RESUMO
Temperature is a key factor influencing microbial growth rates and yields. In literature, the influence of temperature on growth is studied either on yields or rates but not both at the same time. Moreover, studies often report the influence of a specific set of temperatures using rich culture media containing complex ingredients (such as yeast extract) which chemical composition cannot be precisely specified. Here, we present a complete dataset for the growth of Escherichia coli K12 NCM3722 strain in a minimal medium containing glucose as the sole energy and carbon source for the computation of growth yields and rates at each temperature from 27 to 45°C. For this purpose, we monitored the growth of E. coli by automated optical density (OD) measurements in a thermostated microplate reader. At each temperature full OD curves were reported for 28 to 40 microbial cultures growing in parallel wells. Additionally, a correlation was established between OD values and the dry mass of E. coli cultures. For that, 21 dilutions were prepared from triplicate cultures and optical density was measured in parallel with the microplate reader (ODmicroplate) and a UV-Vis spectrophotometer (ODUV-vis) and correlated to duplicate dry biomass measurements. The correlation was used to compute growth yields in terms of dry biomass.
RESUMO
Recent efforts have focused on providing a systematic analysis of syntrophic microbial growth yields. These biokinetic parameters are key to developing an accurate mathematical description of the anaerobic digestion process. The agreement between experimentally determined growth yields and those obtained from bioenergetic estimations is therefore of great interest. Considering five important syntrophic groups, including acetoclastic and hydrogenotrophic methanogens, as well as propionate, butyrate and lactate oxidizers, previous findings suggest that measured and estimated growth yields were consistent only for acetoclastic methanogens. A re-analysis revealed that data are also consistent for lactate oxidizers and hydrogenotrophic methanogens, whereas the limited data available for propionate and butyrate oxidizers are unsupportive of firm conclusions. These results highlight pertinent challenges in the analysis of microbial syntrophy and encourage more accurate measurements of syntrophic microbial growth yields in the future.
Assuntos
Euryarchaeota , Metano , Anaerobiose , Reatores Biológicos , Metabolismo Energético , ÁguaRESUMO
A compilation and analysis of experimentally determined microbial growth yields for syntrophic volatile fatty acid (VFA), lactate oxidisers and methanogens in anaerobic digestion (AD) systems is presented. Only studies based on experimental determinations or sound model-to-data fitting that specifically address parameter identifiability, have been considered. The experimentally determined values are compared and discussed with estimations based on bioenergetic correlations. Only for acetoclastic methanogens the experimentally determined microbial yields appear in good consistency with bioenergetic estimations. For syntrophic microbial groups, the experimetal yield values reported appear much higher than those expected from the low amount of metabolic energy available. These large deviations imply either inaccuracy on the microbial biomass quantification methods or that the syntrophic interspecies electron transfer occurs under mechanisms, or hydrogen equivalent intermediate activities, much below those ever observed in methanogenic environments. In addition, the microbial growth yield values most widely adopted in AD model applications (those reported in the IWA Anaerobic Digestion Model No. 1 (ADM1)) are even higher than the experimental determinations from literature. It is therefore proposed that microbial growth yield values should be restricted by the maximum harvestable ATP calculated through a detailed bioenergetic pathway analysis. Model simulations with different parameter configurations for different yield sources (default ADM1, experimentally determined and bioenergetically estimated values) displayed low sensitivity of the simulations with respect to the yield values as long as the maximum specific microbial growth rate (µmax) remain the same. This suggests that model calibrations could target the accuracy of µmax maintaining the bioenergetic upper limit for microbial growth yields.