The catabolism of ethylene glycol by Rhodococcus jostii RHA1 and its dependence on mycofactocin
ABSTRACT
Ethylene glycol (EG) is a widely used industrial chemical with manifold applications and also generated in the degradation of plastics such as polyethylene terephthalate. Rhodococcus jostii RHA1 (RHA1), a potential biocatalytic chassis, grows on EG. Transcriptomic analyses revealed four clusters of genes potentially involved in EG catabolism: the mad locus, predicted to encode mycofactocin-dependent alcohol degradation, including the catabolism of EG to glycolate; two GCL clusters, predicted to encode glycolate and glyoxylate catabolism; and the mft genes, predicted to specify mycofactocin biosynthesis. Bioinformatic analyses further revealed that the mad and mft genes are widely distributed in mycolic acid-producing bacteria such as RHA1. Neither ΔmadA nor ΔmftC RHA1 mutant strains grew on EG but grew on acetate. In resting cell assays, the ΔmadA mutant depleted glycolaldehyde but not EG from culture media. These results indicate that madA encodes a mycofactocin-dependent alcohol dehydrogenase that initiates EG catabolism. In contrast to some mycobacterial strains, the mad genes did not appear to enable RHA1 to grow on methanol as sole substrate. Finally, a strain of RHA1 adapted to grow ~3× faster on EG contained an overexpressed gene, aldA2, predicted to encode an aldehyde dehydrogenase. When incubated with EG, this strain accumulated lower concentrations of glycolaldehyde than RHA1. Moreover, ecotopically expressed aldA2 increased RHA1’s tolerance for EG further suggesting that glycolaldehyde accumulation limits growth of RHA1 on EG. Overall, this study provides insights into the bacterial catabolism of small alcohols and aldehydes and facilitates the engineering of Rhodococcus for the upgrading of plastic waste streams.
IMPORTANCE
Ethylene glycol (EG), a two-carbon (C2) alcohol, is produced in high volumes for use in a wide variety of applications. There is burgeoning interest in understanding and engineering the bacterial catabolism of EG, in part to establish circular economic routes for its use. This study identifies an EG catabolic pathway in Rhodococcus, a genus of bacteria well suited for biocatalysis. This pathway is responsible for the catabolism of methanol, a C1 feedstock, in related bacteria. Finally, we describe strategies to increase the rate of degradation of EG by increasing the transformation of glycolaldehyde, a toxic metabolic intermediate. This work advances the development of biocatalytic strategies to transform C2 feedstocks.
INTRODUCTION
Millions of tonnes of ethylene glycol (EG) are produced annually for use in manifold applications, ranging from antifreeze formulations to the manufacture of polyester fibers, resins, and polyethylene terephthalate (PET) (1). More recently, EG has garnered attention as a component for a carbon neutral bio-economy with the development of a two-step process to generate it electrochemically from syngas (2). Although EG is broken down chemically and biologically in the environment, it can contaminate water sources and soil due to its high-volume production and widespread use, leading to harmful consequences for aquatic life, plants, and animals (3). Moreover, glycolaldehyde, a highly toxic intermediate of EG catabolism, is often present at significant concentrations in lignocellulose-derived streams (4). Given the widespread occurrence of EG, there is burgeoning interest in understanding and engineering its bacterial catabolism. This catabolism has been explored as part of the upcycling of PET and in the broader context of establishing circular economic routes for the use of EG (5–9).
Two pathways for the catabolism of EG have been described in bacteria. In the acetogenic Acetobacterium woodii, EG is dehydrated to acetaldehyde, then converted to ethanol and acetyl coenzyme A (10). In the second pathway, best described in Escherichia coli (11) and Pseudomonas putida (12), EG is successively oxidized to glycolaldehyde, glycolate, and glyoxylate, the latter of which feeds into the central metabolism. In P. putida, the oxidation of EG to glycolaldehyde is catalyzed by PedE and PedH, functionally redundant periplasmic alcohol dehydrogenases that utilize pyrroloquinoline quinone (PQQ), a redox cofactor (13). This pathway has been engineered in P. putida KT2440 (KT2440), a biocatalytic chassis that does not efficiently catabolize EG (5) to produce microbial cell factories for EG transformation. For example, overexpression of gcl, encoding a glyoxylate carboligase, in combination with other genes in KT2440, yielded a strain that grows on 2 M EG (5). In another study, KT2440 was subject to adaptive laboratory evolution to create a strain that grows on 120 mM EG at a rate comparable to that on acetate (6). This EG-specific adaptation was explained by an improved metabolic flux of EG resulting in lower accumulation of growth-inhibiting intermediates, such as glycolaldehyde, and higher levels of reducing equivalents from EG (5, 6). More recently, the β-hydroxyaspartate cycle was implemented in KT2440 to improve biomass yield and growth rate of the organism by 20% and 35% on EG, respectively (8).
Another genus with considerable biocatalytic potential, including for the upcycling of PET, is Rhodococcus, a mycolic acid-producing Actinobacteria that catabolize an exceptionally wide range of aromatic compounds (14, 15). Recently, Rhodococcus jostii PET was shown to grow on terephthalate and EG as sole substrates and, as a proof-of-concept, was engineered to upcycle PET hydrolysate to lycopene (16). Other growth substrates for rhodococci include alkylguaiacols and acetovanillone, which are derived from the chemocatalytic fractionation of lignocellulosic feedstocks (17–19). The catabolic capacity of rhodococci, combined with their high resistance to stressors, such as organic solvents, contributes to these strains being ideal candidates for biocatalysis (20). Indeed, rhodococcal biocatalysts are used to generate thousands of tons of acrylamide annually (21). The engineering of rhodococci for biocatalysis is assisted by the availability of numerous genetic tools (22–24). Within this genus, R. jostii RHA1 (RHA1), originally isolated from lindane-contaminated soil, has been well characterized for its ability to catabolize a variety of aromatic compounds (25, 26).
Mycolic acid-producing Actinobacteria, such as Mycobacterium smegmatis, utilize the mycofactocin (MFT)-dependent alcohol degradation (MAD) pathway, encoded by the madABCD genes, to grow on methanol and ethanol (27, 28). In this pathway, alcohol catabolism is initiated by methanol oxidase (Mno) (29), an NADP+-containing enzyme that reduces MFT to MFTH2 to oxidize small alcohols to their aldehydes (27, 30). Mno possesses striking functional and regulatory similarities to PedE and PedH of KT2440 despite sharing less than 20% amino acid sequence identity with these enzymes. MFT, a redox cofactor similar to PQQ with respect to its biosynthesis, structure, and function, is produced through modification of a precursor peptide, MftA, by proteins encoded by the mftABCDEF cluster (31). Interestingly, Mno also acts on formaldehyde and has higher specific activity for ethanol, propanol, and butanol than for methanol (27, 30). A related enzyme in Rhodococcus erythropolis N9T-4 has formaldehyde dismutase activity and is induced by formaldehyde and under oligotrophic growth conditions (32). Many rhodococci have been predicted to contain MFT biosynthesis genes (31), and RHA1 is predicted to contain 19 MFT-dependent oxidoreductases (33). However, these enzymes have not been characterized.
In this study, we investigated the catabolism of EG by RHA1. We conducted transcriptomic and bioinformatic analyses to identify genes potentially involved in EG catabolism and related processes, such as glycolate and methanol catabolism. The madA and mftC genes, predicted to encode Mno and an MFT radical SAM maturase, respectively, were deleted, and the mutants were characterized to validate gene function. Additionally, we adapted RHA1 to grow on increased concentrations of EG and used transcriptomics to investigate processes involved in the increased tolerance. As part of this, we used a strain overproducing AldA2 to investigate the role of this enzyme in glycolaldehyde metabolism, a key step in EG degradation. This work is compared and contrasted with respect to similar studies recently described by Shimizu et al. (34). More generally, the elucidated EG catabolic pathway is discussed with respect to the catabolism of related compounds in mycolic acid-producing bacteria and to the engineering and development of application-specific microbial cell factories for utilizing C2 feedstocks.
MATERIALS AND METHODS
Chemicals and reagents
All reagents were of analytical grade unless otherwise noted. Enzymes for DNA amplification and manipulation were purchased from New England Biolabs. Oligonucleotides were synthesized by Integrated DNA Technologies. Buffers were prepared using water purified on a Barnstead NANOpure Diamond UV apparatus to a resistance of 18 MΩ/cm. Media were prepared using double distilled water. All other reagents were of analytical grade.
Growth media and culture conditions
Strains and plasmids used in this study are listed in Table 1. E. coli strains were grown in lysogeny broth (LB) at 37°C, shaking at 200 rpm. RHA1 was cultured at 30°C in either LB or M9 minimal medium supplemented with Goodies mix containing trace elements (hereafter referred to as M9G medium) (35) and an appropriate growth substrate. Cultures were shaken at 200 rpm in 250-mL flasks containing 50 mL of medium. Media components were sterilized by autoclaving or filtration (0.22-µm pore size) as appropriate. Solid growth medium for all strains was LB supplemented with 1.5% (wt/vol) Bacto agar. Media was further supplemented with 50 µg/mL of carbenicillin (E. coli carrying pTip-derived plasmids), 10 µg/mL of neomycin (E. coli carrying pK18-derived plasmids), 34 µg/mL of chloramphenicol (RHA1 carrying pTip-derived plasmids), or 30 µg/mL of nalidixic acid (for selecting RHA1 after conjugation) as appropriate. Expression from the tipA promoter of pTipQC2 in RHA1 was induced by adding thiostrepton to 1 µg/mL for complementation experiments. Except for carbenicillin, which was dissolved in water, antibiotics were dissolved in dimethyl sulfoxide. Cell growth in liquid media was measured by diluting the cultures to an appropriate density in 1-mL cuvettes and determining the optical density at 600 nm (OD600).
TABLE 1
| Strain or plasmid | Description | Source |
|---|---|---|
| E. coli strains | ||
| DH5α | DNA propagation | Invitrogen |
| S17.1 | Conjugation of plasmids into RHA1 | (36) |
| Rhodococcus strains | ||
| R. jostii RHA1 | Wild type | (26) |
| R. jostii RHA1-EG | EG-adapted RHA1 | This study |
| ΔmadA | RHA1 deletion mutant of madA | This study |
| ΔmftC | RHA1 deletion mutant of mftC | This study |
| Plasmids | ||
| pK18mobsacB | sacB, oriT, aphII | (37) |
| pTip-QC2 | Expression in RHA1, PtipA, Chlr, repAB | (38) |
| pK18ΔmadA | pK18mobsacB-derived construct to delete madA | This study |
| pK18ΔmftC | pK18mobsacB-derived construct to delete mftC | This study |
| pTip-madA | pTip-QC2 harboring madA | This study |
| pTip-mftC | pTip-QC2 harboring mftC | This study |
| pTip-aldA2 | pTip-QC2 harboring aldA2 | This study |
DNA manipulation, plasmid construction, and gene deletions
DNA was isolated, manipulated, amplified, and analyzed using standard protocols (39). Oligonucleotides used in this study are listed in Table S1. RHA1 genes were amplified from genomic DNA using gene-specific primers and Phusion DNA polymerase. Chemically competent E. coli DH5α cells (100 µL) were transformed with plasmid DNA by heat shock at 42°C for 45 s. Electrocompetent RHA1 cells (50 µL) were electroporated using a MicroPulser with GenePulser cuvettes at 2.0 kV for 5 ms (Bio-Rad). Constructs were propagated in E. coli DH5α and their nucleotide sequences confirmed before transformation into RHA1.
The madA and mftC genes were deleted using homologous recombination and SacB counter selection as previously described (37). Briefly, the two ~800-bp flanking regions of the genes were amplified from RHA1 genomic DNA using the upstream and downstream primer pairs. The resulting amplicons were inserted into pK18mobsacB linearized with BamHI and HindIII using Gibson Assembly, resulting in pK18ΔmadA and pK18ΔmftC. The sequence-confirmed construct was transformed into E. coli S17.1 and then conjugated into RHA1. After the second recombination step, kanamycin-sensitive/sucrose-resistant RHA1 colonies were screened and confirmed using PCR. Constructs based on pTip-QC2 were transformed into RHA1 using electroporation.
Adaptive laboratory evolution of RHA1
The adapted strain, RHA1-EG, was derived from RHA1 through four sequential cultivations at increasing EG concentrations. Briefly, RHA1 was grown on 60 mM sodium acetate in M9G medium and used to inoculate 30 mM EG in M9G at an OD600 of 0.05 in 50-mL shake flasks. Cultures were incubated for 2 to 3 days until cells stopped replicating exponentially, then were used to inoculate 60 mM EG in M9G at an OD600 of 0.05. Serial transfers were repeated, inoculating 120 mM then 180 mM EG. After each EG increment, 25% glycerol stocks of the cultures were stored at −80°C. Single colonies from the final culture were isolated on LB agar plates and used for subsequent growth experiments.
HPLC analysis
For EG and glycolaldehyde quantification, culture supernatants were centrifuged (16,000 × g for 10 min). Samples were run over an Aminex HPX-87H 250 × 4 mm column at 0.6 mL/min at 35°C using an Agilent 1260 Infinity separation high-performance liquid chromatography (HPLC) module with an isocratic 8 mM sulfuric acid mobile phase. EG and glycolaldehyde were detected using Wyatt Optilab tREX Refractive Index Detector with a light source wavelength of 658 nm. Concentrations were determined by interpolation on a calibration curve of 0 to 200 mM of authentic standard for EG and 0 to 20 mM of glycolaldehyde.
RNA extraction and sequencing
For RNA extraction, 50-mL cultures were grown on 30 mM acetate, EG, or glycolate in M9G medium to mid-log phase. Cultures were inoculated at an OD600 of 0.05, and experiments were performed in triplicate. Ten microliters of culture was centrifuged at room temperature. The cell pellets were suspended in 2 mL of TRIzol (Thermo Fisher Scientific) and stored at −80°C. RNA isolation was performed as described in Ref. (18). Samples were sequenced by the Sequencing + Bioinformatics Consortium at UBC using a NextSeq550 system (Illumina) with Mid-output 75-bp paired-end reads. Reads were analyzed as described (18). RNA reads were subject to quality control, filtered and trimmed using Trimmomatic 0.3.6 (40) with default settings. Transcripts were quantified using Salmon 0.8.1 (41) and mapped to the RHA1 genome using the NCBI reference sequence for the chromosome and the three plasmids (NC_008268.1, NC_008269.1, NC_008270.1, NC_008271.1). Differential expression was analyzed using DeSeq2 1.18.1 (42) in RStudio 1.3.1 and R version 4 with false discovery rate correction. Data tables were compared using tidyverse 1.3.0 in RStudio.
For RT-qPCR, RNA isolated from EG- and acetate-grown cells was reverse transcribed to cDNA using the SuperScript VILO cDNA synthesis kit (Life Technologies). Amplification reactions were performed using an ABI StepOnePlus Real-Time PCR System with PowerUp SYBR Green Master Mix (Thermo Fisher Scientific) and oligonucleotides shown in Table S1. The cycling conditions were as follows: 95°C for 5 min followed by 40 cycles of 95°C for 30 s, 52°C for 20 s, and 72°C for 30 s. Transcript levels were divided by normalized levels of the sigA transcript. Relative fold differences were calculated using acetate-grown cells as a reference.
Bioinformatics, data analysis and visualization
Database searches and alignments were performed using BLAST (43) and MUSCLE (44). Reference DNA and protein sequences were retrieved from the NCBI, UniProtKB, and BioCyc (45) databases. Other data were analyzed using Excel (Microsoft) unless otherwise noted. Graphs were created and statistically analyzed using GraphPad Prism 9 (GraphPad Software). Figures were edited using PowerPoint (Microsoft). Chemical structures and metabolic pathways were drawn using ChemDraw 20.0 (Perkin Elmer Informatics).
RESULTS
Growth of RHA1 on EG
To characterize RHA1’s ability to grow on EG, we first determined the bacterium’s growth kinetics on EG and several of its putative catabolic intermediates. RHA1 grew on 15 and 30 mM EG at a rate of 0.05 h−1 after a lag time of approximately 32 h and grew more slowly on 60 mM EG (Fig. 1). By comparison, the strain grew on up to 60 mM acetate, another C2 compound, at 0.17 h−1 after a lag of only 9 h. Among putative EG catabolites, RHA1 grew at a similar rate on 15 mM glycolate as on EG (Fig. S1A). However, the cultures grown on 15 mM glycolate only reached about half the OD600 as cultures grown on 15 mM EG or acetate. RHA1 did not grow on either glycolaldehyde or glyoxal, two other potential EG catabolites, even after incubation for 60 h (data not shown). Indeed, 1.5 mM glyoxal (Fig. S1C; Table 2) and 5 mM glycolaldehyde (Fig. S1E) inhibited the growth of RHA1 on acetate.
Fig 1
TABLE 2
| RHA1 | RHA1-EG | RHA1 (aldA2) | |
|---|---|---|---|
| Glycolaldehyde | 5 | 7 | 7 |
| Formaldehyde | 2 | 4 | 2 |
| Glyoxal | 1.5 | 1.5 | NDb |
a
Strains were grown on 15 mM acetate with increasing concentrations of the indicated aldehyde. The listed value indicates the minimum concentration of aldehyde (in mM) that inhibited growth of the strain. Glycolaldehyde and formaldehyde were tested at 1 mM increments. Glyoxal was tested at 0.5 mM increments.
b
ND, not determined.
Identification of EG and glycolate catabolic genes by RNA-seq
Having established that RHA1 grows on EG, we conducted transcriptomic studies to identify genes and pathways that are involved in its catabolism. Cells grown on 30 mM EG, glycolate, or acetate were harvested during exponential growth. We hypothesized glycolate to be an intermediate in the catabolism of EG by RHA1 as it is in the catabolism of EG by P. putida (12). Acetate was used as a control as it is a C2 compound whose metabolism is distinct from that of EG. Analysis of the RNA-seq data revealed that 433 genes were significantly upregulated during growth of RHA1 on EG versus acetate (log2FC > 2.50, padj <0.0001), and 100 were significantly downregulated (Table S2). By comparison, 427 genes were significantly upregulated, and none were downregulated during growth on glycolate versus acetate (Table S2). Finally, 51 genes were upregulated and 58 were downregulated during growth on EG versus glycolate. The transcriptomics and bioinformatics data revealed four clusters of genes predicted to be involved in EG and glycolate catabolism (Fig. 2; Table 3): the mad locus, predicted to encode mycofactocin-dependent alcohol degradation, including the catabolism of EG to glycolate; two glyoxylate carboligase (GCL) clusters (6), predicted to encode glycolate and glyoxylate catabolism; and the mft genes, predicted to specify the biosynthesis of the mycofactocin used by one of the mad-encoded enzymes.
Fig 2
TABLE 3
| Gene | ORFa | Gene product | Closest characterized homologb | IDc (%) | FCd (EG) | Refe |
|---|---|---|---|---|---|---|
| EG catabolism and regulation | ||||||
| madA | RS29605 | MFT-dependent alcohol dehydrogenase | Mno, M. smegmatis mc2155 (A0R5M3) | 92 | 482 | (27) |
| madB | RS29610 | MoxR family ATPase | None | - | 389 | - |
| madC | RS29615 | VWA domain-containing protein | None | - | 302 | - |
| madD | RS29620 | Iron-dependent alcohol dehydrogenase | ErcA, Pseudomonas aeruginosa PAO1 (Q9I2B8) | 42 | 7 | (46) |
| madS | RS29625 | Sensor histidine kinase | MnoS, M. smegmatis mc2155 (A0R5L9) | 60 | 10 | (29) |
| madR | RS29630 | Response regulator transcription factor | MnoR, M. smegmatis mc2155 (A0R5L8) | 76 | 8 | (29) |
| Glyoxylate catabolism, GCL1 pathway | ||||||
| garK1 | RS12580 | Glycerate kinase | GlxK/GarK, E. coli K-12 (P77364/P23524) | 40 | 69 | (47, 48) |
| gcl1 | RS12585 | Glyoxylate carboligase | Gcl, E. coli K-12 (P0AEP8) | 73 | 78 | (47) |
| glxR1 | RS12590 | Tartronate semialdehyde reductase | GlxR, Streptomyces coelicolor (Q9Z597) | 60 | 161 | (49) |
| hyi1 | RS12595 | Hydroxypyruvate isomerase | Hyi, S. coelicolor (Q9Z596) | 53 | 133 | (49) |
| Glycolate/glyoxylate catabolism, GCL2 pathway | ||||||
| gcl2 | RS15645 | Glyoxylate carboligase | Gcl, E. coli K-12 (P0AEP8) | 72 | 1186 | (47) |
| glxR2 | RS15650 | Tartronate semialdehyde reductase | GlxR, S. coelicolor (Q9Z597) | 61 | 426 | (49) |
| hyi2 | RS15655 | Hydroxypyruvate isomerase | Hyi, S. coelicolor (Q9Z596) | 52 | 459 | (49) |
| glcD | RS15665 | FAD-linked oxidase | GlcD, (P0AEP9, E. coli K-12) | 39 | 165 | (50) |
| garK2 | RS15675 | Glycerate kinase | GlxK/GarK, E. coli K-12 (P77364/P23524) | 39 | 174 | (47, 48) |
| Mycofactocin (MFT) biosynthesis | ||||||
| mftR | RS29670 | MFT system transcriptional regulator | MftR, M. smegmatis mc2155 (A0QSB5) | 52 | 2 | (28) |
| mftA | RS45350 | MFT precursor | MftA, M. smegmatis mc2155 (A0QSB6) | 77 | 6 | (28) |
| mftB | RS29675 | MFT biosynthesis chaperone | MftB, M. smegmatis mc2155 (A0QSB7) | 64 | 4 | (28) |
| mftC | RS29680 | MFT radical SAM maturase | MftC, M. smegmatis mc2155 (A0QSB8) | 77 | 3 | (28) |
| mftD | RS29685 | MFT biosynthesis FMN-dependent deaminase | MftD, M. smegmatis mc2155 (A0QSB9) | 75 | 4 | (28) |
| mftH | RS29690 | MFT system FadH/OYE family oxidoreductase 1 | DgcA, P. aeruginosa PAO1 (Q9HTG6) | 28 | 7 | (51) |
| mftI | RS29695 | MFT-coupled SDR family oxidoreductase | Rv0687, Mtb H37Rv (P9WGS7) | 58 | 6 | (33) |
| mftJ | RS29700 | MFT system FadH/OYE family oxidoreductase 2 | DgcA, P. aeruginosa PAO1 (Q9HTG6) | 33 | 6 | (51) |
| mftE | RS29705 | MFT biosynthesis peptidyl-dipeptidase | MftE, M. smegmatis mc2155 (A0QSC0) | 58 | 1 | (28) |
| mftF | RS29710 | MFT biosynthesis glycosyltransferase | MftF, M. smegmatis mc2155 (A0QSC1) | 55 | 1 | (28) |
| mftG | RS29715 | MFT system GMC family oxidoreductase | None | - | 2 | - |
a
The prefix RHA1 was omitted for simplicity.
b
Closest homolog with an experimentally verified function (species, gene identifier). Rv0687, uncharacterized short-chain dehydrogenase with solved structure.
c
Percent amino acid sequence identity calculated over the entire length of the proteins.
d
Fold-change during growth on EG versus acetate (padj <0.0001). ND, not detected.
e
Reference.
The mad locus includes madA (RHA1_RS29605), which was the fourth highest upregulated gene during growth on EG versus acetate and was also highly upregulated on glycolate, (Fig. 2). RT-qPCR confirmed that madA was upregulated ~1,400-fold on EG versus acetate, while madD (RHA1_RS29620) was upregulated sixfold. MadA is the reciprocal best hit of Mno from M. smegmatis, with which it shares 92% amino acid sequence identity and the same genomic context (Fig. 2). As noted above, Mno is a mycofactocin-dependent methanol oxidase that is required for growth on methanol and ethanol and that also acts on formaldehyde (27, 28). MadA also shares 97% amino acid sequence identity with Mno from R. erythropolis N9T-4, which possesses formaldehyde dismutase activity (32). Based on the activity of these close homologs in mycobacteria and rhodococci, as well as the evidence presented below, we annotated MadA as a mycofactocin-dependent alcohol dehydrogenase that initiates EG catabolism in RHA1.
The mad genes are arranged in two putative operons based on RNA-seq reads, madABC and madDSR, and are homologous to the mno locus of M. smegmatis (Fig. 3) The madS and madR genes are predicted to encode the sensor kinase and response regulator, respectively, of a two-component signal transduction system that regulates the transcription of the mad genes. MnoSR, the reciprocal best hits of MadSR, regulate the expression of mno in M. smegmatis (29). MadD, is the reciprocal best hit of ErcA (PA1991) of Pseudomonas aeruginosa PAO1 (Table 3), an iron-dependent alcohol dehydrogenase, which may play a regulatory role in ethanol catabolism (46). The homolog encoded by the mno cluster, MSMEG_6239, is a putative 1,3-propanediol dehydrogenase and is also regulated by MnoSR (29). Finally, as summarized in Table 3, the physiological functions of madB and madC are unknown (29).
Fig 3
The MFT biosynthesis genes were identified based on their similarity to mftABCDEF of M. smegmatis (28). However, the architecture of the cluster in RHA1 differs from the typical organization in mycobacteria (53). Notably, the mftABCD and mftEFG genes in RHA1 are interrupted by three genes annotated here as mftHIJ. These three genes, together with mftA, were slightly upregulated on EG versus acetate, while none of the other mft genes were differentially regulated (Table 3). Furthermore, mftG, encoding a predicted GMC oxidoreductase, is likely part of the mft operon. Interestingly, the mft locus is located within 10 kbp of the mad genes in RHA1. By contrast, the mft genes are more than 2 Mbp away from the mno genes in M. smegmatis.
The most highly upregulated genes on EG and glycolate versus acetate occur in two clusters, designated here as GCL1 and GCL2 (Table 3; Fig. 4). GCL1 and GCL2 are predicted to encode glyoxylate catabolic enzymes analogous to the Gcl pathways in E. coli, P. putida, and Streptomyces coelicolor, which are associated with allantoin catabolism (5, 47, 49). Glyoxylate is an intermediate in catabolism of both EG and allantoin. GCL1 includes gcl, glxR, hyi, and garK, which, based on putative promoters and RNA-seq reads, are part of an eight-gene operon predicted to encode the catabolism of allantoin to glyoxylate and urea (Fig. 4A and B). Other highly upregulated genes in this region include allP and puuE, which are also involved in allantoin catabolism; aceE2 and pyk2, which encode glycerate catabolism (Fig. 4); and RHA1_RS12640-RS12655, which encodes the mycothiol-dependent detoxification of formaldehyde. The glcB gene, located upstream of GCL1 and which codes for malate synthase, was not significantly upregulated. Moreover, aceA, which encodes an isocitrate lyase, was downregulated on EG versus acetate. Together, this suggests that the glyoxalate shunt was not as active during growth on EG as on acetate.
Fig 4
GCL2 includes a second set of gcl, glxR, hyi, and garK homologs as well as glcD, encoding glycolate oxidase (Fig. 4). In E. coli and P. putida, GlcD transforms glycolate to glyoxylate and requires GlcE and GlcF, although the precise roles of the latter are unknown (50, 54). Interestingly, the glcDEF operon in E. coli and P. putida is part of the allantoin pathway in these organisms and is not associated with the glyoxylate cluster (5, 50). Although GCL2 does not contain glcE and glcF homologs, we have provisionally annotated GlcD of RHA1 as a glycolate oxidase. Four other genes of interest lie close to GCL2 (Fig. 4). Two of these, RHA1_RS15700 and RHA1_RS15705, form a putative operon and encode a lactate/glycolate transporter and a second GlcD homolog, respectively. However, they were not significantly upregulated during growth on EG or glycolate. The other two genes, RHA1_RS15635 (pyk3) and RHA1_15680, predicted to encode a pyruvate kinase and an MSF transporter, respectively, were highly expressed on EG and glycolate. This suggests that glycolate is metabolized via an independently regulated glycerate pathway and that RHA1_RS15680 may translocate glycolate or a related metabolite.
The GCL1 and GCL2 transcripts had very similar relative abundances in EG- and glycolate-grown cells (P(GCL1) = 0.067; P(GCL2) = 0.107), consistent with the conclusion that EG and glycolate catabolism share many steps. Finally, the GCL2 genes were on average 4 and 16 times more highly expressed on EG and glycolate, respectively, compared to the GCL1 genes [P(EG) = 0.0432, P(glycolate) = 0.0003], suggesting that GCL2 plays a bigger role in catabolizing these compounds than GCL1.
Comparison of the differentially regulated genes during growth on EG versus glycolate did not provide further insight into the transformation of EG to glycolate, and a glycolaldehyde dehydrogenase candidate was not identified (Fig. S2). The majority of the highly up- and downregulated genes encode hypothetical proteins or proteins for which no characterized homologs exist. Operons putatively involved in polyketide synthesis (RHA1_RS09515 to RHA1_RS09520 and RHA1_RS02760 to RHA1_RS02775) were among the highest upregulated genes during growth on EG versus glycolate or acetate. Moreover, eda and edd of the Entner–Doudoroff pathway were significantly upregulated on EG compared to glycolate. The functional significance of these adaptations in EG catabolism is unclear.
Characterization of ΔmadA and ΔmftC mutants
To validate the role of MadA and MFT in EG catabolism, we deleted each of madA and mftC and tested the growth of the mutants and their respective complemental strains on EG. The mutants were generated via homologous recombination, and their genotypes were verified using PCR (Fig. S3). Neither mutant grew on 30 mM EG or ethanol, but both grew normally on 30 mM acetate and glycolate (Fig. 5; Table 4). Complementation of madA and mftC using a plasmid vector restored growth on EG and ethanol (Fig. 5B and D). Finally, neither mutant was more sensitive to inhibition by glycolaldehyde or formaldehyde than the WT strain (Fig. S1E through H and S4). These results establish that madA is essential for growth on EG and ethanol and that catabolism of these alcohols is dependent on MFT. Moreover, it appears that MadA is not involved in metabolizing short-chain aldehydes such as glycolaldehyde.
Fig 5
TABLE 4
| WT | RHA1-EG | ΔmadA | ΔmadA-C | ΔmftC | ΔmftC-C | |
|---|---|---|---|---|---|---|
| Acetate | +++ | +++ | +++ | +++ | +++ | +++ |
| EG | + | +++ | - | + | - | + |
| Ethanol | ++ | ++ | - | ++ | - | ++ |
| Glycolate | ++ | ++ | ++ | ND | ++ | ND |
a
Symbols indicate comparative growth rates and densities among tested substrates: +++, high; ++, medium; +, low; -, no growth; ND, not determined.
To further elucidate the role of MadA in the catabolism of EG, we measured the ability of the madA deletion strain to consume EG (Fig. 7A through C) and glycolaldehyde (Fig. 6A and B). The deletion strain was unable to catabolize EG (Fig. 6B). Interestingly, the complemented strain catabolized EG at a faster rate than WT (Fig. 6C). Glycolaldehyde was transiently detected during catabolism of EG by both the WT and complement strains. Furthermore, the madA deletion strain catabolized glycolaldehyde at the same rate as WT RHA1 (Fig. 7A and B). These results indicate that MadA is involved in EG oxidation, but not in glycolaldehyde oxidation.
Fig 6
Fig 7
Role of the mad pathway in methanol catabolism
As noted above, the Mad pathway enables the growth of M. smegmatis on methanol (27), and the latter’s catabolism is initiated by the madA-encoded Mno (29). We therefore investigated the ability of RHA1 to grow on methanol. Attempts to grow RHA1 on M9G supplemented with up to 2% (~660 mM) methanol as sole substrate were not successful. However, RHA1 grew to higher cell densities on 5 mM acetate when the medium was further supplemented with 300 mM methanol (Fig. 8; Fig. S6). Conversely, the ΔmadA mutant did not grow to a higher cell density in media supplemented with methanol (Fig. 8). Complementation of the deletion strain with a plasmid vector harboring madA resulted in greater cell growth than wild type and the mutant strain (Fig. 8A and B). This conclusion was supported by CFU data (Fig. S5) and indicates RHA1 is able to utilize methanol for growth in a MadA-dependent fashion. Nevertheless, it is unclear whether RHA1 utilizes methanol as a carbon source or simply oxidizes it to extract reducing equivalents.
Fig 8
Adaption of RHA1 on EG
We next tested if RHA1 can be adaptively evolved to grow on higher EG concentrations, similar to what has been achieved in KT2440 (6). RHA1 was grown in batch culture using shake flasks and was successively transferred to M9G media amended with 30, 60, 90, 120, and 180 mM EG, respectively. This yielded the strain RHA1-EG, which grew at a rate of ~0.13 h−1 on 180 mM EG (Table 5). Furthermore, this strain grew at three times the rate of the WT strain on 30 mM EG, comparable to its growth rate on acetate, and attained ~50% higher growth yields (0.62 ± 0.03 vs 0.40 ± 0.04 mg cell dry weight (CDW)/mL; P < 0.002). Interestingly, the lag times of RHA1-EG on acetate or glucose were similar whether the cells were pre-grown on EG (10 h) or acetate (12 h) (Fig. S6). In contrast, the lag times of WT on acetate and glucose were approximately twice as long when pre-grown on EG (19 h) versus acetate (10 h) (Fig. S6). In shake flasks, the final OD600 of RHA1-EG cultures increased linearly with substrate concentration to 300 mM EG, which yielded an OD600 of 31.6 ± 0.7. On 600 mM EG, cultures attained an OD600 of ~34. However, the pH of the spent medium was very low, indicating that the buffering capacity of the medium had been exceeded.
TABLE 5
| RHA1 | RHA1-EG | |||
|---|---|---|---|---|
| Substrate | λ (h−1) | R2 | λ (h−1) | R2 |
| 10 mM glucose | 0.24 ± 0.02 | 0.96 | 0.25 ± 0.01 | 0.99 |
| 60 mM acetate | 0.16 ± 0.01 | 0.98 | 0.17 ± 0.01 | 0.96 |
| 60 mM EG | NDb | 0.16 ± 0.02 | 0.98 | |
| 120 mM EG | ND | 0.15 ± 0.03 | 0.90 | |
| 180 mM EG | ND | 0.13 ± 0.02 | 0.91 | |
a
Growth rate, λ, was calculated from the linear portion of a plot of ln(OD600) vs t for 150 µl cultures in 96-well plates, 30°C. R2 values indicate the goodness of fit. Values represent means of biological replicates (n = 3) ±standard error. Cultures were pre-grown on 15 mM EG.
b
ND, not determined.
We also tested growth of RHA1-EG on glycolate, glycolaldehyde, and glyoxal. Like the WT strain, RHA1-EG grew at a reduced rate on 15 mM glycolate and to half the OD600 as on 15 mM acetate (Fig. S1B). Furthermore, the growth yields of the two strains on 30 mM glycolate were comparable (0.15 mg CDW/mL). Moreover, glyoxal inhibited growth of RHA1-EG to a similar extent as RHA1 (Fig. S1D). However, RHA1-EG tolerated 50% higher concentrations of glycolaldehyde than did WT RHA1 (Table 2; Fig. S1F). RHA1-EG also tolerated higher concentrations of formaldehyde (Table 2), growing in the presence of 3 mM formaldehyde, while WT did not grow in the presence of 2 mM formaldehyde (Figure S1G and H). Finally, the adaptive laboratory evolution did not affect the strain’s growth on acetate or glucose (Table 5; Fig. S6). Moreover, the growth rates and yields were not affected by the substrate used to grow the inoculating culture (i.e., acetate vs EG). Glycerol stocks of this strain grew at similar rates on 60, 120, or 180 mM EG regardless of the growth substrate used in the starter culture, although lag times were shorter when the cells were pre-grown on EG (data not shown).
Elucidating the basis of improved growth of RHA1-EG
To elucidate the basis of the improved growth of RHA1-EG, we compared the transcriptomes of the strain grown on EG with that of the WT strain (Fig. 2). Comparison of the transcriptomes of the two strains growing on EG revealed 180 downregulated but no upregulated genes. However, compared to the transcriptomes of the WT strain grown on acetate and glycolate, 116 and 183 genes, respectively, were upregulated in the transcriptome of EG-grown RHA1-EG (Table S2). None of these included any of the Mad, GCL1, or GCL2 pathway genes. However, the upregulated genes included a cluster on plasmid pRHL1 spanning RHA1_RS39745 to RHA1_RS39775 (Table S3). This cluster includes RHA1_RS39755, annotated here as aldA2, whose product shares 66% amino acid sequence identity with PedI (PP_2680) and AldB-I (PP_0545), enzymes from KT2440 that have glycolaldehyde dehydrogenation activity (12). Intriguingly, AldA2 differs by a single amino acid from AldA1 whose gene, RHA1_RS29725, is part of a putative operon that sits immediately downstream of the mft operon (Table 3). AldA1 and AldA2 are likely isofunctional.
To test the hypotheses that AldA2 catalyzes glycolaldehyde dehydrogenation and that its activity can improve the growth of RHA on EG, we overexpressed aldA2 in RHA1 using pTipQC2. Similar to RHA1-EG, the strain overexpressing aldA2 grew on 30 mM EG (Fig. S7A and B) and its growth on acetate was not inhibited by 5 mM glycolaldehyde (Fig. S7C and D). However, the strain’s growth was inhibited by 1 mM formaldehyde (Figure S7E and F). When grown on EG, RHA1-EG accumulated approximately 50% of the glycolaldehyde relative to wild type (Fig. 6D). Interestingly, the strain overexpressing aldA2 did not detectably accumulate any glycolaldehyde when grown on EG (Fig. 6E). Furthermore, when grown on glycolaldehyde, RHA1-EG and the aldA2 overexpressor depleted glycolaldehyde at faster rates than wild type (Fig. S5C and D). These results indicate that AldA2 plays a role in glycolaldehyde catabolism and that the overexpression of aldA2 may contribute to the growth phenotype of RHA1-EG.
DISCUSSION
Our study establishes that MadA is an MFT-dependent alcohol dehydrogenase that initiates the catabolism of EG in RHA1 (Fig. 9). Transcriptomic studies revealed that madA and the mft biosynthetic genes were upregulated during growth on EG. Targeted gene deletion studies then established that each of madA and a key MFT biosynthesis gene, mftC, is required for the initial transformation of EG to glycolaldehyde, but not for the latter’s subsequent catabolism. The RNA-seq data further suggest that EG is eventually oxidized to glycolate, which feeds into the tricarboxylic acid cycle (TCA) cycle via a pathway encoded by two Gcl clusters, GCL1 and GCL2, which appear to be largely redundant. Interestingly, only GCL2 encodes a homolog of GlcD, predicted to oxidize glycolate to glyoxylate. However, the other pathway enzymes are encoded by both clusters and are predicted to transform glyoxylate into 2-phosphoglycerate, which feeds into glycolysis. It is not clear why all the allantoin catabolic-related genes were upregulated during growth on EG. Overall, this catabolic pathway (Fig. 9) is remarkably similar to that in P. putida in which EG catabolism is initiated by a PQQ-dependent dehydrogenase (5, 12). As noted in the Introduction, the biosynthesis, structure and function of PQQ are similar to those of MFT (31).
Fig 9
The current study does not definitively identify the second enzyme of the pathway, glycolaldehyde dehydrogenase. However, several lines of evidence indicate that this enzyme is AldA1, an apparent isofunctional paralog of AldA2 (99.6% amino acid sequence identity). As noted above, aldA1 is located in a putative operon immediately downstream of the mft operon. Moreover, overproduction of AldA2 increased the rate of glycolaldehyde consumption (Fig. 7D), reduced accumulation of glycolaldehyde during growth of RHA1 (Fig. 6E) on EG, and improved the growth of RHA1 on EG. AldA1 and AldA2 share 66% amino acid sequence identity with PedI and AldB-I, enzymes from KT2440 that catalyze glycolaldehyde dehydrogenation (12). Finally, a close homolog of the two RHA1 paralogs, AldhR (95% amino acid sequence identity), is a broad-specificity aldehyde dehydrogenase that catalyzes formaldehyde dehydrogenation in R. erythropolis UPV-1 (55). Nevertheless, other than madA and madD, the only gene in RHA1 predicted to encode an aldehyde dehydrogenase involved in the catabolism of two-carbon compounds that was significantly upregulated on EG versus acetate was RHA1_RS02195 (Fig. S2). The encoded protein shares 85% amino acid sequence identity with Adh1, a dehydrogenase involved in the metabolism of 2-propanol and other small secondary alcohols in Gordonia sp. strain TY-5 (56). It is unclear whether RHA1_RS02195 contributes to growth of RHA1 on EG.
The apparent inability of RHA1 to grow on methanol as sole substrate is in striking contrast to M. smegmatis’s ability to do so using a very similar Mad pathway (27, 30). This could be due to differences in the respective Mad pathways of these bacteria or the metabolism of formaldehyde, a toxic catabolite produced of methanol. Notably, Mno, the homolog of MadA in M. smegmatis, catalyzes the dismutation of formaldehyde (27). Given that Mno and MadA share 92% amino acid sequence identity, it seems likely that MadA also possesses this activity. Nevertheless, the ΔmadA mutant depleted glycolaldehyde at the same rate as WT RHA1 (Fig. 7A and B), suggesting that MadA does not significantly contribute to aldehyde catabolism under physiological conditions. Finally, it is noted that genes encoding multiple formaldehyde metabolic pathways, including a mycothiol-dependent pathway and two copies of the ribulose-monophosphate pathway (RuMP), were upregulated during growth of RHA1 on EG versus acetate (Fig. 2) suggesting that this strain is well-adapted to detoxifying formaldehyde. Further work is required to determine why RHA1 is unable to grow on methanol as sole substrate.
The adaptive laboratory evolution of RHA1 to grow on higher EG concentrations is similar to what has been achieved in KT2440 (5, 6). In KT2440, this adaptation was explained by an improved metabolic flux of EG in the mutant resulting in lower accumulation of toxic intermediates and higher levels of reducing equivalents from EG (5, 6). The improved growth of RHA1-EG on EG appears also to be due to the improved flux of EG as suggested by the approximately 50% reduction in the accumulation of glycolaldehyde relative to wild type (Fig. 7D) and the faster rate at which RHA1-EG depleted glycolaldehyde (Fig. 7C). Notably, similar phenotypes were observed in RHA1 overexpressing aldA2 (Fig. 7E). Importantly, the similar growth rate of RHA1-EG on acetate and glucose compared to that of WT RHA1 indicates that the mutation(s) of RHA1-EG are specific to the metabolism of EG and not a general growth adaptation (Fig. S6). Interestingly, the lag times of the WT on acetate and glucose were longer when cells were precultured using EG, which was not the case for adapted strain (Fig. S6). Nevertheless, this adaption is not simply overproduction of AldA2 given that RHA1-EG tolerates higher concentrations of formaldehyde than the strain overexpressing aldA2 (Table 5; Fig. S1G and H). In this respect, it is noted that the mft genes were upregulated two- to threefold higher in RHA1-EG compared to RHA1, suggesting that adaptation of RHA1-EG may involve an MFT-dependent system.
Overall, this study provides insights into the bacterial catabolism of small alcohols and aldehydes. More particularly, elucidating the EG pathway in RHA1 and demonstrating the viability of adaptive laboratory evolution in this strain facilitate the engineering of Rhodococcus for the upgrading of EG-containing waste streams. This work should also facilitate the development of rhodococcal biocatalysts to upcycle PET given the robust growth of strains, such as RHA1, on terephthalate and the ease with which they may be engineered to produce valuable oleochemicals (16, 17, 57). More generally, the increased tolerance of RHA1-EG and the aldA2 overexpression strain for small aldehydes suggest strategies for developing the biocatalytic potential of rhodococci for a variety of feedstocks.
ACKNOWLEDGMENTS
This study was supported by a grant from the Natural Sciences and Engineering Research Council of Canada (DG 171359). M.E.W. is a recipient of a Canada Graduate Scholarship—Doctoral. L.D.E. is a recipient of a Canada Research Chair.
Much of the data presented in this paper was published in a PhD dissertation several years ago (58). Very recently, Shimizu et al. described the MFT-dependent catabolism of EG in RHA1 (34). In their work, Shimizu et al. demonstrated that targeted deletion of any one of madA (egaA in their study), mftAB, aldA1 (aldA in their study), or glcD resulted in loss of growth on EG. In addition, the authors detected activities for glycolaldehyde dehydrogenase, glycolate dehydrogenase, and D-glycerate dehydrogenase in extracts of cells grown on EG. Ultimately, the authors proposed the same pathway for EG catabolism presented here as well as largely in the PhD dissertation (58).
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Information & Contributors
Information
Published In
Applied and Environmental Microbiology
Volume 90 • Number 7 • 24 July 2024
eLocator: e00416-24
Editor: Marina Lotti, University of Milano-Bicocca, Milan, Italy
PubMed: 38837369
Copyright
© 2024 American Society for Microbiology. All Rights Reserved.
History
Received: 11 March 2024
Accepted: 14 May 2024
Published online: 5 June 2024
Keywords
Data Availability
RNA-seq data are deposited and openly available at the National Center for Biotechnology Information (NCBI) database under accession numbers GSE261336, GSM8140739, GSM8140740, GSM8140741, GSM8140742, GSM8140743, GSM814044, GSM814045, GSM814046, GSM814047, GSM8140748, GSM8140749, and GSM8140750.
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Marina Lotti
Editor
University of Milano-Bicocca, Milan, Italy
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The catabolism of ethylene glycol by Rhodococcus jostii RHA1 and its dependence on mycofactocin. Appl Environ Microbiol
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