the method described in our previous study (Wang et al, 2020a). Briefly, sample tissues (0.5 g) from the CR and control (CK) groups was finely ground, followed by extraction in an 1 ml buffer containing 50% methanol and 0.1% formic acid for 15 min in a shaker.…”

Elucidating tumor-stromal metabolic crosstalk in colorectal cancer through integration of constraint-based models and LC-MS metabolomics

“…Metabolite pool size profiling alone may be insufficient for understanding the causes of metabolic alterations due to the intertwined structure of metabolic networks, as we have shown in Section 3.1 . While transcriptomics and proteomics data are commonly used to investigate drivers of metabolic/phenotypic differences ( Hahne et al, 2010 ; Wang et al, 2020a ; Suh et al, 2015 ; Nuber et al, 2021 ), the expression levels of genes encoding the metabolic enzymes do not fully represent their enzymatic activities. Our method serves to complement the tool box available for metabolism research by making direct use of data obtained at the metabolite level.…”

Elucidating Tumor-stromal Metabolic Crosstalk in Colorectal Cancer through Integration of Constraint-Based Models and LC-MS Metabolomics

“…Metabolite pool size profiling alone may be insufficient for understanding the causes of metabolic alterations due to the intertwined structure of metabolic networks, as we have shown in Section 2.1. While transcriptomics and proteomics data are commonly used to investigate drivers of metabolic/phenotypic differences [38, 39, 40, 41], the expression levels of genes encoding the metabolic enzymes do not fully represent their enzymatic activities. Our method serves to complement the tool box available for metabolism research by making direct use of data obtained at the metabolite level.…”