Modelling the sporulation dynamics of arbuscular mycorrhizal fungi in monoxenic culture

Abstract

Spore production of arbuscular mycorrhizal fungi is important in inoculum production, and monoxenic culture is a promising way to produce large amounts of contaminant-free inoculum. Mass production of spores is therefore essential and mathematical models useful as descriptive and predictive tools of sporulation dynamics. We followed the sporulation dynamics of three Glomus strains i.e. G. intraradices, G. proliferum and G. caledonium, cultured monoxenically on a nutrient agar medium containing macro-and microelements, vitamins and sucrose. Three models (Schnute, logistic, and Gompertz) were fitted to the data and compared in order to select the most adequate model. The Schnute model was the reference against which the two other models were tested. For all three Glomus strains examined, the sporulation dynamics followed a sigmoidal curve with a lag, a log, and a plateau phase. Visually, all three models fitted the data very well, with R 2 values ranging from 0.9703 to 0.9995. They thus appeared adequate for describing the temporal dynamics of spore production. In most cases the Gompertz model described sporulation as accurately as the Schnute model, but the performance of the logistic model was seldom as good. The Gompertz model is thus convenient for modelling the sporulation dynamics of Glomus strains grown in a well-defined nutrient agar medium. As such, its use may facilitate and help improve exploitation of monoxenic culture systems.

A new cheese population in Penicillium roqueforti and adaptation of the five populations to their ecological niche

“…In order to estimate growth latency and growth rate for each strain and parameter tested, we performed a primary modelling step with the MatLab software (R2018b, Natick, Massachusetts: The MathWorks Inc.; see Figure 2a). We fitted a growth curve to the measured values for each strain and tested parameter using the modified Gompertz Equation () (Zwietering et al, 1990), as it is the most robust for fungal growth modelling (Declerck et al, 2001; Savary et al, 2022). where y 0 is the value for time 0, y is the turbidity signal (in RNU) measured at time t , a is the maximal amplitude of the turbidity signal in RNU, μ m is the growth rate (RNU.h −1 ) in the exponential phase (hereafter called “maximal growth rate” as typically done in modelling growth studies) and λ is the lag time in hours (i.e., the time before fungal growth is detected).…”

“…In order to estimate growth latency and growth rate for each strain and parameter tested, we performed a primary modelling step with the MatLab software (R2018b, Natick, Massachusetts: The MathWorks Inc.; see Figure 2a). We fitted a growth curve to the measured values for each strain and tested parameter using the modified Gompertz Equation (1) (Zwietering et al, 1990), as it is the most robust for fungal growth modelling (Declerck et al, 2001;Savary et al, 2022).…”

Soil Microbial Assemblages Are Linked to Plant Community Composition and Contribute to Ecosystem Services on Urban Green Roofs

“…Numerous field and greenhouse experiments have shown the effects of mycorrhizal fungi on stomatal conductance, the rate at which CO 2 enters and water exits the leaf, with higher stomatal conductance in drought vs. well-watered conditions (Augé, 2001;Augé et al, 2015). While adverse abiotic conditions reduce AM fungal diversity compared to non-disturbed soil, some AM fungi exhibit opportunistic life history strategies including investing energy into spore production (Declerck et al, 2001) and, in the case of Rhizophagus irregularis, rapidly colonizing plant roots after disturbance (Sýkorová et al, 2007). In the green roof survey samples, the three most abundant OTUs in Glomeromycota aligned to Rhizophagus irregularis, which occurs in high relative abundance with Asteraceae plants (Wehner et al, 2014), and have previously been observed in green roof fungal communities in New York City (McGuire et al, 2013).…”

Arbuscular Mycorrhizal Fungi as Biostimulant and Biocontrol Agents: A Review

“…Furthermore, AMF from different clades can develop differently depending on favorable or unfavorable environmental conditions [222] by adopting completely divergent resource-use strategies (R or K strategies), also known as "Life History Strategies" (LHS) [223][224][225]. For example, AMF from the Glomeraceae family allocate resources to grow mainly inside roots, forming structures such as arbuscules, vesicles, hyphae [226], reproducing quickly [227] and sporulating abundantly [228]. De facto, Glomeraceae can develop even under an unstable environment (R strategies) [223].…”