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Critical Review
Bacteria that make a meal of sulfonamide antibiotics: blind spots and emerging opportunities Yu Deng, Bing Li, and Tong Zhang Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b06026 • Publication Date (Web): 02 Mar 2018 Downloaded from http://pubs.acs.org on March 3, 2018
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Environmental Science & Technology
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Bacteria that make a meal of sulfonamide antibiotics:
3
blind spots and emerging opportunities
4 Yu Deng1, Bing Li2 and Tong Zhang1
5 6 7
1
8
University of Hong Kong, Pokfulam Road, Hong Kong
9
2
10 11
Environmental Biotechnology Laboratory, Department of Civil Engineering, The
Division of Energy & Environment, Graduate School at Shenzhen, Tsinghua
University, Shenzhen 518055, China Corresponding author, +852-28578551; fax:+852-25595337;
[email protected] ACS Paragon Plus Environment
Environmental Science & Technology
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ABSTRACT
13 14
The release of sulfonamide antibiotics into the environment is alarming, because the
15
existence of these antibiotics in the environment may promote resistance in clinically
16
relevant microorganisms, which is a potential threat to the effectiveness of antibiotic
17
therapies. Controllable biodegradation processes are of particular significance for the
18
inexpensive yet effective restoration of sulfonamide-contaminated environments.
19
Cultivation-based techniques have already made great strides in successfully isolating
20
bacteria with promising sulfonamide degradation abilities, but the implementation of
21
these isolates in bioremediation has been limited by unknown microbial diversity, vast
22
population responsiveness, and the impact of perturbations from open and complex
23
environments. Advances in DNA sequencing technologies and metagenomic analyses
24
are being used to complement the information derived from cultivation-based
25
procedures. In this review, we provide an overview of the growing understanding of
26
isolated sulfonamide degraders and identify shortcomings of the prevalent literature in
27
this field. In addition, we propose a technical paradigm that integrates experimental
28
testing with metagenomic analysis to pave the way for improved understanding and
29
exploitation of these ecologically important isolates. Overall, this review aims to
30
outline how metagenomic studies of isolated sulfonamide degraders are being applied
31
for the advancement of bioremediation strategies for sulfonamide contamination.
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INTRODUCTION
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Introduced as the earliest first-line antibiotics1, sulfonamides remain one of the most
35
purchased antibiotic classes currently on the market and are mainly used for the
36
intensification of food animal production in agriculture2. Recent survey data reported
37
that the sales of sulfonamides in 2011 accounted for nearly 11% of the total sales of
38
veterinary antibiotics in 25 European countries.3 As a result of their extensive use,
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sulfonamides are frequently detected in contamination sources and environmental
40
compartments (Figure 1). Three levels of contaminated wastewater can be
41
distinguished based on the detected concentrations of sulfonamide residues: (1)
42
wastewater derived from pharmaceutical production factories; (2) wastewater derived
43
from livestock farms, hospitals, and municipal sewer systems; and (3) discharged
44
effluent from wastewater treatment plants (WWTPs). Concentrations of sulfonamide
45
residues were found to be highest in pharmaceutical wastewater (up to 1340 µg/L4),
46
followed by the second and third types of wastewaters (Table 1). Extremely high
47
sulfonamide concentrations were also found in manure (up to 18 mg/kg5). When
48
investigated (Table S1), surface waters receiving wastewater from contaminated
49
WWTP effluents or livestock farms were seen to have higher sulfonamide
50
concentrations (max. concentration of 2.1±2.9 µg/L, number of detected datasets
51
(n)=4) than counterparts situated far from contamination sources (0.2±0.4 µg/L, n=10).
52
Moreover, a decreasing trend in sulfonamide concentrations was observed when the
53
sulfonamide residues were transported away from the sewage discharge point via
54
surface waters.6, 7 In addition to surface waters, quantitative survey data have also
55
indicated the spatial movement of sulfonamide residues from livestock wastewater
56
lagoons to hydraulically downgradient groundwater8, and a low-level yet continuous
57
transport of sulfonamide residues from manure to soil through common agricultural
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manure fertilization practices5, 9. A more striking indication of the ubiquitous
59
occurrence of sulfonamide residues is the detection of these residues in drinking water
60
samples at maximal concentrations between 3 and 116 ng/L10-14. Of the reviewed
61
publications pertaining to sulfonamide contamination sources and the associated
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environmental compartments (Table 1), the highest prevalence was observed for
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sulfamethoxazole (SMX, 92 positive samples out of 101 total sampled datasets),
64
followed by sulfamethazine (SMT, 40/101) and sulfadiazine (SDZ, 33/101).
65 66
Sulfonamides at such concentrations in the environment were found to be not acutely
67
toxic but mutagenic to most aquatic organisms tested (reviewed by García-Galán et
68
al.15). For example, the reported acute median effective or lethal concentration values
69
(E/LC50s) of SMX, which is the most frequently detected sulfonamide, for the marine
70
bacterium Vibrio fischeri (Microtox® test) ranged from 16.916 to 118.7 mg/L17.
71
However, Bengtsson-Palme et al.18 estimated that the no-effect concentration for
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SMX-resistance selection was only 16 µg/L. The sulfonamide concentrations in
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contamination hotspots (including wastewaters derived from pharmaceutical factories,
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livestock farms and hospitals) could possibly exert a selective pressure on resistant
75
pathogens, which can threaten therapeutic effectiveness19. To reduce the
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environmental concentrations of sulfonamides, in addition to the optimization of the
77
use of sulfonamide antibiotics in human and animal treatments, we must prioritize the
78
development of remediation processes. Sulfonamide transformation in natural or
79
engineered environment involves both abiotic processes20-25 and biotic processes26-31.
80
Abiotic degradation such as photolysis and hydrolysis of the photo- and thermostable2
81
sulfonamides found at contaminated sites, is less likely to be significant than biotic
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degradation. Upon the release of sulfonamides to wastewater and soil, which is a
83
common occurrence32, the
adsorption of sulfonamides by sludge or soil particles
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was negligible, as indicated by their low distribution coefficients (Kd values ranging
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from 0.6 to 4.9)33 , while aerobic sulfonamide biodegradation is assumed to play a
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critical role2, 34. The microbially mediated process is of significant research interests
87
since it can be implicated as a simple, inexpensive and environmentally friendly
88
remediation strategy. An array of bacteria that can aid in the environmental
89
remediation of sulfonamide-contaminated hotspot sites through biodegradation have
90
been isolated and characterized using molecular and physiological techniques.
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Additional experimental studies have recently started to reveal the genetic
92
determinants of sulfonamide degradation, until recently, the sole sulfonamide
93
catabolism gene, sadA, has been heterologously expressed and functionally validated
94
in Escherichia coli host cells35.
95 96
In this review, we highlight studies that shed light on the bacteria that are responsible for
97
sulfonamide biodegradation, and we present new considerations that must be addressed when
98
studying the factors affecting the degradation efficiencies of bacteria that specialize in
99
sulfonamide degradation. The integration of appropriate experimental testing with
100
metagenomics is discussed in the context of studying sulfonamide biodegradation in research
101
areas with different levels of microbial complexity, ranging from individual isolates and
102
closed and artificial systems, to open and complex environment matrices. Restrictions in the
103
translational implications of the proposed technical guide are also briefly discussed.
104 105
BACTERIAL PLAYERS IN SULFONAMIDE BIODEGRADATION
106 107
Sulfonamide-degrading bacteria can survive and thrive in the presence of sulfonamide
108
antibiotics. In addition to breaking down the mother compound, in some cases, these
109
degraders can subsist on sulfonamides as sole carbon sources. In this section, we first
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provide a framework that defines the concepts of sulfonamide resistance, tolerance,
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catabolism and subsistence in bacteria. Then, past attempts to
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sulfonamide-degrading or sulfonamide-subsisting isolates are presented along with
113
the newly identified gene that initiate sulfonamide biodegradation. The risks
114
presented by sulfonamide resistant degraders in the environment are discussed at the
115
end of this section, as are possible approaches for the management of these risks.
identify
116 117
Sulfonamide resistance and tolerance in bacteria
118 119
Sulfonamide antibiotics can outcompete their close structural analog p-aminobenzoic
120
acid (PABA) on binding to a catalytic enzyme (i.e., dihydropteroate synthase (DHPS))
121
in the folate synthesis pathway, thereby inhibiting bacterial growth.36 Resistance
122
against sulfonamides emerged only six years after their introduction into the clinic in
123
19351. Resistance allows bacteria to sustain and thrive in the presence of antibiotics
124
and is usually evaluated by the minimal inhibitory concentration (MIC) of the
125
antibiotic, i.e., the minimum antibiotic concentration that prevents the net growth of a
126
bacterium.37 Bacteria typically resort to target-alteration strategy to resist
127
sulfonamides. This strategy exploits two mechanisms of preventing sulfonamides
128
from binding to DHPS, namely, chromosomal resistance resulting from mutations in
129
the DHPS gene (folP) and, more frequently, plasmid-borne resistance conferred by an
130
alternative DHPS gene (sul) whose enzyme product has a lower binding affinity for
131
sulfonamides than DHPS.36 On the other hand, the recently identified two-component
132
flavin-dependent
133
mechanism. This sadA gene-encoded enzyme has no sequence homology to known
134
sulfonamide resistance genes, and can inactivate sulfonamides in Escherichia coli by
135
previously undescribed oxidative mechanisms35.
monooxygenase
represent
a
novel
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resistance
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Different from resistance, tolerance to sulfonamide antibiotics was reported to be the
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results of physiological adaptations38 in bacterial variants39. During a transient
139
antibiotic treatment, even at concentrations that are higher than the MIC37, tolerance
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to antibiotics could enable the survival of these variants through a dormancy
141
mechanism40. It should be noted that tolerant variants are still antibiotic sensitive (as
142
reflected by the MIC value, which is the same as that of susceptible strains) and can
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be killed with extended antibiotic treatment, and therefore, it has been suggested that
144
tolerance should be evaluated by the minimum duration for killing (MDK), i.e., the
145
minimum antibiotic treatment period that can kill a certain proportion of the bacteria
146
at different concentrations.37
147 148
Sulfonamide catabolism and subsistence by bacterial isolates
149 150
Bacteria capable of sulfonamide catabolism can evade sulfonamide-induced toxicity
151
while, counterintuitively, exhibiting the ability to degrade sulfonamides. Sulfonamide
152
catabolism by bacteria is thought to involve either (1) the action of common
153
resistance genes (sul) in tandem with sulfonamide catabolism genes that are unrelated
154
to the resistance mechanism, or (2) the sole action of sulfonamide catabolism genes
155
that provide resistance through degradation mechanisms (e.g. sadA gene). The first
156
sulfonamide-degrading bacterium was isolated almost ten years ago41, and a large
157
amount of follow-up studies isolated a set of bacteria that can degrade or transform
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disparate classes of sulfonamides (including sulfamethoxazole, SMX; sulfamethazine,
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SMT; sulfadiazine, SDZ; sulfadimethoxine, SDM; sulfapyridine, SPY; and
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sulfathiazole, STZ) at a concentration range of 600 ng/L42 to 152 mg/L43 (Table 2).
161
Phylogenetic profiling of the isolated bacteria revealed a diverse range of species in
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the phyla Proteobacteria (81%, 39 out of 48) and Actinobacteria (19%) (Figure 2). Of
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the 17 genera represented, Burkholderia constituted most (23%) of the species
164
isolated, followed by Pseudomonas (15%), Ralstonia (10%), and Microbacterium
165
(10%). The capabilities of these isolates to catabolize sulfonamides were variable, as
166
were their original habitats (Figure 3a). Activated sludge and soil were the main
167
habitats from which 34 out of the 48 sulfonamide-degrading bacteria were isolated.
168 169
Analyses of the degradation products revealed that the heterocyclic moieties of
170
sulfonamides were typically accumulated as a stable metabolite in a few
171
representative isolates, independent of the specific substrates or conditions provided
172
(Figure 3b). Though the final extent of sulfonamide mineralization in pure cultures
173
was generally limited by the degradation abilities of the isolates, the heterocyclic
174
moieties formed by sulfonamide breakdown, such as 3-amino-5-methylisoxazole
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(3A5MI, SMX heterocyclic moiety), were shown to have lower potential
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environmental impacts due to the loss of the antibacterial action of sulfonamides42, 44.
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For example, during SMX degradation by the strain Microbacterium sp. BR1, 3A5M
178
was detached from SMX, releasing 4-iminoquinone and sulfur dioxide simultaneously
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(C10H11N3O3S (SMX) + OH- → C6H5NO (benzoquinone-imine) + SO2 + C4H5N2O-
180
(3A5MI-) + 2H+ + 2e-).45 Comparative analyses on proteomic patterns of sulfonamide
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presence-absence conditions during BR1’s cultivation, together with sequencing of
182
partially
183
monooxygenase was the catabolic enzyme that initiated the breakdown of SMX via a
184
strategy that pairs ipso-hydroxylation with subsequent fragmentation of the mother
185
compound (Figure 3b), and this reaction mechanism allows the maintenance of the
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molecular skeleton of the leaving groups35. In silico genomic analyses further found
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sadA homologues in other four sulfonamide degraders (including Arthrobacter sp. D2
purified
protein
fraction
indicated
that
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sadA
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and D4, Microbacterium sp. C448 and Microbacterium sp. strain SDZm4) which were
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isolated from different continents35. Despite a few studies45,
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obtained evidences on genes that initiated the sulfonamide degradation, the newly
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identified sadA gene was the only sequence that was functionally validated.
46
have previously
192 193
Of the 17 bacterial genera that can degrade or transform sulfonamides, with the
194
exception of the genus Alcaligenes47, 48, 16 genera have demonstrated the ability to
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use sulfonamides as the sole carbon source. The capacity of a bacterium to deploy
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antibiotics for energy and biomass growth was defined as antibiotic subsistence41, 49.
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Bacteria subsisting on sulfonamides are often isolated by plating serial dilutions of an
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inoculum (usually an enriched culture of naturally occurring microbial communities)
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on sulfonamide-containing mineral salts medium (MSM) solidified with agar. Notably,
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the growth of a colony on a sulfonamide-MSM agar plate cannot be taken as direct
201
evidence of its degradation ability. Degradation ability should be confirmed in liquid
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medium, in which cell growth coupled with the disappearance of the sulfonamide can
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be observed. It is crucial to emphasize that the sulfonamide-MSM should contain
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certain sulfonamides as sole carbon and energy sources, and alternative carbon
205
sources should be avoided. Initial attempts to obtain sulfonamide-subsisting bacteria
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have to the isolation of 18 soil bacteria with the ability to grow on either
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sulfamethizole (SMZ) or sulfisoxazole (SSZ) as a sole carbon source41 (Table 2 and
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Figure 3a). In Particular, two seawater strains50, Escherichia sp. HS21 and
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Acinetobacter sp. HS51, as well as Microbacterium sp. BR151 and Achromobacter
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denitrificans PR143 were shown to be capable of subsisting on a variety of
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sulfonamides
212 213
Limitations of cultivation-based studies
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Current studies on isolates subsisting on sulfonamide have been focused on isolating
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these degraders, characterizing the extent of degradation and the metabolites produces,
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and evaluating the effects of the sulfonamide concentration42, 52, the presence of
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additional carbon substrates (e.g., glucose53, tryptone52, sodium-acetate54, succinate43),
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the carbon to nitrogen ratio in the medium54, pH and temperature52,
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degradation efficiencies of these degraders. A few studies have experimentally proven
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the carbon mineralization of the sulfonamide aniline moiety to CO2 and biomass using
222
isotope-labeled sulfonamides43, 45, 51, 57. For example, during degradation experiments
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with Microbacterium lacus SDZm4 using
224
moiety, 56% and 16% of the applied radioactivity were detected in the CO2 and
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biomass produced, respectively; however, in parallel experiments using pyrimidine
226
ring-labeled SDZ, all of the applied radioactivity was identified in the dead-end
227
metabolite, 2-aminopyrimide (2-AP).57 These experiments demonstrated that it was
228
the limited ability of strain SDZm4 to assimilate carbon from the SDZ pyrimidine
229
moiety that prevented complete SDZ mineralization. One study43 showed a general
230
improvement in the SMX degradation efficiency of Achromobacter denitrificans PR1
231
with either the addition of a mixture of 18 kinds of amino acids alone or the addition
232
of a combination of these 18 kinds of amino acids with 14 kinds of vitamins and
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nitrogenous bases. Zhang et al.47 reported that 100 mg/L exogenous vitamin C,
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vitamin B6 or oxidized glutathione significantly enhanced the SMX degradation by
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Alcaligenes faecalis CGMCC 1.767, while no enhancements were observed when
236
vitamin B2 and vitamin B12 were added. However, only Ricken et al.35specifically
237
identified FMNH2 as an indispensable cofactor in the SMX degradation by
238
Microbacterium sp. strain BR1. Micronutrients involved in the sulfonamide
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subsistence of isolated degraders require further research.
14
55, 56
on the
C-labeled SDZ, labeled at its aniline
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Even though the sulfonamide degradation abilities of the characterized isolates were
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promising in laboratory microcosms, the results from the application of these
243
sulfonamide-degrading strains under conditions similar to those in the field situations
244
were often disppointmenting58, 59. The uncertainty in the extrapolation of the results from
245
laboratory degradation to field processes mainly stems from two related issues: the
246
interactions within the microbial communities; and the correlations between community
247
members and environmental variables. To date, mechanistic insights into the above issues are
248
very limited, partially due to the difficulties in using traditional cultivation-based techniques
249
to decipher the roles of key sulfonamide degraders in complex microbial communities.
250
Metagenomics, a technique that applies shotgun sequencing to genomic fragments extracted
251
from a microbial community, has been demonstrated to be a cultivation-independent and
252
high-resolution method for probing microbial structure and functions in both natural60-62 and
253
engineered63-65 communities.
254 255
APPLYING METAGENOMICS TO SULFONAMIDE DEGRADERS
256 257
The genetic determinants of sulfonamide degradation are key factors that must be
258
studied to understand and exploit sulfonamide degraders. In this section, two
259
strategies (comparative genomics and functional metagenomics) for the fast screening
260
of catabolism genes in sulfonamide-degrading isolates or various environmental
261
microorganisms are discussed. In addition, the use of metagenomic profiling to
262
monitor population responsiveness to sulfonamide exposure within a simplified
263
microbial community is also demonstrated, with a focus on addressing issues
264
associated with experimental design (Figure 4). The application of metagenomic
265
analyses to the study of the correlations between degrader effectiveness and
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environmental variables is also briefly discussed.
267 268
Screening of sulfonamide catabolism genes
269 270
The newly identified sulfonamide catabolism gene (sadA) was the only sequence that
271
was functionally validated in heterologous cells, and its homologues were only found
272
in sulfonamide degraders affiliating with the phylum Actinobacteria. However, since
273
around 81% of the known sulfonamide degraders were belonging to the phylum
274
Proteobacteria, the diversity of the sulfonamide catabolism genes is still needed to be
275
discovered. With increasingly available genomic sequences of sulfonamide degraders
276
on public database like NCBI, genomic mining and physiological characterization of
277
sulfonamide-degrading isolates and their phylogenetic relatives can provide
278
information about the genomic basis of sulfonamide biodegradation. An illustrative
279
implementation of this strategy has been performed using three Dehalococcoides
280
strains to correlate their genomic contents with their disparate dechlorination
281
profiles66. The observed physiological differences among those strains were found to
282
be dictated by the presence of distinct reductive dehalogenase-encoding genes with
283
specific chlorinated ethane functions. Though highly informative, comparative
284
genomic analyses are unable to directly measure gene function. Tiered experimental
285
designs encompassing both genome-physiology relationships and transcriptomic
286
analyses may facilitate more robust functional annotations of identified gene
287
candidates.
288 289
Another technique that has been demonstrated to be useful in the discovery of novel
290
catabolic genes is functional metagenomics. This technique can facilitate the retrieval
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of genetic information from complex environmental matrices for various phenotypes
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without culturing efforts67. The utility of functional metagenomics has been
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exemplified by recent applications of this method for the functional elucidation of
294
novel enzymes such as hydrolase68, carbon-fixation enzymes69 and bilirubin-oxidizing
295
enzymes70. Briefly, this technique paires cloning and functional selection of
296
environmental DNA fragments with metagenomic sequencing71. Notably, for the gene
297
candidates discovered using the above mentioned approaches, functional validation in
298
a host is needed to confirm sulfonamide-degrading activities of these candidates.
299
Since the facile hosts commonly used for functional expression are gram-negative
300
bacteria (such as Escherichia coli), functional expression experiments probably
301
preclude the discovery of gram-positive bacteria-specific genes.
302 303
Identifying the roles of individual isolates
304 305
As might be expected given the cultivation limitations, the roles of isolates from
306
sulfonamide-degrading consortia have not been identified. There is a lack of
307
information linking the identities of these isolates to their activities in artificial or
308
natural habitats. Additionally, the mechanisms by which isolated degraders establish
309
and maintain their membership within a community, especially the as-yet-uncultured
310
members that may be involve in sulfonamide degradation, remain unknown.
311
Incorporation of the genomic data of sequenced sulfonamide-degrading isolates and
312
metagenomic studies of sulfonamide-degrading communities can complement and
313
expand the information derived cultivated bacteria.
314 315
A current highlight of metagenomic analysis is genome-resolved metagenomics,
316
which uses binning algorithms to extract genome sequences of individual species
317
from metagenomic datasets of environmental samples72-74 to evaluate community
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membership. If the genomes of a certain sulfonamide-degrading isolate and a
319
reconstructed population bin are identical to each other (as reflected by identical
320
average amino acid or nucleotide identities; online calculation available at
321
http://enve-omics.ce.gatech.edu75), we can confidently assign the bin genome to the
322
matched isolate. In contrast to molecular analyses such as fluorescence in situ
323
hybridization (FISH), real-time quantitative PCR (RT-PCR) and DNA stable-isotope
324
probing (SIP), this explicitly proactive approach is independent of sample availability.
325
The growing publicly available metagenomic-data resources for environmental
326
samples (web-based platform includes IMG/ER, NCBI-SRA and MG-RAST)
327
currently provide a framework within which the identification and surveillance of
328
sulfonamide-degrading isolates can be carried out in diverse microbial ecosystems. It
329
should be noted that the presence of a matched sulfonamide-degrading isolate in an
330
environmental sample cannot be viewed as evidence that sulfonamide biodegradation
331
is occurring in situ; ecological validation of field activity is still required.
332 333
Tracking microbial community responses to sulfonamide exposure
334 335
Monitoring of microbial community responses to sulfonamide exposure, including
336
determining community compositions and tracking changes in the abundance of
337
various members present in the community76, can provide information for the
338
prediction of microbial interaction processes (such as competition for nutrients) that
339
underpin steady biodegradation. Several studies have investigated the community
340
changes in response to sulfonamide exposure, often via 16S rRNA gene-based
341
molecular methods (Table S2). The community responses measured in these studies
342
were variable, probably due to the heterogeneity of the initial inoculum communities
343
or due to different sulfonamide additions and carbon source amendments (including
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manure77, spent mushroom compost78, 79, glucose80, yeast extract81, sodium acetate82-84,
345
and other assimilable carbon sources85; see Table S2 for treatment specifications).
346 347
Nevertheless, even with this variable background in these studies, reduced microbial
348
diversitywas commonly observed as a shared feature. In fact, when sulfonamides
349
were supplied as the sole carbon source, the decrease in community diversity could be
350
accounted for by the selective force for bacteria specializing in sulfonamide
351
degradation, such as Achromobacter and Pseudomonas spp86. In particular, there were
352
a few studies that examined the effects of sulfonamides as the sole carbon source on
353
microbial community dynamics. The time frames for these enrichment studies ranged
354
from days to months. Even with short term enrichment, substantial changes in the
355
composition of the initial inoculum community were observed. One study that
356
performed sulfanilamide enrichment using sulfonamide-contaminated lake water as
357
inoculum revealed that the dominant Burkholderia spp. were rapidly succeeded by
358
Bacilli and Flavobacteriia members over a period of 48 days87. These enrichment
359
processes indicated the abilities of the microorganisms to assimilate sulfonamides.
360
Enrichment culturing of naturally occurring microbial communities with devised
361
growth conditions is an applicable strategy for the identification of novel
362
sulfonamide-degrading isolates. For instance, in a recent application of enrichment
363
culturing for the specific purpose of isolating SDZ degraders, activated sludge from a
364
municipal wastewater treatment plant was used to inoculate a defined mineral salts
365
medium containing SDZ (50 mg/L) as the sole carbon source46. After 10-month
366
incubation, when the SDZ was extensively and stably mineralized (~85% TOC
367
reduction within 72 h), small volumes of the enriched culture were spread onto SDZ
368
mineral-salts agar. Single colonies that grew on SDZ were selected, further purified,
369
identified and characterized by appropriate physiological procedures and phylogenetic
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classifications. Two Arthrobacter strains capable of subsisting on SDZ were obtained,
371
revealing an additional, previously unappreciated ecological significance for
372
Arthrobacter. Sulfonamide degraders are relatively straightforward to isolate by using
373
enrichment culturing strategies. However, the ecological roles of these isolates in the
374
enriched communities are difficult to identify based on phylogenetic analyses.
375 376
Moving towards degradation in the open environment
377 378
The remarkable propensity of microorganisms to environmental perturbations is
379
critical for enrichment culturing processes; however, this propensity can be a major
380
impediment for biodegradation studies in mesocosm and field conditions. Occurring
381
as responses to nutrient availability or variations in physicochemical parameters,
382
quantitative or qualitative alterations in the interactions within microbial populations
383
(such as competition, predation and cooperation) and the relevant degradation
384
reactions are to be expected. A recent example is a soil bioremediation study using the
385
SMT-degrading strain C44859: The inoculation of a native soil containing 1 mg/kg
386
SMT with strain C448 failed to increase SMT mineralization rate, indicating the low
387
activity and poor survival of the inoculated strain C448 in the environment to which it
388
was exposed.
389 390
Associations inferred from community dynamics can help determine the keystone
391
populations of distinct ecological relevance and the responsiveness of these
392
populations to nutritional substrates and physiological conditions, which in turn can
393
guide the design of cultivation media so that ecologically significant microorganisms
394
can be isolated, and the relevant functional genes from these microorganisms can be
395
activated under laboratory conditions. With respect to sulfonamide biodegradation,
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the dynamics of sulfonamide-degrading bacteria were mainly followed by
397
amplicon-based sequencing using the 16S rRNA gene (Table S2). However,
398
phylogenetic analysis based on the 16S rRNA gene was insufficient for the
399
determination of strain-level variations, necessitating the implementation of other
400
analytical methods under the umbrella of shotgun metagenomic sequencing (reviewed
401
in the references88,
402
microbiomes. Sulfonamide biodegradation studies can take a nested approach
403
incorporating microbial association networks and whole-community ordination to
404
identify consistent patterns of successful biodegradation at the community level.
405
Microbial association networks are a powerful tool for modeling and visualizing the
406
statistical co-occurrence of clusters of keystone species90, 91 that cannot be examined
407
directly. Network features include positive and negative co-occurrence. Positive
408
co-occurrence may suggest symbiosis or shared preferences for environmental
409
conditions, and negative co-occurrence may arise due to competition or distinct
410
preferences for mutually exclusive environmental conditions. Visualization of these
411
network features has often been performed via analysis platforms such as Gephi92 and
412
Cytoscape93. On the other hand, whole-community ordination analyses, such as
413
non-metric multidimensional scaling and canonical correspondence analysis, can
414
simplify the complexities associated with environmental variability by visualizing the
415
data in two or three dimensions94, thereby linking community structures with
416
environmental
417
biodegradation.
89
) for the analysis of community dynamics of diverse
determinants
that
are
conducive
to
enhanced
sulfonamide
418 419
Limitations in the translational implications of the proposed technical guide
420 421
There are three important questions which can help to improve our understanding on
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422
biodegradation, including identifying the catabolic genes that initiates the
423
biodegradation, deciphering the complexity of pollutant-degrading communities, as
424
well as increasing impetuses for the inquiry of the ecological role of isolated
425
degraders. And all these important steps towards progress in biodegradation studies
426
are articulated in Figure 4, thus this figure can illustrate how metagenomics
427
approaches are deployed in studies concerning other pollutant biodegradation.
428
However, metagenomic approaches have a fundamental limitation, that is, the
429
degradation activity of an isolate or a microbial community under a certain condition
430
cannot be measured. Thus, in order to fully describe the relationship between genetic
431
controls and degradation processes, additional multi-omic data, such as the levels of
432
RNA (i.e., transcriptomics), are needed, preferably integrated with appropriate
433
experimental designs.
434 435
OUTLOOK
436 437
Extensive survey of the widespread occurrence of sulfonamides in diverse
438
environment matrices has brought attention to sulfonamide contamination. As the
439
amount of residual sulfonamides that enter the environment can be anticipated to
440
increase, the importance of in situ remediation of sulfonamide contaminant is
441
becoming
442
sulfonamide-contaminated water are focused on chemical methods such as advanced
443
oxidation processes95-97. Though highly efficient in removing the mother compounds,
444
the high costs of the application of these methods and the production of highly toxic
445
daughter products during the transformation processes98,
446
methods less desirable for in situ sulfonamide remediation. By contrast, sulfonamide
447
biodegradation is more likely to be the predominant mechanism for field remediation.
apparent.
Preliminary
studies
aimed
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the
99
remediation
of
make these chemical
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448 449
Given
that
sulfonamide
subsistence
represents
alternative
sulfonamide
450
resistance-mechanism, a question that remains unanswered is whether degraders that
451
subsist on sulfonamides are the “bugs” that contribute to the increasingly elevated
452
levels of antibiotic resistance in certain environment matrices. This paradox is mainly
453
associated with the specialized catabolic niche in these degraders, which enables them
454
to be tolerant to these toxins and confers on them a selection advantage over other
455
environmental microorganisms in the presence of sulfonamides. A recent study that
456
examined resistance mechanisms of natural benthic biofilm communities exposed to
457
high sulfonamide concentrations proposed that sulfonamide biodegradation is an
458
adaptive resistance strategy for survival100. In addition, the distribution of bacteria that
459
subsist on sulfonamides in the open environment would probably result in the
460
detoxification of the surrounding microenvironment, which would be beneficial to
461
other susceptible pathogens sharing that microenvironment. In our opinion, due to the
462
above mentioned ecological concerns, control strategies (e.g. membrane separation
463
and subsequent incineration) used for bioremediation of contaminated sites using with
464
sulfonamide-subsisting bacteria have the potential to prevent the dissemination of
465
antibiotic resistance carried by these degraders. As a pragmatic measure that combats
466
antibiotic resistance by reducing the direct exposure of environmental microbial
467
populations to sulfonamides, in situ remediation of hotspots is essential. When taking
468
steps to further develop sulfonamide bioremediation strategies, it is important to
469
acknowledge the risks involved with certain degraders that have the ability to subsist
470
on antibiotics.
471 472
Before drawing wider conclusions by interpreting the degradation abilities measured
473
for sulfonamide-degrading isolates or enriched consortia, however, it is important to
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474
address certain considerations; for example, it is important to know whether the
475
laboratory results can be extrapolated to open environmental conditions. Identifying
476
ecologically significant species and understanding their interactions with other
477
community members or environmental variables hold the key to the empirical
478
development of sulfonamide bioremediation. Complementary and convergent
479
information derived from cultivation-based procedures and sequencing-based
480
techniques will surely make these questions increasingly addressable.
481 482
SUPPLEMENTARY INFORMATION
483 484
This information is available free of charge via the Internet at http://pubs.acs.org/.
485
This file contains two supplementary tables (Table S1 and S2).
486 487
AUTHOR INFORMATION
488 489 490
Corresponding Author Phone: +852-28578551; Fax:+852-25595337; E-mail:
[email protected] 491
Notes
492
The authors declare no competing financial interest.
493 494
ACKNOWLEDGMENTS
495 496
This work was funded by the Theme-based Research Scheme (T21-711/16-R). Yu
497
Deng would like to thank The University of Hong Kong for the postgraduate
498
studentship.
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Table of Contents (TOC) Art
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Table and Figure Legends
1050 1051
Table 1.
contamination sources and environmental compartments
1052 1053
Maximum concentrations of the most frequently detected sulfonamides in
Table 2.
An overview of reported sulfonamide-degrading isolates
Figure 1.
Boxplot of sulfonamide occurrence in contamination sources and
1054 1055
environmental compartments.
1056 1057
Figure 2.
reported sulfonamide-degrading bacterial isolates.
1058 1059
Figure 3.
1062
An overview of bacterial isolates that subsist on sulfonamides (a) and their main degradation pathways (b).
1060 1061
A phylogenetic tree based on 16S rRNA gene sequences covering all
Figure 4.
Model for the integration of experimental testing and metagenomic analysis
1063
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Table 1. Maximum concentrations of the most frequently detected sulfonamides in contamination sources and environmental compartments Contamination source Pharmaceutical wastewater (2.05-1340 µg/L) Livestock wastewater (0.39-25.4 µg/L) Hospital wastewater (0.028-27.8 µg/L) WWTP influent (0.034-7.91 µg/L) WWTP effluent (0.015-9.46 µg/L) Manure (140-18000 µg/kg) Activated Sludge (0.04-665 µg/kg) Environmental compartment Surface water (0.01-12 µg/L) Groundwater (0.001-0.113 µg/L) Drinking water (0.003-0.116 µg/L) Soil (0.37-760.1 µg/L) Total sampled datasets
Detection
Sulfonamide
Max concentration
5/5
Sulfamethazine
3.41-139.7 µg/L
3/5
Sulfadiazine
2.05-697.4 µg/L
2/5
Sulfamethoxazole
24.8-1340 µg/L
6/6
Sulfamethazine
0.8-25.4 µg/L
4/6
Sulfathiazole
0.4-10.57 µg/L
3/6
Sulfamethoxazole
0.44-8.84 µg/L
12/12
Sulfamethoxazole
0.2-27.8 µg/L
3/12
Sulfadiazine
0.3-2.33 µg/L
2/12
Sulfamethazine
0.028-1.7 µg/L
14/14
Sulfamethoxazole
0.36-7.91 µg/L
105, 109, 111,
3/14
Sulfadiazine
0.094-5.15 µg/L
112, 114,
3/14
Sulfapyridine
0.15-3.27 µg/L
119-126
13/13
Sulfamethoxazole
0.09-9.46 µg/L
111,
4/13
Sulfadiazine
0.019-4.18 µg/L
117, 119-127
4/13
Sulfapyridine
0.18-0.446 µg/L
5/6
Sulfamethoxazole
840-18000 µg/kg
3/6
Sulfadiazine
800-1980 µg/kg
2/6
Sulfamerazine
140-4590 µg/kg
10/10
Sulfamethoxazole
0.11-665 µg/kg
5,
7/10
Sulfapyridine
13.3-296.4 µg/kg
133-139
6/10
Sulfadiazine
5.99-112.3 µg/kg
Detection
Sulfonamide
Max concentration
Referenc
13/13
Sulfamethoxazole
0.036-4.3 µg/L
4,
10/13
Sulfamethazine
0.065-6.19 µg/L
8/13
Sulfadiazine
0.013-2.3 µg/L
10/12
Sulfamethoxazole
0.009-1.11 µg/L
7/12
Sulfamethazine
0.013-0.6 µg/L
4/12
Sulfamerazine
0.05-0.744 µg/L
4/4
Sulfamethoxazole
0.03-0.116 µg/L
2/4
Sulfadimethoxine
0.011-0.092 µg/L
2/4
Sulfamethizole
0.09-0.098 µg/L
6/6
Sulfamethoxazole
0.9-671.5 µg/kg
5, 106, 129, 131,
4/6
Sulfamethazine
0.66-74 µg/kg
135, 159, 160
3/6
Sulfadiazine
4.26-760.1 µg/kg
101
Total references
ACS Paragon Plus Environment
Reference 4, 101-104
8, 101, 105-108
4, 101, 109-118
112,
117,
114,
5, 128-132
124,
6,
7,
125,
105,
140-148
8, 126, 149-158
10-14
70
Page 39 of 46
Environmental Science & Technology
1068
Table2. An overview of reported sulfonamide-degrading isolates. aFor the first eighteen strains in the table41, positive biomass growth (at least 108cells/ml) was observed when the strains were supplied with sulfonamides as the sole carbon source; the concentration changes of sulfonamide were not recorded. bDuring the degradation process, the total cell number increased; the final biomass was not recorded. cFor strains BR1, BR2,
1069 1070
BR3, HB1 and HB251, sulfonamide removal was recorded as the extent of mineralization of SMX to CO2. dRate refers to the removal extent which was normalized to biomass and degradation time. MSM, mineral salts medium; MBR, lab-scale membrane bioreactor; RT, room
1071 1072
temperature; PBS, phosphate-buffered saline; ASBR, aerobic sequence batch reactor; NaAc, sodium acetate; – indicates that values are not available.
1066 1067
1073 Organism Burkholderia ginsengisoli Burkholderia ginsengisoli Serratia sp Methylobacterium sp Haemophilus sp Ralstonia pickettii
Strain
Habitat
Slfm-S1P-M1LLLSSL-1
Soil
Slfm-S1P-M1LLLSSL-2 Slfm-S1T-M1LLLSSL-1 Slfm-S1T-M1LLLSSL-2 Slfm-S1T-M1LLLSSL-3 Slfm-S2N-M1LLLSSL-1
Soil Soil Soil Soil Soil
Biodegradation conditions MSM+1000 ppm SMZ, 26°C MSM+1000 ppm SMZ, 26°C MSM+1000 ppm SMZ, 26°C MSM+1000 ppm SMZ, 26°C MSM+1000 ppm SMZ, 26°C MSM+1000 ppm SMZ, 26°C
Biomass
Removala
Time
>108 cells/ml
–
30 d
8
–
30 d
8
–
30 d
8
–
30 d
8
–
30 d
8
–
30 d
8
>10 cells/ml >10 cells/ml >10 cells/ml >10 cells/ml >10 cells/ml
Ralstonia pickettii
Slfm-S2N-M1LLLSSL-2
Soil
MSM+1000 ppm SMZ, 26°C
>10 cells/ml
–
30 d
Ralstonia pickettii
Slfm-S2N-M1LLLSSL-3
Soil
MSM+1000 ppm SMZ, 26°C
>108 cells/ml
–
30 d
8
Burkholderia phenazinium
Slfm-S2R-M1LLLSSL-1
Soil
MSM+1000 ppm SMZ, 26°C
>10 cells/ml
–
30 d
Burkholderia phenazinium
Slfm-S2R-M1LLLSSL-2
Soil
MSM+1000 ppm SMZ, 26°C
>108 cells/ml
Burkholderia phenazinium Burkholderia sediminicola Burkholderia sediminicola
Slfm-S2R-M1LLLSSL-3 Slfm-S2T-M1LLLSSL-1 Slfm-S2T-M1LLLSSL-2
Soil Soil Soil
MSM+1000 ppm SMZ, 26°C MSM+1000 ppm SMZ, 26°C MSM+1000 ppm SMZ, 26°C
ACS Paragon Plus Environment
–
30 d
8
–
30 d
8
–
30 d
8
–
30 d
>10 cells/ml >10 cells/ml >10 cells/ml
Ref
41
Environmental Science & Technology
Burkholderia sediminicola Burkholderia ginsengisoli Burkholderia ginsengisoli Burkholderia ginsengisoli
Slfm-S2T-M1LLLSSL-3 Slfm-S3F-M1LLLSSL-1 Slfm-S3F-M1LLLSSL-2 Slfm-S3F-M1LLLSSL-3
Serratia marcescens
Slfs-S3F-M1LLLSSL-3
Rhodococcus rhodochrous
ATCC 13808
Rhodococcus equi
ATCC 13557
Soil Soil Soil Soil Soil Purchased
Purchased
MSM+1000 ppm SMZ, 26°C
Microbacterium sp.
S-3
BR1
ASBR
MBR
>108 cells/ml
–
30 d
8
–
30 d
8
–
30 d
8
–
30 d
8
>10 cells/ml
–
30 d
MSM+32 ppm SMX+3 g/L glucose, 26°C
–
20%
36 d
MSM+43 ppm SMZ+3 g/L glucose, 26°C
–
14%
12 d
MSM+6 ppm SMX+0.5 g/L glucose, 26°C
OD540=1.36
29%
5d
MSM+6 ppm SMX, 26°C
OD540=0.64
15%
5d
Growing cellb
33.4%
2d
PBS+25 ppm SMX, RT45
100%
2.5 h
PBS+25 ppm SDZ, RT
100%
2h
100%
2h
PBS+31 ppm SDM, RT
100%
5h
PBS+28 ppm SMT, RT
100%
21 h
MSM+1000 ppm SMZ, 26°C MSM+1000 ppm SMZ, 26°C MSM+1000 ppm SMZ, 26°C MSM+1000 ppm SSZ, 26°C
MSM+5 ppm SMT+17 g/L glucose +10 g/L Achromobacter sp
Page 40 of 46
peptone + 3 g/L beef extract, 30°C
PBS+27 ppm SMZ, RT
>10 cells/ml >10 cells/ml >10 cells/ml
OD595=0.50
MSM+127 ppm SMX, 28°C
Growing cell
40%c
6.5h
BR3
MSM+127 ppm SMX, 28°C
Growing cell
44%
6.5h
Ralstonia sp
HB1
MSM+127 ppm SMX, 28°C
Growing cell
24%
6.5h
Ralstonia sp
HB2
MSM+127 ppm SMX, 28°C
Growing cell
44%
6.5h
Escherichia sp
HS21
66%
2d
45%
2d
Rhodococcus sp
BR2
Achromobacter sp
MBR
Seawater
MSM+10 ppm SPY, 28°C MSM+10 ppm STZ, 28°C
ACS Paragon Plus Environment
107 CFU/mL
161
53
55
51
50
Page 41 of 46
Environmental Science & Technology
Acinetobacter sp
HS51
Seawater
MSM+10 ppm SPY, 28°C
72%
2d
67%
2d
10 CFU/mL
30%
2d
MSM+10 ppm SDZ, RT
–
100%
21 d
10% Mueller-Hinton broth+10 ppm SDZ, RT
–
100%
4.2 d
–
100%
–
MSM+10 ppm STZ, 28°C Pseudomonas sp
DX7
Microbacterium lacus
SDZm4
Seawater Soil
MSM+10 ppm SDX +2-8 g/L tryptone , 30°C
107 CFU/mL 7
Microbacterium sp
C448
Soil
MSM+ 50 ppm SMT
Brevundimonas sp
SMXB12
AS
10 ppm SMX in R2A/MSM+NaAc/MSM
Rated (mg/L/d), 2.5/1.7/1.0
Microbacterium sp
SMXB24
AS
10 ppm SMX in R2A/MSM+NaAc/MSM
Rate (mg/L/d), 2.5/1.25/1.25
Microbacterium sp
SMX348
AS
10 ppm SMX in R2A/MSM+NaAc/MSM
Rate (mg/L/d), 2.5/1.7/1.25
Pseudomonas sp
SMX321
AS
10 ppm SMX in R2A/MSM+NaAc/MSM
Rate (mg/L/d), 2.5/2.5/1.7
Pseudomonas sp
SMX330
AS
10 ppm SMX in R2A/MSM+NaAc/MSM
Rate (mg/L/d), 2.5/1.7/1.25
Pseudomonas sp
SMX331
AS
10 ppm SMX in R2A/MSM+NaAc/MSM
Rate (mg/L/d), 2.5/1.7/1.25
Pseudomonas sp
SMX344
AS
10 ppm SMX in R2A/MSM+NaAc/MSM
Rate (mg/L/d), 2.5/1.7/1.25
Pseudomonas sp
SMX345
AS
10 ppm SMX in R2A/MSM+NaAc/MSM
Rate (mg/L/d), 2.5/1.25/1.25
Variovorax sp
SMX332
AS
10 ppm SMX in R2A/MSM+NaAc/MSM
Rate (mg/L/d), 2.5/1.7/1.25
Pseudomonas psychrophila
HA-4
AS
MSM+100 ppm SMX, 10°C
Protein=0.1 g/L
34.3%
8d
MSM+152 ppm SMX
OD600=1.00
100%
14 d
MSM+152 ppm SMX +590 ppm succinate
OD600=1.00
100%
1.8 d
MSM+25 ppm SDZ
OD600=1.00
98%
2.3 d
MSM+31 ppm SDM
OD600=1.00
48%
2.3 d
MSM+28 ppm SMT
OD600=1.00
98%
2.3 d
MSM+25 pm SPY
OD600=1.00
100%
2.3 d
Achromobacter denitrificans
PR1
AS
ACS Paragon Plus Environment
52
57
162
54
56
43
Environmental Science & Technology
MSM+26 pm STZ
Page 42 of 46
OD600=1.00
47%
2.3 d
OD540=0.20
94%
16 h
OD595=0.30
100%
53 h
MSM+50 ppm SMX+ 1 g/L NaAc+1 g/L Alcaligenes faecalis
CGMCC 1.767
Arthrobacter sp
D2
Purchased AS
glucose+100 ppm Vitamin C, 30°C MSM+50 ppm SMX, 37°C
47
46
MSM+50 ppm SMX, 37°C
OD595=0.30
99%
11 d
Manure
MSM+5 ppm SDZ+0.04% yeast extract, 30°C
OD600=~0.8
50%
12 d
SDZ-W2-SJ40
AS
MSM+5 ppm SDZ+0.04% yeast extract, 30°C
OD600=~1.0
55%
12 d
SDZ-3S-SCL47
Sediment
MSM+5 ppm SDZ+0.04% yeast extract, 30°C
OD600=~1.1
60%
12 d
Arthrobacter sp
D4
Paracoccus sp
DZ-PM2-BSH30
Methylobacterium sp Kribbella sp
AS
1074
ACS Paragon Plus Environment
163
Page 43 of 46
Environmental Science & Technology
10.0
1000
15000
0.9
600
20 7.5 0.6
10000
0.3
5000
200
0
0
0
400
5.0 500
10
2.5
0
1075 1076 1077 1078
0
Pharmaceutical wastewater
Figure 1.
0
Livestock Hospital WWTP wastewater wastewater influent
WWTP effluent
Surface water
Groundwater
Drinking water
Manure
Soil
Sewage sludge
Boxplot of sulfonamide occurrence in contamination sources and environmental compartments. The presented data summarized the maximal concentrations of 11types of frequently encountered sulfonamides from 70 publications. The three most frequently detected sulfonamides are listed in Table 1. Details of the concentration values (both maximum and average) are included in Table S1.
ACS Paragon Plus Environment
Environmental Science & Technology
Sl Sl fm-S f Sl m-S 3Ff Sl m-S 2R- M1L M fm 2 Slf -S R-M 1LL LLS m- 2R S Slf S1 -M 1LL LSS L-1 L 1 m Slf -S3 P-M1 LLL SSL L-3 m F Slf -S3 -M1 LLLSSSL -2 F -1 m L β-Proteobacteria Slf -S1P -M1L LLS SL-2 mS L M S2 Slf 1L LSS L-3 N m L -M L Slfm -S2N- 1LL LSSL -2 L M -1 Slfm S2N-M 1LLL SSL-3 S 1 Slfm S2T-M LLLS SL-2 S L1LL -S 2 T LSS 1 Slfm -M1 L Rals -S2T-M LLLSS -3 1LL L tonia L SSL -2 sp. H Rals to 1 B2 Vario nia s vorax p . HB sp. S 1 M X 332 Achro mob Achrom acter sp. PR Pseudom obacter 1 onas sp. sp. BR3 Pseudomon DX7 as psychrop
Ou
t-g r
ou p
Page 44 of 46
in g
Ni tro sp
ira
hila HA-4
Pseudomonas sp.
γ-Proteobacteria
SMX321 Pseudomonas sp. SMX3 30 Pseudomonas sp. SMX331 Pseudomonas sp. SMX345 Pseudomonas sp. SMX344 L-3 Slfm-S1T-M1LLLSS s-S3F-M1LLLSSL-3 Slf
HS51 HS21 aceticus cter sp. cter calco Acinetoba Enteroba 1LLLSSL-1
Tree scale: 0.01
1T-M L-2 Slfm-S LLLSS J40 1T-M1 2-S Slfm-S p. SDZ-W 30 s 2 -BSH 48 rium BR 3 12 bacte -PM2 p. α-Proteobacteria Methylo as sp. SMXuBs sp. SDZ sp. SMXXB24 ss u 7 c m 4 on SM iu 48 occ C L c oc cter m sp. p. C4 1 undim Parac Brev s R r oba iu S - S do Mic bacter erium sp. B m4 Z-3 Rho t D Z o c r m S Mic icroba cteriu us SD 4 p. a M as l a c p. D 2 rob ell Mic terium cter s p. D ribb K rs ac ba rob rthro acte Mi c A ob thr r Actinobacteria A
Sulfonamide-degrading isolates (n=48)
1079 1080 1081 1082 1083 1084 1085
Figure 2.
A phylogenetic tree based on 16S rRNA gene sequences covering all reported sulfonamide-degrading bacterial isolates. Phylogeny in this tree corresponds to 1000 bootstrap replicates. The tree has been rooted with the out-grouping 16S rRNA gene sequence from Nitrospira sp (GenBank accession number AJ224042).
.
ACS Paragon Plus Environment
Page 45 of 46
Environmental Science & Technology
1086
ACS Paragon Plus Environment
Environmental Science & Technology
1087 1088
Figure 3.
Page 46 of 46
Overview of bacterial isolates that subsist on sulfonamides (a) and their main degradation pathways (b). Bacterial isolates capable of utilizing specific sulfonamides as sole carbon sources are colored based on their original habitat. Detailed information for the individual strains is included in Table 2.
1089 1090 1091
Sulfonamide as sole C source Assembly and annotation
Amplify and sequencing
Extrapolation of labscale results Roles of sulfonamidedegrading isolates
Individual
Community complex level
Populations
1092 1093
1094 1095 1096
Figure 4.
Model for the integration of experimental testing and metagenomic analysis.
1097 1098
ACS Paragon Plus Environment