Fungal Lignocellulose Utilisation Strategies from a Bioenergetic Perspective: Quantification of Related Functional Traits Using Biocalorimetry

Abstract

In the present study, we investigated whether a non-invasive metabolic heat flux analysis could serve the determination of the functional traits in free-living saprotrophic decomposer fungi and aid the prediction of fungal influences on ecosystem processes. For this, seven fungi, including ascomycete, basidiomycete, and zygomycete species, were investigated in a standardised laboratory environment, employing wheat straw as a globally relevant lignocellulosic substrate. Our study demonstrates that biocalorimetry can be employed successfully to determine growth-related fungal activity parameters, such as apparent maximum growth rates (AMGR), cultivation times until the observable onset of fungal growth at AMGR (tAMGR), quotients formed from the AMGR and tAMGR (herein referred to as competitive growth potential, CGP), and heat yield coefficients (YQ/X), the latter indicating the degree of resource investment into fungal biomass versus other functional attributes. These parameters seem suitable to link fungal potentials for biomass production to corresponding ecological strategies employed during resource utilisation, and therefore may be considered as fungal life history traits. A close connection exists between the CGP and YQ/X values, which suggests an interpretation that relates to fungal life history strategies.

Biocalorimetry-aided monitoring of fungal pretreatment of lignocellulosic agricultural residues

“…Calorimetry is a smart tool to track fungal activity as it provides real-time metabolic information, does not affect growth and product formation processes, and can serve for the delivery of thermodynamic state variables for fungal activity prediction (Duong et al 2022b ). Previous studies have already established biocalorimetry for process monitoring in order to identify unexpected metabolic events (Maskow and Kleinsteuber 2004 ), to record metabolic shifts (Duboc et al 1998 ; Maskow and Babel 1998 ), to control the conversion of toxic substrates into valuable products such as biopolyesters, or to protect compounds in fed-batch or a continuous manner (Maskow and Babel 2001 ; Maskow et al 2006 ; Rohde et al 2016 ).…”

“…Previous studies have already established biocalorimetry for process monitoring in order to identify unexpected metabolic events (Maskow and Kleinsteuber 2004 ), to record metabolic shifts (Duboc et al 1998 ; Maskow and Babel 1998 ), to control the conversion of toxic substrates into valuable products such as biopolyesters, or to protect compounds in fed-batch or a continuous manner (Maskow and Babel 2001 ; Maskow et al 2006 ; Rohde et al 2016 ). In previous studies we have applied the non-invasive measurement of metabolic heat fluxes to monitor fungal activity during the colonisation of wheat straw, which was used as a solid lignocellulosic agricultural residue of global relevance (Duong et al 2022a , b ). Fungal biomass yields observed during fungal growth on wheat straw were strongly correlated with the released metabolic heat, which enabled to determine a range of species-specific growth-related activity parameters being indicative of different fungal strategies employed during resource utilisation (Duong et al 2022b ).…”

“…In previous studies we have applied the non-invasive measurement of metabolic heat fluxes to monitor fungal activity during the colonisation of wheat straw, which was used as a solid lignocellulosic agricultural residue of global relevance (Duong et al 2022a , b ). Fungal biomass yields observed during fungal growth on wheat straw were strongly correlated with the released metabolic heat, which enabled to determine a range of species-specific growth-related activity parameters being indicative of different fungal strategies employed during resource utilisation (Duong et al 2022b ). For example, one of these parameters (the metabolic heat yield coefficient Y Q / X , i.e.…”

“…For example, one of these parameters (the metabolic heat yield coefficient Y Q / X , i.e. the metabolic heat released per increase of fungal biomass unit) can be considered an indicator for the degree of resource investment into fungal biomass vs. other functional attributes such as extracellular enzymes contributing to lignocellulose decomposition (Duong et al 2022b ).…”

Special Issue “Advances in Monitoring Metabolic Activities of Microorganisms by Calorimetry”

“…Finally, Doung et al demonstrate that IMC enables much less error-prone determination of energy utilization patterns of fungi than biomass- and substrate-based estimations [ 11 ]. By studying seven fungi with different substrate requirements, the authors show that ecologically relevant “trait-complexes” can be built on metabolic heat curves to predict ecological performance and biomass production by these saprotrophic lignocellulose decomposer fungi.…”