**Keywords:** corn gluten meal; glutamine; ulcerative colitis

#### **1. Introduction**

Inflammatory bowel disease (IBD) mainly includes ulcerative colitis (UC) and Crohn's disease (CD), and it is a complex disease of the digestive system characterized by repeated chronic intestinal inflammation, intestinal epithelial dysfunction, and mucosal tissue damage in the gastrointestinal tract [1]. Epidemiology shows that in recent years, the prevalence of UC has been on the rise worldwide [2,3]. Multiple causes of UC have been identified, and its consequences usually include the impaired structure and function of the intestinal mucosa [4]. At present, the main drugs for the treatment of UC include salicylazosulfapyridine, immunosuppressants, and an anti-tumor necrosis factor-α monoclonal antibody. Unfortunately, the long-term use of these drugs can cause serious side effects and are expensive, which severely limits their use [5,6]. Hence, safer and more efficient naturally active substances for the treatment of UC are urgently needed.

Glutamine (Gln) is one of the most abundant amino acids in the human body and has many physiological functions, such as enhancing the immune capacity of the body and protecting the intestinal barrier function [7,8]. However, the application of Gln is limited due to its unstable monomer, easy decomposition, and low solubility. A few studies have found that glutamine peptide not only retains a variety of physiological functions

**Citation:** Jing, Y.; Liu, X.; Wang, J.; Ma, Y.; Zheng, X. Production of Corn Protein Hydrolysate with Glutamine-Rich Peptides and Its Antagonistic Function in Ulcerative Colitis In Vivo. *Foods* **2022**, *11*, 3359. https://doi.org/10.3390/ foods11213359

Academic Editors: Fuping Lu and Wenjie Sui

Received: 17 September 2022 Accepted: 24 October 2022 Published: 25 October 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

and nutrition of Gln, but also has good water solubility and stability, which is a stable substitute for Gln. Researchers have also found that glutamine peptide has antioxidant activity, promotes protein synthesis, and protects human intestinal health function. Under stress conditions such as fatigue, intense exercise, and disease, glutamine peptides can be rapidly decomposed into glutamine to meet the needs of the body. For example, Juan Tian et al. reported that alanine–glutamine could attenuate soya saponin-induced growth inhibition and intestinal injury in zebrafish [9]. Bie Tan et al. found that alanine–glutamine could replace glutamine as a source of energy and protein in the gastrointestinal tract [10]. Therefore, the development of bioactive peptides rich in Gln can effectively solve the problem of the limited application of Gln.

Corn is one of the three major cereals in the world, and China's yield of corn reached 272.55 million tons in 2021. Nearly one-sixth of corn is used to produce corn starch using the wet milling process. It generates a large amount of corn gluten meal (CGM) as a main co-product, which contains about 67–72% (*w/w*) protein [11,12]. These proteins mainly include zein and gluten; the content of Gln is about one-third of the total amino acids in gluten [13,14] and is an excellent raw material for preparing glutamine active peptides. Therefore, corn protein hydrolysate with glutamine-rich peptides (APH) was first prepared from the hydrolysis of CGM by proteases in the present study, and then its antagonistic effect on DSS-induced UC in vivo was systematically evaluated.

#### **2. Materials and Methods**

#### *2.1. Materials*

CGM was purchased from Longjiang Fufeng Biotechnology Co., Ltd. (Qiqihar, China). The proteases Alcalase and Protamex were purchased from Novo Nordisk (Bagsvaerd, Denmark). DSS (36–50 kDa) was purchased from Macklin (Shanghai, China). All of the other reagents and chemicals were of analytical grade.

#### *2.2. Preparation of CGM Hydrolysates*

The CGM was pretreated using the method described in our previous report [15,16]. Pretreated CGM (20 g) was added to 200 mL of distilled water, and then Alcalase and Protamex were added successively for hydrolysis. The optimum hydrolysis conditions for Alcalase were a temperature of 64 ◦C, hydrolysis time of 2.5 h, amount of enzyme of 1300 U/g, and a pH of 8.0. The optimum hydrolysis conditions for Protamex were a temperature of 50 ◦C, hydrolysis time of 2.5 h, amount of enzyme of 200 U/g, and a pH of 7.0. For the sequential hydrolysis of the two proteases, first of all, the CGM was hydrolyzed with one protease (Alcalase or Protamex), and then the second protease was added after adjusting the reaction conditions. After the reaction, the hydrolysates were centrifuged at 4500 rpm for 15 min to collect the supernatant and were lyophilized.

#### *2.3. Determination of Gln Content in Hydrolysates*

The Gln content of the corn protein hydrolysate was determined by Katharina's method [17]. Briefly, 500 μL corn protein hydrolysate (100 mg/mL) was transferred into an ampoule (Hawk, Harbin, China), and then 2 mL bis-1,1-trifluoroacetoxy-iodobenz-ene (BTI) acetonitrile-aqueous solution (10 mg/mL) and 500 μL pyridine (50 μmol/mL) were added into the ampoule. The reaction was carried out at 50 ◦C for 2 h to protect the Gln in the hydrolysate, and the other hydrolysate sample was not subjected to BTI protection reaction. Then, 5 mL HCl (6 mol/L) was added to the two ampoules for acid hydrolysis, and the ampoules were sealed in a vacuum and hydrolyzed at 110 ◦C for 24 h. After cooling, the pH of the hydrolysate was adjusted to 6–8 with NaOH, and the glutamic acid content was determined using a glutamate biosensor analyzer; the difference in the glutamic acid between the two samples was the content of Gln.

#### *2.4. Animals and Experimental Design*

Male Kunming mice (6–8 weeks) were provided by the Laboratory Animal Technology of Changchun Yisi (Changchun, Jilin, China, Permission No. SCXK (JI) 2020-0002). The animal study protocol was approved on 25 March 2021 by the Animal Ethics Committee of College of Food and Bioengineering, Qiqihar University (Approval No. 2021-003). The care and treatment of the mice were in accordance with international guidelines for laboratory animals (Association for Assessment and Accreditation of Laboratory Animal Care, AAALAC). Before the experiment, all animals were fed and watered freely for one week, and the room temperature was maintained at 23 ± 3 ◦C. Then, the mice were randomly divided into five groups (*n* = 10). All mice were fed a normal diet during the experiment, and dextran sulfate sodium (DSS) was used as an inducer to establish the colitis model. In GroupI (control group), the mice received drinking water; in GroupII (DSS model group), the mice received drinking water for the first 7 days, and drinking water containing 3% DSS for the next 7 days; GroupIII (APH low-dose group) received 100 mg kg−1 APH + 3% DSS; GroupIV (APH medium-dose group) received 300 mg kg−1 APH + 3% DSS; and GroupV (APH high-dose group) received 500 mg kg−1 APH + 3% DSS. During the experiment, the APH group mice were given the corresponding APH dose by gavage daily and treated with drinking water containing 3% DSS from days 8 to 14. The weight and stool changes of the mice were recorded daily, and the disease activity index (DAI) was established (Table 1) [18]. At the end of the experiment, blood was taken from the retro-orbital sinus, and the serum was obtained and centrifuged at 8000 rpm at 4 ◦C for 20 min, and stored at −80 ◦C. Then, the mice colonic samples were collected for further analysis.

**Table 1.** Disease activity index scoring system.

#### *2.5. Histopathology*

The colon specimens were fixed in 10% formalin for 24 h and embedded in paraffin. After the paraffin-embedded sections were dewaxed and stained with haematoxylin and eosin, the degree of inflammation, depth of the lesion, crypt, and epithelial damage of the colon tissue were observed under a light microscope.

#### *2.6. Determination of DAO, SOD, GSH-Px, and Inflammatory Cytokine Concentrations*

3 11–15 - - 4 >16 Diarrhea Gross bleeding

The concentrations of diamine oxidase (DAO), IL-1β, IL-6, IL-10, and TNF-α in serum were determined with mouse ELISA kits (Shanghai Jianglai Biotechnology Co., Ltd., Shanghai, China) following the manufacturer's instructions. The concentrations of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) of the colon tissue were assessed with commercial kits (Jianglai, Shanghai, China).

#### *2.7. 16S rRNA High Throughput Sequencing*

Genomic DNA was obtained from frozen fecal samples using a DNA isolation kit (Jianglai, Shanghai, China). The structural changes of the intestinal microbiota were conducted by 16S rRNA sequencing analysis. The data were analyzed on the online platform Majorbio Cloud Platform (Majorbio, Shanghai, China).

#### *2.8. Statistical Analysis*

The results were represented as mean ± standard deviation (SD). DAI was assessed with the unpaired two-tailed Student's *t*-test. Multiple comparisons were evaluated using one-way ANOVA followed by Tukey's multiple-comparison test. *p* < 0.05 was considered significant.

#### **3. Results**

#### *3.1. Preparation of APH*

The preparation of bioactive peptides by enzymatic hydrolysis is widely used due to its high safety, mild reaction conditions and easy control of the hydrolysis process. In order to obtain corn protein hydrolysate with glutamine-rich peptides, Alcalase (A) and Protamex (P) were used to hydrolyze the CGM in this study, and the effect of a different order of enzyme addition (A + P and P + A) on the Gln content in the hydrolysate was compared. The content of Gln in the hydrolysate by A + P and P + A were 12.53% and 9.99%, respectively, showing a significant difference (*p* < 0.05). The sequential hydrolysis of A + P was more conducive to the release of glutamine peptides from CGM than P + A. Thus, the sequential hydrolysis of CGM by A + P was selected to prepare the APH.

#### *3.2. APH Alleviates Colitis Symptoms in Mice*

It is well known that the rate of change in body weight and DAI score are the main evaluation indexes of UC. The body weight change rate of all groups of mice before DSS treatment was low, and their activity status was normal (Figure 1A,B). DSS treatment was started on the eighth day: the activity of the mice decreased and the DAI score increased gradually with the increase of treatment time in the model group.  According to the above phenomena, the model could be considered successful. Compared with the DSS group, the rate of change in body weight and the degree of diarrhea and bloody stools in the APH groups were significantly improved (*p* < 0.05), especially in the APH (500 mg/kg·d) group.

**Figure 1.** *Cont.*

**Figure 1.** APH ameliorates clinical signs of colitis in mice. (**A**) Changes in body weight; (**B**) DAI scores; (**C**,**D**) colon length. Data are expressed as mean ± SD (*n* = 8). Different letters indicate significant differences (*p* < 0.05).

The colon length of the animals usually shortens under inflammatory stress. The colon length was measured in each group (Figure 1C,D) and, compared to the control group, the model group's colon length significantly shortened. The length of the colon of mice in the APH groups was considerably longer than those in the model group, especially in the medium-dose APH (300 mg/kg·d) group. This indicated that APH inhibited the intestinal stress response and alleviated colitis symptoms.

#### *3.3. APH Alleviates Histopathological Changes in Mice*

A pathologic examination was conducted to observe the extent of colonic injury (Figure 2). In the control group, the colonic mucosal layer was intact, there was a neat arrangement of glands, and no inflammatory cell infiltration was observed. The DSS group showed serious damage to the colonic mucosa, including edema, loss of some glands and crypt, and the infiltration of inflammatory cells. However, in the APH groups, the degree of inflammatory cell infiltration and colonic mucosa injury were reduced, especially in the high-dose APH group, where the structure of the colonic epithelial was more complete, and the colonic tissue injury was significantly improved. The colonic tissue morphology was similar to the control group, indicating that APH can substantially reduce the damage of colon tissue, and has a specific protective effect on the colon.

**Figure 2.** *Cont.*

**Figure 2.** APH alleviates DSS-induced histopathological changes.

#### *3.4. Effects of APH on the Inflammatory Cytokines in Mice*

Inflammatory cytokines are critical signaling molecules of inflammatory response in vivo, and colitis severity is closely related to their expression levels. The contents of inflammatory cytokines in serum were detected by ELISA (Figure 3). The serum IL-10 levels of mice in the DSS group were significantly lower than the control group (*p* < 0.05) (Figure 3A). In contrast, the levels of TNF-α, IL-6, and IL-1β were increased considerably (Figure 3B–D), indicating that colon inflammation was induced in mice after DSS treatment. After treatment with different doses of APH, the contents of IL-10 in the serum increased, and the contents of TNF-α, IL-6, and IL-1β decreased. These results indicated that APH played a specific role in regulating the levels of inflammatory factors, and it further revealed that APH had a particular anti-inflammatory effect on colitis in vivo.

#### *3.5. Effects of APH on Oxidative Stress-Related Indicators in Mice*

To further evaluate the effect of APH on UC from the perspective of oxidative stress, two oxidative stress markers, GSH-Px and SOD in the colon tissue, were examined (Figure 4). The contents of GSH-Px and SOD in the model group were significantly lower than in the control group (*p* < 0.05). The levels of the two oxidative stress markers were significantly increased in a dose-dependent manner after treatment with different doses of APH, indicating that APH could improve the antioxidant capacity of mice with colitis, and had a specific regulatory effect on oxidative stress.

**Figure 3.** Effects of APH on the inflammatory cytokines, including the serum levels of IL-10 (**A**), TNF-α (**B**), IL-6 (**C**) and IL-1β (**D**). Data are expressed as mean ± SD (*n* = 8). Different letters indicate significant differences (*p* < 0.05).

**Figure 4.** Effects of APH on the oxidative stress-related indicators, including the colonic concentrations of GSH-Px (**A**) and SOD (**B**). Data are expressed as mean ± SD (*n* = 8). Different letters indicate significant differences (*p* < 0.05).

#### *3.6. Effects of APH on Intestinal Permeability in Mice*

Diamine oxidase (DAO) is an intracellular enzyme with strong activity located in the upper layer of the intestinal villi in mammals. It is also a marker enzyme of intestinal mucosal cells. When intestinal mucosal epithelial cells are damaged, the intracellular DAO releases into the intestine and blood, which increases the level of DAO in the blood, indicating the increase of intestinal permeability [19]. Therefore, the change of DAO level is closely related to the integrity and damage degree of the intestinal mucosal mechanical barrier, and can be used as a sensitive indicator to reflect the change of intestinal permeability. The serum DAO levels in the DSS group were significantly higher (*p* < 0.05) than in the control group (Figure 5), indicating that the intestinal mucosa of the mice in the model group was severely damaged and the permeability increased. After APH treatment with different doses, the serum DAO levels of the mice significantly decreased (*p* < 0.05), especially in the high-dose APH group. These results indicated that APH could reduce the damage to the intestinal mucosa, reduce the permeability of the intestinal mucosa, and exhibit a particular protective effect on the mechanical barrier of the intestinal mucosa.

**Figure 5.** Effects of APH on DAO level in serum of DSS-induced colitis mice. Data are expressed as mean ± SD (*n* = 8). Different letters indicate significant differences (*p* < 0.05).

#### *3.7. Effects of APH on Intestinal Microbiota in Mice*

The intestinal microbiota of mice were measured using 16S rRNA high-throughput sequencing. A total of 203 OTUs were shared by the five groups, and the unique OTUs of each group was 61, 6, 19, 28, and 12, respectively (Figure 6A). This indicated that DSS reduced the diversity of the intestinal microbiota in mice, and the number of OTUs increased after APH treatment with different doses. Principal coordinate analysis (PCoA) can reflect the similarity between the samples: the shorter the distance between the sample and the sample in the figure, the more similar the samples are. The control group was closely clustered (Figure 6B), and there was an obvious dividing line and a long distance with the DSS group, which indicated that DSS had a particular influence on the intestinal microbiota. After APH treatment with different concentrations, the abundance and structure of the intestinal microbiota of the mice improved. The results of alpha diversity analysis demonstrated that DSS reduced the diversity and richness of the intestinal microbiota (Figure 6C), while APH improved it.

The analysis results of intestinal microbiota abundance at the phylum level showed that the overall microbiota composition predominantly changed in the DSS group: the relative abundance of *Firmicutes*, *Actinobacteriota*, *Desulfobacterota*, and *Patescibacteria* significantly decreased, while *Bacteroidota* and *Verrucomicrobiota* increased (Figure 6D). After treatment with different concentrations of APH, the relative abundance of Firmicutes in the high-dose APH (500 mg/kg·d) group and *Actinobacteriota*, *Desulfobacterota*, and *Patescibac-* *teria* in the medium-dose APH (300 mg/kg·d) group significantly increased, while the relative abundance of *Bacteroidota* and *Verrucomicrobiota* significantly decreased.

The intestinal microbiota also changed significantly at the genus level (Figure 6E). The abundance of Lactobacillus, a family that regulates intestinal health, decreased in the DSS group. The abundance of other genera including *Desulfovibrio* and *Pediococcus* in the DSS group also decreased. After treatment with different concentrations of APH, the relative abundance of *Lactobacillus* and *Pediococcus* in the high-dose APH (500 mg/kg·d) group and *Desulfovibrio* in the medium-dose APH (300 mg/kg·d) group significantly increased, while the relative abundance of *Aerococcus* significantly decreased.

**Figure 6.** *Cont.*

**Figure 6.** Effects of APH on the intestinal microbiota in mice with DSS-induced colitis. (**A**) Venn diagrams of OTU of each group; (**B**) principal coordinate analysis (PCoA); (**C**) rarefaction curve; (**D**) microbiota analysis at the phylum level; (**E**) microbiota analysis at the genus level.

#### **4. Discussion**

As a high-quality protein raw material rich in Gln, CGM was hydrolyzed by two commercial microbial proteases to prepare APH in the present study. Alcalase is produced by the fermentation of *Bacillus licheniformis*, which is an endopeptidase with serine in its catalytic site. Protamex, produced from *Bacillus subtilis*, is also an endopeptidase with broad specificity for peptide bonds. It has been reported that Alcalase and Protamex have little effect on the hydrolysis of the amide group in Gln, and can effectively protect the Gln in the raw material [20,21]. According to the results of this study, the content of Gln in the hydrolysate prepared by the sequential hydrolysis of A + P was significantly higher than that of P + A. It is possible that the cleavage sites of the two proteases are different, and the change of enzyme addition order will lead to different hydrolysates, which will result in the difference of Gln content in the hydrolysates. During the first step of hydrolysis, Alcalase showed a more intense cleavage effect on CGM than Protamex, which resulted in a relatively high Gln content in the hydrolysate. More importantly, more sites were exposed in CGM after the hydrolysis of Alcalase, which was beneficial for Protamex to play a better role in the second step of hydrolysis. On the contrary, the cleavage site of Alcalase was preempted if the Protamex was used as the first hydrolase, which is the reason why Alcalase exhibited lower hydrolysis effects on the residual peptides after the action of Protamex, and the Gln content in the hydrolysate was lower than that of A + P. Thus, the sequential hydrolysis of CGM by A + P was more suitable for the preparation of the APH.

Intestinal mucosal barrier injury is a typical symptom experienced by UC patients, and the pathological manifestation is increased intestinal permeability. With the increase of intestinal permeability, harmful substances such as bacteria and endotoxins can enter the body and affect human health. Preventing mucosal damage or promoting the efficient regeneration of mucosal cells is one of the ways to alleviate UC. As an essential amino acid of the intestinal tract, Gln is the main energy source of the intestinal cells that contribute to enhancing the metabolism and synthesis of mucosal proteins and cells, promote the

regeneration and renewal of intestinal mucosal cells, and effectively protect the integrity of cells [22]. The corn protein hydrolysate prepared in this study was rich in Gln peptides, which significantly alleviated colonic tissue damage and reduced the intestinal permeability in mice with colitis. The effect of APH in the high-dose group was significantly better than that in the low-dose group. It could be speculated that Gln peptides, especially Gln, might play an important role in antagonizing UC. Evidence shows that under severe stress such as infection or trauma, the Gln in intestinal mucosal epithelial cells is rapidly depleted. The timely supplementation of Gln can effectively prevent intestinal mucosal atrophy [23,24]. Further investigation is required to confirm the mechanism of glutamine peptide in APH.

The infiltration of neutrophils in intestinal mucosa and epithelial cells is another feature of UC, which can impair epithelial barrier function, damage tissues, release proinflammatory factors, and increase inflammation. Studies have shown that inflammatory mediators have an important relationship with inflammatory bowel disease. The excessive production of pro-inflammatory factors will intensify the inflammatory cascade and cause colon injury, forming a vicious cycle [25]. IL-6 is a crucial mediator in UC inflammation produced by T cells and macrophages [26]. TNF-α, the earliest endogenous mediator of inflammatory processes in tumors, can promote the diffusion and differentiation of T cells, disrupting the intestinal barrier [27]. IL-1β is involved in the recruitment and retention of leucocytes in inflammatory tissues [28], while IL-10 is an anti-inflammatory factor involved in immune regulation and produced by regulatory T cells and mononuclear macrophages. IL-10 can inhibit the development of UC by downregulating inflammatory signaling and mucosal inflammation. The dynamic balance between inflammatory cytokines determines the development and outcome of inflammation. The present study found that APH reduced the inflammatory response by upregulating the content of IL-10 and downregulating the content of TNF-α, IL-1β, and IL-6, which demonstrates that APH could alleviate ulcerative colitis. The underlying regulatory mechanism may be related to Gln peptide or Gln in APH. Gln is an important fuel for the immune system: it plays a crucial part in immune regulation and can enhance the function of the immune system [29]. The proliferation and activation of immune cells can effectively regulate the synthesis and secretion of inflammatory cytokines, leading to the regulation of immune homeostasis. Furthermore, NF-κB is one of the main signaling pathways mediating the inflammatory response. It is mediated by Toll-like receptor 4 and induces intracellular signal transduction through myeloid differentiation factor 88, which activates NF-κB and leads to the increased secretion of inflammatory cytokines. It has been found that Gln supplementation can regulate the activation of NF-κB to inhibit inflammation in colitis models [30]. Mengya Zhang et al. also reached the same conclusion when studying the preserved egg-white anti-inflammatory peptides [31]. Meanwhile, the function of hydrolysate is closely related to the amino acid sequence of peptides in the hydrolysate. Peptides with anti-inflammatory activity were rich in positively-charged and hydrophobic amino acids [32]. It has been reported that one or more residues of Gln, Pro, Tyr, Trp, Cys, Ala, and Asp might contribute to the immunomodulatory activity of peptides [33]. In the present study, CGM, the raw material for the preparation of APH, contains lots of Gln and hydrophobic amino acids (Table S1). The hydrophobic amino acid content accounts for about 50% of the total amino acid content. Therefore, many peptides containing hydrophobic amino acids may be obtained after the enzymatic hydrolysis of CGM. Hence, we speculate that the antagonistic effect of APH on UC might be related to the special amino acid sequence in peptides. González-Montoya et al. reported that the anti-inflammatory peptides obtained from germinated soybean protein hydrolysates all contained Gln residue, and the identified peptides were rich in Gln, which had strong anti-inflammatory activity, such as QQQQQGGSQSQ, QEPQESQQ, QQQQQGGSQSQSQKG, and PETMQQQQQQ [34]. It further confirmed our speculation, and more research is necessary to elucidate the mechanics of Gln and hydrophobic amino acids in antagonizing UC.

The inflammatory response is closely related to oxidative stress. Oxygen radicals are the initiator of inflammatory response, which can accelerate the release of inflammatory factors and aggravate the damage of the inflammatory response [35]. Oxidative stress not only produces inflammation in the gut, but also causes tissue damage. Studies have shown that the overproduction of reactive oxygen and nitrogen, as well as their associated oxidative stress regulation, are related to UC [36]. Yuji Naito et al. reported that ROS levels in the colon samples of UC patients significantly increased and were positively correlated with IBD [37]. Two primary markers (GSH-Px and SOD) of oxidative stress were detected in our study, and the results revealed that APH increased the levels of GSH-Px and SOD. As a precursor of glutathione, Gln supplementation can effectively maintain and increase the storage of glutathione in cells and improve the body's antioxidant capacity, thereby stabilizing the cell membrane and protein structure, and maintaining the function of intestinal and immune cells. This might be a major reason why APH significantly regulates GSH-Px and SOD levels. On the other hand, corn protein hydrolysate contains lots of hydrophobic amino acids, which contribute to its antioxidant activity and may also increase anti-inflammatory activity [38]. Our previous studies have also shown that CGM hydrolysates contain substances that activate SOD and GSH-Px factors, which interact with free radicals to produce stable products [16]. Therefore, APH possibly played a positive role in relieving oxidative stress and subsequently reducing tissue damage. The imbalance between tissue oxidation and antioxidant reaction is the basis of disease progression in many cases, so APH can also be used from an antioxidant perspective to reduce the severity of UC.

The stability of intestinal microecology is the basis of intestinal health, which is directly related to the structure and function of the intestinal barrier [39]. The intestinal microbiota are a large number of microorganisms colonized in the human digestive tract, with diverse functions and complex species. Different species in the normal intestinal microbiota, as well as the intestinal microbiota and the host, are always in a state of dynamic balance, forming an interdependent and mutually restricted system. The intestinal microbiota are beneficial to the human body under normal circumstances. However, when the system is out of balance, it might cause or exacerbate chronic inflammation. In the present investigation, the alpha-diversity analysis, including the rarefaction curve, indicated that APH at different concentrations could effectively prevent the change of the diversity and abundance of intestinal microbiota. According to the beta-diversity analysis, DSS caused intestinal microflora disorder in mice, while APH could effectively alleviate this phenomenon. Recent research also showed that the structure of the intestinal microbiota plays a crucial role in UC [40]. Haolong Zhang et al. reported that the proliferation of probiotics such as lactobacillus can alleviate the severity of UC [41]. Xiaokun Cai et al. found that increasing beneficial bacteria and reducing harmful bacteria could partially reverse the changes in intestinal microbiota, thus alleviating the symptoms of colitis [42]. Up to now, intestinal microflora have become a new target of gastrointestinal disease treatment, while APH could improve the symptoms of colitis by regulating the structure and abundance of intestinal microflora. Therefore, APH can be further studied as a functional food to prevent UC.

Accumulating evidence has shown that in patients with UC, there are fewer probiotics and more pathogenic and harmful bacteria [43]. Powell and Chen reported that *Bacteroides* and *Proteobacteria* can promote the intestinal tract to produce excessive pro-inflammatory cytokines, and they are the main pathogenic bacteria of colitis [44,45]. As the major metabolites of probiotics, short-chain fatty acids (SCFAs) have been shown to increase tight junction protein expression and reduce pro-inflammatory cytokine production in intestinal epithelial cells [46]. At the phylum and genus levels in this study, we found that the relative abundance of *Bacteroides* and *Aerococcus* was enhanced by DSS, yet suppressed with APH treatment. In addition, APH promoted the abundance of probiotics such as *Lactobacillus*. This presumably might be due to the fact that APH increased the content of SCFAs by regulating the abundance of probiotics, thereby reducing the level of proinflammatory factors and alleviating the symptoms of colitis. Moreover, the decreased level of pro-inflammatory cytokines in the APH groups might be related to the reduced

abundance of *Bacteroidetes*. This further indicated that regulating intestinal microbiota may be one of the mechanisms by which APH exerts anti-UC effects.

In conclusion, the results obtained in this study clearly demonstrate that APH could effectively relieve DSS-induced ulcerative colitis in vivo, which played its role mainly by regulating the level of inflammatory cytokines and the structure of intestinal microbiota. Overall, our study provided a new strategy for antagonizing UC, and also offered a highvalue utilization for CGM.

**Supplementary Materials:** The following supporting information can be downloaded at: https:// www.mdpi.com/article/10.3390/foods11213359/s1, Table S1. Amino acid composition of CGM and APH.

**Author Contributions:** Y.J.: writing—original draft; X.L.: writing—reviewing and editing; J.W.: experiments and data analysis; Y.M.: experimental data analysis; X.Z.: experimental design and funding acquisition. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was funded by Heilongjiang Province key research and development program guidance projects (No. GZ20210097), Talent Foundation of the Central Government Supporting Local Universities (No. 2020GSP08), the National Key Research and Development Plan of China (No. 2021YFD2100900), and Heilongjiang Province basic scientific research operating expenses scientific research projects (No. 135509223).

**Data Availability Statement:** Data is contained within the article or Supplementary Material.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

## *Article* **Sacha Inchi Oil Press-Cake Protein Hydrolysates Exhibit Anti-Hyperuricemic Activity via Attenuating Renal Damage and Regulating Gut Microbiota**

**Kun Wang, Shanshan Wu, Pan Li, Nan Xiao, Jiamin Wen, Jinming Lin, Siming Lu, Xin Cai, Yanan Xu and Bing Du \***

College of Food Science, South China Agricultural University, Guangzhou 510642, China **\*** Correspondence<EMAIL_ADDRESS>
**Abstract:** The incidence of hyperuricemia has increased globally due to changes in dietary habits. The sacha inchi oil press-cake is generally discarded, resulting in the waste of resources and adverse environmental impact. For the purpose of developing sacha inchi oil press-cake and identifying natural components with anti-hyperuricemic activities, we systemically investigated the underlying mechanisms of sacha inchi oil press-cake protein hydrolysates (SISH) in the hyperuricemic rat model. SISH was obtained from sacha inchi oil press-cake proteins after trypsin treatment, and 24 peptides with small molecular weight (<1000 Da) were identified. The results of animal experiments showed that SISH significantly decreased the serum uric acid (UA) level by inhibiting the xanthine oxidase (XOD) activity and regulating the gene expression related to UA production and catabolism in hyperuricemia rats, such as Xdh and Hsh. In addition, SISH attenuated the renal damage and reduced the gene expression related to inflammation (Tlr4, Map3k8, Pik3cg, Pik3ap1, Ikbke, and Nlrp3), especially Tlr4, which has been considered a receptor of UA. Notably, SISH reversed high purine-induced gut microbiota dysbiosis, particularly by enhancing the relative abundance of butyric acid-producing bacteria (unidentified\_*Ruminococcaceae*, *Oscillibacter*, *Ruminiclostridium*, *Intestinimonas*). This research provided new insights into the treatment of hyperuricemia.

**Keywords:** sacha inchi oil press-cake protein hydrolyzates; hyperuricemia; renal injury; gut microbiota

#### **1. Introduction**

Hyperuricemia has become prevalent due to changes in dietary habits [1,2]. It is a leading cause of gout [3,4] and a risk factor for hypertension [5], obesity [6], cardiovascular disease [7], and renal failure [8]. Hyperuricemia is characterized by an increase in uric acid (UA) levels in serum due to the imbalance between the blood UA generation and excretion [9]. UA is one product in the purine metabolism pathway. Xanthine oxidase (XOD), a critical enzyme in the purine catabolic pathway, catalyzes the oxidation and conversion of hypoxanthine and xanthine to UA [10]. In in vivo settings, kidneys are responsible for most UA excretion, while approximately 25% of UA is excreted into the intestines and further metabolized by gut microbiota [9]. In fact, a recent report indicated that gut microbiota could serve as a candidate intervention target to relieve hyperuricemia pathogenesis [9]. Therefore, both kidney health and gut microbiota integrity are critical in hyperuricemia prevention. At present, three categories of medicines are commonly used to treat hyperuricemia: inhibitors of xanthine oxidase, uricosuric agents, and recombinant uricases [11,12]. However, these drugs have unfavorable side effects, such as serious allergic reactions and rashes resulting from allopurinol [13]. Consequently, it is critical to identify more effective alternatives to manage hyperuricemia with fewer side effects.

Protein hydrolysates are more digestible than protein, releasing more bioactive peptides and exhibiting a variety of biological functions, such as anticancer and immunoregulation [14]. Recently, it has been reported that certain protein hydrolysates exhibited anti-hyperuricemic activity. Whey protein hydrolysates lessened renal dysfunction caused

**Citation:** Wang, K.; Wu, S.; Li, P.; Xiao, N.; Wen, J.; Lin, J.; Lu, S.; Cai, X.; Xu, Y.; Du, B. Sacha Inchi Oil Press-Cake Protein Hydrolysates Exhibit Anti-Hyperuricemic Activity via Attenuating Renal Damage and Regulating Gut Microbiota. *Foods* **2022**, *11*, 2534. https://doi.org/ 10.3390/foods11162534

Academic Editors: Fuping Lu and Wenjie Sui

Received: 22 July 2022 Accepted: 12 August 2022 Published: 22 August 2022

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by hyperuricemia by restraining the production of UA and promoting the excretion of UA [15]. Bonito protein hydrolysates significantly reduce the serum UA level, inhibit the XOD enzyme activity, and alleviate renal damage in hyperuricemic rats [16]. In addition, walnut protein hydrolysate, tuna protein hydrolysates, and kidney bean protein hydrolysates exhibited anti-hyperuricemic activity [17–19]. Therefore, protein hydrolysates are reasonable resources to treat hyperuricemia. However, despite these previous studies that documented the anti-hyperuricemic activity of protein hydrolysates, a systemic and comprehensive investigation is needed to mechanistically address several essential unknowns. For instance, the major components and compositions of these hydrolysates need to be clarified, and the physiological impacts of protein hydrolysates on the kidney and gut biology and physiology demand specifications.

Sacha inchi (*Plukenetia volubilis* L.) is a plant belonging to the Euphorbiaceae family native to the Amazon Rainforest in Peru [20]. Sacha inchi kernels serve as an enriched source of various nutrients, especially in the forms of oils (35~65%) and proteins (25~30%) [21]. Sacha inchi kernels are mainly used for oil extraction, with the press-cake as a by-product. Although sacha inchi oil press-cake is rich in high-quality proteins (47~59%), it has been generally ignored, causing a massive waste of protein resources [22]. In addition, improper handling of the press-cake can readily result in environmental pollution. As reported, green tea residue contained 18~20% protein, and its hydrolysates showed various biological activity, including antioxidant and anti-hypertensive activity [23]. Sacha inchi oil presscake is also a good source of protein hydrolysates with various biological activities [24,25]. Consistently, upon hydrolyzation of the sacha inchi oil press-cake by calotropis proteases and crude papain, the obtained protein hydrolysates possess substantial antioxidant properties [25]. In line with these findings, hydrolyzation of the sacha inchi oil press-cake by alcalase, neutrase, and flavourzyme yields protein hydrolysates that have antioxidant activities, as well [24]. Therefore, sacha inchi oil press-cake protein hydrolysates may be an effective way to address resource waste. However, the therapeutic value of the sacha inchi oil press-cake protein hydrolysates on hyperuricemia has not been defined yet.

Given the above considerations, there are multiple advantages to further developing sacha inchi oil press-cake to bring gains in the economy, environment, and the sacha inchi industry. In addition, it is also very important to explore more effective alternatives to treat and prevent hyperuricemia. Therefore, the aim of this study was to find the sacha inchi oil press-cake protein hydrolysates (SISH) with anti-hyperuricemic activity. Additionally, 16S rRNA gene sequencing, UPLC-Q-TOF/MS-based metabolomics, and RNA-Seq transcriptomics were used to determine the anti-hyperuricemic mechanisms underlying SISH. This study provides novel insights into the utilization of SISH and the treatment of hyperuricemia.

#### **2. Materials and Methods**

#### *2.1. Preparation and Characterization of SISH*

About 5 kg of defatted and squeezed sacha inchi seed flour was provided by the Pure U-Multitude Biological Resources Co., Ltd. (Yunnan Province, China). The sacha inchi seed flour was soaked in water (1:25, *w*/*v*) for 3 h. After that, the solution was hydrolyzed with 5% trypsin at 55 ◦C for 6 h, and the enzyme was inactivated by heating at 90 ◦C for 15 min [26]. Upon centrifugation (4000× *g*, 10 min), the supernatant was passed through an ultrafiltration membrane (3000 Da). The permeated solvent was then concentrated by evaporation and lyophilized to obtain SISH.

The amino acid analysis of SISH was conducted similarly as previously described [27]. The Shimadzu LC-20A HPLC system (Shimadzu, Japan) was used to measure the molecular weight distribution of SISH content according to the method described by Li et al. [28]. The peptide sequence of SISH was similarly identified using high-performance liquid chromatography-mass spectrometry (LC/MS-MS) [29].

#### *2.2. Animals and Experimental Design*

All animal experiments were conducted in the Guangdong Medical Laboratory Animal Center (Approval No: SCXY(Yue) 2018-0137) in accordance with Chinese laws and regulations on the use and care of laboratory animals. A total of 36 male Sprague Dawley (SD) rats were provided by the Medical Experimental Animal Center of Guangdong Province and housed in standard laboratory cages (temperature, 22~26 ◦C; humidity, 40~60%) with 10 h light/14 h dark cycle.

After adaptive feeding for 7 days, the rats were randomly divided into the blank control (CD) group (*n* = 9) and the model groups (*n* = 27). The model groups were orally gavaged with adenine (200 mg/kg BW) and injected intraperitoneally with potassium oxonate (100 mg/kg BW), while the CD group was fed with a normal diet. After feeding for 10 days, eyelid blood was collected to determine the serum UA level. UA levels above 110 μmoL/L were considered to be qualified as hyperuricemic in the rat model [16]. Then, the administration of adenine and potassium oxonate was halted, and the model group rats were randomly divided into three groups (*n* = 9 each), the hyperuricaemic model group (MG), the SISH treatment group (SISH), and the allopurinol treatment group (DG). Rats in the SISH and DG groups were intragastrically administered SISH (0.42 g/kg BW) and allopurinol (10 mg/kg BW), respectively, while the CD and MG groups were given the same volume of 0.9% saline. After SISH treatment for 4 weeks, the blood, liver, kidney, and colon contents were sampled and stored at −80 ◦C until use.

#### *2.3. Biochemical Determination*

XOD activity and the levels of UA, creatinine (Cr), and blood urea nitrogen (BUN) in the rat serum were determined by commercial detection kits (Jiancheng Bioengineering Institute, Nanjing, China) according to instructions of the manufacturer. The liver tissues were homogenized and centrifuged (3000 r/min, 10 min) at 4 ◦C, and XOD activity in the supernatant was then determined by the kit accordingly.

#### *2.4. Histology*

The kidney samples were stained with hematoxylin-eosin (HE) and examined by light microscopy. Scoring the renal tubule and interstitial injury was set up based on the following criteria: 0 points = no significant lesion; 1 point = the range of lesions does not exceed 1/4 area; 2 points = the range of lesions does not exceed 1/2 area; 3 points = the lesion range does not exceed 3/4 area; 4 points = the lesion range exceeds 3/4 area.

#### *2.5. 16S rRNA Gene Amplification and Sequencing*

The colon contents samples of each rat (*n* = 6) were collected aseptically for 16S rRNA gene sequencing analysis. According to the manufacturer's recommendation, genomic DNA from the colonic content was extracted through a fecal DNA isolation kit (MoBio Laboratories, Carlsbad, CA, USA). The primers 515F (5 -GTGCCAGCMGCCGCGGTAA-3 ) and 806R (5 -GGACTACHVGGGTWTCTAAT-3 ) were used to amplify the V4 region of 16S rRNA genes. The resulting PCR products were purified with GeneJETTMGel Extraction Kit (Thermo Scientific, Waltham, MA, USA). According to the manufacturer's recommendation, the Ion Plus Fragment Library Kit 48 rxns (Thermo Scientific) was used to generate the sequencing library. The sequencing test was performed by the TNovogene Bioinformatics Technology Co., Ltd. (Tianjin, China) using the Illumina MiSeq sequencing platform.

In order to obtain high-quality clean reads, the raw reads were trimmed and filtered under standard operations based on Cutadapt (V1.9.1, http://cutadapt.readthedocs. io/en/stable/, accessed on 13 January 2021). The operational taxonomic units (OTUs) with 97% sequence similarity were obtained using the Uparse software (Version 7.0.1001; Edgar, Robert C; Belvedere Tiburon, CA, USA). With the Mothur algorithm, the Silva Database (https://www.arb-silva.de/, accessed on 13 January 2021) was used to annotate the taxonomic information of each representative sequence. The alpha diversity and beta diversity of the gut microbiota were calculated by QIIME (Version 1.7.0; Rob Knight; Fort Collins, CO, USA). Principal Coordinate Analysis (PCoA) was performed with the WGCNA package, stat packages, and ggplot2 package in the R software (Version 2.15.3; Mathsoft Company; Cambridge, MA, USA). Anosim and multi-response permutation procedure (MRPP) analyses were conducted with QIIME. The Galaxy platform was used for linear discriminant analysis effect size (LEfSe) analysis based on *p* < 0.05 and LDA score>3[30].

#### *2.6. Serum Metabolomic Analysis*

A total of 100 μL of serum samples were mixed with 400 μL of prechilled methanol. All samples were centrifugated at 15,000 rpm for 5 min, and the supernatant was diluted to a final concentration of 60% methanol. After filtration with a 0.22 μm filter, samples were centrifuged at 15,000× *g* for 10 min. Each sample was subjected to ultra-high performance liquid chromatography analysis in combination with quadrupole time-of-flight mass spectrometry (UHPLC-MS/MS) (Thermo Fisher). Samples were injected onto a Hyperil Gold column (100 × 2.1 mm, 1.9 μm) at a flow rate of 0.2 mL/min by a 16 min linear gradient. Eluent A (aqueous solution containing 0.1% fomic acid) and eluent B (methanol) were used for the positive polar mode, while eluent A (5 mM ammonium acetate, pH 9.0) and eluent B (methanol) were used for the negative polar mode. The solvent gradient was set as follows: 2% B, 1.5 min; 2–100% B, 12.0 min; 100% B, 14.0 min; 100–2% B, 14.1 min; 2% B, 16 min. Q ExActive HF-X mass spectrometer was operated in positive/negative polarity mode with the following parameters: spray voltage of 3.2 kV, capillary temperature of 320 ◦C, sheath gas flow rate of 35 arb, and auxiliary gas flow rate of 10 arb. Compound Discoverer 3.0 (Thermo Fisher) was used to analyze the original data files generated by the UHPLC–MS/MS, and peak alignment, peak calling, and quantitation were performed for each metabolite. In order to obtain accurate qualitative and relative quantitative results, peaks were aligned with mzCloud (https://www.mzcloud.org/, accessed on 21 December 2020) and ChemSpider (http://www.chemspider.com/, accessed on 21 December 2020) databases. Multivariate analyses, including principal component analysis (PCA) and Orthogonal partial least-squares discriminant analysis (OPLS-DA), were performed using the SIMCA-P 11.0 software (Umetrics AB, Umea, Sweden). Metabolites with significant differences between groups were obtained under variable influence on projection (VIP) > 1, and *p*-value < 0.05 based on the peak areas.

#### *2.7. Renal Transcriptome Analysis*

Total RNA was isolated from kidneys in compliance with the protocol of TRIzol reagent (Beyotime, Shanghai, China). The integrity and quality of total RNA were evaluated with the RNA Nano 6000 Assay Kit of the Bioanalyzer 2100 system (Agilent Technologies, Palo Alto, CA, USA). Then, 3 μg of total RNA for each sample was used as the input material for the RNA sample preparations. Based on the manufacturer's recommendations and index codes, TruSeq RNA Sample Preparation Kit was applied to generate the sequencing libraries, which were then sequenced on the Illumina HiSeq 2500 platform by the Novogene Bioinformatics Technology Co., Ltd. (Tianjin, China).

Index of the reference genome was established, followed by alignment using Hisat2 (Version2.0.5; Daehwan Kim; Missouri City, TX, USA) with the paired-end clean reads. The relative expression of each gene was normalized and inferred using fragments per kilobase of transcript per million mapped reads (FPKM). Differential expressions with statistical analysis were calculated using the software DESeq2 R package (Version 1.16.1; Michael I Love; Heidelberg, Germany), and the threshold was set as Fold Change > 1.5 and *p*-value < 0.05. Finally, the Gene Ontology (GO) program was applied to annotate the unigenes and analyze the pathway enrichment for differential expression genes (DEGs) [31].

#### *2.8. Correlation Analysis and Statistical Analysis*

The statistical analysis of quantitative data was conducted with the one-way variance analysis (one-way ANOVA) followed by Duncan's multiple comparisons test using the SPSS 16.0. Spearman's correlation coefficients of gut microbiota, DEGs, and metabolites were calculated with R software (v3.2.1; Mathsoft Company) and visualized with the Complex Heatmap package in R software (v3.2.1). All data are expressed as means ± SD.

#### **3. Results**

#### *3.1. Identification of SISH Composition*

SISH was obtained from sacha inchi oil press-cake upon trypsin treatment, and the molecular weight distribution and amino acid composition of SISH were determined (Table 1). The results indicated that most of the peptides in SISH were oligopeptides with a molecular weight of less than 1000 Da (90.70%). In addition, SISH contained 17 kinds of amino acids in total, mainly including glutamic acid (16.7%), aspartic acid (12.6%), and arginine (10.8%). Among them, the essential amino acid content was in the range of 30%, and the hydrophobic amino acid content was 24.9%. De novo sequencing was performed on the collected high-resolution mass spectrometry dataset, and 24 polypeptides were identified based on scores, peak areas, fragment ion error distribution, and other factors (Table 2). MVVKK, KVVL, RLLVWELER, WLPDVK, and TVLLPR were identified as the most abundant peptides in SISH.

**Table 1.** The molecular weight distribution and amino acid composition of SISH.

#### *3.2. SISH Attenuated Hyperuricemia*

Established SD rat models were used to evaluate the anti-hyperuricemia activity of SISH, and elevated serum UA level was monitored as an indicator, which is a common clinical observation in patients with hyperuricemia. After the initial 10 days of high purine diet feeding, the levels of serum UA were above 110 μmoL/L in the MG, SISH, and DG groups, a significant increase (*p* < 0.05) as compared with the CD group, demonstrating the success in the establishment of the hyperuricemic rat model (Supplementary Figure S1). After four weeks of indicated SISH treatments, there were no significant differences in body weight among the four test groups (*p* > 0.05) (Figure 1a). However, the serum UA of hyperuricemic rats after SISH treatment significantly decreased by 38.56% compared to the

MG group (Figure 1b). As reported, XOD is highly expressed in the liver, and an increase in XOD activity would enhance UA production [32]. Therefore, we next examined the effect of SISH treatment on the XOD activity in hyperuricemic rats. As compared with the CD group, XOD activity in serum and hepatic was significantly increased in the MG group (*p* < 0.001), and its activity was reversed to normal levels upon SISH supplementation (*p* < 0.01) (Figure 1c,d). These results indicated that SISH could effectively rescue the induced hyperuricemia by inhibiting XOD activity.

**Table 2.** The peptides sequence identified in SISH by HPLC/MS-MS analysis.

#### *3.3. SISH Attenuated Renal Damage in Hyperuricemic Rats*

Hyperuricemia would increase the risk of renal injury, and thus we needed to examine the effects of SISH on the rat kidney. As shown, SISH supplement indeed profoundly reduced the kidney index as compared with the MG group (Figure 2a). The BUN and Cr, as the indexes of kidney functions, were also evaluated in hyperuricemic rats (Figure 2b,c). The levels of BUN and Cr were substantially increased in the MG group, indicating that the renal functions of hyperuricemia rats were impaired. However, both the BUN and Cr levels were markedly decreased by 12.12% and 13.63% upon SISH treatment (*p* < 0.05). These results showed that SISH could ameliorate renal damage in hyperuricemic rats. Histologically, the sections of kidneys from the CD group showed normal architecture with intact glomerulus and renal tubules. However, in contrast to the normal group, glomerular atrophy, renal tubular dilation, and inflammatory cell infiltration were present

in the MG group, suggesting that hyperuricemic rats had obvious renal damage (Figure 2d). Nevertheless, renal lesions were alleviated upon SISH treatment, which was manifested by a moderate decrease in glomerular volume, mild tubules dilation, and mild inflammatory cell infiltration in the interstitium. Simultaneously, injury scores in the SISH group were also significantly lower than that in the MG group (Figure 2e), and the glomerular counts were similarly reversed (Figure 2f). These results showed that SISH treatment effectively relieved the renal damage in hyperuricemic rats.

**Figure 1.** Evaluation of SISH anti-hyperuricemic activities in hyperuricemic rats. (**a**) Body weight. (**b**) Serum uric acid (UA) levels. (**c**) Serum xanthine oxidase (XOD) activity. (**d**) Hepatic XOD activity. All data are expressed as means ± SD. \*\* *p* < 0.01, and \*\*\* *p* < 0.001 vs. the CD group; ## *p* < 0.01, and ### *p* < 0.001 vs. the MG group.

**Figure 2.** The effects of SISH on renal damage in hyperuricemic rats. (**a**) The kidney indexes. (**b**) Blood urea nitrogen (BUN) levels. (**c**) Serum creatinine (Cr) levels. (**d**) Photomicrographs of representative sections of kidneys. (**e**) Renal injury score. (**f**) Glomerular number in each group. All data are expressed as means ± SD. \*\* *p* < 0.01, and \*\*\* *p* < 0.001 vs. the CD group; # *p* < 0.05, and ## *p* < 0.01 vs. the MG group.

#### *3.4. SISH Reshaped the Gut Microbiota Community in Hyperuricemic Rats*

The gut microbiota alteration was analyzed by 16S rRNA gene sequencing. A total of 2,021,638 clean reads were generated based on sequencing the V4 region of 16S rRNA genes, and each colonic sample produced an average of 84,234 ± 4205 clean reads. The rarefaction curves were close to the saturation plateau (Figure 3a), indicating that the sequencing depth covered rare new phylotypes and represented most of the accessible microbiota. The Shannon index that indicates the diversity of microbial communities [33] was significantly decreased in the MG group as compared to that of the CD group (*p* < 0.001). Upon SISH and allopurinol treatments, the Shannon index was significantly increased in the SISH and DG groups as compared with the MG group (Figure 3b). Therefore, SISH clearly increased the diversity of gut microbiota in hyperuricemic rats. Meanwhile, PCoA analysis also showed that the community composition of the MG group was separated from the other three groups (Figure 3c). Anosim and MRPP algorithms further confirmed significant differences (*p* < 0.05) between the MG groups versus the CD, SISH, and DG groups (Figure 3d).

**Figure 3.** The effects of SISH on the diversity and integrity of the gut microbiota in hyperuricemic rats. (**a**) Rarefaction curves. (**b**) Shannon index. (**c**) Principal coordinate analysis (PCoA). (**d**) Anosim and multi-response permutation procedure (MRPP) analyses. (**e**) Relative abundance at phylum levels. (**f**) The heatmap analysis at genus levels. All data are expressed as means ± SD. \*\* *p* < 0.01 vs. the CD group; # *p* < 0.05 vs. the MG group.

Taxonomic profiling was also used to define SISH effects on the gut microbiota composition in hyperuricemic rats (Figure 3e). As shown, *Firmicutes*, *Bacteroidetes*, *Proteobacteria*, and *Tenericutes* were the dominant phylum in all test groups (Figure 3e). There was no significant difference among groups at the phylum levels. Nevertheless, heatmap analysis showed a dramatic alteration of gut microbiota distribution at the genus level (Figure 3f). Compared with the CD group, *Romboutsia* (1.64% vs. 6.71%) and unidentified\_*Clostridiales* (0.42% vs. 0.80%) were markedly increased, while unidentified\_*Ruminococcaceae* (9.63% vs. 6.16%), *Ruminiclostridium* (1.54% vs. 0.66%), *Oscillibacter* (1.92% vs. 0.88%), and *Intestinimonas* (1.01% vs. 0.52%) were significantly decreased in the MG group. Of importance, SISH intervention substantially rescued the relative abundance of those intestinal florae in hyperuricemic rats (Figure 3f, Supplementary Figure S2). Specifically, SISH enhanced the relative abundance of probiotics such as *Akkermansia* and *Alistipes* and reduced the *Streptococcus* (XOD-producing bacteria) population [10]. Taken together, these results evidenced that SISH could modulate the gut microbial organization and enhance the microbial diversity in hyperuricemic rats.

#### *3.5. SISH Intervention Altered Serum Metabolome in Hyperuricemic Rats*

The effects of SISH on serum metabolome in hyperuricemia rats were next determined by the UHPLC-MS/MS analyses. PCA score plotting showed a clear separation trend between the CD and the MG groups, with similar separation trends being observed between the SISH and the MG groups and between the DG and the MG groups (Figure 4a), respectively. In comparison with that of the MG group, a total of 58, 56, and 70 metabolites were significantly changed in the CD, the SISH, and the DG groups, respectively (Figure 4b,c). OPLS-DA analysis further showed that there was a distinct classification in the metabolite profiles between the MG and the SISH groups (Figure 4d). In addition, cluster analyses revealed a distinct separation of serum metabolites between the MG and the SISH groups (Figure 4e). We also found that UA levels were significantly increased, while 2 -deoxycytidine levels were decreased in the MG group. Other metabolites related to amino acid and energy metabolism, such as L-threonine, DL-carnitine, and tigliylcarnitine, were also substantially reduced in the MG group, indicating that hyperuricemia is extensively linked to amino acid and energy metabolic dysfunction [34,35]. In any case, upon SISH treatment, levels of the above five metabolites were all pronouncedly restored. In comparison, allopurinol treatment rescued the levels of UA, L-threonine, and tigliylcarnitine only (Figure 4f, Supplementary Table S1).

We further performed Spearman correlation analysis to visualize an association between the gut microbiota and metabolome (Figure 4g). As shown, UA was positively (*p* < 0.05) correlated with the gut genus of *Turicibacter* while negatively (*p* < 0.05) correlated with the gut genus of *Ruminiclostridium* and *Intestinimonas*. 2 -deoxycytidine was positively (*p* < 0.05) correlated with *Ruminiclostridium* while negatively (*p* < 0.05) correlated with *Romboutsia*, unidentified\_*Clostridiales*, *Rodentibacter,* and *Faecalibacterium*. Metabolite of L-threonine was positively (*p* < 0.05) correlated with the gut genu of *Ruminiclostridium*, but negatively (*p* < 0.05) correlated with the gut genus of *Romboutsia*, unidentified\_*Clostridiales*, *Rodentibacter,* and *Faecalibacterium*. Overall, these results delineated the impacts of SISH on the serum metabolome in hyperuricemic rats.

**Figure 4.** The impacts of SISH on the serum metabolome of hyperuricemic rats. (**a**) Principal component analysis (PCA) score plot. (**b**) Venn diagram. (**c**) The numbers of differential metabolites. (**d**) The Orthogonal partial least-squares discriminant analysis (OPLS-DA) scores plot. (**e**) A heatmap of differential metabolites potentially associated with hyperuricemia. (**f**) A heatmap of differential metabolites potentially associated with hyperuricemia disease for each treatment. (**g**) Spearman correlation analysis between the metabolites and the gut microbiota. Note: \* *p* < 0.05, \*\* *p* < 0.01, and \*\*\* *p* < 0.01.

#### *3.6. Identification of the Potential SISH Target Genes and Signaling Pathways Involved in Hyperuricemic Rats*

In order to further define the molecular determinants underlying SISH beneficial effects in hyperuricemic rats, we then explored the renal transcriptome. As compared with the CD group, 2584 genes were differentially expressed in the MG group. Furthermore, a total of 1394 genes were differentially expressed between the SISH and the MG groups

(Figure 5a). Hierarchical clustering and PCA analysis revealed that DEGs in the SISH group were obviously distinct from those in the MG group (Figure 5b,c).

**Figure 5.** The Effects of SISH on the renal transcriptome in hyperuricemic rats. (**a**) Venn diagram. (**b**) Heatmap for hierarchical cluster analysis of differential expression genes (DEGs) (fold change of ≥ 1.5 or ≤ −1.5, *p* < 0.05). (**c**) The principal component analysis (PCA) score plot. (**d**) Heatmap for genes involved in purine metabolism. (**e**) Spearman correlation analysis between the metabolites and genes related to purine metabolism. Differences were assessed by ANOVA. (**f**) Heatmap for genes involved in inflammatory responses. Note: \* *p* < 0.05, \*\* *p* < 0.01, and \*\*\* *p* < 0.01.

Next, we evaluated the expression of several crucial genes related to purine metabolism (Figure 5d, Supplementary Table S2). Compared with the CD group, Xdh, Gucy1α3, Gucy1β3, Pde7a, and Pde11a transcripts were markedly upregulated in the MG group, while Prim2, Nme7, and Entpd8 were substantially downregulated. Importantly, compared with the MG group, the expression levels of Xdh, Gucy1α3, Gucy1β3, Pde7a, and Pde11a were all downregulated, while Hsh was upregulated upon SISH treatment. Consistently, based on the Spearman correlation analysis, we found that the metabolite of UA was positively (*p* < 0.05) correlated with Xdh, Gucy1α3, and Gucy1β3, but negatively (*p* < 0.05) correlated with Hsh (Figure 5e). These results demonstrated that SISH could reduce UA levels by regulating genes functioning in purine metabolism.

Excessive levels of serum UA are known to increase the risk of kidney inflammation and damage [36]. In accordance, the transcriptomic analysis identified enrichment in a group of DEGs relevant to inflammation (Figure 5f). Compared with the MG group, the SISH group substantially reduced the expression of genes involved in the PI3K-Akt signaling pathway, Jak-STAT signaling pathway, Toll-like receptor signaling pathway, and NOD-like receptor signaling pathway. Among them, Tlr4, Map3k8, Ikbke, Nlrp3, Pik3cg, Pik3ap1, and Akt3 genes were significantly downregulated in the SISH group as compared with the MG group. According to GO analysis (Supplementary Figures S3 and S4), the significantly upregulated DEGs in the SISH group (as compared to the MG group) were functionally enriched in the transport and metabolic-related processes. In comparison, most of the significantly downregulated genes were associated with inflammatory responses, such as chemotaxis, ERK1 and ERK2 cascade, regulation of ERK1 and ERK2 cascade, and positive regulation of MAPK cascade. Together, these findings specified these inflammationrelated genes that could mediate the beneficial effects of SISH on hyperuricemia.

#### **4. Discussion**

With the increasing prevalence of hyperuricemia worldwide, it is imperative to seek more effective alternatives for hyperuricemia intervention with fewer side effects. Plant protein hydrolysates are among the best options in terms of scientific, economic, social, environmental, and industrial values. In this study, we evidenced that sacha inchi oil press-cake is a good source of bioactive protein hydrolysates that have favorable antihyperuricemia effects. Instead of discarding the sacha inchi oil press-cake as industrial by-products and environmental biohazards, we could obtain SISH from it by hydrolyzing proteins. A series of tests in biochemical, biological, and physiological settings helped us to define the composition and anti-hyperuricemic effects of SISH, potentializing its use and application in various food and bio-industrial domains.

Hyperuricemia is characterized by high levels of UA in serum [37], and previous studies have shown that some small molecular weight peptides (<1 kDa) could lower the serum UA level [18,38,39]. In this study, SISH was confirmed to contain a large number of small peptides (up to 90.7%, <1 kDa) and shown to reduce serum UA levels in hyperuricemic rats, effects that were validated in serum metabolome analysis, as well. Purine metabolism disorders could also lead to an increase in serum UA, in which the XOD plays a central role by catalyzing the oxidation and conversion of hypoxanthine to UA [18]. Consistently, our study found that SISH inhibited the XOD activity in serum and liver in hyperuricemic rats, providing a mechanistic explanation. It should be noted that Trp residue in peptides, as identified in the SISH oligopeptides, acts as a critical factor for achieving XOD inhibitory activity [37]. Moreover, a mixture of peptides in the SISH would confer combinatory effects on UA metabolism, likely due to synergistic interactions among these peptides [40]. In line with these findings, renal transcriptome analysis indicated that SISH could downregulate genes relevant to UA production (such as Xdh, Gucy1α3, Gucy1β3, Pde7a, and Pde11a) [41] and UA catabolism (like Hsd) that promotes the degradation of UA into allantoin [42]. Collectively, we propose that the anti-hyperuricemic activities of SISH are derived from its inhibitory activity on XOD and its regulation of genes engaged in UA metabolism.

The imbalance between UA production and excretion leads to hyperuricemia, and approximately 2/3 of UA is excreted through the renal route [9]; however, a high level of UA in serum could cause renal injury [43]. Therefore, normal renal function is an essential factor in ensuring the balance of UA production and excretion. Serum BUN and Cr are important indicators of renal functions, and consistently, in our study, both levels of BUN and Cr were enhanced in hyperuricemic rats. On the contrary, SISH treatment significantly reversed the increases in BUN and Cr, in agreement with the findings by Shan et al. [44]. In addition, high UA in serums could induce renal inflammation [36], and histopathological examination did show inflammatory cell infiltration in the interstitium of the kidney in hyperuricemic rats, while SISH again alleviated the inflammation. Mechanistically, renal transcriptome analysis in hyperuricemic rats further demonstrated that SISH downregulated genes relevant to inflammatory signaling, namely the PI3K-Akt signaling pathway, Toll-like receptor signaling pathway, chemokine signaling pathway, Jak-STAT signaling pathway, and NOD-like receptor signaling pathway. Of significance, SISH repressed the

Tlr4 gene that functions as a UA receptor [45]. Upon Tlr4 activation by UA, its downstream signal cascade (like the IKK/IκB/NF-κB pathway) will be unleashed, ultimately leading to the induction of pro-inflammatory cytokines/mediators and the onset of tissue damage [36,46]. Together, we determined by multiple channels that SISH markedly alleviates the kidney damage bound with hyperuricemia.

In addition to the predominant excretion of UA through the kidneys, the remaining about 1/3 of UA is excreted from the intestines [9]; importantly, UA excretion will be mainly converted to the intestine when kidneys become dysfunctional [43]. Gut microbiota, as an important component of the intestine, plays an active role in UA excretion [9,47]. In accordance, previous studies indicated that the anti-hyperuricemic effects of some oligopeptides were mediated by the gut microbiota, such as tuna meat oligopeptides [40], Val-Val-Tyr-Pro peptide [48], and *Apostichopus japonicus* oligopeptide [49]. As reported, the diversity of intestinal flora in the hyperuricemia group is generally lower than that in the normal group [50]. Indeed, the alpha diversity analysis in the current study revealed that the Shannon diversity index was significantly decreased in the hyperuricemic rats, whereas it was substantially enhanced by SISH supplementation. Short-chain fatty acids (SCFAs), especially butyric acid, can relieve hyperuricemia by providing energy to intestinal wall cells to promote UA excretion [9]. Compared with the hyperuricemic group, the SISH group had a significantly increased abundance of *Ruminococcaceae* (unidentified\_*Ruminococcaceae*, *Oscillibacter*, *Ruminiclostridium*, *Intestinimonas*) which are considered butyrate-producing prebiotics [51]. In addition, SISH also increased the abundance of probiotics (*Akkermansia*, *Alistipes*) and reduced the population of the XOD-producing bacteria (*Streptococcus*) [10]. *Lactobacillus* is known to sequentially degrade UA to urea by synthesizing uricase, allantoinase, and allantoicase, thereby improving UA excretion [9]. Unexpectedly, we found that the relative abundance of *Lactobacillus* was higher in the MG group as compared with the CD group, and SISH decreased *Lactobacillus* in hyperuricemic rats, which is in contradiction to some reports [9,50]. We speculated that the increase in *Lactobacillus* in the MG group could reflect the body's intrinsic compensatory system as a part of feedback at certain time points to consume excess UA in hyperuricemic rats [43]. Overall, these results clearly indicate that SISH supplementation could reverse gut microbiota dysbiosis in hyperuricemic rats.

By integrating the results of 16S rRNA gene sequencing, serum metabolome, and renal transcriptome analyses, we also found that UA level was negatively correlated with the *Ruminococcaceae* (unidentified\_*Ruminococcaceae*, *Oscillibacter*, *Ruminiclostridium*, *Intestinimonas*) abundance and *Hsh* gene expression level, and an increase in those bacteria and the *Hsh* gene can enhance UA excretion [51]. In addition, UA levels positively correlated with *Streptococcus* abundance and *Xdh* gene expression, and increases in those bacteria and the *Xdh* gene would enhance UA production [10,41]. Consistently, SISH boosted the *Ruminococcaceae* abundance and Hsh gene expression and reduced the *Streptococcus* abundance and *Xdh* gene expression, consequentially leading to a decline in serum UA and relief of hyperuricemia. In summary, SISH attenuated hyperuricemia by ameliorating renal damage and maintaining intestinal flora integrity. Our findings provide new insights on the utilization of sacha inchi oil press-cake and the potential of derived SISH as a hyperuricemia therapeutic regime.

#### **5. Conclusions**

In conclusion, SISH could reduce the serum UA level and improve hyperuricemia. The underlying mechanisms could be related to the inhibition of the XOD activity, regulation of gut microbiota structure, and attenuation of the renal injury in SD rats. However, additional studies are required to investigate the deeper mechanisms underlying the antihyperuricemic activity of SISH; for instance, fecal microbiota transplantation could be used to further explore whether alterations in the gut microbiota are a key factor in the anti-hyperuricemic activity of SISH. Overall, these results suggest that the protein in sacha

inchi oil pressed-cake is a valuable source of hydrolysates, and SISH could be used as a potential functional component for preventing hyperuricemia.

**Supplementary Materials:** The following supporting information can be downloaded at: https:// www.mdpi.com/article/10.3390/foods11162534/s1, Table S1, Identification of the potential biomarkers in SISH treated hyperuricemic rats; Table S2, Identification of candidate functional genes in SISH treated hyperuricemic rats; Figure S1, The serum UA levels in rats upon adenine and potassium oxonate treatments for 10 days; Figure S2, Comparison of indicated specific taxa between the four test groups; Figure S3, GO enrichment analyses between the CD and the MG groups; Figure S4, GO enrichment analyses between the SISH and the MG groups.

**Author Contributions:** Conceptualization, K.W., S.W. and P.L.; data curation, P.L.; formal analysis, J.L. and S.L.; investigation, N.X. and X.C.; methodology, K.W., S.W. and J.W.; project administration, P.L. and B.D.; resources, J.W.; software, K.W., N.X. and Y.X.; writing—original draft, K.W.; writing review and editing, S.W. and P.L.; supervision: B.D.; funding acquisition, B.D. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the China Agriculture Research System of MOF and MARA (CARS-21), the Natural Science Foundation of Guangdong Province (2020A1515011268), the Key-Area Research and Development Program of Guangdong Province (2020B020226008) and Du Bing Expert Workstation Project of Yunnan Province (202005AF150071).

**Institutional Review Board Statement:** The animal study protocol was approved by the Ethics Committee of Guangdong Medical Laboratory Animal Center (protocol code:<PHONE_NUMBER>8370; date of approval: 5 April 2019).

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author.

**Acknowledgments:** We would like to thank Novogene (Beijing, China) for sharing the Illumina platform. We also thank Pure U-Multitude Biological Resources Co., Ltd. (Puer, China) for the supply of the defatted and squeezed sacha inchi seed flour.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

## *Article* **Crosslinking Mechanism on a Novel** *Bacillus cereus* **Transglutaminase-Mediated Conjugation of Food Proteins**

**Hongbin Wang 1,†, Yuanfu Zhang 1,†, Zhaoting Yuan 1, Xiaotong Zou 1, Yuan Ji 1, Jiayi Hou 1, Jinfang Zhang 2,\*, Fuping Lu 1 and Yihan Liu 1,\***

**Abstract:** Until now, *Streptoverticillium mobaraense* transglutaminase (TG) is the only commercialized TG, but limited information is known about its selection tendency on crosslinking sites at the protein level, restricting its application in the food industry. Here, four recombinant *Bacillus* TGs were stable in a broad range of pH (5.0–9.0) and temperatures (<50 ◦C), exhibiting their maximum activity at 50–60 ◦C and pH 6.0–7.0. Among them, TG of *B. cereus* (BCETG) demonstrated the maximal specific activity of 177 U/mg. A structural analysis indicated that the Ala147-Ala156 region in the substrate tunnel of BCETG played a vital role in catalytic activity. Furthermore, bovine serum albumin, as well as nearly all protein ingredients in soy protein isolate and whey protein, could be cross-linked by BCETG, and the internal crosslinking paths of three protein substrates were elucidated. This study demonstrated *Bacillus* TGs are a candidate for protein crosslinking and provided their crosslinking mechanism at the protein level for applications in food processing.

**Keywords:** transglutaminase; enzymatic characterization; structural analysis; crosslinking properties; protein substrate crosslinking mechanism

#### **1. Introduction**

Proteins perform a vital role in food quality as a critical fraction of food products. Nowadays, protein modification technologies attract more and more attention due to their importance in satisfying the consumers' various food requirements [1]. Compared to chemical modification, protein modification using enzymatic techniques demonstrates lots of advantages, such as a low frequency of side reactions, high reaction specificity, and the lack of a need for chemical solvents (environmental friendliness) or high-pressure and high-temperature conditions [2]. In this context, protein crosslinking, which is described as "the process of joining protein molecules by inter or intra-molecular covalent bonds", plays an important role in determining the functional characteristics of foods [3].

Transglutaminase (EC <IP_ADDRESS>, TG) leads to inter- and intra-molecular crosslinking through catalyzing the generation of ε-(g-glutamyl) lysine "isopeptide" covalent bonds in proteins. Currently, TGs have been discovered and characterized in prokaryotes and eukaryotes. Comparing with the eukaryotic counterparts, bacterial TGs demonstrate lots of obvious advantages, such as cofactor independency, small size, high stability and improved performance [4], and they have been chiefly discovered in *Bacillus* and *Streptoverticillium* strains. TG derived from *Streptoverticillium mobaraense* (MTG) is the sole transglutaminase commercialized for food processing [5]. It is mainly used for changing proteins' elasticity and solubility, producing textured products, improving protein encapsulation capacity, emulsifying properties, and water-holding capacity, improving the nutritious value of food products by the incorporation of essential amino acids, forming heat and water-resistant

**Citation:** Wang, H.; Zhang, Y.; Yuan, Z.; Zou, X.; Ji, Y.; Hou, J.; Zhang, J.; Lu, F.; Liu, Y. Crosslinking Mechanism on a Novel *Bacillus cereus* Transglutaminase-Mediated Conjugation of Food Proteins. *Foods* **2022**, *11*, 3722. https://doi.org/ 10.3390/foods11223722

Academic Editor: Cristina Martínez-Villaluenga

Received: 23 September 2022 Accepted: 14 November 2022 Published: 19 November 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

films, avoiding gelation by thermal treatment, and, recently, to reduce allergenicity [6]. MTG demonstrates its stability below 40 ◦C from pH 5.0 to 8.0 and its maximum activity at 50 ◦C between pH 6.0 and 7.0 [7]. However, TG from *B. subtilis* (BSUTG) exhibits its maximum activity at pH 8.0 and 60 ◦C, which are more stable under wide ranges of pH (pH 5.0–9.0) and temperature (30–60 ◦C). Meanwhile, BSUTG and MTG have only ∼10% homology in amino acid sequences, and they also show lots of differing preference in substrates such as soy protein isolate (SPI) and whey protein (WP). Obviously, it would be helpful to meet the large number of needs of various food substrates and processing due to the diversity of TGs in nature. Hence, it would offer a novel challenge for utilizing TGs in the rising food field by exploring novel TGs. In addition, our previous study investigated BSUTG's crosslinking characteristics on peptide levels [8]. Nevertheless, selecting food protein crosslinking sites might be affected by both the neighboring amino acids and the protein spatial structure of BSUTG. So far, limited information on the favorite amino acid crosslinking sites is known on the food protein level.

In this study, we characterized TGs derived from *B. amyloliquefaciens*, *B. cereus*, *B. safensis*, and *B. aryabhattai*. Then, molecular dynamics simulation was performed to analyze the *B. cereus* TG's tertiary structure to explore the molecular mechanism of its catalytic activity under different temperatures. Finally, we estimated the abilities of *B. cereus* TG towards various substrates and the preferred crosslinked amino acid sites. This study facilitates the applications of *Bacillus* TGs in the food industry and the depth our understanding of them.

#### **2. Materials and Methods**

#### *2.1. Strains, Plasmids, Materials, and Growth Media*

*B. amyloliquefaciens* TCCC 111018, *B. cereus* TCCC 111006, *B. safensis* TCCC 111022, and *B. aryabhattai* TCCC 11368 were kept in our laboratory, and they were incubated at 37 ◦C in liquid LB medium. *Escherichia coli* BL21 (DE3) was utilized for expressing the recombinant enzyme, and kanamycin was added when necessary. The pET-28a(+) was employed as an expression vector.

Reagents were provided by the following sources: *N*,*N*-dimethylcasein and dansyl cadaverine [N-(5-aminopentyl)-5-dimethylamino-1-naphthalenesulfonamide, MDC] were ordered from Sigma-Aldrich Co. (St. Louis, MO, USA) and Aladdin Chemical Co., Ltd. (Shanghai, China), respectively. Bovine serum albumin (BSA, ≥98%), soy protein isolate (SPI, ≥88%), and whey protein (WP, ≥80%) were provided by Solarbio Science & Technology Co., Ltd. (Beijing, China), Macklin Biochemical Co., Ltd. (Shanghai, China), and Sigma-Aldrich (St Louis, MO, USA), respectively.

#### *2.2. Strains Construction*

The TG genes encoding *bamtg*, *bcetg*, *bsatg*, and *bartg* were obtained using the forward and reverse primers presented in Table S1 and genomic DNA from *B. amyloliquefaciens* TCCC 111018, *B. cereus* TCCC 111006, *B. safensis* TCCC 111022, and *B. aryabhattai* TCCC 11368 as templates. After digestion with *Nco*I and *Hin*dIII, the PCR products *bamtg*, *bsatg*, and *bartg* were inserted into the *Nco*I and *Hin*dIII-linearized pET-28a (+). However, the PCR product *bcetg* was ligated to the *Nco*I–*Not*I-linearized pET28a(+) due to the *Hin*dIII restriction site in the *bcetg* gene. The sequences of *bamtg*, *bcetg*, *bsatg*, and *bartg* were deposited in GenBank, respectively (Accession No: MN537144, MW281568, MW292483, and MW916358). *E. coli* BL21 (DE3) cells harboring the recombinant vectors pET-*bamtg*, pET-*bcetg*, pET-*bsatg*, and pET-*bartg* were utilized for protein expression. Their protein sequences were analyzed using DNAMAN for multiple protein sequence alignment, and the signal peptides were predicted by the Signal P 3.0 server (http://www.cbs.dtu.dk/services/SignaIP-3.0 (accessed on 8 June 2019)).

#### *2.3. Production and Purification of TGs*

Each single colony of BL21/pET-*bamtg*, BL21/pET-*bcetg*, BL21/pET-*bsatg*, and BL21/ pET-*bartg* was grown at 37 ◦C for 12 h in 5mL of LB medium containing 50 μg/mL

kanamycin with shaking at 200 rpm. Subsequently, the seed culture (1 mL) was inoculated into 50 mL of fresh LB medium with kanamycin (50 μg/mL). When OD600 of the cells reached 0.6–0.8, 0.5 mM isopropyl-β-D-1-thiogalactopyranoside (IPTG) was utilized to induce the production of recombinant TGs (rTGs) at 16 ◦C for 20 h.

Cells were centrifugally collected at 8000× *g* and 4 ◦C for 15 m, followed by resuspension in the lysis buffer (20 mmol/L CAPS, 0.5 mol/L NaCl, 10% glycerol, 10 mmol/L imidazole, pH 8.0). Then, the cells were sonicated at 260 W with 2 s strokes and 4 s intervals. After centrifugation at 12,000× *g* for 30 min, the resulting supernatant was loaded onto a nickel–nitrilotriacetic acid (Ni-NTA) agarose column (Qiagen, Germany) which was preequilibrated with lysis buffer. After removing non-target proteins with washing buffer (20 mmol/L CAPS, 0.5 mol/L NaCl, 10% glycerol, 300 mmol/L imidazole, pH 8.0), the purified rTGs were collected after eluting with elution buffer (20 mmol/L CAPS, 0.5 mol/L NaCl, 10% glycerol, 60 mmol/L imidazole, pH 8.0). Sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) was performed to analyze the purified protein, and the Bradford method was utilized toevaluate the protein concentration, with bovine serum albumin as the standard.

#### *2.4. TGs Activity Assays*

TG activities were measured based on the protocol described by Liu et al. [9] with some modifications. After mixing 200 μL of phosphate buffer (50 mM, pH 6.0 or 7.0, optimal pH for various TGs) and 100 μL of enzyme-incorporating MDC (12.5 μM) and *N*,*N*dimethylcasein (0.2%), the enzymatic reaction was performed for 20 min at 50 ◦C or 60 ◦C (the optimum temperature for different TGs). The fluorescent intensity was recorded by the Fluorescence Spectrophotometer-Infinite 200PRO (Tecan, Austria) based on a previous study [8].

#### *2.5. Characterization of TGs*

The effect of pH on the activities of TGs was determined over the pH ranging from 5.0 to 9.0 under their optimum temperatures. The following buffer systems were applied in this work: citrate-phosphate buffer (50 mM, pH 5.0), phosphate buffer (50 mM, pH 6.0–8.0), and Tris-HCl buffer (50 mM, pH 9.0). After incubating the enzyme in the above-mentioned buffers at 4 ◦C for different times, the influence of pH on the stability of TGs was tested at pH = 5.0–9.0 by calculating the retained enzyme activity under standard conditions.

The optimum temperatures of TGs were ascertained by measuring the activities in the buffer of their optimal pH at differing temperatures of 30–80 ◦C. Thermostability was detected by keeping TGs in phosphate buffer (50 mM, pH 7.0) for various periods at 30–80 ◦C, and then calculating the residual activity.

#### *2.6. Molecular Dynamics Simulations*

The docking of TG (BCETG) from *B. cereus* TCCC 111006 with the substrate was conducted using AutoDock4.2.6 software [10]. After inputting the protein sequence of BCETG, the searching results were obtained on SWISS-MODEL (http://www.swissmodel. expasy.org (accessed on 7 January 2020)). We selected the 3D structure of TG from *B. subtilis* (BSUTG, PDB accession No. 4P8I) as the template for building the BCETG structure. In addition, we obtained the 3D structure of the MDC substrate from the PubChem Web site (http://pubchem.ncbi.nlm.nih. gov (accessed on 7 January 2020)). By observing the location of the BCETG active site (Cys117, Glu116, and Glu189), the volume of 60 Å × 60 Å × 60 Å was chosen for the center of the grid box to fit the ligand easily and cover the whole pocket of the active center. Then, MD simulation was carried out using the best conformation exhibiting the minimum binding energy for protein–substrate docking.

MD simulation was conducted with GROMACS 5.1.4 software in combination with the GROMOS96 54a7 force field parameters [11], using almost the same simulation parameters as those reported in detail [12,13]. The minimum distance of BCETG and the cube box edge was 15 Å under the periodic boundary conditions, and then water molecules filled in the box. The SPC/E model was utilized to describe water. The system was charged zero to replace the equivalent number of ions by using random water molecules. The simulation systems were optimized using the steepest decent method of 50,000 steps. Both short-range van der Waals (vdW) and electrostatic interaction (ELE) were easily truncated at 10 Å. Different temperature gradients (323 K and 353 K) were repeated in the isochoricisothermal (NVT) ensemble three times. The size of the mesh was 0.16 Å with the intercept at 12 Å. The external temperature and pressure baths were to couple MDC, protein and water molecules. In the end, each simulation was carried out for 100 ns while recording the coordinates every 2 ps.

The trajectory of the MD simulation was evaluated with the supplementary program in the GROMACS 5.1.4 software package (SciLifeLab, Stockholm, Sweden). The typical snapshots of the BCETG tertiary structures were obtained using the Visual Molecular Dynamics (VMD) 1.9.4 software [14].

#### *2.7. Protein Substrates Crosslinked by BCETG*

The BSA (1 mg/mL), SPI (8 mg/mL), and WP (1 mg/mL) solutions were made in sodium phosphate buffer (50 mM, pH 6.0). Then, the crosslinking was performed at 50 ◦C by mixing BCETG with protein in the concentrations of substrate (0.1, 0.03, 0.1 mg/mg) containing DTT (2 mM) for various periods (1–6 h). Finally, SDS-PAGE was utilized to characterize BCETG that catalyzed the crosslinking conditions of BSA, SPI, and WP for differing periods, as noted by Liu et al. [5,7,15].

#### *2.8. Analysis of Protein Substrate's Crosslinked Amino Acid Sites by BCETG*

The crosslinked sites in the crosslinked protein samples by BCETG were identified by liquid chromatography linked to the tandem mass spectrometry (LC-MS/MS) through analyzing the crosslinked peptides. After being boiled for 10 min to stop crosslinking, the protein samples that were crosslinked for 1 h were then denatured, reduced and digested with trypsin based on the previous method [8]. LC-MS/MS analysis was performed by a 1260 series HPLC coupled to an ESI-Q/TOF mass spectrometry (Agilent Technologies, Palo Alto, CA, USA) using the previously reported conditions [8]. The crosslinked peptides were identified and quantified using the software PLink 2 (The Institute of Computing Technology of the Chinese Academy of Sciences, Beijing, China) and the Masshunter B.08.00 of Agilent (Palo Alto, CA, USA), respectively, by processing the mgf data. The conditions used for the identification by the software PLink were as the following. Protein database: BSA for BSA protein, soybean proteins for SPI sample, and whey proteins for WP sample; protease: trypsin; variable modifications: methionine oxidation; fixed modification: cysteine carbamidomethylation; missed cleavages: no more than two; fragment ion tolerance: 50 ppm; precursor mass tolerance: 50 ppm.

#### **3. Results and Discussion**

#### *3.1. Molecular Cloning and Genes Sequence of bamtg, bcetg, bsatg, and bartg Genes*

The *bamtg*, *bcetg*, *bsatg*, and *bartg* genes showed an open reading frame of 735, 828, 738, and 813 bp, coding for a full-length protein of 244, 275, 245, and 270 amino acids with a theoretical molecular mass of 28.3, 31.4, 28.4, and 31.3 kDa (BAMTG, BCETG, BSATG, and BARTG), respectively. No signal peptide was found to locate at the N-terminus of the BAMTG, BCETG, BSATG, and BARTG after analysis using the Signal P program. The gene sequences were stored in the NCBI database, and the accession numbers of the *bamtg*, *bcetg*, *bsatg*, and *bartg* genes were MN537144, MW281568, MW292483, and MW916358, respectively. BAMTG, BCETG, BSATG, and BARTG showed 71.4%, 34.7%, 51.8%, and 38.3% of protein sequence identities with the reported BSUTG, respectively, after multiple amino acid sequence alignments (Figure S1). Meanwhile, they only shared ~10% identity with MTG. It suggested that they were probably the novel members of TG. As the first TG isolated from *Bacillus* species, BSUTG is produced to crosslink the highly resilient spore surface during sporulation [16]. In addition, it is the smallest TG produced as an

active single-domain protein. Furthermore, it functions via a peculiar partly redundant catalytic dyad containing Glu115 and Cys116 or Glu187. Comparative analysis of the primary sequences indicated that BAMTG, BCETG, BSATG, and BARTG contained the conserved amino acids correspondent to Glu115, Cys116, and Glu187 of BSUTG, which were considered to play a catalytic role. However, their amino acid sequences showed a significant homology with BSUTG, and especially MTG, which could cause differing characteristics and substrate preference from MTG and BSUTG.

#### *3.2. Heterologous Production and Purification of TGs*

The genes of *bamtg*, *bcetg*, *bsatg*, and *bartg* from *B. amyloliquefaciens* TCCC 111018, *B. cereus* TCCC 111006, *B. safensis* TCCC 111022, and *B. aryabhattai* TCCC 11368 in *E. coli* with a C-terminal 6 × His tag. The clear bands corresponding to the purified BAMTG, BCETG, BSATG, and BARTG were observed on the SDS-PAGE gel (Figure S2)

#### *3.3. Biochemical Characterization of BAMTG, BCETG, BSATG, and BARTG*

The profile of BARTG activity as a function of temperature variation indicated its optimum condition around 60 ◦C (Table 1), and BARTG displayed > 40% of its highest activity between 40 ◦C and 70 ◦C (Figure 1a). MTG only showed about 60% of its maximal activity at 60 ◦C and showed no activity at 70 ◦C, though it was most active at 55 ◦C [9]. Additionally, BAMTG, BCETG, and BSATG showed their maximal activity at 50 ◦C (Table 1, Figure 1a). MTG retained merely ∼20% of its initial activity after incubating at 50 ◦C for 100 min [9], but BAMTG, BCETG, BSATG, and BARTG retained about 100%, 100%, 60%, and 50% of their original activities after 120 min incubation at 50 ◦C, respectively (Figure 2a–d). These results verify that four TGs had better thermostabilities than MTG.

**Figure 1.** The optimum temperature and pH of recombinant TGs. (**a**) The influence of temperature on the BAMTG, BCETG, BSATG, and BARTG activities; (**b**) The influence of pH (5.0–9.0) on the activities of BAMTG, BCETG, BSATG, and BARTG. Three independent experiments were performed to calculate the values described by means ± SD.

BAMTG showed over 50% activity from pH 5.0 to 9.0, and its optimal pH was 7.0, but the optimal pH of BARTG, BCETG, and BSATG was 6.0 (Table 1, Figure 1b). By contrast, MTG showed no activity at pH 9.0 [9]. Moreover, BAMTG, BARTG, BCETG, and BSATG kept stable under an extensive pH range of 5.0 to 9.0, retaining approximately

100%, > 90%, > 80%, > 70% of the initial activity after incubation for 5 d between pH 5.0 and 9.0, respectively (Figure 3a–d), which was superior to MTG with a pH stability range of 5.0–8.0 [9]. These data indicate that these TGs could be a potential candidate for various biotechnological processes under acidic–neutral–alkaline conditions.

**Figure 2.** The thermostability of recombinant TGs. The effect of temperature on the stability of (**a**) BAMTG, (**b**) BCETG, (**c**) BSATG, and (**d**) BARTG. Three independent experiments were performed to calculate the values described by means ± SD.

**Figure 3.** The pH stability of recombinant TGs. The effect of pH on the stability of (**a**) BAMTG, (**b**) BCETG, (**c**) BSATG, and (**d**) BARTG. Three independent experiments were performed to calculate the values described by means ± SD.

As the most common enzyme applied for protein crosslinking, MTG is the only commercially available enzyme utilized in the food industry. However, the biological approach might be limited by the enzymatic properties. Hence, it could be essential to provide an extensive range of available TGs for crosslinking to the food processors. These four TGs demonstrated various temperature and pH ranges for their activities and stabilities, and these properties were clearly unlike that of MTG. Thus, they were beneficial for covering the disadvantages of MTG's properties in different types of food processing.

#### *3.4. Molecular Dynamics Simulation*

According to the optimum pH and temperature, the specific activities of BAMTG, BCETG, BSATG, and BARTG were determined to be 4.3, 176.8, 2.5, and 9.1 U/mg, respectively. BCETG exhibited the highest specific activity; however, its optimum temperature (50 ◦C) was unremarkable. Therefore, in order to investigate the reason for the low catalytic activity of BCETG at high temperatures, MD simulation was used to analyze the structural changes of BCETG at 323 K (50 ◦C) and 353 K (80 ◦C). Figure 4a shows the change in BCETG's root-mean-square deviation (RMSD) values at 50 ◦C and 80 ◦C as the function of simulation time (100 ns). It demonstrates that BCETG at 50 ◦C and 80 ◦C showed stabilized RMSD values after 80 ns, and BCETG showed a ~0.05 Å lower RMSD value at 50 ◦C than that at 80 ◦C, finally. This indicates that the structure of BCETG at 50 ◦C was more stable than that at 80 ◦C.

**Figure 4.** The structural changes of BCETG at 323 K and 353 K. (**a**) The root-mean-square deviation (RMSD) of BCETG at 323 K and 353 K. (**b**) The root-mean-square fluctuation (RMSF) value for each residue in BCETG at 323 K and 353 K.

During MD simulation, the root-mean-square fluctuation (RMSF) values of every amino acid residue at 50 ◦C and 80 ◦C were analyzed and represented to determine the sensitive part of BCETG with the increasing temperature (Figure 4b). Comparing to BCETG at 50 ◦C, the two regions of Trp83-Phe91 and Ala147-Ala156 exhibited an observable increase in RMSF values at 80 ◦C, suggesting that the two regions demonstrated enhanced flexibility from 50 ◦C to 80 ◦C. The Ala147-Ala156 region, which was adjacent to the Trp83-Phe91 region, was situated at one side of the substrate channeling tunnel of BCETG (Figure 5a,b). Leu88 and Trp150, which were both in the loop region, were the two typical residues demonstrating the largest enhancement of RMSF values in each region. As exhibited in Figure 5a,b, the two regions of Trp83-Phe91 and Ala147-Ala156 were closer to each other at 80 ◦C than 50 ◦C. However, the two regions were far from another region, Val177-Trp186 (the other side of the tunnel), resulting in the expansion of the tunnel entrance of the substrate MDC and the change in interaction between the active sites of BCETG and substrate MDC (Figure 5a,b). As suggested in Figure 5c, a short distance was discovered between the active center of BCTG and substrate MDC at the beginning of the MD simulation. Substrate MDC showed similar positions at 50 ◦C (Figure 5d) in the end. By contrast, substrate MDC was far from the active center of BCETG at 80 ◦C and moved into the inside of BCETG in the end (Figure 5e). In addition, it was clear that the

distance between MDC and BCETG's active center was enhanced with the temperature raising from 50 ◦C to 80 ◦C during 15–100 ns of MD simulation (Figure S3). At 80 ◦C, the distance was quickly enhanced to approximately 0.29 Å from an initial 0.25 Å, and subsequently fluctuated close to 0.36 Å, suggesting the removal of the substrate from the active center. Hence, the WT activity might be remarkably destroyed at 80 ◦C. Nevertheless, the distance kept stable in the process of the whole simulation at 50 ◦C, demonstrating the stable manifold structure of the BCETG and MDC. Therefore, we speculated that the conformation change of critical regions Trp83-Phe91 and Ala147-Ala156 at the high temperature indeed enlarged the substrate tunnel entrance, leading to the substrate MDC being 'beyond control'. This indicated that substrate MDC not only was far away from the active center of BCETG, but also entered into the BCETG's structure interior, leading to the decrease in catalytic activity of BCETG and the impediment of substrate MDC release and enzyme regeneration. Thus, the two Trp83-Phe91 and Ala147-Ala156 regions of BCETG could be modified to improve its high-temperature activity in future research.

**Figure 5.** The structural illustration of BCETG-MDC at (**a**) 323 K and (**b**) 353 K. (**a**) The front view for the conformation of BCETG-MDC at 323 K at the end of molecular dynamics simulation. (**b**) The

front view for the conformation of BCETG-MDC at 353 K at the end of molecular dynamics simulation. The Trp83-Phe91, Ala147-Ala156, and Val177-Trp186 regions are labeled in cyan, red, and magenta, respectively. The structure of BCETG is exhibited in gray. (**c**) The side view for the conformation of BCETG-MDC at the beginning of molecular dynamics simulation. (**d**) The side view for the conformation of BCETG-MDC at 323 K at the end of molecular dynamics simulation. (**e**) The side view for the conformation of BCETG-MDC at 353 K at the end of molecular dynamics simulation. The active center is colored in yellow. The structure of BCETG and MDC are shown in gray and cyan, respectively.

#### *3.5. Electrophoresis Analysis of Protein Substrates Crosslinked by BCETG*

SDS-PAGE was utilized to monitor the changes that occurred in the course of BSA, SPI, and WP treated with BCETG (Figure 6) for different times (1–6 h). A remarkable difference was noticed among the samples treated with various times. It was observed that a gradual loss of monomers simultaneously occurred with intensifying higher molecular-weight bands. However, some crosslinked proteins still stayed in the stacking gel and could not get into the resolving gel (Figure 6). As demonstrated in Figure 6a, the SDS-PAGE profiles of the BCETG-treated BSA samples were similar to that of MTG-treated samples [17–19]. The primary components of SPI (Figure 6b, lane 2) are 7S globulin, which is a trimer containing three subunits such as α, α , and β subunits (45 kDa to 116 kDa), and 11S globulin chiefly composed of basic subunits and acidic subunits (18.4–45 kDa). The results demonstrate that BCETG could crosslink almost all components in SPI (Figure 6b, lane 4–9). However, no BCETG preference was observed in the crosslinking reaction for the protein ingredients of SPI. However, the BS in 11S globulin was hardly crosslinked by MTG [15]. The untreated WP showed three main bands (∼14 kDa, ∼18 kDa, and ∼67 kDa) on the SDS-PAGE gel, matching α-la, β-lg, and BSA monomers, respectively (Figure 6c, lane 2). WPs crosslinked by BCETG resulted in the slow reduction in α-la, β-lg, and BSA amounts with the increasing incubation time, suggesting that BCETG could effectively catalyze the three components in WP (Figure 6c, lane 4–9). Nevertheless, α-la was the major substrate in WPI for MTG, which showed a weak capability of crosslinking β-lg and BSA [17,18,20]. These results indicate BCETG showed differing substrate preferences from MTG, which could be owing to the various structures of proteins. Hence, it suggested that BCETG and other *Bacillus* TGs would be potential candidates for supplementing MTG functions in the food-processing industry.

#### *3.6. Crosslinked Amino Acid Preference in Protein Substrates by BCETG Treatment*

So far, the crosslinking mechanism of TGs at the protein level has not been investigated; thus, it is difficult to obtain the real abilities of TGs to promote the crosslinking of proteins with different characteristics, as well as rationally modulate and control the functional properties of protein matrices. Hence, the application of TG in food processing could be benefited by revealing the crosslinked sites in proteins. LC-MS/MS was utilized to determine the crosslinked sites in BSA, SPI, and WP by BCETG through identifying the crosslinked peptides. BCETG-treated BSA was taken as an example, and the characterization results of ADEKKFWGK and QNCDQFEK peptides are demonstrated in Figure S4. Figure S4a shows the extraction ion chromatogram of the crosslinked peptide ADEKKFWGK-QNCDQFEK and the uncrosslinked QNCDQFEK. However, uncrosslinked ADEKKFWGK was not observed. The mass spectra of the ADEKKFWGK-QNCDQFEK and QNCDQFEK peptides are presented in Figure S4b,c, respectively. The mass obtained from the experiment was consistent with the calculated theoretical monoisotopic mass.

Only a few Q and K sites were crosslinked in BSA, SPI, and WP. Figure 7 exhibits the investigation of crosslinked sites of BCETG-treated BSA, SPI, and WP. Figure 7a–c demonstrates the five most plentiful crosslinked peptides from BCETG-treated proteins. It was obvious that only a smaller number of them showed higher abundance than others, indicating that BCETG had remarkable site preference on crosslinking these proteins. Figure 7d–f presents the most plentiful crosslinked sites in the protein materials. As suggested in Figure 7d, the favorite cross-linking sites of BCETG were Q (118), K (156), Q (413), K (235) and K (245) on BSA. As exhibited in Figure 7e, the five favorite crosslinking sites of BCETG on soybean proteins were Seed linoleate 13S-lipoxygenase-1's K (250), Seed linoleate 13S-lipoxygenase-1's Q (322), P24 oleosin isoform B's Q (180), Glycinin G4's K (535), and P34 probable thiol protease's K (119), which were from differing SPI protein ingredients. As demonstrated in Figure 7f, the four favorite crosslinking sites of BCETG on WP were found in BSA, such as K (155), K (244), Q (603), and K (160), and some were distinct from those from BSA. The possible reason should be that BSA could be crosslinked with other protein constituents in WP. Additionally, one preferred crosslinked site of BCETG on WP were K (133), which was from α-lactalbumin. Figure 7g–i suggested that these sites were mostly on the surface of BSA, SPI, and WP. Based on the above results, the internal crosslinking mode of BCETG at the protein level could help to estimate its crosslinking ability and regulate its applied manner.

**Figure 7.** The crosslinking sites in the crosslinked BSA, SPI, and WP were analyzed by BCTG. (**a**) Five of the most plentiful peptides crosslinked in BSA were A (QEPER-FGERALKAWSVAR),

B (ADEKKFWGK-QNCDQFEK), C (LSQKFPK-ATEEQLK), D (QEPER-ADEKKFWGK), and E (QNCDQFEK-TPVSEKVTK). (**b**) The five most plentiful peptides crosslinked in SPI were F (Glycinin G4/QQLQDSHQKIR-Seed linoleate 9S-lipoxygenase-2/KDQNSEK), G (Seed linoleate 13S-lipoxygenase-1/TDGQHILK-P34 probable thiol protease/DVSQQIKMANKK), H (Glycinin G4/AKSSSR-β-conglycinin alpha subunit 1/QSQVSELK), I (Glycinin G2/GRSQRPQDRHQK-Seed linoleate 9S-lipoxygenase/PLANGKGKVGK), and J (Glycinin G5/SQQQLQDSHQK-β-conglycinin alpha subunit 1/SSSRKTISSEDKPFNLR). (**c**) The five most plentiful peptides crosslinked in WP were: K (BSA/QEPER-ADEKKFWGK), L (α-lactalbumin/ALCSEKLDQWLCEK-BSA/LVVSTQTALA), M (β-lactoglobulin/TPEVDDEALEKFDK-BSA/NYQEAK), N (BSA/ADEKK-ALKAWSVARLSQK), and O (BSA/FWGKYLYEIARR-AWSVARLSQK). (**d**) The five most plentiful sites crossllinked in BSA: Q (118), K (156), Q (413), K (235), and K (245). (**e**) The five most plentiful sites crosslinked in SPI: Seed linoleate 13S-lipoxygenase-1/K (250), P24 oleosin isoform B/Q(180), Seed linoleate 13S-lipoxygenase-1/Q (322), P34 probable thiol protease/K (119), Glycinin G4/K (535). (**f**) The five most plentiful sites crosslinked in WP sample: BSA/K (244), α-lactalbumin/K (133), BSA/Q (603), BSA/K (155), and BSA/K (160). (**g**) The sites crosslinked in the tertiary structure of BSA containing K (28), Q (118), K (156), K (160), K (204), Q (219), Q (227), K (235), Q (244), K (245), K (303), Q (343), Q (413), K (463), K (495), K (557), and Q (566). (**h**) The sites crosslinked in the SPI-β-conglycinin alpha subunit 1 containing K (382) and K (397). (**i**) The sites crosslinked in the tertiary structure of WP-α-lactalbumin containing K (133).

#### **4. Conclusions**

In brief, four novel TGs demonstrating better thermostability and pH stability than MTG were exploited from *Bacillus* strains, which could offer different options for various food-processing processes. A structural analysis indicated that the Ala147-Ala156 region in the substrate tunnel of BCETG was related to its high temperature adaptability, which could be modified in further research. Furthermore, BCETG exhibited better preference for the protein constituents in SPI and WP than MTG, and the crosslinking mode of BCETG towards BSA, SPI, and WP displayed the intramolecular and intermolecular crosslinked path of glutamine and lysine in food protein substrates. Hence, novel protein crosslinking enzymes were provided in this study, which enhanced the understanding of the structure– activity relationship in new TGs associated with a high temperatures and further promoted its applications in food industry.

**Supplementary Materials:** The following supporting information can be downloaded at https:// www.mdpi.com/article/10.3390/foods11223722/s1. Table S1. Primers used in this study. Figure S1. Multiple alignments analysis of protein sequences for BAMTG, BCETG, BSATG, and BARTG with software DNAMAN. The similar amino acids were labeled in grey and the identical amino acids were highlighted in solid black. The active sites were presented in yellow color. Figure S2. The purified rTGs analyzed using SDS-PAGE. (a) Purified BAMTG. (b) Purified BCETG. (c) Purified BSATG. (d) Purified BARTG. Lane M: Standard protein ladder; Lane 1: purified BAMTG, BCETG, BSATG, and BARTG. Figure S3. Distance between the active center of BCETG and MDC as a function of time (100 ns) at 323 K and 353 K. Figure S4. LC-MS evaluation of the cross-linked peptides of ADEKKFWGK and QNCDQFEK from cross-linked BSA. (a) EIC of the cross-linked peptides ADEKKFWGK-QNCDQFEK and QNCDQFEK. (b) Mass spectrum of cross-linked peptide ADEKKFWGK-QNCDQFEK. (c) Mass spectrum of peptide QNCDQFEK.

**Author Contributions:** H.W.: Conceptualization, Validation, Formal analysis, Writing—original draft. Y.Z.: Formal analysis, Investigation, Writing—original draft. Z.Y.: Investigation. X.Z.: Investigation. Y.J.: Investigation. J.H.: Investigation. J.Z.: Conceptualization, Investigation. F.L.: Conceptualization, Formal analysis. Y.L.: Conceptualization, Formal analysis, Resources, Writing—review and editing, Supervision, Project administration, Funding acquisition. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by the National Key Research and Development Program of China (2021YFC2100300) and the Tianjin Key-Training Program of "Project and Team" of China (XC202032).

**Data Availability Statement:** The data used to support the findings of this study can be made available by the corresponding author upon request.

**Conflicts of Interest:** There are no conflicts to declare.

#### **References**

## *Article* **The Loading of Epigallocatechin Gallate on Bovine Serum Albumin and Pullulan-Based Nanoparticles as Effective Antioxidant**

**Zikun Li 1, Xiaohan Wang 1, Man Zhang 1, Hongjun He 1, Bin Liang 2,\*, Chanchan Sun 1,\*, Xiulian Li 3 and Changjian Ji 4**

**Abstract:** Due to its poor stability and rapid metabolism, the biological activity and absorption of epigallocatechin gallate (EGCG) is limited. In this work, EGCG-loaded bovine serum albumin (BSA)/pullulan (PUL) nanoparticles (BPENs) were successfully fabricated via self-assembly. This assembly was driven by hydrogen bonding, which provided the desired EGCG loading efficiency, high stability, and a strong antioxidant capacity. The encapsulation efficiency of the BPENs was above 99.0%. BPENs have high antioxidant activity in vitro, and, in this study, their antioxidant capacity increased with an increase in the EGCG concentration. The in vitro release assays showed that the BPENs were released continuously over 6 h. The Fourier transform infrared spectra (FTIR) analysis indicated the presence of hydrogen bonding, hydrophobic interactions, and electrostatic interactions, which were the driving forces for the formation of the EGCG carrier nanoparticles. Furthermore, the transmission electron microscope (TEM) images demonstrated that the BSA/PUL-based nanoparticles (BPNs) and BPENs both exhibited regular spherical particles. In conclusion, BPENs are good delivery carriers for enhancing the stability and antioxidant activity of EGCG.

**Keywords:** bovine serum albumin; pullulan; epigallocatechin gallate; nanoparticles; antioxidant activity

#### **1. Introduction**

Previous studies have shown that catechins have antioxidant effects [1] and that they are highly effective natural antioxidants with low toxicity [2]. Furthermore, they also have anticancer [3], anti-obesity [4], and anti-inflammatory properties [5]. Catechins contain three basic ring nuclei—A, B and C—that form a D ring after esterification. According to the different groups connected to the B and C rings, common catechins can be divided into four forms, which can be divided as follows: epicatechin (EC), epigallocatechin (EGC), epicatechin gallate (ECG), and epigallocatechin gallate (EGCG) [6]. Among them, EGCG has the highest content, accounting for approximately 70% of the total catechins. The molecular structure of EGCG contains eight monophenolic hydroxyl groups and it is the most active catechin.

Although EGCG has various beneficial health effects, its application in pharmaceuticals and nutritional supplements is very limited, mainly due to its low bioavailability [7]. In addition, reactions such as oxidation and polymerization can occur easily under conditions such as high temperatures and high humidity, and it can be easily decomposed in neutral and alkaline physiological environments [8]. The hydrophobic benzene ring and more than five hydrophilic hydroxyl groups in the molecule make EGCG both hydrophilic and lipophilic. However, the solubility of EGCG is poor. Its low solubility and poor stability lead to its low bioavailability [9]; however, these problems can be effectively solved by nano-delivery systems.

**Citation:** Li, Z.; Wang, X.; Zhang, M.; He, H.; Liang, B.; Sun, C.; Li, X.; Ji, C. The Loading of Epigallocatechin Gallate on Bovine Serum Albumin and Pullulan-Based Nanoparticles as Effective Antioxidant. *Foods* **2022**, *11*, 4074. https://doi.org/10.3390/ foods11244074

Academic Editors: Fuping Lu and Wenjie Sui

Received: 12 October 2022 Accepted: 8 December 2022 Published: 16 December 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Nanoparticles are fine microparticles with more than one dimension, and they are between 1–100 nm in size. Furthermore, they are generally composed of natural macromolecular substances or synthetic macromolecular substances. They can be used as carriers for conducting or delivering active substances and drugs. Embedding small-molecule active substances or drugs in nanoparticles can alter their release rate, increase the permeability of their biofilms, and improve their bioavailability [10].

The use of bovine serum albumin (BSA) to prepare nanoparticles as carriers has been gradually gaining attention. Due to the special heart-shaped structure of BSA, a large number of hydrophobic amino acids are concentrated inside it, which form a hydrophobic inner core and a hydrophilic outer shell. This structure allows BSA to interact with both hydrophilic and hydrophobic small molecules [11]. BSA is widely used as a drug carrier due to its non-antigenicity, its degradability, and its nontoxicity [12], in spite of its allergenic disadvantage [13].

Pullulan (PUL) is a natural, degradable macromolecular polymer that is nonhazardous and has been widely used in many fields [14]. PUL contains three hydroxyl groups in each glucose unit and has good solubility in aqueous solutions. Its aqueous solution is stable and less dense than other water-soluble polysaccharides and is not affected by temperature, pH, or most metal ions. Thus, PUL is often used as a food additive [15]. It is widely used in food processing because of its high non-immunogenicity [16], non-carcinogenicity [17], and biocompatibility [18].

In this context, an attempt was made to encapsulate EGCG into a BSA-PUL nanoparticulate (BPNs) system to retain or enhance its antioxidant potential. The objectives of this study were as follows: (1) to investigate the particle size, the polydispersity index (PDI), zeta potential, and thermal stability of BSA or BSA-PUL complexes prepared at different ratios of BSA and PUL or with different pH solutions; (2) to study the encapsulation efficiency and loading rate of EGCG-loaded BPNs (BPENs); (3) to determine the effect of EGCG concentrations on the antioxidant activity and to release the capacity of BPENs in vitro; and (4) to characterize the structures of BPNs and BPENs using Fourier transform infrared spectra (FTIR) and a transmission electron microscope (TEM).

#### **2. Materials and Methods**

#### *2.1. Materials*

Bovine serum albumin (BSA), epigallocatechin gallate (EGCG), anhydrous ferric chloride, potassium ferricyanide, ferrous ammonium sulfate hexahydrate, salicylic acid, trichloroacetic acid, 1,1-diphenyl-2-Picrylhydrazine (DPPH), and 2,2 -Diaza-bis-3 ethylbenzothiazoline-6-sulfonic acid (ABTS) were obtained from Shanghai Macklin Biochemical Co., Ltd. (Shanghai, China). Pullulan (PUL) was purchased from Shanghai Yien Chemical Technology Co., Ltd. (Shanghai, China). Hydrogen peroxide (purity ≥ 30%), potassium dihydrogen phosphate, dipotassium hydrogen phosphate, absolute ethanol, hydrochloric acid, and sodium hydroxide were purchased from China National Medicines Corporation Ltd. (Shanghai, China).

#### *2.2. Preparation and Characterization of BPNs*

#### 2.2.1. Preparation of BPNs

First, 0.25 g of BSA and 0.25 g of PUL were dissolved in 50 mL of deionized water. After complete dissolution, the solution was placed in a refrigerator at 4 ◦C overnight to fully hydrate.

The 5 mg/mL PUL stock solution was diluted to the following three concentrations: 2.5 mg/mL, 1 mg/mL, and 0.5 mg/mL. Equal volumes of 5 mg/mL BSA solution and four concentrations of PUL (5 mg/mL, 2.5 mg/mL, 1 mg/mL, and 0.5 mg/mL) were mixed. Finally, the ratios of BSA/PUL were 1:1, 2:1, 5:1, and 10:1 (all of the BSA concentrations were 2.5 mg/mL). The mixtures of each ratio were adjusted to pH 4.5, 5.0, 5.5, 6.0, 6.5, and 7.0, with 0.01 M hydrochloric acid and 0.01 M sodium hydroxide solution. Next, the solution

was incubated overnight to enable it to become completely mixed and homogeneous. The preparation of BPNs is shown in Figure 1(1).

Samples with different BSA-PUL ratios were called BPNs (1:1), BPNs (2:1), BPNs (5:1), and BPNs (10:1).

#### 2.2.2. Determination of Particle Size, PDI, and Zeta-Potential of BPNs

The particle size and distribution of the samples were determined with a particle size analyzer (90Plus Zeta, BIC, NYC, USA). All determinations were performed using three batches of the samples, and the results are expressed as mean ± standard error.

#### 2.2.3. Thermal Stability

The BSA and BPNs solutions with different ratios and pH levels were heated at 80 ◦C for 30 min and then cooled to room temperature in ice water [19]. The turbidity (OD600) of the BSA and BPNs solutions with and without a heating treatment was measured using a UV spectrophotometer (UV-2500, Shimadzu, Shanghai, China). The turbidity curves were plotted with the change in turbidity (OD600) as the dependent variable and the change in pH as the independent variable to characterize the thermal stability of the BSA and BPNs.

#### *2.3. Preparation and Characterization of EGCG-Loaded BPNs (BPENs)*

#### 2.3.1. Preparation of BPENs

Different concentrations (0.5 mg/mL, 1.0 mg/mL, 1.5 mg/mL, 2.0 mg/mL, and 2.5 mg/mL) of EGCG solutions were added to the BPNs solution, which was prepared under optimum conditions. The EGCG solution was mixed thoroughly with the protein solution, and then it was mixed with the polysaccharide solution. After adjusting the dispersion to the desired pH, using a 0.1 M hydrochloric acid solution or sodium hydroxide solution, the samples were left overnight and lyophilized. The preparation of BPENs is shown in Figure 1(2).

In this paper, the samples loaded with different concentrations of EGCG are called BPENs (0.5), BPENs (1.0), BPENs (1.5), BPENs (2.0), and BPENs (2.5).

#### 2.3.2. Encapsulation Efficiency and Loading Rate

The BPEN solutions were centrifuged at 3500× *g* for 30 min. The free EGCG in the clear supernatant was measured according to the vanillin–hydrochloric acid colorimetric method. The measurement of EGCG was determined by the absorbance method at 285 nm, and the standard curve is presented in Figure S1. All analyses were performed using three batches of the samples. The results were calculated according to Equations (1) and (2) [20]:

$$\text{Encapsulation efficiency } (\%) = \left( 1 - \frac{\text{The amount of free EGCG}}{\text{The amount of total EGCG}} \right) \times 100\% \tag{1}$$

$$\text{Loading rate} \left(\text{mg EGCG/mg BSA}\right) = \frac{\text{Encapsulated EGCG amount}}{\text{Total BSA amount}} \tag{2}$$

#### 2.3.3. DPPH Scavenging Assay

We modified this assay slightly according to the method used by Tang et al. [21]. We added 2 mL of the sample solutions to the 2 mL of 0.2 mM DPPH% ethanol solution. The reaction mixture was incubated for 30 min on a shaker at room temperature in a dark place. The absorbance of the reaction solution was recorded at 517 nm, using a UV spectrophotometer (UV-2500, Shimadzu, Shanghai, China). The DPPH scavenging activity (%) was calculated using Equation (3), as follows:

$$\text{DPPH scavenging activity } \left( \% \right) = \frac{\left( \text{A}\_0 - \text{A}\_i \right)}{\text{A}\_0} \times 100\% \tag{3}$$

where A0 is the absorbance of the DPPH solution after reacting with deionized water, and Ai is the absorbance of the DPPH solution after reacting with the sample.

#### 2.3.4. ABTS+ Scavenging Assay

The method was slightly changed with reference to Wang et al. [22]. ABTS powder was dissolved in deionized water to prepare a 7 mM ABTS solution. Potassium persulfate was dissolved in a 75 mM phosphate buffer solution (PBS) at pH 7.4 to prepare a 4.9 mM potassium persulfate solution. Next, ABTS+ was generated by the equal volume oxidation of the ABTS solution and the aforementioned potassium persulfate solution. Next, the ABTS+ solution was diluted with PBS to the absorbance value of 0.70 ± 0.02 (λ = 734 nm). Finally, 0.2 mL of the sample solutions were added to 4 mL of the ABTS+ solution and mixed thoroughly. Immediately after incubation in the dark for 15 min, the absorbance of the reaction mixture was recorded at 734 nm. The ABTS+ scavenging activity was calculated using Equation (4), as follows:

$$\text{ABTS}^+ \text{ scavenging ansatz} \left( \% \right) = \frac{\text{A}\_0 - \text{A}\_i}{A\_0} \times 100\% \tag{4}$$

where A0 represents the absorbance value of the ABTS+ solution after reacting with deionized water, and Ai represents the absorbance of the ABTS+ solution after reacting with the samples.

#### 2.3.5. Ferric-Reducing Antioxidant Power (FRAP) Assay

This experiment was carried out with reference to the method of Liu et al. [23]. We added 30 μL of the BPENs solution and 2.5 mL of 10 g/L potassium ferricyanide to 2.5 mL of PBS (0.2 mol/L, pH 6.6). The mixed samples were put into thermostatic water for 15 min at 37 ◦C. After adding 2.5 mL of 100 g/L trichloroacetic acid, 2.5 mL of the supernatant was taken after standing. Next, 2.5 mL of deionized water and 0.5 mL of 1 g/L FeCl3 were added to the supernatant, and, subsequently, the absorbance was measured at 700 nm.

#### 2.3.6. Hydroxyl Radicals (OH) Scavenging Assay

The hydroxyl radical (OH) was generated by a Fenton reaction model system, and the scavenging activity of the nanoparticles was determined following the procedures of Yang et al. [24]. We mixed 1.0 mL of 9 mmol/L ammonium ferrous sulfate and 1.0 mL of a 9 mmol/L salicylic acid–ethanol solution and left the solution for 10 min. We added 1.0 mL of an 8.8 mmol/L H2O2 solution and 1.0 mL of the BPENs solutions to the above solution. After mixing evenly, the mixture was placed at 37 ◦C to react for 1 h. Subsequently, the absorbance was measured at 510 nm. The ·OH scavenging activity was calculated using Equation (5), as follows:

$$\text{Hydroxyl radical scanning rate } (\%) = \text{A}\_0 - \frac{\text{A}\_{\text{i}} - \text{A}\_{\text{i0}}}{\text{A}\_0} \times 100\% \tag{5}$$

where A0 is the absorbance of the ·OH solution after reacting with deionized water, Ai is the absorbance of the ·OH solution after reacting with the BPENs solutions, and Ai0 represents the absorbance of the ·OH solution after reacting with the BPENs solutions, without H2O2.

#### 2.3.7. In Vitro Release Behavior

The in vitro release behaviors of BPENs with different EGCG contents were studied using the dynamic dialysis method in deionized water [25]. Briefly, the dispersion of BPENs in distilled water was placed into dialysis tubing (molecular weight cut-off 8–14 kDa, Solarbio Science and Technology Co., Ltd., Beijing, China) and dialyzed against deionized water at 37 ± 0.2 ◦C in an air-bath shaker at 120 rpm. At predefined time intervals, 4 mL of the release media were collected, and the fresh release media were added. The cumulative percentage of EGCG released was determined at 285 nm and calculated using Equation (6), as follows:

$$\text{The cumulative percentage of EGCG released} = \frac{\sum\_{i=1}^{13} \text{C}\_{i} [\text{V}\_{2} - (\text{i} - 1)\text{V}\_{1}]}{W} \tag{6}$$

where Ci is the concentration of EGCG in the released medium obtained in time i, mg/mL; V1 is the volume of the release media, 4 mL; and V2 is the volume of dialysis deionized water, 200 mL.

#### 2.3.8. Fourier Transform Infrared Spectra (FTIR) Analysis

All samples (BPNs, BPENs, BSA, and PUL) were freeze-dried and fully mixed with 200 mg of KBr and pelletized [26]. Spectrum scanning was taken in the wavelength range of 4000–400 cm−1, at a resolution of 4 cm−1, and with a scan speed of 2 mm/s, using a Fourier transform infrared spectrometer (FTIR, VERTEX70, Bruker, Germany).

#### 2.3.9. Morphological Observation of BPNs and BPENs

The freshly prepared samples were dropped onto the copper mesh, and the morphology of the BPNs and BPENs were observed using a transmission electron microscope (TEM, TECNAI F20, FEI Company, HIO, OSU, Columbus, OH, USA) after drying.

**Figure 1.** The preparation process of BPNs (**1**) and BPENs (**2**).

#### 2.3.10. Statistical Analysis

All the tests were repeated in triplicate, and the data are expressed as the means ± SDs (standard deviations). A one-way analysis of variance (ANOVA) and significant difference tests were performed using SPSS 27.0 software. Significant differences were determined with an independent sample *t*-test or Duncan's multiple-range tests, at *p* = 0.05. Mean differences were considered significant when *p* < 0.05.

#### **3. Results and Discussion**

#### *3.1. Particle Size and Zeta-Potential of BPNs*

The results of the particle size of the nanoparticles are summarized in Table 1. It can be seen from Table 1 that the pH level had a significant effect on the particle size of the BPNs. As the pH deviated from the isoelectric point, the particle size first decreased and then increased, probably because they were in a neutral environment [27], which led to some particle aggregation. In addition, as shown in Table 1, the different BSA/PUL ratios had a significant effect on the particle size of the BPNs. The particle size of the BPNs at each pH was the smallest when the BSA/PUL ratio was 1:1. As the BSA/PUL ratio increased, the particle size of the BPNs also increased. This can be mainly attributed to the decrease in the concentration of PUL, which led to the rapid nucleation of the BSA at different rates, which, in turn, resulted in the formation of larger and more uneven particles [27]. Therefore, the optimal ratio of BSA/PUL was 1:1.