pubs.acs.org/est
Article
Microbial Transformation of Dissolved Organic Sulfur during the
Oxic Process in 47 Full-Scale Municipal Wastewater Treatment
Plants
Caifeng Liu,† Kewei Liao,† Jinfeng Wang, Bing Wu, Haidong Hu,* and Hongqiang Ren
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sı Supporting Information
*
ABSTRACT: Dissolved organic sulfur (DOS) is a significant part of
effluent organic matter of wastewater treatment plants (WWTPs) and
poses a potential ecological risk for receiving waters. However, the oxic
process is a critical unit of biological wastewater treatment for
microorganisms performing organic matter removal, wherein DOS
transformation and its mechanism are poorly understood. This study
investigated the transformation of DOS during the oxic process in 47
full-scale municipal WWTPs across China from molecular and
microbial aspects. Surprisingly, evident differences in DOS variations
(ΔDOS) separated sampled WWTPs into two groups: 28 WWTPs with
decreased DOS concentrations in effluents (ΔDOS < 0) and 19
WWTPs with increased DOS (ΔDOS > 0). These two groups also
presented differences in DOS molecular characteristics: higher
nitrogen/carbon (N/C) ratios (0.030) and more peptide-like DOS (8.2%) occurred in WWTPs with ΔDOS > 0, implying that
peptide-like DOS generated from microbes contributed to increased DOS in effluents. Specific microbe−DOS correlations
(Spearman correlation, p < 0.05) indicated that increased effluent DOS might be explained by peptide-like DOS preferentially being
produced during copiotrophic bacterial growth and accumulating due to less active cofactor metabolisms. Considering the potential
environmental issues accompanying DOS discharge from WWTPs with ΔDOS > 0, our study highlights the importance of focusing
on the transformation and control of DOS in the oxic process.
KEYWORDS: dissolved organic sulfur, molecular characteristics, microbial community, FT-ICR−MS, wastewater treatment
in aquatic ecosystems.7,9 The oxic process in municipal
WWTPs is the critical contributor for the degradation and
removal of various organic matter, which are biologically
utilized or decomposed via microbial biochemical reactions in
the presence of oxygen.10,11 Microbes in the oxic process are
deemed responsible for the changes in dissolved organic
matter, including dissolved organic carbon, dissolved organic
nitrogen, dissolved organic phosphorus, and DOS.5,10,11 So far,
transformation characteristics of carbon, nitrogen, or phosphorus parts in dissolved organic matter have been
documented. However, the transformation of DOS and the
microbial mechanisms during the oxic process remain poorly
understood.
1. INTRODUCTION
Effluents from municipal wastewater treatment plants
(WWTPs) are an important source of dissolved organic sulfur
(DOS) entering water bodies. Wastewater-derived DOS
originates from the sulfidation process of natural organic
matter and anthropogenic release of sulfur-containing chemicals (e.g., micropollutants of detergents, surfactants, and
drugs) and from microbial metabolism in biological treatment
processes in WWTPs (e.g., microbial products of sulfurcontaining amino acids and peptides).1−3 DOS in wastewater,
which has a potential endocrine disruption effect and
exceptionally strong binding affinity with mercury, may reduce
water quality in receiving waters.4−6 Additionally, as a major
component of dissolved organic matter, DOS presents a special
property of forming mercury−DOS complexes, differentiating
from other components in dissolved organic matter (e.g.,
dissolved organic carbon or dissolved organic nitrogen).7,8 The
mercury−DOS complexes alter the mobility and bioavailability
of mercury and promote the production of neurotoxic
methylmercury.7,8 As a consequence of environmental risks
posed by DOS, two consecutive publications in the journal
Science highlighted that DOS is critical for ecological security
© 2023 American Chemical Society
Received: September 15, 2022
Revised: December 24, 2022
Accepted: December 27, 2022
Published: January 6, 2023
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2. MATERIALS AND METHODS
2.1. Sample Collection and Processing. The sampling
campaign was carried out between the fall of 2020 and spring
of 2021 using a uniform sampling protocol that was designed
according to publications involving the broad-scale survey of
municipal WWTPs.18 We tried to collect samples in the same
season and in relatively stable conditions at municipal WWTPs
(between 10:00 and 16:00 h without rainfall events). In brief,
municipal WWTPs for sampling were selected based on the
following criteria: (1) sampling spanned latitude (from 19.996
to 45.814°) and longitude (from 86.079 to 126.715°) and
covered six different climate types in China to account for
substantial impacts of climate zone and geographical location.
(2) Multiple WWTPs were sampled, and multiple samples per
WWTP were collected in individual cities to ensure that
samples were obtained on a broad spatial scale. (3) anaerobic/
anoxic/oxic process (A2O), anoxic/oxic (AO), and their
modified processes are the most common types of biological
nitrogen removal processes in WWTPs in China19 and thus we
sampled the aerobic zone of these processes. Sample positions
were set based on the administrative divisions, including
northeast, north, east, central, south, northwest, and southwest
China. We collected samples from WWTPs in each province
per division as much as possible and intensively sampled in
divisions with a high population density. Details of WWTPs
(e.g., locations of wastewater treatment processes and
wastewater properties) are listed in the Supporting Information.
In the oxic process of each WWTP, wastewater samples
(influent and effluent) were collected in 10 L precleaned
polypropylene bottles without headspace, and sludge samples
were transferred into 50 mL sterile tubes. Samples were kept at
4 °C and transported to the laboratory by express delivery.17
Once in the laboratory, wastewater samples were filtered
through 0.45 μm pore-size cellulose filters and frozen (≤4 °C)
before analysis, while sludge samples were centrifuged and
stored at −80 °C until DNA extraction. The filtered
wastewater samples were used for analysis of bulk chemical
properties, DOS concentrations, and DOS molecular compositions. Details on analysis methods for bulk chemical
properties and procedures for solid-phase extraction were
described in our previous study.20 Briefly, first, aliquots were
used for the analysis (in triplicate) of bulk chemical properties
including chemical oxygen demand, total nitrogen, total
phosphorus, nitrate, nitrite, and ammonia. We measured the
conductivity, pH, dissolved oxygen, and temperature in situ
and collected operation parameters from WWTP technicians.
Second, 1 L wastewater samples were loaded onto solid-phase
extraction tubes using PPL cartridges (500 mg, 6 mL
Supelclean-ENVI-Chrom P SPE Tube, USA), to extract
DOS.6,20 The extracted DOS was eluted with methanol and
concentrated to 1 mL for instrumental analysis. Extractable
DOS was isolated from bulk DOS in sampled wastewater, and
inorganic sulfur (e.g., sulfate) was removed to ensure the sulfur
in this study belongs to the organic species. It should be
noticed that the term of “DOS” remained unchanged for
simplification, but its content indicated for extractable DOS
and differentiated from the bulk DOS before solid-phase
extraction. Method blank (Milli-Q water) was analyzed
identically for blank correction and quality control.
2.2. DOS Concentration Analysis. Before HR-ICP−MS
analysis, 200 μL was taken from 1 mL extracted DOS of each
DOS characteristics depend on its chemical composition.
The accessibility of Fourier transform ion cyclotron resonance
mass spectrometry (FT-ICR−MS) with ultrahigh resolving
power (>200,000) and mass accuracy (error < 1 ppm) enables
molecular-level identification of DOS in complex environmental samples.3,8,12 Currently, our knowledge of DOS
characteristics in wastewater is derived from a small number
of sulfur-containing organic compounds that are interpreted
from dissolved organic matter data. For example, Geng et al.4
found that the majority of identified organic molecules
included CHO5S1 formulas, and they regarded these molecules
as sulfur-containing transformation products from WWTP
influents. Previous research has mainly focused on the highly
abundant mass peaks and nonbiologically originated DOS
from wastewater influent.4,13 Unfortunately, a considerable
amount of DOS from biological treatment processes that
predominantly consists of sulfur-containing microbial metabolites and high-molecular-weight mercaptans has not been
characterized thus far.13 These DOS compounds that originate
from microbes, often presenting as CHONS class species, are
linked to excretion during microbial activity, but they have
received less attention owing to the challenge of identifying
compounds originating from microbes during transformation
processes in DOS mixtures.
The transformation of DOS in biological treatment
processes presumably involves a series of microbial activities
through which DOS is returned to inorganic-form sulfur by
microbial mineralization or sulfur-containing products are
generated by microbial metabolism.14−16 Recent work of Tang
et al.16 coupling high-throughput sequencing with FT-ICR−
MS found that microbial species can modify the compositions
and properties of DOS, such as the stoichiometry, oxidation
state, and aromaticity, all of which have consequences for DOS
transformation. However, the deduction regarding microbe−
DOS relationships is based on the information from only one
WWTP and could be contradictory when differences in the
sampling scale and wastewater treatment systems are present.
Consequently, the DOS transformation mechanisms underlying microbe−DOS relationship requires further investigation
on a broad scale.
To fill this gap, a broad-scale survey of the transformation
characteristics of DOS in the oxic process was conducted at 47
full-scale municipal WWTPs located in 28 provinces across
China. Other valuable information (i.e., details on the
sampling) obtained from this survey has been published
recently.17 In this study, we quantitatively analyzed DOS
concentrations in influents and effluents of the oxic process
and specifically profiled DOS molecular compositions using
high-resolution inductively coupled plasma mass spectrometry
(HR-ICP−MS) and FT-ICR−MS. Since the bulk DOS in
wastewater is at a low concentration mixing with various
inorganic salts, we isolated it as DOS extracts by solid-phase
extraction for DOS-related analysis (i.e., analysis of DOS
concentration and molecular compositions). Furthermore, we
integrated DOS molecules and 16S rRNA sequencing data and
applied statistical tools to elucidate the underlying mechanism
that determines DOS transformation in the oxic process in
terms of microbial composition and function. This study
contributes to a mechanistic understanding of the DOS
transformation characteristics in the oxic process and is
beneficial for the reduction of its ecological risk.
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Figure 1. Variations of DOS concentrations in the oxic processes of 47 WWTPs across China, wherein the distribution map shows the sampling
location in 28 provinces, and boxplots classify the oxic processes presenting increased effluent DOS concentrations (ΔDOS > 0) and the oxic
processes presenting decreased effluent DOS concentrations (ΔDOS < 0).
highly unsaturated-like (H/C < 1.5, AImod ≤ 0.5), polyphenollike (0.5 < AImod ≤ 0.66), and condensed aromatic-like (AImod
> 0.66) compounds.
2.4. Microbial Composition and Function Analysis.
DNA was extracted in triplicate using a FastDNA Spin Kit
(MP Biomedicals, USA) following the manufacturer’s protocol,
and the sequencing analysis targeting V3/V4 region of 16S
rRNA was performed on an Illumina-MiSeq platform
(Shanghai Majorbio Bio-pharm Technology Co., Ltd). The
raw sequence data were quality filtered using fastp (v0.20.0)
and then merged using FLASH (v1.2.11). Based on 97%
consensus threshold, operational taxonomic units (OTUs)
were clustered by UPARSE (v7.1), and representative OTUs
were assigned by taxonomy according to the SILVA database
(v138). Microbial function was predicted using the R
PICRUST2 package based on annotation information from
16S rRNA in the SILVA database, inferred using the KEGG
pathway database, and extracted from the tier 2 categories.25
Details of 16S rRNA sequencing and analysis can be found in
the Supporting Information.
2.5. Statistical Analysis. The corresponding sections in
Text S4 show details of statistical analysis clearly in terms of
the following: (1) DOS molecular accumulation and rank
abundance curves were calculated following Kellerman et al.,23
and identification of produced, shared, and removed molecules
follows our previous research.26 (2) Calculations involving
microbes followed Zhou et al.,27 including indicator species,
microbial co-occurrence networks of OTUs, and network
properties (i.e., degree, betweenness centrality, within-module
connectivity, among-modules connectivity of each node);
based on within-module and among-module connectivity,
nodes in networks were categorized into peripheral nodes,
connectors, module hubs, and network hubs. (3) Spearman
correlations were evaluated between indicator species and
DOS, and structural equation modeling (SEM) by partial leastsquares path modeling approach (PLS-PM) was conducted to
quantify their links. (4) Variation partitioning analysis (VPA)
sample, dried with nitrogen gas, and then redissolved in 2%
nitric acid solution (LC−MS grade). Redissolved extracted
DOS was analyzed using HR-ICP−MS (Element XR, Thermo
Scientific, USA). The instrument settings were specified
according to the published method with modifications: scan
mode, electrical scanning; resolving power, medium (m/Δm =
4000); radio frequency power, 1200 W; nebulizer gas flow,
1.03 L/min; auxiliary gas flow, 0.97 L/min; cooling gas flow,
15 L/min; and sample uptake time, 25 ms.21,22 The variation
and removal rate of DOS in the oxic process were calculated
using eqs 1 and 2, respectively.
DOS (variation of DOS concentration)
= conc. (DOSeff )
Removal rate =
conc. (DOSinf )
(1)
DOS/conc. (DOSinf )
(2)
where “DOSinf” and “DOSeff” represent DOS in the influent
and effluent of the oxic process, respectively; “conc.” represents
concentrations. Specifically, ΔDOS < 0 represents the effluent
DOS concentration lower than the influent DOS concentration
with a positive removal rate and effective reduction of DOS,
while ΔDOS > 0 represents the effluent DOS concentration
higher than the influent DOS concentration with a negative
removal rate and an increase in DOS.
2.3. DOS Molecular Composition Analysis. The
remaining extracted DOS was analyzed using a FT-ICR−MS
system (Bruker Daltonik, Bremen, Germany) with a 15.0 T
actively shielded superconducting magnet and an electrospray
ionization source and was annotated following Kellerman et
al.23 with some modifications (details are shown in the
Supporting Information). Assigned DOS formulas can be
classified into six compound categories by molecular traits [i.e.,
nitrogen (N), hydrogen/carbon (H/C) ratios, and modified
aromaticity index (AImod)] according to Kellerman et al.23 and
Poulin et al.24 with some modifications, including saturated
fatty acid-like (H/C ≥ 2.0), peptide-like (1.5 ≤ H/C < 2.0, N
> 0), unsaturated aliphatic-like (1.5 ≤ H/C < 2.0, N = 0),
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was used to assess the relative contribution of different factors
to DOS variations.
account for important components of DOSeff. In particular,
previous studies have provided evidence for substantial
microbial products released in the oxic process.29,30 Although
small differences (e.g., operational conditions) exist among the
oxic processes of sampled WWTP, previous studies have
reported that significant influences from these differences
could exist only when WWTPs are located near each other and
fed by similar influents.18,31 More importantly, our VPA results
also suggest that microbial factors outcompeting other factors
largely dominated DOS variations (Figure S1d). Therefore, we
speculate that the phenomenon of “DOSeff > DOSinf” can be
attributed to the generation of sulfur-containing microbial
products. This hypothesis will be further substantiated in
Section 3.2.
3.2. Patterns of DOS Molecular Transformation
Characteristics during the Oxic Process. To understand
the phenomenon of “DOSeff > DOSinf,” the transformation
characteristics of DOS molecules in the oxic process of
WWTPs with ΔDOS > 0 and WWTPs with ΔDOS < 0 were
further identified. Based on the molecular accumulation curve
of 47 WWTPs, a total of 32,808 (698 on average) DOS
molecular formulas were detected, in which 6226 formulas
occurred in >3 sampled WWTPs (Figure S3a). Moreover, 95%
DOS molecular richness was achieved in 23 of the 47 WWTPs
(Figure S3a), and DOS molecules with normalized relative
peak intensities in the highest 5% were present in >83.2%
samples (Figure S3b). These results revealed that although the
abundances of DOS molecules varied in different samples, a
core group of DOS molecules were ubiquitous in the oxic
process of sampled WWTPs.
DOS molecular transformation in each WWTP is shown in
Figures 2 (S8−S36 in Supporting Information presenting
details in each WWTP), presenting complex changes in DOS
molecular compositions during the oxic processes. DOS
molecules were identified into the produced, shared, and
removed classes, and these three classes of molecules were
further sorted into six compound categories in van Krevelen
diagrams (Figure 2). A higher proportion of peptide-like
compounds were found in new produced DOS molecules in
the processes of WWTPs with ΔDOS > 0 (19.4%) compared
to those in WWTPs with ΔDOS < 0 (18.6%). It implies that
more peptide-like DOS molecules produced in the oxic process
of WWTPs with ΔDOS > 0 may account for increased
concentrations of DOSeff. Traits of molecular formulas, such as
AImod and ratios of H/C, oxygen/carbon (O/C), and
nitrogen/carbon (N/C), were calculated, which may provide
information complementary to molecular transformation
processes.10,12,32 Lee et al.32 found previously that compounds
with a higher N/C ratio were associated with microbial
products. As expected, distinct variation in DOS molecules in
the oxic process of WWTPs with ΔDOS > 0 and WWTPs with
ΔDOS < 0 was observed (Table 1). In the oxic processes of
WWTPs with ΔDOS < 0, N/C and P/C ratios in DOSeff were
comparable to those in DOSinf. However, N/C and P/C ratios
increased from 0.023 to 0.007, respectively, in DOSinf to 0.03
and 0.009 in DOSeff of WWTPs with ΔDOS > 0 (Table 1).
Molecular compositions of DOSeff in WWTPs with ΔDOS > 0
shifted toward higher nitrogen and phosphorus contents,
which was not found in WWTPs with ΔDOS < 0. Collectively,
increased nitrogen in the molecular content of DOSeff (i.e., N/
C) suggested that microbial products may be generated in the
oxic processes of WWTPs with ΔDOS > 0. For the
phenomenon of “DOSeff > DOSinf,” this shift in the N/C
3. RESULTS AND DISCUSSION
3.1. Variations of DOS Concentrations during the
Oxic Process. Influent DOS (DOSinf) concentrations ranged
from 54.4 to 287.1 μg/L, and effluent DOS (DOSeff)
concentrations ranged from 46.7 to 407.6 μg/L in the oxic
process of 47 municipal WWTPs located in 28 provinces
across China (Figures 1 and S8−S36 in the Supporting
Information, presenting details of DOS variations in each
WWTP). Previous studies have reported DOS concentrations
in natural aquatic environments of 3.2 μg/L in estuarine or
riverine environments8 and 2.6−9.6 μg/L in the ocean
surface.9 Clearly, compared with these natural aquatic
environments, DOS concentrations are at higher levels in
DOSeff. Therefore, it can be expected that effects of DOSeff on
receiving waters might be pronounced when DOSeff is
discharged into receiving waters. Due to the relevance and
potential contribution of DOSeff to DOS reservoirs, variations
of DOS (ΔDOS) during the oxic process cannot be ignored.
DOS removal rates in the oxic processes across sampled
municipal WWTPs ranged from −184.1 to 59.9% (−5.1% on
average) and had no significant correlation with latitude or
administrative divisions (Figure S1). Interestingly, more than
40% of sampled WWTPs had negative DOS removal rates
(DOSeff > DOSinf; Table 1) in the oxic process. This
Table 1. DOS Average Concentrations and DOS Molecular
Traits of Influent and Effluent in the Oxic Processes of
WWTPs
WWTPs with ΔDOS > 0
WWTPs with ΔDOS < 0
items
influent
effluent
influent
effluent
Cavg (μg/L)a
H/Cb
O/Cc
N/Cd
S/Ce
P/Cf
AImodg
DBEh
126.8
1.42
0.38
0.023
0.065
0.007
0.080
6.66
171.5
1.38
0.39
0.030
0.066
0.009
0.074
7.37
148.8
1.43
0.38
0.021
0.065
0.006
0.078
6.56
119.2
1.40
0.39
0.021
0.065
0.006
0.100
6.79
Article
a
Cavg: average concentration. bH/C: hydrogen/carbon. cO/C:
oxygen/carbon. dN/C: nitrogen/carbon. eS/C: sulfur/carbon. fP/C:
phosphorus/carbon. gAImod: modified aromaticity index. hDBE:
double bond equivalence.
phenomenon indicates that the removal of DOS during the
oxic process is not necessarily effective and that concentrations
of DOSeff may even be higher than that of DOSinf. Based on
this phenomenon, WWTPs with negative DOS removal rates
(−39.1% on average; DOSeff > DOSinf) were grouped as
“ΔDOS > 0,” while WWTPs with positive DOS removal rates
(18.4% on average; DOSeff < DOSinf) were grouped as “ΔDOS
< 0.” Moreover, the phenomenon of “DOSeff > DOSinf” further
suggested the production of additional DOS during the oxic
process, which likely had a bacterial origin. Wastewater
bacteria manipulate most of the degradation and transformation of organics (e.g., organic sulfur and organic carbon)
in the oxic process by means of microbial activities.10,11,28
Owing to these processes, microbial products, such as
cysteine-, methionine-, and sulfur-containing peptides, are
released by exudation or lysis of microbial cells,29 which might
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Figure 2. van Krevelen diagrams of DOS molecular transformation in the oxic processes of WWTPs with ΔDOS > 0 and WWTPs ΔDOS < 0. Five
aeras are separated by dotted lines, showing six compound categories of DOS molecules (saturated fatty acids, peptide, unsaturated aliphatics,
highly unsaturated, polyphenols, or condensed aromatics). Circle colors denote variations of DOS molecules in the oxic processes, including
produced (blue), shared (brown), and removed DOS molecules (orange).
ratio supports our speculation that increased DOS concentrations in effluents were related to the formation of sulfurcontaining microbial products during oxic processes. Specifically, there were clear differences between WWTPs with
ΔDOS < 0 and WWTPs with ΔDOS > 0 in terms of
aromaticity. After the oxic process, AImod decreased by 0.006 in
WWTPs with ΔDOS > 0, whereas this value increased by
0.022 in WWTPs with ΔDOS < 0 (Table 1). Interestingly, it
was reported previously that after biological treatment
processes, molecular compositions of dissolved organic matter
became more aromatic, more complex, and less bioavailable.28
DOS, as an important component of dissolved organic matter,
in contrast, showed the opposite pattern in WWTPs with
ΔDOS > 0 relative to this previous report. Generally,
wastewater microbes tend to utilize and convert easily
degradable molecules into more recalcitrant compounds,
resulting in an increase in aromaticity.28 Consequently, the
opposite pattern indicates the formation of active DOS in
WWTPs with ΔDOS > 0.
Variations of DOS traits suggested more active molecules in
DOSeff of WWTPs with ΔDOS > 0. In this case, compared
with WWTPs with ΔDOS < 0, molecular compositions in
DOSeff of WWTPs with ΔDOS > 0 would present higher
environmental concerns for receiving waters. Clearly, differ-
ences were observed in the relative abundances of six
compound categories (Figure 3). Among DOSeff molecules,
lower relative abundances of unsaturated aliphatics (7.5%) and
highly unsaturated (22.3%) categories were observed in
WWTPs with ΔDOS > 0 compared with 11.3 and 25.6%,
respectively, in WWTPs with ΔDOS < 0. Other fractions in
WWTPs with ΔDOS > 0 had higher relative abundances than
the corresponding fractions in WWTPs with ΔDOS < 0.
However, it is interesting that only differences between relative
abundances of peptide-like DOS in WWTPs with ΔDOS > 0
(8.2%) and WWTPs with ΔDOS < 0 (5.9%) were statistically
significant (Mann−Whitney U test, p < 0.05; Figure 3).
Molecules assigned as peptides were previously reported to be
associated with microbial products from microbial metabolism.4,7 This result indicated that molecules in peptide
categories would play a critical role in differences of DOSeff
between WWTPs with ΔDOS > 0 and ΔDOS < 0 and thus
peptide-like DOS deserves more attention. Specifically, prior
studies have demonstrated high bioavailability in peptide-like
molecules,24,33 meaning that DOS in peptide categories is
liable to bind with trace heavy metals in receiving waters via its
abundant sulfhydryl groups.24,29 Therefore, the presence of
relatively more peptide-like molecules in DOSeff from the oxic
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analysis of microbes with DOS molecules was performed to
further confirm the speculation in Section 3.2.
3.3.1. Links between Microbial Composition and Molecular Components. Indicator species enable the comprehensive
description of prevalent and rare microbial species in microbial
communities,34 which were used for elucidating microbial
composition−DOS relationships (Tables S3 and S4). Among
microbial composition−DOS relationships, microbes in
WWTPs with ΔDOS > 0 and ΔDOS < 0 were classified
into two distinct clusters (Figure S7). Cluster 1 consisted of 11
indicator species involved in the oxic processes of WWTPs
with ΔDOS > 0 (e.g., Bacteroidia and SAR324_cladMarine_group_B). These taxa had significantly positive correlations
with peptide categories (p < 0.05) but negative correlations
with highly unsaturated and unsaturated aliphatic categories (p
< 0.05). Cluster 2 contained five indicator species assigned by
taxonomy at the phylum or class level (e.g., Alphaproteobacteria
and Chloroflexia) in WWTPs with ΔDOS < 0. In contrast,
indicator species in cluster 2 showed reverse associations with
DOS molecules in comparison with microbial composition−
DOS relationships in cluster 1 (Figure S7). These results
indicated that microbial communities in the oxic processes of
WWTPs with ΔDOS > 0 or ΔDOS < 0 displayed distinct
functions in manipulating DOS transformation.
Microbial drivers of significantly increased peptide-like DOS
molecules can be found by microbial composition−DOS
relationships. In the oxic processes of WWTPs with ΔDOS >
0, peptide-like DOS showed positive correlations with
Bacteroidia, Calditrichia, SAR324_cladeMarine_group_B, and
Anaerolineae (r = 0.077−0.455, p < 0.05; Figure 4a), wherein
the strongest interactions were Bacteroidia−DOS in peptide
categories. Notably, the presence of these microbial species
might be evidence for the increase of peptide-like DOS, since
copiotrophic attributes were found in these microbial species;
they tend to grow and accumulate in circumstances with
abundant bioavailable compounds.35,36 An increase in peptidelike DOS may allow the assembly of copiotrophic bacteria,
Figure 3. Relative abundance of six compound categories of DOS
molecules, including condensed aromatics, polyphenols, highly
unsaturated, unsaturated aliphatics, peptide, and saturated fatty acids.
processes of WWTPs with ΔDOS > 0 would result in an
increase in the ecological risk of WWTP discharge.
3.3. Microbial Mechanisms of DOS Transformation
during the Oxic Process. Our findings in Section 3.2 suggest
that the increased concentrations of DOSeff in the oxic
processes of WWTPs with ΔDOS > 0 might be caused by
microbial activities generating sulfur-containing microbial
products. Additionally, VPA results revealed that DOS
variations can be best explained by microbial effects (Figure
S1d). Moreover, results in Section 3.2 indicate that the
formation of peptide-like DOS may be a significant contributor
to those microbial products. In this case, Spearman correlation
Figure 4. (a) Spearman’s correlation coefficients of microbial indicator species with peptide-like DOS. Significant correlations are denoted as * (p <
0.05), ** (p < 0.01), or *** (p < 0.001). Classification of microbial species in microbial co-occurrence networks in the oxic processes of (b)
WWTPs with ΔDOS < 0 and (c) WWTPs with ΔDOS > 0. Areas are separated into four parts in terms of module hub, network hub, peripheral
hub, and connector.
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Figure 5. (a) Spearman’s correlation between DOS molecules and microbial functions. Only significant correlation with p < 0.05 are shown. (b)
Spearman’s correlation coefficients of microbial functions with peptide-like DOS (* denoting p < 0.05).
such as Bacteroidia, and promote their metabolic activities, and
vice versa. However, in the oxic process of WWTPs with
ΔDOS < 0, increased peptide-like DOS negatively correlated
with indicator species of Alphaproteobacteria (r = −0.17, p <
0.05; Figure 4a), which dominate in oligotrophic conditions
and enable the utilization of refractory organic compounds.37
Therefore, relative abundances of peptide-like DOS decreased
with the decomposition activities of oligotrophic bacteria (i.e.,
Alphaproteobacteria), which might explain the lower peptidelike DOS in the oxic process of WWTPs with ΔDOS < 0.
Altogether, these results confirmed that the discrepancy
between DOS transformation in the oxic processes of WWTPs
with ΔDOS > 0 and WWTPs with ΔDOS < 0 is related to
divergent effects of microbial compositions on DOS
components. Specifically, microbial composition−DOS relationships supporting this deduction also highlight the role of
microbial functions in regulating DOS transformation. For
example, in the oxic processes of WWTPs with ΔDOS < 0,
almost all nodes (96.2%) of microbial co-occurrence networks
were assigned to peripheral nodes, representing the specialist
microbes (Figure 4b,c).38,39 It was previously reported that
microbes belonging to peripheral nodes had excellent
capabilities for xenobiotic degradation and metabolism.39
Thus, effective degradation would be performed due to
abundant peripheral nodes in microbial composition−DOS
networks, which might explain the higher aromaticity and
lower bioavailability of DOS molecules in the oxic process of
WWTPs with ΔDOS < 0.
3.3.2. Links between Microbial Function and Molecular
Components. 46 metabolic functions of microbes in oxic
processes were annotated, containing 12 abundant metabolic
functions with a relative abundance >1% (Table S5).
Significant differences in microbial functions between the
oxic processes of WWTPs with ΔDOS > 0 and WWTPs with
ΔDOS < 0 were verified. For example, lipid metabolism had a
higher abundance in the oxic processes of WWTPs with
ΔDOS > 0 in comparison with WWTPs with ΔDOS < 0
(Mann−Whitney U test, p < 0.05). Additionally, the relative
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Article
Figure 6. (a) SEM quantifying causal−effect relationships between microbes and DOS. Rectangles are reflective indicators in the outer model and
ellipses are latent variables in the inner model. (b) Variation portioning analysis on the contribution of microbial composition and function to
variation in the DOS composition.
abundances of energy and cofactor metabolisms were
significantly lower in the oxic processes of WWTPs with
ΔDOS > 0 (p < 0.05). These metabolisms were the most
abundance functions with relative abundances greater than 4%
in the oxic processes of WWTPs with ΔDOS < 0 and WWTPs
with ΔDOS > 0 and could contribute to differences in DOS
compositions.
Microbial function−DOS relationships demonstrated evident differences in the oxic processes of WWTPs with ΔDOS
> 0 and WWTPs with ΔDOS < 0. For example, only cofactor
metabolism appeared to be significantly related to peptide-like
DOS (r = −0.245, p < 0.05; Figure 5), while other
metabolisms among the 12 predominant metabolisms in
Table S5 had no significant associations with those molecules
(p > 0.05; Figure 5). To an extent, peptide-like DOS content is
maintained by cofactor metabolism activities, and thus changes
in peptide-like DOS will follow variations in cofactor
metabolism. Furthermore, we showed that the relative
abundance of cofactor metabolism in the oxic processes of
WWTPs with ΔDOS > 0 was significantly lower than that in
WWTPs with ΔDOS < 0 (p < 0.05; Table S5). This result
implied that less active cofactor metabolism is responsible for a
higher relative abundance of peptide-like DOS in the oxic
processes of WWTPs with ΔDOS > 0. For example, cysteine,
the key precursor of coenzyme A biosynthesis,40 would be
decreasingly utilized when biosynthesis becomes less active. In
turn, cysteine could contribute to DOS components, and
peptide-like DOS might increase as a result of cysteine
accumulation. Besides cofactor metabolism, cysteine is a key
metabolite participating in other metabolism pathways, for
example, glutathione metabolism. Effects of cysteine accumulation may delivery to cysteine-related metabolisms, leading to
an increase in sulfur-containing compounds.7,41 A previous
study of Kertesz et al.41 investigated compounds such as
cysteine regenerated during the metabolic activities of
heterotrophs (i.e., Pseudomonas putida) on inorganic matter.
This indicates that cysteine may be a crucial factor that can
give a deeper explanation on differences in DOS trans-
formation, which can be explored in the future study.
Collectively, these results reflect differences in microbial
functions and their correlations with DOS molecules between
the oxic processes in WWTPs with ΔDOS > 0 and WWTPs
with ΔDOS < 0. In particular, increased peptide-like DOS
could be primarily attributed to less active cofactor metabolism
in the oxic processes in WWTPs with ΔDOS > 0.
Differences in microbial mechanisms of DOS transformation
in the oxic processes of WWTPs with ΔDOS > 0 and WWTPs
with ΔDOS < 0 were revealed by microbe−DOS relationships.
A deeper analysis using SEM by PLS−PM was conducted to
quantify causal−effect relationships between microbes and
DOS transformation in the oxic process (Figure 6a). High
loadings of links in the outer model (e.g., 0.842 for
Anaerolineae-microbial composition) reveal that these reflective
indicators in the outer model can well explain latent variables
in the inner model. Specifically, cofactor metabolism reflected
microbial functions to a great extent (loading = −0.814), and
microbial functions had the strongest effects on DOS
composition which was well represented by peptide-like
DOS (loading = −0.929). Results of PLS−PM confirmed
that cofactor metabolism was responsible for the accumulation
of sulfur-containing microbial products. In particular, microbial
composition related to DOS composition (loadings = 0.568)
probably impact DOS molecules through links of microbial
composition−microbial function (loading = 0.4741) and
microbial function−DOS composition (loading = −0.623).
This deduction was supported by VPA (Figure 6b), showing
that 24.3% of variation in DOS composition was explained by
microbial composition and function together. More importantly, VPA results revealed that DOS composition was best
explained by microbial functions (58.5%) rather than microbial
composition (41.5%; Figure 6b). In summary, all of these
causal effects corroborate that peptide-like molecules generated
from copiotrophic bacterial metabolism and accumulating in
cofactor metabolism are the major contributors to increased
DOS concentrations in WWTPs with ΔDOS > 0. Moreover,
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microbial functions played a more important role during this
process.
3.4. Implications. Traditionally, oxic processes enable
efficient treatment of wastewater with low organic loading
(treated wastewater from anaerobic or anoxic processes) by
assimilating organic matter and nutrients.10,11 However, based
on data from 47 municipal WWTPs, an interesting finding was
obtained: 28 of the sampled WWTPs had decreased DOSeff
concentrations in the oxic processes, while the other 19
WWTPs showed increased concentrations (Figures 1 and S1).
That is, DOS is an important component of organic matter in
wastewater, and it did not necessarily appear that DOS
concentrations decreased effectively after oxic processes. This
finding opposes our traditional understanding of pollutant
variation in oxic processes. More importantly, our results
suggest that not only poor DOS degradation but also new
DOS production (e.g., peptide-like DOS) originating from
microbial activities occur in the oxic processes of WWTPs with
ΔDOS > 0 (Figure 2). A considerable portion of peptide-like
compounds were low-molecular-weight (<3 kDa) molecules
with a relatively high biodegradability, which would be
transformed into disinfectant byproducts in subsequent
chlor(am)ination processes and persist during UV irradiation.42−44 Moreover, due to the hydrophilic functional groups
and low-molecular-weight molecules in DOS, the complexation and adsorption of DOS by conventional metal salt
coagulants and organic coagulants are not effective. Therefore,
such DOS molecules pose a problem not only in the oxic
process but also in a tertiary treatment process.
There are two approaches to reduce DOS entering receiving
waters. One is to regulate operations to minimize effluent DOS
of the oxic process and another is to remove DOS by a tertiary
treatment process. Since sulfur-containing microbial products
are deduced to be responsible for increased effluent DOS in
the oxic process, for the former, previous studies on microbial
products (i.e., SMP) may provide relevant ideas for developing
DOS control strategies or techniques.45−47 Operational
parameters in the biological (oxic) treatment processes are
the effective cost tools to control microbial products, for
example, the optimal solid retention time for minimizing SMP
formation in the oxic process is 2−15 d,45 which may also have
positive effects on DOS control. Furthermore, a previous study
found that some microbial species, for example, Pannonibacter,
can effectively mineralize DOS with a sulfonate group as a
carbon source for growth.48 Therefore, the technique
accumulating such functional microbes or estimating whether
operational parameters can effectively act in DOS control
could become the next step of the work on DOS in the oxic
process. For the latter approach, a new coagulant having a
higher positive charge density and a higher degree of
polymerization shows a greater removal efficiency in
comparison with the conventional coagulants in terms of
removal of sulfur-containing low-molecular-weight molecules.4
As such, the application of effective coagulants may be another
practicable alternative for DOS control. Finally, DOS in the
oxic process in effluents of WWTPs deserves more special
attention.
HR-ICP−MS analysis; FT-ICR−MS analysis; 16S rRNA
sequencing; statistical analysis; information on 47
WWTPs; description of treatment processes; indicator
species; microbial functions; DOS concentrations and
removal rates; bulk chemical properties; DOS molecular
distribution; microbial compositions; microbial cooccurrence networks; microbial compositions−DOS
correlations; DOS concentration and molecular transformation in 47 WWTPs; and van Krevelen diagrams of
DOS molecules in 47 WWTPs (PDF)
FT-ICR−MS data have been deposited in figshare,
which are publicly accessible at: https://figshare.com/
articles/dataset/FTICR_MS_formula/21621246
■
■
Article
AUTHOR INFORMATION
Corresponding Author
Haidong Hu − State Key Laboratory of Pollution Control and
Resource Reuse, School of the Environment, Nanjing
University, Nanjing, Jiangsu 210023, China; orcid.org/
0000-0003-0193-0333; Phone: +86 25 89680512;
Email: hdhu@nju.edu.cn; Fax: +86 25 89680569
Authors
Caifeng Liu − State Key Laboratory of Pollution Control and
Resource Reuse, School of the Environment, Nanjing
University, Nanjing, Jiangsu 210023, China
Kewei Liao − State Key Laboratory of Pollution Control and
Resource Reuse, School of the Environment, Nanjing
University, Nanjing, Jiangsu 210023, China; orcid.org/
0000-0001-5303-8828
Jinfeng Wang − State Key Laboratory of Pollution Control
and Resource Reuse, School of the Environment, Nanjing
University, Nanjing, Jiangsu 210023, China; orcid.org/
0000-0001-9001-1413
Bing Wu − State Key Laboratory of Pollution Control and
Resource Reuse, School of the Environment, Nanjing
University, Nanjing, Jiangsu 210023, China; orcid.org/
0000-0001-7117-580X
Hongqiang Ren − State Key Laboratory of Pollution Control
and Resource Reuse, School of the Environment, Nanjing
University, Nanjing, Jiangsu 210023, China; orcid.org/
0000-0002-6434-692X
Complete contact information is available at:
https://pubs.acs.org/10.1021/acs.est.2c06776
Author Contributions
†
C.L. and K.L. contributed equally to this work.
Notes
The authors declare no competing financial interest.
■
ACKNOWLEDGMENTS
This study was funded by the Research Program of State Key
Laboratory of Pollution Control and Resource Reuse
(PCRRZZ-202104) and the Excellent Research Program of
Nanjing University (ZYJH005).
■
ABBREVIATIONS
dissolved organic sulfur
dissolved organic sulfur in effluents of the oxic
process
DOSinf
dissolved organic sulfur in influents of the oxic
process
DOS
DOSeff
ASSOCIATED CONTENT
* Supporting Information
sı
The Supporting Information is available free of charge at
https://pubs.acs.org/doi/10.1021/acs.est.2c06776.
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variation of dissolved organic sulfur concentrations, that is, dissolved organic sulfur concentrations in effluents minus those in influents
ΔDOS > 0 dissolved organic sulfur concentrations in effluents higher than those in influents, that is, DOSeff
> DOSinf
ΔDOS < 0 dissolved organic sulfur concentrations in effluents lower than those in influents, that is, DOSeff
< DOSinf
■
Article
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