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Identification and function of extracellular protein in wastewater treatment using proteomic approaches: A minireview
Journal of Environmental Management 233 (2019) 24–29
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Review
Identification and function of extracellular protein in wastewater treatment using proteomic approaches: A minireview
T
Peng Zhanga,b,∗, Jing Zhua, Xiao-Yan Xua, Tai-Ping Qinga, You-Zhi Daia, Bo Fenga,∗∗ a b
College of Environment and Resources, Xiangtan University, Xiangtan, 411105, China Key Laboratory of the Three Gorges Reservoir Region's Eco-Environments of MOE, Chongqing University, Chongqing, 400045, China
A R T I C LE I N FO
A B S T R A C T
Keywords: Extracellular proteins Proteomics Microbial attachment Biodegradation Response to environmental stresses
Microbial extracellular proteins serve as important functions in wastewater treatment process. Analysis of their compositions and properties is crucial to probe their specific functions. However, conventional analytical techniques cannot obtain interest protein information from complex proteins. Recently, the extracellular proteomics method has been applied to resolve the composition of extracellular proteins. In order to better understand the roles of extracellular protein in wastewater treatment process, this review provides the information on the proteomics methods and their application in investigating extracellular proteins involved in microbial attachment/aggregation, biodegradation of pollutants, and response to environmental stresses. Future work needs to exploit the full capability of the proteome.
1. Introduction In microbial aggregates, e.g., activated sludge, biofilm, and granule sludge, extracellular polymeric substances (EPS) provide spatial organization and structural stability, mediating both cell-to-cell and cell-tosurface interactions during microbial aggregate development. EPS consist of a complex high-molecular-weight mixture of polymers that are mainly released by microorganisms and are composed of proteins, polysaccharides, humic substances, nucleic acids, lipids, etc. EPS mainly comprise proteins and polysaccharides. In activated sludges, extracellular proteins are more abundant than polysaccharides, and they serve important functions in the wastewater treatment (Park et al., 2008; Mahendran et al., 2012; Xiao and Wiesner, 2013). Extracellular proteins consist of enzymes and structural proteins. Their major functions in wastewater treatment include the formations of microbial aggregate, pollutant migration and transformation, and resisting of toxic substances. Extracellular proteins can promote the formation of microbial aggregates, and maintain their structural integrity due to the connection between negatively charged amino acids in proteins via multivalent cation bridging (Flemming and Wingender, 2010). They also contribute to pollutant removal in wastewater treatment via adsorption and catalysis. They wrap on the cell surfaces and initially contact with extracellular substrates, and can strongly bind heavy metals, organic matter, and nanoparticles. Extracellular enzymes
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supply an external digestion system, playing an important role in the degradation of the organic small molecules, organic colloidal fraction and particulate biomass (Guellil et al., 2001; Habermacher et al., 2015). In addition, extracellular proteins can reduce the effects of toxic substances because hydroxyl, carboxyl, phosphate and amide groups in extracellular proteins provide binding sites for antibiotics, heavy metals, and nanoparticles (Joshi and Juwarkar, 2009; Li and Yu, 2014). However, the specific functions of these proteins in the extracellular matrix or microbial physiology are unclear. The compositions and properties of extracellular proteins must be determined to probe their specific functions. The analysis of extracellular proteins involves conventional quantification, spectral characteristics, molecular weight, amino acid sequences, secondary structures, viscoelasticity, enzyme activity, and affinity (Yin et al., 2015; Le et al., 2016; Zhang et al., 2017). However, these techniques cannot obtain interest protein information and cannot screen the key functional protein from the compound proteins. In recent years, the extracellular proteome or called exoproteome has been used to reveal the composition of extracellular proteins and has deepened the understanding of their functions in wastewater treatment. The proteome is the total corresponding proteins expressed by the genome, which reflects the presence and active of all proteins in a cell, tissue and organism. The genome is normally stable, whereas the amount and types of proteins expressed by the genome vary based on
Corresponding author. College of Environment and Resources, Xiangtan University, Xiangtan, 411105, China. Corresponding author. E-mail addresses: [email protected] (P. Zhang), [email protected] (B. Feng).
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https://doi.org/10.1016/j.jenvman.2018.12.028 Received 30 March 2018; Received in revised form 4 November 2018; Accepted 9 December 2018 0301-4797/ © 2018 Elsevier Ltd. All rights reserved.
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2DE. The efficient separation of complex proteins is important to improve peptide coverage in MS analysis. 2DE protein identification technology can separate proteins in 2D through isoelectric focusing and SDS-PAGE based on the difference of the isoelectric point and the molecular weight of the proteins, and different natural proteins distribute in the gel in the form of spot. Interest proteins in gel spot can be directly determined using MS without LC separation. Jachlewski et al. (2015) found that the cation exchange resin extraction was the best suited method to isolate Sulfolobus acidocaldarius biofilm EPS among the five extraction methods, and several hundreds of protein spots were determined. Speda et al. (2017) developed one direct precipitation method and one extraction/precipitation method for obtaining extracellular proteins, which provided high gel spot detection abilities, especially for low abundance extracellular proteins. Two-dimensional fluorescence difference gel electrophoresis (2DDIGE) is a quantitative proteomics technique developed on the basis of traditional 2DE, and the principle of protein separation is consistent with that of 2DE. The sample and added internal standard are marked with fluorescent dyes (Cy2, Cy3, Cy5), and the differential proteins can be accurately and sensitively revealed (Llama-Palacios et al., 2017). However, humic acids adulterated in protein could interfere or mask the visualization of protein bands in gel electrophoresis, which indicated that preparing of high-purity proteins is necessary (Silva et al., 2012). Furthermore, for some special proteins, such as having extremes in molecular mass, or that are hydrophobic or insolvable, gel based separation is often unsuitable.
the growth period and environmental condition. Therefore, specific extracellular proteins involved in the development of microbial aggregate and the pollutant migration and transformation can be revealed using proteomics. In this review, we describe the analytical methods including qualitative and quantitative proteomics for extracellular proteins, and discuss their application in probing extracellular proteins involved in microbial attachment/aggregation, biodegradation, and response to environmental stress. 2. Identification of extracellular proteome After extracting EPS from microbial aggregates, the extracellular proteins can be crudely purified from EPS for proteomics analysis. Purification methods mainly include centrifugation, precipitation, dialysis and ultrafiltration, which are mentioned in the related reference books (Marshak et al., 1996). The crude proteins can be isolated through gel-based separation and gel-free separation (Rodrigues et al., 2012). The former includes sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and 2D gel electrophoresis (2DE). The latter is chromatography, such as ion exchange chromatography, size exclusion chromatography, hydrophobic interaction chromatography, affinity chromatography and chromatofocusing. Fig. 1 shows the analysis procedures of extracellular proteins. 2.1. Protein isolation
2.1.2. Gel-free separation Chromatographic separation can overcome the limitations of gel based separation and can effectively separate components from mixtures. High-pressure liquid chromatography (HPLC) and reversed phase HPLC separation are generally used (Wohlbrand et al., 2013). For complex proteome samples, multi-dimensional liquid chromatographic (MDLC) separation system is developed, which mainly includes 2D and 3D chromatographic separation (Xiao et al., 2017). MDLC separation system can optimize the combination of two or more liquid phase separation methods with different separation principles, and it can effectively improve the resolution and peak capacity of the system.
2.1.1. Gel-based separation SDS-PAGE. SDS-PAGE is a biochemical analytical approach for the separation of charged molecules (proteins) in mixtures by their molecular weight in an electric field. The mobility of protein depends only on their molecular weight. Interest gel pieces in SDS-PAGE are digested, and are separated and determined using liquid chromatography and mass spectrometry (LC-MS). Park et al. (2008) extracted the activated sludge EPS from a municipal wastewater treatment plant using three cation-associated extraction methods, and the proteins in EPS were precipitated by ammonium sulfate. Their results showed that the SDS-PAGE protein profiles were dependent on the extraction method used. However, there are only several proteins were identified. Silva et al. (2012) compared various concentrations and precipitation methods, and analyzed both the extracellular proteins in the soluble and bound EPS from activated sludge. The results identified 25–32 and 17 proteins in soluble EPS and bound EPS, respectively. Therefore, proteome information resulted from SDSPAGE is limited.
2.2. Mass spectrometry analyses Protein identification is highly dependent on mass spectrometry (MS). Based on the different ionization methods, multiple mass spectrometry including electrospray ionization (ESI) MS, matrix assisted laser desorption ionization (MALDI) MS, fast atom bombardment MS, atmospheric pressure ionization MS are used to protein detection. Among them, ESI and MALDI MS are the most widely utilized (Xiao et al., 2017). MS can realize the qualitative and quantitative analysis of proteome through corresponding experimental design. The protein identification is built on peptide spectrum match principle (Kopczynski et al., 2017). The similarity of MS/MS spectra between sample peptide and the theoretical peptide in the database is statistically analyzed and scored by the algorithm, and the theoretical peptide with the highest score is the result of identification. The commonly used search software is Mascot, X!Tandem, OMSSA, SEQUEST, and Andromeda (Xiong et al., 2015). The principal methods of protein bioinformatics analysis include cluster analysis, gene ontology functional classification analysis, biological pathway analysis and protein interaction network analysis (Xiao et al., 2017). The available software contains Cluster & TreeView, DAVID, go Surfer, GenMAPP, and ingenuity pathway analysis. 2.2.1. Qualitative proteomics Full spectrum analysis. The full spectrum analysis of proteins may also be termed as shotgun analysis based on MS. A SDS-PAGE gel or hydrolyzed peptide mixture in solution is separated and detected by LC-
Fig. 1. Proteomics workflow for extracellular protein analysis. 25
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3. Functions of extracellular proteome
MS/MS. The proteins are identified via MS/MS spectra search against the protein database (Zhang et al., 2018). This method can systematically and comprehensively identify thousands of proteins from microbial aggregates. For example, Zhang et al. (2015a,b) analyzed the extracellular proteins extracted from anaerobic, anoxic and aerobic sludges in a municipal wastewater treatment plant using the shotgun method, and classified 130, 108 and 114 proteins, respectively. Their results indicated that most proteins originated from the intracellular release due to cell lysis.
3.1. Microbial attachment and aggregation Microbial aggregation and biofilm formation are essential for resisting environmental stress, such as hydraulic shear force and toxic substances, and are also necessary for sludge-water separation in the effluent of wastewater treatment plants. Many extracellular proteins can promote bacterial attachment and aggregation through non-specific interactions. For example, Dong et al. (2017) comparatively researched the extracellular proteomes between inoculated activated sludge and mature granular sludge based on 2D gels. They found 5 types of proteins, including chaperonins, binding proteins, metabolism-related proteins, a-synthesis proteins, and other functional proteins were associated with the granulation of aerobic sludge and EPS secretion. Some extracellular proteins related to specific attachment were found based on the proteomics. Oliveira et al. (2015) identified and characterized an extracellular protein (Alr0267) named HesF from filamentous cyanobacterium Anabaena sp. PCC 7120. Their results exhibited that HesF was associated with the filament adhesion and microbial aggregation in heterocyst-forming cyanobacteria. The extracellular adhesion proteins can vary owing to the abundant microbial species in wastewater treatment system. Zhang et al. (2015b) evaluated the extracellular proteins in biofilm. An extracellular protein named adhesion and penetration protein autotransporter was identified and can promote the microbial adhesion. The pili, an important group of proteins polymerized into fibers, are also involved in microbial attachment (Romero et al., 2010). Floyd et al. (2015) determined the spatial proteome of intact biofilms in situ using MALDI time-of-flight (TOF) imaging MS, and their results showed that the protein species are distinctly localized within surface-associated Escherichia coli biofilms. And two adhesive fibers, including type I pili and curli amyloid fibers were found, which are critical for Escherichia coli biofilm formation. Their work offered insight into the spatial regulation of proteins within bacterial biofilms during microbial attachment and biofilm formation. Type IV pili are intrinsic structural elements in biofilm formation of many bacteria and can serve as conductive nanowires together with a number of c-type cytochromes in extracellular electron transfer process. Posttranslational modification (PTM) plays a fundamental role in cellular biological regulation, which potentially changing the physical or chemical properties, activity, cell localization or stability of proteins. The modified kind and site of protein or polypeptide can be detected by proteomics. Richter et al. (2017) investigated that a posttranslational modification of a non-conserved amino acid residue within the PilA protein, which is the structural subunit of the type IV pili in Geobacter sulfurreducens. MALDI MS revealed a posttranslational modification of tyrosine-32 with a moiety of a mass consistent with a glycerophosphate group in the secreted PilA protein. Their results implied that glycerophosphate modification of Y32 plays an important role in controlling the surface charge of type IV pili, and influences the attachment of
2.2.2. Quantitative proteomics The qualitative proteomics can only obtain the total expressed extracellular proteins of the microbes under a certain physiological state, which is difficult to reflect the protein changes in different environmental condition. Therefore, quantitative proteomics is needed to investigate the differential proteins and protein-protein interaction networks of microbes under various physiological state or environmental condition. Isobaric tags for relative and absolute quantitation (iTRAQ) or tandem mass tag (TMT) is a quantitative technique based on in vitro isotope labelling. The protein samples are analyzed using high precision tandem MS after the N terminal of polypeptide or lysine side-chain groups in protein labeled with various isotopes. iTRAQ/TMT can simultaneously compare the differences between protein samples, which is commonly used high-throughput screening technology in quantitative proteomics. For example, Wu et al. (2017) reported the transformation of extracellular proteins extracted from raw and enzyme disintegrated waste activated sludge using iTRAQ proteomic analysis. They found 25 differential proteins in the two samples, and offered a better understanding of the EPS changes in enzymatic treatment of sludge at molecular levels. Stable isotope labelling amino acids in cell culture (SILAC) is an in vivo metabolic labelling method (Ravikumar et al., 2014). The cells are cultured using essential amino acids with light and heavy isotopes, and the cell proteins are labeled by stable isotopes and identified by MS. Label-free quantitative proteomics can obtain the relative quantification of the corresponding proteins in different samples based on two methods: signal intensity and spectral count, which do not require expensive stable isotope labelling (Carvalhais et al., 2015). The former is based on mass spectral peak intensities, peak areas, and LC retention time, whereas the latter is estimated according to peptide coverage or spectral counts and ion counts of identified peptides. Table 1 lists the principles, merits, and drawbacks of the above mentioned relative quantitative methods for extracellular protein identification. Wang et al. (2016) showed the diagrammatic sketches of these techniques, which could be helpful for understanding and applying them. Absolute quantitative analysis methods, such as parallel reaction monitoring are also an alternative. Therefore, an appropriate technique is needed to be employed to reveal the interest proteins.
Table 1 Principles, advantages, and limitations of quantitative proteomics in identification of extracellular proteins. Techniques
Main principles
Virtues
Limitations
2D-DIGE
The sample and the added internal standard marked with fluorescent dyes, and their separation consisting with 2D electrophoresis. Microbial cells cultured using essential amino acid including isotopes, and the cell proteins labeled by stable isotopes N terminal of polypeptide or lysine side-chain groups in proteins labeled with various isotopes
More sensitive and precise, and higher dynamic range than 2D electrophoresis
Undetectable for the extremes molecular mass, hydrophobic or alkaline proteins
High accuracy and repeatability; Compatible with hydrophobic or alkaline proteins High accuracy and repeatability; Simultaneous detection of 10 samples; Suitable for low abundance sample Without expensive stable isotope labeling; Easy operation; Suitable for mass sample analysis
Requirement of expensive isotope labeling; Long analytical period Requirement of isotope labeling
SILAC iTRAQ/TMT
Label-free
The quantification is based on mass spectral peak intensities, peak areas, and LC retention time, or based on peptide hide or spectral counts and ion counts of identified peptides.
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Accuracy lower than SILAC and iTRAQ; High requirement for stability and repeatability of experimental operation
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degradation of organic carbon in EPS. Stuart et al. (2016) identified cyanobacterial extracellular enzymes and determined the enzymatic activities, indicating that extracellular enzymes contribute to degradation of EPS. Their results implied that cyanobacteria can reuse excess organic carbon in EPS and constitute a dynamic pool of extracellular resources in these microbial aggregates. These studies highlight the importance of the proteome for identification of key extracellular enzymes to that efficiently degrade various substrates. The findings demonstrate that proteomics technique can be a valuable tool for describing the physiological state and functional proteins of interested microorganism's populations growing in different substrates.
Geobacter to specific surfaces. Attachment contributes to microbial aggregation and biofilm formation, however, proteins also can result in membrane fouling during membrane separation processes. Comparison of the similarities between biocake proteins and extracellular proteins by proteomics is conducive to trace the sources of proteins resulting in membrane fouling. Huang et al. (2012) identified proteins in membrane fouling layers, and they mainly originated from intracellular proteins, and chaperonin and outer membrane proteins were observed in all membrane fouling layers. Zhou et al. (2015) found that 183 discrepant abundant protein gel spots were marked in three biocakes, and only 32 protein spots are commonly presented in the 2D gels of the three biocakes. Therefore, proteomics technique provides insight into reveal the sources and compositions of biocake proteins in membrane fouling on the molecular levels, which could be useful for developing antifouling membrane materials.
3.3. Response to environmental stress Extracellular protein expression can change when microbes respond environmental stress. For example, Jiao et al. (2011) identified extracellular proteins in biofilms at two developmental stages to understand the biofilms in an acid mine drainage environment. Their results showed that the extracellular proteins involved in motility and defense functions. Toyofuku et al. (2012) conducted a contrastive study on the extracellular proteins from planktonic and biofilm of Pseudomonas aeruginosa PAO1. They demonstrated that the distinct protein contents of outer membrane vesicles from planktonic and biofilm may be related to their various physiological states. De et al. (2015) researched the relative abundance of the exoproteome, cytoplasmic proteins, and related phenotypic traits of Lactobacillus plantarum grown under planktonic and biofilm conditions. DIGE data showed that planktonic and biofilm L. plantarum DB200 cells obtained different extracellular proteome (115 protein spots) and proteome (44). High expression levels of stress proteins indicated that biofilm cells exhibit enhanced survival under environmental stress. Therefore, the resistance mechanism of microbes to environmental stress can be elucidated by addressing the changes in the intracellular and extracellular proteins. Table 2 summarizes different proteomic techniques for characterizing the extracellular proteins involved in microbial attachment and aggregation, biodegradation, and response to environmental stress. In general, the important proteins resulted from MS are needed to verification by western blotting, enzyme-linked immunosorbent assay, enzyme activity assay, or absolute protein quantification.
3.2. Biodegradation Both pure and mixed culture microorganisms are utilized in wastewater treatment. Extracellular enzymes extensively distributed in microbial aggregates and can be revealed by proteomics methods. For example, Nandakumar et al. (2006) identified three extracellular proteases using 2DE protease zymogram. Jiao et al. (2011) detected extracellular enzymes including protein peptidases, disulfide-isomerases from an acid mine drainage microbial community, especially confirmed β-N-acetylhexosaminidase and cellulase. The use of microorganisms cultured with different substrates can be helpful to utilize such a system for producing different hydrolytic enzymes by understanding the composition of an aqueous hydrolytic system. To reveal the degradation for various substrates, Matsui et al. (2013) analyzed the exoproteome of Clostridium cellulovorans, a cellulosomes produced bacterium, including cellulosomal and noncellulosomal proteins. A total of 639 proteins were identified and quantified for C. cellulovorans cultured with cellobiose, xylan, pectin, or phosphoric acid-swollen cellulose. Furthermore, 79 proteins participated in saccharification, consisting of 35 cellulosomal and 44 noncellulosomal proteins. Their results implied that widely produced cellulosomal proteins can efficiently degrade any substrate, whereas noncellulosomal proteins specifically are expressed to promote the degradation of a particular substrate. Esaka et al. (2015) determined the changes in the extracellular proteins of C. cellulovorans for degradation of several types of natural soft biomass using quantitative proteomics. Their results exhibited that 18 proteins were specifically produced responding to the degradation of some types of natural soft biomass. The protein (Clocel_3197) was found to be involved in the degradation of all selected natural soft biomass. Parrado et al. (2014) evaluated the extracellular enzyme production of Bacillus licheniformis with different types of feathers as fermentation media. These identified hydrolytic enzymes were main keratinase, gamma-glutamyl transpeptidase, chitosanases, and glicosidases. Quantitative proteomics can reveal the expression diversity of extracellular enzymes under different environmental conditions. Adav et al. (2015) profiled the secretome of Aspergillus fumigatus cultured with cellulose, xylan and starch by iTRAQ. Their results indicated that the expression of specific cellulases and hemicellulases are promoted when A. fumigatus cultured with cellulose and xylan, and their expression level as a function of substrate. Fungi are involved in polymer conversion by secreting different enzymes, which play an important role in the degradation of non-degradable pollutants. de Eugenio et al. (2017) described the β-glucosidase secreted by a cellulase-producer fungus Talaromyces amestolkiae using shotgun proteomics analysis, and found different induction patterns. They identified two different β-glucosidases including one induced by cellulose and the other one with carbon source-independence. As a C reservoir, cyanobacterial EPS are crucial to C cycling in many microbial populations, which are related to the production and
4. Future work Proteomics has been widely used in the analysis of extracellular proteins in biological wastewater treatment systems, and hundreds of proteins are identified from the preceding work. Protein identification involves searching from a protein database, however, the current database is limited and cannot cover the total microbes in wastewater treatment systems (Heyer et al., 2017). Therefore, the protein database needs to be enlarged. Key functional proteins with low abundance can be difficult to determine because of the interference of high-abundance proteins. Singlecell imaging MS is a powerful and promising technique for mapping the distribution of the extracellular protein with subcellular resolution (Passarelli and Ewing, 2013). Total internal reflection microscopy is another powerful tool for imaging of the specific proteins secreted in real time (Shirasaki et al., 2015). Therefore, these techniques can be used to visualize low-abundance proteins production and functional protein-involved biochemical processes in the extracellular microenvironment. In addition, the proteome along with the genome and transcriptome can be used to obtain comprehensive and intensive information.
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Journal of Environmental Management 233 (2019) 24–29 Richter et al. (2017) Nandakumar et al. (2006) Jiao et al. (2011) Matsui et al. (2013) Esaka et al. (2015) Parrado et al. (2014) Adav et al. (2015) de Eugenio et al. (2017) Stuart et al. (2016) Toyofuku et al. (2012) De et al. (2015)
5. Conclusions
PilA Proteinase II, Putative lipase and Putative protease ß-N-acetylhexosaminidase and cellulase Cellulosomal and noncellulosomal proteins Protein (Clocel_3197) Keratinase, gamma-glutamyl transpeptidase, chitosanases, and glicosidases Cellulases and hemicellulases β-glucosidases Peptidases, glycosyl hydrolase, aminotransferases and ribonuclease Proteins in outer membrane vesicles Stress proteins (e.g., DnaK, GroEL, ClpP, GroES, and catalase)
Zhang et al. (2015a,b) Floyd et al. (2015) Adhesion and penetration protein autotransporter Type I pili and curli amyloid fibers
Acknowledge
The proteomics techniques for extracellular proteins determination were described, and their utilization in researching extracellular proteins involved in microbial attachment and aggregation, biodegradation for pollutants, and response to environmental stress were reviewed. However, the current protein database does not contain the total microorganism species in wastewater treatment systems. The analysis of key functional proteins with low-abundance could be difficult. Therefore, the future work including database expansion and single-cell imaging needs to be developed.
This work was supported by the National Natural Science Foundation of China (51708475 and 21777135), the Natural Science Foundation of Hunan Province, China (2018JJ3496), and Hunan 2011 Collaborative Innovation Center of Chemical Engineering & Technology with Environmental Benignity and Effective Resource Utilization. References Adav, S.S., Ravindran, A., Sze, S.K., 2015. Quantitative proteomic study of Aspergillus Fumigatus secretome revealed deamidation of secretory enzymes. J. Proteom. 115, 154–168. Carvalhais, V., Cerca, N., Vilanova, M., Vitorino, R., 2015. Proteomic profile of dormancy within Staphylococcus epidermidis biofilms using iTRAQ and label-free strategies. Appl. Microbiol. Biotechnol. 99, 2751–2762. de Eugenio, L.I., Mendez-Liter, J.A., Nieto-Dominguez, M., Alonso, L., Gil-Munoz, J., Barriuso, J., Prieto, A., Martinez, M.J., 2017. Differential Beta-glucosidase expression as a function of carbon source availability in Talaromyces amestolkiae: a genomic and proteomic approach. 10, 161. De, A.M., Siragusa, S., Campanella, D., Di, C.R., Gobbetti, M., 2015. Comparative proteomic analysis of biofilm and planktonic cells of Lactobacillus plantarum DB200. Proteomics 15, 2244–2257. Dong, J., Zhang, Z., Yu, Z., Dai, X., Xu, X., Alvarez, P.J.J., Zhu, L., 2017. Evolution and functional analysis of extracellular polymeric substances during the granulation of aerobic sludge used to treat p-chloroaniline wastewater. Chem. Eng. J. 330, 596–604. Esaka, K., Aburaya, S., Morisaka, H., Kuroda, K., Ueda, M., 2015. Exoproteome analysis of Clostridium cellulovorans in natural soft-biomass degradation. AMB Express 5, 1–8. Flemming, H., Wingender, J., 2010. The biofilm matrix. Nat. Rev. Microbiol. 8, 623–633. Floyd, K.A., Moore, J.L., Eberly, A.R., Good, J., Shaffer, C.L., 2015. Adhesive fiber stratification in uropathogenic Escherichia coli biofilms unveils oxygen-mediated control of type 1 Pili. PLoS Pathog. 11, 1–26. Guellil, A., Boualam, M., Quiquampoix, H., Ginestet, P., Audic, J.M., Block, J.C., 2001. Hydrolysis of wastewater colloidal organic matter by extracellular enzymes extracted from activated sludge flocs. Water Sci. Technol. 43, 33–40. Habermacher, J., Benetti, A.D., Derlon, N., Morgenroth, E., 2015. The effect of different aeration conditions in activated sludge – side-stream system on sludge production, sludge degradation rates, active biomass and extracellular polymeric substances. Water Res. 85, 46–56. Heyer, R., Schallert, K., Zoun, R., Becher, B., Saake, G., Benndorf, D., 2017. Challenges and perspectives of metaproteomic data analysis. J. Biotechnol. 261, 24–36. Huang, Y.T., Huang, T.H., Yang, J.H., Damodar, R.A., 2012. Identifications and characterizations of proteins from fouled membrane surfaces of different materials. Int. Biodeterior. Biodegrad. 66, 47–52. Jachlewski, S., Jachlewski, W.D., Linne, U., Sen, C.B., Wingender, J., 2015. Isolation of extracellular polymeric substances from biofilms of the thermoacidophilic archaeon Sulfolobus acidocaldarius. Front. Bioeng. Biotechnol. 3, 1–13. Jiao, Y., D'Haeseleer, P., Dill, B.D., Shah, M., VerBerkmoes, N.C., Hettich, R.L., Banfield, J.F., Thelen, M.P., 2011. Identification of biofilm matrix-associated proteins from an acid mine drainage microbial community. Appl. Environ. Microbiol. 77, 5230–5237. Joshi, P.M., Juwarkar, A.A., 2009. In vivo studies to elucidate the role of extracellular polymeric substances from azotobacter in immobilization of heavy metals. Environ. Sci. Technol. 43, 5884–5889. Kopczynski, D., Sickmann, A., Ahrends, R., 2017. Computational proteomics tools for identification and quality control. J. Biotechnol. 261, 126–130. Le, C., Kunacheva, C., Stuckey, D.C., 2016. “Protein” measurement in biological wastewater treatment systems: a critical evaluation. Environ. Sci. Technol. 50, 3074–3081. Li, W., Yu, H., 2014. Insight into the roles of microbial extracellular polymer substances in metal biosorption. Bioresour. Technol. 160, 15–23. Llama-Palacios, A., Potupa, O., Sanchez, M.C., Figuero, E., Herrera, D., Sanz, M., 2017. Aggregatibacter actinomycetemcomitans growth in biofilm versus planktonic state: differential expression of proteins. J. Proteome Res. 16, 3158–3167. Mahendran, B., Lishman, L., Liss, S.N., 2012. Structural, physicochemical and microbial properties of flocs and biofilms in integrated fixed-film activated sludge (IFFAS) systems. Water Res. 46, 5085–5101. Marshak, D.R., Kadonaga, J.T., Burgess, R.R., Knuth, M.W., Brennan, W.A., Lin, S., 1996. Strategies for Protein Purification and Characterization: a Laboratory Course Manual.
Response to environmental stress
Geobacter sulfurreducens Escherichia coli W3110 Acid mine drainage biofilms Clostridium cellulovorans Clostridium cellulovorans Bacillus licheniformis Aspergillus fumigatus Talaromyces amestolkiae Cyanobacteria Pseudomonas aeruginosa PAO1 Lactobacillus plantarum
MDLC-MS/MS MALDI-TOF imaging MS, LCMS/MS SDS-PAGE-MALDI MS/MS 2DE-MALDI-TOF MS 2D-LC-MS/MS LC-MS/MS (TMT) LC-MS/MS (TMT) LC-MS SDS-PAGE-LC-MS/MS (iTRAQ) LC-MS LC-MS/MS SDS-PAGE-LC-MS MALDI MS Biodegradation
Oliveira et al. (2015) SDS-PAGE-MALDI TOF/TOF MS
cyanobacterium Anabaena sp. PCC 7120 Biofilm Escherichia coli biofilms
Dong et al. (2017)
Chaperonins, binding proteins, metabolism-related proteins, a-synthesis proteins, and other functional proteins HesF 2DE- MALDI-TOF MS/MS Activated sludge and granular sludge Microbial attachment and aggregation
References Interest proteins Proteomic techniques Samples types Extracellular protein functions
Table 2 Different functions of extracellular proteins identified using proteomic techniques.
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associated with the Pseudomonas aeruginosa biofilm extracellular matrix. J. Proteome Res. 11, 4906–4915. Wang, J., Gao, L., Lee, Y.M., Kalesh, K.A., Ong, Y.S., Lim, J., Jee, J.E., Sun, H., Lee, S.S., Hua, Z.C., Lin, Q., 2016. Target identification of natural and traditional medicines with quantitative chemical proteomics approaches. Pharmacol. Ther. 162, 10–22. Wohlbrand, L., Trautwein, K., Rabus, R., 2013. Proteomic tools for environmental microbiology–a roadmap from sample preparation to protein identification and quantification. Proteomics 13, 2700–2730. Wu, B., Su, L., Song, L., Dai, X., Chai, X., 2017. Exploring the potential of iTRAQ proteomics for tracking the transformation of extracellular proteins from enzyme-disintegrated waste activated sludge. Bioresour. Technol. 225, 75–83. Xiao, M., Yang, J., Feng, Y., Zhu, Y., Chai, X., Wang, Y., 2017. Metaproteomic strategies and applications for gut microbial research. Appl. Microbiol. Biotechnol. 101, 3077–3088. Xiao, Y., Wiesner, M.R., 2013. Transport and retention of selected engineered nanoparticles by porous media in the presence of a biofilm. Environ. Sci. Technol. 47, 2246–2253. Xiong, W., Abraham, P.E., Li, Z., Pan, C., Hettich, R.L., 2015. Microbial metaproteomics for characterizing the range of metabolic functions and activities of human gut microbiota. Proteomics 15, 3424–3438. Yin, C., Meng, F., Chen, G., 2015. Spectroscopic characterization of extracellular polymeric substances from a mixed culture dominated by ammonia-oxidizing bacteria. Water Res. 68, 740–749. Zhang, P., Chen, Y., Peng, M., Guo, J., Shen, Y., Yan, P., Zhou, Q., Jiang, J., Fang, F., 2017. Extracellular polymeric substances dependence of surface interactions of Bacillus subtilis with Cd2+ and Pb2+: an investigation combined with surface plasmon resonance and infrared spectra. Colloids Surf. B 154, 357–364. Zhang, P., Shen, Y., Guo, J., Li, C., Wang, H., Chen, Y., Yan, P., Yang, J., Fang, F., 2015a. Extracellular protein analysis of activated sludge and their functions in wastewater treatment plant by shotgun proteomics. Sci. Rep. UK 5, 12041. Zhang, P., Guo, J., Shen, Y., Yan, P., Chen, Y., Wang, H., Yang, J., Fang, F., Li, C., 2015b. Microbial communities, extracellular proteomics and polysaccharides: a comparative investigation on biofilm and suspended sludge. Bioresour. Technol. 190, 21–28. Zhang, P., Xu, X., Chen, Y., Xiao, M., Feng, B., Tian, K., Chen, Y., Dai, Y., 2018. Protein corona between nanoparticles and bacterial proteins in activated sludge: characterization and effect on nanoparticle aggregation. Bioresour. Technol. 250, 10–16. Zhou, Z., Meng, F., He, X., Chae, S., An, Y., Jia, X., 2015. Metaproteomic analysis of biocake proteins to understand membrane fouling in a submerged membrane bioreactor. Environ. Sci. Technol. 49, 1068–1077.
Cold Spring Harbor Laboratory Press. Matsui, K., Bae, J., Esaka, K., Morisaka, H., Kuroda, K., 2013. Exoproteome profiles of Clostridium cellulovorans grown on various carbon sources. Appl. Environ. Microbiol. 79, 6576–6584. Nandakumar, M.P., Cheung, A., Marten, M.R., 2006. Proteomic analysis of extracellular proteins from Escherichia coli W3110. J. Proteome Res. 5, 1155–1161. Oliveira, P., Pinto, F., Pacheco, C.C., Mota, R., Tamagnini, P., 2015. HesF, an exoprotein required for filament adhesion and aggregation in Anabaena sp. PCC 7120. Environ. Microbiol. 17, 1631–1648. Park, C., Novak, J.T., Helm, R.F., Ahn, Y., Esen, A., 2008. Evaluation of the extracellular proteins in full-scale activated sludges. Water Res. 42, 3879–3889. Parrado, J., Rodriguez-Morgado, B., Tejada, M., Hernandez, T., Garcia, C., 2014. Proteomic analysis of enzyme production by Bacillus licheniformis using different feather wastes as the sole fermentation media. Enzym. Microb. Technol. 57, 1–7. Passarelli, M.K., Ewing, A.G., 2013. Single-cell imaging mass spectrometry. Curr. Opin. Chem. Biol. 17, 854–859. Ravikumar, V., Shi, L., Krug, K., Derouiche, A., Jers, C., Cousin, C., Kobir, A., Mijakovic, I., Macek, B., 2014. Quantitative phosphoproteome analysis of Bacillus subtilis reveals novel substrates of the kinase PrkC and phosphatase. PrpC 13, 1965–1978. Richter, L.V., Franks, A.E., Weis, R.M., Sandler, S.J., 2017. Significance of a posttranslational modification of the PilA protein of Geobacter sulfurreducens for surface attachment, biofilm formation, and growth on insoluble extracellular electron acceptors. J. Bacteriol. 199. https://doi.org/10.1128/JB.00716-16. Rodrigues, P.M., Silva, T.S., Dias, J., Jessen, F., 2012. Proteomics in aquaculture: applications and trends. J. Proteom. 75, 4325–4345. Romero, D., Aguilar, C., Losick, R., Kolter, R., 2010. Amyloid fibers provide structural integrity to Bacillus subtilis biofilms. Proc. Natl. Acad. Sci. U. S. A. 107, 2230–2234. Shirasaki, Y., Yamagishi, M., Suzuki, N., Izawa, K., Nakahara, A., Mizuno, J., Shoji, S., Heike, T., Harada, Y., Nishikomori, R., Ohara, O., 2015. Real-time single-cell imaging of protein secretion. Sci. Rep. UK 4, 4736. Silva, A.F., Carvalho, G., Soares, R., Coelho, A.V., Barreto Crespo, M.T., 2012. Step-bystep strategy for protein enrichment and proteome characterisation of extracellular polymeric substances in wastewater treatment systems. Appl. Microbiol. Biotechnol. 95, 767–776. Speda, Johansson, M.A., Carlsson, U.J., Karlsson, M., 2017. Assessment of sample preparation methods for metaproteomics of extracellular proteins. Anal. Biochem. 516, 23–36. Stuart, R.K., Mayali, X., Lee, J.Z., Craig, E.R., Hwang, M., 2016. Cyanobacterial reuse of extracellular organic carbon in microbial mats. ISME J. 10, 1240–1251. Toyofuku, M., Roschitzki, B., Riedel, K., Eberl, L., 2012. Identification of proteins
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Journal of Environmental Management journal homepage: www.elsevier.com/locate/jenvman
Review
Identification and function of extracellular protein in wastewater treatment using proteomic approaches: A minireview
T
Peng Zhanga,b,∗, Jing Zhua, Xiao-Yan Xua, Tai-Ping Qinga, You-Zhi Daia, Bo Fenga,∗∗ a b
College of Environment and Resources, Xiangtan University, Xiangtan, 411105, China Key Laboratory of the Three Gorges Reservoir Region's Eco-Environments of MOE, Chongqing University, Chongqing, 400045, China
A R T I C LE I N FO
A B S T R A C T
Keywords: Extracellular proteins Proteomics Microbial attachment Biodegradation Response to environmental stresses
Microbial extracellular proteins serve as important functions in wastewater treatment process. Analysis of their compositions and properties is crucial to probe their specific functions. However, conventional analytical techniques cannot obtain interest protein information from complex proteins. Recently, the extracellular proteomics method has been applied to resolve the composition of extracellular proteins. In order to better understand the roles of extracellular protein in wastewater treatment process, this review provides the information on the proteomics methods and their application in investigating extracellular proteins involved in microbial attachment/aggregation, biodegradation of pollutants, and response to environmental stresses. Future work needs to exploit the full capability of the proteome.
1. Introduction In microbial aggregates, e.g., activated sludge, biofilm, and granule sludge, extracellular polymeric substances (EPS) provide spatial organization and structural stability, mediating both cell-to-cell and cell-tosurface interactions during microbial aggregate development. EPS consist of a complex high-molecular-weight mixture of polymers that are mainly released by microorganisms and are composed of proteins, polysaccharides, humic substances, nucleic acids, lipids, etc. EPS mainly comprise proteins and polysaccharides. In activated sludges, extracellular proteins are more abundant than polysaccharides, and they serve important functions in the wastewater treatment (Park et al., 2008; Mahendran et al., 2012; Xiao and Wiesner, 2013). Extracellular proteins consist of enzymes and structural proteins. Their major functions in wastewater treatment include the formations of microbial aggregate, pollutant migration and transformation, and resisting of toxic substances. Extracellular proteins can promote the formation of microbial aggregates, and maintain their structural integrity due to the connection between negatively charged amino acids in proteins via multivalent cation bridging (Flemming and Wingender, 2010). They also contribute to pollutant removal in wastewater treatment via adsorption and catalysis. They wrap on the cell surfaces and initially contact with extracellular substrates, and can strongly bind heavy metals, organic matter, and nanoparticles. Extracellular enzymes
∗
supply an external digestion system, playing an important role in the degradation of the organic small molecules, organic colloidal fraction and particulate biomass (Guellil et al., 2001; Habermacher et al., 2015). In addition, extracellular proteins can reduce the effects of toxic substances because hydroxyl, carboxyl, phosphate and amide groups in extracellular proteins provide binding sites for antibiotics, heavy metals, and nanoparticles (Joshi and Juwarkar, 2009; Li and Yu, 2014). However, the specific functions of these proteins in the extracellular matrix or microbial physiology are unclear. The compositions and properties of extracellular proteins must be determined to probe their specific functions. The analysis of extracellular proteins involves conventional quantification, spectral characteristics, molecular weight, amino acid sequences, secondary structures, viscoelasticity, enzyme activity, and affinity (Yin et al., 2015; Le et al., 2016; Zhang et al., 2017). However, these techniques cannot obtain interest protein information and cannot screen the key functional protein from the compound proteins. In recent years, the extracellular proteome or called exoproteome has been used to reveal the composition of extracellular proteins and has deepened the understanding of their functions in wastewater treatment. The proteome is the total corresponding proteins expressed by the genome, which reflects the presence and active of all proteins in a cell, tissue and organism. The genome is normally stable, whereas the amount and types of proteins expressed by the genome vary based on
Corresponding author. College of Environment and Resources, Xiangtan University, Xiangtan, 411105, China. Corresponding author. E-mail addresses: [email protected] (P. Zhang), [email protected] (B. Feng).
∗∗
https://doi.org/10.1016/j.jenvman.2018.12.028 Received 30 March 2018; Received in revised form 4 November 2018; Accepted 9 December 2018 0301-4797/ © 2018 Elsevier Ltd. All rights reserved.
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2DE. The efficient separation of complex proteins is important to improve peptide coverage in MS analysis. 2DE protein identification technology can separate proteins in 2D through isoelectric focusing and SDS-PAGE based on the difference of the isoelectric point and the molecular weight of the proteins, and different natural proteins distribute in the gel in the form of spot. Interest proteins in gel spot can be directly determined using MS without LC separation. Jachlewski et al. (2015) found that the cation exchange resin extraction was the best suited method to isolate Sulfolobus acidocaldarius biofilm EPS among the five extraction methods, and several hundreds of protein spots were determined. Speda et al. (2017) developed one direct precipitation method and one extraction/precipitation method for obtaining extracellular proteins, which provided high gel spot detection abilities, especially for low abundance extracellular proteins. Two-dimensional fluorescence difference gel electrophoresis (2DDIGE) is a quantitative proteomics technique developed on the basis of traditional 2DE, and the principle of protein separation is consistent with that of 2DE. The sample and added internal standard are marked with fluorescent dyes (Cy2, Cy3, Cy5), and the differential proteins can be accurately and sensitively revealed (Llama-Palacios et al., 2017). However, humic acids adulterated in protein could interfere or mask the visualization of protein bands in gel electrophoresis, which indicated that preparing of high-purity proteins is necessary (Silva et al., 2012). Furthermore, for some special proteins, such as having extremes in molecular mass, or that are hydrophobic or insolvable, gel based separation is often unsuitable.
the growth period and environmental condition. Therefore, specific extracellular proteins involved in the development of microbial aggregate and the pollutant migration and transformation can be revealed using proteomics. In this review, we describe the analytical methods including qualitative and quantitative proteomics for extracellular proteins, and discuss their application in probing extracellular proteins involved in microbial attachment/aggregation, biodegradation, and response to environmental stress. 2. Identification of extracellular proteome After extracting EPS from microbial aggregates, the extracellular proteins can be crudely purified from EPS for proteomics analysis. Purification methods mainly include centrifugation, precipitation, dialysis and ultrafiltration, which are mentioned in the related reference books (Marshak et al., 1996). The crude proteins can be isolated through gel-based separation and gel-free separation (Rodrigues et al., 2012). The former includes sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and 2D gel electrophoresis (2DE). The latter is chromatography, such as ion exchange chromatography, size exclusion chromatography, hydrophobic interaction chromatography, affinity chromatography and chromatofocusing. Fig. 1 shows the analysis procedures of extracellular proteins. 2.1. Protein isolation
2.1.2. Gel-free separation Chromatographic separation can overcome the limitations of gel based separation and can effectively separate components from mixtures. High-pressure liquid chromatography (HPLC) and reversed phase HPLC separation are generally used (Wohlbrand et al., 2013). For complex proteome samples, multi-dimensional liquid chromatographic (MDLC) separation system is developed, which mainly includes 2D and 3D chromatographic separation (Xiao et al., 2017). MDLC separation system can optimize the combination of two or more liquid phase separation methods with different separation principles, and it can effectively improve the resolution and peak capacity of the system.
2.1.1. Gel-based separation SDS-PAGE. SDS-PAGE is a biochemical analytical approach for the separation of charged molecules (proteins) in mixtures by their molecular weight in an electric field. The mobility of protein depends only on their molecular weight. Interest gel pieces in SDS-PAGE are digested, and are separated and determined using liquid chromatography and mass spectrometry (LC-MS). Park et al. (2008) extracted the activated sludge EPS from a municipal wastewater treatment plant using three cation-associated extraction methods, and the proteins in EPS were precipitated by ammonium sulfate. Their results showed that the SDS-PAGE protein profiles were dependent on the extraction method used. However, there are only several proteins were identified. Silva et al. (2012) compared various concentrations and precipitation methods, and analyzed both the extracellular proteins in the soluble and bound EPS from activated sludge. The results identified 25–32 and 17 proteins in soluble EPS and bound EPS, respectively. Therefore, proteome information resulted from SDSPAGE is limited.
2.2. Mass spectrometry analyses Protein identification is highly dependent on mass spectrometry (MS). Based on the different ionization methods, multiple mass spectrometry including electrospray ionization (ESI) MS, matrix assisted laser desorption ionization (MALDI) MS, fast atom bombardment MS, atmospheric pressure ionization MS are used to protein detection. Among them, ESI and MALDI MS are the most widely utilized (Xiao et al., 2017). MS can realize the qualitative and quantitative analysis of proteome through corresponding experimental design. The protein identification is built on peptide spectrum match principle (Kopczynski et al., 2017). The similarity of MS/MS spectra between sample peptide and the theoretical peptide in the database is statistically analyzed and scored by the algorithm, and the theoretical peptide with the highest score is the result of identification. The commonly used search software is Mascot, X!Tandem, OMSSA, SEQUEST, and Andromeda (Xiong et al., 2015). The principal methods of protein bioinformatics analysis include cluster analysis, gene ontology functional classification analysis, biological pathway analysis and protein interaction network analysis (Xiao et al., 2017). The available software contains Cluster & TreeView, DAVID, go Surfer, GenMAPP, and ingenuity pathway analysis. 2.2.1. Qualitative proteomics Full spectrum analysis. The full spectrum analysis of proteins may also be termed as shotgun analysis based on MS. A SDS-PAGE gel or hydrolyzed peptide mixture in solution is separated and detected by LC-
Fig. 1. Proteomics workflow for extracellular protein analysis. 25
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3. Functions of extracellular proteome
MS/MS. The proteins are identified via MS/MS spectra search against the protein database (Zhang et al., 2018). This method can systematically and comprehensively identify thousands of proteins from microbial aggregates. For example, Zhang et al. (2015a,b) analyzed the extracellular proteins extracted from anaerobic, anoxic and aerobic sludges in a municipal wastewater treatment plant using the shotgun method, and classified 130, 108 and 114 proteins, respectively. Their results indicated that most proteins originated from the intracellular release due to cell lysis.
3.1. Microbial attachment and aggregation Microbial aggregation and biofilm formation are essential for resisting environmental stress, such as hydraulic shear force and toxic substances, and are also necessary for sludge-water separation in the effluent of wastewater treatment plants. Many extracellular proteins can promote bacterial attachment and aggregation through non-specific interactions. For example, Dong et al. (2017) comparatively researched the extracellular proteomes between inoculated activated sludge and mature granular sludge based on 2D gels. They found 5 types of proteins, including chaperonins, binding proteins, metabolism-related proteins, a-synthesis proteins, and other functional proteins were associated with the granulation of aerobic sludge and EPS secretion. Some extracellular proteins related to specific attachment were found based on the proteomics. Oliveira et al. (2015) identified and characterized an extracellular protein (Alr0267) named HesF from filamentous cyanobacterium Anabaena sp. PCC 7120. Their results exhibited that HesF was associated with the filament adhesion and microbial aggregation in heterocyst-forming cyanobacteria. The extracellular adhesion proteins can vary owing to the abundant microbial species in wastewater treatment system. Zhang et al. (2015b) evaluated the extracellular proteins in biofilm. An extracellular protein named adhesion and penetration protein autotransporter was identified and can promote the microbial adhesion. The pili, an important group of proteins polymerized into fibers, are also involved in microbial attachment (Romero et al., 2010). Floyd et al. (2015) determined the spatial proteome of intact biofilms in situ using MALDI time-of-flight (TOF) imaging MS, and their results showed that the protein species are distinctly localized within surface-associated Escherichia coli biofilms. And two adhesive fibers, including type I pili and curli amyloid fibers were found, which are critical for Escherichia coli biofilm formation. Their work offered insight into the spatial regulation of proteins within bacterial biofilms during microbial attachment and biofilm formation. Type IV pili are intrinsic structural elements in biofilm formation of many bacteria and can serve as conductive nanowires together with a number of c-type cytochromes in extracellular electron transfer process. Posttranslational modification (PTM) plays a fundamental role in cellular biological regulation, which potentially changing the physical or chemical properties, activity, cell localization or stability of proteins. The modified kind and site of protein or polypeptide can be detected by proteomics. Richter et al. (2017) investigated that a posttranslational modification of a non-conserved amino acid residue within the PilA protein, which is the structural subunit of the type IV pili in Geobacter sulfurreducens. MALDI MS revealed a posttranslational modification of tyrosine-32 with a moiety of a mass consistent with a glycerophosphate group in the secreted PilA protein. Their results implied that glycerophosphate modification of Y32 plays an important role in controlling the surface charge of type IV pili, and influences the attachment of
2.2.2. Quantitative proteomics The qualitative proteomics can only obtain the total expressed extracellular proteins of the microbes under a certain physiological state, which is difficult to reflect the protein changes in different environmental condition. Therefore, quantitative proteomics is needed to investigate the differential proteins and protein-protein interaction networks of microbes under various physiological state or environmental condition. Isobaric tags for relative and absolute quantitation (iTRAQ) or tandem mass tag (TMT) is a quantitative technique based on in vitro isotope labelling. The protein samples are analyzed using high precision tandem MS after the N terminal of polypeptide or lysine side-chain groups in protein labeled with various isotopes. iTRAQ/TMT can simultaneously compare the differences between protein samples, which is commonly used high-throughput screening technology in quantitative proteomics. For example, Wu et al. (2017) reported the transformation of extracellular proteins extracted from raw and enzyme disintegrated waste activated sludge using iTRAQ proteomic analysis. They found 25 differential proteins in the two samples, and offered a better understanding of the EPS changes in enzymatic treatment of sludge at molecular levels. Stable isotope labelling amino acids in cell culture (SILAC) is an in vivo metabolic labelling method (Ravikumar et al., 2014). The cells are cultured using essential amino acids with light and heavy isotopes, and the cell proteins are labeled by stable isotopes and identified by MS. Label-free quantitative proteomics can obtain the relative quantification of the corresponding proteins in different samples based on two methods: signal intensity and spectral count, which do not require expensive stable isotope labelling (Carvalhais et al., 2015). The former is based on mass spectral peak intensities, peak areas, and LC retention time, whereas the latter is estimated according to peptide coverage or spectral counts and ion counts of identified peptides. Table 1 lists the principles, merits, and drawbacks of the above mentioned relative quantitative methods for extracellular protein identification. Wang et al. (2016) showed the diagrammatic sketches of these techniques, which could be helpful for understanding and applying them. Absolute quantitative analysis methods, such as parallel reaction monitoring are also an alternative. Therefore, an appropriate technique is needed to be employed to reveal the interest proteins.
Table 1 Principles, advantages, and limitations of quantitative proteomics in identification of extracellular proteins. Techniques
Main principles
Virtues
Limitations
2D-DIGE
The sample and the added internal standard marked with fluorescent dyes, and their separation consisting with 2D electrophoresis. Microbial cells cultured using essential amino acid including isotopes, and the cell proteins labeled by stable isotopes N terminal of polypeptide or lysine side-chain groups in proteins labeled with various isotopes
More sensitive and precise, and higher dynamic range than 2D electrophoresis
Undetectable for the extremes molecular mass, hydrophobic or alkaline proteins
High accuracy and repeatability; Compatible with hydrophobic or alkaline proteins High accuracy and repeatability; Simultaneous detection of 10 samples; Suitable for low abundance sample Without expensive stable isotope labeling; Easy operation; Suitable for mass sample analysis
Requirement of expensive isotope labeling; Long analytical period Requirement of isotope labeling
SILAC iTRAQ/TMT
Label-free
The quantification is based on mass spectral peak intensities, peak areas, and LC retention time, or based on peptide hide or spectral counts and ion counts of identified peptides.
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Accuracy lower than SILAC and iTRAQ; High requirement for stability and repeatability of experimental operation
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degradation of organic carbon in EPS. Stuart et al. (2016) identified cyanobacterial extracellular enzymes and determined the enzymatic activities, indicating that extracellular enzymes contribute to degradation of EPS. Their results implied that cyanobacteria can reuse excess organic carbon in EPS and constitute a dynamic pool of extracellular resources in these microbial aggregates. These studies highlight the importance of the proteome for identification of key extracellular enzymes to that efficiently degrade various substrates. The findings demonstrate that proteomics technique can be a valuable tool for describing the physiological state and functional proteins of interested microorganism's populations growing in different substrates.
Geobacter to specific surfaces. Attachment contributes to microbial aggregation and biofilm formation, however, proteins also can result in membrane fouling during membrane separation processes. Comparison of the similarities between biocake proteins and extracellular proteins by proteomics is conducive to trace the sources of proteins resulting in membrane fouling. Huang et al. (2012) identified proteins in membrane fouling layers, and they mainly originated from intracellular proteins, and chaperonin and outer membrane proteins were observed in all membrane fouling layers. Zhou et al. (2015) found that 183 discrepant abundant protein gel spots were marked in three biocakes, and only 32 protein spots are commonly presented in the 2D gels of the three biocakes. Therefore, proteomics technique provides insight into reveal the sources and compositions of biocake proteins in membrane fouling on the molecular levels, which could be useful for developing antifouling membrane materials.
3.3. Response to environmental stress Extracellular protein expression can change when microbes respond environmental stress. For example, Jiao et al. (2011) identified extracellular proteins in biofilms at two developmental stages to understand the biofilms in an acid mine drainage environment. Their results showed that the extracellular proteins involved in motility and defense functions. Toyofuku et al. (2012) conducted a contrastive study on the extracellular proteins from planktonic and biofilm of Pseudomonas aeruginosa PAO1. They demonstrated that the distinct protein contents of outer membrane vesicles from planktonic and biofilm may be related to their various physiological states. De et al. (2015) researched the relative abundance of the exoproteome, cytoplasmic proteins, and related phenotypic traits of Lactobacillus plantarum grown under planktonic and biofilm conditions. DIGE data showed that planktonic and biofilm L. plantarum DB200 cells obtained different extracellular proteome (115 protein spots) and proteome (44). High expression levels of stress proteins indicated that biofilm cells exhibit enhanced survival under environmental stress. Therefore, the resistance mechanism of microbes to environmental stress can be elucidated by addressing the changes in the intracellular and extracellular proteins. Table 2 summarizes different proteomic techniques for characterizing the extracellular proteins involved in microbial attachment and aggregation, biodegradation, and response to environmental stress. In general, the important proteins resulted from MS are needed to verification by western blotting, enzyme-linked immunosorbent assay, enzyme activity assay, or absolute protein quantification.
3.2. Biodegradation Both pure and mixed culture microorganisms are utilized in wastewater treatment. Extracellular enzymes extensively distributed in microbial aggregates and can be revealed by proteomics methods. For example, Nandakumar et al. (2006) identified three extracellular proteases using 2DE protease zymogram. Jiao et al. (2011) detected extracellular enzymes including protein peptidases, disulfide-isomerases from an acid mine drainage microbial community, especially confirmed β-N-acetylhexosaminidase and cellulase. The use of microorganisms cultured with different substrates can be helpful to utilize such a system for producing different hydrolytic enzymes by understanding the composition of an aqueous hydrolytic system. To reveal the degradation for various substrates, Matsui et al. (2013) analyzed the exoproteome of Clostridium cellulovorans, a cellulosomes produced bacterium, including cellulosomal and noncellulosomal proteins. A total of 639 proteins were identified and quantified for C. cellulovorans cultured with cellobiose, xylan, pectin, or phosphoric acid-swollen cellulose. Furthermore, 79 proteins participated in saccharification, consisting of 35 cellulosomal and 44 noncellulosomal proteins. Their results implied that widely produced cellulosomal proteins can efficiently degrade any substrate, whereas noncellulosomal proteins specifically are expressed to promote the degradation of a particular substrate. Esaka et al. (2015) determined the changes in the extracellular proteins of C. cellulovorans for degradation of several types of natural soft biomass using quantitative proteomics. Their results exhibited that 18 proteins were specifically produced responding to the degradation of some types of natural soft biomass. The protein (Clocel_3197) was found to be involved in the degradation of all selected natural soft biomass. Parrado et al. (2014) evaluated the extracellular enzyme production of Bacillus licheniformis with different types of feathers as fermentation media. These identified hydrolytic enzymes were main keratinase, gamma-glutamyl transpeptidase, chitosanases, and glicosidases. Quantitative proteomics can reveal the expression diversity of extracellular enzymes under different environmental conditions. Adav et al. (2015) profiled the secretome of Aspergillus fumigatus cultured with cellulose, xylan and starch by iTRAQ. Their results indicated that the expression of specific cellulases and hemicellulases are promoted when A. fumigatus cultured with cellulose and xylan, and their expression level as a function of substrate. Fungi are involved in polymer conversion by secreting different enzymes, which play an important role in the degradation of non-degradable pollutants. de Eugenio et al. (2017) described the β-glucosidase secreted by a cellulase-producer fungus Talaromyces amestolkiae using shotgun proteomics analysis, and found different induction patterns. They identified two different β-glucosidases including one induced by cellulose and the other one with carbon source-independence. As a C reservoir, cyanobacterial EPS are crucial to C cycling in many microbial populations, which are related to the production and
4. Future work Proteomics has been widely used in the analysis of extracellular proteins in biological wastewater treatment systems, and hundreds of proteins are identified from the preceding work. Protein identification involves searching from a protein database, however, the current database is limited and cannot cover the total microbes in wastewater treatment systems (Heyer et al., 2017). Therefore, the protein database needs to be enlarged. Key functional proteins with low abundance can be difficult to determine because of the interference of high-abundance proteins. Singlecell imaging MS is a powerful and promising technique for mapping the distribution of the extracellular protein with subcellular resolution (Passarelli and Ewing, 2013). Total internal reflection microscopy is another powerful tool for imaging of the specific proteins secreted in real time (Shirasaki et al., 2015). Therefore, these techniques can be used to visualize low-abundance proteins production and functional protein-involved biochemical processes in the extracellular microenvironment. In addition, the proteome along with the genome and transcriptome can be used to obtain comprehensive and intensive information.
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5. Conclusions
PilA Proteinase II, Putative lipase and Putative protease ß-N-acetylhexosaminidase and cellulase Cellulosomal and noncellulosomal proteins Protein (Clocel_3197) Keratinase, gamma-glutamyl transpeptidase, chitosanases, and glicosidases Cellulases and hemicellulases β-glucosidases Peptidases, glycosyl hydrolase, aminotransferases and ribonuclease Proteins in outer membrane vesicles Stress proteins (e.g., DnaK, GroEL, ClpP, GroES, and catalase)
Zhang et al. (2015a,b) Floyd et al. (2015) Adhesion and penetration protein autotransporter Type I pili and curli amyloid fibers
Acknowledge
The proteomics techniques for extracellular proteins determination were described, and their utilization in researching extracellular proteins involved in microbial attachment and aggregation, biodegradation for pollutants, and response to environmental stress were reviewed. However, the current protein database does not contain the total microorganism species in wastewater treatment systems. The analysis of key functional proteins with low-abundance could be difficult. Therefore, the future work including database expansion and single-cell imaging needs to be developed.
This work was supported by the National Natural Science Foundation of China (51708475 and 21777135), the Natural Science Foundation of Hunan Province, China (2018JJ3496), and Hunan 2011 Collaborative Innovation Center of Chemical Engineering & Technology with Environmental Benignity and Effective Resource Utilization. References Adav, S.S., Ravindran, A., Sze, S.K., 2015. Quantitative proteomic study of Aspergillus Fumigatus secretome revealed deamidation of secretory enzymes. J. Proteom. 115, 154–168. Carvalhais, V., Cerca, N., Vilanova, M., Vitorino, R., 2015. Proteomic profile of dormancy within Staphylococcus epidermidis biofilms using iTRAQ and label-free strategies. Appl. Microbiol. Biotechnol. 99, 2751–2762. de Eugenio, L.I., Mendez-Liter, J.A., Nieto-Dominguez, M., Alonso, L., Gil-Munoz, J., Barriuso, J., Prieto, A., Martinez, M.J., 2017. Differential Beta-glucosidase expression as a function of carbon source availability in Talaromyces amestolkiae: a genomic and proteomic approach. 10, 161. De, A.M., Siragusa, S., Campanella, D., Di, C.R., Gobbetti, M., 2015. Comparative proteomic analysis of biofilm and planktonic cells of Lactobacillus plantarum DB200. Proteomics 15, 2244–2257. Dong, J., Zhang, Z., Yu, Z., Dai, X., Xu, X., Alvarez, P.J.J., Zhu, L., 2017. Evolution and functional analysis of extracellular polymeric substances during the granulation of aerobic sludge used to treat p-chloroaniline wastewater. Chem. Eng. J. 330, 596–604. Esaka, K., Aburaya, S., Morisaka, H., Kuroda, K., Ueda, M., 2015. Exoproteome analysis of Clostridium cellulovorans in natural soft-biomass degradation. AMB Express 5, 1–8. Flemming, H., Wingender, J., 2010. The biofilm matrix. Nat. Rev. Microbiol. 8, 623–633. Floyd, K.A., Moore, J.L., Eberly, A.R., Good, J., Shaffer, C.L., 2015. Adhesive fiber stratification in uropathogenic Escherichia coli biofilms unveils oxygen-mediated control of type 1 Pili. PLoS Pathog. 11, 1–26. Guellil, A., Boualam, M., Quiquampoix, H., Ginestet, P., Audic, J.M., Block, J.C., 2001. Hydrolysis of wastewater colloidal organic matter by extracellular enzymes extracted from activated sludge flocs. Water Sci. Technol. 43, 33–40. Habermacher, J., Benetti, A.D., Derlon, N., Morgenroth, E., 2015. The effect of different aeration conditions in activated sludge – side-stream system on sludge production, sludge degradation rates, active biomass and extracellular polymeric substances. Water Res. 85, 46–56. Heyer, R., Schallert, K., Zoun, R., Becher, B., Saake, G., Benndorf, D., 2017. Challenges and perspectives of metaproteomic data analysis. J. Biotechnol. 261, 24–36. Huang, Y.T., Huang, T.H., Yang, J.H., Damodar, R.A., 2012. Identifications and characterizations of proteins from fouled membrane surfaces of different materials. Int. Biodeterior. Biodegrad. 66, 47–52. Jachlewski, S., Jachlewski, W.D., Linne, U., Sen, C.B., Wingender, J., 2015. Isolation of extracellular polymeric substances from biofilms of the thermoacidophilic archaeon Sulfolobus acidocaldarius. Front. Bioeng. Biotechnol. 3, 1–13. Jiao, Y., D'Haeseleer, P., Dill, B.D., Shah, M., VerBerkmoes, N.C., Hettich, R.L., Banfield, J.F., Thelen, M.P., 2011. Identification of biofilm matrix-associated proteins from an acid mine drainage microbial community. Appl. Environ. Microbiol. 77, 5230–5237. Joshi, P.M., Juwarkar, A.A., 2009. In vivo studies to elucidate the role of extracellular polymeric substances from azotobacter in immobilization of heavy metals. Environ. Sci. Technol. 43, 5884–5889. Kopczynski, D., Sickmann, A., Ahrends, R., 2017. Computational proteomics tools for identification and quality control. J. Biotechnol. 261, 126–130. Le, C., Kunacheva, C., Stuckey, D.C., 2016. “Protein” measurement in biological wastewater treatment systems: a critical evaluation. Environ. Sci. Technol. 50, 3074–3081. Li, W., Yu, H., 2014. Insight into the roles of microbial extracellular polymer substances in metal biosorption. Bioresour. Technol. 160, 15–23. Llama-Palacios, A., Potupa, O., Sanchez, M.C., Figuero, E., Herrera, D., Sanz, M., 2017. Aggregatibacter actinomycetemcomitans growth in biofilm versus planktonic state: differential expression of proteins. J. Proteome Res. 16, 3158–3167. Mahendran, B., Lishman, L., Liss, S.N., 2012. Structural, physicochemical and microbial properties of flocs and biofilms in integrated fixed-film activated sludge (IFFAS) systems. Water Res. 46, 5085–5101. Marshak, D.R., Kadonaga, J.T., Burgess, R.R., Knuth, M.W., Brennan, W.A., Lin, S., 1996. Strategies for Protein Purification and Characterization: a Laboratory Course Manual.
Response to environmental stress
Geobacter sulfurreducens Escherichia coli W3110 Acid mine drainage biofilms Clostridium cellulovorans Clostridium cellulovorans Bacillus licheniformis Aspergillus fumigatus Talaromyces amestolkiae Cyanobacteria Pseudomonas aeruginosa PAO1 Lactobacillus plantarum
MDLC-MS/MS MALDI-TOF imaging MS, LCMS/MS SDS-PAGE-MALDI MS/MS 2DE-MALDI-TOF MS 2D-LC-MS/MS LC-MS/MS (TMT) LC-MS/MS (TMT) LC-MS SDS-PAGE-LC-MS/MS (iTRAQ) LC-MS LC-MS/MS SDS-PAGE-LC-MS MALDI MS Biodegradation
Oliveira et al. (2015) SDS-PAGE-MALDI TOF/TOF MS
cyanobacterium Anabaena sp. PCC 7120 Biofilm Escherichia coli biofilms
Dong et al. (2017)
Chaperonins, binding proteins, metabolism-related proteins, a-synthesis proteins, and other functional proteins HesF 2DE- MALDI-TOF MS/MS Activated sludge and granular sludge Microbial attachment and aggregation
References Interest proteins Proteomic techniques Samples types Extracellular protein functions
Table 2 Different functions of extracellular proteins identified using proteomic techniques.
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