Negative correlations between cultivable and active-yet-uncultivable pyrene degraders explain the postponed bioaugmentation

Article abstract of DOI:10.1016/j.jhazmat.2021.127189

Bioaugmentation is an effective approach to remediate soils contaminated by polycyclic aromatic hydrocarbons (PAHs), but suffers from unsatisfactory performance in engineering practices, which is hypothetically explained by the complicated interactions between indigenous microbes and introduced degraders. This study isolated a cultivable pyrene degrader (Sphingomonas sp. YT1005) and an active pyrene degrading consortium (Gp16, Streptomyces, Pseudonocardia, Panacagrimonas, Methylotenera and Nitrospira) by magnetic-nanoparticle mediated isolation (MMI) from soils. Pyrene biodegradation was postponed in bioaugmentation with Sphingomonas sp. YT1005, whilst increased by 30.17% by the active pyrene degrading consortium. Pyrene dioxygenase encoding genes (nidA, nidA3 and PAH-RHDα-GP) were enriched in MMI isolates and positively correlated with pyrene degradation efficiency. Pyrene degradation by Sphingomonas sp. YT1005 only followed the phthalate pathway, whereas both phthalate and salicylate pathways were observed in the active pyrene degrading consortium. The results indicated that the uncultivable pyrene degraders were suitable for bioaugmentation, rather than cultivable Sphingomonas sp. YT1005. The negative correlations between Sphingomonas sp. YT1005 and the active-yet-uncultivable pyrene degraders were the underlying mechanisms of bioaugmentation postpone in engineering practices.

Full text of DOI:10.1016/j.jhazmat.2021.127189

Journal Pre-proof
Negative correlations between cultivable and
active-yet-uncultivable pyrene degraders explain
the postponed bioaugmentation
Bo Jiang, Yating Chen, Yi Xing, Luning Lian,
Yaoxin Shen, Baogang Zhang, Han Zhang,
Guangdong Sun, Junyi Li, Xinzi Wang, Dayi
Zhang
PII:
S0304-3894(21)02157-9
DOI:
https://doi.org/10.1016/j.jhazmat.2021.127189
HAZMAT127189
Reference:
To appear in: Journal of Hazardous Materials
Received date: 18 June 2021
Revised date: 6 September 2021
Accepted date: 7 September 2021
Please cite this article as: Bo Jiang, Yating Chen, Yi Xing, Luning Lian, Yaoxin
Shen, Baogang Zhang, Han Zhang, Guangdong Sun, Junyi Li, Xinzi Wang and
Dayi Zhang, Negative correlations between cultivable and active-yet-uncultivable
pyrene degraders explain the postponed bioaugmentation, Journal of Hazardous
Materials, (2021) doi:https://doi.org/10.1016/j.jhazmat.2021.127189
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Negative correlations between cultivable and
active-yet-uncultivable pyrene degraders explain the
postponed bioaugmentation
1
,2,3
1,2
1,2
1,2
1,2
Bo Jiang , Yating Chen , Yi Xing , Luning Lian , Yaoxin Shen , Baogang
4
4
5
6
5
7,*
Zhang , Han Zhang , Guangdong Sun , Junyi Li , Xinzi Wang , Dayi Zhang
1
School of Energy and Environmental Engineering, University of Science &
Technology Beijing, Beijing 100083, PR China
2
Beijing Key Laboratory of Resource-oriented Treatment of Industrial Pollutants,
University of Science & Technology Beijing, Beijing 100083, PR China
3
National Engineering Laboratory for Site Remediation Technologies, Beijing
1
00015, PR China
4
School of Water Resources and Environment, MOE Key Lab Groundwater
Circulation and Environment Evolution, China University of Geosciences, Beijing
1
00083, PR China
5
School of Environment, Tsinghua University, Beijing 100084, PR China
Department of Research and Development, Yiqing (Suzhou) Environmental
6
Technology Co. Ltd, Suzhou 215163, PR China
7
College of New Energy and Environment, Jilin University, Changchun 130021, PR
China
*
Corresponding author
Dr Dayi Zhang, College of New Energy and Environment, Jilin University,
Changchun 130021, PR China, email: zhangdayi@tsinghua.org.cn
1
/ 54

Abstract
Bioaugmentation is an effective approach to remediate soils contaminated by
polycyclic aromatic hydrocarbon (PAHs), but suffers from unsatisfactory performance
in engineering practices, which is hypothetically explained by the complicated
interactions between indigenous microbes and introduced degraders. This study
isolated a cultivable pyrene degrader (Sphingomonas sp. YT1005) and an active pyrene
degrading consortium (Gp16, Streptomyces, Pseudonocardia, Panacagrimonas,
Methylotenera and Nitrospira) by magnetic-nanoparticle mediated isolation (MMI)
from soils. Pyrene biodegradation was postponed in bioaugmentation with
Sphingomonas sp. YT1005, whilst increased by 30.17% by the active pyrene degrading
consortium. Pyrene dioxygenase encoding genes (nidA, nidA3 and PAH-RHDα-GP)
were enriched in MMI isolates and positively correlated with pyrene degradation
efficiency. Pyrene degradation by Sphingomonas sp. YT1005 only followed the
phthalate pathway, whereas both phthalate and salicylate pathways were observed in
the active pyrene degrading consortium. The results indicated that the uncultivable
pyrene degraders were suitable for bioaugmentation, rather than cultivable
Sphingomonas sp. YT1005. The negative correlations between Sphingomonas sp.
YT1005 and the active-yet-uncultivable pyrene degraders were the underlying
mechanisms of bioaugmentation postpone in engineering practices.
Keywords: Bioaugmentation, pyrene, soils, magnetic nanoparticle-mediated isolation
(
MMI), degradation pathway
2
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1. Introduction
Polycyclic aromatic hydrocarbons (PAHs) are a typical group of persistent organic
pollutants (POPs) containing two or more combined aromatic rings in linear, angular
or cluster arrangements (Ghosal, et al., 2016). As natural constituents in fossil fuels,
PAHs are present with high concentrations at sites with petroleum refining and
transportation activities (Kanaly and Harayama, 2000). At least 600 of 1,408 most
severely contaminated sites in USA are contaminated with PAHs (Duan, et al., 2015).
Additionally, PAHs can migrate into soils through dry and wet atmospheric deposition
(
Nam, et al., 2008, Wang, et al., 2017a), and soils are able to attenuate PAHs transport
and serve as major sinks (Liu, et al., 2019, Okere, et al., 2017). Moreover, soil PAHs
can enter the food chain through bioaccumulation, imposing serious threats to human
health (Kim, et al., 2013, Wang, et al., 2017b). Thus, PAHs have gained great
attention in recent decades for their ubiquitous presence in environment and high
resistance to degradation.
Bioremediation is known as a cost-efficient and environmentally friendly approach to
degrade soil pollutants, with low risks in secondary pollution (Haleyur, et al., 2018,
Peng, et al., 2008). PAH-degrading bacteria are capable of metabolizing various PAHs
via enzymatic attacks on different carbon positions (Segura, et al., 2017, Zeng, et al.,
2
017). PAH ring hydroxylating dioxygenase (PAH-RHD) are responsible for the initial
step of PAHs metabolism (Cebron, et al., 2008), and the encoding genes include ahd
Pinyakong, et al., 2003), dox (Denome, et al., 1993), flnA1/A2 (Schuler, et al., 2008),
nag (Izmalkova, et al., 2013), nahR (Bosch, et al., 2000), nar (Liu, et al., 2011), nidA/B
(
(
(
Stingley, et al., 2004), nidA3 (Chen, et al., 2016), pah (Takizawa, et al., 1999), pdo
Krivobok, et al., 2003), phd (Saito, et al., 1999) and phn (Izmalkova, et al., 2013).
3
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Pyrene is a typical PAH for its similar structure to several carcinogenic PAHs (Peng, et
al., 2008). Pyrene biodegradation has been intensively studied, either as carbon and
energy source, or as a non-growth substrate in co-metabolism (Johnsen, et al., 2005,
Nzila, 2013). Pyrene degraders include Acinetobacter (Jiang, et al., 2018b),
Burkholderia (Vaidya, et al., 2017), Bacillus (Rabodonirina, et al., 2018), Klebsiella
(
Elyamine, et al., 2021), Kocuria (Sakshi, et al., 2021), Mycobacterium (Elyamine, et
al., 2021, Wu, et al., 2019), Pseudomonas (Elyamine, et al., 2021, Khan, et al., 2018),
Rhodococcus (Jia, et al., 2019, Sakshi, et al., 2021) and Sphingomonas (Guo, et al.,
2
017).
Bioaugmentation is a practical strategy to improve bioremediation performance at
contaminated sites by introducing competent strains or consortia capable of degrading
target contaminants (Perelo, 2010). For instance, bioaugmentation with autochthonous
Acinetobacter tandoii LJ-5 significantly improved phenanthrene removal efficiency
by changing the diversity of phenanthrene degraders (Li, et al., 2018a). Other strains
in bioaugmentation for PAH degradation include Klebsiella pneumonia (Mohanrasu,
et al., 2018) and Acinetobacter johnsonii (Jiang, et al., 2018b). Although several field
studies have demonstrated the feasibility of bioaugmentation to enhance
bioremediation performance in groundwater (Major, et al., 2002), wastewater (Wu, et
al., 2018) and aquifer (Dybas, et al., 2002), scaling up from laboratory to
commercial-scale field is always a challenge. Both abiotic (temperature, moisture, pH,
organic matter, aeration, nutrient and soil type) (Heinaru, et al., 2005) and biotic
factors (competition between indigenous and exogenous microorganisms for limited
nutrients) (Mrozik and Piotrowska-Seget, 2010, Sørensen, et al., 1999) influence
bioaugmentation performance. Additionally, the mechanisms of bioaugmentation are
4
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argued (Thompson, et al., 2005), and little is known about the interactions of the
introduced degraders with indigenous microbes during bioaugmentation process.
Although cultivation approaches have isolated many PAH degraders, only around 1%
(
(
Kaeberlein, et al., 2002, Vartoukian, et al., 2010) or slightly more proportions
Martiny, 2019) of soil microorganisms are cultivable under artificial conditions.
Stable isotope probing (SIP) is a well-developed approach to identify
functional-yet-uncultivable microorganisms in situ (Jiang, et al., 2018a), which
however, relies on the isotope incorporation in the active degraders and in most cases
cannot isolate living degraders suitable for bioaugmentation. Although SIP coupled
with single cell technologies could help in isolating the functional-yet-uncultivable
microorganisms for bioaugmentation, the following cultivation step is still
challenging for engineering purposes (Wang, et al., 2016b). Recently, a novel
technique, magnetic-nanoparticles (MNPs) mediated isolation (MMI), is innovated and
aims at separating active degraders from inert bacteria by magnetic gradient (Zhang, et
al., 2015, Zhao, et al., 2016). This isotope-independent approach MMI can isolate the
active degraders from complex environment in a cost-effective manner. Importantly,
the separated microbes remain viable to be used in bioaugmentation (Sun, et al., 2021).
In the present study, both pure cultivation and MMI approaches were applied to isolate
pyrene degraders from an abandoned steel plant site. Using cultivable pyrene degrader
Sphingomonas sp. YT1005 and MMI-enriched active pyrene-degrading consortium in
bioaugmentation, we analyzed the pyrene degradation efficiency, metabolic pathway,
and pyrene dioxygenase encoding genes. With the hypothesis that microbial
intra-correlations play critical roles in pyrene degradation process and affect pyrene
metabolism, this work aims to investigate the bioaugmentation performance with
5
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cultivable pyrene degraders, unravel the active pyrene degraders via MMI, explore the
bacterial interactions during bioaugmentation process, and explain the underlying
mechanisms leading to the postponed bioaugmentation. As the first study to separate
and introduce the active pyrene-degrading microbes in soil bioaugmentation, this work
can broaden our knowledge on the influential factors affecting bioaugmentation
performance and provide novel ideas for improving bioaugmentation performance.
2. Materials and methods
2
.1.Soil sample
Soil samples were collected at an abandoned site of Capital Steel Plant located in
Shijingshan District, Beijing. This site was severely contaminated by PAHs and the
PAHs concentration ranged from several to over 500 mg/kg. One kilogram of soils was
obtained from the surface layer (0-20 cm) in the absence of PAHs contamination, stored
at 4ºC and transferred to laboratory. After homogenization, stones and plant debris were
removed. Soil geochemical properties were analyzed and listed in Table S1 (Supporting
Information). There was no detectable PAHs in the collected soils and the limits of
detection and quantification of PAHs are listed in Table S2 (Supporting Information).
2
.2.Isolation of cultivable bacterial pyrene degraders, and pyrene degradation
experiment in pure culture
Four grams of original soils were added into 100 mL of enrichment medium (details in
Supporting Information) supplemented with pyrene (100 mg/L, details in Supporting
Information). After 7-day incubation with continuous shaking (180 rpm) at 28ºC in the
dark, 1 mL of the suspension was transferred into 100 mL of fresh enrichment medium
with increasing pyrene concentration (200, 300, 400 and 500 mg/L). Afterwards, the
6
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enriched suspension was diluted and spread onto a mineral medium agar plate
supplemented with pyrene (500 mg/L, Supporting Information) as the sole carbon
source (Zhang, et al., 2012). After incubation at 28ºC for 2 days in the dark, single
colonies were picked from the plate and streaked twice on fresh mineral medium agar
plates supplemented with pyrene (500 mg/L). Then the 16S rRNA of all the isolates
were sequenced, and compared to that in NCBI database.
The isolated pyrene-degrading strain were pre-cultured in 10 mL minimal medium
(
containing 500 mg/L pyrene) at 28 °C for 24 h, shaking at 180 rpm. When the cells
reached the logarithmic phase with an OD 600 of 0.5-0.6, they were washed twice at
000 rcf for 10 min and resuspended in fresh minimal media. Subsequently, the
4
resuspended cells were transferred to 100 mL minimal medium containing 500 mg/L
pyrene for further study on pyrene degradation in pure culture.
2
.3.Pyrene degradation microcosms
To enrich active pyrene degraders and explore pyrene biodegradation performance in
soils, five treatments were carried out. The sterile control (OS_CK) was prepared by
sterilizing the soils with HgCl (0.1%) and supplemented with pyrene to study abiotic
2
pyrene degradation. As bioaugmentation is normally applied to original soils by adding
target degraders, we followed the same principle to use original soils for
bioaugmentation treatments. Generally, treatments with original soils were named as
‘OS_’, treatments with soils functionalized with MNP were designated as ‘MMI_’, and
bioaugmentation treatments were named as ‘BA_’. The four biotic treatments included
original soils without pyrene (OS_NC), original soils supplemented with pyrene
(
OS_Pyr), MNP-functionalized soils without pyrene (MMI_NC) and
MNP-functionalized soils supplemented with pyrene (MMI_Pyr).
7
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MNPs synthesis followed our published method (Zhang, et al., 2011) and the
concentration was 9.1 g/L. To functionalize soils, 0.91 mg of synthesized MNPs (0.1
mL) were added to 500 mg soils (dry weight) according to the optimal dosage for soil
magnetic functionalization (Wang, et al., 2016a). For OS_CK, OS_Pyr and MMI_Pyr
treatments, pyrene was set at a final concentration of 100 mg/kg, meeting with the
average contamination level at the contaminated site. Each treatment was conducted in
triplicates and incubated at room temperature for 30 days. After 0, 10, 20 and 30 days of
cultivation, 5.0 g of soil samples were collected for chemical analysis and DNA
extraction. To separate the active pyrene degrading consortium (magnetic-free cells,
MFCs), 2.0 g of soils were collected from MMI_NC and MMI_Pyr treatments on Day
0
, 10, 20 and 30. Subsequently, the soils were added with 3 mL of soil extraction
solution (2.0 g of original soils with 20 mL deionized water and passing through a
.45-mm filter) and further separated by a permanent magnet (Li, et al., 2018b). MFCs
0
in suspensions separated from MMI_NC and MMI_Pyr treatment were designated as
MFC_NC and MFC_Pyr.
Bioaugmentation experiment introduced the cultivable pyrene degrader Sphingomonas
sp. YT1005 or MFCs (MMI-enriched pyrene-degrading consortium) into soils with
9
total populations of 10 cells/g soil. The four treatments included: original soils
supplemented with the cultivable pyrene degrader (Sphingomonas sp. YT1005) was
represented as BA_Sph, and sterile soils (treated with UV-254 for 30 min)
supplemented with the cultivable pyrene degrader (Sphingomonas sp. YT1005) was
represented as CK_Sph, original soils supplemented with MFCs was represented as
BA_MFC, and sterile soils (treated with UV-254 for 30 min) supplemented with MFCs
was represented as CK_MFC. Pyrene was set at a final concentration of 100 mg/kg in
8
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all treatments, which were incubated at 28ºC in the dark in triplicates. Finally, 5.0 g of
soils were sacrificed after 0, 10 and 20 days for chemical analysis and DNA extraction.
2
.4.DNA extraction, quantification, sequence and analysis
Soil genomic DNA was extracted from all 19 soil samples in all treatments using a
MO BIO PowerSoil DNA Isolation Kit (MoBio Laboratories, Inc., USA) according to
the manufacturer’s instructions. DNA concentration was determined by
spectrophotometry (NanoDrop 2000, Wilmington, DE). Quantitative PCR (qPCR)
was performed for the abundance of bacterial 16S rRNA and pyrene dioxygenase
encoding genes (Cebron, et al., 2008, Zhou, et al., 2006), including PAH-RHDα-GP,
PAH-RHDα-GN, nidA and nidA3 (in Table S3). The 20 μL qPCR system consisted of
2
μL of each primer, 1 μL of DNA template, 5 μL of ultrapure water and 10 μL of
®
iTaq™ Universal SYBR Green Supermix (BioRad, USA). Standard curves were
obtained with serial dilutions of quantified plasmid DNA containing the fragment of
1
6S rRNA and pyrene-degrading genes (Jiang, et al., 2019). The primer and qPCR
programs were listed in Table S3.
To assess bacterial community composition and diversity, the extracted DNA was
amplified and sequenced targeting the V3-V4 regions of 16S rRNA genes (Sangon
Biotech Co., Ltd, Beijing, China). PCR was performed using the universal primer set
of
515F
(5’-GTGCCAGCMGCCGCGGTAA-3’)
and
806R
(
5’-GGACTACHVGGGTWTCTAAT-3’) (Song, et al., 2015). Sequencing was
performed by Illumina Miseq™ and all sequence reads were quality checked after
removing primer connector sequences, merging paired reads and distinguishing
samples according to barcodes (NCBI BioProject ID: PRJNA534380). Sequences
were classified as operational taxonomic units (OTUs) with 97% similarity and then
assigned by Ribosomal Database Project (RDP) classifier based on Bergey’s
9
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taxonomy. Bacterial alpha-diversity indices (Chao1, Shannon and Simpson) were
analyzed by QIIME (v1.80) to assess bacterial species richness and diversity. The
distance matrices from samples were generated by the Bray-Curtis metric and
visualized by principal coordinates analysis (PCoA) by QIIME (Quantitative Insights
Into Microbial Ecology) software (Wang, et al., 2016a).
2
.5.Chemical analysis
To analyze soil pyrene contents, 5.0 g of soils were blended with 3 g of anhydrous
Na
2
SO
4
, spiked with 10 mL of surrogate standards (10 μg/mL, phenanthrene-d10,
®
AccuStandard , Inc.), and added with 15 mL of extraction solvent
(
hexane:acetone=1:1, v/v). After ultrasonication-assisted extraction for 20 min, the
suspension was centrifuged for 3 min at 15,000 rcf. The extraction process was
repeated twice, and the three fractions of supernatants were mixed and concentrated
using a rotary evaporator to a final volume of approximately 2 mL at 60°C. It was
further purified by solid phase extraction cartridges (Bond Elut-C18, 100 mg/1 mL,
Agilent), which were pre-conditioned with 4 mL of dichloromethane and 10 mL of
hexane, and washed by 5 mL of dichloromethane:hexane (1:9, v/v). After soaking for 2
min, another 5 mL of dichloromethane:hexane (1:9, v/v) were added to elute pyrene
and the filtrates were concentrated to completely dry under a gentle stream of nitrogen
gas. Internal standards (fluorene, 100 μg/mL) were added to each filtrate prior to
instrumental analysis.
The quantitative analysis of pyrene was performed using a gas chromatography mass
spectrometry (GC-MS, Shimadzu, QP2010SE) equipped with a DB-5MS capillary
column (30 m in length, 0.25 mm in diameter, 0.25 μm thickness) and a mass
spectrometric detector (ionisation energy, 70 eV, details in Supporting Information).
10 / 54

Five pyrene standard concentrations (5-500 ng/mL) were used to derive the calibration
2
curve for pyrene (R >0.999). Mean recoveries of surrogate standards
(
phenanthrene-d10) in the present study ranged from 90% to 105% and the final
concentrations of pyrene were corrected by surrogate recovery. For the detection of
PAH metabolites, the samples were derivatized with BSTFA/TMCS (99:1)
(
bis(trimethylsilyl) trifluoroacetamide N trimethylchlorosilane) for 1 h at 68°C, and
then detected with GC-MS as previously reported (Lu, et al., 2013, Wu, et al., 2019).
The details for PAHs metabolite detection were provided in Supporting Information.
The molecular mass of each metabolite was searched against previous literatures and
the database of PAH metabolites (National Institute of Standards and Technology,
NIST). The chemical structure of each possible metabolite was confirmed by the
pattern of fragment ions in the mass spectrum.
2
.6.Statistical analysis
Statistical analysis was performed by SPSS 20.0 software. One-way analysis of
variance (ANOVA) was used to compare the difference in pyrene contents and the
relative abundance of 16S rRNA and pyrene dioxygenase encoding genes (p<0.05).
The correlation matrix was calculated and visualized using R (version 3.5.3). The
phylogenetic tree of 16S rRNA genes was constructed according to the neighbor
joining method using Molecular Evolutionary Genetics Analysis (MEGA). Molecular
ecological network was constructed by online MENA (Molecular Ecological Network
Analyses) pipeline (http://ieg2.ou.edu/MENA) using Spearman's Rho with default
parameters (Deng, et al., 2018).
11 / 54

The logarithmic nonlinear regression between pyrene degradation efficiency (P
D
, %)
and the abundance of pyrene dioxygenase encoding genes (Pyrene
followed Equation (1):
g
, copies/g soil)
푃 = 푃 + 푎 × ln
(푃푦푟푒푛푒푔)
(1)
퐷
0
Here, 푃 and 푎 represents pyrene degradation efficiency in abiotic treatments and
0
correlation slope, respectively.
3. Results
3
.1.Biodegradation and bioaugmentation performance
Pyrene degradation efficiencies in different treatments are illustrated in Figure 1. In
abiotic treatment (OS_CK), pyrene content did not show significant decrease
throughout the incubation period. An acceptable pyrene degradation was achieved in
OS_Pyr treatment, and pyrene degradation efficiency was 30.18% on day 10 and 44.24%
on day 20.
After introducing the cultivable pyrene degraders (Sphingomonas sp. YT1005 in
BA_Sph and CK_Sph treatments and MMI-isolated active pyrene-degrading
consortium in BA_MFC and CK_MFC treatments) in bioaugmentation, pyrene
degradation performance varied remarkably across treatments (Figure 1). An
unexpected postpone of pyrene degradation was found in BA_Sph and CK_Sph
treatments that pyrene degradation efficiency was less than 20% after 20-day
incubation, exhibiting no significant difference with that in abiotic sterile treatment
(
OS_CK, p>0.05). BA_MFC treatment (original soils with MMI-isolated active
pyrene-degrading consortium) accelerated pyrene degradation efficiency to 57.79% on
12 / 54

day 10 and 74.41% on day 20. It is worth highlighting that CK_MFC treatment (sterile
soils with MMI-isolated active pyrene-degrading consortium) had a similar pyrene
degradation curve as OS_Pyr treatment, suggesting that the introduced active
pyrene-degrading consortium alone had the same pyrene degradation capabilities as
indigenous soil microbes.
Both first-order and second-order pyrene degradation kinetics were calculated for the
five treatments, including OS_Pyr, BA_ Sph, CK_ Sph, BA_MFC and CK_MFC.
Except for pyrene degradation in BA_ Sph treatment as a second-order kinetics with a
2
half-life (t1/2) of 14.28 d (R =0.5895), other pyrene degradation processes all followed
2
the first-order kinetics, and t1/2 was 9.49 (OS_Pyr, R =0.7656), 10.50 (CK_ Sph,
2
2
2
R =0.6515), 6.99 (BA_MFC, R =0.9108) and 7.89 d (CK_MFC, R =0.7673). This
result indicated that bioaugmentation with the active pyrene degraders (BA_MFC and
CK_MFC) could significantly accelerate pyrene biodegradation.
3
.2.Microbial community diversity and structure during pyrene degradation
process
After processing raw data obtained by Illumina Miseq, a total of 895,290 raw reads
with a length of >450 bp were obtained from 19 soil samples in five treatments, ranging
from 50,899 in MMI_Pyr_30 to 77,369 in MMI_Pyr_20. They were assigned into
1
5,210 OTUs affiliated with 30 bacterial phyla and 100 bacterial genera. Across all
samples, the Good’s coverage ranged from 0.95 to 0.99, indicating a satisfactory
coverage of bacterial lineages for further analysis. In all treatments, bacterial
alpha-diversity indices (Chao1, Shannon and Simpson) did not show significant
difference (Table S4).
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Sphingomonas was the most predominant bacterial genus, accounting for 4.12% of
total bacterial populations in treatment without pyrene (OS_NC) to 37.81% in
MFC_Pyr treatments. Other dominant bacterial genera included Arthrobacter (9.33%
to 9.87%), Lysobacter (3.42% to 6.24%), Rhodococcus (3.07% to 5.19%), Pedobacter
(
3.43% to 4.06%), Aeromicrobium (3.00% to 3.07%) and Pseudonocardia (2.47% to
.58%) in original soils and OS_NC treatments (Figure S1).
3
From bacterial beta-diversity distance matrices (Figure 2A), bacterial community
compositions in OS_NC and OS_Pyr treatments were similar and clustered together in
the first 10-day of pyrene degradation. Afterwards, the relative abundance of some
bacterial taxa in OS_Pyr treatments was significantly higher than that in OS_NC
treatments, including Kribbella (2.00%), Streptomyces (2.92%), Lysobacter (8.69%),
Streptomyces (4.75%) and Thermomonas (3.24%). Accordingly, the groups of OS_NC
and OS_Pyr were separated after day 10. Similarly, bacterial communities in MMI_NC
and MMI_Pyr treatments were also clustered (Figure 2A). In the absence of pyrene,
bacterial community composition showed no difference between MMI_NC and
MFC_NC (Figure 2B).
3
.3.Pyrene
degraders
revealed
by
cultivation-dependent
and
cultivation-independent methods
In total, 8 isolates were obtained from mineral medium agar plates supplemented with
pyrene. The results of 16S rRNA gene sequencing demonstrated that all isolates have
identical sequence, exhibiting 98% similarity with Sphingomonas echinoides DSM
1
805 (NCBI Accession No: MK934417). This cultivable pyrene degrader was then
designated as Sphingomonas sp. YT1005 (amplification and sequence details in
Supporting Information, NCBI Accession No. MK934417.1). With pyrene as the sole
14 / 54

carbon source, this strain formed orange pigmented colonies on agar plates.
Additionally, Sphingomonas sp. YT1005 had a satisfactory pyrene degradation
efficiency, which achieved 62.3% after 10-day incubation in mineral medium.
In treatments with MNPs functionalized bacteria (MMI_Pyr treatment), the active
pyrene degraders could utilize pyrene and proliferate, gradually losing MNPs on the
membrane of the newly-formed pyrene degrading cells. In contrast, all the other inert
cells maintained their magnetism and could be separated by external magnetic field
(
Wang, et al., 2016a, Zhang, et al., 2011, Zhang, et al., 2015). Bacterial beta-diversity
distance matrices illustrated that MFCs isolated from MMI_Pyr treatment (MFC_Pyr)
were separated from the whole community in MMI_Pyr treatment and MFC_NC
(
MFCs from MMI_NC treatments, Figure 2B). Accordingly, by comparing the
relative abundance of bacterial lineages, several bacterial genera were much higher in
MFC_Pyr and they were potentially the active pyrene degraders. They included Gp16,
Streptomyces, Pseudonocardia, Panacagrimonas, Methylotenera and Nitrospira,
which was 1.442±0.207, 1.511±0.216, 1.621±0.615, 4.573±1.641, 2.526±0.698 and
1
.533±0.052 times more enriched in MFC_Pyr, respectively (Figure 2C).
In treatments without pyrene (OS_NC), neither Sphingomonas sp. YT1005 nor the
active pyrene degrading consortium (Gp16, Streptomyces, Pseudonocardia,
Panacagrimonas, Methylotenera and Nitrospira) were enriched in the magnetic-free
fraction (MFC_NC, Figure 3A), remaining 28.0-30.6% and 1.9-3.0% throughout the
pyrene degradation process, respectively. In contrast, the relative abundance of
Sphingomonas sp. YT1005 in MFC_Pyr fraction significantly decreased from 26.5% to
8
2
.5%, whereas the relative abundance of the potential pyrene degraders increased from
.3% to 5.2% (Figure 3B).
15 / 54

The phylogenetic tree of the cultivable pyrene degrader Sphingomonas sp. YT1005 and
the potential active pyrene degraders in MFC_Pyr was illustrated in Figure 3C.
Sphingomonas sp. YT1005 is clustered with other Sphingomonas species, e.g.,
Sphingomonas echinoides and Sphingomonas glacialis. All the potential active pyrene
degraders isolated from MMI_Pyr treatment, including Nitrospira (OTU23472), Gp16
(
OTU33542),
Streptomyces
(OTU29458),
Pseudonocardia
(OTU29851),
Panacagrimonas (OTU4395) and Methylotenera (OTU583), were clustered in a
separate branch.
3
.4.Intra-correlation within soil bacterial community
To explain the mechanisms of bioaugmentation postpone in BA_Sph and CK_Sph
treatments, we analyzed the bacterial intra-correlations by molecular ecological
network (Figure 4, Table S5). The results suggested a complex microbial network in
soils (avgK=4.356 and avgCC=0.205), including 4 major modules, 360 nodes and 784
significant correlations (p<0.01). The majority (90.1%) of the correlations were
positive, and the cultivable pyrene degrader Sphingomonas (OTU33525) exhibited 12
positive links with Module 2. Four of the potential active pyrene degraders (Nitrospira,
OTU23472; Streptomyces, OTU29458; Panacagrimonas, OTU4395; Methylotenera
OTU583) had 39 correlations with other bacterial lineages, 56.4% of which were
negative. It is worth noting that, although there was no direct correlation between the
cultivable pyrene degrader Sphingomonas and the potential active pyrene degraders, 11
indirect correlations (mediated by other microbes from the 4 major modules) were
observed and they were all negative. Additionally, Mantel test confirmed the negative
correlations between Sphingomonas and the potential active pyrene degraders (p<0.05),
and the correlation coefficient was -0.7285 for Gp16, -0.7533 for Streptomyces,
16 / 54

-
0.8287 for Pseudonocardia, -0.7548 for Panacagrimonas and -0.7956 for
Methylotenera (p<0.05). Our results therefore uncovered negative correlations between
the cultivable pyrene degrader Sphingomonas sp. YT1005 and the active pyrene
degrading consortium isolated by MMI, which suppressed the bioaugmentation
performance at the beginning in BA_Sph and CK_Sph treatments.
3
.5.Dynamics of pyrene dioxygenase encoding genes
No PAH-RHDα-GN gene was successfully amplified in any treatment. The relative
abundance of nidA, nidA3, and PAH-RHDα-GP genes in OS_NC treatment remained
-7
constant throughout the incubation period (Figure 5A), ranging from 0.96×10 to
-7
-7
-7
-7
-7
1
.32×10 , 3.62×10 to 4.25×10 and 44.5×10 to 50.1×10 , respectively. It indicated
a neglectable increase of pyrene dioxygenase encoding genes in the absence of pyrene.
The relative abundance of nidA, nidA3 and PAH-RHDα-GP genes increased
significantly (p<0.01) in OS_Pyr treatments since day 20 and finally achieved
-5
-5
-5
1
.00×10 , 2.84×10 and 2.15×10 on day 30, which was 105.5, 74.6 and 4.7 times
higher than those in OS_NC treatments. Interestingly, all these pyrene dioxygenase
encoding genes dramatically increased in MFC_Pyr from day 10. After 30-day
degradation, the relative abundance of nidA, nidA3 and PAH-RHDα-GP genes
-4
-4
-4
increased to 1.13×10 , 2.88×10 and 2.24×10 , which was 1182.6, 754.8 and 49.3
times higher than that in OS_NC treatments.
There were significantly positive correlations between pyrene degradation efficiency
and the relative abundance of nidA, nidA3 and PAH-RHDα-GP genes (p<0.01, Table
-6
2
-6
2
S6). The regression coefficient was 2.72×10 (r =0.9671), 4.74×10 (r =0.9064) and
-6
2
1
5
.60×10 (r =0.8790) for nidA, nidA3 and PAH-RHDα GP genes, respectively (Figure
D).
17 / 54

The abundance of the active pyrene degraders in MFC_pyr increased during the
degradation process from 2.3% (Day 10) to 5.2% (Day 30, Figure 3B), 1.74- and
2
.26-times higher on Day 20 and Day 30, respectively. The relative abundance of
pyrene-degrading genes in MFC_pyr treatment also increased (Figure 5C). For
-5
-5
-4
instance, the relative abundance of nidA gene was 3.68×10 , 3.71×10 and 1.13×10
on Day 10, 20 and 30, respectively. The relative abundance of nidA3 and
PAH-RHDα-GP genes was 3.88- and 2.60-times higher on Day 30 than those on Day
1
0. The similar increasing trends of the active pyrene degraders (Figure 3B) and
pyrene-degrading genes (Figure 5) hinted that these active pyrene degraders harbor
the studied pyrene-degrading genes for pyrene metabolism.
3
.6.Metabolites and degradation pathway of pyrene
To understand pyrene degradation pathways in bioaugmentation, metabolites were
analyzed during pyrene biodegradation process in CK_Sph and CK_MFC treatments.
In total, ten metabolites were identified, and two pyrene degradation pathways were
proposed (Figure 6 and S3, Table S7).
In CK_Sph treatment, the metabolite cis-4,5-pyrene dihydrodiol (m/z=364, t =19.82
R
min) might be generated from an initial pyrene oxidation at C-4 and C-5 positions by
dioxygenase, designated as metabolite ① . Although the following metabolite
phenanthrene-4-carboxylic acid (by ortho-cleavage and decarboxylation) was not
detectable, its downstream metabolite was detected as dihydroxyphenanthrene
(
metabolite ②, m/z=355, t =5.31 min). Further oxidation of dihydroxyphenanthrene
R
generated 2-hydroxy-2-H-benzo[h]chromene-2-carboxylic acid (metabolite ③ ,
m/z=415) by extradiol dioxygenase after ring cleavage, and subsequent to
18 / 54

2
-methylnaphthalene (metabolite ④ , m/z=142) and 1-hydroxy-2-naphthoic acid
(
metabolite ⑤, m/z=202). Finally, metabolite ⑥ (m/z=167, t =21.73 min) was
R
identified as phthalic acid comparing to the mass spectral library (NIST). From these
metabolites, there was only one phthalate pathway by the cultivable pyrene degrader
Sphingomonas sp. YT1005.
In CK_MFC treatments, all ten metabolites are identified (Figure 6 and S3, Table S7).
Besides those in the phthalate pathway in CK_Sph treatment, metabolite ⑦
(
m/z=427) was protocatechuic acid, a downstream metabolite of phthalic acid by
dioxygenase, dehydrogenase and decarboxylase. It suggested that phthalic acid was
further metabolized by the active pyrene degrading consortium enriched by MMI and
entered the tricarboxylic acid (TCA) cycle via β-ketoadipate pathway. Alternatively,
metabolite
phenanthrene-4-carboxylic acid. Metabolite ⑨ (m/z=206, t
metabolite ⑩ (m/z=206, t =20.87 min) was trans-2'-carboxybenzalpyruvate and
salicylic acid, respectively. They were two downstream metabolites of
-hydroxy-2-naphthoic acid (metabolite ⑤). As metabolites ⑨ and ⑩ were only
⑧
(m/z=267) was identified as 4-phenanthrenol from
R
=8.47 min) and
R
1
detectable in CK_MFC treatment, MMI-enriched active pyrene degrading consortium
exhibited a unique salicylate pathway for pyrene degradation.
In the phthalate pathway, metabolites ①, ②, ③ and ④ were detected in all
treatments but only on Day 10. Metabolite ⑤ was detected on all sampling days in
all treatments, whereas metabolites ⑥ was only detectable on Day 20. These results
suggested metabolites ① , ② , ③ and ④ were gradually metabolized into
downstream metabolites (⑤ and ⑥), which accumulated during pyrene degradation
1
9 / 54

process. In the salicylate pathway, metabolite ⑧ was detected on days 20 and 30,
also suggesting a significant accumulation of downstream metabolites.
4. Discussion
Pyrene is a typical PAH for its similar structure to several carcinogenic PAHs (Peng, et
al., 2008). Pyrene biodegradation has been intensively studied, either as carbon and
energy source, or as a non-growth substrate in co-metabolism (Johnsen, et al., 2005,
Nzila, 2013). Pyrene degraders include Acinetobacter (Jiang, et al., 2018b),
Burkholderia (Vaidya, et al., 2017), Bacillus (Rabodonirina, et al., 2018),
Mycobacterium (Wu, et al., 2019), Pseudomonas (Khan, et al., 2018), Rhodococcus (Jia,
et al., 2019) and Sphingomonas (Guo, et al., 2017). In the present study, Sphingomonas
sp. YT1005 was identified as a cultivable pyrene degrader from soils at an abandoned
steel plant site. Sphingomonas is a typical PAH-degrading microorganism (Zhao, et al.,
2
017). Sphingomonas LB126 is reported to use fluorene as the sole carbon or energy
source and can co-metabolize phenanthrene, fluoranthene, anthracene and
dibenzothiophene (van Herwijnen, et al., 2003). Sphingomonas sp. GY2B isolated from
petroleum-contaminated soils could degrade phenanthrene through the salicylate
pathway (Tao, et al., 2007). However, the isolated strain Sphingomonas sp. YT1005 in
this study was affiliated close to Sphingomonas echinoides, which is not previously
linked with pyrene degradation, and our study brought direct evidence of their
functions in metabolizing pyrene.
The dominant bacterial genera in soils (Sphingomonas, Arthrobacter, Lysobacter,
Rhodococcus, Pedobacter, Aeromicrobium and Pseudonocardia) are abundant soil
bacterial lineages (Delgado-Baquerizo, et al., 2018) and participate in soil carbon and
nitrogen cycles (Schimel and Schaeffer, 2012). After pyrene degradation, the relative
2
0 / 54

abundance of Pseudonocardia, Streptomyces, Lysobacter and Thermomonas
significantly increased. They are reported to be responsible for PAHs biodegradation by
many previous studies. Lysobacter is linked to pyrene degradation (Wang, et al., 2018)
and Thermomonas has the capacity of degrading anthracene (Nzila, et al., 2018). Our
findings were consistent with these reports and indicated that predominant bacterial
taxa in pyrene-contaminated soils were related to pyrene tolerance or degradation.
Both bacterial α-diversity and community composition were of no significant
difference between OS_NC and MMI_NC treatments, indicating that
MNP-functionalization had little impacts on soil bacterial community and did not affect
pyrene biodegradation process (Wang, et al., 2016a). During the pyrene degradation
process, the active pyrene degraders utilized pyrene and lost magnetism gradually,
resulting in their enrichment in the magnetic-free fractions of MFCs (Zhang, et al.,
2
015). Accordingly, the community structure of MFC_Pyr was different from
MFC_NC and the enriched bacterial lineages were the potential active pyrene
degraders (Figure 2B).
The active pyrene degrading consortium isolated by MMI included Gp16,
Streptomyces, Pseudonocardia, Panacagrimonas, Methylotenera and Nitrospira
(
Figure 3C). Among them, the roles of Streptomyces and Pseudonocardia in PAH
biodegradation have been previously reported (Chaudhary, et al., 2011, Chen, et al.,
018). Pseudonocardia could degrade pyrene in agricultural soils (Chen, et al., 2018)
2
and Streptomyces rochei was capable of using anthracene, fluorene, phenanthrene and
pyrene as the sole carbon source (Chaudhary, et al., 2011). As for other bacterial taxa,
Gp16 is reported to tolerate toxic chemicals (De, et al., 2003, De and Ramaiah, 2007),
and Methylotenera is a methylamine- and methanol-utilizing bacterium with
denitrification capability (Kalyuzhnaya, et al., 2010, Mustakhimov, et al., 2013).
2
1 / 54

Panacagrimonas is newly isolated from soils (Im, et al., 2010) and enriched in the
rhizosphere of pioneer plants in metal-contaminated soils (Navarro-Noya, et al., 2010).
Nitrospira is normally viewed as key nitrifiers in soils (Li, et al., 2019, Wang, et al.,
2
019). However, no study has ever reported their involvement in pyrene degradation,
and this work broadened our understanding on pyrene-degrading microbes, suggesting
that numerous soil microbes have the capability to degrade pyrene.
The relative abundance of all pyrene dioxygenase genes was higher in OS_Pyr than
OS_NC treatments, hinting the enrichment of pyrene degraders harboring
dioxygenase genes with pyrene amendment. Additionally, their relative abundance
was around 10-200 folds higher in MFC_Pyr than OS_Pyr, proving the successful
isolation of the active pyrene degrading microbes in MFC fractions (Figure 5A). Each
pyrene dioxygenase gene exhibited a positive correlation with pyrene degradation
efficiency (Figure 5 and Table S6), suggesting their critical roles in pyrene
degradation. nidA, nidA3 and PAH-RHDα-GP genes are reported as biomarkers for
pyrene degradation in many previous studies. As a key gene for the initial
hydroxylation of PAH aromatic ring, the α subunit of nidA-encoding dioxygenase was
cloned in Mycobacterium sp. strain PYR-1 (Hall, et al., 2005, Khan, et al., 2001) and
proved to be critical in pyrene degradation (Guo, et al., 2010). The relative abundance
of nidA3 gene was linked to pyrene biodegradation efficiency by PAH-degrading
communities (Chen, et al., 2016). PAH-RHD -GP genes in the initial step of PAH
α
aerobic metabolism demonstrated a positive correlation with PAH biodegradation
potential in soils (Cebron, et al., 2008, Jurelevicius, et al., 2012). In addition, the
relative abundance of all pyrene dioxygenase genes was also positively correlated
with that of the potential active pyrene degraders in MFC_Pyr treatment (0.8611,
p<0.01), hinting that they might harbor these pyrene dioxygenase encoding genes.
2
2 / 54

Cultivable pyrene degrader Sphingomonas sp. YT1005 was found to degrade pyrene
following the phthalate pathway. All the metabolites in CK_Sph treatments have been
reported as key metabolites in the phthalate pathway by previous studies, e.g.,
cis-4,5-pyrene dihydrodiol (metabolite ①) (Luan, et al., 2006, Zhong, et al., 2006),
dihydroxyphenanthrene
(metabolite
②
)
(Beaubien,
2020),
2
2
1
-hydroxy-2-H-benzo[h]chromene-2-carboxylic acid (metabolite ③) (Wu, et al.,
019, Zhou, et al., 2016), 2-methylnaphthalene (metabolite ④) (Wu, et al., 2019) and
-hydroxy-2-naphthoic acid (metabolite ⑤ ). In contrast, metabolites of
protocatechuic acid (metabolite ⑦) (Jin, et al., 2016a), 4-phenanthrenol (metabolite
⑧
⑨
) (Beaubien, 2020, Wu, et al., 2019), trans-2'-carboxybenzalpyruvate (metabolite
) and salicylic acid (metabolite ⑩) (Zhong, et al., 2017, Zhou, et al., 2016) are
involved in the salicylate pathway of PAHs degradation. Thus, MMI-isolated pyrene
degrading consortium metabolized pyrene through both phthalate and salicylate
pathways (Figure 6). Both phthalate and salicylate pathways are important in pyrene
metabolism (Sun, et al., 2019) and previously reported for the degradation of other
PAHs. Pyrene-degrading strains mainly exhibit the phthalate pathway for pyrene (Jin,
et al., 2016b, Liang, et al., 2006). Only few studies suggested the involvement of
salicylate pathway in pyrene degradation, such as Mycobacterium sp. WY10 which
degrades pyrene predominantly in the phthalate pathway and minorly in the salicylate
pathway (Sun, et al., 2019). The extra salicylate pathway imposed by MMI-isolated
pyrene degrading consortium suggested a more complex pyrene degradation pathways
in natural habitats than individual pyrene-degrading strains (Gallego, et al., 2014,
Zafra, et al., 2017), hinting a underestimated diversity of pyrene degraders. MMI is
therefore an effective approach to separate the active pyrene degraders from soil
2
3 / 54

matrices, not only helping in building up high-efficient degrading consortiums for
bioaugmentation but also contributing to our deeper understanding on the actual
players and pathways for pyrene metabolism in soils.
Enhanced pyrene degradation performance by bioaugmentation with soil indigenous
microbes has been reported in many previous studies (Chen, et al., 2016, Wang, et al.,
2
018). However, bioaugmentation postpone or even failure commonly occurs,
generally explained by microbial acclimation to environment changes, e.g.,
morphological, physiological and behavioral adjustments (Macleod and Semple, 2006,
Ren, et al., 2018). In the present study, bioaugmentation with Sphingomonas sp.
YT1005 in either sterile (CK_Sph) or original soils (BA_Sph) did not achieve
satisfactory pyrene degradation performance at the initial stage (0-20 days, Figure 1).
This result suggested that Sphingomonas sp. YT1005 was a cultivable pyrene degrader
in artificial medium and did not exhibit significant pyrene degradation ability in
ambient soils. In addition, the consistent pyrene degradation efficiency in OS_Pyr and
CK_MFC treatments proved that MMI-enriched bacterial consortiums consisting of
Gp16, Streptomyces, Pseudonocardia, Panacagrimonas, Methylotenera and
Nitrospira were the actual pyrene degraders responsible for in-situ pyrene metabolism.
The half-life (t1/2) of pyrene in bioaugmentation with the active pyrene degrading
consortium (6.99-7.89 d) was significantly shorter than previous reports (10-59 d)
(
Kashyap and Moholkar, 2021, Obayori, et al., 2017, Ukalska-Jaruga, et al., 2020),
indicating the potential to use MMI-enriched consortium for enhanced bioremediation.
We found negative intra-correlations between Sphingomonas sp. YT1005 and the
active pyrene degraders from the co-occurrence molecular ecological network (Figure
4
), and also observed their opposite trends during the pyrene degradation process
2
4 / 54

(
Figure 3B), possibly explaining the postponed pyrene degradation in CK_Sph and
BA_Sph treatments at the beginning stage of bioaugmentation.
A further insight into correlation network of Sphingomonas sp. YT1005 and the active
pyrene degraders (Figure S2) demonstrated that the introduction of Sphingomonas sp.
in BA_Sph treatments therefore inhibited their activities and consequently resulted in
bioaugmentation postpone, attributing to the complex bacterial intra-correlations
within the bacterial community. This explanation was consistent with some previous
studies that the correlation between pure-cultivation isolated and indigenous degraders
affected the bioaugmentation performance. Non-active degrader Marmoricola LJ-33
significantly enhanced biphenyl degradation efficiency in soils by changing bacterial
diversity in biphenyl metabolism (Tang, et al., 2020). Another bioaugmentation by
PAH-degrader Acinetobacter tandoii LJ-5 produced a significant increased
phenanthrene mineralization, attributing to the altered diversity of the active
phenanthrene degraders, instead of Acinetobacter tandoii LJ-5 itself (Li, et al., 2018a).
We then propose the mechanism explaining bioaugmentation performance regarding
intra-correlations between cultivable and active pyrene degraders. Ehanced
bioaugmentation is expected when these two groups of bacteria exhibit positive
intra-correlations, whereas negative intra-correlations between cultivable and active
pyrene degraders consequently result in bioagumentation postpone or failure. As for
neutral intra-correlations, the effectiveness and performance of bioaugmentation is
non-deterministric and potentially dependent on other environmental variables.
2
5 / 54

5. Conclusions
This study investigated soil pyrene degraders via both cultivation-dependent and
cultivation-dependent approaches. Sphingomonas sp. YT1005 was isolated via pure
cultivation, and the active pyrene degrading consortium consisting of Gp16,
Streptomyces, Pseudonocardia, Panacagrimonas, Methylotenera and Nitrospira was
isolated by MMI. An unexpected postpone of pyrene degradation was found in
bioaugmentation with Sphingomonas sp. YT1005, explained by its negative
intra-correlations with the active pyrene degraders. In contrast, bioaugmentation with
MMI-isolated pyrene degrading consortium significantly accelerated pyrene
degradation in soils. It was supported by the increasing relative abundance of pyrene
dioxygenase encoding genes (nidA, nidA3 and PAH-RHDα-GP) along with pyrene
degradation efficiency. Further analysis of pyrene degradation pathway suggested that
Sphingomonas sp. YT1005 only exhibited the phthalate pathway, whereas
MMI-isolated pyrene degraders possessed both phthalate and salicylate pathways. This
work broadens our vision on the actual pyrene degradation process and mechanisms in
soils, suggesting that intra-correlations between the introduced degraders and the
indigenous active degraders are key factors determining bioaugmentation performance.
Isolating and reintroducing the active indigenous active degraders is a more promising
strategy for bioaugmentation.
6. Acknowledgments
Financial support was provided by the National Natural Science Foundation of China
41807119), the Natural Science Foundation of Beijing, China (8212030), Special
(
Fund of State Key Joint Laboratory of Environment Simulation and Pollution Control
6 / 54
2

(
(
19K04ESPCT), Fundamental Research Funds for the Central Universities
FRF-TP-20-010A3), the Open Fund of National Engineering Laboratory for Site
Remediation Technologies (NEL-SRT201907), and Beijing Municipal Science and
Technology Project (Z181100002418016). DZ also acknowledges the support of
Chinese Government's Thousand Talents Plan for Young Professionals.
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