- Original article
- Open Access
Response of microbial community structure and metabolic profile to shifts of inlet VOCs in a gas-phase biofilter
© The Author(s) 2018
- Received: 15 September 2018
- Accepted: 25 September 2018
- Published: 3 October 2018
The effects of inlet VOCs (Volatile Organic Compounds) shifts on microbial community structure in a biofiltration system were investigated. A lab-scale biofilter was set up to treat eight VOCs sequentially. Short declines in removal efficiency appeared after VOCs shifts and then later recovered. The number of OTUs in the biofilter declined from 690 to 312 over time. At the phylum level, Actinobacteria and Proteobacteria remained dominant throughout the operation for all VOCs, with their combined abundance ranging from 60 to 90%. The abundances of Planctomycetes and Thermi increased significantly to 20% and 5%, respectively, with the intake of non-aromatic hydrocarbons. At the genus level, Rhodococcus was present in the highest abundance (≥ 10%) throughout the experiment, indicating its wide degradability. Some potential degraders were also found; namely, Thauera and Pseudomonas, which increased in abundance to 19% and 12% during treatment with ethyl acetate and toluene, respectively. Moreover, the microbial metabolic activity declined gradually with time, and the metabolic profile of the toluene-treating community differed significantly from those of other communities.
- Microbial community
- Metabolic profile
There has been growing interest in control of the emission of volatile organic compounds (VOCs) because of their potential to harm the environment and human health toxicity (Zheng et al. 2013). Recently, waste gases emitted in high volume containing complex VOCs at low concentration have hindered performance enhancement of related treatments (Cheng et al. 2016). This has led to increased interest in biofiltration systems, which have advantages of high efficiency, minimal secondary pollution and low costs (Khan and Ghoshal 2000).
Microorganisms play an important role in biodegradation, having direct interactions with contaminants. In previous studies, significant shifts in the bacterial community were observed during biodegradation, especially in the initial period (Qiu et al. 2013). Increasing doses also impact microbial communities (Li et al. 2017). Efforts were also paid on microbial community structures analysis to determine microbial indicators of contaminants (Obi et al. 2017). Evaluation of the influence of different degrading conditions on microbial communities also revealed significant effects (Techtmann et al. 2017). However, it is worth noting that previous studies were predominantly conducted using simple and stable inlet chemicals, while few investigations have focused on microbial changes with contaminant shifts.
Various VOCs have physical and chemical characteristics that differ significantly. Water-solubility and biodegradability are the two main factors that influence the removal efficiency of biofilters (Deshusses and Webster 2000). Low water-solubility limits mass transfer prior degradation (Alonso et al. 1998), while biodegradability influences the degradation of soluble VOCs. Among all pollutants, hydrocarbons (i.e., alcohols, ketones, esters etc.) have been shown to be the easiest degraded compounds, before alkene and aromatic hydrocarbon (Delhomenie and Heitz 2005). Therefore, different types of VOCs alter biofilter performances and microbial community structures significantly. However, precise analyses and conclusive studies are not yet available, especially for waste air treatments.
Few studies have investigated the interactions between environments and microorganisms (Zhang et al. 2018); therefore, the present study was conducted to elucidate these interactions. Specifically, this study investigated a biofilter applied to treat a variety of volatile organic compounds (toluene, ethylbenzene, chlorobenzene, acetone, isopropyl alcohol, ethyl acetate, n-hexane and tetrahydrofuran) in sequence. Differences in degrading performance and the changes in microbial structures during the process were then evaluated. The data obtained in this study will provide insight into microbial community function, functional diversity, and other aspects of the biofilter operation.
Biofilter configuration and operation
Biofilter set up
The system had a height of 335 mm and an internal diameter of 118, giving an effective height of packing material of 150 mm with an approximately 1.7 L volume (Additional file 1: Figure S1). The air flow was pressurized and controlled with an electromagnetic air compressor (ACO-318, Hailea Co., Ltd., Guangdong, China) and a flowmeter (LZB-WB, Zhenxing Flowmeter Factory, China). Pressurized airflow entered the mixing chamber, which contained multiple vials of evaporating VOCs. The quantity of the vials, volume and volatile area of the VOCs was used to control the inlet concentration. Mixed air flow then entered the biofilter from the bottom and passed through the packing materials containing the microorganisms, after which the treated air was discharged from the top of the biofilter. An electromagnetic flowmeter (Iwaki Co., Ltd, EH-B20VC-220R1) was used to control the liquid flow rate and a microcomputer time controlled switch (Toone Co., Ltd., Shanghai, China) was used to control the spraying rate.
Eight common volatile organic compounds were selected in this study for biofilter performances and microbial community analyses. The selected compounds, including aromatic and non-aromatic hydrocarbons, were common industrial materials or organic solvents (Additional file 1: Table S1). Different VOCs were applied one by one in the order toluene, ethylbenzene, chlorobenzene, acetone, isopropyl alcohol, ethyl acetate, n-hexane and tetrahydrofuran. The duration of operation for each compound ranged from 12 to 17 days, depending on the time spent to reach a stable state.
The inlet air flow rate was 2.2 L min−1 with an empty bed residence time of 46 s. Spraying was conducted for 1 min every 3 h, giving a total sprayed volume of 90 mL. The nutrient medium was renewed every 3–4 days, the pH of the medium was controlled at 6.5–7.2, and temperature ranged from 25 to 32 °C.
Nutrient medium and inoculation
The nutrient medium used consisted of 10 g NaNO3, 2.56 g Na2HPO3 and 1.66 g KH2PO3 per L water, and the pH values ranged from 6.5 to 7.2. The medium was inoculated with suspended activated sludge, and 1.7 L packing materials were filled into the biofilter after being soaked in 1 L of the activated sludge suspension for an hour.
VOCs, CO2 and biomass concentration
The concentrations of the chemicals were analyzed by gas chromatography (GC-14C, Shimadzu Co. Ltd., Shanghai, China). The temperatures of the inlet, column (HICRON HP-1, 50 m × 0.25 mm) and detector were 150 °C, 100 °C and 150 °C, respectively.
The concentration of CO2 was tested using a portable CO2 m (Testo 535, Testo China Co. Ltd., China), while decreases in pressure were analyzed with a manometer (Testo 512, Testo China Co. Ltd., China).
Biomass in different periods was tested 2 h after spraying to minimize the influence of sprayed nutrient medium. The growth of biomass was compared among treatments to evaluate increases in microorganisms.
DNA extraction was performed during the stable phase using a Fast DNA™ SPIN Kit for Soil (MP Biomedicals, Canada), after which the extracted DNA was sequenced using the Illumina MiSeq sequencing platform (Novogene Co., Beijing, China) and the 515F (5′-GTGCCAGCAGCCGCGGTAA-3′) and 806R (5′-GGACTACCAGGGTATCTAAT-3′) targeting the V4 region of the 16S rRNA gene. Each reverse primer contained a 6-bp error-correcting unique barcode and PCR amplification was conducted by subjecting the samples to 98 °C for 5 min, followed by 40 cycles of 94 °C for 30 s, 55 °C for 30 s and 72 °C for 45 s, and then final extension at 72 °C for 10 min. Sequences were then analyzed using the Illumina MiSeq platform (Novogene Co., Beijing, China).
Illumina MiSeq original DNA sequence data were processed and analyzed by Qiime (http://qiime.org/) and UPARSE (http://drive5.com/uparse/). Paired-end reads from the original DNA fragments were combined using FLASH18. All sequences were aligned with the SILVA bacterial 16S rRNA database. Sequences were clustered into operational taxonomic units (OTUs) at a cutoff of 97% sequence identity, after which the unweighted UniFrac in principal coordinate analysis (PCoA) was determined by Qiime. Some indices (rarefaction curves, Chao, Simpson, Shannon, coverage) were calculated to reveal Alpha diversity using mothur v.1.32. (http://www.mothur.org).
The Illumina MiSeq sequencing raw data have been deposited in the NCBI Sequence Read Archive database, and the SRA accession is SRP148831.
BIOLOG ECO Plates and high-throughput sequencing were used in this study to monitor microbial communities. High-throughput sequencing has helped investigators identify changes in the microbial structure and diversity (Alpana et al. 2017).
BIOLOG Eco-plates were used to investigate Sole-Carbon-Source Utilization (SCSU) of different microbial communities. Each plate contained a total of 31 carbon sources in triplicate. The suspension samples required a 5-min resting after they were obtained from the biofilter. Then, the supernatant was diluted to make the OD600 close to 0.05. Next, 150 µL aliquots of the diluted supernatants were added to the wells of the microplate and incubated at 30 °C for 3–4 days.
In this equation, Ai refers to the OD600 value in well number “i”, among which No. 1, 33, and 66 were blank values.
The results were then subjected to principal component analysis (PCA) using SPSS 22.
Removal and mineralization of VOCs
Performances of the biofilter with different inlet VOCs
Inlet concentration (mg m−3)
Removal efficiency (%)
Elimination capacity (mg m−3 min−1)
Similar results were observed among VOC mineralization rates (Fig. 1). Surprisingly, the mineralization rate of tetrahydrofuran was lowest among all tested compounds. More tetrahydrofuran was degraded into intermediates or microorganisms instead of CO2 and H2O.
Different performance was observed for different inlet VOCs, suggesting that the characteristics of the microbial community changed with inlet VOCs.
Indexes of microbial following treatment with different types of VOCs
Shannon’s index was lower for compounds of aromatic hydrocarbons, indicating lower microbial diversity. A similar trend was observed for Simpson’s index, indicating that a higher microbial diversity led to lower dominance of the dominant species, as occurred with toluene. High consistency was seen between degrading performance and microbial community. As previously mentioned, higher microbial diversity was observed for toluene, which had the highest biodegradability among the aromatic hydrocarbons.
Microbial community structure
Actinobacteria and Proteobacteria remained dominant throughout the experimental period. Upon further analysis, the abundance of Actinobacteria was found to fluctuate from 17 to 72%, while that of Proteobacteria varied from 19 to 57%. As the inlet VOCs were changed from toluene to ethylbenzene and chlorobenzene, the abundance of Actinobacteria increased in a stepwise fashion to 33.2%, 63.9% and 71.1%, respectively, while that of Proteobacteria decreased from 56.4 to 24.6% and then 19.8%. Surprisingly, the sum of the two phyla remains stable, with values of 89.6%, 88.5% and 90.9% being observed for toluene, ethylbenzene and chlorobenzene, respectively.
The changes in the microbial community occurred when the VOCs were switched from aromatic to non-aromatic hydrocarbons. The sum of Actinobacteria and Proteobacteria decreased from 90% to approximately 60%–70%, while the abundances of Planctomycetes and Thermi increased significantly after the hydrocarbons were changed. The abundance of the phylum Planctomycetes increased when some aromatic chemicals were removed. Moreover, their abundance increased when the aromatic hydrocarbons were replaced with non-aromatic chemicals such as acetone. Thermi remained stable during purification of non-aromatic hydrocarbons, fluctuating at levels of 5.0–8.0%. The abundance of Bacteroidetes peaked at 14.6% in response to acetone and then decreased to 1.0% upon application of n-hexane. These findings indicate that acetone was a better carbon and energy source for species in the phylum Bacteroidetes than n-hexane. The abundance of Cyanobacteria tripled in the presence of tetrahydrofuran when compared to other compounds. It has been speculated that members of the phylum Cyanobacteria could include more tetrahydrofuran degraders than other phyla.
A total of 264 genera were obtained during the operation, 21 of which were present in high abundance. The sum of these dominant genera accounted for 75%–91% of the total biomass (Fig. 2b). All genera belonged to the top seven phyla, with most belonging to the phyla Actinobacteria and Proteobacteria. Four genera, including Rhodococcus, Pseudonocardia and other two unidentified genera from the phylum Actinobacteria, had high abundances. Among them, Rhodococcus had significant advantages in abundance throughout the experimental period. The phylum Proteobacteria, which contained Pseudomonas, Devosia, Aquimonas, Marinobacter and eight other genera, showed high stability and uniformity with increased abundance when treating various contaminants, as opposed to genera belonging to the phylum Actinobactria.
The genus Rhodococcus, which belongs to the phylum Actinobacteria, was obtained in high abundance (> 10%) throughout the operation. Surprisingly, higher values of relative abundance were observed when aromatic hydrocarbons were being eliminated. Similarly, the abundance of Devosia sp. increased in response to the inlet of aromatic hydrocarbons. During the operation, specific degraders were identified. Specifically, high abundance (18.8%) of Thauera was observed in the presence of ethyl acetate, while less than 1% was observed in the presence of other VOCs. In addition, the genus Pseudomonas showed highest abundance during the inlet of toluene, while it comprised less than 0.5% in the presence of other VOCs.
Microbial metabolic profile
The dominant phyla Actinobacteria and Proteobacteria are the most commonly reported prokaryotic degraders (Coleman et al. 2006). As reported in previous studies, many members of the phylum Actinobacteria have aromatic hydrocarbon degrading abilities, and some species can utilize complicated chemicals as carbon or energy sources for growth; however, the capability for degradation decreases with increasing carbon chain length (Wen et al. 2014; Zylstra et al. 2000). Proteobacteria has previously been widely applied in bioremediation for hydrocarbon purification in combination with Actinobacteria, which is another dominant phylum commonly seen in aromatic hydrocarbon biodegradation (Fuentes et al. 2014). Hence, we can conclude that Actinobacteria and Proteobacteria played crucial roles in aromatic hydrocarbon purification in this study. Increasing abundance of the phylum Planctomycetes when some aromatic chemicals were being removed have also been confirmed in previous study (Delgado-Balbuena et al. 2016).
On genus level, it was previously reported that Rhodococcus can utilize and removal a large variety of pollutants (Maia et al. 2018; Warhurst and Fewson 1994). Members of the genus Rhodococcus were found to have the considerable ability to degrade a great number of aromatic hydrocarbons several decades ago (Sorkhoh et al. 1990). As well-known VOCs degraders, Rhodococcus species can utilize various chemicals and have therefore been applied frequently in VOCs purifications (Li et al. 2016). It was also confirmed that Rhodococcus species can degrade complicated chemicals like three to five rings polycyclic aromatic hydrocarbons (PAHs) (Song et al. 2011). Moreover, some strains of Rhodococcus were shown to have broad degradation capacities toward a mixture of 16 VOCs including benzene, toluene, ethylbenzene, m-xylene, p-xylene, o-xylene, and octane (Auffret et al. 2009). Because of its efficient and broad degradation capacities, Rhodococcus was used to remediate heavily PAH-contaminated soil with total PAHs of 375 mg, and up to 55% was removed (Sun et al. 2012). These performances could explain the high abundance of Rhodococcus throughout the experimental period and likely contributed greatly to the biodegradation performance in this system.
In consideration of other genera, the findings in this study are consistent with those of previous reports. High abundances of Devosia sp. were previously observed in aromatic compounds purification systems (Ramos et al. 2015), and they have been used as aromatic compounds degraders in previous studies (Papale et al. 2017). Ethyl acetate can be utilized as carbon resources by Thauera sp. (Du et al. 2017). The genus Pseudomonas was previously reported to be a toluene utilizer and degrader (Hernandez and Torre 2011; Su et al. 2014). Pseudomonas sp. was previously proposed to be indicators of biodegradation because of their sensitivity to substrate change (Obi et al. 2017; Yakimov et al. 2007).
The significant differences observed in this study indicated that target VOCs had significant effects on microorganisms, particularly at the genus level. The population of utilizers and degraders increased rapidly in the response to VOCs, with some becoming dominant species. Subsequently, changes in inlet VOCs caused dramatic decreases shifts in these populations. Taken together, these results indicate that the microbial community has the ability to adapt to new environmental conditions. Accordingly, there is the potential to develop specific measures to facilitate such adaptation to optimize biodegradation, such as increasing the abundance of specific degraders artificially.
The results revealed that the microbial community was significantly different when purifying toluene then when treating other VOCs. Surprisingly, the communities were highly similar in the presence of all other test compounds. This might have occurred because of significant microbial community shifts in the initial operations (Qiu et al. 2013). After the initial operation, the system became relatively stable, possibly indicating that the community stabilized with time.
Biodegradability of different VOCs has remarkable influences on microbial elimination performance, community structures and metabolic profiles. The highest diversity was obtained at the beginning of the operation while eliminating toluene. Diversity declined with prolonged operation, and significant differences were found in microbial community structures at both the phylum and genus levels. As the experiment continued, the carbon source metabolic capacity declined gradually. The metabolic characteristics of carbon source utilization differed significantly following toluene input, while it was similar among all other treatment groups. Artificial addition of degraders and measures to increase microbial activity might optimize biofiltration.
JX conceived the original idea and supervise the project. GW, MY and LL completed the experiment and data analysis. LL wrote the draft of the manuscript. All authors discussed the results and contribute to the final manuscript. All authors read and approved the final manuscript.
This study was supported by the National Natural Science Foundation of China (No. 51378286). This study was also supported by the Science and Technology Program for Water Pollution Control (No. 2011ZX07301-003). Help from the State Environmental Protection Key Laboratory of Microorganism Application at Tsinghua University is appreciated. Thanks are given to Dr. Guo Qian for her linguistic assistance during the preparation of this manuscript, and the anonymous reviewers for their helpful comments regarding the manuscript. We would like to thank LetPub (http://www.letpub.com) for providing linguistic assistance during the preparation of this manuscript.
The authors declare that they have no competing interests.
Availability of data and materials
All datasets supporting the conclusion of the manuscript were included in the manuscript.
Consent for publication
All authors gave their consent for publication.
Ethics approval and consent to participate
This article does not contain any studies with human participants or animals performed by any of the authors.
This work has been supported by the National Natural Science Foundation of China (No. 51378286) and the Science and Technology Program for Water Pollution Control (No. 2011ZX07301-003).
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
- Alonso C, Suidan MT, Kim BR, Kim BJ (1998) Dynamic mathematical model for the biodegradation of VOCs in a biofilter: biomass accumulation study. Environ Sci Technol 32(20):3118–3123View ArticleGoogle Scholar
- Alpana S, Vishwakarma P, Adhya TK, Inubushi K, Dubey SK (2017) Molecular ecological perspective of methanogenic archaeal community in rice agroecosystem. Sci Total Environ 596:136–146View ArticleGoogle Scholar
- Auffret M, Labbe D, Thouand G, Greer CW, Fayolle-Guichard F (2009) Degradation of a mixture of hydrocarbons, gasoline, and diesel oil additives by Rhodococcus aetherivorans and Rhodococcus wratislaviensis. Appl Environ Microbiol 75(24):7774–7782View ArticleGoogle Scholar
- Cheng ZW, Lu LC, Kennes C, Ye JX, Yu JM, Chen DZ, Chen JM (2016) A composite microbial agent containing bacterial and fungal species: optimization of the preparation process, analysis of characteristics, and use in the purification for volatile organic compounds. Bioresour Technol 218:751–760View ArticleGoogle Scholar
- Choi KH, Dobbs FC (1999) Comparison of two kinds of Biolog microplates (GN and ECO) in their ability to distinguish among aquatic microbial communities. J Microbiol Methods 36(3):203–213View ArticleGoogle Scholar
- Coleman NV, Bui NB, Holmes AJ (2006) Soluble di-iron monooxygenase gene diversity in soils, sediments and ethene enrichments. Environ Microbiol 8(7):1228–1239View ArticleGoogle Scholar
- Delgado-Balbuena L, Bello-Lopez JM, Navarro-Noya YE, Rodriguez-Valentin A, Luna-Guido ML, Dendooven L (2016) Changes in the bacterial community structure of remediated anthracene-contaminated soils. PLoS ONE 11(10):e0160991View ArticleGoogle Scholar
- Delhomenie MC, Heitz M (2005) Biofiltration of air: a review. Crit Rev Biotechnol 25(1–2):53–72View ArticleGoogle Scholar
- Deshusses MA, Webster TS (2000) Construction and economics of a pilot/full-scale biological trickling filter reactor for the removal of volatile organic compounds from polluted air. J Air Waste Manage 50(11):1947–1956View ArticleGoogle Scholar
- Du R, Cao SB, Li BK, Niu M, Wang SY, Peng YZ (2017) Performance and microbial community analysis of a novel DEAMOX based on partial-denitrification and anammox treating ammonia and nitrate wastewaters. Water Res 108:46–56View ArticleGoogle Scholar
- Fuentes S, Mendez V, Aguila P, Seeger M (2014) Bioremediation of petroleum hydrocarbons: catabolic genes, microbial communities, and applications. Appl Microbiol Biotechnol 98(11):4781–4794View ArticleGoogle Scholar
- Hernandez M, Torre RM (2011) Long-term influence of the presence of a non-aqueous phase on the cell surface hydrophobicity of Pseudomonas in two-phase partitioning bioreactors. Appl Microbiol Biotechnol 89(5):1573–1581View ArticleGoogle Scholar
- Khan FI, Ghoshal AK (2000) Removal of volatile organic compounds from polluted air. J Loss Prev Process Ind 13(6):527–545View ArticleGoogle Scholar
- Li C, Zhang CY, Song GL, Liu H, Sheng GH, Ding ZF, Wang ZL, Sun Y, Xu Y, Chen J (2016) Characterization of a protocatechuate catabolic gene cluster in Rhodococcus ruber OA1 involved in naphthalene degradation. Ann Microbiol 66(1):469–478View ArticleGoogle Scholar
- Li Y, Hua Q, Chen CH, Wang XL, Gao DW (2017) Performance and microbial community structure in an integrated anaerobic fluidized-bed membrane bioreactor treating synthetic benzothiazole contaminated wastewater. Bioresour Technol 236:1–10View ArticleGoogle Scholar
- Maia AS, Tiritan ME, Castro PML (2018) Enantioselective degradation of ofloxacin and levofloxacin by the bacterial strains Labrys portucalensis F11 and Rhodococcus sp FP1. Ecotox Environ Safe 155:144–151View ArticleGoogle Scholar
- Obi CC, Adebusoye SA, Amund OO, Ugoji EO, Ilori MO, Hedman CJ, Hickey WJ (2017) Structural dynamics of microbial communities in polycyclic aromatic hydrocarbon-contaminated tropical estuarine sediments undergoing simulated aerobic biotreatment. Appl Microbiol Biotechnol 101(10):4299–4314View ArticleGoogle Scholar
- Papale M, Giannarelli S, Francesconi S, Di Marco G, Mikkonen A, Conte A, Rizzo C, De Domenico E, Michaud L, Lo Giudice A (2017) Enrichment, isolation and biodegradation potential of psychrotolerant polychlorinated-biphenyl degrading bacteria from the Kongsfjorden (Svalbard Islands, High Arctic Norway). Mar Pollut Bull 114(2):849–859View ArticleGoogle Scholar
- Preston-Mafham J, Boddy L, Randerson PF (2002) Analysis of microbial community functional diversity using sole-carbon-source utilisation profiles—a critique. FEMS Microbiol Ecol 42(1):1–14PubMedGoogle Scholar
- Qiu GL, Song YH, Zeng P, Duan L, Xiao SH (2013) Combination of upflow anaerobic sludge blanket (UASB) and membrane bioreactor (MBR) for berberine reduction from wastewater and the effects of berberine on bacterial community dynamics. J Hazard Mater 246:34–43View ArticleGoogle Scholar
- Ramos C, Suarez-Ojeda ME, Carrera J (2015) Long-term impact of salinity on the performance and microbial population of an aerobic granular reactor treating a high-strength aromatic wastewater. Bioresour Technol 198:844–851View ArticleGoogle Scholar
- Rutgers M, Wouterse M, Drost SM, Breure AM, Mulder C, Stone D, Creamer RE, Winding A, Bloem J (2016) Monitoring soil bacteria with community-level physiological profiles using Biolog (TM) ECO-plates in the Netherlands and Europe. Appl Soil Ecol 97:23–35View ArticleGoogle Scholar
- Sempere F, Gabaldon C, Martinez-Soria V, Marzal P, Penya-Roja JM, Alvarez-Hornos FJ (2008) Performance evaluation of a biotrickling filter treating a mixture of oxygenated VOCs during intermittent loading. Chemosphere 73(9):1533–1539View ArticleGoogle Scholar
- Song XH, Xu Y, Li GM, Zhang Y, Huang TW, Hu Z (2011) Isolation, characterization of Rhodococcus sp P14 capable of degrading high-molecular-weight polycyclic aromatic hydrocarbons and aliphatic hydrocarbons. Mar Pollut Bull 62(10):2122–2128View ArticleGoogle Scholar
- Sorkhoh NA, Ghannoum MA, Ibrahim AS, Stretton RJ, Radwan SS (1990) Crude-Oil and hydrocarbon-degrading strains of rhodococcus-rhodochrous isolated from soil and marine environments in Kuwait. Environ Pollut 65(1):1–17View ArticleGoogle Scholar
- Su Y, Xia FF, Tian BH, Li W, He R (2014) Microbial community and function of enrichment cultures with methane and toluene. Appl Microbiol Biotechnol 98(7):3121–3131View ArticleGoogle Scholar
- Sun GD, Xu Y, Jin JH, Zhong ZP, Liu Y, Luo M, Liu ZP (2012) Pilot scale ex situ bioremediation of heavily PAHs-contaminated soil by indigenous microorganisms and bioaugmentation by a PAHs-degrading and bioemulsifier-producing strain. J Hazard Mater 233:72–78View ArticleGoogle Scholar
- Techtmann SM, Zhuang MB, Campo P, Holder E, Elk M, Hazen TC, Conmy R, Domingo JWS (2017) Corexit 9500 enhances oil biodegradation and changes active bacterial community structure of oil-enriched microcosms. Appl Environ Microbiol. https://doi.org/10.1128/AEM.03462-16 View ArticlePubMedPubMed CentralGoogle Scholar
- Warhurst AM, Fewson CA (1994) biotransformations catalyzed by the genus Rhodococcus. Crit Rev Biotechnol 14(1):29–73View ArticleGoogle Scholar
- Wen ZD, Gao DW, Wu WM (2014) Biodegradation and kinetic analysis of phthalates by an Arthrobacter strain isolated from constructed wetland soil. Appl Microbiol Biotechnol 98(10):4683–4690View ArticleGoogle Scholar
- Yakimov MM, Timmis KN, Golyshin PN (2007) Obligate oil-degrading marine bacteria. Curr Opin Biotechnol 18(3):257–266View ArticleGoogle Scholar
- Zhang Y, Sun R, Zhou AJ, Zhang JG, Luan YB, Jia JN, Yue XP, Zhang J (2018) Microbial community response reveals underlying mechanism of industrial-scale manganese sand biofilters used for the simultaneous removal of iron, manganese and ammonia from groundwater. Amb Express. https://doi.org/10.1186/s13568-017-0534-7 View ArticlePubMedPubMed CentralGoogle Scholar
- Zheng JY, Yu YF, Mo ZW, Zhang Z, Wang XM, Yin SS, Peng K, Yang Y, Feng XQ, Cai HH (2013) Industrial sector-based volatile organic compound (VOC) source profiles measured in manufacturing facilities in the Pearl River Delta, China. Sci. Total Environ. 456:127–136View ArticleGoogle Scholar
- Zylstra GJ, Goyal AK, Cigolini JF, Dennis JD (2000) Bioprospecting for novel aromatic oxygenases. Abstracts of Papers of the American Chemical Society 219:U158–U158Google Scholar