Discovery and Characterization of the Highly Active Fungal

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Discovery and Characterization of the Highly Active Fungal Immunomodulatory Protein Fip-vvo82 Ying Wang, Ying W#ng, Yingnv Gao, Yan Li, Jia-Ning Wan, Rui-Heng Yang, WenJun Mao, Chen-Li Zhou, Li-Hua Tang, Ming Gong, Ying-Ying Wu, and Da-Peng Bao J. Chem. Inf. Model., Just Accepted Manuscript • DOI: 10.1021/acs.jcim.6b00087 • Publication Date (Web): 20 Sep 2016 Downloaded from http://pubs.acs.org on September 28, 2016

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Journal of Chemical Information and Modeling

Discovery and Characterization of the Highly Active Fungal Immunomodulatory Protein Fip-vvo82 Ying Wang†, Ying Wāng†, Yingnv Gao†, Yan Li†, Jia-Ning Wan†, Rui-Heng Yang†, Wen-Jun Mao†, Chen-Li Zhou†, Li-Hua Tang†, Ming Gong†, Ying-Ying Wu† and Da-Peng Bao*† †

National Engineering Research Center of Edible Fungi; Key Laboratory of Applied

Mycological Resources and Utilization, Ministry of Agriculture; Shanghai Key Laboratory of Agricultural Genetics and Breeding; Institute of Edible Fungi, Shanghai Academy of Agriculture Science, Shanghai 201403, China

The first two authors contributed equally to this work.

ACS Paragon Plus Environment


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ABSTRACT: Volvaria volvacea (Bull. ex Fr.) Sing, an important edible and medicinal macro-fungus, has been used to remedy various diseases for hundreds of years in East Asia. To identify key proteins with the unique therapeutic activity in V. volvacea, we conducted a genome-wide comparison of V. volvacea protein families and those of other edible fungi that lack therapeutic functions and identified 7 fungal immunomodulatory proteins (FIPs) in V. volvacea. Based on the predicted physiological and biochemical characteristics of the 7 FIPs, the novel Fip-vvo82 was inferred to have high immunomodulatory activity; this was confirmed by molecular and immunological experiments and further characterized by modeling the 3D structure and protein–protein docking. This is the first study to show that V. volvacea has more than one FIP.

1. INTRODUCTION

The use of macro-fungi for medicinal applications dates back to 3000 BC, when they were used to remedy diseases particularly in traditional oriental therapies.1 Volvaria volvacea (Bull. ex Fr.) Sing, an important edible and medicinal macro-fungus, is ranked third worldwide in terms of production, and its commercial importance continues to increase owing to its flavor, texture, and nutritional attributes.2 Furthermore, several secondary metabolites, including polysaccharides, glycopeptides

complexes,

proteoglycans,

proteins,

and

triterpenoids,

with

immunomodulatory and/or antitumor activity, have been isolated from the fungus.3 Studies of its physiological functions and their underlying molecular mechanisms


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have primarily concentrated on polysaccharides and triterpenoids, rather than the fungal proteins which have increase interests due to their pharmaceutical potential.4, 5 However, the structure and molecular weight of polysaccharides are highly diversified and complicated, thus it is difficult to be produced on the same quality and to be purified. In contrast, along with the development of biopharmaceutical technology, a large number of proteins and peptides with interesting biological activities, such as lectins, fungal immunomodulatory proteins (FIPs), ribosome inactivating proteins (RIPs), antimicrobial/antifungal proteins, ribonucleases and laccases,5 can be isolated and purified from mushrooms used in traditional Chinese medicines, and can be stably expressed in vitro. And these mushroom proteins and peptides show greater diverse activites.6 Therefore, comparative studies involving whole genome scanning comprise one strategy for the identification of unique functional proteins in V. volvacea.

Adcanced sequencing technologies have enabled the determination of the genome sequences of different edible mushroom species. The draft genomes of V. volvacea and other important mushrooms are now available in the Joint Genome Institute (JGI) databases.7 These genome sequences can be used to mine special functional genes and will influences fundamental research strategies for these species. The publication of the complete genome sequence of V. volvacea has provided insight into multiple problems that have restricted the development of the V. volvacea industry.8 However, the functional properties and applications of many V. volvacea proteins are still unknown.



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Proteins contain functional units known as domains, and various combinations of domains result in different protein formations.9 Therefore, protein domain identification is essential to gain insights into their functions. Genomic domain analysis and comparative analyses of the structures of protein domain families will enable the identification of species-specific genomic features and the mining of related genes.

In this study, we performed a comparative genome-wide protein family analysis of V. volvacea and 4 additional mushroom species (Agaricus bisporus, Coprinopsis cinerea, Pleurotus ostreatus, and Schizophyllum commune), which show some similarities, but do not share the therapeutic effects of V. volvacea, and examined the similarities and differences between the genomes of these species. In particular, we identified 7 unique proteins with immunomodulatory activity in V. volvacea, one of them is the known Fip-vvo, and the other 6 proteins are entirely new FIPs. The physiological and biochemical characteristic of 7 FIPs had been bioinformatically analyzed,

and

infer

that

a

novel

FIP

(Fip-vvo82)

could

have

higher

immunomodulatory activity. Subsequently, the coding sequences of 7 FIPs in V. volvacea were cloned into a bacterial expression vector for recombinant protein production in Escherichia coli and immunological experiment assay. Finally, the molecular mechanism of the outstanding immunomodulatory activity of Fip-vvo82 has been explored by modeling 3D structure and employing protein-protein docking. This study developed an efficient strategy for the identification of novel proteins


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related to V. volvacea traits, and would be helpful for future engineering of the structure in order to further improve the medicinal activity of FIPs and its homologs.

2. EXPERIMENTAL SECTION

2.1. Data sources and materials

The complete genome of V. volvacea has been sequenced, annotated, analyzed, and uploaded to the JGI website (http://genome.jgi.doe.gov/Volvo1/Volvo1.home.html) by our laboratory.8 The complete genome sequence and annotation data for A. bisporus,10 C. cinerea,11 P. ostreatus,12 and S. commune13 were downloaded from the JGI database. The amino acid sequence of Fip-vvo was described previously.14 V. volvacea strain V23 was provided by the Institute of Edible Fungi, Shanghai Academy of Agricultural Sciences, and maintained in our laboratory.

2.2. Protein family analysis of genome-wide protein sets

For functional annotation and to investigate protein families in whole genome scans of V. volvacea, A. bisporus, C. cinerea, P. ostreatus, and S. commune, proteins were searched against known the protein families in Pfam database. The multiple sequence alignments of each family was turned into a position-specific scoring system for searching homologous sequences in Pfam by the profile hidden Markov models (HMMs),15 which is a high-quality standard pair-wise comparison methods for large-scale sequence analysis.16 The genome-wide protein dataset was submitted to



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the Pfam server to predict protein families, motifs, repeats, and clans using the default Pfam parameters (http://pfam.sanger.ac.uk/).

2.3. Bioinformatics analysis

Primary structure analyses of V. volvacea FIPs were performed using the Protparam and ProtScale17 web servers to confirm the sequences properties, including the molecular weight, theoretical isoelectric point (pI), amino acid residue composition, total number of negatively or positively charged residues, half-life, and hydrophobicity.

The prediction of the presence and location of signal peptide cleavage sites in V. volvacea FIPs was detected by SignalP 4.118 based on a combination of several artificial neural networks. And the TMHMM19 online software tool based on the HMMs was used to predict transmembrane structures. Additionally, WoLF PSORT20 applying a feature selection algorithm was used to predict the subcellular localization of the proteins, and TargetP21,

22

was used for verification and analysis. The

MEGA5.023 package was used to construct phylogenetic trees, using the neighbor-joining method.

2.4. Protein expression and identification

The core cDNA sequences encoding the FIPs retrieved from the V. volvacea genome were synthesized by Sangon Biotech (Shanghai, China). The synthesized products were cloned into the pUC57 vector and transferred into E. coli DH5α cells


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using a standard protocol. Plasmid DNA in positive clones was digested by the NdeІ and EcoRІ enzymes at 37°C for 2 h. The digested products encoding the FIPs of V. volvacea were sub-cloned into the pET28b(+) vector, which contained a His-6 tag. The recombinant proteins were expressed in E. coli BL21 (DE3) pLysS cells (Promega, Madison, WI, USA) and were designated pET28b-FIP-vvos. The pET28b (+) vector without the targeted product was transferred into E. coli BL21 (DE3) pLysS cells as a negative control and was named pET-0. The bacteria were cultured in Luria-Bertani liquid medium to an optical density at 600nm (OD600) of 0.3 at 37°C, and induced with 1 mM IPTG at 25°C for 4h with shaking. The bacterial cells were then harvested and disrupted by ultrasonication. The soluble fraction was separated by centrifugation at 15,000 rpm for 30 min at 4°C. The liquid supernatant proteins were examined by 15% sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and stained with Coomassie Brilliant Blue R-250. Protein concentration was determined using the BCA Protein Assay Kit with bovine serum albumin as a standard.

2.5. IL-2 release assay

IL-2 production was measured as an indicator of the immunomodulatory activity of FIPs in V. volvacea using Jurkat T-cells.24 The human T-cell line Jurkat E6-1 (American Type Culture Collection, Manassas, VA, USA) was grown under standard conditions in RPMI 1640 medium (Gibco, Grand Island, NY, USA) supplemented with 10% heat-inactivated bovine calf serum (Hyclone, Logan, UT, USA),



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penicillin/streptomycin (100U/mL and 100 µg/mL, respectively, Gibco) and Glutamax (2mM, Gibco) in a 37°C and 5% CO2 humidified cell culture incubator. Jurkat T-cells (1 × 106 cells/mL, 100µL) were added to each well of a 96-well plate and were incubated with 100µL of V. volvacea FIPs (final concentration of 10 µg/mL) for 40 min at 37°C in a 5% CO2 humidified incubator. Meanwhile, 1.5µg/mL phytohemagglutinin (PHA) and total protein derived from pET-28(b), i. e. pET-0, were used as the positive and negative controls. After incubation at 37°C and 5% CO2 for 48 h, the culture supernatant was collected by centrifugation at 1000 ×g for 5 min. The amount of IL-2 in the supernatant was detected using the ELISA Kit for Mouse IL-2 (USCN Life Science, Inc., Wuhan, China). Colorimetric absorbance was measured at 450 nm on a Bio-Rad 3550 Micro-plate Reader (Hercules, CA, USA).

2.6. Homology modeling of V. volvacea FIPs

Homology modeling of the FIPs of V. volvacea was performed using the MODELLER, a program for comparative protein modeling by satisfaction of spatial restraints, with the crystal structure of LZ-8 (PDBID: 3F3H) as a template generated with highest similarity percentage. Ten models were produced and ranked by the discrete optimized potential energy score and the value of the modeler objective function. The best one was selected and optimized by a 1000 steps energy minimization with the steepest descents method. The three-dimensional (3D) structures of V. volvacea FIPs were evaluated using PROCHECK25 and the QMEAN26 servers.


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2.7. Protein–protein docking and refinement of docked proteins ZDOCK,27 a rigid body protein-protein docking algorithm was used to perform docking and to construct the FIP dimers of V. volvacea. ZDOCK uses a pair-wise statistical potential and optimized Fast Fourier Transform (FFT) algorithm to search possible binding positions of the two proteins in translational spaces. The angular step size for rotational sampling of ligand orientations was set to 6°, which can be used to perform fine-scale conformational sampling and typically results in highly accurate predictions.28 The top 2000 poses were retained for evaluation using the ZRANK29 scoring function. The ZRANK score is the energy of the docked posed calculated using the ZRANK rescoring method. The remaining poses were then processed using a clustering method. RDOCK, an algorithm for refining docked complexes using CHARMm-based minimization, was used to optimize and re-rank the docking poses to identify near-native structures.30 The docked poses were typed with the CHARMm Polar H force field in advance. Default parameters were used.

2.8. Electrostatic and charge calculations

The electrostatic properties of the FIP homo-dimers in V. volvacea were calculated using DelPhi,31 which is a collection of programs that use the Brook haven database format coordinate files as inputs to calculate electrostatic potential in and around the molecules, using finite differences in solutions to the non-linear Poisson-Boltzmann equation for any given ionic strength, solvent, and molecule dielectrics. The mean



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potential of each surface residue was calculated using default parameters. Additional image renderings were prepared using VMD.32

3. RESULTS

3.1 Pfam analysis of five edible mushroom protein sequences

Pfam, generates higher-level groupings of related families, known as clans. However, some proteins have domain family information but are not assigned to clans. We used Pfam multiple alignments to survey the predicted proteins in the 5 complete genomes (V. volvacea, A. bisporus, C. cinerea, P. ostreatus, and S. commune), and found that 9084, 7809, 9524, 9536, and 9927 Pfam families were divided into 2970, 2135, 3043, 3063, and 3088 categories, respectively, for each genome. As shown in Figure 1, S. commune proteins belonged to more families and clans than proteins encoded other mushroom genomes, while the opposite result was observed for proteins from A. bisporus. This was likely because the S. commune genome encoded the most predicted proteins (14,652), while the A. bisporus genome encoded the fewest (10,438). However, the number of categories represented by the Pfam families was not proportional to the number of predicted proteins. For example, the numbers of categories assigned to Pfam families in the V. volvacea, C. cinerea, P. ostreatus, and S. commune genomes were very similar. We observed a high variety of Pfam families for proteins encoded by the V. volvacea genome despite relatively few families.


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Figure 1.Comparison of Pfam results among V. volvacea, A. bisporus, C. cinerea, P. ostreatus, and S. commune protein sequences. CL0, No clan, Family, Category and Protein denote the clans, domain families without clans, total domain families, categories of domain family and all expressed proteins, respectively.

To identify proteins related to V. volvacea characteristics, we further compared the Pfam families represented in the five mushroom genomes. As shown in Figure 2, the five genomes shared very similar Pfam family categories, and the proportions of categories that were shared among genomes relative to the total number of categories were 63.4%(V. volvacea), 88.1%(A. bisporus), 61.8%(C. cinerea), 61.4% (P. ostreatus), and 60.9% (S. commune). We observed 789 Pfam categories for proteins in V. volvacea, C. cinerea, P. ostreatus, and S. commune. The V. volvacea protenme-wide protein set contained 29 unique Pfam family categories including 42 proteins (Figure 2). These unique protein domain families provide insights into the physiological characteristics or particular functions of V. volvacea.



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We detected a unique Pfam family (PF09259.6) that was involved in fruiting body specification and possessed immunomodulatory activity that may be involved in the immunoregulatory effects of V. volvacea; this family was assigned to 7 different V. volvacea proteins. These 7 proteins had the same Gene Ontology (GO) terms (GO:0030246 and GO:0002682), indicating that they function in carbohydrate binding and immune system regulation. A literature search revealed that the FIP was originally isolated and purified from V. volvacea in 1997.14 To date, FIPs have been isolated from Ganoderma lucidum,33 G. microsporum,34 G. applanatum (GenBank: AEP68179), G. japonicum (GenBank: AAX98241), G. tsugae,35 G. sinense,36 Nectria haematococca,37 Trametes versicolor,38 Flammulina velutipes,39 Postia placenta40 and V. volvacea, no found from A. bisporus, C. cinerea, P. ostreatus, and S. commune. Data from these species were consistent with our proteme-wide Pfam family results. Using the known amino acid sequence of Fip-vvo as a reference, the 7 V. volvacea protein sequences were aligned. Amino acid sequence homology was up to 100% identity between Fip-vvo and the No. 114437 protein, and 75%–95% identity in comparisons with the other 6 V. volvacea proteins. Accordingly, we found 7 V. volvacea genes that were related to the distinctive medicinal functions of V. volvacea, one of which encoded Fip-vvo, while the others encoded 6 novel FIPs designated Fip-vvo77, Fip-vvo78, Fip-vvo79, Fip-vvo80, Fip-vvo82, and Fip-vvo98.


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Figure 2.Venn diagram showing the overlap of Pfam categories among the V. volvacea, A. bisporus, C. cinerea, P. ostreatus, and S. commune proteomes, and a summary of unique Pfam protein domain families in V. volvacea. 29 unique Pfam family categories were contained in V. volvacea genomes, and one of Pfam family categories was Fve including 7 domains in 7 different V. volvacea proteins.

3.2 Bioinformatic prediction of 7 FIPs of V. volvacea

Each FIP of V. volvacea consisted of 113 amino acid residues, had a calculated molecular weight of approximately 13kDa, and had a pI value 6.06–8.83. The physicochemical characteristics of the 7 FIPs were presented in Supplemental Table S1. The characteristics of Fip-vvo82 differed from those of the 7 other V. volvacea FIPs, showing the highest instability index (II 20.77), the lowest aliphatic index



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(80.18), and high valine and lysine richness. As shown in Figure 3, the hydrophobicity/hydrophilicity range was -3 to +3 indicating the 7 FIPs were very similar with respect to hydrophobicity, but a clear hydrophilicity region was located between amino acids 79 and 90 of Fip-vvo82, which included 1 α-helix, 1 β-sheet, and 2 loops.

Figure 3.Hydrophilicity profile of 7 FIPs of V. volvacea. Every amino acid residue of the 7 FIPs in V. volvacea had a hydrophobicity/hydrophilicity score which was ranged from -3 to +3. Positive scores denote hydrophobic and negative scores denote hydrophilic.

The combined use of the neural network method and HMMs enabled the prediction of signal peptides and splice sites. Each amino acid corresponds to an S value, which is trained to distinguish the signal peptide position. The D value, a weighted average of the mean S, is used to discriminate signal peptides from non-signal peptides at a cutoff of 0.45. As shown in Figure 4, the S-score values of amino acid residues 1–21


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of Fip-vvo82 were higher than those of the other 6 FIPs. Only the D value of Fip-vvo82 (0.482) was higher than 0.45, suggesting that Fip-vvo82 has the strongest signal peptide and is likely secreted to the extracellular space. In a phylogenetic tree of available FIP sequences, the FIPs from V. volvacea formed a highly supported lineage, and Fip-vvo82 formed a unique, separate lineage, indicating substantial phylogenetic divergence between this protein and the other FIPs from V. volvacea (Figure 5). Based on an analysis of physicochemical properties, we observed that Fip-vvo82 may have higher immunomodulatory activity than the other FIPs of V. volvacea.

Figure 4.Signal peptide prediction for FIPs of V. volvacea. The S-score can be interpreted as an estimate of the probability of the position belonging to the signal peptide. The S-score values of the amino acid residues 1–21 of Fip-vvo82 fluctuated and had an abrupt change from a high to low value at residue 22 and the D value of



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Fip-vvo82 =0.482, suggesting the Fip-vvo82 may have a typical signal peptide. The dotted red line is the threshold value.

Figure 5.Phylogenetic tree based on protein sequences indicating the relationship between members of the fungal immunomodulatory protein family. The numbers at the nodes indicate bootstrap support values. The scale bar represents 0.05 substitutions per site


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3.3 Heterologous expression and identification of rFIPs of V. volvacea

The genes encoding FIP of V. volvacea were synthesized and expressed in E. coli as a His-fusion protein. The molecular weights of the 7 FIPs of V. volvacea based on Tris-glycine SDS-PAGE were approximately 13kDa, which is consistent with the theoretical molecular weight (Figure 6). The in vitro immunomodulatory activity of recombinant FIPs (rFIPs) of V. volvacea was investigated by examining IL-2 release from the human T-cell line Jurkat E6-1. The human T-cell line was cultured with various rFIPs of V. volvacea for 48h and IL-2 levels were measured. As shown in Figure 7, the level of IL-2 induced by Fip-vvo82 was 296.64pg/mL, which was close to the IL-2 concentrations using the positive control PHA (315.07pg/mL). It has been reported that rFip-gts or rFip-fve(10 µg/mL each) purified from E. coli can induce IL-2 production at concentrations of 412.8 or 165.3 pg/mL, respectively.41, 42 Thus, the immunomodulatory activity of rFip-vv82 is very strong and is similar to that of rFip-gts.



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Figure 6.Tris-glycine SDS-PAGE analysis of Fip-vvo and Fip-vvo82. pET28(b) was used as the negative control.


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Figure 7.IL-2 release assay of V. volvacea FIPs. The human T-cell line Jurkat E6-1was incubated with various FIPs of V. volvacea (10µg/mL). pET-0 was used as the negative control; PHA (1.5µg/mL) served as the positive control. Each bar represents the mean ± SD (n = 3). There existed significant difference among all groups (p < 0.001).

3.4 Molecular mechanism of the strong immunomodulatory activity of rFip-vvo82

Among the 10 models generated by the MODELER program, the 3D structures of FIPs from V. volvacea with the lowest probability density function for total energy



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were predicted using the crystalline structure of a FIP from G. lucidum (PDB ID:3F3H) as a template and were further refined by energy minimization. These predicted 3D structures of FIPs from V. volvacea had an accuracy of more than 90%. The quality of the refined 3D structures of V. volvacea FIPs was assessed by a Ramachandran plot using PROCHECK (Figure S1) and verified based on QMEAN score (Table S2). Overall, the Ramachandran plot and QMEAN-score analysis indicated that the backbone conformation and non-bonded atomic interactions of our refined homology models for the FIPs of V. volvacea were both well within the acceptable range.

As shown in Figure 8, our refined Fip-vvo monomer model, which was similar with the other FIP crystal structures, has the fibronectin III (FNIII) fold and N-terminal connected region. The FNIII fold is a transition between the seven β-stranded s-type and the eight β-stranded h-type topologies. The N-terminal connected region includes an α-helix and a loop near the N-terminus of the protein. These two sub-structures form a hook-like structure. The FNIII fold, which has the closest similarity to the Ig-like fold of immunoglobulins (Igs),43 may be responsible for the immunity adjustment function of Fip-vvo. And Fip-vvo monomers would be attracted to each other to form dimers through the N-terminal connected regions. The main chain backbone of Fip-vvo was superimposed with those of other novel FIPs from V. volvacea, and indicated that most structures of FIPs from V. volvacea coincided, except for Fip-vvo82, which has a relatively high RMSD value.


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Figure 8.Homology model of the Fip-vvo monomer and superimpose of Fip-vvo monomer and crystal structures of FIP isolated from F. velutipes (PDB ID:1OSY), G. lucidum (PDB ID:3F3H), and G. microsporum (PDB ID:3KCW). The 4 3D structures were colored by red, green, blue and yellow, respectively. Dimerization is very critical for the activity of FIPs.35 The level of difficulty in producing a homo-dimer can be used as an indicator of immunomodulatory activity. Docking between two FIP monomers in V. volvacea was investigated using the ZDOCK and RDOCK programs, which predict several protein complexes using pair-wise shape complementarity of the input protein structure and provide further refinement. Docking poses were ranked according to ZRANK and E_RDOCK (energy RDOCK) scores. To predict the best docking pose, the ‘E_RDOCK score’ is



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often preferred over the ZRANK score.30 A more negative E_RDOCK score indicates a stronger protein–protein interaction. The known binding motifs of Fip-fve dimer were used to ensure the accuracy of the docking data. After refinement of each FIP in V. volvacea, 100 poses were retained for further consideration, and E_RDOCK scores were used to rank the remaining poses. The top 10 poses were subjected to visual analysis, and best pose was selected from these through having the lowest E_RDOCK score and was similar to the known Fip-fve structure since the Root Mean Square Deviations (RMSD) between their binding locations was not exceed 0.24 nm. The results obtained from docking studies involving 7 FIP dimers from V. volvacea are presented in Table 1. Analysis of the top poses of 7 FIPs from V. volvacea docking outcomes suggested that the dimer of Fip-vvo82 is more stable than those of other FIP dimers from V. volvacea because it showed the highest number of hydrogen bonds. The two extra hydrogen bonds of the Fip-vvo82 dimer, shown in Supplemental Figure S2, were identified between atoms in the Thr6 (A chain)-Lys48 (B chain) and Lys18 (A chain)-Asp22 (B chain). In addition, the best pose of Fip-vvo82 dimer showed the lowest E_RDOCK (-51.97 kcal/mol) and electrostatics energy (-20.85 kcal/mol) which plays an important role in protein–protein interactions,44,

45

especially in

forming homodimeric proteins.46

Table 1.Various energy parameters of FIP homo-dimers in V. volvacea after RDOCK refinement Vdw1a

Elec1b Vdw2c

Elec2d Sole

E_RDOCKf H- Bondg


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Fip-vvo77 -144.81 1.74

-145.50 -7.70

-34.30 -41.23

8

Fip-vvo78 -131.56 4.57

-130.92 -7.19

-33.80 -40.27

8

Fip-vvo79 -134.06 2.36

-142.90 -7.67

-35.80 -42.70

8

Fip-vvo80 -138.64 2.61

-146.21 -7.49

-35.50 -42.24

8

Fip-vvo82 -138.21 -1.15

-134.61 -20.85 -33.20 -51.97

10

Fip-vvo98 -127.26 2.23

-144.53 -6.70

-35.10 -41.13

8

Fip-vvo

-140.69 -7.30

-33.70 -40.27

8

-133.81 2.17

The RCOCK program conducts two-stage energy minimizations. aVdw1: van der Waals interactions in the first stage. bElec1: electrostatic interactions in the first stage. c Vdw2: van der Waals interactions in the second stage. dElec2: electrostatic interactions in the second stage. eSol: solvational interactions were computed after both steps of minimization. fE_RDOCK: the sum of desolvation energy and the CHARMm electrostatics energy. gH-bond: hydrogen-bonding interactions. Energy unit is kcal/mol. The electrostatic potential of a protein surface plays an important role in protein function because proteins are composed of atoms carrying partial charges.47 In our study, DelPhi, a common software package, was used to calculate the spatial distribution of electrostatic potential and the potential around 7 FIP homo-dimer models from V. volvacea obtained from protein–protein docking. Very similar electrostatic potential were observed for Fip-vvo77, Fip-vvo78, Fip-vvo79, Fip-vvo80, Fip-vvo98, and Fip-vvo, but an obvious difference was detected in the electrostatic potentials of Fip-vvo82 (Figure 9). As shown in Figure 10, the calculated electrostatic potentials at the homologous monomer binding site suggested better compatibility between the highly positively charged interface of the A-chain N-terminal and the more negatively charged interface of Fip-vvo82 B-chain than the other mildly positively charged interfaces of the Fip-vvo77, Fip-vvo78, Fip-vvo79, Fip-vvo80, Fip-vvo98, and Fip-vvo B-chain.



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Figure 9.Comparison of Delphi electrostatic potential calculation for Fip-vvo82, Fip-vvo77, Fip-vvo78, Fip-vvo79, Fip-vvo80, Fip-vvo and Fip-vvo98. Two mutant sites N47D and Q51E in Fip-vvo82 were marked. 1kT/e = 0.592 kcal/mol.


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Figure 10.Comparison of electrostatic potential on the interface of the Fip-vvo77 dimer (A) and Fip-vvo82 dimer (B). The electrostatic scale ranges from -1 (red) to 1 (blue) kT/e. In Fip-vvo77 dimer (A), the calculated electrostatic potential for binding site residues are Thr6 = 37.99 kT/e, Thr12 = 0.59 kT/e, Leu16 = 0.92 kT/e, Asn47 = 1.2 kT/e, Lys48 = 16.48 kT/e, Tyr50 = -0.58 kT/e, Val98 = 0.81 kT/e, and in



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Fip-vvo82 dimer (B), Thr6 = 39.61 kT/e, Leu12 = -0.01 kT/e, Leu16 = 0.09 kT/e, Asp47 = -34.03 kT/e, Lys48 = 12.74 kT/e, Tyr50 = -8.41 kT/e, Val98 = -1.13 kT/e.

Alignment of the amino acid sequence of Fip-vvo82 with the sequence of Fip-vvo77 revealed that there were 28 position's mutations. 6 mutations (L8I, T12L, W14F, N20S, T46S and N47D) in Fip-vvo82 were at the interface between two monomers, and the other mutations were far away from the binding site. As shown in Figure 11A, mutations L8I, T12L, W14F and N20S were located in the N-terminal α-helix and loop. And the mutations T46S and N47D were located on the surface which interacted with the positively charged N-terminal α-helix. In order to evaluate the energetic effect of these 6 mutations on forming homo-dimer, we performed virtual alanine mutation of these 6 key residues, optimized these models and then calculated the affinity between two mutated monomers by ZDOCK and RDOCK (Table 2). By comparing the E_RDOCK score before and after mutation, found that the alanine mutation of Leu12 (-48.11 kcal/mol), Phe14 (-44.53 kcal/mol) and Asp47 (-46.78 kcal/mol) dramatically affect the stability of Fip-vvo82 homo-dimer, but the other 3 mutations have no obvious influence. The alanine mutation of Leu12 and Phe14 reduced the solvational interactions, and the alanine mutation of Asp47 mainly reduced the electrostatic interactions between tow monomers. Further electrostatic potential analysis suggested the acidic Asp47 in Fip-vvo82 form a negatively charged surface. As shown in Figure 11B, the alanine mutation of Asp47 altered the electrostatic surface potential of the monomer interaction binding site, allowing for a decreased negative charge that may reduce interactions with the positively charged


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N-terminal group. In addition, the immunomodulatory activity assay of D47N and D47A mutant of Fip-vvo82 demonstrated the reliability of the simulation results (Figure 12)

Figure 11.The mutational loci in Fip-vvo82 monomer interface (A) and the effects of residue Asp47 on electrostatic surface potential of the Fip-vvo82 monomer interaction binding site (B). The electrostatic scale ranges from -1 (red) to 1 (blue) kT/e. (A) Mutations L8I, T12L and W14F were colored as blue, N20S was colored as orange, and T46S and N47D were colored as red. (B) The left one shows the electrostatic surface potential of the Fip-vvo82, and the right one shows the electrostatic surface potential of the Fip-vvo82, in which the Asp47 is mutated to alanine.



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Table 2.Various energy parameters of 6 mutated Fip-vvo82 homo-dimers after RDOCK refinement Mutated site Vdw1a

Elec1b Vdw2c

Elec2d Sole

E_RDOCKf

I8A

-126.27 -1.87

-134.03 -20.30 -32.80 -51.07

L12A

-122.12 -2.06

-127.61 -20.57 -29.60 -48.11

F14A

-117.23 -1.90

-120.03 -16.48 -29.70 -44.53

S20A

-133.49 -1.56

-133.88 -19.66 -34.00 -51.69

S46A

-139.82 0.55

-141.95 -15.11 -38.10 -51.70

D47A

-142.74 1.42

-141.71 -9.42

WT

-138.21 -1.15

-134.61 -20.85 -33.20 -51.97

-38.3

-46.78

The RCOCK program conducts two-stage energy minimizations. aVdw1: van der Waals interactions in the first stage. bElec1: electrostatic interactions in the first stage. c Vdw2: van der Waals interactions in the second stage. dElec2: electrostatic interactions in the second stage. eSol: solvational interactions were computed after both steps of minimization. fE_RDOCK: the sum of desolvation energy and the CHARMm electrostatics energy. Energy unit is kcal/mol.

Figure 12. Expression clone and effect on IL-2 release of Fip-vvo82 mutants. (A) SDS-PAGE of native and mutated Fip-vvo82: pET-0 negative control (lane 1); D47N mutant (lane 2); D47A mutant (lane 3); native Fip-vvo82 (lane 4); molecular weight


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markers (lane 5). (B) IL-2 release assay of mutated Fip-vvo82 and wild type. Fip-vvo82 mutant (10 µg/mL) was used to treat human T-cell for 48 h. PHA (1.5): positive control; pET-0: negative control. Each bar represents mean ± SD (n = 3). There existed significant difference among all groups (p < 0.001).

4. DISCUSSION

In this study, to identify key genes and proteins related to the therapeutic properties of V. volvacea, we compared the protein families encoded by the full-length genomes of V. volvacea with those of other edible fungi that do not have therapeutic properties. This strategy differs from those used in previous studies,37 which have identified genes and then examined their functions. Our strategy enables a more complete characterization of related genes than previous strategies. Specifically, genes encoding 7 proteins with immunomodulatory activity were identified in the V. volvacea genome based on a comparative sequence analysis, one of these proteins was a known FIP isolated from the V. volvacea fruiting body, Fip-vvo, and the other 6 proteins were new FIPs. These results were surprising because it has previously been thought that only one FIP exists in V. volvacea.

FIPs constitute a recently established family of proteins that exhibit a range of immunomodulatory activities including mediating the effects of hemagglutinin on red blood cells, stimulating lymphocyte proliferation, cell cycle regulation, cancer cell growth inhibition, and selective enhancement of cytokine mRNA expression.48 FIPs



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consist of approximately 110 amino acids, have molecular weights between 12.4 to 13.0 kDa, and share high amino acid sequence homology ranging from 57% to 100% identity.49 However, despite the high levels of amino acid conservation, different FIPs have unique properties, including diverse effects on different cancer cells.50 To determine the structural basis of this functional divergence, the 3D structures of FIPs isolated from F. velutipes (PDB ID:1OSY),43 G. lucidum (PDB ID:3F3H),50 and G. microsporum (PDBID:3KCW) have been resolved and compared. All of these FIPs are non-covalently linked homo-dimers, and each monomer consists of an N-terminal α-helix followed by a FNIII fold (Figure 8).43 The FNIII modules appear to be responsible for receptor binding because this structure is typically involved in the specific recognition of partner molecules such as cell hormones, cell adhesion molecules, cytokine receptors, chaperonins, and carbohydrate binding domains.50 N-terminal α-helix interactions are thought to be the primary mechanism of dimerization, which plays an important role inimmunomodulatory activity.35 Thus, both FNIII modules and N-terminal α-helices are critical for FIP function.

Based on bioinformatics predictions, most FIPs in V. volvacea were hydrophilic, basic, stable proteins, while the sub-cellular localization and signal peptide data suggested that they are secreted without a typical signal peptide, except for Fip-vvo82 which has demonstrable flexibility and a typical signal peptide. The phylogenetic tree topology showed that the 7 FIPs from V. volvacea clustered into a main lineage, but Fip-vvo82 formed a unique and separate lineage, indicating substantial divergence between Fip-vvo82 and the other FIPs in V. volvacea. Therefore, we predict that the


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immunomodulatory activity of Fip-vvo82 is higher than that of other FIPs from V. volvacea.

Fip-vvo agglutinates rat erythrocytes, exhibits mitogenic effects on human peripheral blood lymphocytes, and induces both Th1-specific cytokines (IL-2, INF-γ, and LT) and the Th2-specific cytokine IL-4.48 Fip-vvo also prevents systemic anaphylactic reactions and significantly decreases foot-pad edema during the Arthus reaction in vivo.14 We predicted that the 6 novel FIPs from V. volvacea have similar or stronger immunomodulatory activity. We successfully expressed FIPs derived from V. volvacea in E. coli BL21 (DE3) cells; the rFIPs in soluble form showed significant bioactivity. All FIPs derived from V. volvacea enhanced the transcriptional expression of the cytokine IL-2. Notably, the ability of Fip-vvo82 to stimulate IL-2 was similar to the IL-2 stimulation for the positive control and Fip-gts, an atypical FIP from G. tsugae. This result agreed with our predictive analysis. The different activities of FIPs in V. volvacea may be explained by differences in critical amino acid residues at the monomer–monomer binding sites. Further structural comparison of FIPs from V. volvacea may provide insight into the structure–function relationship and information regarding which amino acid(s) are critical for immunomodulatory activity.

The 3D structure of FIPs in V. volvacea obtained by homology modeling showed that the proteins contained an N-terminal amphipathic α-helix, which has various reported functions, such as glucagon binding to its receptor, plasma apolipoprotein solubilization of lipids, antimicrobial peptide disintegration of bacterial cells, and



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signal peptide targeting to mitochondria.35 The N-terminal amphipathic α-helix in FIPs has signal peptide function, but it is also very important in homo-dimer formation. Therefore, this structure must be retained and should not be excised as a signal peptide. This indicates that the N-terminal α-helix is an important multi-functional domain for FIPs from V. volvacea.

FIP homo-dimer complex models of V. volvacea were developed using a protein-protein docking study. The primary forces responsible for the formation and stabilization of V. volvacea FIP homo-dimers included van der Waals interactions, electrostatic interactions, solvational interactions, and hydrogen bonding between the N-terminal connected regions. The hydrogen bonding, van der Waals energies, desolvation energies and electrostatics energies varied widely among the 7 FIP homo-dimers of V. volvacea, and were particularly distinct for Fip-vvo82 (Table 1). In the case of Fip-vvo82 homo-dimer, not only the formation of two extra H-bonds51 (Thr6-Lys48 and Lys18-Asp22) could enhance homo-dimer affinity, but also the high stability of homo-dimer mainly relies on the lowest electrostatic energy (-20.85 kcal/mol). According to the electrostatic potential comparison of 7 FIPs in V. volvacea (Figure 9), the electrostatic potential of the Asp47 and Glu51 in Fip-vvo82 are obviously different, due to their side chains have carboxylic acid groups whose pKa's are low enough to lose protons, becoming negatively charged. The Q51E doesn’t affect affinity between homologous monomers, because it is far away from monomer-monomer binding site. The N47D is located on the surface which interacted with the positively charged N-terminal α-helix, and strengthened the electromagnetic


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interactions between the negatively and positively charged surfaces of the monomer-monomer interaction-binding site.

The amino acids sequence alignment between Fip-vvo77 and Fip-vvo82 suggested there are 28 mutations in Fip-vvo82, and 6 mutations of them (L8I, T12L, W14F, N20S, T46S and N47D) are on the monomer-monomer interaction-binding site. Therefore, these 6 residues (Ile8, Leu12, Phe14, Ser20, Ser46 and Asp47) are thought to be the key residues related to the high immunomodulatory activity of Fip-vvo82. Furthermore, single point alanine mutations of above 6 key residues were performed in turn. And the comparison of the Fip-vvo82 homo-dimer stability before and after virtual alanine mutation suggests the Leu12, Phe14 and Asp47 play important role in stabilizing the Fip-vvo82 homo-dimer. As shown in Table 2, the alanine mutation of Leu12 and Phe14 can destabilize the binding through increasing the desolvation energy which was computed using the Atomic Contact Energy (ACE) algorithm.52 And the alanine mutation of Asp47 also destabilizes the binding between two homologous monomers through raising the CHARMm electrostatics energy, which is consistent with the analysis of the electrostatic potential comparison of 7 FIPs in V. volvacea. Therefore, the Asp47 is the key point to be responsible for the highest electrostatic energy effect for the affinity between two homologous monomers, and plays an important role on the high immunomodulatory activity of Fip-vvo82. Based on the theoretical calculations, the point mutation experiment was given to verify the operational and validity of the model. Expression clone of the optimal FIP mutant will be the next step of our research.



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5. CONCLUSION

V. volvacea (Bull. ex Fr.) Sing, an important edible and medicinal macro-fungus, has been used to treat many diseases for hundreds of years in East Asia. However, in contrast to its nutritional composition and organoleptic properties, the mechanisms underlying the beneficial effects of V. volvacea with respect to a wide range of ailments remain unclear. In this study, we used an efficient strategy to identify novel proteins related V. volvacea medicinal functions. First, we identified 7 FIPs of V. volvacea with the unique therapeutic activity including the previously identified Fip-vvo and 6 newly identified FIPs, by comparative analysis of amino acid sequences. The physiological and biochemical characteristics of the 7 FIPs were predicted and analyzed using several bioinformatics approaches, which suggested that Fip-vvo82, a novel FIP, has higher expected immunomodulatory activity than the other FIPs. The results of molecular and immunological experiments agreed with the computational predictions. Finally, the molecular mechanism of the outstanding immunomodulatory activity of Fip-vvo82 was determined by modeling the 3D structure and employing protein-protein docking, providing directions for the future engineering of structures that will further improve the medicinal activity of FIPs from V. volvacea and their homologs.

ASSOCIATED CONTENT Supporting Information Available: Tables S1−S2. Figure S1−S2. This material is available free of charge via the Internet at http://pubs.acs.org.


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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected].

Notes

The authors declare no competing financial interest.

ACKNOWLEDGMENT This study was supported by the Shanghai Municipal Agricultural Commission, P. R. China [Hu nong qing zi (2015) No. 1-11 and No. 1-10]; a National Natural Science Foundation of China (No. 31471925); Shanghai Agriculture Applied Technology Development

Program,

China

(Grant

No.G2015060201);

and

the

Science and Technology Development Fundation of Shanghai Academy of Agricultur al Sciences [2013(2)].

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for Table of Contents use only

Discovery and Characterization of the Highly Active Fungal Immunomodulatory Protein Fip-vvo82 Ying Wang†, Ying Wāng†, Yingnv Gao†, Yan Li†, Jia-Ning Wan†, Rui-Heng Yang†, Wen-Jun Mao†, Chen-Li Zhou†, Li-Hua Tang†, Ming Gong†, Ying-Ying Wu† and Da-Peng Bao*†


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Figure 1.Comparison of Pfam results among V. volvacea, A. bisporus, C. cinerea, P. ostreatus, and S. commune protein sequences. CL0, No clan, Family, Category and Protein denote the clans, domain families without clans, total domain families, categories of domain family and all expressed proteins, respectively. 203x110mm (300 x 300 DPI)



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Figure 2.Venn diagram showing the overlap of Pfam categories among the V. volvacea, A. bisporus, C. cinerea, P. ostreatus, and S. commune proteomes, and a summary of unique Pfam protein domain families in V. volvacea. 29 unique Pfam family categories were contained in V. volvacea genomes, and one of Pfam family categories was Fve including 7 domains in 7 different V. volvacea proteins. 203x150mm (300 x 300 DPI)


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Figure 3.Hydrophilicity profile of 7 FIPs of V. volvacea. Every amino acid residue of the 7 FIPs in V. volvacea had a hydrophobicity/hydrophilicity score which was ranged from -3 to +3. Positive scores denote hydrophobic and negative scores denote hydrophilic. 203x106mm (300 x 300 DPI)



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Figure 4.Signal peptide prediction for FIPs of V. volvacea. The S-score can be interpreted as an estimate of the probability of the position belonging to the signal peptide. The S-score values of the amino acid residues 1–21 of Fip-vvo82 fluctuated and had an abrupt change from a high to low value at residue 22 and the D value of Fip-vvo82 =0.482, suggesting the Fip-vvo82 may have a typical signal peptide. The dotted red line is the threshold value. 203x125mm (300 x 300 DPI)


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Figure 5.Phylogenetic tree based on protein sequences indicating the relationship between members of the fungal immunomodulatory protein family. The numbers at the nodes indicate bootstrap support values. The scale bar represents 0.05 substitutions per site 203x230mm (300 x 300 DPI)



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Figure 6.Tris-glycine SDS-PAGE analysis of Fip-vvo and Fip-vvo82. pET28(b) was used as the negative control. 203x261mm (300 x 300 DPI)


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Figure 7.IL-2 release assay of V. volvacea FIPs. The human T-cell line Jurkat E6-1was incubated with various FIPs of V. volvacea (10µg/mL). pET-0 was used as the negative control; PHA (1.5µg/mL) served as the positive control. Each bar represents the mean ± SD (n = 3). There existed significant difference among all groups (p < 0.001). 203x179mm (300 x 300 DPI)



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Figure 8.Homology model of the Fip-vvo monomer and superimpose of Fip-vvo monomer and crystal structures of FIP isolated from F. velutipes (PDB ID:1OSY), G. lucidum (PDB ID:3F3H), and G. microsporum (PDB ID:3KCW). The 4 3D structures were colored by red, green, blue and yellow, respectively. 203x148mm (300 x 300 DPI)


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Figure 9.Comparison of Delphi electrostatic potential calculation for Fip-vvo82, Fip-vvo77, Fip-vvo78, Fipvvo79, Fip-vvo80, Fip-vvo and Fip-vvo98. Two mutant sites N47D and Q51E in Fip-vvo82 were marked. 1kT/e = 0.592 kcal/mol. 203x103mm (300 x 300 DPI)



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Figure 10.Comparison of electrostatic potential on the interface of the Fip-vvo77 dimer (A) and Fip-vvo82 dimer (B). The electrostatic scale ranges from -1 (red) to 1 (blue) kT/e. In Fip-vvo77 dimer (A), the calculated electrostatic potential for binding site residues are Thr6 = 37.99 kT/e, Thr12 = 0.59 kT/e, Leu16 = 0.92 kT/e, Asn47 = 1.2 kT/e, Lys48 = 16.48 kT/e, Tyr50 = -0.58 kT/e, Val98 = 0.81 kT/e, and in Fipvvo82 dimer (B), Thr6 = 39.61 kT/e, Leu12 = -0.01 kT/e, Leu16 = 0.09 kT/e, Asp47 = -34.03 kT/e, Lys48 = 12.74 kT/e, Tyr50 = -8.41 kT/e, Val98 = -1.13 kT/e. 203x257mm (300 x 300 DPI)


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Figure 11.The mutational loci in Fip-vvo82 monomer interface (A) and the effects of residue Asp47 on electrostatic surface potential of the Fip-vvo82 monomer interaction binding site (B). The electrostatic scale ranges from -1 (red) to 1 (blue) kT/e. (A) Mutations L8I, T12L and W14F were colored as blue, N20S was colored as orange, and T46S and N47D were colored as red. (B) The left one shows the electrostatic surface potential of the Fip-vvo82, and the right one shows the electrostatic surface potential of the Fip-vvo82, in which the Asp47 is mutated to alanine. 203x156mm (300 x 300 DPI)



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Figure 12. Expression clone and effect on IL-2 release of Fip-vvo82 mutants. (A) SDS-PAGE of native and mutated Fip-vvo82: pET-0 negative control (lane 1); D47N mutant (lane 2); D47A mutant (lane 3); native Fip-vvo82 (lane 4); molecular weight markers (lane 5). (B) IL-2 release assay of mutated Fip-vvo82 and wild type. Fip-vvo82 mutant (10 µg/mL) was used to treat human T-cell for 48 h. PHA (1.5): positive control; pET-0: negative control. Each bar represents mean ± SD (n = 3). There existed significant difference among all groups (p < 0.001). 203x104mm (300 x 300 DPI)


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Table of Contents 203x120mm (300 x 300 DPI)


Discovery and Characterization of the Highly Active Fungal

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