*Article* **Transcriptional Stages of Conidia Germination and Associated Genes in** *Aspergillus flavus***: An Essential Role for Redox Genes**

**Chong Li 1, Sifan Jia 1, Shahid Ali Rajput 2, Desheng Qi 1,\* and Shuai Wang 1,\***


**Abstract:** Aflatoxin is a threatening mycotoxin primarily present in the agricultural environment, especially in food and feedstuff, and poses significant global health risks. Aflatoxins are produced mainly by *Aspergillus flavus*. Conidia germination is the first step for *A. flavus* development. In this study, the transcriptome of *A. flavus* conidia was analyzed at three different stages of conidia germination, which were characterized by two different microscopes. Dormant conidia grew isotropically with the cell size increasing up to 5 h of after being inoculated in a liquid medium. Conidia changed towards polarized growth from 5 to 10 h of germination, during which germ tubes formed. Moreover, transcriptome analyses revealed that a larger number of genes changed in the isotropic growth stages compared to polarized growth, with 1910 differentially expressed genes (DEGs) up-regulated and 969 DEGs down-regulated in isotropic growth. GO and KEGG pathway analyses and pathway enrichment demonstrated that, in the isotropic growth stage, the top three pathways were translation, amino acid and carbohydrate metabolism. The ribosome was a key pathway in translation, as *RPS28e*, *RPL53* and *RPL36e* were the top three DEGs. For polarized growth stage, lipid metabolism, amino acid metabolism and carbohydrate metabolism were the top three most active pathways. *POX1* from alpha-linolenic acid metabolism was a DEG in lipid metabolism as well. Genes related to the antioxidant system were crucial for conidia germination. Furthermore, RT-PCR results showed the same trends as the transcriptome for redox genes, and essential oils have a significant inhibitory effect on germination rate and redox gene expression. Therefore, redox genes play an important role during germination, and the disruption of redox genes is involved in the mechanism of action of coumalic acid and geraniol against *A. flavus* spore germination.

**Keywords:** *Aspergillus flavus*; conidia; germination; transcriptome; redox genes

**Key Contribution:** We have demonstrated the morphological changes, transcriptome changes, the key pathways and genes during two stages of Aspergillus. Flavus conidia germination. This study highlights that the redox genes could be a potential target to inhibit conidia germination.

### **1. Introduction**

The mycotoxin contamination of food and agricultural products is a significant threat towards human and animal health and causes enormous economic losses [1]. In particular, aflatoxins are common and one of the most toxic substances in the world [2]. Aflatoxins, including AFB1, AFB2, AFG1 and AFG2, are characterized as class A carcinogens by the International Agency for Research on Cancer [3]. *Aspergillus flavus* is one of the primary fungi that produces aflatoxins [4].

Mature *Aspergillus.* spp. produce billions of single-celled dormant conidia that are found all over the world, including in the desert, polar regions or other severe environmental conditions that are not suitable for living [5]. *A. flavus* is not only associated with food and feed spoilage but also acts as an opportunistic pathogen in plants and animals [6–8].

**Citation:** Li, C.; Jia, S.; Rajput, S.A.; Qi, D.; Wang, S. Transcriptional Stages of Conidia Germination and Associated Genes in *Aspergillus flavus*: An Essential Role for Redox Genes. *Toxins* **2022**, *14*, 560. https:// doi.org/10.3390/toxins14080560

Received: 5 July 2022 Accepted: 12 August 2022 Published: 18 August 2022

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**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/).

Conidia are the main vehicles of distribution for *A. flavus* and are reproductive structures; they are characterized by a dormant state that is essential for survival in hostile conditions [9,10]. Air-dispersed conidia are highly resistant to extreme environments and can remain viable for several years and begin to germinate as soon as they are in hospitable environmental conditions and in the presence of nutrients such as fermentable sugars, inorganic salts and a nitrogen source [11,12]. Therefore, understanding the process of *A. flavus* conidia germination is important for food and feed safety.

The germination of a fungal spore is also an important way for target organisms to be infected during the spoilage of food and feed. Dormant conidia have irregular spherical shapes. Upon the activation of germination, water uptake leads to an increase in intracellular osmotic pressure [13]. For *Aspergillus niger*, during this stage, the first morphological change in conidia germination involves swelling, with the diameter of the spore increasing two-fold or more. The swelling phase of conidia is also called isotropic growth [14]. Swelling is concomitant with many metabolic activities such as respiratory metabolism, amino acid biosynthesis, protein biosynthesis, and so on [15]. Swollen conidia are followed by polarized growth that leads to germ-tube formation. During this phase, the formation of a germ tube is also called polarized growth. A large number of metabolism activities are the same as those found in isotropic growth, and only some special metabolic activities, such as cytoskeleton formation, the vesicle trafficking system and landmark protein, are different [16]. Next, conidia complete germination when the length of the germ tube is equal to the half of the diameter of the spore. At later stages of development, the germ tube grows faster and faster and branching leads to agglomeration, mutually resulting in fungus hypha accumulation. During this phase, the secondary metabolite aflatoxins are major secreted from hypha [17].

RNA-Seq technology has been widely used in microbiology research for investigating the dynamic changes in RNA expression, including conidia germination, mycotoxin biosynthesis, environmental stress response, nutrient metabolism and so on [5,18–20]. In this study, the germination rate of *A. flavus* conidia at different times was analyzed to determine the various stages of conidia germination. Subsequently, we used different microscopes to study the morphological changes of *A. flavus* conidia during germination on Czapek–Dox (CZ) culture medium. Then, RNA-Seq technology was used to identify transcriptomic changes in developing conidia involved in various *A. flavus*, and the molecular functions of differentially expressed genes (DEGs) and their metabolic pathways were analyzed using bioinformatic methods. Most changes in the transcriptome occurred during the early phase of germination. The data showed that the transcriptome of the dormant spore is very different from that of conidia during all germination phases. Our study focused on the different changes on translation, carbohydrate and lipid metabolism.

#### **2. Results**

#### *2.1. Conidia Germination Rate*

Conidia germination of *A. flavus* has a maximal rate between 28 and 30 ◦C. In this study, *A. flavus* spores were inoculated in CZ culture medium at 30 ◦C, with approximately 50% conidia germination after 10 h (Figure 1a). Isotropic growth (swelling phase) was observed before 5 h after inoculation, and polarized growth (germ tube forming) occurred at 5 h and 10 h (Figure 1b). The cell size of dormant conidia was about 3 × 4 μm, but in the isotropic growth stage, the cell size was much larger than dormant conidia. The morphology of the swelling conidia was different with the dormant conidia, with wrinkle recoveries and flat cell walls. In the polarized growth stage, conidia completed germination when the length of the germ tube was equal to the conidia' radius, and some conidia had more than one germ tube.

**Figure 1.** (**a**) Conidia germination rate of *A. flavus* in CZ culture medium. (**b**) Germination of *A. flavus* conidia as observed by SEM. Microscope images are shown for dormant conidia (0 h) and germinating conidia at 5 h and 10 h, respectively. Bar represents 10 μm, 4 μm and 5 μm (10 h). <sup>a</sup> Columns with different lowercase letters indicated significant differences between the compared groups (*p* < 0.05).

#### *2.2. Flow Cytometry*

Conidial samples were prepared and analyzed by flow cytometry over a 10 h period to measure the increase in the size of dormant conidia harvested with PDA. The Flowjo software provided numerical values for the FSCs of the conidial and generated a graph (Figure 2). The counts of conidia demonstrated that evident isotropic growth expansion occurs over the first few hours of germination, and polarity formation and germ tube emergence were also apparent between 5 and 10 h.

#### *2.3. Transcriptional Profiling*

In this study, nine samples of *A. flavus* NRRL 3357 were sequenced using RNA-Seq technology, averaging 24,136,399 raw sequencing reads and 24,125,185 clean reads after filtering out low quality reads. Table 1 briefly summarizes the information of sequencing data for each sample.

#### *2.4. Gene Expression*

Gene expression levels were quantified by a software package called RSEM. The number of identified expressed genes was counted and calculated in proportion to the total gene number in the database for each sample in Figure 3a. Dormant conidia averaged 10,966 transcripts. The number of expressed genes increased to 11,656 5 h after inoculation and then gradually increased to 11,702 10 h after germination. According to principal component analysis (PCA) analysis (Figure 3b), the dormant conidia sample differed from all other time points in that it contributes to the majority of the first principal component while the variation in the other time points was predominantly confined to the second principal component. The correlation of expressions (Figure 3c) showed that the RNA profile of dormant conidia was the most different when compared to other samples.

**Figure 2.** The differences in size of conidia germination under three different stages. The *x*-axis indicates forward scatter (FCS), and the y-axis indicates counts of profiles of 10,000 conidia at 0 h, 5 h and 10 h (**a**). Average size of 10,000 conidia measured as the FSC parameter (**b**). The means and standard errors of duplicate samples have been plotted (*n* = 3). The"\*"on column diagram indicate a statistically difference of treatment at "\*\*\*"means *p* < 0.001.

**Table 1.** Statistical summary of the different conidia RNA-Seq datasets.


<sup>1</sup> Clean Data Rate (%) = Clean Reads Number/Raw Reads Number.



**Figure 3.** The number of expressed genes (**a**) during germination of *A. flavus* and the similarity of the RNA profiles of the different stages of germination represented by principal component analysis (**b**) and correlation coefficients (**c**).

#### *2.5. Differential Gene Expression and Functional Analysis*

The results of the differential gene expression analysis revealed that were many germination responsive genes existing in the spore (Figure 4). Compared to dormant conidia, 1910 genes were up-expressed and 969 genes were down-expressed with a two-fold change or greater (*p* < 0.05). Meanwhile, a number of differentially expressed genes were much lower between the 5 h and 10 h time points. Genes numbering 321 were up-regulated between 5 h and 10 h, whereas 80 genes were down-regulated.

**Figure 4.** Overview of the global changes in the transcriptome of conidia during germination. Inside the spore, the number of expressed transcripts is provided. Green and red represent numbers of genes with fold change ≥2 up-regulated and down-regulated between two stages, respectively.

Moreover, compared to dormant and 5 h conidia, GO analysis results indicated that 726 DEGs, accounting for 27.13% of all significant DEGs, were associated with cellular compounds; 1297 DEGs, accounting for 22.32% of all significant DEGs, were annotated with molecular functions; 1207 DEGs, accounting for 22.96%, were classified with biological processes. The groups in the three main categories are shown in Figure 5a. Within the biological process category, the most highly represented groups were metabolic processes, cellular processes, single-organism processes and localization. In the cellular component, cells, cell parts, organelles, membranes and macromolecular complexes were the most abundant groups. Meanwhile, binding, catalytic, structural molecular activity, transport activity and nucleic-acid-binding transcription factor activity were the largest terms with respect to molecular functions. Likewise, the results of GO analysis revealed that metabolic processes, single-organism processes and cellular processes are the most abundant terms between the 5 h and 10 h time point (Figure 5b). Cells, cell parts, membranes, membrane parts and organelles in the cellular component and binding and catalytic activity in molecular functions were the most highly represented terms.

Genes usually interact with each other to play roles in certain biological functions. Pathway enrichment analysis of DEGs based on the KEGG database was performed. After comparisons of dormant with 5 h time point conidia, 1849 genes were annotated for 121 known metabolic and signal pathways. During the late stages of germination (5 h vs. 10 h), 238 genes were classified into 92 pathways. However, the pathway distributions of these changes in genes in both isotropic growth and polarized growth were in accordance with each other, and more genes displayed at least a 2-fold change in isotropic growth. Carbohydrate metabolism, amino acid metabolism, translation, lipid metabolism and metabolism of cofactors and vitamins involved in metabolism and genetic information processing were the most abundant groups.

In addition, the top 20 KEGG enrichment results (shown in Figure 6a) were generated. In the isotropic growth stage (Figure 6b), ribosome- and oxidative phosphorylation-related DEGs were the most significant, which indicated that the initiation of energy metabolism and translation constitute key processes in the initial stages of germination (Figure 7a). Furthermore, the map of ribosome and the most changeable genes are represented in Figure S1; RPS28e was the most up-regulated gene and RPl36e was the most down-regulated gene. During polarized growth stages (Figure 6b), organic acid metabolism and lipid metabolism were the most abundant pathways. These data showed that lipid metabolism was an important process for germ-tube growth (Figure 7b). Furthermore, alpha-linolenic acid metabolism from lipid metabolism was the most important from pathway enrichment analysis. All five DEGs in this pathway were down-regulated and they are shown in Table 2 and Figure S2.

represents

 second KEGG pathway

 on

 terms. All second pathway

 terms are grouped in top pathway

 vs.

 vs.

 terms indicated

 with different colors.

 means

differentially

factor means greater

displayed

 the top 20 enriched

 pathway

 terms.

 expressed

 gene numbers

intensiveness.

 Q-value is corrected

annotated

 in this pathway

 term to all gene numbers

*p*-value ranging from 0 to 1, and a lower Q-value means greater

annotated

 in this pathway

 term. A greater rich

intensiveness.

 We only


**Table 2.** The differentially expressed genes grouped by GO, KEGG and enriched pathways of interest between 5 and 10 h.

<sup>a</sup> log2Ratio was determined as the log2 mean value of mRNA abundance at 5 h vs. 10 h.

Additionally, the aflatoxin biosynthesis pathway activated in the stage of germination (Table 2 and Figure S3), which means that the secondary metabolism was triggered with the germination process and became ready for aflatoxin biosynthesis.

#### *2.6. Antioxidant System during Conidia Germination*

The identification of the redox gene effect during conidia germination is of paramount importance. The essential oil has been reported to efficiently kill conidia of *A. flavus* via triggering reactive oxygen species and causing redox-balance damage. According to the results of RNA-Seq, the redox gene expression was determined by RT-PCR (Figure 8a) more specifically during conidia germination and separated into four different stages. Real-time qPCR results showed that redox gene mRNA levels of ss-cat and cat2 increased, while m-cat decreased as conidia germination progresses, which was also demonstrated in RNA-Seq results. With the coumalic acid and geraniol supplementation, conidia germination was inhibited as Figure 8b shows, and the mRNA abundance of ss-cat, cat, and cat2 increased.

**Figure 8.** Relative mRNA abundance of redox genes during conidia germination of *A. flavus* (**a**). Germination rate with coumalic acid and geraniol supplement (**b**) during the germination of *A. flavus*. Effect on coumalic acid and geraniol supplement on relative mRNA abundance of redox genes after 8 h germination of *A. flavus* (**c**). Values are mean ± SEM, *n* = 6. Means without a common letter differ, *p* < 0.05.

#### **3. Discussion**

For the conidia of *A. flavus*, germination is the first crucial step from asexual propagule to vegetative mycelium growth and the production of aflatoxin, which causes contamination and the spoilage of food and feed. Therefore, an improved understanding of the conidia germination process, metabolism and key genes and pathways can provide significant contributions to studies focused on controlling aflatoxin contamination and improving food and feed safety.

The transitions of conidia germination are recognized in three different stages: dormant conidia, isotropic growth and polarized growth [21]. The generated hyphae are then separated into compartments by septa [22]. Each stage has its own unique morphological characteristics. A previous study found that dormant conidia are highly stress-tolerant structures [23], and they are able to survive and germinate under high-pressure conditions such as dehydration, extreme temperature, osmotic pressure variations in pH and UV due to the three layers of the cell wall and several inner characteristics [11,24]. Dormant conidia germinated when flexible nutrients such as sugars, inorganic salt and nitrogen source were supplemented in most *Aspergillus* strains. However, germination times depend on the different culture conditions and variations in different *Aspergillus* strains.

In our study, we chose 5 h after inoculation as the stage of isotropic growth and 10 h germination as the stage of polarized growth, respectively, using a series of microscopes and flow cytometry. While the morphology change was similar to other typical *Aspergillus* such as *A. niger* and *A. fumigatus*, during the isotropic stage, the cell's size was up to twice that of dormant conidia and the germ tube grew out from one side [25]. When the length of the tube was equal to the conidia's radius, this meant that conidia germination was successful. The morphological impact of germinating conidia on the surface ultrastructure of *A. flavus* spores was investigated by scanning electron microscope (SEM).

The goal to understand the transcriptome landscape of dormant and geminating conidia of the filamentous fungi *A. flavus* was achieved in this study. Presumably, our research is the first report to analyze the transcriptome levels of the dormant and germinating conidia within the aflatoxigenic *A. flavus* strain. In the current study, the RNA-Seq produced an average of 1.21 billion bp raw data size and 24.1 million raw reads for each treatment, and approximately 10,000 genes were characterized after filtering out low quality reads. The data indicated that the RNA expression level of dormant conidia is substantially different when compared to other stages of germination, each of which is characterized by a typical morphology. The transcriptome of conidia changed gradually before the stage of isotropic growth (swelling), in which the gene's expression had many variations. The correlation of the expression of the dormant and germinating conidia 5 h after inoculation (0.350) and 10 h after inoculation (0.348), as well as the correlation between the 5 h and 10 h time points, is 0.92, which provides evidence for these changes.

About 23,320 genes were expressed in vegetative growth in a control group of *A. flavus* in different water activity treatments, while transcripts of 33% of the genes were active in dormant conidia of *A. niger* [18] and a similar trend was found in *Aspergillus. fumigatus* [10]. Compared to vegetative hyphae and aerial structures, the complexity of conidial RNA is lower because these spores represent a single cell type [26]. In contrast, mycelium, vegetative hyphae and aerial structures are composed of different types of hyphae and cells. Previous studies have shown that the RNA profile has a few changes after one-year storage in the dormant conidia of *A. fumigatus,* and it was thought that mRNA was in a pre-packed pool stage for the translation and quick response of conidia germination [10]. For instance, a few compounds such as heat shock proteins, trehalose, mannitol and dehydrins in dormant conidia are key for maintaining the structures for surviving extreme conditions [11]. The transcripts of genes for encoding these related proteins were not only highly accumulated but the transcripts of genes related to the synthesis and degradation of compatible solutes were also unique in dormant spores. Similar research has shown that genes involved in the defense of the conidia cell wall (for example, the genes responsible for making hydrophobins and pigmentation [27,28]) are specific for dormant conidia in *A. niger* and *A. fumigatus*. Furthermore, some transcription-factor-related genes that are essential for spore formation and maturation were only found in dormant conidia but absent in germinating conidia [18].

In this study, to evaluate the changes between the breaking of dormancy and dormant conidia in *A. flavus*, RNA-Seq was performed. Compared to other research, significant transcriptional changes occurred over the first 2 h of germination in *A. niger* by using genome-wide microarrays, but the total gene number was only about 4000, which is far less than the 11,000 genes in our study [15]. Other research also revealed that the most significant changes occurred over the initial stages of conidia germination when compared to the subsequent stages of germination in *A. fumigatus* [9]. As a result of this observation, RNA-Seq technology was used to study this period of the breaking of dormancy in more detail and as a tool to validate the microarray's results. In our study, we found that significant changes occurred during the first stages of *A. flavus* conidia germination.

For GO class analysis, metabolic processes in biological process contain the largest number of DEGs between dormant conidia and conidia 5 h after inoculation. With the exception of the global and overview maps of KEGG enrichment analysis, the DEGs enriched in the nutrient metabolism pathway were the most considerable amount. From a metabolic perspective, the germination process involves a transitioning from a relatively quiescent, dormant state to a germinated state. There needs to be resumption and an increase in metabolic activities including respiration, DNA synthesis, mitosis, cell wall synthesis, RNA and protein biosynthesis throughout germination.

Protein synthesis is vital for germination in *A. fumigatus* and *A. niger* because the protein synthesis inhibitor cycloheximide prevents germ tube formation at moderate concentrations [13,15]. Both protein synthesis and polysome assembly are early events in germination and transcriptome research, with *A. niger* also supporting this conclusion [5]. In our study, pathway enrichment analyses revealed that the genes related to the ribosome and ribosome biogenesis significantly changed after conidia germination. In CZ culture medium, sodium nitrate was the only nitrogen source, and several genes involved in the nitrogen's metabolism were regulated at the onset of germination. For instance, *NR*, *RT* and *NIT-6* were responsible for converting nitrate into ammonia and increased their transcript levels upon germination. Then, L-amino acids were synthesized after a series of biological processes. L-amino acids are the building blocks of new proteins, and the data showed that transcripts encoding transcription factor *CpcA*, which monitors L-amino acid metabolism increased at the initial stages of germination [28], possibly act as signals for replenishing the pool of L-amino acids intracellularly, which involved the same tendency as conidia germination in *A. niger* [24].

For the energy process, the transcript-encoding enzymes of the tricarboxylic acid cycle (TCA), glycolysis/gluconeogenesis and pentose phosphate pathway were found to be highly abundant in the first stage of germinating conidia but were absent in dormant conidia. Fatty acids can act as a catalyst that starts the gluconeogenesis pathway because they can feed into it. The mRNA profile of genes in *Aspergillus* conidia indicates that gluconeogenesis may be significant for spore survival and germination through the use of stored lipids [15]. In our study, the highly abundant fatty acid degradation and metabolism at 5 h of germination also agreed with this conclusion. Furthermore, the fatty acid elongation and biosynthesis were also highly abundant in the swelling stage, which means lipid metabolism is crucial for the breaking of dormancy.

L-amino acids are also possible substrates for gluconeogenesis after germination and the transcriptome suggested that the proteasome is an organelle that could be functional. Additionally, in contrast to *A. niger* conidia germination, there was a lower abundance of transcripts encoding the proteasome in the 5 h germinating conidia compared to the dormant conidia [18].

In translation, the sequence of codons on mRNA directs the synthesis of a polypeptide chain. This process takes place on the ribosome and the movement of tRNA and mRNA through the ribosome is a complicated process that combines high speeds with high accuracy [29]. The ribosome, a large ribonucleoprotein particle, comprises two subunits (large and small) in all species. In our study, most DEGs related to the ribosome (see details in Table 3 and Figure S1) were upregulated between the first two stages, which means translation activity was highly frequent between these changes. Based on our data, the lipid metabolism pathway was a key pathway for the germ-tube stage, sphingolipids, a type of lipid, are major components of fungal plasma membranes and also an inhibition target that prevents polarized growth in *Aspergillus. nidulans* [30]. Alpha-linolenic acid metabolism was the most influenced pathway in the lipid metabolism pathway, whereby alpha-linolenic acid reduced growth and aflatoxin synthesis after several hours [31]. This finding also supported our research, whereby all four DEGs in this pathway were down-regulated in polarized growth stage.



<sup>a</sup> log2Ratio was determined as the log2 mean value of mRNA abundance of 0 h vs. 5 h.

With conidia germination, respiration become more active, and the antioxidant system simultaneously become more effective [13,18,32]. In this regard, conidia germination affected four DEGs involved in the antioxidant process (Figure 8, Table 3). Notably, the *ss-cat* (spore-specific catalase) and *cat2* (bifunctional catalase-peroxidase) genes were upregulated, while the *m-cat* (mycelial catalase) gene for protein was down-regulated, and the *cat* (catalase) gene was down-regulated and then up-regulated. These changes in gene abundance could result in mitigating oxidative stress during conidia germination. However, the different gene expression changes need to be explored in the future. Numerous studies have shown that the *cat* (catalase) gene plays an important role in fungal development, aflatoxin biosynthesis and virulence [33]; mycelial catalases transiently protect the fungus from external conditions [34]. However, few studies focus on the antioxidant system during conidia germination, and the function of these genes requires further research.

Coumalic acid and geraniol found in the essential oil of fruit and herbs have been suggested to represent a new class of agents to control *A. flavus* and aflatoxin contamination. The two materials have been reported to inhibit the germination of resting spores of some pathogens by interrupting the antioxidant balance system [35–37]. Consistent with previous studies, coumalic acid and geraniol exhibited a potent inhibitory effect on *A. flavus* conidia germination and the *ss-cat*, *cat*, and *cat2* genes were up-regulated at 5 h of germination via the induced antioxidant system imbalance (Figure 8). The changes in these genes might help us figure out the mechanism of *A. flavus* conidia germination. Most importantly, redox genes could be a potential target to inhibit *A. flavus* conidia germination.

In conclusion, the present study found that the many changes in the transcriptome were not correlated with distinct morphological changes during germination. In addition, DEGs related to aflatoxin synthesis were found during polarized growth, which means that the transcription process was triggered in an early stage. In general, RNA-Seq was used to uncover transcriptome changes at the conidia germination of *A. flavus*. Translation, amino acid metabolism and carbohydrate metabolism were the most active pathway in breaking conidia germination. Moreover, lipid metabolism, amino acid metabolism and carbohydrate metabolism were the top three pathways during germ-tube growth. Additionally, the antioxidant system plays a crucial role in conidia germination, and *ss-cat*, *cat* and *cat2* are essential redox genes. However, the further validation of the exact functions and mechanisms of these key DEGs in conidia germination needs to be further studied and might potentially be beneficial in preventing aflatoxin contamination.

#### **4. Materials and Methods**

#### *4.1. Culturing Conditions and Sampling*

*Aspergillus flavus* NRRL 3357 was obtained from Prof. Zhumei He (Sun Yat-Sen University, Guangzhou, China) [38]. The strain was grown on Potato Dextrose Agar (PDA) for 7 days at 30 ◦C to develop mature spores. Spores were then harvested with sterile 0.05% (*w*/*v*) Tween 80 solution. The spore suspension was filtered through 3 sterile layers of lens paper and kept on ice until further processing on the same day, and the spore population was quantified using a hemocytometer. For spore germination, 20 mL of 106 mL−<sup>1</sup> spores was inoculated in 200 mL liquid Czapek–Dox (CZ) Medium. Three replicates were shaken at 150 rpm at 30 ◦C for each RNA isolation. At each time point, samples were pooled and centrifuged at 5 ◦C for 10 min at 3000× *g*. The pellet was frozen in liquid nitrogen for later RNA isolation. Coumalic acid and geraniol were dissolved in ethanol into a 100 mg/mL stock solution, protected from light, and stored at 4 ◦C. The final concentration of the coumalic acid treatment groups was 200 mg/L and geraniol was 100 mg/L.

#### *4.2. Microscopy*

For scanning electron microscopy (SEM) analysis, 1 × <sup>10</sup><sup>6</sup> conidia of *A. flavus* were harvested by centrifugation at 3000× *g* and washed with PBS (phosphate buffered saline, pH 7.4) twice. Then, conidia were fixed in 2.5% glutaraldehyde in PBS for 2 h at room temperature. The conidia were washed with PBS for 3 times, 15 min each, and then the

conidia were post-fixed in 1% osmium tetroxide for 1–2 h at room temperature. After that, conidia were washed in PBS for 3 times. The dehydration of samples was achieved by transferring by increasing the concentration of (30–100%) ethanol solutions, and the samples were dried with Critical Point Dryer [39]. The samples were then attached to metallic stubs using stickers and sputter-coated with gold for 30 s. The observations were made on a HITACHI Regulus 8100 SEM (Tokyo, Japan).

#### *4.3. Flow Cytometry of Spores*

Flow cytometry was used to measure the size of spores (1 × <sup>10</sup>5) over the first few hours of germination when the conidia were swelling. Liquid CZ medium was inoculated with *A. flavus* conidia at a concentration of 106/mL and shaken at 150 rpm at 28 ◦C. The samples were collected 5 and 10 h after inoculation. The supernatant was removed, and conidia were washed 3 times with 1 mL Tween 80 (0.01% *v*/*v*) and resuspended in 0.5 mL Tween 80. The sample was then analyzed using flow cytometry (Beckman-CytoFLEX Coulter, Brea, CA, USA). FlowJo software was used to determine the forward scatter (FSC) parameter for each sample, which is a measure of conidial size [25]. The same number of dormant conidia was analyzed as well.

#### *4.4. RNA Extraction and RNA-Seq*

Total RNA was extracted from conidia using a TRIzol and chloroform RNA extraction protocol, as previously described [5]. Three replicate RNA-Seq libraries were prepared from dormant conidia at 5 h and 10 h after the inoculation of *A. flavus*. A total of the nine libraries were sequenced separately using BGISEQ-500 sequencer. Raw sequencing reads were cleaned by removing adaptor sequences, reads containing ply-N sequences and low-quality reads. Approximately 24,006,405 clean reads were mapped to the Nipponbare reference genome using HISAT [40]/Bowtie [41] tools. After data were mapped, normalization was performed and then FPKM (fragments per kilobase per million mapped reads) was calculated using RESM software [42]. As previously described [43], a false discovery rate (FDR) < 0.01 and absolute value of log2 ratio ≥ 1 were used to identify differentially expressed genes in dormant conidia versus 5 h and 5 h versus 10 h samples.

#### *4.5. Real-Time Quantitative PCR*

Total RNA from 6 individual *A. Flavus* spore samples in each treatment (0 h, 4 h, 8 h and 12 h) and 2 essential oil supplement groups (after 8 h inoculation) were isolated, and the quality and quantity of RNA were analyzed by using Thermo NanoDrop (Thermo, Waltham, MA, USA). To estimate the accuracy of transcriptome results and for further investigation, 4 DEGs, *ss-cat* (spore-specific catalase), *cat2* (bifunctional catalase-peroxidase), *m-cat* (mycelial catalase) and *cat* (catalase), were selected using Real-time quantitative PCR (RT-qPCR). RT-qPCR was conducted on a Bio-Rad CFX384 Real-Time PCR System (Bio-Rad, Hercules, CA, USA) with TB Green® Premix Ex Taq™ II (Tli RNaseH Plus) (Takara, Dalian, China). The relative amounts of mRNAs were normalized with the housekeeping gene *GAPDH* and were analyzed by the 2−ΔΔCt method.

#### *4.6. Statistical Analysis*

For spore germination rates and transcriptomic data, statistical analyses were performed using Graphpad Prism (San Diego, CA, USA) for Windows (version 8.00). The data were expressed as mean ± SEM (standard error of mean). Differential effects were analyzed by one-way analysis of variance (ANOVA). A *p* value < 0.05 was considered significant (\*), and *p* value < 0.001 was considered extremely significant (\*\*\*).

#### *4.7. Data Submission*

All the amplicon sequencing datasets in this study were submitted to NCBI Sequence Read Archive (SRA) under accession number PRJNA698788.

**Supplementary Materials:** The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/toxins14080560/s1, Figure S1: DEGs in ribosome pathway in *A. flavus* between 0/5 h. Figure S2: DEGs in alpha-linolenic acid metabolism pathway in *A. flavus* between 5/10 h. Figure S3: DEGs in aflatoxin biosynthesis pathway in *A. flavus* between 5/10 h. Excel S1: All DEGs between 0 h vs. 5 h. Excel S2: All DEGs between 5 h vs. 10 h.

**Author Contributions:** D.Q. and S.W. designed the research study. C.L., S.J. and S.A.R. performed research, analyzed data and wrote the paper. All authors have read and agreed to the published version of the manuscript.

**Funding:** This project was funded by the National Natural Science Foundation Project of China (Project no. 31772635).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available in this article and supplementary materials.

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

#### **References**


### *Article* **Aflatoxin B1 Degradation by Ery4 Laccase: From In Vitro to Contaminated Corn**

**Martina Loi 1,\*, Silvana De Leonardis 2, Biancamaria Ciasca 1, Costantino Paciolla 2, Giuseppina Mulè <sup>1</sup> and Miriam Haidukowski 1,\***


**Abstract:** Aflatoxins (AFs) are toxic secondary metabolites produced by *Aspergillus* spp. and are found in food and feed as contaminants worldwide. Due to climate change, AFs occurrence is expected to increase also in western Europe. Therefore, to ensure food and feed safety, it is mandatory to develop green technologies for AFs reduction in contaminated matrices. With this regard, enzymatic degradation is an effective and environmentally friendly approach under mild operational conditions and with minor impact on the food and feed matrix. In this work, Ery4 laccase, acetosyringone, ascorbic acid, and dehydroascorbic acid were investigated in vitro, then applied in artificially contaminated corn for AFB1 reduction. AFB1 (0.1 μg/mL) was completely removed in vitro and reduced by 26% in corn. Several degradation products were detected in vitro by UHPLC-HRMS and likely corresponded to AFQ1, epi-AFQ1, AFB1-diol, or AFB1dialehyde, AFB2a, and AFM1. Protein content was not altered by the enzymatic treatment, while slightly higher levels of lipid peroxidation and H2O2 were detected. Although further studies are needed to improve AFB1 reduction and reduce the impact of this treatment in corn, the results of this study are promising and suggest that Ery4 laccase can be effectively applied for the reduction in AFB1 in corn.

**Keywords:** aflatoxin B1; laccase; corn; bioremediation; degradation products; hydrogen peroxide; ascorbic acid; dehydroascorbic acid; AFQ1; AFB2a; AFB1-diol

**Key Contribution:** Aflatoxin degradation in vitro and in corn flour was assessed. Degradation products were detected by UHPLC-HRMS. In addition, the protein content and oxidative status of the matrix after the enzymatic treatment were evaluated. Significant improvement in the safety and a minimum impairment of the oxidative status were observed, proving that the laccase treatment was a promising aflatoxin reducing treatment.

#### **1. Introduction**

Aflatoxins (AFs) are secondary toxic metabolites produced by *Aspergillus* spp., which can contaminate food and feed worldwide [1]. AFs include more than 20 different furanocoumarin derivatives with carcinogenic, teratogenic, mutagenic, nephrotoxic, and hepatotoxic properties [2,3]. AFB1 is the most potent carcinogen known (Group 1 carcinogen) and the most occurring mycotoxin reported by the Rapid Alert System for Food and Feed [4]. AFs are chemically stable compounds, and currently their post-harvest reduction is performed only by physical methods, i.e., by sorting and adsorption. Thus far, effective AFs degradation can be achieved only by means of strong oxidants from physical (plasma, photolysis, photocatalysis), chemical (ammoniation), or biological (oxidoreductase enzymes) origin [5,6].

**Citation:** Loi, M.; De Leonardis, S.; Ciasca, B.; Paciolla, C.; Mulè, G.; Haidukowski, M. Aflatoxin B1 Degradation by Ery4 Laccase: From In Vitro to Contaminated Corn. *Toxins* **2023**, *15*, 310. https:// doi.org/10.3390/toxins15050310

Received: 31 March 2023 Revised: 17 April 2023 Accepted: 24 April 2023 Published: 27 April 2023

**Copyright:** © 2023 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/).

Enzymes represent an effective yet mild and environmentally friendly method to reduce AFs. So far, AFs enzymatic degradation has been achieved by using oxidoreductases, such as laccases, peroxidases, or so-called "aflatoxin oxidases" [7,8]. In particular, laccases (LCs, benzenediol: oxygen oxidoreductase, EC 1.10.3.2) are copper containing enzymes, able to oxidize simple and substituted phenolic compounds, thiols, anilines, amines, and complex aromatic compounds to the corresponding quinones, concurrently to the fourelectron reduction in oxygen to water [9]. The catalytic activity of LCs can be further broadened to compounds which cannot be oxidized due to their high redox potential or steric hindrance thanks to the use of redox mediators. The use of these compounds allows for fine-tuning of the oxidation process and degrade a wide range of chemically unrelated compounds, such as mycotoxins [10]. Among redox mediators, the use of natural antioxidant compounds, such as phenols, has attracted attention because they are regarded as safe and can be used to improve existing industrial processes or develop new ones for the production of high value products [11]. Although the enzymatic degradation has been proven to be an effective method for mycotoxins reduction in feed, its application in food still has to be investigated. In Europe, Regulation 786/2015 defines the acceptability criteria for detoxification processes applied to products intended for animal feed [12].

A detoxification process implies that the toxin is converted to a less toxic, possibly safe, compound. Oxidases convert AFB1 into hydroxylated metabolite AFQ1, or to the 8,9-epoxy-AFB1, which spontaneously converts to 8,9-dihydroAFB1. Other hypothesized products derive from hydrolysis of the lactone ring followed by its opening (i.e., AFD1), from addition of water to the double bond of the terminal furan (AFB2a), or from demethylation (AFP1) [13]. These compounds have been found in vivo as a result of cytochrome detoxification in the liver [14].

Other than safety and efficacy, another mandatory requisite is that the method must not adversely affect the characteristics and the nature of the feed. Although food detoxification is not authorized yet, similar, if not more stringent, criteria will be likely set for food detoxification procedures in the near future.

Corn is one of the main staple food commodities worldwide and performs a central role in global agro-food systems. Contamination of corn grain with AFs is a concerning issue, especially in developing countries, where the majority of the product is self-produced by smallholder farmers in rural subsistence farming communities [15]. Despite being an important component of the human diet, corn is one of the main ingredients of livestock feed, it has multiple industrial uses, and its by-products find application in the energetic supply chain [16–18].

The application of an enzymatic degradation step within the common corn processing should encompass the addition of a buffered solution to easily convey the enzyme and natural redox mediators. Water addition is already included in both dry and wet milling processes.

Dry milling is the main industrial process used in the corn supply chain to separate the pericarp, the endosperm, and the germ; and obtain hominy grits, corn flours and feed meals [19,20]. It may encompass the tempering step, in which water is added to faster separate corn tissues and obtain fractions with low fat content, suitable for the manufacture of extruded products. In wet milling process, the kernels are steeped in SO2 and lactic acid solution for 24–48 h to facilitate the separation of kernel's components [21]. In a complex matrix, such as corn flour, the addition of exogenous antioxidants could be investigated to support mediator reconversion and reduce the oxidative damage induced by the laccase mediator systems (LMS). Vitamin C (L-ascorbic acid, ascorbate, and ASC) is the most abundant water-soluble compound widely used as antioxidant in food and feed products. Its oxidation product, dehydroascorbic acid (DHA), in the apoplast, is readily taken up by the plasma membrane and reduced to ascorbate in the cytosol [22]. In this regard, either the direct or indirect (by reduced DHA) addition of vitamin C could be beneficial in supporting the enzymatic AFB1 reduction.

Therefore, in this work, an enzymatic treatment for AFB1 reduction was investigated in vitro using different LMSs, including acetosyringone (AS), a naturally occurring phenol, ASC, and DHA; in vitro degradation products were also identified. Then, AFB1 reduction was assayed in corn to assess enzyme performance in the real matrix. Additionally, to monitor the oxidative status, the effect of the different treatments in terms of protein content, lipid peroxidation, and H2O2 was also assessed.

#### **2. Results**

### *2.1. Aflatoxin B1 Degradation in Buffer Solution Using Different LMSs*

In a previous work, the efficacy of different LMSs for AFB1 was screened in a 72 h-in vitr*o* assay. The maximum degradation of 1 μg/mL of toxin was 73%, obtained using AS as redox mediator [10]. This LMS was selected for further investigations to improve AFB1 degradation.

Therefore, in this study, AFB1 degradation (0.1 μg/mL) was evaluated over time using different LMS, namely Ery4 with AS, also in combination with ASC or DHA at 1 and 10 mM. Degradation, expressed as percentage with respect to the control not containing LC, is shown in Table 1.

**Table 1.** Time course in vitro degradation of aflatoxin B1 (0.1 μg/mL) using Ery4 laccase (5 U/mL), acetosyringone (AS) in combination with dehydroascorbic acid (DHA) 1 or 10 mM.


AFB1 was completely removed from the buffer by Ery4 + AS even after only 1 h. The addition of ASC and DHA was deleterious, especially at higher concentrations. No degradation was observed using ASC. When used at 1 mM, DHA slowed the enzymatic degradation, and AFB1 was completely removed only after 24 h. DHA 10 mM inhibited AFB1 degradation, which reached only 20.3 ± 1.8% after 48 h.

#### *2.2. In Vitro Study of Aflatoxin B1 Degradation Products*

To further study the ability of Ery 4 laccase to degrade AFB1 in the presence of the mediator AS, an UPLC-HRMS analysis was carried out. For this purpose, fullscan/variable data-independent acquisitions in positive ion mode of control samples containing Ery4 5 U/mL and AS 10 mM in sodium acetate buffer 1 mM (pH5) (C\_Ery4\_AS) and treated samples with AFB1 (1 μg/mL) incubated with Ery4 laccase (5 U/mL), and AS 10 mM in sodium acetate buffer 1 mM, pH 5, for 24 h (AF\_Ery4\_AS) were acquired. The comparison between the control and the AFB1-treated sample confirmed a decrease of 55% of AFB1 content and the formation of additional peaks after enzymatic treatment, which could be attributed to oxidation products of AFB1. Proposed reaction products, chemical structure and formulas are presented in Figure 1.

A measured mass of 347.0761, which was attributable to a molecular formula C17H14O8 corresponding to the ion [M+H]+, showed one peak eluting at 21.5 min (mass error: 1.6 ppm) and two overlapping peaks at 23.6 min (mass error: 1.3 ppm) and 24.7 min (mass error: 1.3 min) (Figure 2). A difference of 34 mass units compared to aflatoxin B1 indicated the presence of two hydroxyl groups; therefore, the following molecular formula could be attributed to AFB1 8,9-dihydrodiol or to AFB1 dialdehyde. Considering the polarity of these compounds, the peak at 21.5 was assumed to be relative to dihydrodiol or dialdehyde. The [M+H]<sup>+</sup> molecular ion at 331.0812, which was attributable to a molecular formula C17H14O7, showed one main peak at 22.0 min (mass

error: 1.2 ppm) and could be related to AFB2a or product 1 (P1) (Figure 1). Finally, the [M+H]<sup>+</sup> molecular ion at 329.0656, which was attributable to a molecular formula of C17H13O7, corresponded to two main peaks, eluting at 22.8 min (mass error: 2.2 ppm) and 23.6 min (mass error: 1.9 ppm); one less abundant peak eluted at 24.8 min (mass error: 3.2 ppm). These peaks could be related to AFQ1, epi AFQ1, AFB1-8,9-epoxyde, or AFM1.

**Figure 1.** Proposed AFB1 degradation products.

**Figure 2.** UHPLC-HRMS chromatogram of treated sample with AFB1 (1 μg/mL) incubated with Ery4 laccase (5 U/mL) and AS 10 mM in sodium acetate buffer 1 mM, pH5, for 24 h (AF\_Ery4\_AS). Peaks attributable to AFB1 and LMS oxidation products (AFB2a, AFQ1, epi AFQ1, AFM1, AFB1 dialdehyde and isomers of AFB1 dihydrodiol are shown. Resolution: 70,000 full width at half maximum; extraction window tolerance 5 ppm.

Identity confirmation of the putative product of the enzymatic reaction was performed by matching the detected fragments with MS2 spectra reported in the literature (if available), as shown in Table 2. In the case of precursor at 329.0656, fragments obtained in AF\_Ery4\_AS sample were reported in Figure 3. MS/MS spectra of the first two peaks (22.8 min and 23.6 min) showed some characteristic fragments of AFQ1, such as the peak of m/z 311.0547, originated by the loss of water (neutral loss of 18 a.m.u.), and fragments of m/z 283.0606, 206.0673, and 141.0180.


**Table 2.** Precursor ion, exact mass, retention time, and fragments of proposed AFB1 degradation products.

Peak eluting at 24.81 min presented different relative abundances of fragments 329.0652 and 301.0706. In addition, the fragment ion at 273.0757 [M − 74 + H]<sup>+</sup> was shown. These fragments are characteristic of AFM1 [9,23].

In the case of the precursor at 331.0812, fragments at m/z 303.0861 [M-CO + H]+, 284.0316, 267.0288, and 239.0338 were shown. No fragments were detected for the precursor at 347.0812.

**Figure 3.** Parallel reaction monitoring (PRM) spectra (collision energy 35 eV) of 329.0656 in treated sample with AFB1 (1 μg/mL) incubated with Ery4 laccase (5 U/mL) and AS 10 mM in sodium acetate buffer 1 mM, pH 5, for 24 h (AF\_Ery4\_AS).

A rough estimation on the basis of peak area ratios indicated that among the identified products, the most prevalent one was AFQ1 (41.2%), followed by AFB2a/P1 (29.6%), AFB1-dihydrodiol/AFB1dialdehyde (14.8%), and AFM1 (3.7%). AFB2a may also be formed spontaneously in acidic conditions, in agreement with other literature data [13].

#### *2.3. Aflatoxin B1 Degradation in Corn*

Following the results obtained in vitro, only three LMSs (Ery4, AS and DHA) were tested in artificially contaminated corn flour (50 μg/kg AFB1). After the reaction, samples were centrifuged, and both the supernatant and pellets were analyzed. No AFB1 was detected in the supernatant, while appreciable degradation could be observed in the pellets (Figure 4). AFB1 degradation levels were lower with respect to the **in vitro** trials, although Ery4+AS was confirmed to be the most efficient LMS. While no difference could be observed when DHA 1 mM was added, a clear inhibiting effect was exerted by DHA 10 mM, leading to ineffective degradation.

#### *2.4. Protein Content*

As shown in Figure 5, the enzymatic treatment did not alter the total protein content, calculated as a sum of water-soluble, ethanol soluble, and insoluble fractions. Conversely, statistically significant differences were shown in samples containing DHA. In particular, a dose dependent reduction was observed irrespectively of the presence of Ery4 and AS, highlighting that protein reduction could be ascribed to DHA addition rather than to LMS.

**Figure 4.** Aflatoxin B1 degradation (%) in corn samples treated with Ery4 (5 U/mL) acetosyringone (AS, 10 mM) 10 mM and dehydroascorbic acid (DHA) at 1 and 10 mM. Different lowercase letters above columns indicate significant differences between treatments (*p* < 0.05).

**Figure 5.** Total protein content (mg mL−1) in untreated corn samples (Control) and samples treated with Ery4 (5 U/mL), acetosyringone (AS, 10 mM), and dehydroascorbic acid (DHA) at 1 and 10 mM. Different lowercase letters above columns indicate significant differences between treatments (*p* < 0.05).

#### *2.5. Lipid Peroxidation and H2O2 Content*

The oxidative status of both supernatant and pellets was analyzed in terms of H2O2 content and MDA levels. The enzymatic treatment had a detrimental effect on H2O2 content, both in the pellet (Figure 6A) and in the supernatant (Figure 6B; a synergistic oxidative effect was observed in samples treated with DHA 1 mM, as H2O2 levels further increased up to 95,65 ± 0.79 mmol/mL. Conversely, lower H2O2 values were registered in samples containing DHA 10 mM (66.5 ± 0.20 mmol/mL).

As reported for H2O2, higher MDA content was shown in the supernatants rather than in the pellets. In this latter case, only samples containing DHA 10 mM showed statistically significant increased level. In the supernatants, the oxidative effect of Ery4 + AS enzymatic treatment was more pronounced, and the synergic effect of DHA could be observed only at 10 mM concentration.

**Figure 6.** Hydrogen peroxide (Panel (**A**), pellet; Panel (**B**), supernatant) and lipid peroxidation (Panel (**C**), pellet; Panel (**D**), supernatant) content of corn samples using Ery4 (5 U/mL) acetosyringone (AS) 10 mM, and dehydroascorbic acid (DHA) at 1 and 10 mM. Data were expressed as mmol or nmol per fresh weight (F.W.). Different lowercase letters above columns indicate significant differences between treatments (*p* < 0.05).

#### **3. Discussion**

Mycotoxins degradation via LMS has been explored with several mediators of natural and synthetic origin [10]. Natural phenols, such as AS, were applied as promising mediators for bioremediation, with potential application in the food industry [24].

AS is a syringic acid derivative found as phenolic humic constituents in natural organic matter [25]. AS, together with other structurally related compounds, have been reported to be efficient mediators for the reduction in organic pollutants, dyes, and mycotoxins [10,26–28].

AS has a redox potential of 0.580 V, which is not among the highest potential reported for LC mediators. Nonetheless, the mediator efficacy does not only depend upon the redox potential but also on the rate of oxidation by LC, stability of the oxidized form of the mediator, its capacity of being recycled, and not to inhibit LC active site [29]. AS's good mediator activity is due to the presence of 2,6-dimethoxy electron-donating groups that give stable phenoxy radicals with a relative long half-life and low free radical activity [30,31].

AS oxidation was reported to proceed via electron transfer and hydrogen atom abstraction mechanism to give a phenoxy radical. This radical intermediate is also stabilized by the acetyl group in orto position, where a further electron delocalization takes place. Additionally, AS oxidation intermediates can still be oxidized by LC as long as it has a phenolic group that can be oxidized [30]. Due to the radical nature of the oxidation mechanism, the addition of a natural antioxidant, ASC, was evaluated for AS reconversion. Moreover, due to the existing reconversion route of ASC from DHA in plasma membrane, DHA supplementation was also assayed.

ASC is a pivotal antioxidant compound and a key element for the metabolism of almost all living organisms. It is a dibasic acid with an enediol group on C2 and C3 of a heterocyclic lactone ring, and at physiological pH, the hydroxyl group at C3 is deprotonated, giving a monovalent anion, ASC [32,33].

The ASC is the only reductant present at a significant level in the apoplast, with a redox potential ranging from +0.40 to +0.50 V [34]. When both electrons of the enediol group of ASC are donated, ASC can be oxidized in this compartment to DHA by ASC oxidases [22,35]. Conversely, when in excess, DHA can be transported via the cell membrane through a carrier mediated uptake and reduced again to ASC. This is part of the cellular redox gradient across the plasma membrane, connecting intra- and extra-cellular environments. The redox environment of the cell is determined by the global poise of its oxidation/reduction systems and may contribute to regulating the effectiveness of the LMS. Indeed, there is a complex link between redox state and simplistic and apoplastic metabolism [36], which is also determined by ROS level, produced at either physiological or toxic levels [35].

The addition of ASC completely inhibited AFB1 degradation. Similarly, DHA negatively impacted AFB1 degradation, proving that DHA does not participate in LMS and possibly inhibits LC at high concentration.

ASC was reported to non-competitively inhibit LC from *Botritis cynerea* [37]. Accordingly, in our study, ASC reduced the rate of AFB1 degradation, possibly by inhibiting LC or scavenging AS reactive radicals before toxin degradation. To our knowledge, no report is available on how DHA affects LC activity. DHA can undergo further irreversible degradation, such as hydrolyzation to 2,3-diketo-L-gulonate, or oxidation to a range of products, such as L-threonic acid, oxalic acid, and their esters; therefore, it may contribute to radical quencing [38].

In the present study, we wanted also to investigate the effectiveness of the detoxification process of AFB1 by LMS under the optimal degradation condition. To this purpose, a UHPLC-HRMS analysis was carried out to investigate the degradation products by LMS in presence of AS 10 mM after 24 h incubation and 1 μg/mL in **in vitro** samples. To date, neither the mechanism of the laccase-catalyzed degradation of AFB1 nor the degradation products have been fully disclosed; however, a review on the application of both bacterial and fungal laccase enzyme in AFB1 degradation was reported by Okawara and colleagues [39]. LCs act on AFB1 in two ways; on the terminal furan ring of AFB1, leading to the formation of AFB1-8,9 epoxide, which is further converted to AFB1-8,9 dihydrodiol or may directly open the lactone ring by introducing hydroxyl groups at the carbon 10 and 11 positions in AFB1 (product P1 Figure 1).

*Trametes versicolor* laccase, Lac2 from *Pleurotus pulmonarius* and the Ery4 from *P. eryng*ii were demonstrated to degrade AFB1 via the mediation of natural phenolic compounds such as AS, syringaldehyde, ferulic acid, etc., or synthetic compounds; however, the degradation products have not been reported. The oxidation of AFB1 in AFQ1 was reported in degradation study on CotA laccase from *Bacillus licheniformis* [7] and on Lac2 produced by *Cerrena unicolor* 6884 [40]. The latter study also reported the presence of AFQ1 epimer (epi AFQ1). In these studies, the presence of AFQ1 and epi AFQ1 products was justified assuming the action of LMS on the lactone ring of AFB1, possibly by hydrogen atom transfer followed by addition of water to C3. In our study, based on the structure, relative polarity and fragment ions, the epi AFQ1, AFQ1, and AFM1 were identified as oxidation products, corresponding to the peaks at 22.8, 23.6, and 24.8 min. The presence of AFQ1 is in agreement with the several reports of AFB1 degradation with LCs [40,41], peroxidases [8], or other oxidases [7].

LC and oxidases were also reported to convert AFB1 into the toxic 8,9-AFB1 epoxide [13,39]. Nonetheless, this compound has a fast rate, non-enzymatic conversion to AFB1-diol in water [42], thus it is hardly detectable by UPLC-HRMS. Based on 8,9-AFB1 epoxide hydrolysis and kinetics of rearrangement of the dihydrodiol, and considering LMS mechanism, retention times, and polarity of detected compounds in UPLC-HRMS, the ion at m/z 347.0812 corresponding to a molecular formula C17H14O8 could be likely addressed as AFB1-dialdehyde or AFB1-diol isomers.

In addition, a measured mass of m/z 331.0812, which was attributable to the molecular formula C17H14O7, corresponding to the ion [M+H]+, with a mass accuracy of 1.2 ppm, was detected. Two candidate compounds were in agreement with this formula (AFB2a

and P1). Despite LCs have been reported to degrade AFB1 into P1, according to polarity compounds, the measured mass of m/z 331.0812 at retention time 22.0 min could be more likely AFB2a.

All detected degradation products show a higher polarity and a higher excretion rate via urine and faeces, thus, lower toxicity than AFB1 [43]. Some of the products found lack of the reactive C8–C9 double bond and possess reduced mutagenicity. Nonetheless, they retain the ability to form Shiff bases with primary amines in proteins, leading to adducts responsible for residual cytotoxicity.

The same degradation trend was registered in vitro and in corn samples, though the differences were evened out, likely due to the matrix effect. Indeed, the interaction between the toxin and the active mediator may be hindered by proteins, carbohydrates, and lipids in corn flour, resulting in a lower efficacy. Competition of food components for the enzyme, enzyme adsorption to food components, and higher viscosity may also contribute to reducing the efficacy of LMS in corn flour.

The enzymatic treatment had slightly impacted the oxidative status of the matrix, while more significant effects were observed in the supernatants. The increased MDA content in corn sample pellets treated with higher DHA-concentration indicated the presence of increased lipid peroxidation of the biological membranes. This reflects the fact that the DHA is toxic in cell if is largely accumulated [44] and may activate induced systemic resistance via ROS production and salicylic acid pathway activation [45]. On the other hand, the decreased hydrogen peroxide level observed, at least for the corn pellet samples treated with the highest DHA concentration, indicates that H2O2 could oxidize the biological membranes, as supported by the higher lipid peroxidation in these samples.

Overall, these results suggest that the transport mechanism for DHA via the plasma membrane with its reconversion to ASC would appear not to be present, at least for the corn kernel.

H2O2 is the most commonly studied ROS due to its stability and capability of penetrate through cellular membranes, and it has been recognized as a subcellular signaling molecule. Plants can well tolerate relatively high H2O2 (up to 102–2 × <sup>10</sup><sup>5</sup> <sup>μ</sup>M), and its endogenous concentration was reported to range from nanomoles to several hundred micromoles [46,47]. Thus, H2O2 levels found in this study, although significantly higher in the LMS treated samples, were still in the tolerable ranges reported in the literature for plant cells [47].

The decreased total protein content in the DHA-treated samples underlines the presence of an action of DHA on the protein structure and an interference with the dye response. Particularly, corn proteins are rich in prolamins, which are thiol containing proteins. Indeed, a link between reduction DHA and oxidation of thiol group has been found [48]. Consequently, this event could have a negative impact on the protein folding due to the interaction of carbonyl groups of the DHA with amino acid residues. Indeed, DHA irreversibly inhibits some enzymes, such as human type I hexokinase, that shows a smaller number of cysteine residues [49,50].

A wide number of reports of in vitro enzymatic AFs degradation are available in the literature [10,51,52]. Conversely, fewer studies have been conducted on food matrices. Enzymatic degradation has been explored in food or feed for AFs, zearalenone, thricothecenes, and fumonisin [53–56], although they did not focus on the evaluation of the characteristics of the food matrix after the treatment. To our knowledge, this is the first study that evaluates the oxidative status of corn flour after the application of an enzyme-based degradation treatment.

In order to be applied in feed matrices, mycotoxin reduction methods must not alter the characteristics of the matrix. Therefore, the evaluation of the effects exerted by any reduction treatment must be assessed. So far, this is the first time that the effects on protein content and the oxidative status of corn flour after an enzymatic reduction treatment were studied. Indeed, the work performed by Dini and colleagues [57] only focus on aflatoxins enzymatic degradation in corn flour, obtaining similar results (30% of reduction) with the same level of contamination. Aflatoxin degradation was studied in other matrices, such as milk and beer, with promising results [8,10,58–61]. Nonetheless, few studies investigated the effect of the enzymatic treatment on the protein content and quality, antioxidant activity and technological properties though in a liquid matrix, such as milk [60,61].

#### **4. Conclusions**

Different LMSs were tested in vitro and in corn flour with the aim of reducing AFB1 contamination. Complete degradation was achieved in vitro with Ery4 and AS; the addition of ASC completely inhibits the degradation, while DHA decreased AFB1 degradation in a dose-dependent manner. The same behavior was observed in corn, even though the rate of degradation was reduced of one fourth due to matrix effect. Several degradation products characterized by lower toxicity were found in vitro by UHPLC-HRMS, namely AFQ1, epi-AFQ1, AFB1-diol or AFB1dialehyde, AFB2a, and AFM1.

The protein content was not altered by the sole enzymatic treatment, while it was lowered by DHA in a dose dependent manner. Conversely, LMS treatment affected the oxidative status of corn flour. Increased lipid peroxidation and H2O2 content were registered in enzyme- treated samples irrespectively of the amount of DHA added.

Even though further studies are needed to reduce matrix effect and assess the technological impact of this reduction methods, the results of this study are promising and suggest that AFB1 can be reduced completely in vitro and by 26% in corn flour. Therefore, since only slight oxidation occurred in corn flour, minimum impairment of the nutritional or technological properties could be expected by this treatment, but with significant improvement in its safety.

#### **5. Materials and Methods**

#### *5.1. Chemicals, Reagents, and Corn Kernels*

Analytical-grade acetonitrile (ACN), methanol (MeOH), and toluene (for HPLC purpose) were purchased from Mallinckrodt Baker (Milan, Italy). Ultrapure water was produced by a Millipore Milli-Q system (Millipore, Bedford, MA, USA). Filter paper and Glass microfiber filters (GF/A) were purchased from Whatman (Maidstone, UK).

Standard of aflatoxin B1, 2-azino-di-[3-ethylbenzo-thiazolin-sulphonate] (ABTS), syringaldehyde, and acetosyringone were obtained from Sigma Aldrich (Milan, Italy). Immunoaffinity columns AflaTest® Wide Bore were obtained from Vicam L.P. (Watertown, MA, USA).

Organic corn kernels (*Zea Mais* L.) were purchased from Bioseme s.c.a.r.l.

#### *5.2. Preparation of Standards*

Standard solution of AFB1 was prepared by dissolving the solid commercial toxin in toluene/acetonitrile (9:1, *v*/*v*) to a concentration of 10 μg/mL. The exact concentration of AFB1 was determined according to AOAC Official Method 971.22 [62]. Aliquots of the solution were transferred to 4 mL amber silanized glass vials and evaporated to dryness under a stream of nitrogen at 50 ◦C. The residue was dissolved with water/methanol (60:40, *v*/*v*) to obtain final concentrations in a range of 0.5 to 50 ng/mL of aflatoxin B1. Standard solutions were stored at −20 ◦C and warmed to room temperature before use.

#### *5.3. Laccase Production and Purification*

The recombinant Ery4 laccase was produced from *Saccharomyces cerevisiae* ITEM 17,289 of the Agri-Food Microbial Fungi Culture Collection of the Institute of Sciences of Food (http://www.ispa.cnr.it/Collection, accessed on 25 October 2022). Laccase purification was performed by concentration/ultrafiltration of the cultured media with Tris HCl 50 mM, pH 8, and anion exchange chromatography, as reported in Loi et al. [61].

#### *5.4. Laccase Activity Assay*

The enzymatic activity was assessed by the ABTS colorimetric assay using a spectrophotometer (Ultraspec 3100pro, Amersham Pharmacia Biotech Italia, Cologno Monzese, Italy). [7]. The reaction was performed in 100 mM sodium acetate pH 4.5, 5 mM ABTS and an appropriate amount of enzyme solution in a final volume of 1 mL. The oxidation of ABTS was determined after 10 min at 420 nm (ε420 = 36,000 M−1cm−1). One unit was defined as the amount of enzyme which oxidized 1 μmol of substrate per min.

#### *5.5. Aflatoxin B1 Degradation In Vitro*

AFB1 degradation (0.1 μg/mL) was assessed in sodium acetate buffer (1 mM, pH 5) using 5 U/mL of Ery4 laccase and AS 10 mM. ASC and DHA were also tested at two concentrations (1 or 10 mM). Aliquots were incubated at 25 ◦C and withdrawn after 1 h, 2 h, 3 h,6 h, 24 h, and 48 h, respectively, then immediately added with methanol (1:1 *v*/*v*) and stored at −20 ◦C until analysis.

#### *5.6. In Vitro Study of Aflatoxin B1 Degradation Products*

In order to analyze AFB1 degradation products, a degradation assay was performed as described in Section 5.4, but with higher amount of toxin (1 μg/mL). Controls and samples containing Ery4 were analyzed after 24 h of static incubation at 25 ◦C.

#### *5.7. UHPLC-HRMS Analysis*

The UHPLC-HMRS analysis was performed on a Q-Exactive Plus mass spectrometer equipped with a heated electrospray ion source (HESI II) coupled to an Ultimate 3000 UHPLC system (all from Thermo Fisher Scientific, San Jose, CA, USA).

The LC column was a Gemini C18 column (150 mm × 2 mm, 5-μm particles) (Phenomenex, Torrance, CA, USA) preceded by a Gemini C18 guard column (4 mm × 2 mm). The mass spectrometer operated in full scan mode combined with 5 MS2 events (all related instrumental parameters can be found in Ciasca et al. (2020) [63]. In addition, putative compound was identified by target MS/MS analysis (parallel reaction monitoring (PRM) mode). Settings for PRM data acquisition were as follows: resolution, 70,000 fwhm; microscans, 1; AGC target, 5 × <sup>10</sup>5; maximum injection time, 200 ms; isolation window, 0.5 m/z; nor-malized collision energy (NCE), 35 eV; spectrum data type, centroid. The inclusion list contained the monoisotopic masses of main significant features. The system was controlled by the Xcalibur (version 3.1), Chromeleon MS Link 6.8, and Q-Exactive Tune 2.8 software package.

#### *5.8. Aflatoxin B1 Degradation in Corn*

Corn kernels were finely ground (≤500 μm of diameter) by a Model Retsch ZM 200 laboratory mill (Retsch, Haan, Germany) and spiked with 50 μg/kg of AFB1. The sample was left all night to allow solvent evaporation prior to perform the degradation test.

The enzymatic reactions were performed using 2 g of corn flour in 15 mL tubes with 6 mL of sodium acetate buffer containing Ery4 (5 U/mL) and AS 10 mM. The effect of DHA was also evaluated together with Ery4 and AS at two different concentrations, namely 1 and 10 mM. Samples were incubated at 25 ◦C under shaking 150 rpm for 3 h.

#### *5.9. Aflatoxin Extraction and Chemical Analyses*

#### 5.9.1. Corn Samples Clean-Up

After incubation, all sample tubes were centrifuged at 15,000 rpm for 10 min, giving a supernatant (buffer) and a pellet (corn flour); then, AFB1 was quantified. AFB1 analyses were performed according to the AOAC Official Method 991.31 [64], based on immunoaffinity column clean-up and toxin determination by HPLC/FLD with post-column photochemical derivatization (UVE™, LCTech GmbH, Dorfen, Germany).

Briefly, the pellet plus 0.5 g of NaCl was extracted with 8 mL of methanol/water (70:30, *v*/*v*) by 60 min shaking. After filtration (filter paper, Whatman n. 4), 4 mL was diluted with 8 mL water and filter (glass microfiber filter, Whatman GF/A). The supernatant was filter through glass microfiber filter. A total of 6 mL of pellet extract fraction and 3 mL supernatant extract were purified through Afla Test™ WB immunoaffinity

column. The column was washed with 10 mL water, then eluted with 1 mL methanol. Afterwards the extracts were diluted with 1 mL of water.

#### 5.9.2. HPLC Analyses

Analyses were performed on a HPLC apparatus with a full loop injection system; 100 μL of each sample were injected. The fluorometric detector was set at wavelengths of 365 nm (excitation) and 435 nm (emission). The mobile phase consisted of a mixture of water/acetonitrile (70:30, *v*/*v*), and the flow rate was 1.0 mL/min. The temperature of the column was maintained at 40 ◦C. AFB1 was quantified by measuring peak areas at the retention time of aflatoxin standard solutions and comparing these areas with the relevant calibration curve. With this mobile phase, the retention time was about 12 min. The limit of quantification (LOQ) was 2 μg/kg for pellet and 1 μg/kg for supernatant based on a signal to noise ratio of 10:1, and the limit of detection (LOD) were 1 μg/kg for pellet and 0.5 μg/kg for supernatant based on a signal to noise ratio of 3:1.

#### *5.10. Lipid Peroxidation and H2O2 Content*

Lipid peroxidation was measured in terms of malondialdehyde (MDA) concentrations, following the method reported by Villani and colleagues [65]. Absorbance was measured at 532 and 600 nm, and MDA content was calculated and expressed as nmol g−<sup>1</sup> fresh weight.

The homogenate was filtered through four layers of cheesecloth to remove cellular debris and then centrifuged at 18,000× *g* for 20 min at 4 ◦C. The H2O2 content was measured as reported by Lanubile et al. [66]. A supernatant aliquot of the reaction mixture was read at 436 nm, and its absorbance was compared to the extinction coefficient of an H2O2 standard.

#### *5.11. Protein Content*

After the enzymatic treatment, samples were added with NaCl 0.4 M and 0.4% (*v*:*v*) of protease inhibitor cocktail (Sigma Aldrich, Milan, Italy) and incubated for additional 20 min. Then, samples were centrifuged at 10,000 rpm for 20 min, and the pellet and supernatant were separated.

The supernatant was dialyzed against H2O for 3 h to obtain the first water-soluble protein fraction. The pellet was resuspended in a solution containing EtOH 70% and 2-mercaptoethanol 0.01 M and incubated for 20 min. After centrifugation at 10,000 rpm for 20 min, an ethanol soluble fraction was obtained, while the pellet was further extracted using PBS 0.1 M, pH 7.4, SDS 2.5%, and NaCl 0.01 M to obtain the alcohol-insoluble protein fraction. The three protein fractions were quantified using Bradford method [67].

#### *5.12. Statistical Analyses*

Data are the means ± standard deviation of at least three independent biological replicates. One-factor analysis of variance (ANOVA), followed by Tukey's HSD test, was performed on means. Differences between samples and relative control were considered significant for a *p* < 0.05.

**Author Contributions:** Conceptualization, M.L., G.M. and C.P.; investigation, M.L., S.D.L., B.C. and M.H.; writing—original draft preparation, M.L., G.M., C.P., B.C. and M.H; writing—review and editing, M.L., G.M., C.P., B.C. and M.H.; visualization, M.L., S.D.L. and B.C.; supervision, M.H., G.M. and C.P. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

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

#### **References**


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## *Article* **Epigallocatechin Gallate and Glutathione Attenuate Aflatoxin B1-Induced Acute Liver Injury in Ducklings via Mitochondria-Mediated Apoptosis and the Nrf2 Signalling Pathway**

**Yanan Wang 1, Jiayu Wu 1, Lingfeng Wang 1, Ping Yang 1, Zuhong Liu 2, Shahid Ali Rajput 3, Mubashar Hassan <sup>1</sup> and Desheng Qi 1,\***


**Abstract:** Aflatoxin B1 (AFB1) exists widely in feed and food with severe hazards, posing a serious threat to human and animal health. Epigallocatechin gallate (EGCG) and glutathione (GSH) have been reported as having anti-oxidative and other functions. The present study aimed to investigate the detoxification effect of EGCG and GSH alone or in combination on AFB1 exposure in ducklings. Fifty one-day-old male ducklings were randomly assigned into five experimental groups (*n* = 10): 1. Control (CTR); 2. 0.3 mg/kg BW AFB1 (AFB1); 3. 0.3 mg/kg BW AFB1 + 100 mg/kg BW EGCG (AFB1 + EGCG); 4. 0.3 mg/kg BW AFB1 + 30 mg/kg BW GSH (AFB1 + GSH); 5. 0.3 mg/kg BW AFB1 + 100 mg/kg BW EGCG + 30 mg/kg BW GSH (AFB1 + EGCG + GSH). The experiment lasted for seven days. Compared with the CTR group, AFB1 reduced growth performance, total serum protein and albumin content, increased serum enzyme activity (alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, and γ-glutamyl transpeptidase), and caused pathological damage to the ducklings' livers. AFB1 exposure increased malondialdehyde content and decreased superoxide dismutase, total antioxidant capacity, catalase, glutathione peroxidase activities, and glutathione content in the liver. EGCG and GSH alone or in combination mitigated these adverse effects. Meanwhile, EGCG and GSH attenuate apoptosis of hepatocytes, and regulated AFB1-induced changes in the abundance of genes contained in the Keap1/Nrf2 signalling and apoptotic pathways. Collectively, these results suggest that EGCG and GSH alleviate the hepatocyte injury induced by AFB1 by inhibiting oxidative stress and attenuating excessive mitochondria-mediated apoptosis.

**Keywords:** aflatoxin B1; duckling; epigallocatechin gallate; glutathione; oxidative stress; Keap1/Nrf2 signalling; apoptosis

**Key Contribution:** EGCG and GSH alleviate AFB1-induced liver injury in ducklings by increasing antioxidant capacity and antagonising apoptosis.

#### **1. Introduction**

Mycotoxins are harmful naturally occurring secondary metabolites produced by fungi [1]. Aflatoxins (AFs) are poisonous mycotoxins produced principally by *Aspergillus flavus* and *Aspergillus parasiticus*, of which Aflatoxin B1 (AFB1) is the most hepatotoxic [2]. Corn, wheat, and other grains have a high detection rate of AFB1 [3], which seriously affects the health of poultry and humans throughout the food chain [4]. AFB1 has been reported to cause diarrhoea, poor feather quality, weight loss, multifocal hepatic necrosis,

**Citation:** Wang, Y.; Wu, J.; Wang, L.; Yang, P.; Liu, Z.; Rajput, S.A.; Hassan, M.; Qi, D. Epigallocatechin Gallate and Glutathione Attenuate Aflatoxin B1-Induced Acute Liver Injury in Ducklings via Mitochondria-Mediated Apoptosis and the Nrf2 Signalling Pathway. *Toxins* **2022**, *14*, 876. https://doi.org/10.3390/ toxins14120876

Received: 3 November 2022 Accepted: 13 December 2022 Published: 15 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/).

bile duct hyperplasia, skeletal deformation, and altered muscle alignment in poultry [5,6]. Liver cancer, immunosuppression, and stunted children have all been linked with foods contaminated with AFB1 [7]. Over 70% of the world's ducks are raised in China [8]. As ducklings are more sensitive to AFB1 than turkeys, lower doses of AFB1 can cause them bodily damage [9]. AFB1 exhibits its toxic action by being metabolised to exo-8, 9-epoxide (AFBO) in the liver [10]. The Keap1 (Kelch-like ECH-associated protein 1)/Nrf2 (nuclear factor erythroid 2-related factor 2) pathway enables cells to adapt to oxidative stress caused by external stimuli, and some plant extracts may activate this pathway [11]. Apoptosis plays an essential role in maintaining stability in the internal environment [12]. AFB1 can dysregulate the Keap1/Nrf2 pathway and cause excessive apoptosis in hepatocytes [13]. Hence, it will be an effective measure to improve the antioxidant capacity and inhibit excessive apoptosis caused by liver injury.

Epigallocatechin gallate (EGCG) is the main active ingredient in green tea. Other catechins include epicatechin-3-gallate, epigallocatechin and epicatechin, but EGCG is the most abundant [14]. It not only promotes animal growth performance and egg quality, ameliorates body fatty acid metabolism, and regulates intestinal health [15,16], but also contributes to cardioprotection, renoprotection, hepatoprotection, and neuroprotection in humans [17]. More importantly, EGCG is a scavenger of reactive oxygen/nitrogen and has potent antioxidant capacities. Moreover, it reduces the damage to cells caused by oxidative stress by capturing oxygen free radicals, restoring their redox status and mitochondrial function [18,19]. Previous studies have shown that EGCG can attenuate bleomycin-induced pulmonary fibrosis through the Keap1/Nrf2 signalling pathway [20]. Four hundred mg/kg of EGCG in the diet significantly alleviated heat stress in quail [21]. The preventive effect of EGCG against AFB1-induced liver injury and the mechanisms involved are not clarified. Therefore, it is necessary to proceed with this work.

Glutathione (GSH) is a tripeptide comprising cysteine, glutamic acid, and glycine. It exists in two forms in animals, oxidised (GSSG) and reduced (GSH), both of which play a significant role in bodily redox status [22]. The leading absorption site of exogenous GSH is the small intestine. Oral GSH in animals and humans can increase the content of GSH in the body [23], improve antioxidant capacity (i.e., protect cells from oxidative damage), protect intestinal mucosa, and enhance the transport and absorption of nutrients [22]. Studies have shown that GSH can increase the resistance of carp to nitric oxide stress and lipopolysaccharide (LPS) stimulation [24]. Adding GSH to the diet alleviated the oxidative damage caused by ochratoxin A and significantly inhibited cell apoptosis in rats [25]. Therefore, GSH may exhibit a positively beneficial effect in mitigating the hazards of AFB1.

The present study used EGCG and GSH to alleviate the damage caused by AFB1 in ducklings. In particular, we investigated whether EGCG and GSH could alleviate liver damage through the Keap1/Nrf2 signalling pathway and the inhibition of apoptosis and whether there was a mutual effect between them. The present experiment hoped to prompt the individual and combined use of EGCG and GSH to ameliorate toxin damage in animals.

#### **2. Results**

#### *2.1. EGCG and GSH Inhibit AFB1-Induced Changes in Growth Performance and Liver Index of Ducklings*

The effects of AFB1 and EGCG or GSH on ducklings' growth are shown in Figure 1A,B. In this experiment, ducks were treated with gavage, and each group of ten ducks was individually numbered but housed in a combined pen, so only the mean values of feed intake were calculated. As can be seen from the Figure 1A,B, there was no significant difference in the initial body weight, but after acute attacks, the AFB1 group had significantly reduced body weight (*p* < 0.01) compared with the CTR group, and the feed intake decreased by 13.1%. However, the EGCG and GSH alone and in combination significantly increased the ducklings' body weights compared with the AFB1 group, while the feed intake increased by 7.7%, 2.5%, and 9.8%, respectively, showing that the combination of EGCG and GSH

was more effective. As Figure 1C shows, AFB1 significantly increased the relative weight of the ducklings' livers (*p* < 0.01), while EGCG and GSH significantly decreased as compared with the AFB1 group. The results indicate that EGCG and GSH alleviated the damage caused by AFB1, but a combination was more effective.

**Figure 1.** Effect of Epigallocatechin gallate (EGCG) and Glutathione (GSH) on Aflatoxin B1 (AFB1) induced changes in growth performance and liver index of ducklings. (**A**) Average total feed intake per duckling during the experiment. (**B**) Body weight of each duckling at the beginning and end of the experiment. (**C**) Relative weight of the liver. Results are expressed as means ± SEM (*n* = 10). \* *p* < 0.05, \*\* *p* < 0.01 vs. control (CTR) group; # *p* < 0.05, ## *p* < 0.01 vs. AFB1 group; Δ *p* < 0.05, ΔΔ *p* < 0.01 significant difference between AFB1 + EGCG + GSH and AFB1 + EGCG or AFB1 + GSH groups.

#### *2.2. EGCG and GSH Protect against AFB1-Induced Liver Damage in Ducklings*

The effects of EGCG and GSH alone or in combination on the serum biochemistry of AFB1-exposed ducklings are shown in Figure 2. Serum biochemistry was affected adversely by AFB1 as the enzyme activities of alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), and γ-glutamyl transpeptidase (γ-GT) were elevated (*p* < 0.01, Figure 2A–C,F). The use of EGCG or GSH mitigated these adverse effects. Compared with the AFB1 group, the enzyme activities of ALT, AST, ALP, and γ-GT decreased by 19.4%, 41.2%, 23.0%, and 35.2%, respectively, in the combined detoxification group. The AFB1-treated group reduced total serum protein (TP, 37.9%) and albumin (ALB, 49.2%) levels extremely significantly (*p* < 0.01; Figure 2D,E). Both EGCG or GSH increased the levels of TP and ALB compared with the AFB1 group, with the combined group increasing by 45.0% and 47.1%, respectively. This was still lower than the control group. The results indicate that EGCG and GSH alleviated the negative effects caused by AFB1 on the serum biochemistry of ducklings, but a combination was more effective.

#### *2.3. EGCG and GSH Mitigate AFB1-Induced Oxidative Stress in the Livers of Ducklings*

To evaluate the damage caused by AFB1 and the protective effect of EGCG and GSH, we examined the antioxidant capacity of the ducklings' livers. Compared with the CTR group, the AFB1 group highly significantly elevated malondialdehyde (MDA) content (*p* < 0.01), while EGCG, GSH, and a combination of both decreased MDA content by 27.8%, 25.7%, and 37.7%, respectively (Figure 3A). Meanwhile, the levels of antioxidant enzymes and GSH were also negatively affected, with the enzymatic activities of superoxide dismutase (SOD), glutathione peroxide (GPX), total antioxidant capacity (T-AOC), and catalase (CAT) decreasing by 23.0%, 26.0%, 34.2%, and 38.4% (Figure 3B,D–F), respectively, compared with the CTR group, while the levels of GSH decreased by 40.6% (Figure 3C). Thus, EGCG and GSH effectively prevented their alteration, especially in MDA, T-AOC, and CAT, where there was a significant joint effect (*p* < 0.05). The results indicate that EGCG or GSH alleviated the oxidative damage caused by AFB1, but a combination was more effective.

**Figure 2.** Effect of EGCG and GSH on AFB1-induced changes in serum biochemical parameters. (**A**) ALT, alanine aminotransferase; (**B**) AST, aspartate aminotransferase; (**C**) ALP, alkaline phosphatase; (**D**) TP, total protein; (**E**) ALB, albumin; (**F**) γ-GT, γ-glutamyl transpeptidase. Results are expressed as means ± SEM (*n* = 10). \* *p* < 0.05, \*\* *p* < 0.01 vs. CTR group; # *p* < 0.05, ## *p* < 0.01 vs. AFB1 group; Δ *p* < 0.05, ΔΔ *p* < 0.01 significant difference between AFB1 + EGCG + GSH and AFB1 + EGCG or AFB1 + GSH groups.

**Figure 3.** Effect of EGCG and GSH on AFB1-induced oxidative stress in the livers of ducklings. (**A**) MDA, malondialdehyde; (**B**) SOD, superoxide dismutase; (**C**) GSH, glutathione; (**D**) GPX, glutathione peroxidase; (**E**) T-AOC, total antioxidant capacity; (**F**) CAT, catalase. Results are expressed as means ± SEM (*n* = 10). \* *p* < 0.05, \*\* *p* < 0.01 vs. CTR group; # *p* < 0.05, ## *p* < 0.01 vs. AFB1 group; Δ *p* < 0.05, ΔΔ *p* < 0.01 significant difference between AFB1 + EGCG + GSH and AFB1 + EGCG or AFB1 + GSH groups.

#### *2.4. EGCG and GSH Prevent AFB1-Induced Alterations in the Microstructure and Ultrastructure of Duckling Livers*

The liver is the target organ of AFB1 action, so we observed its microscopic and ultrastructural structure. As Figure 4 shows, the liver tissue structure of the CTR group was normal, with an intact hepatocyte structure and no fatty degeneration, necrosis, or inflammatory cell infiltration. However, we observed that large areas of hepatocytes were ill-defined, some cells were swollen and necrotic, and disappeared nuclei or pyknosis was present in the AFB1 group. Compared with the AFB1 group, inflammatory cell infiltration and hepatocyte necrosis were reduced in the detoxification group alone or in combination, especially in the combined detoxification group. However, lipid droplets were still present in some hepatocytes.

**Figure 4.** Effect of EGCG and GSH on the microscopic pathological structure of the livers of ducklings exposed to AFB1. Magnification 200×, scale bars = 100 μm. Green arrows: cell swelling and necrosis, nuclear pyknosis; black arrows: inflammatory cell infiltration in the hepatic parenchyma; red arrows: a small number of lipid droplets can be seen in the cytoplasm.

To examine the internal structure of hepatocytes more closely, we performed transmission electron microscopy scans (Figure 5). In the CTR group, the nuclei and mitochondrial structures were normal, while in the AFB1 group, the nuclei underwent significant wrinkling, and the mitochondrial structures were heavily abnormal, with swelling and disrupted mitochondrial ridges. Although the mitochondrial structure was also lesioned to varying degrees in the EGCG or GSH groups, it was largely improved relative to the AFB1 group. The best results were seen in the combined group.

#### *2.5. EGCG and GSH Alleviate the Interference of AFB1 on the Keap1-Nrf2 Antioxidant Signalling Pathway*

As Figure 6 shows, the abundance of related genes in the Nrf2 signalling pathway was significantly downregulated in the AFB1 group compared with the CTR group (*p* < 0.01). However, the gene expression of Keap1, an Nrf2 repressor, was significantly elevated (*p* < 0.01). These changes were back-regulated to varying degrees in the EGCG and GSH groups and in the combined group. The combined group Nrf2, HO-1 and SOD1 gene expression reached significant levels (*p* < 0.05) compared to the group used alone. The results indicate that EGCG and GSH can alleviate the oxidative damage caused by AFB1 and that they interact to some degree.

**Figure 5.** Effect of EGCG and GSH on the ultramicro-pathological structure of the livers of ducklings exposed to AFB1. Magnification 20,000×, scale bars = 1 μm. Red arrows represent the nucleus of the cell, and green arrows represent mitochondria.

**Figure 6.** Effect of EGCG and GSH on the abundance of genes involved in the Keap1-Nrf2 signalling pathway in the livers of ducklings exposed to AFB1. All results are expressed as means ± SEM (*n* = 6). \* *p* < 0.05, \*\* *p* < 0.01 vs. CTR group; # *p* < 0.05, ## *p* < 0.01 vs. AFB1 group; Δ *p* < 0.05, ΔΔ *p* < 0.01 significant difference between AFB1 + EGCG + GSH and AFB1 + EGCG or AFB1 + GSH groups.

#### *2.6. Protective Effects of EGCG and GSH on AFB1-Induced Apoptosis of Duckling Hepatocytes*

In order to evaluate the protective effect of EGCG and GSH alone or in combination against AFB1-induced apoptosis, hepatocyte apoptosis and the expression of genes related to apoptosis mediated by mitochondria were examined by terminal deoxynucleotidyl transferase dUTP nick end-labelling (TUNEL) staining and RT-qPCR, respectively. Green fluorescence was significantly enhanced (as evidenced in the increased number of apoptotic cells) in all AFB1-exposed groups (Figure 7A); the apoptosis rate (TUNEL positive rate) was elevated to 8.31% in the AFB1 group, while the apoptosis rate decreased by 61.5%, 49.2%, and 74.0% in the EGCG, GSH, and combined groups, respectively, compared with the AFB1 group (Figure 7B). Compared with the CTR group, the gene abundance of the pro-apoptotic gene Bax, as well as Cyt-c, Caspase-3, and p53 were significantly up-regulated (*p* < 0.01), and the anti-apoptotic gene Bcl-2 was significantly down-regulated (*p* < 0.01, Figure 7C) in the AFB1 group; EGCG and GSH alone or in combination had a positive effect. It was concluded that EGCG and GSH attenuated AFB1-induced apoptosis in hepatocytes.

**Figure 7.** Effects of EGCG and GSH on AFB1-induced apoptosis of ducklings' hepatocytes. (**A**) Terminal deoxynucleotidyl transferase dUTP nick end-labelling (TUNEL) staining to detect apoptosis. Magnification 200 ×, scale bars = 100 μm. Fluorescently labelled green indicates apoptotic cells, and blue indicates the nucleus. (**B**) TUNEL positive cells. (**C**) Expression of genes associated with mitochondria-mediated apoptosis, Cyt-c, Bax, Bcl-2, Caspase-3, Caspase-9, p53. All results are expressed as means ± SEM (*n* = 6). \* *p* < 0.05, \*\* *p* < 0.01 vs. CTR group; # *p* < 0.05, ## *p* < 0.01 vs. AFB1 group; Δ *p* < 0.05, ΔΔ *p* < 0.01 significant difference between AFB1 + EGCG + GSH and AFB1 + EGCG or AFB1 + GSH groups.

#### **3. Discussion**

It is well-known that AFB1 is commonly found in feed and causes severe damage to commercial animals, especially ducks [26,27]. Growth retardation and hepatic lesion are among the most important symptoms of AFB1 poisoning. In the present study, we discovered that AFB1 reduced the ducklings' feed intake and body weight, as well as caused liver damage. Our findings are consistent with previous research showing that AFB1 causes a decrease in food intake, metabolic capacity, body weight, and significantly higher liver coefficients [28–30]. The results of the present study indicated that EGCG and GSH significantly increased body weight and decreased liver indices. Serum ALT, AST, and ALP are the most sensitive indicators for evaluating liver damage, and AFB1 in the

diet can increase the levels of these enzymes [31]. In one study, when ducklings were fed a diet of 0.1 mg/kg AFB1, the levels of AST, ALT, and the ratio of AST/ALT increased [32]. Because AFB1 inhibits protein biosynthesis, serum TB and ALB can be used to evaluate its impact [33]. Our results confirmed this: AFB1 elevated the levels of ALT, AST, ALP, and γ-GT while decreasing the content of TB and ALB compared with the CTR group. The addition of EGCG and GSH slowed down the change.

Oxidative stress can promote the formation of reactive oxygen species (ROS) in animal target organs [34]. Numerous studies have shown that excessive ROS can damage macromolecules such as proteins and nucleic acids, thereby producing a large amount of MDA. Therefore, MDA, as the end product of lipid peroxidation, is an important indicator for detecting oxidative damage [35,36]. However, excessive ROS in the body can be scavenged by antioxidant enzymes, including SOD, GPX, CAT, and GSH. In the present study, exposure to AFB1 increased the amount of MDA, while the content of GSH and the enzymatic activities of T-AOC, SOD, CAT, and GPX decreased. Apparently, AFB1 induced oxidative stress in the ducklings' livers. The addition of EGCG and GSH also alleviated oxidative stress. Previous studies have shown that EGCG can attenuate carbon tetrachloride-induced oxidative stress in mouse livers and protect against H2O2-induced cellular oxidative damage [37,38]. Exogenous GSH has been found to have similar antioxidant effects in acute kidney injury in rats [39]. At the same time, we observed that AFB1 induced pathological changes in the liver. These results indicated that AFB1 caused oxidative damage to the liver, but EGCG and GSH could protect it by enhancing its antioxidant status. The antioxidant properties of EGCG and GSH themselves, as well as the fact that GSH can act as a substrate for GPX and GST, may explain the common effect exhibited by them.

Oxidative stress caused by AFB1 can regulate the expression of a series of genes involved in the antioxidant system through the Keap1-Nrf2 signalling pathway. Nrf2 is the main regulator of cells that respond to environmental stress, inducing the expression of detoxification and antioxidant enzymes. The activity of Nrf2 is dependent on the regulation of the Keap1 adaptor protein, which is a negative regulator of the former [40,41]. Under non-stress conditions, Nrf2 binds to Keap1 in the cytoplasm to promote Nrf2 ubiquitination and proteasomal degradation; when stimulated, Nrf2 dissociates from Keap1 into the nucleus and combines with nuclear receptors to regulate the expression of downstream target genes (NQO1, HO-1, GCLC, GCLM, and so on) [42], thereby performing antioxidant or detoxification functions. It has been demonstrated that EGCG can strengthen cellular defences against chemical carcinogens as well as ultraviolet (UV) and oxidative stress through the Keap1-Nrf2 signalling pathway [43]. In one experiment, the EGCG treatment group normalised the expression of Keap1-Nrf2 and its downstream regulatory proteins in fluoride-treated rat kidneys [44]. We noted a significant upregulation of Keap1 mRNA expression in the AFB1-treated group compared with the CTR group, indicating an enhanced negative regulation of Nrf2 by Keap1, while Nrf2 and its related genes (NQO1, HO-1, GCLC, GCLM, SOD1, GPX1, and CAT) were downregulated. Treatment with EGCG significantly reversed these effects (a finding that is consistent with previous studies). However, the effect of GSH on this pathway has not been investigated, so we speculated that it might regulate the expression of genes by balancing ROS production. This deserves more investigation. We concluded that EGCG and GSH contribute to the antioxidant capacity of the body through the Keap1-Nrf2 signalling pathway and that they are most effective in combination.

Apoptosis (i.e., programmed cell death) plays an essential role in controlling cell numbers and maintaining the homeostasis of multicellular organisms. Abnormal regulation of apoptosis has been associated with the development of a variety of diseases [45]. AFB1 has been reported to induce apoptosis in hepatic, pulmonary, and bone marrow cells [46,47]. The present study found hepatocytes undergoing significant apoptosis in the AFB1 group. It is widely known that mitochondria perform a central role in apoptosis initiated by many kinds of stimuli and that key events in apoptosis are associated with mitochondria [48]. Livers have been observed with severe mitochondrial lesions. In such cases, membrane

permeability is altered, and Cyt-c enters the cytoplasm from the mitochondria, binding to the apoptosis protease activator Apaf-1 and caspase-9 and activating caspase-9, which in turn induces the activation of caspase-3 and subsequently triggers apoptosis mediated by the mitochondria [49]. However, mitochondria-mediated apoptosis is regulated by the proapoptotic protein Bax and the anti-apoptotic protein Bcl-2 [50]. The present study showed that AFB1 reduced the mRNA expression of Bcl-2 and elevated the mRNA expression of Bax, while the expression of associated apoptotic genes (Cyt-c, caspase-3, caspase-9, and so on) was significantly elevated. However, EGCG and GSH inhibited the excessive apoptosis of hepatocytes caused by AFB1 by regulating the expression of these genes. Studies have shown that EGCG protects against apoptosis in human umbilical vein endothelial cells by regulating the mitochondria-dependent apoptotic signalling pathway [51], while exogenous GSH defends IPEC-J2 cells from oxidative stress-induced apoptosis [52]. Apoptosis can be activated by oxidative stress [36]. Therefore, we speculate that EGCG and GSH alleviate apoptosis caused by AFB1 in hepatocytes either directly or by inhibiting oxidative stress. However, the mechanism of interaction between EGCG and GSH needs to be further researched.

#### **4. Conclusions**

In the present study, AFB1 caused serious damage to the ducklings. The results suggest that EGCG and GSH can alleviate acute liver injury by improving hepatic antioxidant capacity through the Keap1-Nrf2 signalling pathway and inhibiting the excessive apoptosis of hepatocytes mediated by mitochondria. This explains the protective mechanism of EGCG and GSH alone or in combination against AFB1-induced liver injury. The present study also provides a theoretical basis for their application, and we suggest that EGCG and GSH could be used as promising duck feed additives to counteract AFB1 damage.

#### **5. Materials and Methods**

#### *5.1. Animals and Experimental Design*

Age is an important factor affecting the bird's resistance to AFB1, and male ducklings are more sensitive (male ducklings produce more AFBO than females), so we chose younger males to complete the experiment [53]. One-day-old male Cherry Valley ducks were purchased from Wuhan Yongsheng Duck Industry Co., Ltd. (Wuhan, China). The ducklings were kept in a controlled environment at a temperature of 30 ± 2 ◦C and 60 ± 5% humidity. The experiment (No. HZAUDU-2022-0002) was approved by the Animal Ethics Committee of Huazhong Agricultural University (Wuhan, China).

After three days of acclimatisation, 50 male ducklings were randomly divided into five groups (*n* = 10): 1. Control group (CTR); 2. Treated with AFB1 (>99%, Pribolab, Qingdao, China) 0.3 mg/kg BW (AFB1); 3. Treated with AFB1 0.3 mg/kg BW + EGCG (98%, Shanghai Yuanye Biotech Co., Ltd., Shanghai, China) 100 mg/kg BW (AFB1 + EGCG); 4. Treated with AFB1 0.3 mg/kg BW + GSH (Reduced, 98%, Aladdin, Shanghai, China) 30 mg/kg BW (AFB1 + GSH); 5. Treated with AFB1 0.3 mg/kg BW + EGCG 100 mg/kg BW + GSH 30 mg/kg BW (AFB1 + EGCG + GSH). Each group of ten ducklings was kept in a pen, marked and weighed individually. All ducklings were gavaged with the same concentration and 1 mL Volume/200 g BW. The acute liver injury experiment cycle lasted for 7 days. On Days 1–6, they were weighed daily and gavaged with distilled water, distilled water, EGCG, GSH, and EGCG + GSH, respectively. On Day 4, Groups 2 to 5 were treated with AFB1 0.5 h after the first gavage, and the control group was given the corresponding solvent gavage (4% dimethyl sulfoxide). Slaughter sampling took place on Day 7. The composition and nutrient levels of the basal diet are shown in Appendix A, Table A1. The acute toxic dose of AFB1 was determined based on previous reports [54,55] and preliminary experiments. Gavage doses of EGCG and GSH refer to preliminary experiment. The health status of the ducklings was strictly observed, and the body weight and feed intake were recorded during the experiment.

#### *5.2. Sample Collection*

After the ducklings fasted for 12 h, blood samples were collected using wing venipuncture into a tube. The blood samples were centrifuged at 3500 rpm for 10 min to obtain serum, which was divided and stored at −80 ◦C for biochemical analysis. The ducklings were immediately sacrificed and dissected to remove the liver, rinsed in cold saline, and weighed. A portion of liver tissue was cut and placed in paraformaldehyde fixative and 2.5% glutaraldehyde, respectively, for hematoxylin and eosin (H&E) staining or TUNEL detection and ultrastructural observation. The remaining part of each liver was stored at −80 ◦C in a refrigerator to detect antioxidant indexes, gene expression, and so on. The relative weight of the livers was calculated using the following formula:

Relative weight = liver weight (g)/body weight (g) × 100%

#### *5.3. Determination of Serum Biochemical Indicators*

The serum enzyme activities of ALT, AST, ALP, and γ-GT, as well as the content of ALB and TP, reflect the function of the liver. These indicators were measured using an automatic biochemical analyser according to the manufacturer's set procedure (Mindray, Shenzhen, China). The serum samples were placed in a cryogenic sample tray. ALT, AST, ALP, and γ-GT were expressed as U/L, while ALB and TP were expressed as g/L. All of these kits were purchased from the same manufacturer (Mindray, Shenzhen, China).

#### *5.4. Detection of Antioxidant Capacity of the Liver*

Liver tissue homogenates were prepared according to the requirements of the corresponding kits, and the protein concentration of the homogenate supernatant was determined by the BCA protein assay kit (Beyotime Biotechnology, Shanghai, China). SOD, GPX, MDA, T-AOC, CAT, and GSH kits were procured and operated according to the manufacturer's instructions (Nanjing Jiancheng Biotech, Nanjing, China). Absorbance was measured by a microplate reader (Multiskan MK3, Thermo Fisher Scientific, Waltham MA, USA) or visible light spectrophotometer (722E, Shanghai Spectrum Instruments Co., Ltd., Shanghai, China), and the enzyme activity or substance content was calculated and analysed.

#### *5.5. Histopathological Analysis*

Fresh liver tissue samples were placed in 4% paraformaldehyde and fixed for more than 24 h. The tissues were dehydrated with different concentrations of alcohol and embedded in wax. The wax blocks were placed in a microtome (Leica RM2016, Wetzlar, Germany) and cut into sections of 4 μm thickness. Staining with hematoxylin and eosin was performed for histopathological observation.

#### *5.6. Ultrastructural Pathology Observation*

Liver samples were cut to around 1 mm<sup>3</sup> in size and placed in 2.5% glutaraldehyde for 24 h. After 24 h, the samples were washed three times with 0.1 M PBS and fixed with 1% osmium acid for 2 h. The samples were rewashed with 0.1 M PBS, then dehydrated with gradient acetone and embedded in resin. The embedded samples were cut into 60 nm sections using an ultramicrotome (Leica UC5, Wetzlar, Germany), stained with uranyl acetate and lead citrate solution, and observed under a transmission electron microscope (Hitachi H-7650, Tokyo, Japan) for scanning and photographing [56].

#### *5.7. Detection of Apoptosis by TUNEL Staining*

Following the TUNEL kit manufacturer's instructions (Roche, Basel, Switzerland), the embedded liver sections were dewaxed, rehydrated, and then incubated with proteinase K at 37 ◦C for 30 min and washed three times with PBS. Fifty 50 μL of TUNEL reaction solution were added dropwise to the tissue, incubated at 37 ◦C for 2 h in the dark, washed again with PBS three times, and then incubated with 4,6-diamidino-2-phenylindole (DAPI) staining solution for 10 min while keeping it out of the light. After blocking, the images were

observed and collected using an inverted fluorescence microscope (Olympus IX51, Tokyo, Japan). Fluorescence signals were analysed with Image-Pro Plus 6.0 (Media Cybernetics, Silver Spring, MD, USA), and apoptosis rates were calculated.

#### *5.8. Quantitative Real-Time PCR*

Total RNA was extracted from the ducklings' livers using Trizol reagent (TaKaRa, Dalian, China), and the quality (A260/A280) and concentration were evaluated using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). Genomic DNA was removed, and RNA was reverse transcribed into cDNA using PrimeScriptTM RT reagent Kit with gDNA Eraser (TaKaRa, Dalian, China) according to the steps in the instructions, and expressed genes were evaluated by Real-Time PCR using TB Green® Premix Ex TaqTM II (TaKaRa, Dalian, China). The primer sequences are shown in Appendix A Table A2. All primers were designed by Sangon Biotech (Shanghai, China) and synthesised by Tsingke Biotechnology Co., Ltd. (Beijing, China). The relative mRNA abundance was analysed following the 2−ΔΔCt formula and normalised with the housekeeping gene GAPDH [57].

#### *5.9. Statistical Analysis*

The results were analysed using one-way ANOVA with SPSS Version 26 (SPSS Incorporated, Armonk, NY, USA) and Tukey's multiple comparisons as the post-hoc test. Outcomes were expressed as mean ± standard error (SEM). GraphPad Prism Version 9.0 (GraphPad Prism, San Diego, CA, USA) was used to visualise the data. In all statistical analyses, *p* < 0.05 was considered significant and *p* < 0.01 was considered highly significant.

**Author Contributions:** D.Q., conceptualisation, writing—review and editing, project administration and funding acquisition; Y.W., methodology, formal analysis, data curation and writing—original draft preparation; J.W., L.W. and P.Y., formal analysis, data curation and visualisation; Z.L., S.A.R. and M.H., writing—review and editing. All authors have read and agreed to the published version of the manuscript.

**Funding:** This project was supported by the National Key Research and Development Program of China (2016YFD0501207).

**Institutional Review Board Statement:** This experiment was approved by the Animal Ethics Committee of Huazhong Agricultural University (No. HZAUDU-2022-0002).

**Informed Consent Statement:** Not applicable.

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

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

#### **Appendix A**

**Table A1.** Composition and nutrient level of basal diet.


<sup>1</sup> Premix provided per kilogram of diet: 10,000 IU of vitamin A, 2500 IU of vitamin D3, 35 IU of vitamin E, 2.5 mg of vitamin K3, 2.5 mg of vitamin B1, 9 mg of vitamin B2, 0.02 mg of vitamin B12, 15 mg of calcium pantothenate, 60 mg of niacin, 1.5 mg of folic acid, and 0.2 mg of biotin; 12 mg of Cu, 80 mg of Fe, 60 mg of Zn, 92 mg of Mn, 0.3 mg of Se, and 0.3 mg of I. <sup>2</sup> All nutrient levels were calculated.


#### **Table A2.** Primer sequences used in qRT-PCR.

#### **References**


### *Communication* **Inhibition of Essential Oils on Growth of** *Aspergillus flavus* **and Aflatoxin B1 Production in Broth and Poultry Feed**

**Bing Han 1,\*, Guang-Wu Fu <sup>2</sup> and Jin-Quan Wang 1,\***


**Abstract:** Aflatoxin B1 (AFB1), a common contaminant in food and feed during storage, does great harm to human and animal health. Five essential oils (thymol, carvacrol, cinnamaldehyde, eugenol, and citral) were tested for their inhibition effect against *Aspergillus flavus* (*A. flavus*) in broth and feed. Cinnamaldehyde and citral were proven to be most effective against *A. flavus* compared to others and have a synergistic effect when used simultaneously. The broth supplemented with cinnamaldehyde and citral was inoculated with *A. flavus* (10<sup>6</sup> CFU/mL) by using the checkerboard method, and mold counts and AFB1 production were tested on days 0, 1, 3, and 5. Similarly, 100 g poultry feed supplemented with the mixture of cinnamaldehyde and citral at the ratio 1:1 was also inoculated with *A. flavus*, and the same parameters were tested on days 0, 7, 14, and 21. In poultry feed, cinnamaldehyde and citral significantly reduced mold counts and AFB1 concentrations (*p* < 0.05). Results showed that cinnamaldehyde and citral have a positive synergy effect and could both inhibit at least 90% the fungal growth and aflatoxin B1 production at 40 μg/mL in broth and poultry feed, and could be an alternative to control aflatoxin contamination in food and feed in future.

**Keywords:** aflatoxin B1; cinnamaldehyde; citral; inhibition; synergy

**Key Contribution:** Cinnamaldehyde and citral were proven to have a synergistic effect when used simultaneously and to be most effective against *A. flavus* and the production of AFB1 in broth and feed in the research.

### **1. Introduction**

Aflatoxins (AF) constitute secondary metabolites produced by *Aspergillus flavus* and *Aspergillus parasitic* which contaminate a variety of feed ingredients, including peanuts, corn, and cottonseed [1]. Aflatoxin B1 (AFB1) is one of the most toxic members of the aflatoxin family [2]. Previous studies showed that young chicks were especially vulnerable to AF, which may depress feed conversion efficiency and body weight gain, and ultimately cause significant economic losses [3,4]. Because of the carcinogenicity of AF, AF residues in chicken may pose risks to human health [5,6]. AF severely influences the health and growth performance of animals. Therefore, it is necessary to develop a method by which to control the production of AF in feed. Essential oils derived from flavorants often have different capacities to inhibit the growth and toxicity of *A. flavus.*

Essential oils (EO) are complex mixtures of secondary plant metabolites. Moreover, because of their antimicrobial effects, essential oils have been widely used as food preservatives. Over the past several decades, some studies have discovered that various essential oils could also resist fungal growth [7,8]. Kumar [9] reported that the eugenol could inhibit the growth of *A. flavus*. Cinnamaldehyde, thymol, carvacrol et al. also have a strong inhibition to the growth of *A. flavus* [10–12]. Therefore, for essential oils derived from plants, it is a safe substitute for antibiotics. The objective of this study was to determine the

**Citation:** Han, B.; Fu, G.-W.; Wang, J.-Q. Inhibition of Essential Oils on Growth of *Aspergillus flavus* and Aflatoxin B1 Production in Broth and Poultry Feed. *Toxins* **2022**, *14*, 655. https://doi.org/10.3390/ toxins14100655

Received: 26 August 2022 Accepted: 20 September 2022 Published: 22 September 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/).

inhibition of five different essential oils to *A. flavus* and the inhibition of AFB1 production in broth and poultry feed; in addition, a low concentration of essential oils was studied, which was not referred to in the previous studies. Low concentrations of essential oil could not only reduce the harm to animals but reduce the cost of feed industry.

#### **2. Results**

#### *2.1. The Inhibition of Different Concentration of Essential Oils against A. flavus*

The fungal growth inhibition was assessed by testing absorbance at 600 nm. In Figure 1, cinnamaldehyde inhibited 94.4% of the four fungal growth types, while other tested essential oils inhibited 93.7%, 86.9%, 80.1%, 78%, respectively. Consequently, it was concluded that cinnamaldehyde and citral had the most significant inhibitory effects on the growth of *A. flavus* CGMCC 3.2890 at the concentration of 40 μg/mL, and inhibition rate of cinnamaldehyde was higher compared to carvacrol (*p* < 0.05) but no significance compared to other essential oils (*p* > 0.05).

**Figure 1.** Inhibition of different essential oils at the concentration of 40 μg/mL. Different small letters in the same row (a, b) denote a significant difference *(p* < 0.05) among values, based on Tukey's test.

Consequently, cinnamaldehyde and citral were screened for further research with regard to their inhibitory effects on the growth of *A. flavus* in feed. Representative strain *A. flavus* CGMCC 3.2890 was considered for further research.

#### *2.2. MIC Tests and Synergy Effects of the Best Effect of Essential Oils on Fungal Growth in Broth by Using Checkerboard*

The synergy effect of cinnamaldehyde and citral against *A. flavus* CGMCC 3.2890 was tested by using the checkerboard method. The modal minimum inhibition concentration (MIC) results are presented in Table 1. The two essential oils synergistically affected *A. flavus* CGMCC 3.2890 as shown in Table 2.

**Table 1.** Modal MIC results by broth microdilution.



**Table 2.** Synergy method results.

From the results of Table 2 and the FIC value (FIC = 0.5), it could be concluded that cinnamaldehyde and citral had the synergy effects when used simultaneously.

#### *2.3. Effects of Essential Oils on Fungal Growth and AFB1 Production in Poultry Feed*

Cinnamaldehyde and citral were screened for further research with regard to their inhibitory effects on the growth of *A. flavus* in poultry feed on days 0, 7, 14, and 21, respectively. Representative strain *A. flavus* CGMCC 3.2890 was considered for further research in feed. The effects of combination of two essential oils on the growth of *A. flavus* CGMCC 3.2890 in feed were shown in Figures 2 and 3, respectively.

**Figure 2.** Inhibition rate (IR) of cinnamaldehyde and citral on the growth of *A. flavus* 3.2890 in feed at 40 μg/mL (CAD40), 80 μg/mL (CAD80), 160 μg/mL (CAD160), and 320 μg/mL (CAD320). Different small letters in the same row (a, b, c) denote a significant difference (*p* < 0.05) among values, based on Tukey's test.

Figure 2 showed that on day 7 there was no significance among the CAD80, CAD160, and CAD320 (*p* > 0.05) with IR almost 100%, but on days 14 and 21, the growth of molds was significantly decreased at 160 μg/mL (CAD160) and 320 μg/mL (CAD320) compared to CAD40 treatment, respectively, at the end of the storage period. Therefore, the addition of cinnamaldehyde and citral could suppress the molds sprouting in feed during the first week.

Figure 3 showed the inhibitory effect of cinnamaldehyde and citral on AFB1 production by *A. flavus* 3.2890 in feed, where it could be seen that CAD160 and CAD320 treatments could completely inhibit the productions of AFB1 on day 14 and day 21 (*p* < 0.05) compared to other groups, and CAD40 and CAD80 could reduce the production of AFB1 to some extent (*p* < 0.05). However, with the time going, a high concentration could still totally inhibit fungus growth and AFB1 production on day 21, while the IR of

low centration decreased, but compared to CT treatment, the low concentration could still play an important inhibition role to some extent.

**Figure 3.** Inhibition rate (IR) of cinnamaldehyde on AFB1 production by *A. flavus* CGMCC 3.2890 in feed at 40 μg/mL (CAD40), 80 μg/mL (CAD80), and 160 μg/mL (CAD160). Different small letters in the same row (a, b, c) denote a significant difference (*p* < 0.05) among values based on Tukey's test.

#### **3. Discussion**

In this research, a high-concentration treatment could totally inhibit the growth of fungus and AFB1 production even on day 21, perhaps because the essential oils have killed the fungus, and the low concentration of essential oils probably just inhibited the fungus. In line with Mahnoud [13] and López–Malo et al. [14], the results of the present study showed that the growth of *A. flavus* CGMCC 3.2890 was inhibited by the five EOs, which was in accordance with Kumar et al. [9]. However, in the former studies, the concentrations of inhibition were all high, rarely studying the inhibition capability of low concentrations. Our research proved that low concentration also has inhibition ability against *A. flavus.* Our results showed that the cinnamaldehyde and citral suppressed the growth of *A. flavus* at low concentrations. Sun et al. [15] also reported that the germination of *A. flavus* was delayed by cinnamaldehyde in PDA medium when administered at 79.29 mg/L, whereas our concentration was only 40 μg/mL. The reason why cinnamaldehyde had the best inhibition ability was perhaps related to its special structure, such as aldehyde and phenol, which could attack the cell membrane or cell wall. Nogueira et al. [16] indicated that essential oil of *Ageratum conyzoides* changed the ultra-structure of *A. flavus*, which was more evident in the endomembrane system, such as mitochondria, thus inhibiting the growth of *A. flavus.* Sun et al. [15] reported that the diameter of the spore size linearly decreased with the increase of concentration of essential oils. The probable mechanism of cinnamaldehyde and citral needs further study.

The checkerboard method is a common method by which to evaluate the synergy effect of different drugs. The results showed that cinnamaldehyde and citral could synergistically affect *A. flavus*, which was rarely reported before.

Cinnamaldehyde and citral dose-dependently inhibited AFB1 production in the liquid medium, which was in accordance with our results in the feed. The mechanism of decreased AFB1 production by cinnamaldehyde and citral may be related to the downregulation of the expression of key genes for AFB biosynthesis, such as *aflC*, *nor1* and *norA* [16].

In the feed industry, essential oil is usually used as an odorant to increase feed intake, and acidifier product is often used to inhibit fungus, but the dosage of acidifier in feed is high, which may cause the negative effect on the performance of animals. Consequently, essential oil could be a good replacement for acidifier. Essential oils could not only inhibit

the fungus, but have many other positive effects on animal production. Thymol was proven to increase the polyunsaturated fatty acid in egg yolk [17], perhaps for its antibacterial and antioxidant properties, which was also proven in other studies [18]. Moreover, essential oils could be improved by increasing the oleic acid content [19], and thiobarbituric acid reactive substances (TBARS) values could be lowered and the color parameters could be increased during storage when using essential oils [20]. Now only rosemary extract and oregano essential oils are permitted to be used as feed additives, but in the future, more essential oils would probably be applied as feed additives.

#### **4. Conclusions**

AFB1 do great harm to the health of human and animals. The research showed cinnamaldehyde and citral could be an alternative to control aflatoxin contamination in food and feed in future.

#### **5. Material and Methods**

#### *5.1. Microbial Cultures*

The following microbial strain were selected for their relevance in the feed industry: *A. flavus* CGMCC 3.2890 was obtained from China General Microbiological Culture Collection Center (CGMCC). The fungi strain was subcultured in potato dextrose agar (PDA) at 28 ◦C for five days. A spore suspension (approx. 106 CFU/mL) was prepared with potato dextrose broth (PDB).

#### *5.2. Preparation of Essential Oils*

Thymol (Sinopharm Chemical Reagent Co., Ltd., Beijing, China, ≥99.0%), cinnamaldehyde (Sinopharm Chemical Reagent Co., Ltd., Beijing, China, ≥99.0%), citral (Sinopharm Chemical Reagent Co., Ltd., Beijing, China, ≥97.0%), eugenol (Sinopharm Chemical Reagent Co., Ltd., Beijing, China, ≥98.5%), and carvacrol (J & KCHEMICA, Beijing, China, ≥98.0%) were mixed with potato dextrose broth (PDB) containing ethanol (5%; *v*/*v*) and tween 80 (0.5%; *v*/*v*) at 1000 μg/mL, 200 μg/mL, and 40 μg/mL, respectively. PDB solution was prepared according to the above method (devoid of essential oils) served as the control.

#### *5.3. Screening of Best Effect of Essential Oils on Mold Growth in Broth*

The modified micro-plate assay used in this study has already been described in detail by Gorran et al. [21]. Briefly, EOs at different concentrations (0, 40, 200 and 1000 μg/mL) were screened for inhibiting *A. flavus* growth. In 96-well micro-plates (Costar®, 3599, Corning, NY, USA), 160 μL PDB and 20 μL of different concentrations of EOs were mixed with 20 μL of four different strains of prepared *A. flavus* spores (at the concentration of 106 CFU per well), and shaken overnight at 28 ◦C. The fungal growth was determined by measuring the absorbance at 600 nm of fungal culture in 96-well micro-plates by using a micro-plate reader (model 680, BIO-RAD Laboratories, Inc., Hercules, CA, USA) for 24 h and 48 h [22]. All assays were performed in triplicates. The essential oils of best inhibition effect were chosen for the next trials.

#### *5.4. MIC Tests and Synergy Effects of the Best Effect Essential Oils on Fungal Growth in Broth*

The MICs of two essential oils' best inhibition effects were separately determined by broth microdilution method by using 96 kits. The MICs were tested in replicates of six. The MIC was defined as the lowest concentration of completely inhibiting the growth of *A. flavus*. The inoculums were approximately 1 × 106 CFU/mL in each well.

The synergy effects of the two essentials were determined by using the checkerboard method. The concentration range of each essential oil in combination ranged from 1/4 MIC to 2 MIC. Dilutions of two essential oils were made with a twofold diluter [14]. The initial inoculum was approximately 1 × <sup>10</sup><sup>6</sup> CFU/mL. The fungal growth was determined by measuring the absorbance at 600 nm of fungal culture in 96-well micro-plates by using a micro-plate reader (model 680, BIO-RAD Laboratories, Inc., Hercules, CA, USA) for 24 h.

To evaluate the effects of combinations, the fractional inhibition concentration (FIC) was calculated for each essential oil in each combination [22]. The following formulas were used to calculate the FIC index. The results were expressed as four situations, including synergy (FIC ≤ 0.5), additive (0.5 < FIC ≤ 1), indifference (1 < FIC ≤ 4) or antagonism (FIC > 4). A and B separately stands for the two tested essential oils:

$$\text{FIC} = (\text{MIC}\_{\text{A}+\text{B}}) / (\text{MIC}\_{\text{A}}) + (\text{MIC}\_{\text{A}+\text{B}}) / (\text{MIC}\_{\text{B}}).\tag{1}$$

#### *5.5. Effects of the Best Effect Essential Oil on Fungal Growth and AFB1 Production in Poultry Feed*

Prior to mixing with cinnamaldehyde, broiler feed free of any toxin binder was sterilized at 121 ◦C for 20 min followed and the moisture of the feed was adjusted to 17% (on dry basis) with sterile water. Then the feed was inoculated with each mold separately by using the method described by Yin et al. [23], wherein *A. flavus* CGMCC 3.2890 was added to 200-g portions of feed to obtain 5.5 log CFU/g feed, and mixed well. After inoculation, cinnamaldehyde and citral were added at 0, 40, 80, 160, and 320 mg/kg (CT, CAD40, CAD80, CAD160, CAD320) feed totally followed by incubation at 28 ◦C in 500 mL Erlenmeyer flasks, sealed with rubber closures. A 20-g portion of the feed was sampled on days 0, 7, 14, and 21, of which 10 g was used for mold enumeration and 5 g for AFB1 detection, respectively, to calculate the inhibition rate (IR) of *A. flavus* CGMCC 3.2890 and AFB1. Each treatment was repeated three times.

The inhibition rate (IR) of *A. flavus* CGMCC 3.2890 was calculated according to the following formula:

$$\text{IR (\%)} = (\Delta \text{OD}\_{\text{\%}} - \Delta \text{ODx}) / \Delta \text{OD}\_{\text{\%}} \times 100. \tag{2}$$

IR means the inhibition rate of *A. flavus*, ΔODc means the difference value of the OD of CT treatment of day (7, 14, 21) and day0, ΔODx means the difference value of OD of the treatments (CAD40, CAD80, CAD160, CAD320) on day x (day 7, 14, and 21) and day 0 respectively;

IR of AFB1 was calculated according to the following formula:

$$\text{IR (\%)} = (\Delta \text{AFB}\_{\text{\%}} - \Delta \text{AFBx}) / \Delta \text{AFB}\_{\text{\%}} \times 100. \tag{3}$$

IR means the inhibition rate of AFB1, ΔAFBc means the difference value of the concentration of AFB1 of CT treatment on day x (day 7, 14, 21) and day0, ΔAFBx means the difference value of the concentration of AFB1 of of the treatments (CAD40, CAD80, CAD160, CAD320) on day x (day 7, 14, 21) and day 0, respectively.

#### *5.6. Determination of Mold Counts*

To enumerate *A. flavus* in the control and treated feed, 10 g portions of feed samples were added to 100 mL of PBS in sterile glass flasks, and blended in a shaker for 30 min. The feed homogenate was serially diluted (1:10) in PBS, and 0.1 mL aliquots from appropriate dilutions were surface-plated on duplicate PDA plates, and incubated as previously described.

#### *5.7. Determination of AFB1 in Feed*

The concentrations of AFB1 were determined by using a commercial ELISA Kit (HEM 00496, Huaan Magnech Bio-Tech Co., Ltd., Beijing, China). All the procedures were performed on the basis of manufacturer's instructions and the absorbance was determined by using a micro-plate reader. The AFB1 kit is an indirect competitive enzyme-labeled immunoassay. The AFB1 antigen is pre-coated on the wells. The pre-coated antigen competes with the AFB1 antibody (antibody solution) with AFB1 in the sample, anti-AFB1 antibody binds to the AFB1-HRP enzyme conjugate. The substrate solution was pipetted into the wells to convert the color. The color of unknown samples is compared to the color of the standards and the AFB1 concentrations of the samples were derived.

Samples were prepared by weighing out a 5.0-g comminuted sample into a 100-mL triangular flask with a stopper. A total of 25 mL of 60% methanol solution was added and blended vigorously for 10 min on a vertex. The sample was transferred to a centrifuge tube and centrifuged for 5 min at 4000 r/min. A total of 1.0 mL of the top-layer liquid was transferred to a new tube, and 4.0 mL of deionized water was added and blended for 5 s. A total of 50 μL of the solution was taken for assay.

#### *5.8. Statistical Analysis*

Data from this study was analyzed with one-way ANOVA followed by Tukey's multiple range test; data were expressed as the mean ± SE by Tukey's multiple range test. Data were expressed as significant if *p* was less than 0.05. All statistical analyses were performed by SPSS 25.0 (SPSS Inc., Chicago, IL, USA).

**Author Contributions:** Conceptualization, B.H. and G.-W.F.; methodology, B.H. and G.-W.F.; software, B.H.; validation, B.H., G.-W.F. and J.-Q.W.; formal analysis, B.H.; investigation, B.H.; resources, B.H.; data curation, B.H.; writing—original draft preparation, B.H.; writing—review and editing, B.H.; visualization, B.H.; supervision, B.H.; project administration, B.H. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

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

#### **References**


### *Article* **Whole-Transcriptome Analysis of Non-Coding RNA Alteration in Porcine Alveolar Macrophage Exposed to Aflatoxin B1**

**Huhe Chao 1,2,†, Haohai Ma 1,†, Jiadong Sun 3, Shuai Yuan 4, Peiyu Dong 1, Aihong Zhao 5, Lan Li 3, Wei Shen <sup>3</sup> and Xifeng Zhang 1,\***


**Abstract:** Aflatoxin B1 (AFB1) is a type of mycotoxin produced by the fungi Aspergillus flavus and Aspergillus parasiticus and is commonly found in cereals, oils and foodstuffs. In order to understand the toxic effects of AFB1 exposure on Porcine alveolar macrophages (3D4/2 cell), the 3D4/2 cells were exposed to 40 μg/mL AFB1 for 24 h in vitro, and several methods were used for analysis. Edu and TUNEL analysis showed that the proliferation of 3D4/2 cells was significantly inhibited and the apoptosis of 3D4/2 cells was significantly induced after AFB1 exposure compared with that of the control group. Whole-transcriptome analysis was performed to reveal the non-coding RNA alteration in 3D4/2 cells after AFB1 exposure. It was found that the expression of cell-cycle-related and apoptosis-related genes was altered after AFB1 exposure, and lncRNAs and miRNAs were also significantly different among the experimental groups. In particular, AFB1 exposure affected the expression of lncRNAs associated with cellular senescence signaling pathways, such as MSTRG.24315 and MSTRG.80767, as well as related genes, Cxcl8 and Gadd45g. In addition, AFB1 exposure affected the expression of miRNAs associated with immune-related genes, such as miR-181a, miR-331-3p and miR-342, as well as immune-related genes Nfkb1 and Rras2. Moreover, the regulation networks between mRNA-miRNAs and mRNA-lncRNAs were confirmed by the results of RT-qPCR and immunofluorescence. In conclusion, our results here demonstrate that AFB1 exposure impaired proliferation of 3D4/2 cells via the non-coding RNA-mediated pathway.

**Keywords:** aflatoxin B1; porcine; porcine alveolar macrophages; apoptosis; cell cycle

**Key Contribution:** AFB1 exposure impaired proliferation of 3D4/2 cells via non-coding RNAmediated pathway.

### **1. Introduction**

Mycotoxin is the toxic metabolite of mold, which is limited to some strains of a few toxigenic molds. Different molds can produce the same mycotoxin, while one strain can produce several mycotoxins [1]. At present, about 200 kinds of mycotoxins have been found, and a few of them can cause poisoning in animals and humans under natural conditions [2]. The most important mycotoxins are aflatoxin B1, ochratoxin A, zearalenone, fumin and deoxynivalenol. Mycotoxins can pollute all types of food and feed and can threaten human and animal health through food chain accumulation, producing hepatotoxicity,

**Citation:** Chao, H.; Ma, H.; Sun, J.; Yuan, S.; Dong, P.; Zhao, A.; Li, L.; Shen, W.; Zhang, X. Whole-Transcriptome Analysis of Non-Coding RNA Alteration in Porcine Alveolar Macrophage Exposed to Aflatoxin B1. *Toxins* **2022**, *14*, 373. https://doi.org/10.3390/ toxins14060373

Received: 26 April 2022 Accepted: 25 May 2022 Published: 27 May 2022

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**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/).

nephrotoxicity, neurotoxicity, hematopoietic tissue toxicity, etc. [3–5]. Some mycotoxins are mutagenic and carcinogenic [6,7].

Aflatoxin B1 is the most toxic mycotoxin; it was listed as a Group 1 carcinogen by the International Agency for Research on Cancer (IARC) in 1996 [8]. AFB1 mainly targets the liver of humans and animals, where it is metabolized by cytochrome 450 into carcinogenic AFB1-8,9-exo-epoxide (AFBO). AFBO combines with phase II enzymes such as glutathione-S-transferase (GST) to form afb1-thiol acid (AFB1-NAC), which is excreted with urine. AFBO can also combine with DNA to form AFB1-N7-Gua, causing DNA mutation [9,10]. AFB1 reduces steroid production by competitively binding StAR protein of rats, affects the secretion of estradiol-17β and progesterone in animal serum, inhibits the growth of oocytes and leads to the decrease of ovarian size and weight [11,12]. In male mice, AFB1 exposure is related to histological changes of testis, reduction of sperm number and differences in sperm motility and litter size [13,14]. In primary broiler hepatocytes, AFB1 results in an increase in mitochondrial ROS production, a decrease in mitochondrial membrane potential and an induction of apoptosis. This is related to the upregulation of *Nrf2* gene expression and downregulation of NAD(P)H: quinine oxidoreductase 1, SOD and HO-1 [15]. AFB1, as a potential endocrine disruptor, can affect the expression of aromatase enzymes (P450s or CYPs enzymes) [16].

Epigenetic modification includes DNA methylation, ncRNA (miRNA, lncRNA and circular RNA) and post-translational modification (PTM) (glycosylation, methylation, acetylation, phosphorylation and ubiquitination) [17,18]. ncRNA participates in various biological processes, and abnormal expression of ncRNA always destroys the balance in vivo and leads to diseases [19,20]. At present, most studies involving ncRNAs focus on miRNA, circRNA and lncRNA. LncRNA is involved in X chromosome silencing, genome imprinting, chromatin modification, transcription activation, transcription interference, nuclear transport and other important regulatory processes, such as apoptosis. LncRNA is often used to study toxicological mechanisms [21,22].

This study was designed to determine the mechanism of lncRNA and microRNA targeting regulatory genes in Porcine alveolar macrophage cells in response to the toxic effects of AFB1. We generated differential expression profiles of lncRNA and miRNA in Porcine alveolar macrophage cells with and without AFB1 exposure. The findings of this research provide the molecular mechanisms involved in the development of AFB1 induced hepatotoxicity and enrich the valuable resources for lncRNA and miRNA in toxicological research.

#### **2. Results**

#### *2.1. AFB1 Inhibited Cell Proliferation and Induced Cell Apoptosis*

EdU assay is a commonly used method for detecting cell proliferation. In order to deeply understand the molecular mechanism of porcine 3D4/2 cell cytotoxicity induced by AFB1 exposure, porcine 3D4/2 cells were treated with 40 μm AFB1 in vitro for 24 h. The whole experimental design is shown in Figure 1A. Compared with the untreated group, cells treated with 40 μm AFB1 had significant morphological differences (Figure 1B). The proliferation ability of porcine 3D4/2 cells was checked with an EdU kit, and the results showed that the number of EdU-positive cells in the AFB1 treatment groups decreased significantly compared with the control group (Figure 1C). After AFB1 treatment, the number of TUNEL-positive cells was significantly increased (23.5%) compared with the control group (2.2%) (Figure 1D).

**Figure 1.** Sequence and data preprocessing of porcine 3D4/2 cell. (**A**) The Schematic diagram of sample treatment and RNA sequencing procedure. (**B**) The morphological changes of porcine 3D4/2 cells exposed to AFB1 for 12 and 24 h in vitro. Scale bar, 100 mm. (**C**) Representative immunofluorescent images of EdU positive cells (red) and the cell nuclei (blue) in the control and AFB1-exposed cells after 24 h (**left**), and the percentages of EdU positive cells (**right**). \*\* *p* < 0.01. (**D**) Percentages of TUNEL-positive cells treated for 24 h in different groups (**left**) and number of TUNEL-positive cells of the total cells (%, (**right**)). \*\* *p* < 0.01. All experiments were repeated 3 times.

#### *2.2. AFB1 Exposure Affected lncRNA and mRNA Expression of Porcine 3D4/2 Cells*

Ribonucleic acid sequencing (RNA-seq) was utilized to explore the effect of AFB1 on the expression of lncRNAs and mRNAs in porcine 3D4/2 cells. Figure 2A shows the number of lncRNA and mRNA transcripts in the control and AFB1-treated groups. Based on the principal component analysis (PCA), the various lncRNA and mRNA datasets with the same treated methods were highly similar, respectively (Figure 2B). According to the volcano plots of differentially expressed genes (DEmRNAs) and lncRNAs (DElncRNAs) of porcine 3D4/2 cells (Figure 2C), there were 4589 and 1308 downregulated mRNA and lncRNA in the control versus the AFB1-treated group, respectively, and the upregulated mRNAs and lncRNAs were 7069 and 2195, respectively (Figure 2D). The distribution and expression of each lncRNA and mRNA on each chromosome are displayed by the chord diagram (Figure 2E). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed based on DEmRNAs. The enriched GO terms included cell adhesion, biological adhesion, vesicle mediated transport, response to endogenous stimulus, negative regulation of signal transduction, and others (Figure 2F). KEGG analysis was used to examine pathway enrichment (Figure 2G). The top 15 enriched KEGG pathways involved the MAPK signaling pathway, P13K-Akt signaling pathway, Hippo signaling pathway, Camp signaling pathway, mTOR signaling pathway, TNF signaling pathway and Focal adhesion (Figure 2G).

**Figure 2.** Divergent expression patterns of lncRNA and mRNA of porcine 3D4/2 cells. (**A**) The number of lncRNA and mRNA transcripts in control and AFB1-treated groups. (**B**) Principal component analysis (PCA) based on lncRNA and mRNA. (**C**) The volcano plots of differentially expressed genes (DEGs) and lncRNAs (DELs) of porcine 3D4/2 cells. (**D**) The number of upregulated and downregulated DEGs and DELs of control vs. AFB1-treated group. (**E**) The chord diagram showing the distribution and expression of differentially expressed lncRNAs and mRNAs in the chromosome. (**F**) GO and (**G**) KEGG enrichment of DEGs.

#### *2.3. Co-Expression Analysis of DELs and DEGs in Porcine 3D4/2 Cells*

To accurately identify the regulatory mechanisms of lncRNAs and mRNAs, we performed co-expression analysis based on Differentially expressed genes (DEGs) and Differentially expressed lncRNAs(DELs). After filtering according to *p*-value (*p* < 0.01) and Pearson correlation coefficient, 3479 mRNAs and 248 lncRNAs were obtained (Figure 3A,B). The heatmap was plotted according to the expression of mRNA and lncRNA (Figure 3C), which were all related to component organization biogenesis, process regulation metabolic, cycle mitotic cell and localization transport establishment (Figure 3D). KEGG pathway analysis was performed to elucidate the function of co-expressed genes (Figure 3E). We obtained similar enrichment results as above, including cellular senescence, cell cycle, mitogen-activated protein kinase (MAPK) signaling pathway, Tumor necrosis factor (TNF)

signaling pathway, p53 signaling pathway and phosphatidylinositol 3 kinase-protein kinase B (PI3K-Akt) signaling pathway, which were all related to apoptosis, indicating that AFB1 exposure affected mRNA and lncRNA expression of 3D4/2 cells and led to cell apoptosis (Figure 3E). For trend analysis of RNA data sets, we also performed GSEA analysis. The results showed that the gene expression related to the focal adhesion pathway was upregulated (Figure 3F). The heatmap shows the gene expression in cellular senescence signaling pathway (Figure 3G).

**Figure 3.** Co-expression analysis of DELs and DEGs in porcine 3D4/2 cells. (**A**) Identification of pairwise lncRNA-mRNA in co-expression analysis; the histogram showing the number of mRNA and lncRNA with *p*-value < 0.01 and |r-value| > 0.99. (**B**) The Venn diagram showing the number of mRNA and lncRNA with *p*-value < 0.01 and |r-value| > 0.99. (**C**) The heatmap showing the expression of mRNA and lncRNA. (**D**) Functional enrichment analysis of co-expressed genes. (**E**) KEGG enrichment results of co-expressed genes. (**F**) GSEA enrichment results of co-expressed genes. (**G**) The heatmap showing gene expression in the cellular senescence signaling pathway.

#### *2.4. Cis-Regulation of mRNA and lncRNAs with Target Genes*

Based on the Venn plots of unique lncRNAs or mRNA in cis-regulation with coexpressed lncRNAs or mRNA, 196 key lncRNAs and 1704 key mRNAs were found (Figure 4A). Subtype statistics of key cis-regulatory mRNA were assayed. According to the illustration, "Genic" includes the subtypes of "overlapping", "containing", and "nested"; "Intergenic" consists of "same strand", "convergent", and "divergent" subtypes (Figure 4B). Genome location statistics showed that the key cis-regulatory mRNAs were located upstream (8.99%), intronic (50.83%), exonic (34.59%) and downstream (5.59%), respectively (Figure 4C). To understand the function of DElncRNAs target genes, we explored the function of these target genes using KEGG analysis (Figure 4D). KEGG analysis showed that there are 15 significantly enriched signal pathways with DElncRNAs, including cellular senescence, cell cycle, MAPK signaling pathway, IL-17 signaling pathway, TNF signaling pathway, autophagy, etc. (Figure 4D). Next, based on co-expression and co-localization analysis, we found that DElncRNAs regulated key genes in cellular senescence signaling pathways, and we display them through chord diagrams (Figure 4E). The relative expression of these genes was determined by Immunofluorescence Staining (Figure 5). Compared to the control group, the expression levels of CXCL8 and GADD45G were significantly upregulated (Figure 5), which was consistent with the whole transcriptome sequence results.

**Figure 4.** Cis-regulation of lncRNAs with target genes. (**A**) The Venn plot of unique lncRNAs or mRNAs in cis-regulation with co-expressed lncRNAs or mRNA. (**B**) Subtype statistics of key cisregulatory mRNA. According to the illustration, "Genic" includes the subtypes of "overlapping", "containing", and "nested"; "Intergenic" consists of "same strand", "convergent", and "divergent" subtypes. (**C**) Genome location statistics of key cis-regulatory mRNA. (**D**) KEGG enrichment analysis of target genes regulated by lncRNA homeopathy. (**E**) The chord graph showing the targeting relationship between key genes in the cellular senescence signaling pathway and lncRNA.

**Figure 5.** Cell immunofluorescence assay of the expression of CXCL8 and GADD45G proteins. (**A**) The fluorescence intensity and positive percentages of CXCL8. Nuclear staining (blue) and CXCL8 positive cells (green). (**B**) The fluorescence intensity and positive percentages of GADD45G. Nuclear staining (blue) and GADD45G-positive cells (red). \*\* Indicates extremely significant differences (*p* < 0.01). All experiments were repeated 3 times.

#### *2.5. AFB1 Exposure Altered miRNA Expression*

To investigate the impact of AFB1 on miRNA in porcine 3D4/2 cells, we performed differential expression analysis of miRNA between three control groups and three AFB1 treated groups (Figure 6A). The volcano plot was used to show the distribution of differentially expressed miRNAs (Figure 6B). Compared with the control group, a total of 5 DEmiRNAs were upregulated and 6 DEmiRNAs were downregulated in the AFB1 treated group. The change of DEmiRNA expression in the different groups is shown in the heatmap (Figure 6C). Moreover, TargetScan, miRanda and RNAhybrid software (http://www.targetscan.org/, http://www.microrna.org/microrna/home.do, and http: //bibiserv.techfak.uni-bielefeld.de/rnahybrid/, accessed on 25 April 2022) was used for predicting the DEmiRNA-related genes (Figure 6D,E), and finally 205 genes were predicted (Figure 6E). The genes were found to be enriched in GO terms associated with the negative regulation of biological processes, execution phase of apoptosis, system development, translation, regulation of cell communication, regulation of growth and regulation of cellular response to growth factor stimulus (Figure 6F). The KEGG analysis showed that the target genes were enriched in the Ras signaling pathway, MAPK cell signaling pathway, Rap1 signaling pathway, P13k-Akt signaling pathway, cAMP signaling pathway, calcium signaling pathway, etc. (Figure 6G). We show the targeting relationship between key genes and miRNAs in the Ras signaling pathway (Figure 6H).

**Figure 6.** AFB1 exposure alters the miRNA expression levels of porcine 3D4/2 cells. (**A**) The cluster dendrogram between AFB1-treated groups and the control groups based on miRNA. (**B**) The volcano diagram showing the distribution of DEmiRNAs between the AFB1-treated group and the control group. (**C**) The heatmap demonstrating the expression level of DEmiRNAs in six samples. (**D**) The histogram showing the number of miRNAs and the number of target genes. (**E**) The Venn diagram showing the number of target genes shared by DEmiRNAs in TargetScan, miRanda and RNAhybrid. (**F**) GO enrichment analysis of DEmiRNA target genes. (**G**) KEGG enrichment analysis of DEmiRNA target genes. (**H**) The circos diagram indicating the targeting relationship of the miRNA-mRNA network in porcine 3D4/2 cells.

We selected genes shared among the DEmRNA and DEmiRNA target genes (Figure S2A). We use the heatmap to show the expression of key genes in different groups (Figure S2B). Subsequently, we performed KEGG enrichment analysis on the 74 target genes (Figure S2C).

The results indicated that the Ras signaling pathway was mainly regulated by miRNAs. Using genetic interactions and co-expression networks, we found that NFKB1 and RRAS2 play key roles in the Ras signaling pathway (Figure S2D). The targeting relationships between miRNAs and key genes are shown in Figure S2E. The relative expression of DEmiRNAs was determined by RT-qPCR. Compared with the control group, the expression levels of miR-181a, miR-331-3p and miR-342 in the AFB1 treatment group were significantly upregulated (Figure 7A). To verify the expression of the previous related genes *Nfkb1* and *Rras2* after AFB1 exposure, we further analyzed their expression using immunofluorescence. The fluorescent intensity of NFKB1 and RRAS2 genes was significantly decreased in the AFB1-treated group compared with that of the control group (Figure 7B,C). These results were consistent with the data of the whole-transcriptome sequence.

**Figure 7.** Validation of miRNA-seq data availability with RT-qPCR and examination of the expression of NFKB1 and RRAS2 proteins with cell immunofluorescence assay. (**A**) Expression of miR-181a, miR-331-3p and miR-342 in 3D4/2 cells after 24 h AFB1 exposure. \* Indicates extremely significant differences (*p* < 0.05), \*\* Indicates extremely significant differences (*p* < 0.01). All experiments were repeated 3 times. (**B**) The fluorescence intensity and positive percentages of NFKB1. Nuclear staining (blue) and NFKB1 positive cells (green). (**C**) The fluorescence intensity and positive percentages of RRAS2. Nuclear staining (blue) and NFKB1 positive cells (red). \*\* Indicates extremely significant differences (*p* < 0.01). All experiments were repeated 3 times.

#### **3. Discussion**

Aflatoxin can induce mutation, inhibit immunity and cause cancer. The liver tissue is the main target organ of aflatoxin, which can lead to liver cancer and even death in severe cases [23,24]. Acute poisoning of animals can lead to serious damage to blood vessels and the central nervous system, and animals may die within several hours to several days after poisoning. Chronic poisoning is characterized by poor appetite, weight loss, decreased production performance, decreased carcass and eggshell quality, liver injury, inhibition of animal immune function and carcinogenesis. Aflatoxin has immunosuppressive properties [25]. Intake of contaminated feed will increase the susceptibility to infection and reduce the immunity of vaccines. AFB1 mainly affects cellular immunity. It can reduce the total number of lymphocytes, especially the total number of circulating activated lymphocytes, inhibit the production of lymphocytes and damage the delayed hypersensitivity and graft-versus-host reaction of skin [26]. AFB1 can also reduce the lysis of natural killer cells and the function of macrophages, such as thiophene swallowing activity, intracellular killing or production of oxidative free radicals [27]. In vitro analysis of mouse peritoneal macrophages exposed to AFB1 showed that the expression of IL-lα and IL-6 or TNF-α increased [28]. Blood lymphocytes of pigs fed with food containing AFB1 feed contaminant were catalyzed by mitogens, and the expression of IL-lP decreased while the expression of IL-10 increased [29]. In addition, studies have shown that AFB1 affects swine growth performance, apparent total tract digestibility and intestinal health, seriously impairing the development of the swine industry [30].

LncRNA plays an important role in many life activities, such as dose compensation effect, epigenetic regulation, cell cycle regulation and cell differentiation regulation [31]. Similarly, microRNA (miRNA) plays a variety of important regulatory roles in cells. Like transcription factors, miRNA regulates gene expression and plays a great role in cell differentiation, biological development and disease occurrence and development, which has attracted more and more attention from researchers [32]. RNA-seq data analysis of mRNA, microRNA and lncRNA provides new clues for gene expression profile and transcriptional regulation in animal cells in response to mycotoxin exposure, and helps to detect biomarkers and drug targets for predicting and controlling mycotoxin contamination [33]. The expressions of lncRNA and miRNA are analyzed by lncRNA microarray, which proves that Zearalenone (Zea) and imprinted lncRNAs are closely related to reproduction and development [34]. Zhang et al. showed that Zearalenone (ZEA) can activate the JAK2– STAT3 signaling pathway through the two lncRNAs MSTRG.22680 and MSTRG.23882 to induce cell apoptosis [35]. ZEN causes toxicological effects by regulating the expression of miRNA and miRNA target genes [36]. Some reports have focused on the role of ncR-NAs (miRNA and lncRNA) in AFB1-induced toxicity, especially the relationship between AFB1 and HCC [37]. ADAMTS4, the targeted mir-1268a gene, is affected by pre miRNA polymorphism to reveal the risk of AFB1 related hepatocellular carcinoma(HCC) [38]. In the toxicological study of AFB1, it was also found that AFB1 can affect the expression of miRNAs and lncRNA in the liver, result in liver fat deposition and hepatocyte apoptosis, and induce hepatotoxicity [21]. Our results revealed that AFB1 exposure affected the expression of miRNAs such as ssc-miR-181a, ssc-miR-331-3p and ssc-miR-342 and affected the expression of lncRNAs such as MSTRG.24315 and MSTRG.80767.

AFB1 can affect the expression of many genes. Chemokines are small proteins that control a variety of tissue functions, including cell recruitment and activation under homeostatic and inflammatory conditions. CXCL8 (Interleukin-8) is a member of the chemokine family and acts on CXCR1 and CXCR2 receptors. CXCL8 and its receptors help eliminate pathogens but may also contribute significantly to disease-related processes, including tissue damage, fibrosis, angiogenesis and tumorigenesis [39]. IL-8 is related to a variety of inflammation and chemotaxis and participates in the occurrence of many diseases. The main biological function of IL-8 is to contribute to the chemotaxis of neutrophils, T lymphocytes and basophil (Basophils) during inflammation, and its chemotaxis are different in different cells [40]. GADD45G protein is a stress protein that responds to the environment. As a stress-sensitive factor, it plays an important role in response to toxic and non-toxic stress responses. It also plays an important regulatory role in many cell functions such as DNA repair, cell cycle regulation and senescence, toxic stress response of genes, inducing cell cycle arrest and apoptosis [41,42]. After AFB1 treatment, as one of the major mediators of the inflammatory response, CXCL8 was upregulated with the highest fold change [43]. In addition, AFB1 exposure induced the expression of Cxcl8 and Gadd45g genes in 3D4/2 cells (Figure 5) in our study, leading to cell inflammation, DNA repair, cell cycle arrest and apoptosis, which is consistent with the results of Figures 2F and 3E. Similarly, the mRNA level of Il6 in the liver of broilers exposed to AFB1 was significantly higher than that of the control group [44].

The *Nfkb1* gene is considered to be anti-apoptotic. In liver cells, increased expression of Nfkb1 has been shown to upregulate other inflammatory genes, such as Tnfa and Il6 [45,46]. However, improper activation of NF-κB is associated with a variety of inflammatory diseases, while persistent inhibition of NF-κB leads to improper development of immune cells or delayed cell growth [47]. AFB1 exposure affected the development of macrophages by inhibiting NF-κB (Figure 7). RRAS2 is necessary for the proliferation of human CLL cells. Rras2 encodes a protein that binds to the plasma membrane and plays an important role in activating the signal transduction pathway that controls cell proliferation. RRAS2 is associated with the BCR in leukemic cells and is required for human CLL cell proliferation [48]. The treatment of AFB1 decreased the expression of RRAS2, thus inhibiting the proliferation of cells (Figures 1C and 7). It is worth noting that studies have shown that curcumin successfully alleviated AFB1-induced oxidative stress, inflammation and apoptosis in broiler liver by regulating the expression of lncRNA [49]. This suggests that our study may provide a therapeutic target for the swine industry to control AFB1 toxicity.

#### **4. Materials and Methods**

#### *4.1. In Vitro AFB1 Treatment of Porcine Alveolar Macrophages*

AFB1 (AFB1, A832707, Macklin, Shanghai, China) was dissolved in Dimethyl sulfoxide (DMSO) and stored at −20 ◦C until use. Porcine alveolar macrophages (3D4/2, ATCC: CRL-2845) were cultured in 96-well plates or 6 cm culture dishes (Corning, 430166, New York, NY, USA) for AFB1 treatment at the concentration of 40 μg/mL.

#### *4.2. EdU Staining for Proliferation*

An EdU Assay/EdU Staining Proliferation Kit (Beyotime, C00755, Shanghai, China) was used to detect and quantify cell proliferation in porcine alveolar macrophage cells using flow cytometry. Proliferating cells were stained for incorporated EdU against total DNA content using Hoechst.

#### *4.3. TUNEL Staining*

Cells were collected after 24 h of AFB1 treatment and then fixated by 4% Paraformaldehyde. The One Step TUNEL Apoptosis Assay Kit (Beyotime, C1086, Shanghai, China) was used to examine apoptosis cells according to the instructions. After sealing with anti-fluorescence quenching sealing solution, cells were observed under a fluorescence microscope (Olympus, BX51, Tokyo, Japan). TUNEL-positive cell rates were counted and analyzed using IPWIN software (Meedia Cybernetics, Rockville, MD, USA).

#### *4.4. RNA Extraction and Sequencing of Whole Transcriptome RNA*

The total RNA from cells was extracted using RNAprep Microkit pure (Aidlab, RN07, Shanghai, China) according to the manufacturer's instructions. The Illumina TruSeq™ RNA preparation kit (Illumina, San Diego, CA, USA) was used to prepare samples, and the Novogene (Beijing, China) HiSeq 4000 platform was used for sequences.

#### *4.5. Pipeline of Data Processing*

FastQC software (http://www.bioinformatics.bbsrc.ac.uk/projects/fastqc/, accessed on 25 April 2022) and Fastp software (https://github.com/OpenGene/fastp/, accessed on 25 April 2022) were used to analyze the quality control of sequencing data and eliminate the low-quality reads from the raw data. The clean reads of samples were mapped using STAR software for mRNA. SAMtools was also used to remove reads not mapping in a proper mate-pair, and the featureCounts software was used to assign sequence reads to genomic features (Figure S1A).

#### *4.6. Screening for Candidate lncRNAs*

Preliminary filtering was done based on "class\_code" type. We then used Coding Potential Calculator (CPC) [50], Coding–Non-coding Index (CNCI) [51] and PfamScan software (http://xfam.org/, accessed on 25 April 2022) to identify lncRNAs [52] (Figure S1B).

#### *4.7. Discovering Differentially Expressed Genes (DEGs) and RNA Target Prediction*

Differentially expressed lncRNAs (DElncRNAs) and miRNAs (DEmiRNAs) were assessed using the R Bioconductor/DESeq2 package (https://support.bioconductor.org/, accessed on 25 April 2022). The targeting relationship of DElncRNAs and DEmRNAs (Differentially expressed mRNA) was predicted using the R package Hmisc (https://github. com/harrelfe/Hmisc, accessed on 25 April 2022). We then used FEELnc (v 0.1.1) (https: //github.com/tderrien/FEELnc, accessed on 25 April 2022) to find mRNAs cis-regulated by lncRNAs [53]. The target genes of the miRNAs were predicted using TargetScan, miRanda and RNAhybrid [54,55].

#### *4.8. GO Classification and KEGG Enrichment Analysis*

Gene Ontology (GO) enrichment analysis was performed using the "org.Ss.eg.db" database (http://bioconductor.org/packages/release/data/annotation/html/org.Ss.eg.db.html, accessed on 25 April 2022) to convert the gene SYMOL to ENTREZID. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways was analyzed using the R Bioconductor/Pathview package (http://bioconductor.org/developers/how-to/buildingPackagesForBioc/, accessed on 25 April 2022).

#### *4.9. RT-qPCR*

The whole transcriptome RNA from cells was extracted with the EASYspin Plus cellular RNA rapid extraction kit (Aidlab, RN2802, Beijing, China), and reverse transcription was conducted using the MiRcute Plus miRNA First-Strand cDNA Kit (Tiangen, KR211-01, Beijing, China). The MiRcute Plus miRNA qPCR Kit (SYBR Green) (Tiangen, FP411-01, Beijing, China) was employed (primers are shown in Table S1). Relative quantitative PCR data analysis was performed using the difference multiple = 2−ΔΔct method.

#### *4.10. Immunofluorescence Staining*

Cells were treated with AFB1 for 24 h in order to perform immunofluorescence staining. The following primary antibodies were used: CXCL8 (IL8, DF6998, Affinity Biosciences, Cincinnati, OH, USA), GADD45G (GADD45G, DF2376, Affinity Biosciences, Cincinnati, OH, USA) and NFKB1 (NFKB1, BF0466, Affinity Biosciences, Cincinnati, OH, USA), RRAS2 (RRAS2, DF9840, Affinity Biosciences, Cincinnati, OH, USA). Goat anti-Rabbit IgG (H + I) (Beyotime, A0521, Nantong, China) was used as the second antibody. The methods of immunofluorescence staining followed the published methods [56].

#### *4.11. Statistical Method*

The differences between mean values were statistically tested using Student's t test or one-way ANOVA followed by the Tukey test for multiple comparisons. Comparisons were considered significant at *p* < 0.05 (\*) and *p* < 0.01 (\*\*).

**Supplementary Materials:** The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/toxins14060373/s1, Figure S1: Data preprocessing and Candidate lncRNA identification; Figure S2: Target genes of DEmRNAs, DEmiRNAs, and miRNA-mRNA network.; Table S1: The sequences of primers.

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

**Funding:** This work was supported by High level talents research fund project of Qingdao Agricultural University in China (1120043) to Zhang XF, Science & Technology Fund Planning Projects of Qingdao City (21-1-4-ny-7-nsh), the Natural Science Foundation of Shandong Province of China (ZR2021MC191), the Taishan Scholar Construction Foundation of Shandong province of China (ts20190946), Gene expression analysis of hormone receptor-negative breast cancer with low HER-2 expression and its potential influence on neoadjuvant chemotherapy (212102310658), the Cultivating Fund of Capital Medical University (Grant No. PYZ2017002).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

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

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