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Water Research X 16 (2022) 100152
Available online 4 August 2022
2589-9147/© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Microbial paracetamol degradation involves a high diversity of novel
amidase enzyme candidates
Ana B. Rios-Miguel
a
,
*
, Garrett J. Smith
a
, Geert Cremers
a
, Theo van Alen
a
, Mike S.M. Jetten
a
,
b
,
Huub J.M. Op den Camp
a
, Cornelia U. Welte
a
,
b
,
*
a
Department of Microbiology, Radboud University, Radboud Institute for Biological and Environmental Sciences, Heyendaalseweg 135, Nijmegen 6525 AJ, the
Netherlands
b
Soehngen Institute of Anaerobic Microbiology, Radboud University, Heyendaalseweg 135, Nijmegen 6525 AJ, the Netherlands
ARTICLE INFO
Keywords:
Amidase evolution
Deaminase
Dioxygenase
Metagenomics
Mobile genetic elements
Pseudomonas
ABSTRACT
Pharmaceuticals are relatively new to nature and often not completely removed in wastewater treatment plants
(WWTPs). Consequently, these micropollutants end up in water bodies all around the world posing a great
environmental risk. One exception to this recalcitrant conversion is paracetamol, whose full degradation has
been linked to several microorganisms. However, the genes and corresponding proteins involved in microbial
paracetamol degradation are still elusive. In order to improve our knowledge of the microbial paracetamol
degradation pathway, we inoculated a bioreactor with sludge of a hospital WWTP (Pharmalter, Delft, NL) and
fed it with paracetamol as the sole carbon source. Paracetamol was fully degraded without any lag phase and the
enriched microbial community was investigated by metagenomic and metatranscriptomic analyses, which
demonstrated that the microbial community was very diverse. Dilution and plating on paracetamol-amended
agar plates yielded two Pseudomonas sp. isolates: a fast-growing Pseudomonas sp. that degraded 200 mg/L of
paracetamol in approximately 10 h while excreting 4-aminophenol, and a slow-growing Pseudomonas sp. that
degraded paracetamol without obvious intermediates in more than 90 days. Each Pseudomonas sp. contained a
different highly-expressed amidase (31% identity to each other). These amidase genes were not detected in the
bioreactor metagenome suggesting that other as-yet uncharacterized amidases may be responsible for the rst
biodegradation step of paracetamol. Uncharacterized deaminase genes and genes encoding dioxygenase enzymes
involved in the catabolism of aromatic compounds and amino acids were the most likely candidates responsible
for the degradation of paracetamol intermediates based on their high expression levels in the bioreactor meta-
genome and the Pseudomonas spp. genomes. Furthermore, cross-feeding between different community members
might have occurred to efciently degrade paracetamol and its intermediates in the bioreactor. This study in-
creases our knowledge about the ongoing microbial evolution towards biodegradation of pharmaceuticals and
points to a large diversity of (amidase) enzymes that are likely involved in paracetamol metabolism in WWTPs.
1. Introduction
Hundreds of pharmaceutical compounds are being detected at low
concentrations in water bodies all around the world posing a severe risk
to the environment and to human health (Gavrilescu et al., 2015; Wil-
kinson John et al., 2022). The consumption of medication and personal
care products will most likely increase in the future. Therefore, there is
an urgent need to develop new technologies able to remove these
chemicals at low concentrations before reaching the environment. Until
now, cost-efcient removal of common pollutants (i.e.
ammonium-nitrogen) has been achieved using microorganisms in
wastewater treatment plants (WWTPs). As large-scale use of
Abbreviations: WWTP, wastewater treatment plant; MBR, membrane bioreactor; GAC, granular activated carbon; APAP, N-acetyl-p-aminophenol or paracetamol;
4-AP, 4-aminophenol; HQ, hydroquinone; HRT, hydraulic retention time; SRT, solid retention time; Pfast, Pseudomonas sp. isolate growing fast on APAP as sole
carbon source; Pslow, Pseudomonas sp. isolate growing slow on APAP as sole carbon source; HGT, horizontal gene transfer; MAG, metagenome-assembled genome;
TPM, transcripts per million.
* Corresponding authors at: Department of Microbiology, Radboud University, Radboud Institute for Biological and Environmental Sciences, Heyendaalseweg 135,
Nijmegen 6525 AJ, the Netherlands.
E-mail addresses: a.riosmiguel@science.ru.nl (A.B. Rios-Miguel), c.welte@science.ru.nl (C.U. Welte).
Contents lists available at ScienceDirect
Water Research X
journal homepage: www.sciencedirect.com/journal/water-research-x
https://doi.org/10.1016/j.wroa.2022.100152
Received 13 May 2022; Received in revised form 13 July 2022; Accepted 3 August 2022
Water Research X 16 (2022) 100152
2
pharmaceuticals has only recently resulted in discharge to many
different environments, the metabolic pathways of their conversion (at
relatively low concentrations) might not have evolved yet or might not
be very efcient.
Acetaminophen (N-acetyl-p-aminophenol, APAP), more commonly
known as paracetamol, is one of the most consumed analgesic drugs
worldwide (Wu et al., 2012). Consequently, its concentration in waste-
water and surface waters is among the highest of all pharmaceutical
micropollutants. APAP concentration can reach more than 100 µg/L in
WWTP inuents and more than 100 ng/L in rivers (Kanama et al., 2018;
Wilkinson et al., 2022; Wu et al., 2012; Watson database - https://data.
emissieregistratie.nl/watson). Unlike many other pharmaceuticals,
APAP is degraded by microorganisms and is often well removed in
WWTPs. Several microorganisms have been related to APAP degrada-
tion in activated sludge and soil samples (i.e. Penicillium, Pseudomonas,
Flavobacterium, Dokdonella, Ensifer, Delftia) (Hart and Orr, 1974; Palma
et al., 2018; Park and Oh, 2020a; b; Rios-Miguel et al., 2021; ˙
Zur et al.,
2018a). However, the genomes of these microorganisms have not yet
been reported and therefore, the responsible genes and mechanisms for
APAP biodegradation in WWTPs are not yet known.
4-Aminophenol (4-AP) and hydroquinone (HQ) have been measured
in several APAP biodegradation experiments (Park and Oh, 2020a; b;
Zhang et al., 2013). Consequently, an aryl acylamidase, a deaminase,
and hydroquinone 1,2-dioxygenase were proposed as enzymes poten-
tially involved in the biodegradation pathway of APAP (Grignet et al.,
2022; Lee et al., 2015; ˙
Zur et al., 2018b). In fact, ve amidases have been
shown to transform APAP to 4-AP or to a brown compound (Supple-
mentary Table S1) (Chen et al., 2016; Ko et al., 2010; Lee et al., 2015;
Yun et al., 2017; Zhang et al., 201220202019). Besides, 1,2,4-trihydrox-
ybenzene could be an intermediate of APAP degradation since it was
measured in a Burkholderia sp. degrading 4-AP (Takenaka et al., 2003).
Despite this knowledge, the exact genes/enzymes that microorganisms
are using for APAP biodegradation in the environment are currently
unknown.
To ll this gap, we analyzed the APAP-degrading microbial com-
munity from a hospital WWTP by metagenomics and metatran-
scriptomics. Furthermore, we were able to isolate two Pseudomonas
species from the bioreactor that were capable of growing on APAP. Our
aim was to identify the genes involved in APAP biodegradation and
determine the genomic location and organization of these genes (clus-
ters) in different microorganisms. These results will help to understand
the evolution of microbial metabolism towards biodegradation of
pharmaceuticals and will provide molecular biomarkers to screen en-
vironments for APAP-degrading microorganisms.
2. Methods
2.1. Sampling and bioreactor set-up
Biomass was obtained from a membrane bioreactor (MBR) and a
granular activated carbon (GAC) process at the Pharmalter WWTP in
Delft, the Netherlands, on 1-2-2021. This plant treats wastewater and
solid waste from the Reinier de Graaf hospital, in Delft, and consists of
an anaerobic-anoxic-oxic MBR, an ozonation tank, and a GAC treatment
(https://www.stowa.nl/publicaties/evaluation-report-pharmalter). A
laboratory-scale membrane bioreactor (1.5 L) was inoculated with 15
mL of the MBR biomass and 15 mL of the GAC biomass. The same
inoculum was autoclaved for 20 min at 121 ◦C and incubated with 50
mg/L of APAP to investigate its adsorption to biomass. The sludge
without heat inactivation was also tested in the experiment. The lab-
scale membrane and bioreactor vessel were built at Radboud Univer-
sity technical center. The bioreactor appliances were from Applikon
Biotechnology B.V. (Delft, The Netherlands). The membrane consisted
of an integral immersed Zenon ZW-1 module with 0.04 µm pore-sized
hollow bers from Suez Water Technologies & Solutions (Feasterville-
Trevose, USA). It was never backwashed or replaced during the
experiment. The bioreactor was fed with synthetic medium containing
0.05-0.4 g/L APAP (Merck, ≥99.0%, Darmstadt, Germany) as sole car-
bon source, 0.2 g/L K
2
HPO
4
, 0.1 g/L KH
2
PO
4
, 0.06 g/L NH
4
Cl, 0.01 g/L
MgSO
4
x 7 H
2
O, 0.01 g/L CaCl
2
, and trace elements solution (Rios-Mi-
guel et al., 2021). Since APAP was degraded very fast, the organic
loading rate was increased over the rst 38 days from 0.022 to 0.227 mg
APAP/min. This was done by increasing the concentration of APAP in
the medium to 400 mg/L and by reducing the hydraulic retention time
(HRT) from 2.4 to 1.8 d (Fig. 1). When bacterial growth became expo-
nential, the solid retention time (SRT) was set to 10 d to reach a steady
state. After about 90 d, the HRT was set to 3.7 d to determine the mi-
crobial community changes at lower APAP loading rates (Fig. 1).
Furthermore, the bioreactor was run in the dark at constant 500 rpm
stirring, a pH value of 7, an airow rate of 30 ml/min, and room tem-
perature (20 ±1 ◦C). A pH sensor was connected to a controller that
activated a KHCO
3
base pump to keep the pH stable at 7.
2.2. Bioreactor monitoring: total suspended solids, paracetamol, 4-ami-
nophenol, and hydroquinone concentration, DNA and RNA sequencing
Total suspended solids (TSS) were regularly measured by passing 30
mL of the sample through a 0.45 µm pore size glass-ber lter which was
dried overnight at 105 ◦C. Samples (2 mL) were taken regularly from the
bioreactor in triplicates, centrifuged, and stored at -20 ◦C (both super-
natant and pellet) until APAP, 4-AP, HQ, and DNA analysis. APAP, 4-AP,
and HQ were measured in the supernatant using an HPLC-UV (Agilent
Technologies 1000 series, injection volume of 100 µL; a mobile phase of
acetate 1%: methanol (9:1); ow rate 1200 µl/min; and a C18 reverse-
phase column: LiChrospher® 100 RP-18 (5 µm) LiChroCART® 125-4,
12.5 cm ×4 mm, Merck, Darmstadt, Germany). The retention times of
APAP, 4-AP, and HQ were 4.4, 1.7, and 2.3 min, respectively. Further-
more, APAP concentration was measured at a wavelength of 249 nm,
and 4-AP and HQ at 280 nm. DNA was extracted from the pellets using
the DNeasy PowerSoil Kit (Qiagen Benelux B.V.) following manufac-
turer’s instructions. The samples were submitted to Macrogen (Seoul,
South Korea) for amplicon sequencing of the V3 and V4 regions of the
bacterial 16S rRNA gene (primers Bac341F and Bac785R (Klindworth
et al., 2013)) using an Illumina MiSeq. Six samples of 30 mL were taken
at day 77 (two weeks after SRT was set to 10 d and the bioreactor was in
a steady state). Three samples were centrifuged and stored at -20 ◦C for
DNA sequencing and the other three were frozen in liquid nitrogen and
stored at -80 ◦C for RNA sequencing. DNA was extracted using the
DNeasy PowerSoil Kit (Qiagen Benelux B.V.) and sequenced at Base-
Clear (Leiden, The Netherlands). RNA was extracted using the RNeasy
PowerSoil Total RNA Kit (Qiagen Benelux B.V.) with an extra DNase
treatment from RibopureTM Kit (Thermo Fisher Scientic, Waltham,
MA USA). Ribosomal RNA was removed using the Microbexpress kit
(Life Technologies, Carlsbad, USA) and rRNA depleted samples were
submitted to Macrogen (Seoul, South Korea) for sequencing. DNA and
RNA samples were sequenced using Illumina Novaseq technology. All
DNA and RNA quantities were determined using the Qubit dsDNA/RNA
HS Assay Kit (Thermo Fisher Scientic, Waltham, MA USA) and a Qubit
uorometer (Thermo Fisher Scientic, Waltham, MA USA). Further-
more, DNA and RNA quality was checked with the Agilent 2100 Bio-
analyzer and the High sensitivity DNA/RNA kit (Agilent, Santa Clara,
USA).
2.3. Isolation and DNA/RNA sequencing of bacteria growing on
paracetamol
We performed serial dilutions of the bioreactor biomass in synthetic
medium (same as the bioreactor) with APAP as sole carbon source
(0.2–0.4 g/L). The biomass of the most highly diluted culture displaying
APAP biodegradation was plated on agar-solidied medium with APAP
as sole carbon source. This solid medium consisted of the bioreactor
synthetic medium, 0.4 g/L of APAP, and 1.5% w/v bacteriological agar
A.B. Rios-Miguel et al.
Water Research X 16 (2022) 100152
3
(VWR, Belgium). Brown and white colonies, designated as Pfast and
Pslow, respectively, were found in the agar plates. Both colonies were
used to inoculate bottles containing synthetic bioreactor medium with
200 mg/L APAP as sole carbon source. One milliliter of these cultures
was used as inoculum for triplicate-bottle experiments where APAP
biodegradation kinetics were measured and the DNA and RNA of the
bacteria were sequenced. DNA and RNA from both isolates were
extracted as described above, except for the Pfast DNA extraction for
ONT sequencing, which was performed at Baseclear with the Wizard
HMW DNA Extraction kit (Promega Benelux B.V., Leiden, The
Netherlands). The genome of the fast-growing isolate Pfast was
sequenced using Illumina Novaseq and ONT GridiON at Baseclear
(Leiden, The Netherlands). RNA of this isolate was sequenced using
Illumina Novaseq, also at Baseclear. Only one of the 3 RNA samples
could be sequenced. The genome and transcriptome of the slow-growing
isolate Pslow were sequenced using an in-house Illumina MiSeq. For
DNA library preparation the Nextera XT kit was used and for tran-
scriptomic library preparation, the TruSeq Stranded mRNA kit was used
according to the manufacturer’s instructions (Illumina, San Diego, USA).
All DNA and RNA quantications and quality checks were performed as
described above (Qubit and Bioanalyzer). For genomic DNA libraries,
300 bp paired-end sequencing was performed and for the tran-
scriptomes, 150 bp single-read sequencing was done, using the Illumina
Miseq sequencing machine (Illumina, San Diego, California). The raw
sequence data and metadata of the bioreactor and isolates have been
deposited at the read sequence archive (SRA) database of the NCBI
under the BioProject ID PRJNA831879.
2.4. Bioinformatic analysis
2.4.1. 16S rRNA gene sequencing data analysis
Analysis of the 16S rRNA sequencing output les was performed
within R version 3.4.1 (Team, 2013) using the DADA2 pipeline (Call-
ahan et al., 2016). Taxonomic assignment of the reads was up to the
species level when possible using the Silva non-redundant database
version 128 (Yilmaz et al., 2014). Count data were normalized to rela-
tive abundances. Data visualization and analysis were performed using
phyloseq and ggplot packages (McMurdie and Holmes, 2013; Wickham
and Wickham, 2007). Chao1, Simpson and Shannon diversity indices
were calculated using the estimate richness function of the phyloseq
package.
2.4.2. DNA assembly, binning, and annotation
The quality of the metagenome sequencing data was assessed using
FASTQC before and after quality processing. Quality-trimming, adapter
removal and contaminant ltering of Illumina paired-end sequencing
reads was performed using BBDuk (BBTools, DOE Joint Genome Insti-
tute, Lawrence Berkeley National Laboratory, USA). The DNA trimmed
reads were assembled using MetaSpades and aligned to the assembly
using BBMap to generate coverage information (Nurk et al., 2017). The
assemblies were binned using different binning algorithms (BinSanity,
CONCOCT, MaxBin 2.0, and MetaBAT 2) (Alneberg et al., 2014; Graham
et al., 2017; Kang et al., 2019; Wu et al., 2015). DAS Tool was used for
consensus binning (Sieber et al., 2018). GTDB-Tk was used to assign
taxonomy and CheckM was used to assess the quality of the bins or
metagenome-assembled genomes (MAGs) (Chaumeil et al., 2019; Parks
et al., 2015). Annotation was performed by Metascan (Cremers et al.,
2022 under revision). The annotation method was described previously
by in ’t Zandt et al. (2020), Poghosyan et al. (2020). Briey, genes were
called by Prodigal (Hyatt et al., 2010) and subsequent open reading
frames were annotated with HMMER (Eddy, 2009) and a set of
custom-made databases.
DNA sequencing data from the slow-growing isolate Pslow were
quality-checked and trimmed with BBDuk, assembled with MetaSpades
and annotated with Metascan. The DNA sample consisted of two ge-
nomes (a very minor contaminant) so we separated the contigs using
Maxbin 2.0. (Wu et al., 2015).
DNA Illumina reads from the fast-growing isolate Pfast were quality
controlled and trimmed using BBduk with minimum trim quality of 18
and length of 100. ONT reads were ltered to a minimum length of 3000
using BBtools utilities, and then were quality controlled and trimmed
using Porechop (https://github.com/rrwick/Porechop) with minimum
split read size of 3000. Illumina and ONT quality-trimmed reads were
assembled using Unicycler with a minimum length of 1000 in the
resulting. Metascan was used for annotation. Completion and contami-
nation scores of the Pslow and Pfast assemblies were estimated using
CheckM’s lineage workow. The whole-genome phylogenetic position
of both assemblies was inferred using GTDB-tk. If not specied, settings
were default.
2.4.3. Transcriptome analysis
The RNA reads were trimmed using Sickle and mapped with BBMap
(allowing 1% mismatch, BBtools) to the protein-coding genes of each
isolate or to the contigs of the whole metagenome. Then, transcripts per
million (TPM) were calculated in Excel for each gene in each sample:
rst, reads per kilobase were calculated (read counts divided by the
length of each gene in kilobases); second, the “per million” scaling factor
was calculated (sum of all the reads per kilobase in one sample divided
by one million); and third, TPM were calculated (reads per kilobase of
each gene divided by the “per million” scaling factor). Approximately,
Fig. 1. A: Total suspended solids in mg/L. Orange dots represent the time points when 16S rRNA genes were sequenced. The black arrow represents the time point
when whole-genome and transcriptome sequencing occurred. B: relative abundance of bacterial 16S rRNA genes in the inoculum and the bioreactor at several time
points. Batch sample represents the serial dilution of the bioreactor biomass in medium containing 400 mg/L of APAP. Abbreviations: HRT, hydraulic retention time;
SRT, solid retention time; APAP, paracetamol; MBR, membrane bioreactor; GAC, granular activated carbon; Mix, mixture of MBR and GAC.
A.B. Rios-Miguel et al.
Water Research X 16 (2022) 100152
4
the top 10% most highly expressed genes in each microorganism or bin
were considered as “highly-expressed”. The RNA coverage of each bin in
the metagenome was calculated or dened as the number of bases
mapped to the set of protein-coding genes from each bin divided by the
total number of bases in each bin. Amidase sequences were retrieved by
searching for “amidase”, “amidohydrolase”, and “amidotransferase”
terms in the annotated metagenome. The highly-expressed and
uncharacterized amidase sequences were aligned with Clustal Omega
(Higgins and Sharp, 1988) and MUSCLE (Edgar, 2004) and the phylo-
genetic trees were created with MEGA7 (Kumar et al., 2016) and
MEGA11 (Tamura et al., 2021) using the maximum likelihood algorithm
(Jones et al., 1992) and bootstrap analysis or the neighbor-joining
method to analyse the tree topology (Saitou and Nei, 1987).
3. Results and discussion
3.1. Bioreactor performance and bacterial community changes
A bioreactor was inoculated with sludge from a WWTP treating
hospital waste. APAP was added as the sole carbon source at all times
during the experiment and it was fully removed since the beginning
without lag phase. No transformation products were detected. To
discard the possibility of abiotic removal such as adsorption to biomass,
we measured APAP concentration in the presence of autoclaved sludge
or active biomass used in the bioreactor inoculum. While active biomass
removed 50 mg/L of APAP in 4 h, autoclaved biomass did not remove
APAP during the four days of the experiment (Supplementary Fig. S1).
The microbial community was very diverse and changed during the
different operational settings (Fig. 1). In the rst start-up phase, the total
suspended solids (TSS) gradually increased to about 1.1 g/L as all
biomass was retained in the bioreactor via a membrane module. The
HRT was 1.8 days. Under these conditions, the microbial community
was dominated by members of the families Chitinophagaceae, Hal-
iangiaceae, Phycisphaeraceae, Pseudomonadaceae, Saccharimonadaceae,
and Sphingobacteriaceae when compared to the inoculum mix. In the
second phase, a SRT of 10 days was maintained in order to keep the
biomass concentration (TSS) stable at a steady state. This led to a
decrease of the relative abundance of Pseudomonadaceae, Phyci-
sphaeraceae, and Sphingobacteriaceae while increasing Burkholderiaceae,
Chitinophagaceae, and Polyangiaceae. In the third phase, the HRT was
increased from 1.8 to 3.7 days resulting in a bacterial community
dominated by the heterotrophic bacteria Blastocatellaceae, Burkholder-
iaceae, and Chitinophagaceae. Nitrospiraceae were also enriched which
might be the result of growth on low concentration of residual ammo-
nium in the reactor. Overall, the alpha diversity (richness and evenness
of species) decreased over time in the bioreactor which corresponds to a
selection and enrichment process (Supplementary Fig. S2). The previ-
ously mentioned taxa are normally found in WWTPs due to their ability
to degrade organic matter or ammonium/nitrite (Nitrospira) (Morin
et al., 2020; Saunders et al., 2016). The presence of heterotrophs able to
degrade complex organic matter (i.e. Chitinophagaceae and Poly-
angiaceae) might indicate possible predation and biomass recycling in
the bioreactor (Petters et al., 2021). Furthermore, members of the
Pseudomonadaceae and Burkholderiaceae families have been reported to
degrade APAP and 4-AP, respectively (Park and Oh, 2020a; Takenaka
et al., 2003; ˙
Zur et al., 2018a).
3.2. Paracetamol degradation by two Pseudomonas spp. isolates
After serial dilutions of the bioreactor biomass, and plating the
highest dilution showing APAP removal on agar mineral medium with
APAP as sole carbon source, two Pseudomonas spp. were obtained
(Fig. 1B (Batch) and Fig. 2). APAP medium without inoculum did not
show APAP removal and both Pseudomonas isolates were not able to
grow on synthetic medium without APAP. Pseudomonas sp. Pfast
degraded 200 mg/L APAP in 10 h and converted it into 4-AP, which
precipitated in the medium as a dark-brown solid. Since 4-AP was pur-
chased as a white solid, we dissolved 4-AP in the bioreactor synthetic
medium without bacteria and observed a color change in the medium
and an abiotic removal due to precipitation (Supplementary Fig. S3).
Kim et al. (2017) observed that HQ was a white solid, but the formation
of a charge-transfer complex with quinone turned it into a dark solid.
Therefore, 4-AP might also be forming complexes that lead to its
coloration and precipitation. 4-AP might also be transformed by the
Pfast isolate much slower than APAP. HQ was also detected as an in-
termediate but in a much lower concentration than 4-AP (data not
shown). The other Pseudomonas sp., Pslow, degraded 200 mg/L APAP in
approximately 90 d without the accumulation of aromatic trans-
formation products. Since APAP was not degraded in the synthetic
medium without bacteria and it did not adsorb to autoclaved sludge
(Supplementary Fig. S1), we hypothesized that Pseudomonas Pslow
cleaved the aromatic ring. If the ring cleavage is a slow reaction, this
step might be coupled to the slow production of 4-AP after APAP amide
cleavage. In the Pfast isolate, this process might be imbalanced because
the formation of 4-AP is faster than the later ring cleavage reaction.
Previous studies showed that other Pseudomonas spp. are also able to
degrade APAP in a few hours (De Gusseme et al., 2011; Hu et al., 2013;
Park and Oh, 2020a; Zhang et al., 2013; ˙
Zur et al., 2018a). However, we
are not aware of reports describing bacteria that degrade APAP at low
rates.
3.3. Highly-expressed amidases in the two Pseudomonas spp. isolates
After DNA and RNA sequencing, a highly expressed gene cluster was
identied in the Pfast isolate that contained a putative amide transporter
(AmiS/UreI family, OACKLNDA_05759) and an amidase-like protein
Fig. 2. APAP biodegradation rates of two Pseudomonas spp. isolated from the bioreactor by serial dilutions and plating. A corresponds to the fast-growing Pseu-
domonas sp. Pfast and B to the slow-growing Pseudomonas sp. Pslow. Abbreviations: APAP, paracetamol; 4-AP, 4-aminophenol.
A.B. Rios-Miguel et al.
Water Research X 16 (2022) 100152
5
(OACKLNDA_05760) with 85% sequence identity to an aryl acylamidase
known to convert APAP into 4-AP and acetate (Ko et al., 2010; Lee et al.,
2015). The transporter might be catalyzing the uptake of APAP or the
excretion of 4-AP. The genome of the Pslow isolate contained neither
this amidase nor the putative amide transporter. Instead, it encoded
three other amidases with ≥95% query coverage and 28–31% identity
to the Psfast amidase. The most similar amidase (31% identity,
BKDBLJDL_05334) was upregulated in the transcriptome of strain Pslow
cultivated with APAP as the sole carbon source. This amidase was
encoded in a gene cluster together with a gene for a zinc-dependent
hydrolase (BKDBLJDL_05335). Interestingly, these genes were also
present in the fast-growing Pseudomonas isolate, but not highly
expressed. The difference in APAP biodegradation rate and conse-
quently, growth between both Pseudomonas spp. was most likely related
to the presence of OACKLNDA_05760 amidase in Pfast, which might be
able to transform APAP to 4-AP at high rates. Another option could be
that the putative amide transporter OACKLNDA_05759 was involved in
a faster uptake of APAP and thus, transformation into 4-AP. Further
studies are needed to answer this question.
The highly expressed amidase gene of strain Pslow was present in the
chromosome of numerous Pseudomonas species registered in the NCBI
nucleotide collection. However, the highly expressed amidase gene from
strain Pfast was only found in a few microorganisms that came from
various locations around the world (Australia, China, Pakistan, India,
Korea, India, Poland): in the plasmid of multi-drug resistant Acineto-
bacter spp. isolated from patients and hospitals (Ghaly et al., 2020;
Kizny Gordon et al., 2020; Zou et al., 2017); and in the chromosome of
Pseudomonas and Burkholderia spp. isolated from soil, activated sludge,
and hospitals (D’Souza et al., 2019; Ko et al., 2010; Patil et al., 2017; ˙
Zur
et al., 2018b). Many bacteria contained a similar AmiS/UreI family
transporter gene next to the amidase gene and different mobile genetic
elements nearby (Tn3 transposons, IS630 insertion sequences and IntI1
integrases). Our strain, Pfast, also had two insertion sequences (IS6100
and IS21, OACKLNDA_05756, OACKLNDA_05781), one Tn3 transposase
gene (OACKLNDA_05752), and one recombinase gene
(OACKLNDA_05755) near the highly-expressed amidase gene. Conse-
quently, the whole gene cluster might have been exchanged between
different species via horizontal gene transfer (HGT) (Rios Miguel et al.,
2020). Finally, the low number of homologous proteins in the NCBI
database might indicate the recent evolution of this amidase towards
paracetamol biodegradation or our limited ability to nd and identify
these genes.
3.4. Amidase diversity in the metagenome
To check and conrm whether the bioreactor microbial community
contained more unidentied amidases involved in APAP and
intermediate conversion, we analyzed the total metagenome at opera-
tional day 77. Before analyzing the amidase genes, 14 MAGs were
recovered from the bioreactor metagenome and approximately 30% of
the total reads remained unbinned. The binning process and taxonomy
assignment is a required step before the analysis of genes of interest
because it allows the linkage of these genes to a specic microbial
genome from the metagenome. Table 1 shows the 14 recovered MAGs
ordered from highest to lowest coverage based on RNA sequencing data
(calculated with RNA bases mapped to protein-coding genes). Chitino-
phagaceae and Myxococcales were the most active (RNA coverage) bac-
teria and also the most abundant (DNA coverage) together with
Microbacterium and Patescibacteria. Despite the high abundance of the
Patescibacteria MAG, it had low completeness. The reason for this might
be that the single copy genes normally used to calculate completeness
are often not detected in Patescibacteria genomes (Brown et al., 2015).
Pseudomonas spp. were low abundant in the metagenome and only
present in the unbinned reads.
The highest BLAST identity match of the Pfast amidase was 50% for
proteins encoded on the unbinned contigs. The 14 MAGs only contained
amidases with a maximum of 30% sequence identity. For the Pslow
isolate, the highest match was 50% for proteins encoded on the unbin-
ned contigs as well as the Rubrivivax and Betaproteobacteria MAGs. Since
the APAP concentration was below the detection limit (~0.2 mg/L) in
the bioreactor, but continuously supplied with the medium inow,
uncharacterized amidases might be responsible for APAP biodegrada-
tion at low concentrations in the bioreactor.
A phylogenetic tree was created with the top 150 most expressed
amidases in the metagenome, the uncharacterized amidases (enzymes
annotated as “amidase” and whose function is not known) present in
both Pseudomonas isolates, and ve amidases known to degrade APAP
obtained from literature and databases (Supplementary Fig. S4, Sup-
plementary Table S1). All the uncharacterized amidases from the met-
agenome and the Pseudomonas isolate genomes clustered together
(green cluster in Supplementary Fig. S4), including four amidases
known to degrade paracetamol (Ko et al., 2010; Lee et al., 2015; Yun
et al., 2017; Zhang et al., 201220202019). This group belongs to the
Amidase Signature (AS) enzyme family [EC:3.5.1.4] characterized by a
highly conserved signature region of approximately 160 amino acids
that includes a canonical catalytic triad (Ser-cisSer-Lys) and a
Gly/Ser-rich motif (GGSS[GS]G). One amidase (AGC74206.1 dimeth-
oate hydrolase DmhA), previously reported to degrade APAP (Chen
et al., 2016), did not cluster in this group (Supplementary Fig. S4).
Consequently, there is the possibility that other amidase families are
also able to transform APAP. For instance, a histone deacetylase-like
amidohydrolase clustered together with the APAP-degrading amidase
DmhA, suggesting its reactivity towards APAP.
The green AS amidase cluster of the phylogenetic tree in
Table 1
Metagenome-assembled genomes (MAGs) from the bioreactor at day 77. CheckM was used to check the quality of the MAGs. Taxonomy was assigned until the highest
level possible using GTDB-Tk. RNA coverage is the average of three replicate samples while DNA coverage is based on one sample.
MAG (metaspades +das_tool) Completeness (%) Contamination (%) Strain heterogeneity Genome size (Mbp) DNA coverage RNA coverage±SD
Chitinophagaceae_2; g_Niabella 98.2 0.7 0.0 3.4 51.4 15.5 ±4.2
Myxococcales_1; g_Haliangium 87.1 3.3 0.0 7.5 21.3 15.3 ±5.5
Bacteroidetes; f_Sphingobacteriaceae 98.7 1.0 100.0 3.2 9.7 5.4 ±1.8
Chitinophagaceae_1; g_Niastella 98.3 2.7 77.8 3.0 10.7 3.7 ±1.2
Patescibacteria;
f_Saccharimonadaceae
66.4 3.4 20.0 1.1 26.7 3.3 ±0.2
Microbacterium 100.0 0.0 0.0 3.5 27.0 2.8 ±1.1
Acidobacteria 97.4 3.7 0.0 4.7 11.1 2.1 ±0.4
Rubrivivax 80.2 40.0 12.4 6.4 7.1 1.6 ±0.5
Myxococcales_2; g_Haliangium 77.4 6.3 30.0 10.3 8.1 1.4 ±0.3
Alicycliphilus denitricans 98.1 1.6 69.2 4.8 16.6 1.4 ±0.4
Chitinophagaceae_3; g_Niabella 76.1 1.0 20.0 3.1 4.6 1.3 ±0.4
Betaproteobacteria; o_Burkholderiales 95.7 11.4 75.0 4.9 20.1 1.1 ±0.3
Actinomycetales; g_Nocardioides 54.8 2.3 0.0 2.0 4.5 0.8 ±0.5
Comamonadaceae 52.0 4.0 20.0 3.6 4.7 0.6 ±0.2
A.B. Rios-Miguel et al.
Water Research X 16 (2022) 100152
6
Supplementary Fig. S4 was analyzed in more detail (Fig. 3). The amidase
gene expression level in each bin/MAG was added to the tree (i.e. top
10%) and the amino acid sequences were manually blasted against the
NCBI non-redundant protein database to improve the annotation.
Furthermore, partial sequences like one highly-expressed amidase gene
from Betaproteobacteria (EAEDEFLN_03924) were removed from the
analysis. Twelve amidases were identied as “Asp-tRNA(Asn)/Glu-tRNA
(Gln) amidotransferase subunit GatA” and they all clustered together
(green cluster in Fig. 3). This type of amidase is involved in the trans-
formation of Glu-tRNA
Gln
to Gln-tRNA
Gln
for the synthesis of proteins.
Gene duplication and mutation events in this amidotransferase were
probably the key contributors to the high number of uncharacterized
amidases with broad substrate specicity.
Another cluster, with low bootstrap support, in the phylogenetic tree
of Fig. 3 contained highly-expressed amidases (top 10%) of the Pseu-
domonas genomes and the Microbacterium MAG (red amidases in Fig. 3,
Fig. 3. Phylogenetic tree of the Amidase Signature (AS) enzyme family [EC:3.5.1.4] proteins in the bioreactor and the Pseudomonas isolates. The evolutionary history
was inferred by using the Maximum Likelihood method (Jones et al., 1992). The tree with the highest log likelihood (-25739.55) is shown after bootstrapping 500
times. The percentage of trees in which the associated taxa clustered together is shown next to the branches. Evolutionary analyses were conducted in MEGA7
(Kumar et al., 2016). Amidases in blue are experimentally validated to degrade APAP. Amidases in red are the ones whose expression lies in the top 10% of all the
genes in the Pseudomonas isolate transcriptomes, and the metatranscriptomes of the bioreactor mapping to a metagenome-assembled genome in this study. Orange
amidases correspond to the amidase genes lying in the top 10% most expressed from the unbinned protein-coding genes. The green cluster corresponds to amidases
annotated as the Asp-tRNA(Asn)/Glu-tRNA(Gln) amidotransferase subunit GatA.
A.B. Rios-Miguel et al.
Water Research X 16 (2022) 100152
7
OACKLNDA_05760, BKDBLJDL_05334, BJLACCKG_02946). The Micro-
bacterium amidase only had 91% query coverage and 63% identity to the
closest amidase in the NCBI non-redundant protein database. This
means that this amidase was sequenced for the rst time and thus, the
evolution of amidases towards paracetamol biodegradation might be an
ongoing process. The Microbacterium amidase was part of a highly-
expressed gene cluster containing a avin reductase
(BJLACCKG_02944), an arylformamidase (BJLACCKG_02945), a
branched-chain amino acid ABC transporter (BJLACCKG_02947,
BJLACCKG_02948, BJLACCKG_02949, BJLACCKG_02950,
BJLACCKG_02951), and one oxidoreductase (BJLACCKG_02952).
Furthermore, an IS110 family transposase gene (BJLACCKG_02943) was
right next to this highly expressed gene cluster. Four amidases known to
degrade APAP were also part of the phylogenetic tree cluster containing
the highly-expressed amidases of the Pseudomonas genomes and Micro-
bacterium MAG (ANS81375.1 arylamidase Mah, ACP39716.2 aryl acy-
lamidase, ANB41810.1 tricocarban amidase TccA, AFC37599.1 aryl-
amidase A AmpA; blue amidases in Fig. 3). Three amidase genes pre-
sent on the unbinned contigs were highly expressed in relation to all the
unbinned protein-coding genes (top 10%, orange amidases in Fig. 3).
They were afliated with Actinomycetia and Comamonadaceae spp.
(KGEGGEOM_07080, KGEGGEOM_08489, KGEGGEOM_08132) and
might also be degrading APAP in the bioreactor. Non-highly-expressed
amidase genes might also have the potential to degrade APAP even
though their genes were not strongly regulated when APAP was present.
For instance, the non-highly-expressed amidase OACKLNDA_00714 of
the Pfast strain was identical to the highly-expressed amidase
BKDBLJDL_05334 of the Pslow strain, so it had the potential to degrade
APAP at slow rates but it was not highly-expressed in Pfast.
Finally, a multiple sequence alignment was performed with the
amidases known to degrade APAP (except for DmhA which is not part of
the AS family) and the highly expressed amidases from the Pseudomonas
genomes and the metagenome (Supplementary File 2). Lee et al.
previously determined the three-dimensional structure of the amidase
ACP39716.2 with APAP as a substrate (Lee et al., 2015). They revealed
several residues involved in catalysis and APAP binding that we inves-
tigated in our alignment. The aligned amidases contained a conserved
catalytic triad (Ser
187
-cisSer
163
-Lys
84
, highlighted in green),
Gly/Ser-rich motif (GGSSGG, in bold) and oxyanion hole ([G]GGS, in
bold). The substrate-binding pocket contained two loop regions (high-
lighted in fair and dark grey) and one
α
-helix (highlighted in blue) that
were less conserved. In the crystal structure of ACP39716, another two
residues (Tyr
136
and Thr
330
, highlighted in yellow) were described to
bind to the hydroxyl group at the para-position in APAP via hydrogen
bonds with two water molecules. However, Thr
330
was only present in
approximately half of the aligned amidase sequences and Tyr
136
was not
present in any of them. Thus, the amidases from this study might have
different substrate specicities compared to the ACP39716.2 amidase.
Furthermore, we conclude that Tyr
136
and Thr
330
are not strictly
necessary for APAP binding and degradation.
3.5. Paracetamol-degradation pathway: highly-expressed gene candidates
The rst step in APAP biodegradation is the cleavage of the amide
bond by an amidase to produce 4-AP and acetate (Fig. 4). In each
Pseudomonas genome, a different highly expressed amidase was identi-
ed presumably performing this cleavage (OACKLNDA_05760,
BKDBLJDL_05334). In the bioreactor metagenome, the Microbacterium
MAG was the only one with a highly expressed amidase inside the AS
family cluster (BJLACCKG_02946), from which four amidases were
previously reported to degrade APAP (Fig. 3). The Betaproteobacteria
MAG also had a highly expressed uncharacterized amidase gene (EAE-
DEFLN_03924). However, the nucleotide sequence was partial so we
could not check its classication. Therefore, Microbacterium (and Beta-
proteobacteria) might have been involved in transforming APAP into 4-
AP together with some low abundant bacteria in the unbinned group.
Fig. 4. Paracetamol degradation pathway by the bioreactor microbial community and the Pseudomonas isolates. The question marks represent candidate enzymes
and metabolites. Dashed lines correspond to conversions requiring more than one step. I paracetamol; II 4-aminophenol; III hydroquinone; IV hydroxyquinol or 1,2,4-
trihydroxybenzene; V 4-hydroxymuconic semialdehyde or 4-hydroxy-6-oxo-2,4-hexadienoic acid; VI 2,5-dihydroxy-6-oxo-2,4-hexadienoic acid; VII 3-hydroxy-cis,
cis-muconate or 3-hydroxy-2,4-hexadienedioic acid; VIII acetate; IX acetyl-CoA; TCA tricarboxylic acid.
A.B. Rios-Miguel et al.
Water Research X 16 (2022) 100152
8
An alternative rst step for APAP biodegradation could be its hydrox-
ylation to form 3-hydroxyacetaminophen, a metabolite measured in soil
by Li et al. (2014).However, due to the high concentration of 4-AP in the
Pseudomonas experiments, the cleavage of the amide bond might be the
dominant mechanism.
The enzyme deaminating 4-AP is still unknown and we did not nd
an obvious gene responsible for this reaction. Uncharacterized RidA
family protein genes were highly expressed in the two Pseudomonas
genomes and in the Microbacterium and Betaproteobacteria MAGs
(OACKLNDA_05815, OACKLNDA_03065, BKDBLJDL_03266,
BKDBLJDL_01320, BJLACCKG_02940, BJLACCKG_02936, EAE-
DEFLN_02051). Therefore, these proteins might have been involved in
deaminating 4-AP or deaminating the aminomuconate intermediates
after ring cleavage (He and Spain, 1998). Furthermore, two
ammonia-lyase genes were highly expressed in the genome of the Pslow
strain: aspartate ammonia-lyase and ethanolamine ammonia-lyase
(BKDBLJDL_01355, BKDBLJDL_02838). However, these genes were
not highly expressed in the Pfast genome and the metagenome from the
bioreactor.
The investigated bacteria did not use any known hydroquinone 1,2-
dioxygenase, which is a type III ring-cleaving extradiol dioxygenase
(cupin superfamily) with a catalytic mechanism analogous to that of the
extradiol-type dioxygenases. Instead, the up-regulated type III extradiol
dioxygenase genes present in bioreactor MAGs (Chitinophagaceae_1,2
and Betaproteobacteria: 3-hydroxyanthranilate 3,4-dioxygenase
(NLCKOFOF_01117, JPNLMFAJ_02227, EAEDEFLN_00964); Bacter-
oidetes, Rubrivivax, and Myxococcales_2: homogentisate 1,2-dioxygenase
(KGEBAGMN_02738, HFDFLMDG_05905, OPIJCCOK_08966)) might
have cleaved the aromatic ring of HQ to produce 4-hydroxymuconic
semialdehyde as previously described (˙
Zur et al., 2018b) (Fig. 4).
Homogentisate 1,2-dioxygenase and 3-hydroxyanthranilate 3,4-dioxy-
genase are type III extradiol dioxygenases able to cleave the aromatic
ring of non-catecholic substrates, which are characterized by not having
vicinal diols. For example, (homo)gentisate and hydroquinone have two
hydroxyl groups in para position and 3-hydroxyanthranilate has one
hydroxyl, one amino, and one carboxylic acid group as ring substituents.
These two dioxygenases are involved in the degradation of aromatic
amino acids. Therefore, bacteria might use the side activities of existing
enzymes to degrade aromatic micropollutants such as APAP.
The ring cleavage of aromatic compounds containing hydroxyl and
amino substituents (i.e. 2-aminophenol, 3-hydroxyanthranilate, and 5-
aminosalicylate) has been previously reported (Hintner et al., 2004;
Li de et al., 2013; Takenaka et al., 1997; Wang et al., 2020). Therefore,
the aromatic ring of 4-AP might also be cleaved before deamination by
class III ring-cleaving dioxygenases. However, metabolites conrming
this pathway have not yet been measured.
An alternative route for the direct ring cleavage of HQ is the hy-
droxylation of HQ to form hydroxyquinol (1,2,4-trihydroxybenzene)
and later, the ring cleavage of hydroxyquinol by an intradiol-type
dioxygenase (Ferraroni et al., 2005; Takenaka et al., 2003) or an
extradiol-type dioxygenase, probably from the vicinal oxygen chelate
(VOC) or type I superfamily (Murakami et al., 1999) (Fig. 4). Catechol
has been previously measured during APAP microbial degradation (Dai
et al., 2021; Ivshina et al., 2005) suggesting that it could be a trans-
formation product that is further cleaved by intradiol-type or
extradiol-type dioxygenases. The hydroxylation of HQ can be performed
by ring-hydroxylating dioxygenases or monooxygenases. In the Pfast
isolate genome, an uncharacterized ring-hydroxylating dioxygenase
(OACKLNDA_03401) and an intradiol catechol 1,2-dioxygenase
(OACKLNDA_05722) were highly expressed. Furthermore, two unchar-
acterized extradiol-type dioxygenases were highly expressed in both
Pseudomonas isolate genomes (OACKLNDA_01459, BKDBLJDL_01807).
These dioxygenases were similar to 4,5-DOPA dioxygenase, which is
part of the VOC extradiol dioxygenases (Wang et al., 2019). In the
bioreactor, the Rubrivivax MAG had a phenol hydroxylase
(HFDFLMDG_03468, HFDFLMDG_03467, HFDFLMDG_03466), an
uncharacterized ring-hydroxylating dioxygenase (HFDFLMDG_03024),
a 4-hydroxybenzoate 3-monooxygenase (HFDFLMDG_05635), and a
extradiol protocatechuate 4,5-dioxygenase (HFDFLMDG_01086,
HFDFLMDG_01087) highly expressed. The Microbacterium MAG con-
tained a highly-expressed VOC extradiol 3,4-dihydroxyphenylacetate
(homoprotocatechuate) 2,3-dioxygenase involved in the degradation
of tyrosine (BJLACCKG_03009). The Betaproteobacteria MAG had a pu-
tative ring hydroxylating dioxygenase (EAEDEFLN_00364), and a
4-hydroxyphenylpyruvate dioxygenase (EAEDEFLN_02889) able to hy-
droxylate and decarboxylate aromatic rings in the tyrosine degradation
pathway. Many other MAGs contained this gene up-regulated, i.e. Bac-
teroidetes, Comamonadaceae and Myxococcales_2 (KGEBAGMN_02075,
JMGBCLMB_02041, OPIJCCOK_08967). Finally, the Alicycliphilus MAG
had a highly expressed gene cluster containing an MFS transporter
(MDKLGIDK_02282), a tripartite tricarboxylate transporter substrate
binding protein (MDKLGIDK_02283), an muconolactone D-isomerase
(MDKLGIDK_02284), an 3-oxoadipate enol-lactonase
(MDKLGIDK_02285), a 1,6-dihydroxycyclohexa-2,4-diene-1-carboxy-
late dehydrogenase (MDKLGIDK_02286), an intradiol catechol 1,2-diox-
ygenase gene (MDKLGIDK_02287), and a muconate cycloisomerase
(MDKLGIDK_02288). This highly-expressed gene cluster suggests the
ability of Alicycliphilus to fully degrade hydroxyquinol via the oxoadi-
pate pathway. Interestingly, the Alicycliphilus MAG had hydroquinone
dioxygenase genes (MDKLGIDK_00653, MDKLGIDK_00654) that were
not highly expressed.
Acetyl-CoA synthetase genes and genes encoding enzymes involved
in the tricarboxylic acid (TCA) and glyoxylate cycles (isocitrate lyase)
were highly expressed in the transcriptome of both Pseudomonas spp.
and several MAGs (i.e. Microbacterium, Rubrivivax, Alycicliphilus, and
Actinomycetales), thus indicating their ability to grow on acetate after
cleaving the APAP amide bond or via cross-feeding from other bacteria
(Fig. 4). Finally, the highly-expressed gene encoding an uncharacterized
carboxymuconolactone decarboxylase family protein could be involved
in the conversion of muconolactone intermediates to eventually reach
the TCA cycle for bacterial growth in the Pseudomonas isolates
(OACKLNDA_03472, BKDBLJDL_01962). The Microbacterium, Rubri-
vivax, and Betaproteobacteria MAGs had highly-expressed dioxygenases
but they did not have up-regulated genes belonging to the β-ketoadipate
pathway, involved in the conversion of aromatic metabolites into TCA
intermediates. Therefore, it is unclear whether they were able to
assimilate aromatic compounds or not. Furthermore, the Rubrivivax and
Alicycliphilus MAGs did not have any highly-expressed amidase from the
AS family suggesting that cross-feeding of acetate and aromatic in-
termediates was happening in the bioreactor.
The Myxococcales family is known for its diverse metabolism and its
predatory nature, so the two bioreactor MAGs afliated to the Myx-
ococcales family might have lived from the metabolites and cellular
components of decaying microorganisms (Müller et al., 2016). Similarly,
the Chitinophagaceae family is known to degrade complex organic matter
and therefore, the three bioreactor MAGs afliated to the Chitinopha-
gaceae family could also have been biomass recyclers in the bioreactor
(Morin et al., 2020). The highest expressed metabolic genes of these
MAGs were involved in the TCA cycle, gluconeogenesis, and metabolism
of lipids, peptidoglycan, nucleotides, and amino acids, thus not
providing many hints about their exact catabolism or energy source.
Similarly, the metabolism of Bacteroidetes, Acidobacteria, Actino-
mycetales, and Comamonadaceae MAGs was ambiguous and they might
also be predators or biomass recyclers. In addition, we found that type II
and type IV secretion systems were highly expressed in several MAGs (i.
e. Acidobacteria, Comamonadaceae) which might have been involved in
predation, defense, and conjugation activities between microorganisms
(Aharon et al., 2021; Sgro et al., 2019). However, some of these MAGs
might also degrade APAP transformation products via their
highly-expressed dioxygenases (i.e. Chitinophagaceae_1_2, Bacteroidetes,
Myxococcales_2). The Patescibacteria MAG mostly contained genes
encoding carbohydrate degrading enzymes, so it might have thrived in
A.B. Rios-Miguel et al.
Water Research X 16 (2022) 100152
9
symbiosis with other microbial community members that produced
exopolysaccharides.
3.6. Highly-expressed nitrication and denitrication genes in the
bioreactor
The majority of the MAGs, except for Patescibacteria and Myx-
ococcales_1, had highly expressed genes encoding enzymes from the
denitrication pathway. All four genes encoding the full pathway of
denitrication could only be found in one MAG, afliated with Alicy-
cliphilus denitricans, as well as the in the unbinned contigs: nitrate
reductase, nitrite reductase, nitric oxide reductase, and nitrous oxide
reductase. The bioreactor was fully aerated, but biomass was spatially
organized in small granules (Supplementary Fig. S5), so there might
have been anoxic conditions towards the inside of the granules favoring
denitrication. Nitrate and nitrite were not added to the medium, so
nitrifying microorganisms were apparently also active in the bioreactor.
A single highly expressed ammonia monooxygenase (subunits A, B, C;
KGEGGEOM_12202, KGEGGEOM_12201, KGEGGEOM_12203) was
encoded in the unbinned contigs, and afliated with the complete
ammonia oxidizer (comammox) Nitrospira sp. This nding suggests that
some ammonia released from decaying biomass, from the paracetamol
degradation and from the ammonia supply in the medium intended for
assimilation (~1 mM) was converted into nitrate by comammox Nitro-
spira sp. and subsequently available for (oxygen-limited) denitrication.
4. Conclusions
On the basis of our cultivation and metagenomic analysis, we
conclude that APAP was immediately degraded by the activated sludge
of a hospital WWTP and that a diverse microbial community was
enriched under low APAP concentrations in a membrane bioreactor.
High APAP concentrations in batch led to the dominance of a fast-
growing Pseudomonas species. Several uncharacterized amidases from
the AS family were highly expressed in the genome of a fast- and a slow-
growing Pseudomonas species and the bioreactor metagenome. They
might be cleaving APAP into 4-AP at different rates. Genes encoding for
uncharacterized RidA family proteins were highly expressed in the
genome of the Pseudomonas isolates and several bioreactor MAGs. They
are known to have deaminase activity, so they might be converting 4-AP
to HQ or cleaving reactive enamine intermediates. Genes encoding for
intradiol- and extradiol-type dioxygenases were highly expressed in the
genomes of the Pseudomonas isolates and the bioreactor metagenome.
Many of these genes are part of the degradation pathway of aromatic
amino acids. Therefore, microorganisms might take advantage of the
side activities of existing enzymes encoded in their genomes for the
degradation of APAP transformation products. Candidate APAP-
degrading amidases, deaminases, and dioxygenases were not com-
bined in the same gene cluster. Highly expressed genes encoding ami-
dases were often found in the vicinity of mobile genetic elements, which
suggests that APAP-degrading amidase genes are currently being
exchanged between different bacteria via HGT.
Taken together, these results suggest a role of uncharacterized ami-
dases, deaminases and dioxygenases in the biodegradation of APAP and
the use of cross-feeding to efciently degrade APAP in WWTP microbial
communities. Furthermore, the high number of microorganisms able to
degrade APAP might be the result of the broad substrate spectrum of
amidases and its evolution, together with the fact that just one enzyme
(amidase) is needed to grow on APAP-derived acetate. This study con-
tributes to a better understanding of microbial evolution towards
pharmaceutical biodegradation and demonstrates the complexity of this
process due to the broad substrate spectrum of the involved enzymes.
Author contributions
ARM, MJ, HOdC, and CW contributed to the conceptual framework
of the manuscript. ARM conducted the experiments and data analysis.
GS, GC, and HOdC contributed to bioinformatics analyses. TvA per-
formed DNA and RNA Illumina sequencing of the slow-growing Pseu-
domonas. ARM wrote the manuscript with input from all the authors.
Data Availability
All raw sequencing data (DNA and RNA) have been deposited at the
read sequence archive (SRA) database of the NCBI under the BioProject
ID PRJNA831879. The amino acid sequences and annotation of all genes
in the metagenome and the Pseudomonas spp. genomes are deposited in
Dans Easy (https://doi.org/10.17026/dans-xwd-fbj5). This dataset also
contains the TPMs of the bioreactor and the Pseudomonas spp. tran-
scriptomes and the amino acid sequences of the amidase genes used to
create the phylogenetic trees in Fig. 3 and Supplementary Fig. S4.
Declaration of Competing Interest
The authors declare that they have no known competing nancial
interests or personal relationships that could have appeared to inuence
the work reported in this paper.
Acknowledgments
The authors thank Stefan Hertel and Erwin Koetse for letting us take
sludge from the MBR and GAC of Pharmalter. We also thank Rob de
Graaf for sharing his expertise with the HPLC and Guylaine Nuijten for
her help with bioreactors. This research was supported by NWO-TTW
grant 15759 and NWO/OCW grant SIAM 024002002.
Supplementary materials
Supplementary material associated with this article can be found, in
the online version, at doi:10.1016/j.wroa.2022.100152.
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