Biodegradation of persistent micropollutants like pesticides often slows down at low concentrations (μg/L) in the environment. Mass transfer limitations or physiological adaptation are debated to be responsible. Although promising, evidence from compound-specific isotope fractionation analysis (CSIA) remains unexplored for bacteria adapted to this low concentration regime. We accomplished CSIA for degradation of a persistent pesticide, atrazine, during cultivation of Arthrobacter aurescens TC1 in chemostat under four different dilution rates leading to 82, 62, 45, and 32 μg/L residual atrazine concentrations. Isotope analysis of atrazine in chemostat experiments with whole cells revealed a drastic decrease in isotope fractionation with declining residual substrate concentration from ε(C) = −5.36 ± 0.20‰ at 82 μg/L to ε(C) = −2.32 ± 0.28‰ at 32 μg/L. At 82 μg/L ε(C) represented the full isotope effect of the enzyme reaction. At lower residual concentrations smaller ε(C) indicated that this isotope effect was masked indicating that mass transfer across the cell membrane became rate-limiting. This onset of mass transfer limitation appeared in a narrow concentration range corresponding to about 0.7 μM assimilable carbon. Concomitant changes in cell morphology highlight the opportunity to study the role of this onset of mass transfer limitation on the physiological level in cells adapted to low concentrations.

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Most contaminants of emerging concern are polar and/or ionizable organic compounds, whose removal from engineered and environmental systems is difficult. Carbonaceous sorbents include activated carbon, biochar, fullerenes, and carbon nanotubes, with applications such as drinking water filtration, wastewater treatment, and contaminant remediation. Tools for predicting sorption of many emerging contaminants to these sorbents are lacking because existing models were developed for neutral compounds. A method to select the appropriate sorbent for a given contaminant based on the ability to predict sorption is required by researchers and practitioners alike. Here, we present a widely applicable deep learning neural network approach that excellently predicted the conventionally used Freundlich isotherm fitting parameters log K F and n (R 2 > 0.98 for log K F , and R 2 > 0.91 for n). The neural network models are based on parameters generally available for carbonaceous sorbents and/or parameters freely available from online databases. A freely accessible graphical user interface is provided.

Biodegradation of persistent pesticides like atrazine often stalls at low concentrations in the environment. While mass transfer does not limit atrazine degradation by the Gram-positive Arthrobacter aurescens TC1 at high concentrations (>1 mg/L), evidence of bioavailability limitations is emerging at trace concentrations (<0.1 mg/L). To assess the bioavailability constraints on biodegradation, the roles of cell wall physiology and transporters remain imperfectly understood. Here, compound-specific isotope analysis (CSIA) demonstrates that cell wall physiology (i.e., the difference between Gram-negative and Gram-positive bacteria) imposes mass transfer limitations in atrazine biodegradation even at high concentrations. Atrazine biodegradation by Gram-negative Polaromonas sp. Nea-C caused significantly less isotope fractionation (ε(C) = -3.5 ‰) than expected for hydrolysis by the enzyme TrzN (ε(C) = -5.0 ‰) and observed in Gram-positive Arthrobacter aurescens TC1 (ε(C) = -5.4 ‰). Isotope fractionation was recovered in cell-free extracts (ε(C) = -5.3 ‰) where no cell envelope restricted pollutant uptake. When active transport was inhibited with cyanide, atrazine degradation rates remained constant demonstrating that atrazine mass transfer across the cell envelope does not depend on active transport but is a consequence of passive cell wall permeation. Taken together, our results identify the cell envelope of the Gram-negative bacterium Polaromonas sp. Nea-C as a relevant barrier for atrazine biodegradation.