Phenol-driven cometabolic degradation of cis-1,2-dichloroethene (cDCE): insights from Acinetobacter pittii and Ectopseudomonas alcaliphila

Desmaraisetal. Environmental Sciences Europe (2025) 37:196 https://doi.org/10.1186/s12302-025-01237-z RESEARCH Open Access © The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Environmental Sciences Europe Phenol-driven cometabolic degradation ofcis-1,2-dichloroethene (cDCE): insights fromAcinetobacter pittii andEctopseudomonas alcaliphila Miguel Desmarais1,7† , Serena Fraraccio1† , Jakub Ridl2 , Jachym Suman1 , Andre Perez‑Potti3,8 , Kenneth A. Dawson3 , Iva Dolinova4,5 , Lenka McGachy6 , Miluse Hradilova2 , Alena Sevcu4 , Michal Strejcek1 and Ondrej Uhlik1* Abstract Accumulation of xenobiotic chlorinated ethenes (CEs) at legacy industrial soil and groundwater sites around the world is a pressing environmental and public health issue. Understanding the biochemical pathways through which microorganisms degrade cDCE is key to developing cost‑effective, sustainable bioremediation strate‑ gies for CE contamination. Two strains, Acinetobacter pittii CEP14 and Ectopseudomonas alcaliphila JAB1, isolated from contaminated industrial sites, have demonstrated the ability to cometabolically degrade cDCE in the presence of phenol. In this study, we integrate transcriptomics, using differential gene expression analysis to pinpoint genes induced during cDCE co‐metabolism, with proteomics to confirm protein‐level expression. We use heterologous expression experiments to demonstrate that phenol monooxygenase is responsible for oxidising cDCE in both strains. Furthermore, we show that CEP14 and JAB1 α‑subunits share 71.4% identity with each other but only 14.6–26.5% identity with established monooxygenases with known cDCE‑oxidising activity, highlighting the diversity of enzymes that may be capable of cometabolic cDCE degradation. Finally, we hypothesise on a two‑branch phenol monooxy‑ genase‑mediated cDCE degradation pathway in which the chemical degradative intermediates 2,2‑dichloroacetalde‑ hyde and cDCE epoxides are formed. This study sheds light on the biochemical mechanisms by which monoaromatic compounds can enhance the biodegradation of cDCE and demonstrates the potential utilisation of strains CEP14 and JAB1 for the biodegradation of cDCE. Keywords Phenol monooxygenase, Cometabolic degradation, Cis‑1,2‑dichloroethene (cDCE), Chlorinated ethenes, Transcriptomics, Heterologous gene expression †Miguel Desmarais and Serena Fraraccio have contributed equally to this work. *Correspondence: Ondrej Uhlik [email protected] Full list of author information is available at the end of the article Page 2 of 15 Desmaraisetal. Environmental Sciences Europe (2025) 37:196 Background Accumulation of xenobiotic chlorinated ethenes (CEs) at legacy industrial soil and groundwater sites around the world is a pressing environmental and public health challenge [32]. In the 1900s, perchloroethene (PCE) and trichloroethene (TCE), known as the higher CEs (HCEs), were heavily used for industrial applications [12]. Due to improper handling and disposal, HCEs and their biodegradation products, the lower CEs (LCEs) dichloroethene (DCE) and vinyl chloride (VC), have become prevalent soil and groundwater contaminants globally [13]. HCEs are readily biodegraded to LCEs by fermenters, methanogens, and sulphate reducers in subsurface anoxic environments, whereas LCEs are mineralised under oxic conditions by aerobes [13, 22]. Few microorganisms have demonstrated the ability to oxidise DCE and VC, which leads to the accumulation of these toxic byproducts at CE-contaminated sites worldwide [10, 14, 16, 43]. More importantly, the chemical degradative intermediate cDCE, a nephroand neuro-toxic compound, is often found in greater concentration than its trans isomer (tDCE) in drinking water supplies (groundwater), causing potential health problems in nearby communities [48]. cDCE commonly co‐occurs with phenolic pollutants at industrial sites (e.g. petrochemical and pulp and paper facilities), where phenol concentrations can reach tens to hundreds of µM [1, 27]. Given that many aerobic bacteria use phenol as a growth substrate, phenol‐driven co‐metabolism represents a promising route to degrade cDCE under mixed‐contaminant conditions. However, the specific enzymes and pathways by which phenol might induce cDCE cometabolism remain unknown, limiting the development of effective, environmentally friendly, and economy‐driven bioremediation strategies for these co‐contaminated environments [7]. Select microbial strains isolated from CE-contaminated sediments, soil, groundwater, and activated sludge have demonstrated the ability to degrade cDCE aerobically. These include Comamonas testosteroni RF2, Cupriavidus sp. CY-1 Methylosinus trichosporium OB3b, Polaromonas sp. JS666, Thauera butanivorans ATCC 43655, Pseudomonas stutzeri OX1, and Xanthobacter sp. Py2, to name a few [9, 10, 14, 16, 38, 43, 51]. These microbes degrade cDCE in a cometabolic manner. The fortuitous oxidation of cDCE depends on the biochemical pathway that utilises other, so-called primary substrates. Methane, toluene, phenol, and natural monoaromatic secondary plant metabolites can serve as primary growth substrates, stimulating cDCE degradation [9, 11, 17, 36]. In addition, microcosm studies have demonstrated the potential for aerobic cometabolic degradation of cDCE using TCE as the primary growth substrate [47]. Recent studies have investigated the biochemical pathways by which the aerobic cometabolic degradation of cDCE occurs. A twobranch monooxygenase-mediated degradation pathway has been proposed in which cDCE is initially oxidised to the chemical degradative intermediates 2,2-dichloroacetaldehyde (DCA) and cDCE epoxide by a monooxygenase (Fig.1) [10, 17, 19, 33, 36]. These chemical intermediates are transformed to glyoxylate by a series of enzymatic Fig. 1 Proposed cDCE degradation pathway in CEP14 and JAB1, including experimentally confirmed and hypothetical reactions, enzymes and chemical intermediates involved. GSH glutathione, NAD + nicotinamide adenine dinucleotide, oxidised form, NAD(P)H nicotinamide adenine dinucleotide (phosphate), reduced Page 3 of 15 Desmaraisetal. Environmental Sciences Europe (2025) 37:196 reactions involving aldehyde dehydrogenases, haloacid dehalogenases (HAD), glutathione S-transferases (GST), and epoxide hydrolases, and ultimately fed into the glyoxylate cycle pathway. Two strains, Acinetobacter pittii CEP14 and Ectopseudomonas alcaliphila JAB1 (formerly Pseudomonas alcaliphila JAB1 as reported by Ridl etal. [36], reclassified by Rudra and Gupta [37]), were isolated, respectively, from groundwater at the Spolchemie chemical factory in Ústí nad Labem and legacy-contaminated soil in Jablonné nad Orlicí—both industrial sites heavily contaminated by chlorinated organic pollutants. They have demonstrated the ability to degrade cDCE in the presence of phenol cometabolically; however, the biochemical pathway by which this occurs remains unknown [11, 36]. In this study, we integrate transcriptomics, using differential gene expression analysis to pinpoint genes induced during cDCE co‐metabolism, with proteomics to confirm protein‐level expression. We use heterologous expression experiments to demonstrate that phenol monooxygenase is responsible for oxidising cDCE in both strains. Finally, we hypothesise on a two-branch phenol monooxygenasemediated cDCE degradation pathway in which the chemical degradative intermediates 2,2-dichloroacetaldehyde and cDCE epoxides are formed. Methods Experimental design The experimental design consisted of four treatments: CEP14 and JAB1 cultures were grown in triplicates in minimal salts medium (MSM: NaNO3 2.0g l−1, K2HPO4 0.5g l−1, MgSO4·7H2O 0.2g l−1, MnSO4·5H2O 0.02g l−1, FeSO4·7H2O 0.02g l−1, CaCl2 0.02g l−1) with either phenol (15µmol l−1) or sodium pyruvate (15µmol l−1) as the primary growth substrate, and with or without cDCE (15µmol l−1) as the secondary substrate (Supplementary Information Table1; culture conditions: Desmarais etal. [11], Ridl et al. [36]). A sodium azide-inactivated cell culture was included as a negative control. This design aimed to identify changes in gene expression unique to the degradation of cDCE, rather than the utilisation of the primary growth substrates. Functional annotation andcomparative genomics The complete CEP14 and JAB1 genomes, along with their functional annotations, were retrieved from the GenBank (National Institute of Health). Proteomes were generated and sequences were further annotated using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the KofamKOALA web tool for KEGG ortholog assignment [4, 23, 42]. Gene and protein sequence similarity were calculated, and sequences were screened using the National Center for Biotechnology Information (NCBI) BlastN and BlastP web tools as well as the Nucleotide Collection (nr/nt) and UniProtKB/Swiss-Prot proteins database [6]. Multiple protein sequence alignments were generated using Clustal Omega using the seeded guide trees and HMM profile–profile techniques on the EMBL-EBI web server [39]. Protein functions were inferred using the InterProScan web tool to obtain protein signatures, predict domains, and classify proteins into families [21]. Transcriptomics anddifferential gene expression analysis Samples for transcriptomic analyses were taken during the period of maximal cDCE depletion, when the expression of catabolic genes involved in cDCE degradation is theoretically at its highest (CEP14: after 9h, JAB1: after 16h). Bacterial pellets were resuspended in a solution containing RNA Protect Reagent (Qiagen, Hilden, Germany) and treated with lysozyme (1mg ml−1). Cells were centrifuged and lysed in RLT buffer (Qiagen) containing beta-mercaptoethanol. RNA extractions were performed on RNeasy Mini spin columns following the manufacturer’s protocol (Qiagen), including on-column DNase I digestion. Isolated RNA was subjected to quantity and quality controls (Qubit RNA BR Assay and Agilent RNA 6000 Nano Kit, La Jolla, CA, USA) and sent to Genecore EMBL Heidelberg for NextSeq 75 cycles High Output sequencing. TruSeq sequencing adapters, indexed adapters, overrepresented sequences (poly-A and poly-G tails), short reads (< 50bp), and low-quality reads (Phred score < 20) were removed using Trimmomatic v0.36 [5]. The quality of RNA-sequencing (RNA-seq) data was assessed preand post-processing using FastQC v0.11.9, after which ribosomal RNA sequences were removed using SortMeRNA [3, 24]. An indexed transcriptome was constructed for each strain using the genomic transcript coordinates generated by PGAP as a reference (CEP14: GenBank accession no.CP084921.1⎯CP084924.1 , JAB1: GenBank accession no. CP016162.1) [11, 36, 42]. The processed reads were aligned to their respective transcriptome using Salmon, and transcript counts were quantified [35]. Differentially expressed transcripts were detected using the DESeq2 package for R Programming in RStudio [29]. Briefly, transcript counts for triplicates were normalised and averaged. Four DESeq2 designs were used for the detection of differentially expressed genes: (i) “design = ~ group”, (ii) “design = ~ condition”, (iii) “design = ~ treatment”, and (iv) “design = ~ condition + treatment + condition:treatment”. This combination of designs allowed for the calculation of log2 fold change of transcript counts between (i) all four treatments, (ii) between primary substrates (cell cultures Page 4 of 15 Desmaraisetal. Environmental Sciences Europe (2025) 37:196 grown on phenol versus sodium pyruvate), (iii) between secondary substrates (cell cultures amended with cDCE or not), and (iv) between phenol-grown cultures amended with cDCE and all other treatments. Cultures grown on cDCE alone were used as a negative control, as no significant depletion of cDCE was observed [11, 36]. To validate our RNA‐Seq dataset, we performed several complementary quality control analyses (Supplementary Information Figs.1–3). First, hierarchical clustering of variance-stabilised gene counts clearly groups biological replicates by treatment and reveals the expected substrate-driven clustering (Supplementary Information Fig. 1). Next, PCA explains 64–70% of the variance on PC1 and confirms tight within‐group clustering for CEP14 and more diffuse grouping in JAB1 (Supplementary Information Fig. 2). Finally, MA plots of the DESeq2 “ ~ condition + treatment + condition:treatment” model demonstrate the distribution of log2 fold changes and adjusted p-values, supporting our cutoffs of log2 fold change ≥ 1 (i.e. at least a two-fold change), for strongly upregulated genes with an FDR below 5% (adjusted p < 0.05) (Supplementary Information Fig.3). Together, these metrics attest to the reproducibility of our data and justify the thresholds used for differential expression calls. No RT-qPCR validation of the differentially expressed genes was performed because the original RNA preparations were completely used up during library preparation. Proteomics Cell pellets were collected from cultures by centrifugation, lyophilised, and subjected to proteomic analyses at the University College Dublin. The lyophilised powder was reconstituted in distilled water and quantified spectrophotometrically by NanoDrop (Thermo Fisher Scientific). Proteins were collected (200 µg) and purified by acetone precipitation, redispersed and denatured in 8M urea and 100mM ammonium bicarbonate containing 10mM dithiothreitol at 60°C for 30min, and alkylated with 55mM iodoacetamide. Trypsin digestion was performed overnight at 37°C at a protein-to-trypsin ratio of 1:50. Peptides were cleaned by C18 StageTips (Thermo Fisher Scientific), vacuum dried, resuspended in 2% acetonitrile and 0.5% acetic acid, and run ona highperformance liquid chromatography (HPLC)-coupled Q Exactive Orbitrap with a 60min gradient. Technical triplicates were assayed for each sample. Data analysis was performed with MaxQuant using the MaxLFQ label-free quantification (LFQ) algorithm for comparative studies, resulting in the identification of proteins present in cultures at the time of sampling [44]. The database search was performed using the following parameters to ensure high-confidence peptide and protein identifications: an initial peptide mass tolerance of 20ppm, a main search tolerance of 4.5ppm, a peptide–spectrum match (PSM) false discovery rate (FDR) of 1%, and a protein FDR of 1%. To assess the robustness and reproducibility of the MS data, we generated Pearson correlation plots of labelfree quantification (LFQ) peptide intensities across three technical replicates for each biological replicate (Supplementary Information Fig.4), which yielded correlation coefficients above 0.95. Unsupervised hierarchical clustering (Supplementary Information Fig. 5) further confirmed condition-specific protein expression by grouping related samples into tight clusters. Although most proteins were identified with one to two peptides, a substantial fraction had more than three (Supplementary Information Fig.6). Finally, the Q-values for all identified proteins were below 0.005 (FDR < 0.5%), underscoring the low overall FDR. Heterologous gene expression The genes coding for the multi-component phenol monooxygenase in CEP14 and JAB1 were heterologously expressed in Escherichia coli (E. coli) as per the methods reported previously [40, 41]. Briefly, the dmpKLMNOP operons found in each strain were amplified by PCR using genomic DNA isolated from CEP14 and JAB1 cultures as a template (primers specified in Supplementary Information Fig.7). The amplified gene clusters were inserted into the commercial plasmid pQE-31 backbone (AmpR, Qiagen) using the In-Fusion® HD Cloning Kit (Takara Bio). The resulting vectors, pQE-dmpCEP14 and pQE-dmpJAB1 (Supplementary Information Fig.7; Supplementary Information Fasta file 1), were used individually to transform E. coli DH11S, and transformants were selected on LB agar supplemented with 150mgl⁻1 ampicillin. Resulting strains were then used for heterologous expression of respective gene clusters following the methodology reported previously [40, 41]. Live and autoclaved E. coli DH11S cells containing an empty pQE-31 served as a reference. Phenol andcDCE depletion assays andmeasurements ofdegradative intermediates The capacity of JAB1 and CEP14 to deplete phenol and cDCE, as well as that of E. coli cells bearing pQE31dmpCEP14 and pQE31-dmpJAB1, was tested using whole-cell assays as per the methods of Suman etal. [41]. Briefly, JAB1 and CEP14 cells were inoculated in 200 ml of MSM containing phenol (10 mM phenol, starting OD 0.05). Cultures were kept at 28 °C with continuous aeration (130rpm) until they reached an OD of 0.4–0.5. These cultures and IPTG-induced E. coli cultures were washed twice, resuspended in MSM, aliquoted into 10ml glass vials, and sealed with crimp caps coated with aluminium. For whole-cell Page 5 of 15 Desmaraisetal. Environmental Sciences Europe (2025) 37:196 cometabolism assays, CEP14 and JAB1 cultures were amended with 15µmol l−1 phenol and cDCE and incubated at 28°C for 12h (CEP14) or 20h (JAB1). In parallel, E. coli strains carrying pQE31-dmpCEP14 or pQE31-dmpJAB1 were grown at 28°C in the presence of 200µmol l−1 phenol and cDCE, with samples taken at 4, 22, 42, 46, and 70h. Catechol measurements were not taken for the CEP14 and JAB1 whole-cell transcriptomic and proteomic assays and were only quantified in our heterologous expression experiments (Supplementary Information Fig.8). Concentrations of catechol as well as cDCE and its hypothetical degradation products, DCA, and 2,2-dichloroacetic acid, were determined by comparison with standards using a DANI Master VH gas chromatograph (GC) equipped with an ECD detector, an Rtx-VMS capillary column (Restek, Edmond, OK, USA), and a Master SHS static headspace auto-sampler as reported previously [31]. Phenol content was measured using the HPLC NexeraXR system with an SPD-M20A UV/VIS diode array detector (Shimadzu, Carlsbad, CA, USA) as described elsewhere [28]. MSM-washed cell suspensions were autoclaved (121°C, 15min) and used analogously as live cells to measure the effect of microbial biomass on phenol and cDCE degradation. In addition, a solution of cDCE in MSM was incubated in parallel to assess the non-enzymatic (abiotic) depletion of cDCE. Results Expression andtranslation ofputative genes involved inphenol andcatechol degradation The genomes of CEP14 and JAB1 harbour gene clusters encoding putative enzymes involved in the degradation of phenol (Fig.2) [11, 36]. In CEP14, these degradative genes are located within two discrete gene clusters that are separated by 728 kbp along the genome (Fig.2A). They encode a phenol monooxygenase responsible for the oxidation of phenol to catechol (dmpKLMNOP) as well as all genes involved in the catechol ortho-cleavage (catABC) and β-ketoadipate (pcaDFIJ) pathways that encode enzymes carrying out the degradation of catechol to acetyl CoA and succinate [50]. In JAB1, genes involved in the degradation of phenol are located within one contiguous gene cluster whose structure is identical to that of the dmp operon found in Pseudomonas pseudoalcaligenes strain C70 and Pseudomonas sp. strain CF600 [20]. This operon encodes a phenol monooxygenase (dmpKLMNOP) and all genes involved in the catechol metacleavage pathway (dmpBCDEFGHI) that encode enzymes carrying out the degradation of catechol to acetyl CoA Fig. 2 Genetic structure of genes encoding putative enzymes involved in the complete degradation of phenol in a CEP14 and b JAB 1 and their respective chemical intermediates (b, c). These gene clusters include the dmp operon (position range 1,861,099–1,866,822) and cat‑pca operon (position range 2,594,895–2,600,570) in b, c CEP14 and the dmp operon (position range 4,397,470–4,409,584) in d JAB1. The organisation of the CEP14 dmpKLMNOP and catABC-pcaDFIJ as well as the JAB1 dmpBCDEFGHIKLMNOPQ gene clusters, each flanked by dmpR, catR, and dmpR, respectively, is identified here as discrete transcriptional units, indicating their independent functional roles Page 6 of 15 Desmaraisetal. Environmental Sciences Europe (2025) 37:196 and pyruvate. The dmpKLMNOP, catABC-pcaDFIJ, and dmpBCDEFGHIKLMNOPQ operons are each flanked by a single regulatory element, dmpR, catR, and dmpR, respectively. Sequence alignment results between the inferred translation products of the CEP14 and JAB1 dmpKLMNOP gene clusters show significant sequence similarity (E < 1.10–23) between all subunits of the phenol monooxygenase, with a query coverage and percent identity greater than 80% and 30%, respectively (Supplementary Information Table2). Sequence similarity between the phenol monooxygenase P3 α subunits (dmpN) of each strain is highly significant and the highest among all subunits, with a query coverage and percent identity of 99% and 72%, respectively. Operons harbouring putative genes responsible for the degradation of phenol, more specifically, the dmp and cat-pca operons in CEP14 and the dmp operon in JAB1, were highly upregulated in cultures grown on phenol as the sole carbon source (log2 fold change 1.9–10.6, Table1). Genes encoding a putative phenol monooxygenase and associated electron transfer chain (dmpKLMNOP) within the dmp operon were among the top ten upregulated transcripts between these two treatments in both strains. Additionally, peptides matching the inferred translation product of the dmp and cat-pca transcripts Table 1 Putative genes involved in the degradation of phenol upregulated in CEP14 (JT734 locus tag prefix) and JAB1 (UYA locus tag prefix) cultures grown on phenol compared to cells grown on sodium pyruvate a The inferred translation product of transcripts marked in bold were found in the proteome of their respective strain grown on phenol b Genes upregulated at with a log2 fold change ≥ 1 in phenol-grown cells compared to sodium pyruvate-grown cells with an FDR of less than 5% (Padj < 0.05). The log2 fold change and p-adjusted value for JT734_12545 were −0.06 and 0.93, respectively c Adjusted p-value (Padj) generated by the Wald test and corrected for multiple testing using the Benjamini and Hochberg method d All proteins identified in the proteomic analysis had Q ≤ 0.005 (< 0.5% FDR), indicating high confidence in the assignments Locus tagaGene abbr Putative enzyme function Change (log2 fold)bPadjc JT734_09015 dmpP Phenol 2-monooxygenase P5 subunit 9.49 1.56E-67 JT734_09020 dmpO Phenol 2-monooxygenase P4 subunit 9.62 1.39E-69 JT734_09025 dmpN Phenol 2-monooxygenase P3/α subunit 9.48 4.58E-93 JT734_09030 dmpM Phenol 2-monooxygenase P2 subunit 9.61 9.17E-42 JT734_09035 dmpL Phenol 2-monooxygenase P1/β subunit 9.31 2.48E-53 JT734_09040 dmpK Phenol 2-monooxygenase P0 subunit 10.56 1.68E-16 JT734_12545 catB Muconate cycloisomerase −0.06 0.93 JT734_12550 catC Muconolactone D-isomerase 2.39 2.11E-08 JT734_12555 catA Catechol 1,2-dioxygenase 4.07 2.04E-18 JT734_12560 pcaI β-ketoadipate succinyl-CoA transferase, α subunit 2.13 5.81E-07 JT734_12565 pcaJ β-ketoadipate succinyl-CoA transferase, β subunit 3.46 7.68E-18 JT734_12570 pcaF β-ketoadipyl-CoA thiolase 4.10 1.82E-27 JT734_12575 pcaD β-ketoadipate enol-lactone hydrolase 3.67 1.15E-28 UYA_20135 dmpI 2-hydroxymuconate tautomerase 2.61 1.96E-03 UYA_20140 dmpH 2-oxo-3-hexenedioate decarboxylase 4.53 6.78E-16 UYA_20145 dmpG 4-hydroxy-2-oxovalerate aldolase 3.29 6.38E-09 UYA_20150 dmpF Acetaldehyde dehydrogenase 2.57 5.66E-05 UYA_20155 dmpE 2-keto-4-pentenoate hydratase 2.14 1.60E-03 UYA_20160 dmpD 2-hydroxymuconate-semialdehyde hydrolase 1.94 1.11E-02 UYA_20165 dmpC 2-hydroxymuconate-6-semialdehyde dehydrogenase 2.27 8.35E-05 UYA_20170 dmpB Catechol 2,3-dioxygenase 2.72 6.91E-05 UYA_20175 dmpQ Ferredoxin 2.15 5.24E-03 UYA_20180 dmpP Phenol 2-monooxygenase P5 subunit 2.88 3.25E-05 UYA_20185 dmpO Phenol 2-monooxygenase P4 subunit 2.91 1.14E-03 UYA_20190 dmpN Phenol 2-monooxygenase P3/α subunit 3.95 9.31E-06 UYA_20195 dmpM Phenol 2-monooxygenase P2 subunit 4.23 1.19E-06 UYA_20200 dmpL Phenol 2-monooxygenase P1/β subunit 4.08 1.23E-06 UYA_20205 dmpK Phenol 2-monooxygenase P0 subunit 2.97 3.28E-03 Page 7 of 15 Desmaraisetal. Environmental Sciences Europe (2025) 37:196 were detected in the sequenced proteome of their respective strain grown on phenol (in bold, Table1). In our heterologous dmpKLMNOP expression assays, we identified the accumulation of catechol, the direct product of phenol monooxygenase activity, further confirming that these genes encode a functional phenol monooxygenase (Supplementary Information Fig.8). The gene encoding a putative muconate cycloisomerase (catB) was the only CDS not significantly upregulated in the CEP14 cat–pca operon, nor found in the proteome data of cultures grown on phenol. The reason for this selective non-expression is unclear. Possible factors include operon polarity, mRNA structure and stability, presence of repressors, or differential protein turnover, and dedicated experiments will be needed to resolve the mechanism. Transcriptomic andproteomic screening: identification ofputative cDCE monooxygenases The CEP14 and JAB1 genomes were screened to identify genes that might facilitate the oxidation of cDCE to DCA as the initial chemical transformation during the cometabolic degradation of cDCE in the presence of phenol (Fig. 1). Briefly, the inferred proteome of each strain was screened using protein sequences of monooxygenases with experimentally demonstrated cDCE catalytic activity (Supplementary Information Table 3). The α subunit of each monooxygenase was used for proteome screening as it encodes the oxidative catalytic centre [25]. These include the α subunits of cDCE monooxygenase (CMOA) in Polaromonas sp. JS666, butane monooxygenase (BMOA) in Thauera butanivorans ATCC 43655, methane monooxygenase (MMOA) in Methylosinus trichosporium OB3b, tolueneo-xylene monooxygenase (TOMOA) in Pseudomonas stutzeri OX1, and alkene monooxygenase (XAMOA) in Xanthobacter autotrophicus Py2. Initial BlastP screening results revealed that the only genes whose inferred translation products share significant sequence similarity with BMOA, MMOA, TOMOA, and XAMOA in the CEP14 and JAB1 proteomes are JT734_09025 and UYA_20190, respectively, both encoding phenol monooxygenase α subunits (dmpN). No CMO sequence identity matches were found in either the CEP14 or JAB1 proteome. Hierarchical clustering of monooxygenase α subunits with demonstrated cDCE catalytic activity based on sequence similarity revealed the grouping of these peptides into four clusters (Fig.3, Supplementary Information Table4). Overall, the inferred protein sequences of bmoA, mmoA, tomoA, JT734_09025, and UYA_20190 clustered together and shared low sequence identity with the CMO of Polaromonas sp. JS666. Candidates for genes encoding a putative cDCE monooxygenase were identified by compiling all genes encoding putative monooxygenases that were upregulated during cDCE degradation, when CEP14 and JAB1 cultures were grown on phenol with cDCE. Both cultures completely depleted the initial amounts of phenol and cDCE after 12h (CEP14) and 20h (JAB1). Maximum degradation rates were 2.3 and 1.9µmoll⁻1h⁻1 for phenol, and 2.9 and 5.3µmoll⁻1h⁻1 for cDCE, respectively Fig. 3 Depletion of phenol (solid blue line) and cDCE (dashed blue line), and accumulation of DCA (dotted blue line) in a CEP14 and b JAB1 cultures grown on 15 µmol l−1 phenol and cDCE at 28 °C over a 12 h and 20 h time course, respectively. Data points are means ± SD from three biological replicates. The vertical “RNA” dashed line indicates sampling time for transcriptomic analysis. Catechol was not measurable in these whole‑cell assays and was only quantified in our heterologous expression experiments (Supplementary Information Fig. 8) Page 8 of 15 Desmaraisetal. Environmental Sciences Europe (2025) 37:196 (Fig. 4). In comparison, the abiotic and inactivated microbial biomass controls depleted 7% and 11% of the initial amount of cDCE, respectively. Seven distinct monooxygenase‐encoding loci were upregulated in each strain (log2 fold change ≥ 1, FDR < 5%; Supplementary Information Tables5 and 6). Of these, only two loci were shared by CEP14 and JAB1: (i) JT734_09015–09040 / UYA_20180–20205, encoding the multi‐component phenol monooxygenase and its electron‐transfer partners (dmpRKLMNOP), and (ii) JT734_09880 / UYA_20305, encoding a 4-hydroxybenzoate 3-monooxygenase (pobA). Crucially, peptides from the dmp operon, but not from pobA, were detected in our whole‐cell proteomic analyses of CEP14 and JAB1 cultures grown on phenol and cDCE. Consequently, we focused on dmpKLMNOP as the most likely cDCE monooxygenase, since it is the sole monooxygenase upregulated in both strains with complementary proteomic evidence. Heterologous dmpKLMNOP expression: evaluating theability ofphenol monooxygenase tooxidise phenol andcDCE We tested the capability of the heterologously expressed multi-component phenol monooxygenases from CEP14 and JAB1 to oxidise phenol and cDCE. Assays were set up using E. coli cultures heterologously expressing the dmpKLMNOP gene clusters. After 24h of incubation, both E.coli cells expressing dmpKLMNOP gene clusters from CEP14 and JAB1depleted 100% of the initial amount of phenol; the accumulation of catechol, the phenol degradation product, was also observed (Supplementary Information Fig.8). Some 50% and 30% of the initial amount of cDCE was depleted by E. coli expressing dmpKLMNOP from CEP14 and JAB1, respectively. Neither phenol nor cDCE depletion by E. coli cells bearing empty pQE31 or by the autoclaved cells was observed. Identification ofcDCE degradation intermediates Using whole‐cell assays of CEP14 and JAB1 expressing dmpKLMNOP, we monitored cDCE depletion alongside degradative intermediate accumulation. Commercial standards were only available for DCA and 2,2-dichloroacetate. After 70h, cDCE (retention time (RT) 3.344min) decreased to 59% (CEP14) and 69% (JAB1) of initial levels (Fig.5A). DCA (RT 5.111min), the direct oxidation product of cDCE, was detectable as early as 4h (Fig.5A, B). A second, unidentified peak (RT 9.977 min) co‐ occurred with cDCE loss but was not characterised further (Fig.5B, C). 2,2-dichloroacetic acid (RT 14.025min), a subsequent hypothetical degradative intermediate arising from the dehydrogenation of DCA, was not detected in either CEP14 or JAB1 reactions at any time point monitored (data not shown). Other proposed pathway intermediates (e.g. cDCE epoxide, chloroglycolate, glyoxylate) were not measured in these assays, and therefore, the Fig. 4 Heatmap of amino acid sequence similarity between the α subunit of monooxygenases with experimentally demonstrated cDCE catalytic activity (Supplementary Information Table 2) and the inferred translation product of genes JT734_09025 and UYA_20190 encoding putative phenol monooxygenases. Sequence similarity was calculated with the Clustal Omega multiple sequence alignment web tool. Units are in percentage, and E < 0.05 for all sequence similarity values. Detailed results can be found in Supplementary Information Table 2 Page 9 of 15 Desmaraisetal. Environmental Sciences Europe (2025) 37:196 Fig. 5 Depletion of cDCE by JAB1 and CEP14 (A) and detection of degradative intermediates in JAB1 (B) and CEP14 (C). A JAB1—dotted line, CEP14—full line; the values shown represent means from three replicates and error bars represent standard deviations. B and C Gas chromatography analyses of the JAB1 and CEP14 reactions, respectively, after 4 h of incubation; black line—the reaction with live cells, red line— the reaction with autoclaved cells. The identity of peaks was assigned based on the parallel analysis of commercial standards