Quantitative structure–activity relationships for primary aerobic biodegradation of organic chemicals in pristine surface waters: starting points for predicting biodegradation under acclimatization

Abstract

Microbial biomass and acclimation can affect the removal of organic chemicals in natural surface waters. In order to account for these effects and develop more robust models for biodegradation, we have compiled and curated removal data for un-acclimated (pristine) surface waters on which we developed quantitative structure-activity relationships (QSARs). Global analysis of the very heterogeneous dataset including neutral, anionic, cationic and zwitterionic chemicals (N = 233) using a random forest algorithm showed that useful predictions were possible (Q = 0.4-0.5) though relatively large standard errors were associated (SDEP ∼0.7). Classification of the chemicals based on speciation state and metabolic pathway showed that biodegradation is influenced by the two, and that the dependence of biodegradation on chemical characteristics is non-linear. Class-specific QSAR analysis indicated that shape and charge distribution determine the biodegradation of neutral chemicals (R ∼ 0.6), e.g. through membrane permeation or binding to P450 enzymes, whereas the average biodegradation of charged chemicals is 1 to 2 orders of magnitude lower, for which degradation depends more directly on cellular uptake (R ∼ 0.6). Further analysis showed that specific chemical classes such as peptides and organic halogens are relatively less biodegradable in pristine surface waters, resulting in the need for the microbial consortia to acclimate. Additional literature data was used to verify an acclimation model (based on Monod-type kinetics) capable of extrapolating QSAR predictions to acclimating conditions such as in water treatment, downstream lakes and large rivers under μg L to mg L concentrations. The framework developed, despite being based on multiple assumptions, is promising and needs further validation using experimentation with more standardised and homogenised conditions as well as adequate characterization of the inoculum used.

Effect of concentration and hydraulic reaction time on the removal of pharmaceutical compounds in a membrane bioreactor inoculated with activated sludge

“…In summary, we did not find any effect of concentration on pharmaceutical removal percentage under the conditions tested in our membrane bioreactor. These results are in contradiction to other studies reporting a correlation between influent concentration and removal percentage of some OMPs in WWTPs(Nolte et al, 2018;Onesios-Barry et al, 2014;Wang et al, 2020).Onesios-Barry et al reported a negative correlation between concentration and removal for pharmaceuticals such as fluorouracil in laboratory columns inoculated with wastewater effluent. The lower removal values at higher concentrations might be related to toxicity.…”

“…diclofenac, metoprolol). The removal differences between compounds is partially governed by the chemical structure's properties (Nolte et al, 2020;Nolte et al, 2018). For example, charged compounds are less biodegradable than neutral compounds probably due to a cellular uptake limitation Nolte et al, 2018).…”

“…The removal differences between compounds is partially governed by the chemical structure's properties (Nolte et al, 2020;Nolte et al, 2018). For example, charged compounds are less biodegradable than neutral compounds probably due to a cellular uptake limitation Nolte et al, 2018). In addition to chemical properties, the higher the concentration of pharmaceuticals and other OMPs in the influent of WWTPs, the more these compounds seem to be removed (Nolte et al, 2018;Wang et al, 2020).…”

“…For example, charged compounds are less biodegradable than neutral compounds probably due to a cellular uptake limitation Nolte et al, 2018). In addition to chemical properties, the higher the concentration of pharmaceuticals and other OMPs in the influent of WWTPs, the more these compounds seem to be removed (Nolte et al, 2018;Wang et al, 2020). The same compound can also have different removal rates/efficiencies in different WWTPs which may depend on the operational parameters and the active microbial community present (Kassotaki et al, 2018;Lautz et al, 2017;Wang et al, 2020).…”

Gene Editing and Systems Biology Tools for Pesticide Bioremediation: A Review

“…The execution of computational tools and bioinformatics resources is an advanced approach toward the pesticide bioremediation (Malla et al, 2018; Vanacek et al, 2018). It takes the online platform of biodegradative databases publicly accessed for retrieving information on biodegradation of xenobiotic (pesticide) by microorganisms and biodegradation pathways of persistent chemicals (Nolte et al, 2018). These databases comprise the University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD), Biodegradation Network-Molecular Biology database (Bionemo), Pesticide Target interaction database (PTID), Microbial Genome Database (MBGD), Biodegradative Oxygenases Database (OxDBase), BioCyc and MetaCyc compatible with both windows as well as Linux operating systems (Arora and Bae, 2014).…”