Relationship and mechanism of gut microbiota and susceptibility to type 2 diabetes mellitus

doi:10.21203/rs.3.rs-1994874/v1

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Research Article

Relationship and mechanism of gut microbiota and susceptibility to type 2 diabetes mellitus

https://doi.org/10.21203/rs.3.rs-1994874/v1

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Journal Publication

published 05 May, 2023

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Purpose

To investigate the relationship between the susceptibility to type 2 diabetes and gut microbiota and explore the potential mechanisms.

Methods

Thirty-two SPF SD rats were raised as the donor rats, and divided into control, type 2 diabetes mellitus (T2DM) and Un-mod groups. Feces were collected and prepared as fecal bacteria supernatant A (T2DM group), B (Un-mod group) and Con (control group). Another seventy-nine SPF SD rats were separated into normal saline (NS) and ABX groups. ABX and NS groups were given antibiotics solution and normal saline, respectively. And then, the ABX group were randomly separated into the ABX1 (4-weeks ordinary diet), ABX2 (4-weeks HFD and STZ ip), FMT-A (fecal microbiota A transplantation, 4-weeks HFD and STZ ip), FMT-B (fecal microbiota B transplantation, 4-weeks HFD and STZ ip) and FMT-Con (normal fecal microbiota transplantation, 4-weeks HFD and STZ ip) groups. The NS group were randomly divided into the NS1 (4-weeks ordinary diet) and NS2 (4-weeks HFD and STZ ip) groups. The short-chain fatty acids (SCFAs) in feces were detected by gas chromatography using 16S rRNA gene sequencing. G protein-coupled receptor 41 (GPR41) and GPR43 were detected by Western blot and quantitative real-time polymerase chain reaction.

Results

g__Ruminococcus_gnavus_group were increased obviously in the FMT-A group (vs ABX2 or FMT-B group). Blood glucose levels, serum insulin, total cholesterol levels, triglyceride levels, and low-density lipoprotein cholesterol levels were evidently increased in the FMT-A group than ABX1 or ABX2 group. It was found that both the FMT-A and FMT-B groups had evidently higher contents of acetic acid and butyric acid (vs ABX2 group). In both FMT-A and FMT-B groups, GPR41 protein expression and GPR43 mRNA and protein expression increased.

Conclusions

G__Ruminococcus_gnavus_group may cause T2DM susceptibility, and T2DM susceptible flora transplantation can evidently increase the susceptibility to T2DM. It is possible that gut microbiota-SCFAs-GPR41/GPR43 play a role in the development of T2DM. A new treatment strategies and methods may be to develop pharmaceutical treatments that reduce blood glucose by controlling gut microbiota.

Type 2 diabetes mellitus

Gut microbiota

16S rRNA gene sequencing

short-chain fatty acids

GPR41/GPR43

Type 2 diabetes mellitus (T2DM) is a chronic inflammatory multiple disease caused by a relative or absolute decrease of insulin secretion due to various factors such as genetics or the environment, resulting in metabolic disorders of glucose and lipid. In traditional Chinese medicine, T2DM is classified as "xiaoke" because it is characterized by polydipsia, polyphagia, polyuria, and weight loss^[1]. Globally, there were about 537 million diabetics, in the light of the 10th edition, with China ranking first with 140 million diabetics. By 2045, the number of diabetes mellitus (DM) patients worldwide will increase to 783 million, of which more than 90% are T2DM^[2]. With the aging of the population and the fast-paced lifestyle, the incidence of DM is rising, and the trend is getting younger and younger. Long-term hyperglycemia can lead to extensive vascular damage, affect the heart, eyes, kidneys and nerves, cause various complications and serious threat to human health and lives^[3], which increase the economic burden on families and society, but its pathogenesis is still unclear.

Recently, a study revealed that pathological state isn't solely regulated by genes, but by the gut microbiota as well, which is called the "second genome" or "microbial organ". The number of gut microbiota is huge and diverse, about 10¹⁴ and more than 500 to 1000 species^[4], which is 10 times as many as the human cells^[5,6]. According to the effects of gut microbiota on the human body, bacteria are generally divided into beneficial, conditional pathogenic, and pathogenic bacteria. They restrict each other in the human intestine and jointly maintain intestinal homeostasis^[7].

As a result of the gut microbiota, diseases like diabetes^[8] and obesity^[9] arise and develop pathologically. T2DM models are typically prepared using high-fat diets (HFD) and streptozotocin (STZ) injections intraperitoneally. However, this approach does not always lead to T2DM, and there is a similar phenomenon in clinical studies, that means, not all people on a high-fat diet suffer from T2DM, which may be related to gut microbiota composition. There are bacteria that predispose hosts to T2DM, as well as bacteria that do not, indicating that gut microbiota plays a significant role in its development and occurrence^[10,11]. Consequently, it is imperative to examine the relationship between T2DM and gut microbiota.

There is evidence that gut microbiota produce SCFAs, which are highly concentrated in the intestine and could motivate GPR41 and GPR43, which increases gastrointestinal hormone secretion, reduces IR, and lowers blood glucose levels^[⁷^]. Therefore, we established pseudo-sterile rats model by giving antibiotic solution and tested susceptibility to T2DM by FMT, and further elucidated the pathological causality among the gut microbiota, SCFAs, GPR41/ GPR43 and T2DM. In this study, we will offer a new method to treat T2DM, clinically.

Animals

Male Sprague-Dawley rats (body weight, 200 ± 20 g) were purchased from SPF (Beijing) Biotechnology Co. Ltd, Licence No. SCXK (Jing) 2019-0010. housed under specific pathogen-free conditions at 24°C with 49 humidity and a 12 h light/dark cycle in the Animal Experiment Center of Beijing University of Chinese Medicine. As the donors of fecal samples, donor rats were randomly divided into two groups: the control group (fed with standard animal chow), and the HFD group (fed with high-fat diet). Rats were fasted for 12 hours after 4-weeks HFD and HFD rats were received 1% STZ citrate buffer solution (0.1 mmol/L, pH = 4.2 to 4.5) (Sigma Aldrich, USA) at a dose of 35 mg/kg ^[12]. Control rats received an equal amounts of citrate buffer solution intraperitoneally. After three days, a cutoff value of 11.1 mmol/L was used to divide the HFD rats into the T2DM and Un-mod groups. T2DM rats' feces were collected as susceptible fecal bacteria A, Un-mod rats' feces were collected as non-susceptible fecal bacteria B and control rats' feces were collected as normal fecal microbiota.

Preparation of pseudo-sterile rats

The experimental process is shown in Fig. 1. Seventy-nine SPF SD rats were adaptively fed for 1 week, of which fifty-eight rats were given antibiotic solution [50 mg/kg Vancomycin, 100 mg/kg neomycin sulfate, 100 mg/kg metronidazole, 100 mg/kg ampicillin (Macklin)] by gavage, once a day, 1 mL/100 g, for 10 consecutive days (ABX group). The other twenty-one rats were intragastrical administrated with normal saline once a day for 10 days (NS group). 10 days later, the feces of rats of both groups were collected for 16S rRNA determination for the first time in terms of the constructed method of feces sample collection^[13].

The first fecal microbiota transplant

On the basis of body weight, the ABX group were randomly separated into 5 groups: ABX1 group (n = 10), ABX2 group (n = 12), fecal microbiota A transplantation (FMT-A) group (n = 12), fecal microbiota B transplantation (FMT-B) group (n = 12) and normal fecal microbiota transplantation (FMT-Con) group (n = 12). According to established method, FMT was performed^[14]. Fresh fecal samples were collected from donor rats under aerobic and sterile conditions, and each gram of mixed feces was resuspended in 5 mL of deionized water. After vigorous vortexing for 10 seconds, the suspension was centrifuged at 3500 rpm for 3 minutes at 4°C, and then, we collected the supernatant. The supernatant of fecal bacteria A, B and Con were prepared in the same way. Rats FMT-A, FMT-B and FMT-Con groups were intragastrical administrated with corresponding fecal bacteria supernatant (1 mL/100 g), once a day, for 7 consecutive days. The ABX1, ABX2 and NS groups were intragastrical administrated the same amount of deionized water 7 consecutive days, once a day. And then the NS group was randomly divided into two groups based on body weight: NS1 group (n = 10), NS2 group (n = 11). The feces of rats in every group were collected for 16S rRNA determination for the second time.

High-fat feeding

After FMT, rats in NS2, ABX2, FMT-A, FMT-B and FMT-Con groups were fed with HFD for 4 weeks, while rats in NS1 and ABX1 groups were fed with ordinary diet for 4 weeks. After 2 weeks (the third time) and 4 weeks (the fourth time) of feeding, feces were collected from the above groups for 16S rRNA determination.

The Second fecal microbiota transplant

After 4 weeks of high-fat feeding, the results of 16S rRNA showed that the gut microbiota of the rats signally recovered, so a second fecal microbiota transplantation was performed. The rats in FMT-A, FMT-B, FMT-Con, ABX1 and ABX2 groups were treated with antibiotic solution again for 10 days, once a day, and the NS1 and NS2 groups were intragastrical administrated with sterile saline. At the same time, the blood glucose of donor rats was measured in the Supplemental Data 1. And then, FMT-A, FMT-B and FMT-Con groups were intragastrical administrated with corresponding fecal bacteria supernatant, ABX1, ABX2, NS1 and NS2 groups were given the same enzyme once a day for 7 days. After that, the feces of rats in every group were collected for 16S rRNA determination for the fifth time.

Oral glucose tolerance test and STZ injection

All rats were fasted and free of water overnight (12 h) and the noral glucose loading (2.0 g/kg) was operated. A glucose meter was used to measure blood glucose before and after loading with oral glucose for 15, 30, 60 and 120 minutes. The AUC was calculated as follows by blood glucose:

AUC (mmol/h/L) = 1/2 × [(BG0 + BG15) × 1/4 + (BG15 + BG30) × 1/4 + (BG30 + BG60) × 1/2 + (BG60 + BG120)]

BG: blood glucose level at different times.

Three days after OGTT, the ABX2, NS2, FMT-A, FMT-B and FMT-Con groups were intraperitoneally injected with 35 mg/kg STZ. The same amount of citrate buffer solution was administered intraperitoneally to both ABX1 and ABX2 groups. Three days later, the modeling rate of rats was calculated. After that, the feces of rats in every group were collected for 16S rRNA determination for the sixth time. In order to make the experiment more meaningful, all rats with blood glucose ≥ 11.1 mmol/L were selected for the follow-up experiment.

ELISA assay

Serum TC, TG, LDL-C, and HDL-C levels were detected by biochemical kits (Nanjing Jiancheng). Serum insulin levels were detected ELISA kit (Kete), and the HOMA-IR index was calculated as follows:

HOMA-IR = fasting insulin (mU/L) × FBG (mM) / 22.5.

Histopathological examination

The Pancreas tissues were fixed in 4% paraformaldehyde solution for 48 hours, dehydrated with ethanol, embedded in paraffin and sectioned stained with hematoxylin–eosin (H&E).and observed the pathological morphology under a microscope.

16S rRNA gene sequencing of gut microbiota

The 16S rRNA gene was sequenced based on an established method^[15]. Briefly, DNA extraction and qRT-PCR amplification were performed first. And then, DNA was purified and sequenced. Finally, sequence processing was performed with an Illumina MiSeq PE300 platform^[¹³^].

GC analysis

We prepared acetic acid (23.9 mg/mL), propionic acid (30.7 mg/mL), isobutyric acid (8.8 mg/mL), butyric acid (36.3 mg/mL) and 2-ethylbutyric acid (5.8 mg/mL) standards. In a 5 mL centrifuge tube, 200 mg of feces was placed, internal standard and appropriate amounts of ether wereput, and hydrochloric acid was used to adjust the pH value. GC analysis was performed after vortexing and centrifuging samples and passing them through a microporous membrane of 0.22 μm^[16]. The chromatographic conditions were based on an established method^[¹³^].

Quantitative real-time PCR

An intestine total RNA extraction was performed by TRIzol® Reagent (Ambion), and reverse transcription with a Revert Aid First Stand cDNA Synthesis SuperMix (Novoprotein) A Real-time quantitative PCR system with the SYBR qPCR SuperMix (Novoprotein) was used to detect gene expression. The PCR was performed in triplicate for each sample, and the data were expressed in arbitrary units after normalization of β-actin expression levels. Supplemental Data 2 provides the primer sequences.

Western blot analysis

The intestinal tissue protein concentration was determined by the bicinchoninic acid protein detection kit following weighing, grinding in liquid nitrogen, and lysing in RIPA Lysis Buffer (Beyotime). PVDF membrane was incubated in an enclosing solution for 2 h. And then PVDF membrane was incubated overnight at 4°C in the required primary antibodies, including β-actin (1:20000, 66009-1-Ig, Proteintech), GPR41 (1:2000, OM184469, OmnimAbs, Alhambra), and GPR43 (1:1000, 19952-1-AP, Proteintech, Rosemont, IL) .Following a wash with Tris buffered saline as well as Tween 20, the membranes were incubated with the corresponding secondary antibodies and then exposed to chemiluminescence reagents and detection with an Amersham enhanced chemiluminescence system. Image-Pro-Plus 6.0 was performed to quantify Western blot bands.

Statistical analysis

SPSS 22.0 and GraphPad Prism 8 software were used to analyze statistically all data which were expressed as mean ± standard deviation (SD) values in each group. For normally distributed data and homogeneous variances, the Wilcoxon rank sum test or one-way ANOVA (LSD t-test) was used; for abnormal distribution of data, non-parametric testing was used. P < 0.05 was considered to be statistically significant.

Summary of sequencing results

The high-quality sequences were retrieved from intestinal stool samples of all the rats which ranged from 735,027 to 3,159,798, with an average length ranged 413–422 bp. In the Alpha diversity of this study, rarefaction curves reached a stable point and Coverage surpassed 99.4%, indicating the microbial community was near saturation, and most species could be detected in the current sequencing amount.

Successful establishment of the pseudo-germ-free rats

Alpha diversity (Fig. 2A–D), including the rarefaction curve, Coverage, Shannon and Chao indexes, showed the Shannon and Chao indexes in the ABX group were considerably lower than the NS group (P < 0.01). The β-diversity results (Fig. 2E–F), containing the hierarchical clustering tree and PCoA, demonstrated distinct clustering for each group at the OTU level. The Circos (Fig. 2G), heatmap (Fig. 2H) and barplot analysis (Fig. 2I) indicated the bacterial genera of the ABX group was slightly less than that of NS group at the genus level. In conclusion, the biological abundance and biodiversity of the ABX group were substantially reduced, and the pseudo-germ-free rats were successfully established.

We used Wilcoxon rank-sum tests to investigate the differences between the two groups' fecal bacterial communities (selecting species with the top 15 mean sums, P < 0.05, Fig. 3A–E). In comparison with the NS group, p__Proteobacteria, c__Gammaproteobacteria, o__Enterobacterales, f__Enterobacteriaceae and f__Morganellaceae increased evidently. At the genus level, g__Klebsiella was evidently increased, the other species were evidently reduced. By utilizing a linear discriminant analysis (LDA) effect size (LEfSe) algorithm (LDA values of > 2 with P < 0.05), we determine the altered specific bacterial taxa between the two groups (Fig. 3F). The NS group had 16 species with abundances exceeding 1%, while the ABX group had 2. Bacteria with abundances exceeding 1% were listed in Supplemental Data 3. There were 123 genera that differed evidently from the NS group, 5 genera that were increased and 118 genera that were decreased in the ABX group, and 16 genera with high abundances (over 1%) between them. There was an obviousincrease in g__Klebsiella in the ABX group compared to the NS group, as well as an obvious decrease in g__Lactobacillus, g__Blautia, g__Prevotella, g__norank_f__Muribaculaceae, g__Allobaculum, g__UCG-005, g__Subdoligranulum, g__Marvinbryantia, g__unclassified_f__Lachnospiraceae, g__Phascolarctobacterium, g__Fusicatenibacter, g__Bacteroides, g__Faecalibaculum, g__Lachnospiraceae_NK4A136_group and g__UCG-008.

Dynamic changes in gut microbiota structure after the first fecal microbiota transplantation

Alpha diversity (Fig. 4A–D) showed the abundance and diversity of gut microbiota in the ABX group were evidently decreased (P < 0.01 vs NS group). The richness and diversity of species in FMT-A, FMT-B and FMT-Con groups were signally increased (P < 0.01 vs ABX group), which demonstrated that the abundance and diversity of gut microbiota in pseudo-germ-free rats were distinctly enhanced after FMT. The β-diversity result showed at the OTU level, the groups were strongly clustered, and the NS and FMT-Con groups had a certain similarity. The FMT-A and FMT-B groups also demonstrated some similarities. The Circos, heatmap and baplot (Fig. 4E-G) showed the groups were distinctly different from each other at the genus level, among which NS and FMT-Con groups had some similarity, and FMT-A and FMT-B groups also had some similarity.

Based on the above analysis, fecal microbiota successfully colonized the intestine of pseudo-germ-free rats by FMT.

Dynamic changes in gut microbiota structure after 2 weeks of HFD

Alpha diversity (Fig. 5A–D) indicated that the richness of ABX1 group was obviously reduced (P < 0.01 vs NS1 group), there was no remarkedly different in diversity, implying that with the extension of feeding time, the gut microbiota of pseudo-germ-free rats progressively revived. Species abundance and diversity of ABX2 group were evidently decreased (P < 0.01 vs ABX1 group), it suggested that HFD is not conducive to the self-recovery of gut microbiota. In comparison with the ABX2 group, the species richness and diversity of FMT-A and FMT-Con groups were evidently increased (P < 0.05), the species richness in the FMT-B group was clearly increased (P < 0.05), the diversity showed a rising trend, but there was no statistically significant difference. At the OTU level, the β-diversity result showed that the NS1 group and the ABX1 group had obvious clustering with each other but had certain similarities. NS2, ABX2, FMT-A, FMT-B and FMT-Con groups had high similarity, and each group had certain clustering. The Circos, heatmap and baplot (Fig. 5E-G) showed, at the genus level, NS1 group and ABX1 group have a certain similarity. The differences among NS2, ABX2, FMT-A, FMT-B and FMT-Con groups were lower than those after the first fecal microbiota transplantation.

Dynamic changes in gut microbiota structure after 4 weeks of HFD

Alpha diversity (Fig. 6A–D) showed in the prevailing sequencing, The richness of community in the ABX2 group was distinctly reduced (P < 0.01 vs ABX1 group), and the difference of diversity was not significant. In comparison with the abundance and diversity of communities in the FMT-A, FMT-Con and NS2 groups were not obviously different, while the abundance of communities in the FMT-B group was remarkedly increased (P < 0.05 vs ABX2 group), and they did not differ remarkedly in diversity. The β-diversity result showed at the OTU level, The similarity between NS1 and ABX1 groups was higher than in two weeks of HFD. The clustering of the NS2, ABX2, FMT-A, FMT-B and FMT-Con groups was poor, and the difference was lower than in two weeks of HFD. The Circos, heatmap and baplot (Fig. 6E-G) showed the similarity between NS1 and ABX1 groups was higher than in two weeks of HFD group. The clustering of NS2, ABX2p, FMT-A, FMT-B and FMT-Con groups was poor, and the difference was lower than in two weeks of HFD group.

Since the gut microbiota of rats have the self-recovery ability, the difference between the groups steadily diminished with the prolongation of time, so we executed a second fecal microbiota transplant.

Dynamic changes in gut microbiota structure after the second fecal microbiota transplantation

Alpha diversity (Fig. 7A–D) showed in the current sequencing, in terms of diversity and richness, the ABX1 and ABX2 groups did not differ evidently. the abundance and diversity of communities in NS2, FMT-A, FMT-B and FMT-Con groups were signally increased (P < 0.01 vs ABX1 group).

The β-diversity result showed at the OTU level, the NS1 group had obvious clustering, which was obviously different from other groups; the ABX1 group was deeply similar to the ABX2 group; the NS2, FMT-A, FMT-B and FMT-Con groups had a high degree of similarity. Nevertheless, in the hierarchical tree diagram, the FMT-A group had apparent clustering and the FMT-Con group also had considerable clustering (Fig. 7E and F). At the genus level, the Circos, heatmap (Fig. 7H) and barplot (Fig. 7G-I) showed bacterial genera were clearly different among the groups, among which the ABX1 and ABX2 groups were highly similar, with g__Klebsiella as the main bacterial genus, and the abundance was higher. The similarity between NS2 and FMT-Con groups was substantial.

In conclusion, the second FMT effectively improved the structure of gut microbiota of rats in each group, and the antibiotic solution also effectively removed gut microbiota.

FMT affects glucose and lipid metabolism and insulin resistance

In Fig 8, peak values of the blood glucose in the NS1 and ABX1 groups was reached at 15 min, and there was no obvious difference at all of the time points. The highest values of the NS2, FMT-B and FMT-Con groups was reached at 30 min, and the ABX2 and FMT-A groups reached peak at 15 and 60 min, respectively. In comparison with the ABX1 and ABX2 groups, the initial blood glucose in the FMT-A group was remarkedly increased (P < 0.01), and the initial blood glucose in the FMT-Con group was markedly decreased (P < 0.01) than that of the FMT-A group. At 15 min, the blood glucose of the NS2 and FMT-A groups was much higher than that of the ABX1 group. The blood glucose in the NS2, FMT-A, FMT-B and FMT-Con groups was evidently increased at 30 min (P < 0.01, vs ABX1 group). The blood glucose in the FMT-A and FMT-B groups was distinctly increased at 30 min (P < 0.01 vs ABX2 group). the blood glucose in NS2, FMT-A, FMT-B and FMT-Con groups increased evidently at 60 min (P < 0.01 vs ABX1 group). The blood glucose in the FMT-A, FMT-B and FMT-Con groups was evidently increased at 60 min (P < 0.01 vs ABX2 group). The blood glucose of all the groups did not differ remarkedly at 120 min. The AUC of NS2, FMT-A, FMT-B and FMT-Con groups was distinctly increased (P < 0.01 vs ABX1 group). The AUC of the FMT-A and FMT-B groups was evidently added (P < 0.01 vs ABX2 group), but they did not differ clearly.

After 3 days of intraperitoneal STZ injection, in the NS2 group, 3 rats died, 1 rat failed to be T2DM model (blood glucose < 11.1mmol/L), and 7 rats were successfully established T2DM model (blood glucose ≥ 11.1mmol/L). The molding rate was 63.64% and the mortality rate was 27.27%. In the ABX2 group, 2 rats died, 2 rats were failed and 8 rats were succeeded. The molding rate was 66.67%, and the mortality rate was 16.67%. In the FMT-A group, 4 rats died, 8 rats became T2DM model, and the molding rate was 66.67% and the mortality rate was 33.33%. In the FMT-B group, 2 rats died, 3 rats did not become T2DM model, 7 rats became T2DM model. The molding rate was 58.33%, and the mortality rate was 16.67%. In the FMT-Con group, 2 rats died, 2 rats did not become T2DM model, and 8 rats became T2DM model. The molding rate was 66.67% and the mortality rate was 16.67%. Blood glucose of rats in ABX2, NS2, FMT-A, FMT-B and FMT-Con groups were obviously increased (P < 0.01 vs ABX1 group). The blood glucose of the FMT-A group was obvious increased (P < 0.05 vs ABX2 group), but there was no distinctly different in the FMT-B and FMT-Con groups. The blood glucose of the FMT-B and FMT-Con groups was obviously reduced than that of the FMT-A group (P < 0.05). The HbA1c level in the FMT-A group was distinctly increased (P < 0.05 vs ABX1 group), but there was no obviously different in the other groups. In comparison with the ABX2 group, the FMT-A group demonstrated an upward trend of HbA1c, but they did not differ signally. Serum insulin and HOMA-IR were remarkedly increased in ABX2, NS2, FMT-A, FMT-B and FMT-Con groups (P < 0.01 vs ABX1 group). And serum insulin level and HOMA-IR were obviously increased in FMT-A group than the ABX2 group (P < 0.05). The serum insulin of the FMT-Con group showed a downward trend, and HOMA-IR was distinctly decreased (P < 0.05 vs FMT-A group). TC, TG and LDL-C of rats in ABX2, NS2, FMT-A, FMT-B and FMT-Con groups were evidently increased (P < 0.01 vs ABX1 group). TC in the FMT-A group was obviously increased than the ABX2 group (P < 0.05). TG, TC, LDL-C and HDL-C among NS2, ABX2, FMT-A, FMT-B and FMT-Con groups were not clearly different.

As shown in Fig. 9, Pancreatic islets were plump and elliptical, and the morphology of islet cells and exocrine acinar cells around islets showed no abnormal pathological changes. in the NS1 and ABX1 groups. The number and volume of islets diminished, islet cell necrosis, vacuolar degeneration and fibrous tissue hyperplasia were observed in the entire field of vision in the NS2 group. The volume of islets in the ABX2 group was markedly reduced, and the structure was disordered, accompanied by fibrous tissue hyperplasia. In the FMT-A group, the islet structure was disordered, the hemosiderin was deposited, accompanied by fibrous tissue hyperplasia, and severe inflammatory reaction. In the FMT-B group, there was decreased number of islets, reduced volume, disordered structure and the hyperplasia of fibrous tissue. In the FMT-Con group, a decrease in the number of islets, a reduction in the volume, and a disorderly structure and a small amount of vacuolar degeneration.

Alpha diversity (Fig. 10A–D) showed in the current sequencing, the richness of gut microbiota revealed no marked difference between the ABX1 and ABX2 groups, while the diversity of gut microbiota in ABX2 group was distinctly decreased (P < 0.01). The richness and diversity of communities in the FMT-A, FMT-B and FMT-Con groups were prominently increased (P < 0.01 vs ABX2 group). The diversity and richness of the FMT-Con group and NS2 group were not clearly different. The richness of communities in the FMT-A group was not evidently different, but the diversity was prominently decreased (P < 0.01 vs FMT-Con group), and the FMT-Con and FMT-B groups did not differ distinctly in the abundance and diversity. The abundance and diversity of communities were not signally different in the FMT-A and FMT-B groups.

The β-diversity result (Fig. 10E and F) showed the NS1 group had distinct clustering and was obviously different from other groups at the OTU level. The ABX1 group was Similar to the ABX2 group, and the NS2, FMT-A FMT-B, and FMT-Con groups had a similarity. Because they were obviously affected by STZ, which exceeded the FMT and made the flora of every group tend to be consistent. At the genus level, the Circos heatmap and barplot (Fig. 10G-I) showed the NS1, ABX and ABX2 groups had good clustering, and the NS2, FMT-A, FMT-B and FMT-Con groups had high similarity.

In the cause of further understanding the differences in every group and obtaining the bacterial genera that may be linked to T2DM development and occurrence, LEfSe multi-level discriminant analysis was conducted. The genera with abundances exceeding 1% can be found in Supplemental Data 4.

ABX2 group and FMT-A group

LEfSe analysis showed (Fig. 11) that the 120 genera changed evidently between groups. In comparison with the ABX2 group, 113 were increased and 7 were decreased in the FMT-A group, and 17 showed high abundance (> 1%). In comparison with the ABX2 group, g__Klebsiella and g__Escherichia-Shigella decreased evidently, and g__Blautia, g__Lactobacillus, g__Ruminococcus_torques_group, g__unclassified_f__Lachnospiraceae, g__Lachnoclostridium, g__Bifidobacterium, g__Ruminococcus_gauvreauii_group, g__Bacteroides, g__Fusicatenibacter, g__Ruminococcus_gnavus_group, g__Coriobacteriaceae_UCG-002, g__norank_f__Butyricicoccaceae, g__norank_f__Lachnospiraceae, g__Anaerostipes and g__Romboutsia increased evidently in the FMT-A group. Among them, g__Klebsiella reached 92.32% in the ABX2 group, and g__Lactobacillus 23.23%, g__Blautia 18.93% and g__Ruminococcus_torques_group 9.978% in the FMT-A group. These genera played a key role in the differences between them.

ABX2 group and FMT-B group

LEfSe analysis showed (Fig. 12) that the 124 genera changed evidently between groups. In comparison with the ABX2 group, 118 genera rised and 6 genera reduced in the FMT-A group, and 18 genera with high abundance (> 1%). In comparison with the ABX2 group, g__Klebsiella and g__Escherichia-Shigella decreased remarkly, and g__Blautia, g__Bifidobacterium, g__unclassified_f__Lachnospiraceae, g__Ruminococcus_torques_group, g__Lachnoclostridium, g__Romboutsia, g__Ruminococcus_gauvreauii_group, g__norank_f__Lachnospiraceae, g__Coriobacteriaceae_UCG-002, g__Anaerostipes, g__Bacteroides, g__Subdoligranulum, g__Adlercreutzia, g__Marvinbryantia, g__Ruminococcus and g__Collinsella increased evidently in the FMT-B group. G__Klebsiella 92.32% in ABX2 group, g__Blautia 18.43%, g__unclassified_f__Lachnospiraceae 13.18% and g__Bifidobacterium 11.37% in the FMT-B group that was very meaningful between the two groups.

FMT-A group and FMT-B group

LEfSe analysis demonstrated (Fig. 13) that the 14 genera changed evidently between groups. In comparison with the ABX2 group, 3 were increased and 11 were reduced in the FMT-A group, and 3 genera were in high abundance (> 1%). In comparison with the FMT-A group, the g__Lactobacillus, g__norank_f__Butyricicoccaceae and g__Ruminococcus_gnavus_group were prominently reduced in the FMT-B group. Our team's previous study showed that g__Ruminococcus_gnavus_group was markedly different in the donor T2DM rats and Un-mod rats, and it was still prominently different after FMT. Therefore, we considered g__Ruminococcus_gnavus_group as a specific genus of T2DM.

ABX1 group and ABX2 group

LEfSe analysis showed (Fig. 14) that the 27 genera changed evidently between groups. In comparison with the ABX2 group, 10 genera that were up and 17 genera that were down in the FMT-A group, and 7 genera in high abundance (> 1%). In comparison with the ABX1 group, g__Lactobacillus, g__Ruminococcus_gnavus_group, g__Enterococcus, g__Parasutterella, g__unclassified_o__Lactobacillales, g__Erysipelatoclostridium decreased evidently and g__Klebsiella increased evidently in the ABX2 group. The above changes genera were the result of the effects of HFD and STZ.

NS2 group and ABX2 group

LEfSe analysis showed (Fig. 15) that the 99 genera changed evidently between groups. In comparison with the ABX2 group, 7 raised and 92 were decreased in the FMT-A group, and 14 genera showed high abundance (> 1%). In comparison with the NS2 group, g__Lactobacillus, g__unclassified_f__Lachnospiraceae, g__Blautia, g__Ruminococcus_torques_group, g__Lachnoclostridium, g__Bifidobacterium, g__Bacteroides, g__Ruminococcus_gauvreauii_group, g__norank_f__Lachnospiraceae, g__Anaerostipes, g__Romboutsia, g__Ruminococcus and g__Subdoligranulum decreased evidently, g__Klebsiella increased evidently in the ABX2 group. These changes in gut microbiota were caused by antibiotics.

FMT-A and FMT-Con group

LEfSe analysis showed (Fig. 16) that the 51 genera changed evidently between groups. In comparison with the ABX2 group, 13 genera that were raisedand 38 genera that were declinedin the FMT-A group, and 11 genera in high abundance (> 1%). In comparison with the FMT-Con group, g__Lachnoclostridium, g__norank_f__Lachnospiraceae, g__Romboutsia, g__unclassified_f__Lachnospiraceae, g__Ruminococcus, g__UCG-005, g__norank_f__Eubacterium_coprostanoligenes_group, g__Marvinbryantia decreased evidently, g__Ruminococcus_torques_group, g__Fusicatenibacter and g__Ruminococcus_gnavus_group increased signally in the FMT-A group.

Mechanism validation

Researchers found that T2DM is associated with SCFAs, primarily acetic acid, propionic acid, and butyric acid, which play a crucial role in regulating glycolipid metabolic disorders, improving insulin resistance, and treating obesity and other metabolic diseases. In Fig. 16A, compared the ABX1 group, the contents of acetic acid and butyric acid were distinctly decreased in the ABX2 group (P < 0.01), the content of propionic acid in the FMT-A and FMT-B groups was obviously increased (P < 0.01). The contents of acetic acid, propionic acid and butyric acid in the FMT-A and FMT-B groups were signally increased (P < 0.01 vs ABX2 group). In addition, the FMT-A and FMT-B groups did not differ obviously, but the FMT-B group showed an increasing trend.

A WB assay was performed as well as a qRT-PCR to examine the connection between SCFAs and T2DM by detecting the GPR41 and GPR43 mRNA and protein levels. In Fig. 16E–I, the results from the WB were in accord with those obtained from qRT-PCR. In comparison with the ABX1 group, the GPR41 mRNA in the ABX2 group showed a downward trend, the GPR41 protein expression was remarkedly decreased (P < 0.01), and the GPR43 mRNA and protein expression were signally reduced (both P < 0.01). The mRNA of GPR41 in the FMT-A group showed a downward trend, and the protein expression of GPR41 was distinctly decreased (P < 0.01). The mRNA expression of GPR43 in the FMT-A group was obviously reduced (both P < 0.01), and the GPR43 protein expression were not evidently different. The GPR41 mRNA in the FMT-B group was prominently increased (P < 0.01), and the GPR41 protein and the GPR43 mRNA and protein expressions were not changed. In comparison with the ABX2 group, the GPR41 mRNA revealed an rising trend, and the GPR41 protein and GPR43 mRNA and protein expressions were markedly increased in the FMT-A group (P < 0.05). The GPR41 and GPR43 mRNA and protein expressions were prominently increased in the FMT-B group (both P < 0.01). The GPR41 mRNA and protein expressions and the mRNA expression of GPR43 in FMT-B group were obviously increased (P < 0.01 vs FMT-A group), and they were not clearly different in the GPR43 protein expression.

Related researches have found that the intestinal florais closely concerned with many metabolic diseases, including T2DM, hepatic steatosis, etc., and FMT can evidently alleviate ulcerative colitis^[17], obesity and metabolic syndrome^[18].The diabetics have moderate intestinal microbial disorder^[19]. There was a discinct decrease in total bacteria and probiotics in the intestines; however, harmful bacteria accounted for a significant increase^[20]. 16S rDNA is an independent risk indicator of diabetes, which confirms that the involvement of bacteria in the onset of human diabetes^[21].Changing the gut microbiota may control the T2DM process^[22,^23]. According to clinical observations, each population is more sensitive to T2DM based on their innate endowments. These differences may reflect differences in gut flora. The above studies show that the gut microbiota plays a vital role in the onset and development of T2DM. Therefore, we tested susceptibility to T2DM and screened the susceptible bacteria of T2DM, which may be conductive in the diagnosis and therapy of T2DM.

In the present study, the pseudo-germ-free rat model was first prepared by gavage of antibiotic solution. 16S rRNA results proved that the species and richness of gut microbiota were greatly reduced, the abundance of g__Klebsiella was only distinctly increased in the ABX group. We hypothesized that the antibiotic had no significant effect on g__Klebsiella, which is an opportunistic pathogen living in the upper respiratory and digestive tract of the body, despite its broad spectrum. When the body's immunity is reduced, g__Klebsiella can proliferate rapidly, impairing organs such as lungs and causing infection^[24]. And then we performed the first FMT, the 16S rRNA analysis results revealed that the FMT could successfully colonize the relevant flora in the pseudo-germ-free rats, and increase the abundance and diversity of gut microbiota in rats. The gut microbiota gradually began to recover as the pseudo-germ-free rats not living in an absolutely sterile environment, combined with the rats themselves also have a certain resilience, along with HFD extension of time. So we performed a second antibiotic to remove the gut microbiota and a second FMT to colonize the flora in the intestines.

T2DM is a disease of glucose and lipid metabolism disorder, and its metabolism of glucose and lipid is abnormal. In this experiment, data showed that transplant fecal bacteria A increased the blood glucose, serum insulin, HOMA-IR, TC, TG and LDL-C, indicating that fecal bacteria A can increase the susceptibility of T2DM rats. Fecal bacteria B did not alleviate or reduce the risk of T2DM in rats in this experiment, which is speculated to be due to the strong destructive effect of STZ on the pancreas, beyond the ability of FMT to regulate blood glucose. However, under the same modeling conditions, the blood glucose, modeling rate and serum insulin levels in the FMT-B group were obviouslylower than those in the FMT-A group, indicating that fecal bacteria B was not susceptible to T2DM in rats to a certain extent.

Previous studies have proved the content of g__Ruminococcus_gnavus_group in T2DM rats is remarkedly higher than that in the control and Un-mod groups^[¹³^]. This experiment further confirmed the association between fecal bacteria A and T2DM susceptibility through FMT, and verified the relationship between T2DM susceptibility and gut microbiota. Among them, g__Ruminococcus_gnavus_group is specific for T2DM, and its abundance in T2DM rats or FMT-A group is evidently higher than that in other groups. G__Ruminococcus_gnavus_group is positive relationship with fasting blood glucose ^[25], which can lead to obesity or overweight by causing cells to absorb too much sugar^[26].

The SCFAs content in feces and the GPR41/43 mRNA and protein expressions in colon tissues of the FMT-A and FMT-B groups were evidently increased, which proved that FMT could signally improve the SCFAs content and GPR41/43 expressions, and those in the FMT-B group were further, indicating that the susceptible bacteria of T2DM could reduce the SCFAs content and the GPR41/43 mRNA and protein expression levels. In conclusion, this experiment proves that the increase of T2DM susceptible bacteria such as g__Ruminococcus_gnavus_group and the decrease of beneficial bacteria such as g__Prevotella and g__Allobaculum lead to the decrease of SCFAs and GPR41/43 expression, thus inducing T2DM. "Gut microbiota – SCFAs - GPR41/43" is involved in the pathological process of T2DM.

T2DM

Type 2 diabetes mellitus

Normal saline

GPR41

G protein-coupled receptor 41

GPR43

G protein-coupled receptor 43

SCFAs

Short-chain fatty acids

FBG

Fasting blood glucose

Total cholesterol

Triglyceride

LDL-C

Low-density lipoprotein cholesterol

Diabetes mellitus

STZ

Streptozotocin

HFD

High-fat diet

GLP-1

Glucagon-like peptide-1

FMT

Fecal microbiota transplantation.

Ethics approval and consent to participate

The animal protocol of this study was approved by the Animal Ethics Committee of Beijing University of Chinese Medicine (BUCM-4-2020102002-4043).

Consent to publish

Not applicable.

Availability of data and materials

All data used and analyzed in thecurrent study are available from the corresponding author upon request.

Competing interests

The authors declare that they have no competing interests.

Funding

This work was supported by the National Natural Science Foundation of China (81973535).

Authors’ contributions

YA contributed to formal analysis and manuscript preparation, was a major contributor in writing the manuscript; YD, HD, LC, LS and CH helped perform investigation, data curation and methodology; CW, HZ, WF, YH, YL and HL contributed to the study with constructive suggestions; WS and BZ made contribution in the conception and funding acquisition, and wrote review & editing.

Author details

^aDepartment of Pharmacology, School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 102488, China. ^b Department of Pharmacognosy, School of Pharmacy, China Medical University, Shenyang 110122, China. ^cSchool of Life Sciences, Beijing University of Chinese Medicine, Beijing 102488, China. ^dGuangZhou Baiyunshan Xingqun Pharmaceutical Company Limited, Guangzhou, 510288, China. ^e Beijing Research Institute of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, 100029, China.

Acknowledgements

Not applicable.

1 Zahra A, Lee E, Sun L, Park J. Cardiovascular disease and diabetes mortality, and their relation to socio-economical, environmental, and health behavioural factors in worldwide view. Public Health. 2015;129(4):385-95.

2 International Diabetes Federation.IDF Diabetes Atlas, 10th edn. Brussels, Belgium: International Diabetes Federation, 2021.

3 Shi L, An Y, Cheng L, Li Y, Li H, Wang C, et al. Qingwei San treats oral ulcer subjected to stomach heat syndrome in db/db mice by targeting TLR4/MyD88/NF-κB pathway. Chin Med. 2022;17(1):1.

4 Gilbert J, Blaser M, Caporaso J, Jansson J, Lynch S, Knight R. Current understanding of the human microbiome. Nat Med. 2018;24(4):392-400.

5 Qin J, Li R, Raes J, Arumugam M, Burgdorf K, Manichanh C, et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature, 2010;464(7285):59-65.

6 Phillips M. Gut reaction: environmental effects on the human microbiota. Environ Health Perspect. 2009;117(5):A198-205.

7 Ma Q, Li Y, Li P, Wang M, Wang J, Tang Z, et al. Research progress in the relationship between type 2 diabetes mellitus and intestinal flora. Biomed Pharmacother. 2019;117:109138.

8 Qin J, Li Y, Cai Z, Li S, Zhu J, Zhang F, et al. A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature. 2012;490(7418):55-60.

9 Turnbaugh P, Hamady M, Yatsunenko T, Cantarel B, Duncan A, Ley R, et al. A core gut microbiome in obese and lean twins. Nature. 2009;457(7228):480-4.

10 Burcelin R, Serino M, Chabo C, Blasco-Baque V, Amar J. Gut microbiota and diabetes: From pathogenesis to therapeutic perspective. Acta Diabetol. 2011;48(4):257-273.

11 Larsen N, Vogensen F, van den Berg F, Nielsen D, Andreasen A, Pedersen B, et al. Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults. PLoS One. 2010;5(2):e9085.

12 Cheng L, Wang J, An Y, Dai H, Duan Y, Shi L, et al. Mulberry leaf activates brown adipose tissue and induces browning of inguinal white adipose tissue in type 2 diabetic rats through regulating AMP-activated protein kinase signalling pathway. Br J Nutr. 2022;127(6):810-822.

13 An Y, Duan Y, Dai H, Wang C, Shi L, He C, et al. Correlation analysis of intestinal flora and pathological process of type 2 diabetes mellitus[J]. JTCMS, 2022;9(2):15.

14 Guo S, Wu H, Zhai C, Cheng G, Cai J. Effects of fecal microbiota transplantation on lipidemia and gut barrier indiet-induced obesity rats. China Modern Doctor. 2016,54(04):25-27+33+169.

15 Lu W, Fu T, Wang Q, Chen Y, Li T, Wu G. The effect of total glucoside of paeony on gut microbiota in NOD mice with Sjögren's syndrome based on high-throughput sequencing of 16S rRNA gene. Chin Med. 20201;15:61.

16 Ning J, Wang Y, Ding W, Wang Z, Song Q, Yang Y, et al. The correlation between short chain fatty acids levles in feces and HbA1c of type 2 diabetes mellitus patients based on gas chromatography. Chin J Microecol. 2020;32(9):1007-1011.

17 Costello S, Hughes P, Waters O, Bryant R, Vincent A, Blatchford P. Effect of Fecal Microbiota Transplantation on 8-Week Remission in Patients With Ulcerative Colitis: A Randomized Clinical Trial. JAMA. 2019;321(2):156-164.

18 Marotz C, Zarrinpar A. Treating Obesity and Metabolic Syndrome with Fecal Microbiota Transplantation. Yale J Biol Med. 2016;89(3):383-388.

19 Qin J, Li Y, Cai Z, Li S, Zhu J, Zhang F, et al. A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature. 2012;490(7418):55-60..

20 Sun Y, Liu B, Zhao J. Comparison of intestinal flora in diabetic patients and healthy adults in Dalian J. World Chinese Journal of Digestology, 2003 (06): 863-865.

21 Amar J, Serino M, Lange C, Chabo C, Iacovoni J, Mondot S, et al. Involvement of tissue bacteria in the onset of diabetes in humans: evidence for a concept. Diabetologia. 2011;54(12):3055-61.

22 Burcelin R, Serino M, Chabo C, Blasco-Baque V, Amar J. Gut microbiota and diabetes: from pathogenesis to therapeutic perspective J. Acta diabetologica, 2011, 48(4): 257-273.

23 Larsen N, Vogensen F, van den Berg F, Nielsen D, Andreasen A, Pedersen B, et al. Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults. PLoS One. 2010;5(2):e9085.

24 Martin R, Bachman M. Colonization, Infection, and the Accessory Genome of Klebsiella pneumoniae. Front Cell Infect Microbiol. 2018;8:4.

25 Li G, Yin P, Chu S, Gao W, Cui S, Guo S, et al. Correlation Analysis between GDM and Gut Microbial Composition in Late Pregnancy. J Diabetes Res. 2021;2021:8892849.

26 Venditto I, Luis A, Rydahl M, Schückel J, Fernandes V, Vidal-Melgosa S, et al.Complexity of the Ruminococcus flavefaciens cellulosome reflects an expansion in glycan recognition. Proc Natl Acad Sci U S A. 2016;113(26):7136-41

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Relationship and mechanism of gut microbiota and susceptibility to type 2 diabetes mellitus

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