LC/MS analysis of mushrooms provided new insights into dietary management of diabetes mellitus in rats

Abstract Mushrooms possess antihyperglycemic effect on diabetic individuals due to their nonfibrous and fibrous bioactive compounds. This study aimed to reveal the effect of different types of mushrooms on plasma glucose level and gut microbiota composition in diabetic individuals. The effects of five different mushroom species (Ganoderma lucidum, GLM; Pleurotus ostreatus, POM; Pleurotus citrinopileatus, PCM; Lentinus edodes, LEM; or Hypsizigus marmoreus, HMM) on alloxan‐induced diabetic rats were investigated in this study. The results indicated that LEM and HMM treatments showed lower plasma glucose levels. For the microbiota composition, ACE, Chao1, Shannon, and Simpson were significantly affected by PCM and LEM treatments (p < .05), while ACE, Shannon, and Simpson indexes were affected by HMM treatment (p < .01). Simpson index was affected in positive control (C+) and POM groups. All these four indices were lower in GLM treatment (p < .05). Dietary supplementation of mushrooms reduced plasma glucose level directly through mushrooms' bioactive compounds (agmatine, sphingosine, pyridoxine, linolenic, and alanine) and indirectly through stachyose (oligosaccharide) and gut microbiota modulation. In conclusion, LEM and HMM can be used as food additives to improve plasma glucose level and gut microbiome composition in diabetic individuals.


| INTRODUC TI ON
Mushrooms possess a necessary dietary ingredient due to their lowcalorie value, different bioactive compounds, and rich fiber content.
These compounds include vitamins (such as riboflavin and niacin), minerals (such as iron and phosphorus) (Alkin et al., 2021), and fibers . Moreover, mushrooms differ in their content of phenols (Alkin et al., 2021) and antioxidants (ergothioneine and glutathione) (Beelman et al., 2019). Thus, each mushroom type possesses different content of bioactive compounds, fiber contents, or both (Alkin et al., 2021). Gut microbiota degrades the dietary fibers as a nondigestible carbon sources and change the microbiota composition (Tang et al., 2017). Unfavorable modulations of gut microbiota are associated with multiple chronic diseases including diabetes mellitus (Tang et al., 2017). In particular, mushrooms possess enriched fibers, such as polysaccharides and heteroglucans (Li et al., 2021), these decrease a pathogen proliferation by inducing the growth of probiotic bacteria in gut (Kumari, 2020). For instance, the species of Ganoderm lucidum is a medicinal mushroom which contains various bioactive compounds that operates as antimicrobial agents (Cor et al., 2018). Fruiting bodies and mycelia of G. lucidum contain polysaccharides, such as glycoproteins, (1 → 3), (1 → 6)-a/β-glucans, and water-soluble heteropolysaccharides (Martin & Jiang, 2010).
Those polysaccharides have antihypoglycemic effect (Chassaing et al., 2017;Xu et al., 2017). G. lucidum increases anti-inflammatory bacteria (Enterococcus and Dehalobacterium) in mice diabetic individuals Chen, Xiao, et al., 2020) and decreases the abundance of harmful bacteria, such as Aerococcus, Corynebactrium, Ruminococcus, and Proteus in type-2 mice diabetic groups Chen, Xiao, et al., 2020). G. lucidum treatment on type-2 diabetes, enhanced SCFA-producing bacterial activity (Chen, Xiao, et al., 2020). In fact, oral administration of extracted polysaccharides from mushrooms (Pleurotus eryngii and Poria cocos) promote SCFA-producing bacterial growth (Li et al., 2021), this improve energy metabolism through affecting the intestinal gluconeogenesis (IGN) and insulin sensitivity simulation (De Vadder et al., 2014). Since IGN releases glucose molecules which can be detected by the glucose sensor in the portal vein. Such signal is transmitted to the brain by the peripheral nervous system regulating glucose metabolism (Delaere et al., 2013). Polysaccharides inhibit digestive enzymes' activity based on the interaction with different sites at enzymes' structure. In addition, polysaccharide's viscoelasticity effect interferences with the enzymes and substrates flow resulting in lipid-lowering effect .
Most mushroom-related studies have investigated the effect of mushroom fibrous bioactive compounds on individual diabetics. While few studies have investigated the non-fibrous bioactive compounds on diabetic individuals (Cor et al., 2018;Lu et al., 2020). Dubey et al. (2019) indicated that few bioactive compounds of edible mushrooms are identified. In a pilot study, mushroom untargeted molecules' composition was investigated, and analyzed; this revealed the existence of some of bioactive compounds in the tested mushrooms. The literature showed that agmatine has an antihyperglycemic effect through increasing glucose uptake in muscles by simulating insulin secretion (Chang et al., 2010;Malaisse et al., 1989;Naoki & Fujiwara, 2019;Nissim et al., 2006Nissim et al., , 2014Shepherd et al., 2012;Su et al., 2008Su et al., , 2009. Whereas stachyose decreases the blood glucose level in alloxan-induced diabetic rats (Zhang et al., 2004), in addition to its regulation effect on the intestinal microflora balance (Liu, Jia, et al., 2018;Liu, Wang, et al., 2018).
Sphingosine (PHS) activates omega-3 fatty acid receptor (GPR120) resulting in an insulin-sensitizing effect (Rudd et al., 2020). Finally, pyridoxine decreases insulin resistance via scavenging the pathogenic reactive carbonyl species (Haus & Thyfault, 2018). There are epidemiological evidences supporting the non-fibrous bioactive compounds safety use, eight mushrooms have been investigated for their effect on DM, that G. lucidum has showed the highest content of phenolic and flavonoids compounds (Wu & Xu, 2015). But this study did not analyze the other bioactive molecules. Generally, the non-fibrous compounds are naturally existed in human foods, for example, agmatine in fermented foods (Galgano et al., 2012), stachyose (oligosaccharides) as a probiotic in human foods (Yang et al., 2018), sphingosine in dairy products (Possemiers et al., 2005), and pyridoxine is a vitamin B6 (Shaik Mohamed, 2001). This revealed a possible therapeutic potency of mushrooms on diabetic individuals.
Mushrooms are basic food components in Chinese table. Thus, revealing their nutritional value and their therapeutic potency are expected to increase the social awareness about dietary mushroom in addition to their therapeutic effect leading to the improving of public health.
To reveal the effect of those bioactive compounds in mushrooms on a diabetic individual, alloxan injection was used to induce the diabetes type II in rats by damaging pancreatic cells and initiating hyperglycemia (Inalegwu et al., 2021). These animals were subjected to different dietary mushrooms to reveal the effect of bioactive compounds sourced from mushrooms on blood glucose level and intestinal microbial composition as basic indicators for the possible effect.
We hypothesized that dietary mushrooms inclusion may decrease plasma glucose level and modulate microbiota composition directly via their bioactive molecules, and indirectly via fiber content and microflora modulation. This study aimed to reveal the effect of non-fibrous bioactive compounds sourced from mushrooms on blood glucose level and intestinal microbial composition in diabetic rat individuals. These molecules may develop a food additive with an effective and specific health functionality considering food processing conditions and their effect on food quality. Diabetes mellitus is a metabolic disease characterized by hyperglycemia, occurring due to abnormal insulin action or insulin secretion. Alloxan induces diabetes type II by damaging pancreatic cells and initiating hyperglycemia (Inalegwu et al., 2021). Experimental animals Albino male rats (Rattus norvegicus) weighed 160-180 g with age 30 days were obtained from the animal's research center, Jilin Agricultural University, Changchun, China. Alloxan-induced diabetic rats (AIDRs) were used as the diabetic model after acclimation period of 30 days. AIDRs were induced by intraperitoneal injection of Alloxan (150 mg/kg of body weight; Shanghai Sinyu Biotechnology Company) after an overnight fast. Three days after Alloxan injection, rats with a plasma glucose concentration of 11 mmol/L or above and symptoms of polyuria, polyphagia, and polydipsia were considered to have diabetes. The animals were distributed among treatments, seven animals per treatment (Table 1). All experimental animals were weighed weekly using a digital balance (Yeng Heng Electronic Scale Company) within the experimental period (4 weeks).

| Determination of plasma glucose
Animals were deprived of food and water overnight and a blood glucose meter and test strips (Hangzhou Econ Biotech Company) were used to measure the blood glucose levels.

| Experimental diets and mushrooms' bioactive compounds
The effect of five types of mushrooms (GLM) Ganoderma lucidum mushroom (traditional Chinese medicinal mushroom), (POM) Pleurotus ostreatus mushroom, (PCM) Pleurotus citrinopileatus mushroom, (LEM) Lentinus edodes mushroom, and (HMM) Hypsizigus marmoreus mushrooms were tested in rats that were fed on a commercial diet (Beijing Keao Cooperative Feed Co.) ( Table 2). Fresh mushrooms were obtained from the Base Centre of Jilin Agricultural University, Changchun, China. Mushroom fruiting bodies were dried under sunlight for 72 h, and crushed into powder using a laboratory mill. Mushroom powder was mixed with the commercial diet as a daily intake of 8.5 g per individual. The nominated mushrooms' bioactive compounds are shown in Table 3.

| Sample preparation
Fifty milligrams of mushroom sample was mixed with 1 ml of the mixture (methanol:acetonitrile:water, 2:2:1). The sample was put into a multi-tissue grinder (frequency 60 Hz, 4 min) for tissue fragmentation, and then ultrasonicated for 10 min and then it was kept in the refrigerator for 1 h. the sample was centrifuged at 4°C for 15 min at 10,000 g. Seven hundred microliters of supernatant was put in a vacuum freeze dryer until it evaporated. The solution was resuscitated with 500 μl acetonitrile water (1:1) for 30 s and ultrasonicated for 10 min. The centrifugation was performed at 4°C for 15 min at 10,000 g. A volume of 50 μl of supernatant was put into the injection bottle and detected by LC-MS.

| Mobile phase
Phase A is ultrapure water containing 25 mM ammonium acetate and 25 mm ammonia, and phase B is acetonitrile. Current Speed 5 ml/min, column temperature 40°C, injection volume 2 μl.

| Liquid phase elution gradient
A gradient elution high-performance liquid chromatographic method is described in Table 4.

| Mass spectrometry conditions
Temperature of EFI ion source was 65°C. MS voltage was 5500 V (positive ion) and was 4500 V (negative ion). Declustering voltage DP was 6 0 V Ion source gas: gas 1 was 60 psi, gas 2 was 60 psi, and curtain gas (cur) was 30 psi.

| DNA extraction, polymerase chain reaction amplification and high-throughput sequencing
Next-generation sequencing (NGS), including library prepara-

| Sequence analysis
Quantitative Insights into Microbial Ecology (QIIME) data analysis software were used to analyze 16S rRNA data (Caporaso et al., 2010).
Quality filtering was performed on raw sequences according to Bokulich et al. (2012), as well as on joined sequences. Any sequence that was not <200 bp, with no ambiguous bases and a mean quality score ≥20 was discarded. Forward and reverse reads were joined and assigned to samples based on barcode and truncated by cutting off the barcode and primer sequence. The sequences were compared with the reference database (Ribosomal Database Project [RDP] Gold database) using the UCHIME algorithm (Edgar et al., 2011)  The RDP classifier uses the SILVA 119 database, which predicts taxonomic categories to the species level. Sequences were rarefied prior to calculation of alpha and beta diversity statistics. Alpha diversity indices were calculated in QIIME from rarefied samples using the Shannon index for diversity and the Chao1 index for richness (Chao, 1984;Chao & Lee, 1992). Beta diversity was calculated using weighted and unweighted UniFrac and principal component analysis (Bamberger & Lowe, 1988). An unweighted Pair Group Method with Arithmetic mean (UPGMA) tree from beta diversity distance matrix was built.

| Statistical analysis
Based on the beta diversity distance matrix and on environmental factor data, canonical correspondence analysis (CCA) between RFPs and BCC was integrated by the R-language software application (Team, 2018). All data were analyzed by one-way (mushroom type) analysis of variance (ANOVA) and were performed using SPSSsoftware, version 11.5 (SPSS, Version 11.5.0; SPSS Inc.). Results were expressed as Mean ± SD. Tukey's contrasts were used to test the significance level for the effects of mushroom types, with p < .05 indicating significant difference.

| Feed intake, plasma glucose level, and body weight
There were significant differences in feed intake between PCM and C−, and between POM and C+ (p < .05) ( Mushroom treatments showed a significant difference compared with C− in body weight (p < .05) ( Table 6). HMM treatment showed a significant difference compared with control (C− and C+) in liver weight (p < .05).

| OTU classification
Similarity among OTUs that were classified as belonging to different phylum, classes, orders, families, genus, and species (Table 8) (Table 10 and Figure 2).

| Alpha diversity
At genus level, Peptostreptococcaceae abundance was higher in C− and GLM treatments. Enterobacteriaceae abundance was higher in C+, POM, and HMM. Allobaculum abundance was high only in C− treatment (Table 11 and Figure 3).

| DISCUSS ION
Mushrooms have antihyperglycemic effects on diabetic individuals. LEM and HMM treatments showed lower plasma glucose levels.
LEM and PCM changed the ACE, Chao1, Shannon, and Simpson microbial indices significantly. Dietary supplementation of mushrooms reduced plasma glucose level directly due to mushrooms' bioactive compounds (agmatine, sphingosine, pyridoxine, linolenic, and alanine) and indirectly through oligosaccharide (stachyose) and gut microbiota modulation. Thus, LEM and HMM can be used as healthy food ingredients to improve gut microbiome composition in diabetic subjects.
Such inhibited KATP channel elevates the ATP/ADP ratio, leading to K + accumulation. This cell depolarization simulates a voltage-gated Ca 2+ channel activity, resulting in Ca 2+ influx and consequent insulin secretion (Velasco et al., 2016). In this study, mushroom treatments (LEM and HMM) showed the lowest blood glucose level, which can be explained by the high content of agmatine in LEM

TA B L E 7 (Continued)
showed a high level of Proteobacteria. That LEM and HMM mushrooms could manipulate the microbiota composition leading to an increased level of secreted insulin.
Such activation promotes incretin GLP-1 secretion, which is notable for having an effects on an anti-metabolic syndrome (Nagasawa et al., 2018). In this study, the HMM mushroom showed the highest level of PHS bioactive compound along with lower blood glucose levels (Rudd et al., 2020). In addition, the HMM mushroom showed the highest level of sphingosine along with lower blood glucose levels.
Pyridoxine decreases insulin resistance via scavenging the pathogenic reactive carbonyl species (Haus & Thyfault, 2018). Such molecule damages insulin protein via covalent modification of some structural amino acids, as well as, via the formation of adducts with phospholipids and DNA (Haus & Thyfault, 2018). In the current study, the GLM mushroom showed the highest level of pyridoxine bioactive compound along with lower blood glucose levels.
Nutritive acids could have a controversial effect on diabetic individuals. For instance, α-linolenic acid is a source for the generated oxylipins. Such molecules are lipid mediators affecting type 1 diabetes (Buckner et al., 2021). In our study, the LEM and HMM mushrooms showed the highest level of linolenic acid along with lower blood glucose levels. However, alanine may induce hyperglycemia in diabetic individuals. Since alanine aminotransferases increased levels are marked in diabetes hepatic cells (Okun et al., 2021). In the current study, the LEM mushroom showed the highest level of TA B L E 8 OTU classification and classification status identification results statistical table   Group  Phylum  Class  Order  Family  Genus  Species  Unclassified  Total   C−  7261  7261  7260  5713  2312  202  7  30,016   C+  2121  2121  2121  2076  1554  36  2  10,031   GLM  4279  4279  4278  3483  1223  111  4  17,657   POM  4699  4699  4698  4029  1519  108  3  19,755   PCM  5333  5333  5333  4419  1754  155  7  22,334   LEM  5477  5477  5477  4579  1867  169  4  23,050   HMM  5510  5510  5510  4609  1844  134  5  23,122   Total  34,680  34,680  34,677  28,908  12,073  915  32  145,965 Note: "Phylum", "Class", "Order", "Family", "Genus" and "Species" respectively correspond to the number of OTUs that can be classified into doors, classes, orders, families, genera, and species in each sample, and "Unclassified" refers to the number of OTUs that failed to belong to any known taxon.     (Agunloye & Oboh, 2022;Hossain et al., 2021;Jayasuriya et al., 2015;Qiu et al., 2022). Chisandra sphenanthera polysaccharide (191.18 kD) showed antidiabetic effect in rats with type 2 diabetes (Niu et al., 2017). Dendrobium officinale leaf polysaccharides of different molecular weights were orally administered daily at 200 mg/ kg/day, this level alleviated type II diabetes in an adult mouse (Fang et al., 2022). Thus, polysaccharides have an effect on diabetes whether they are low or high molecular weights. Stachyose is a non-reducing tetrasaccharide molecule which decreases the blood glucose level in alloxan-induced diabetic rats (Zhang et al., 2004).

F I G U R E 1
In addition, stachyose adjusts blood lipid levels in diabetic individuals (Chen et al., 2019). In the current study, the GLM mushroom showed the highest level of stachyose bioactive compound along with lower blood glucose levels. At the intestinal microbiota level, stachyose as a functional oligosaccharide regulates the intestinal microflora balance. Such prebiotic shifts of gut microbiota including Bifidobacterium and Lactobacillus as they are two common genera affecting a host health (Liu, Jia, et al., 2018;Liu, Wang, et al., 2018).
In this study, the LEM and HMM mushrooms showed the highest level of Lactobacillus genus along with lower blood glucose levels.
LEM and HMM mushrooms could modulate blood glucose levels and intestinal microbiota in diabetic individuals.
Changes in the gut microbiota composition are associated with multiple chronic disease pathologies, such as type 2 diabetes mellitus (Tang et al., 2017). Dietary fiber intake protects against diabetes by lowering dietary glycemic (Anderson et al., 2009). For example, oyster and button mushrooms have hypoglycemic effects, which reduce the fasting blood glucose level (Shehata et al., 2010). G. lucidum extract reduces blood glucose and insulin levels in rats (Hikino et al., 1985). Dietary supplements of I. bartlettii, Bifidobacterium longum, and B. cellulosilyticus in combination with water-soluble viscous fibers improve glucose homeostasis and dyslipidemia. Since gut microbiota affects insulin resistance by decreasing TNFα level in plasma and improving fasting blood glucose level in mice fed a highfat diet (Chuang et al., 2012).
F. prausnitzii abundance is low in individuals with T2D (Karlsson et al., 2013;Qin et al., 2012). Insulin resistance is related to B. wadsworthia and C. bolteae abundances (Qin et al., 2012). The species A. muciniphila, B. faecis, B. nordii, B. cellulosilyticus, B. pectinophilus, I. bartlettii, O. splanchnicus, D. longicatena, and R. inulinivorans were negatively associated with insulin resistance or dyslipidemia (Brahe et al., 2015). Bifidobacterium (B. longum) abundance was higher in healthy individuals than in obese individuals and T2D (Karlsson  et al., 2013). The more decrease in butyric acid production, the more decrease in C. leptum abundance (Wang et al., 2015). Butyrate has an anti-inflammatory activity that could improve insulin resistance (Brahe et al., 2013). F. prausnitzii affects insulin sensitivity, which may be due to its ability to produce butyrate (Louis & Flint, 2009). In this study, Allobaculum was increased in positive control treatment, whereas the Ruminococcus was increased in GLM treatment.
Regarding the mushroom mix potence, as individual mushrooms showed a significant effect on blood glucose level that mushroom mix could provide more effective role in blood glucose control regarding the gathered bioactive compounds and their possible compatible roles. Future studies are required to investigate the potency of mushroom mix with more diabetes parameters to reveal the underlying mechanism on diabetes-based long-term treatment.

| CON CLUS IONS
Dietary supplementation with mushrooms reduced the plasma glucose level and modulated gut microbiota in diabetic rats. Mushrooms showed a direct antihyperglycemic effect due to their content of agmatine, stachyose, phytosphingosine, and pyridoxine bioactive compounds. Mixed dietary mushrooms could develop a food ingredient with an effective and specific health functionality for diabetic individuals.

CO N FLI C T O F I NTE R E S T
None.

DATA AVA I L A B I L I T Y S TAT E M E N T
The data that support the findings of this study are available on request from the corresponding author.