Biology subjects

Passeport, E.

Publications and source records attributed to Passeport, E..

3 recordsLinked to original sources

bioRxiv2025

Dehalobacter converts 2,3-dichloroaniline to aniline via 2-chloroaniline in a methanogenic enrichment culture

12,3-dichloroaniline (2,3-DCA) has widespread use in chemical manufacturing and remains a persistent groundwater contaminant. To better understand the pathway and kinetics of its reductive dechlorination, we conducted a laboratory kinetic experiment using an anaerobic enrichment culture dominated by Dehalobacter. At an initial field-relevant concentration of 40 mg/L, complete and stoichiometric dechlorination of 2,3-DCA to aniline via 2-CA was achieved. The intermediates, 2-chloroaniline (2-CA) and 3-chloroaniline, were transiently formed in a ratio of 8:1. The growth yields of Dehalobacter on 2,3-DCA and 2-CA were 1.2 {+/-} 0.1 x 108 and 1.3 {+/-} 0.1 x 108 16S rRNA gene copies/mol chloride, respectively. The maximum specific growth rate for 2,3-DCA, max, was 0.18 {+/-} 0.03 day-{superscript 1} with a half-saturation constant, Ks, at 45 {+/-} 16 mg /L. The first-order decay constant for Dehalobacter when starved of chlorinated electron acceptors was estimated at 0.017 {+/-} 0.001 day-{superscript 1}. Lactate fermentation, acetogenesis from ethanol, syntrophic propionate oxidation, and hydrogenotrophic methanogenesis were observed during dechlorination. This work provides insights into the organohalide respiration of 2,3-DCA to aniline and advances the understanding of microbial interactions during anaerobic dechlorination. These results offer guidance for developing stable dechlorinating microbial ecosystems and key kinetic parameters for predictive modeling of groundwater 2,3-DCA fate and transport. 3 SynopsisThis study demonstrated stoichiometric dechlorination of 2,3-dichloroaniline to aniline, characterized syntrophic interactions in a mixed anaerobic dechlorinating culture, and determined growth yield, first-order decay and Monod constants for Dehalobacter. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/639126v3_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@5d59c4org.highwire.dtl.DTLVardef@b05a3aorg.highwire.dtl.DTLVardef@1f39f6borg.highwire.dtl.DTLVardef@1676753_HPS_FORMAT_FIGEXP M_FIG C_FIG Created in BioRender. Wang, S. (2025) https://BioRender.com/f47t993

microbiology↗

bioRxiv2021

Efficient prediction of microplastic counts from mass measurements

Microplastics must be characterized and quantified to assess their impact. Current quantification procedures are time-consuming and prone to human error. This study evaluates the use of machine learning to estimate the number of microplastic particles based on aggregate particle weight measurements. Synthetic datasets are used to test the performance of linear regression, kernel ridge regression and decision trees. Kernel ridge regression achieves the strongest performance, and it is also tested with experimental datasets. The numerical results show that the algorithm is better at predicting the counts of larger and more homogeneous samples, and that contamination by organics does not significantly increase error. In mixed samples, prediction error is lower for heavier particles, with an error rate comparable to or better than that of manual counting. Overall, the proposed method is faster and easier than current approaches.

ecology↗

bioRxiv2019

Resilience to multiple stressors in an aquatic plant and its microbiome

PremiseEnvironments are changing rapidly, and outcomes of species interactions, especially mutualisms, are notoriously dependent on the environment. A growing number of studies have investigated responses of mutualisms to anthropogenic changes, yet most studies have focused on nutrient pollution or climate change, and tested single stressors. Relatively little is known about impacts of simultaneous chemical contaminants, which may differ fundamentally from nutrient or climate stressors, and are especially widespread in aquatic habitats.\n\nMethodsWe investigated the impacts of two common contaminants on interactions between the common duckweed Lemna minor and its microbiome. Sodium chloride (salt) and benzotriazole (a corrosion inhibitor) negatively affect aquatic organisms individually, yet commonly co-occur in runoff to duckweed-inhabited sites. We tested three L. minor genotypes with and without the culturable portion of their microbiome across field realistic gradients of salt (3 levels) and benzotriazole (4 levels) in a fully factorial experiment (72 treatments), and measured plant and microbial growth.\n\nKey ResultsWe found that stressors had conditional effects. Salt decreased both plant and microbial growth, but decreased plant survival more as benzotriazole concentrations increased. In contrast, benzotriazole did not affect microbial abundance, and benefited plants when salt and microbes were absent, perhaps due to the biotrans-formation we observed without salt. Microbes did not ameliorate duckweed stressors, as microbial inoculation increased plant growth, but not at high salt concentrations.\n\nConclusionsOur results suggest that multistressor effects matter when predicting responses of mutualisms to global change, but that mutualisms may not buffer organisms from stressors.

plant biology↗