Predominant Bacterial Diversity in Rheumatoid Arthritis Rat After Treated with Caprine CSN1S2 Protein

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http://dx.doi.org/10.11594/jtls.11.02.01

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Research Article

Predominant Bacterial Diversity in Rheumatoid Arthritis Rat After Treated with Caprine CSN1S2 Protein

Eko Suyanto ^{1, 2}, Fatchiyah Fatchiyah ^{1, 2}*

1 Biology Department, Faculty of Mathematics and Natural Sciences, Brawijaya University, Veteran, Malang 65145, Indonesia

2 Research Center of Smart Molecule of Natural Genetics Resource, Brawijaya University, Veteran, Malang 65145, Indonesia

Article history:

Submission September 2020 Revised October 2020 Accepted March 2021

ABSTRACT

Rheumatoid arthritis (RA) is an autoimmune and systemic inflammatory disease that is affected to microbial abnormalities in the gut and altered the metabolism and immune system. Bioactive peptides have many functions in the body that related to health. This study aimed to investigate the effect of caprine CSN1S2 protein and to identify the predominant bacterial diversity in rheumatoid arthritis rats through fecal analysis based on PCR-DGGE and phylogenetic analysis. The animals were divided into 6 groups with 2 types of the rat model, namely control rats (untreated (C), treated with caprine CSN1S2 protein from milk (CM), and treated with caprine CSN1S2 protein from yogurt (CY)) and rheumatoid arthritis rats (rheumatoid arthritis (RA), treated with caprine CSN1S2 protein from milk (RAM), and treated with caprine CSN1S2 protein from yogurt (RAY). Predominant cultivable bacteria were obtained by direct culture and analyzed using PCR-DGGE with several specific primers. The DNA sequences were analyzed and aligned using bioinformatics software to construct the phylogenetic tree. The results showed that bacterial composition in all control groups was dominated by Lactobacillus group but in the rheumatoid arthritis rat (RA) group was dominated by Enterococcus group, particularly Enterococcus faecium and Enterococcus faecalis. Meanwhile, Bacillus coagulans dominated in rheumatoid arthritis rats after treated with caprine CSN1S2 protein. The caprine CSN1S2 protein has effects in rheumatoid arthritis rats with the emergence of predominant bacteria that can promote the growth of B. coagulans and it might be suppressed pathogenic bacteria in the development of rheumatoid arthritis disease.

Keywords:Rheumatoid arthritis, Dysbiosis, CSN1S2, Enterococcus, Bacillus coagulans

*Corresponding author:

E-mail: [email protected]

Introduction

One of the chronic inflammatory diseases, namely rheumatoid arthritis (RA) is characterized by swelling of synovial, pain of bone in the joints, and may have affected other tissues and organs. It occurs in almost 7.3% of the Indonesian popula- tion. It is suffered by the resident at a productive age, with a profound effect on social life, psycho- logical condition, and work productivity disrup- tion [1]. Various inflammatory pathways caused the characteristic of this disease. They were associated with immune system dysregulation and the onset of rheumatoid arthritis disease [2].

The recent studies showed that the develop-

ment of rheumatoid arthritis disease was influ- enced by genetic and environmental factors [3, 4].

Other research had focused on the genetic factor that showed over 100 genetic susceptibility loci have been discovered and involved in rheumatoid arthritis disease [5]. Meanwhile, there are environmental risk factors including smoking [3], hor- mone fluctuation [6], periodontitis [7, 8], and particularly gut microbiota composition correlated with the host immune system due to the symbiotic interactions between a host and gut microbiota [9, 10].

The microbiota composition abnormalities or

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dysbiosis in the gut play a key role in the biological mechanisms of inflammation that affect metabolic disorders and the development of rheumatoid arthritis disease [11–13]. Dysbiosis can be identified through fecal analysis to determine the microbiota composition in the gut. The fecal samples are the end product of the digestive system process that occurred in the gut. It is easily acces- sible and provides raw material to study the microbiota composition in the gut that is related to the emergence of the inflammatory disease. Despite it also provides valuable data in assessing for bi- omarker candidates.

Microbial metabolism that affects the development of rheumatoid arthritis disease is a prospec- tive target for inhibiting by nutrients or bioactive compounds [14, 15]. On the other hand, many studies have reported that malnutrition was associated with pathological conditions and inflammation. Therefore, pathogenic bacteria activity in the gut that affects the development of rheumatoid arthritis is maybe prospectively inhibited by functional food. The bioactive peptide in milk is one of the functional food known to play important roles in physiological function and suppress the metabolic-related to chronic disease [16], anti-glyco- sylation [17], immunomodulatory, as well as antihypertensive [18].

Our previous study reported that bioactive peptide, namely caprine CSN1S2 protein with a molecular weight of 36 kDa, was found in goat milk. It has many functions, such as antioxidant [19], anti-osteoporosis [17], antimicrobial [20], and anti-inflammatory [21]. Although it has many functions, the effect of caprine CSN1S2 protein of fresh milk and yogurt against bacterial composition in rheumatoid arthritis disease did not investigate so far. We used fecal analysis from the rheumatoid arthritis rat model whose is induced by Complete Freund’s adjuvant (CFA) 1) to reveal predominant bacterial diversity in the gut based on culture-independent method after treated with caprine CSN1S2 protein of fresh milk and yogurt by using Denaturing Gradient Gel Electrophoresis (DGGE) analysis and 2) to identify the predominant bacterial by using sequences analysis and phylogenetic clustering.

Material and Methods Ethical clearance

All experiments involving animals were performed following ethical standards. The

Brawijaya University ethics committee evaluated and approved the study protocol with the registra- tion number of ethical clearance, KEP-90-UB.

Preparation of caprine CSN1S2 protein

Caprine (Ethawah crossbreed goat) milk and yogurt were obtained from UPTD Singosari, Ma- lang, Indonesia. According to the previous studies, the caprine CSN1S2 protein (molecular weight is 36 kDa) was isolated from caprine milk and yogurt [17, 22]. The fresh milk and yogurt were heated at 40^oC then were added by glacial acetic acid. It was stirred until precipitate formation. After that, the precipitate was filtered by using a nylon mesh membrane. The caprine CSN1S2 protein was measured using a NanoDrop spectrophotometer and then was stored at -20^oC.

Experimental animals and fecal collection Twenty-four adult male Wistar rats (12 weeks old), weight 150-200 g, were obtained from the In- tegrated Research and Testing Laboratory (LPPT), Universitas Gadjah Mada, Yogyakarta then all rats were acclimatized for 1 week under laboratory conditions before to use for the experimental pro- cedure. These rats were exposed to a 12-hour light and 12-hour dark cycle at room temperature and they had free access to a standard laboratory with diet and water, ad libitum. The induction of rheumatoid arthritis was performed by using an injection technique. A single subcutaneous injection technique was used to inject 100 µl of Complete Freund’s Adjuvant (CFA; Sigma-Aldrich Inc, St.

Louis, USA) into the rats. After 14 days from the first injection, these rats were intradermally injected with 50 µl CFA into the lower extremity.

According to the previous studies, the treatment of caprine CSN1S2 protein of fresh milk and yogurt was performed [21, 23]. The rats were divided into two types of rat models: the control and rheumatoid arthritis rat model. Each rat model consisted of the untreated group, the caprine CSN1S2 protein of the fresh milk-treated group, and the caprine CSN1S2 protein of the yogurt- treated group. Therefore, there were 6 groups (n = 4 each), namely C group (untreated control rat), CM group (control rat treated with caprine CSN1S2 protein of fresh milk), CY group (control rat treated with caprine CSN1S2 protein of yogurt), RA group (rheumatoid arthritis rat), RAM group (rheumatoid arthritis rat treated with caprine CSN1S2 protein of fresh milk), and RAY group

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(rheumatoid arthritis rat treated with caprine CSN1S2 protein of yogurt). Fecal samples were collected from the rats using sterile forceps and then put into sterile microtubes for further analysis.

Bacterial cell and cultivation

A fecal sample from each type of rat model was cultured into Luria Bertani (LB) broth. The bacterial cells were isolated using the serial dilution technique from fecal suspension in saline water (0.85% NaCl). The sample from each dilution was inoculated into de Man Rogosa and Sharpe (MRS) agar medium then it was then incubated anaerobically at 37^oC for 48-72 h [24]. The colo- nies of bacterial cells with different morphological characteristics were isolated from primary culture then re-streaked on agar media using a four-way streak plate technique to obtain a pure colony. All purified isolates were cultured into broth media for DNA isolation.

Bacterial DNA isolation

The 1.5 ml of bacterial cell cultures were centrifuged at 8,000 rpm, 4ôC for 5 min. The superna- tant was removed, then the pellet was added by 1 ml of lysis buffer, vortexed for 5 min, and incubated at 37ôC for 1 h. The suspension was centrifuged at 10,000 rpm, 4ôC for 10 min, then the su- pernatant was removed. The PCI reagent for 1x volume (25 : 24 : 1, v/v) was added to the pellet and homogenized by vortex for 2 min then fol- lowed by centrifugation at 10,000 rpm, 4ôC for 10 min. The upper aqueous phase was transferred into

a 1.5 ml microtube, and the absolute ethanol for 2.5 × volume was added into the microtube and incubated at -20ôC for 5 min. The mixture was centrifuged at 10,000 rpm, 4ôC for 10 min. The pellet was washed with 1x volume of 70% ethanol, vortexed for 5 min, then centrifuged at 10,000 rpm, 4ôC for 10 min. The pellet was air-dried, then dissolved in 50 μl of TE buffer pH 7.6. The purified DNA samples were stored at -20ôC. The quan- tity and quality of DNA samples were measured by NanoDrop spectrophotometer and 1% agarose gel electrophoresis. All primers were designed to amplify the DNA from bacterial groups in the gastrointestinal tract (Table 1). They were used for a preliminary study to identify the bacterial group.

PCR-DGGE analysis and 16S rRNA sequencing In this study, the forward or reverse primer was used to amplify the DNA from each sample.

The primer was added with a 40 bp of GC-clamp and was attached to the 5’ side of a specific primer to scale up the PCR product's sensitivity for DGGE analysis. The PCR mix solution was added with 12.5 μl of GoTaq green (Promega) and the PCR program was carried out as follows: 95ôC for 3 min; 31 cycles of 95ôC for 30 s, 55ôC for 30 s, 72ôC for 1 min, and final extension of 72ôC for 5 min. The PCR product was analyzed using DGGE (Biorad) based on the manufacture’s protocols in combination with several previous studies [30, 31]. The DGGE gel was made with 8% (w/v) of the polyacrylamide gel (acrylamide: bis-acrylamide, 37.5:1), 40% denaturing gradient, 10% am- monium persulfate (APS), and 10 μl of TEMED.

Table 1. Specific primers were used in this study

Primers Primer sequence (5’-3’) Target group References

V6-V8_F TACGGGAGGCAGCAG Universal bacteria [24]

V6-V8_R ATTAACCGCGGCTGCTGG

g-BifidF CTCCTGGAAACGGGTGG Bifidobacterium [25, 26]

g-BifidR GGTGTTCTTCCCGATATCTACA

Ent.1017F CCTTTGACCACTCTAGAG Enterococcus [27]

Ent.1263R CTTAGCCTCGCGACT

Lac1F AGCAGTAGGGAATCTTCCA Lactobacillus [27]

Lac2R ATTYCACCGCTACACATG

Bact_596F TCAGTTGTGAAAGTTTGCG Bacteroides [28]

Bact_826R GTRTATCGCMAACAGCGA

Ccoc_F AAATGACGGTACCTGACTAA Clostridium-

Eubacterium rectale

[29]

Ccoc_R CTTTGAGTTTYATTCTTGCGAA

GC-clamp CGCCGGGGGCGCGCCCCGGGC GGGGCGGGGGCACGGGGGG F = forward primer, R = reverse primer

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The DNA in the gels was run at 60^oC with a con- stant voltage of 60 V for 16 h in 1× TAE buffer.

The gels were stained with 10 μl of Ethidium Bro- mide (EtBr) for 30 min. The visualization of DNA bands in the gels was captured using the Gel-Doc system (Biostep gel documentation system). The similarity of the banding pattern in the profile of DGGE was analyzed based on the presence and absence of bands and expressed as a similarity co- efficient. The PCR products were purified then sent to a sequencing company.

Phylogenetic analysis

The DNA sequences were analyzed using Bi- oEdit 7.0.1 to pair alignment. Each of the DNA sequences was inserted into MEGA-X 10.0.5 software and multiple alignments by MUSCLE using a UPGMA (Unweight Pair Group Method with Arithmetic Average) method for clustering. The pair of taxa from DNA sequences was analyzed using the distance matrix with the Maximum Composite Likelihood model. The phylogenetic tree was constructed using statistical methods, namely the Neighbor-Joining algorithm and the Minimum Evolution algorithm. The phylogeny test was performed using the bootstrap method with 1000 bootstrap replication to predict the evo- lutionary relationship. The DNA sequence data of reference bacterial strains were subjected to ho- mology searches with the BLAST program. The type strains of bacterial DNA sequences were obtained from the GenBank database and EzBio- Cloud database.

Results and Discussions Bacterial diversity

In this study, we found bacterial cells from fecal samples were predominantly cultivable bacteria in agar medium and they were analyzed by using PCR-DGGE. All bacteria were found in anaerobic conditions and they were facultative anaerobe. This result describes the diversity of predominant cultivable bacteria in fecal samples based on the direct culture method to evaluate bacterial composition in the gut of the rheumatoid arthritis rat model after treated with caprine CSN1S2 protein. These bacterial cells were associated with rheumatoid arthritis disease. The morphological analysis of bacterial isolates was determined to characterize the bacteria. Furthermore, a preliminary study was done to test all primers used to identify all bacteria. The result showed that a

difference between samples only appeared on three sets of primers (data not shown). The visualization of PCR products using 1.5% agarose gel showed a single band indicated that the DNA was successfully amplified with forward and reverse primer.

Based on the results, the DNA bands of Bifidobacterium, Bacteroides, and Clostridium- Eubacterium rectale group were disappeared from all treatments. The amplification product of bacteria in the fecal samples were dominated by Lacto- bacillus group with band size ± 800 bp and Enter- ococcus group with band size ± 650 bp (Figure 1).

The predominant bacteria in fecal samples also showed the same DNA bands for the Lactobacillus group with band size ± 250 bp and Enterococcus group with band size ± 300 bp PCR-DGGE analysis (Figure 2). We assumed that the treatment of caprine CSN1S2 protein in control rats had increased Lactobacillus group but suppressed the growth of other bacterial groups including Bifidobacterium, Enterococcus, Bacteroides, and Clostridium-Eubacterium rectale group. In contrast, the RA rat model did not show any band, except the universal bacterial group, after treating caprine CSN1S2 protein of yogurt. This data showed that the growth of bacterial cells from the other species (isolates RAY1 and RAY2) may be correlated with rheumatoid arthritis disease.

Our study showed interesting data that Lacto- bacillus group significantly increased for diversity and abundance in all control rat models. However, predominant bacteria communities in the fecal of rheumatoid arthritis rat model were dominated by Enterococcus group, which belongs to lactic acid bacteria found in humans and animals [32]. The isolate RA1 and RA2 are similar to Enterococcus group based on PCR-DGGE and phylogenetic analysis, namely Enterococcus faecium (99.48%) and Enterococcus faecalis (98.97%), respectively.

We assumed that these bacteria can be suppressed the growth of other bacteria groups such as Lacto- bacillus, Bifidobacterium, Bacteroides, and Clos- tridium since they were not found in the fecal of rheumatoid arthritis rat models.

The Enterococcus group is a bacterial group producing enterocin that may inhibit pathogenic bacteria [33]. One of the bacteria in that group is E. faecium, which has two genes in the genome for producing enterocin A and P and showed antimicrobial activity against pathogenic bacteria [34].

The previous study also revealed that E. faecalis

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has 7 genes for virulence determinants, namely efaAfs, gelE, agg, cpd, cob, ccf, and cad [35]. They were resistant to tetracycline (32.9%), erythromy- cin (9.4%), and vancomycin (2.4%) [36] and also induced pro-inflammatory cytokines through the activation of TLR2 [37]. The Enterococcus group significantly decreased the intestinal epithelial tight junction, autoantibody production and increased the Th17 lymphocytes via activation of the

AhR system. The increase of Th17 cells in the small intestine and spleen were associated with the development of rheumatoid arthritis disease in mice due to K/B × N T cell receptor that can develop inflammatory arthritis [38].

The nucleotide bases of the 16S rRNA gene were aligned with several species in the Bacillus group and Enterococcus group. The alignment results showed that gaps in the sequences were Figure 1. The PCR products of bacterial DNA. The DNA band of bacterial isolates were disappeared for

Bifidobacterium, Bacteroides, and Clostridium-Eubacterium rectale group. Bacterial composition in the fecal were dominated by Lactobacillus group with DNA band size ± 800 bp and Enterococcus group with band size ± 650 bp.

Figure 2. The DNA band profiles from each isolate were determined by using PCR-DGGE. The differences in the appearance of the band were obtained from PCR products by using three specific primers to amplify the predominant bacterial group in fecal samples. A) The profile of bacterial DNA by using universal bacterial primer, B) The profile of bacterial DNA by using Lactobacillus primer, C) The profile of bacterial DNA by using Enterococcus primer. M = marker.

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caused by the change of nitrogen bases, such as substitution (transition and transversion), insertion, and deletion. The DNA sequences from 6 bacterial isolates were compared with the sequence of Bacillus coagulans ATCC 7050T, while the two bacterial isolates were compared with En- terococcus hirae ATCC 9790T. Substitution is a change of base in some parts with another base.

There were around 41% substitution, 6.7% deletion, and 5% insertion in isolate C3. Furthermore, mutation also found in isolate C2, isolate CM1, isolate RAY1 and isolate RAY2 around 0.5% - 18% substitution, 0.5% - 5% deletion and 0.5% - 2.2% insertion. For isolate RA1 and isolate RA2 had around 10% - 12.2% substitution, 1.7% - 2.17% deletion and 0.8% - 2.2% insertion.

Each of the 16S rRNA gene sequences from each isolate was analyzed using bioinformatics software and showed a highly conserved region. A highly conserved region describes the level of phylogenetic relationships, whereas the hypervariable region shows the level of evolution. This

region contains 9 hypervariable regions (V1-V9), which are sequences diversity among different bacteria. Mutation at one of the DNA sites will change the sequences so that it reveals the difference between bacterial isolates. In this result, there were various mutations, including substitution, deletion, and insertion.

We found that the DNA sequences for all bacteria had an average frequency of GC content of 52.36%, while AT content only 47.64% (Table 2).

Generally, the GC content of bacteria was varied dramatically, from less than 25% to more than 75%, showing that it ascribed to differences in the pattern of mutation between bacteria [39–41]. The difference of base composition is not restricted for the particular bacterial group even though the GC content shows a level of phylogenetic inertia.

Most bacteria classes showed substantial variation in genomic GC content, for example, in the α-proteobacteria group. It has GC content ranging from less than 30% to more than 60%.

Furthermore, the previous study showed that Table 2. Interpretation of 16S rRNA gene bands for all isolate based on PCR-DGGE.

Predominaant.

bacteria

Primers Universal

bacteria (±100bp)

Lactobacillus

(±250bp) Bifidobacterium Enterococcus

(±300bp) Bacteroides

Clostridium- Eubacterium

rectale

C1 + - - + - -

C2 + + - - - -

C3 + + - - - -

CM1 + + - - - -

RA1 + - - + - -

RA2 + - - + - -

RAY1 + - - - - -

RAY2 + - - - - -

The symbols were indicating of 16S rRNA gene bands. + = appear, - = disappear.

Table 3. The abundance of nitrogen bases, GC content, AT content, and partial protein in bacterial DNA sequences.

Isolates A C G T GC content (%) AT content (%) Molecular Weight

C1 25.97 22.08 31.60 20.35 53.68 46.32 36899.40 Da

C2 23.71 24.67 30.02 21.61 54.68 45.32 42516.91 Da

C3 25.32 23.89 27.87 22.93 51.75 48.25 51331.30 Da

CM1 23.07 26.70 27.27 22.95 53.98 46.02 72797.33 Da

RA1 26.00 23.25 25.03 25.72 48.28 51.72 60169.71 Da

RA2 27.89 22.63 25.61 23.86 48.25 51.75 46702.11 Da

RAY1 30.03 21.45 29.70 18.81 51.16 48.84 24086.69 Da

RAY2 24.86 24.58 32.49 18.08 57.06 42.94 28276.51 Da

Average 25.85 23.70 28.70 21.8 52.36 47.64 45347.49 Da

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the GC content in bacterial lipoprotein related to TLR2 expression. The triacylated lipoprotein structure (lyso structure) in low-GC Gram positive bacteria (E. faecalis, Bacillus cereus, Bacillus subtilis, Streptococcus sanguinis, and Lactoba- cillus bulgaricus) induced the pro-inflammatory cytokines through the activation of TLR2 due to the absence of the E. coli-type Lnt in their genomes. The lyso structure was also reported in Gram- negative bacteria and high-GC content Gram- positive bacteria due to the presence of E. coli- type Lnt homolog in their genomes [42–44].

Therefore, we assumed that E. faecium and E.

faecalis are predominantly bacteria in the gut of the rheumatoid arthritis rat model induced by CFA and may be associated with the development of rheumatoid arthritis disease. In contrast, the rheumatoid arthritis rat model treated with the caprine CSN1S2 protein did not show any band appearance of Enterococcus and Lactobacillus group except for the universal bacteria it was dominated by Bacillus group.

Phylogenetic tree

Neighbor-Joining and Minimum Evolution constructed the topology of the phylogenetic tree presented in Figure 3 and Figure 4 to see the difference in genetic distance and analyze the simila- rities between bacterial isolates. The construction of a phylogenetic tree resulted in 2 types of similar trees. There were 2 main clades in the phylo-genetic tree. The isolates RA1 and RA2 formed in one clade of the Enterococcus group consisting of 10 accessions. The isolates C1, C2, CM1, RAY1, and RAY2 formed in one subclade, consisting of 11 accessions in the main clade of Bacillus group.

These B. cereus strain N419, B. licheniformis strain sm2, B. megaterium strain BMU4, and B.

cereus ATCC 14579T formed other subclades to- gether. The isolates RAY1 and RAY2 had high similarity with different strains of B. coagulans that are B. coagulans strain SM10 (97.35%) and B. coagulans strain bca1 (96.71%), respectively.

The isolate C3 had a low similarity with the others, so we assumed neither the Enterococcus group nor Figure 3. The phylogenetic tree showing the relationship between all bacterial isolates found in fecal samples

and several other related bacteria. Their genetic relationship is inferred based on 16S rRNA gene sequences. The tree was constructed by using a Neighbor-Joining algorithm and the branching was analyzed by using bootstrap with 1000 replication. Prevotella copri strain JCM 13464(T) was used as an out-group. Scale length 0.1 sequence divergence

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the Bacillus group.

The differences of predominant microbial communities in the fecal samples showed the bacterial diversity in the gut of rats that was checked by deriving a phylogenetic tree. The previous study showed that the bacteria found in the intestinal are anaerobic and facultative anaerobic bacteria from several bacterial groups, such as Firmic- utes, Bacteroides, Proteobacteria, Verrumicrobia, and Actinobacteria [45]. Bifidobacterium and Bacteroides are normal bacteria found in the human intestinal besides Faecalibacterium, Rose- buria, and Lactobacillus [24].

Caprine CSN1S2 protein and predominant bac- teria

Based on the previous study, the bacterial species from the Bacteroides group associated with

rheumatoid arthritis disease is P. copri [38, 46].

The pathogenic bacteria of periodontal disease, Porphyromonas gingivalis, may also correlate with the development of rheumatoid arthritis due to the ability to express peptidyl arginine deimi- nase (PAD) that related to ACPA [47, 48] How- ever, P. copri and P. gingivalis were not found in our study. Interestingly, our study revealed the other bacteria in the fecal of rheumatoid arthritis rat model after treated with caprine CSN1S2 protein. They had a similarity with B. coagulans and it has a different strain based on PCR-DGGE and phylogenetic analysis. The B. coagulans lactic acid bacteria, spore-forming bacterial species of the genus Bacillus, and facultative anaerobe. It is probiotic bacteria in the intestinal and produced the bacteriocin-like substances, namely coagulin, which has the activity against enteric microbes Figure 4. The phylogenetic tree showing the relationship between all bacterial isolates found in fecal samples

and several other related bacteria. Their genetic relationship is inferred based on 16S rRNA gene sequences. The tree was constructed by using a Minimum-Evolution algorithm and the branching was analyzed by using bootstrap with 1000 replication. Prevotella copri strain JCM 13464(T) was used as an out-group. Scale length 0.1 sequence divergence

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[49–51]. It is also used to prevent and treat inflammatory bowel disease, colorectal cancer [52], and anti-diarrheal [53].

In vitro and in vivo studies revealed that B. co- agulans promoted digestion of protein and carbo- hydrate due to secreting various enzymes [54, 55].

The digesting activity can produce metabolites compounds such as short-chain fatty acids (SCFA), vitamins, and diacetyl to promote healthy bowel movement and avoid the accumulation of toxins [55]. The previous study has shown B. co- agulans significantly enhanced the life-survival of the intestinal cells by decreasing inflammation to improve the nutrient absorption on the villi. The B.

coagulans competed with several opportunistic pathogens in the intestinal for maintaining intestinal homeostasis [56, 57].

Furthermore, caprine CSN1S2 protein was found around 20% of the total casein fraction in milk and has unique physicochemical properties so that possess many functions as bioactive com- pound, therapeutic, and health-promoting properties [58]. We assumed that the bacteria used caprine CSN1S2 protein as the carbon source to grow up and change the metabolism pathway in the intestinal [21, 56], and then excreted anti-microbial peptides so that it affected pathogen survival in rheumatoid arthritis [18]. Thus, CSN1S2 protein is a promising prebiotic modulating gut bacteria as a therapy for metabolic syndrome treatment [59]. We also reported that B. coagulans might suppress the pathogenic bacteria that affected the development of rheumatoid arthritis disease. This bacterial species dominated in the gut of rheumatoid arthritis rat model after treated with caprine CSN1S2 protein. Thereby, caprine CSN1S2 protein can support B. coagulans to cre- ate an aerobic and acidic environment in the gut for promoting the growth of probiotics and suppress the pathogenic bacteria as to produce antimicrobial compounds.

Conclusion

The caprine CSN1S2 protein has physicochemical properties and it has affected predominant bacterial diversity in the gut of rat models. It also allows modulating the bacterial cell and metabolism pathways. The treatment of caprine CSN1S2 protein in control rats able increased Lac- tobacillus group but suppressed the growth of other bacteria. A bacterial group, namely Enter- occous group including Enterococcus faecium and

Enterococcus faecalis was found in the rheumatoid arthritis rat model that may be associated with the development of this disease. In contrast, a bacterial species, namely Bacillus coagulans, dominated the rheumatoid arthritis rat model after treated with caprine CSN1S2 protein. This protein may have an important role as a prebiotic in the gut of rat to modulate the growth of B. coagulans and might be suppressed pathogenic bacteria were associated with rheumatoid arthritis.

Acknowlegment

This study is supported by funding from the DPP/SPP grant, Faculty of Mathematics and Nat- ural Sciences, Brawijaya University, grant con- tract no. 1/UN10.F09.01/PG/2019, and a part of PDPT national research grant from Ministry of National Education, Republic of Indonesia. We are grateful to Rista Nikmatu Rohmah, M.Si for her help in DGGE analysis.

References

1. Gibofsky A (2014) Epidemiology, pathophysiology, and diagnosis of rheumatoid arthritis: a synopsis. The American journal of managed care 20 (7 Suppl): S128—

35.

2. Yu MB, Langridge WHR (2017) The function of myeloid dendritic cells in rheumatoid arthritis. Rheumatology International 37 (7): 1043–1051. doi: 10.1007/s00296- 017-3671-z.

3. Bernard NJ (2018) Synergy of environmental and genetic risk in rheumatoid arthritis. Nature Reviews Rheumatology 14 (6): 319. doi: 10.1038/s41584-018- 0015-7.

4. van Steenbergen HW, da Silva JAP, Huizinga TWJ, van der Helm-van Mil AHM (2018) Preventing progression from arthralgia to arthritis: targeting the right patients.

Nature Reviews Rheumatology 14 (1): 32–41. doi:

10.1038/nrrheum.2017.185.

5. Okada Y, Wu D, Trynka G et al. (2014) Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature 506 (7488): 376–381. doi:

10.1038/nature12873.

6. Firestein GS, McInnes IB (2017) Immunopathogenesis of rheumatoid arthritis. Immunity 46 (2): 183–196. doi:

10.1016/j.immuni.2017.02.006.

7. Bartold PM, Lopez-Oliva I (2020) Periodontitis and rheumatoid arthritis: An update 2012-2017.

Periodontology 2000 83 (1): 189–212. doi:

10.1111/prd.12300.

8. Mikuls TR, Payne JB, Yu F et al. (2014) Periodontitis and porphyromonas gingivalis in patients with rheumatoid arthritis. Arthritis and Rheumatology 66 (5): 1090–1100.

doi: 10.1002/art.38348.

9. Carding S, Verbeke K, Vipond DT et al. (2015) Dysbiosis of the gut microbiota in disease. Microbial Ecology in Health and Disease 26 (1): 26191. doi:

10.3402/mehd.v26.26191.

10. Levy M, Kolodziejczyk AA, Thaiss CA, Elinav E (2017)

(10)

Dysbiosis and the immune system. Nature Reviews Immunology 17 (4): 219–232. doi: 10.1038/nri.2017.7.

11. Dietert R, Dietert J (2015) The microbiome and sustainable healthcare. Healthcare 3 (1): 100–129. doi:

10.3390/healthcare3010100.

12. Lamichhane S, Sen P, Dickens AM et al. (2018) Gut metabolome meets microbiome: A methodological perspective to understand the relationship between host and microbe. Methods 149 (April): 3–12. doi:

10.1016/j.ymeth.2018.04.029.

13. Lynch S V, Pedersen O (2016) The human intestinal microbiome in health and disease. New England Journal of Medicine 375 (24): 2369–2379. doi:

10.1056/NEJMra1600266.

14. Gioia C, Lucchino B, Tarsitano MG et al. (2020) Dietary habits and nutrition in rheumatoid arthritis: Can diet influence disease development and clinical manifestations? Nutrients 12 (5): 1–25. doi:

10.3390/nu12051456.

15. Sirdaarta J, Matthews B, Cock IE (2015) Kakadu plum fruit extracts inhibit growth of the bacterial triggers of rheumatoid arthritis: Identification of stilbene and tannin components. Journal of Functional Foods 17 610–620.

doi: 10.1016/j.jff.2015.06.019.

16. Li S, Liu L, He G, Wu J (2018) Molecular targets and mechanisms of bioactive peptides against metabolic syndromes. Food and Function 9 (1): 42–52. doi:

10.1039/c7fo01323j.

17. Fatchiyah F, Setiawan B, Suharjono S, Noor Z (2015) The anti-osteoporosis effects of CSN1S2 protein of goat milk and yogurt on a complete Freund’s adjuvant-induced rheumatoid arthritis model in rats. Biomarkers and Genomic Medicine 7 (4): 139–146. doi:

10.1016/j.bgm.2015.10.001.

18. Mohanty DP, Mohapatra S, Misra S, Sahu PS (2016) Milk derived bioactive peptides and their impact on human health – A review. Saudi Journal of Biological Sciences 23 (5): 577–583. doi: 10.1016/j.sjbs.2015.06.005.

19. Chotimah C, Ciptadi G, Setiawan B, Fatchiyah F (2015) CSN1S2 protein of goat milk inhibits the decrease of viability and increases the proliferation of MC3T3E1 pre- osteoblast cell in methyl glyoxal exposure. Asian Pacific Journal of Tropical Disease 5 (3): 219–223. doi:

10.1016/S2222-1808(14)60657-5.

20. Triprisila LF, Suharjono S, Christianto A, Fatchiyah F (2016) The comparing of antimicrobial activity of CSN1S2 protein of fresh milk and yoghurt goat breed ethawah inhibited the pathogenic bacteria. Mater

Sociomed 28 (4): 244–248. doi:

10.5455/msm.2016.28.244-248.

21. Rohmah RN, Widjajanto E, Fatchiyah F (2015) Protective effect of CSN1S2 protein of goat milk on ileum microstructure and inflammation in rat-CFA-induced rheumatoid arthritis. Asian Pac J Trop Dis 5 (7): 564–568.

doi: 10.1016/S2222-1808(15)60837-4.

22. Budiarti IK, Padaga M, Fatchiyah F (2013) Nutritional composition and protein profile of goat yogurt PE with double culture between Streptococcus thermophilus and Lactobacillus species. Cukurova Medical Journal 38 681–

686.

23. Hernández-Ledesma B, Del Mar Contreras M, Recio I (2011) Antihypertensive peptides: Production, bioavailability and incorporation into foods. Advances in Colloid and Interface Science 165 (1): 23–35. doi:

10.1016/j.cis.2010.11.001.

24. Yusuf F, Ilyas S, Damanik HA, Fatchiyah F (2016) Microbiota composition, HSP70 and caspase-3 expression as marker for colorectal cancer patients in Aceh, Indonesia. Acta Medica Indonesiana 48 (4): 289–

299.

25. Moraes JG de, Motta MEF de A, Beltrão MF de S et al.

(2016) Fecal microbiota and diet of children with chronic constipation. International Journal of Pediatrics 2016 1–

8. doi: 10.1155/2016/6787269.

26. Yang Z, Huang S, Zou D et al. (2016) Metabolic shifts and structural changes in the gut microbiota upon branched-chain amino acid supplementation in middle- aged mice. Amino Acids 48 (12): 2731–2745. doi:

10.1007/s00726-016-2308-y.

27. Sha S, Xu B, Wang X et al. (2013) The biodiversity and composition of the dominant fecal microbiota in patients with inflammatory bowel disease. Diagnostic Microbiology and Infectious Disease 75 (3): 245–251.

doi: 10.1016/j.diagmicrobio.2012.11.022.

28. Mufidah M, Suyanto E, Susanti V, Meidinna HN (2020) Different intestinal microbiota composition inhibits the Lactobacillus growth in rheumatoid arthritis patients in Malang, Indonesia. J Exp Life Sci 10 (2): 79–88.

29. Duytschaever G, Huys G, Bekaert M et al. (2013) Dysbiosis of bifidobacteria and Clostridium cluster XIVa in the cystic fibrosis fecal microbiota. Journal of Cystic Fibrosis 12 (3): 206–215. doi: 10.1016/j.jcf.2012.10.003.

30. Xiong X, Hu Y, Yan N et al. (2014) PCR-DGGE analysis of the microbial communities in three different chinese

“Baiyunbian” liquor fermentation starters. Journal of Microbiology and Biotechnology 24 (8): 1088–1095. doi:

10.4014/jmb.1401.01043.

31. Hong SW, Choi YJ, Lee HW et al. (2016) Microbial community structure of Korean cabbage kimchi and ingredients with denaturing gradient gel electrophoresis.

Journal of Microbiology and Biotechnology 26 (6):

1057–1062. doi: 10.4014/jmb.1512.12035.

32. Vitetta L, Coulson S, Linnane AW, Butt H (2013) The gastrointestinal microbiome and musculoskeletal diseases: A beneficial role for probiotics and prebiotics.

Pathogens 2 (4): 606–626. doi:

10.3390/pathogens2040606.

33. Merlich A, Galkin M, Choiset Y et al. (2019) Characterization of the bacteriocin produced by Enterococcus italicus ONU547 isolated from Thai fermented cabbage. Folia Microbiologica 64 (4): 535–

545. doi: 10.1007/s12223-019-00677-4.

34. Bagci U, Ozmen Togay S, Temiz A, Ay M (2019) Probiotic characteristics of bacteriocin-producing Enterococcus faecium strains isolated from human milk and colostrum. Folia Microbiologica 64 (6): 735–750.

doi: 10.1007/s12223-019-00687-2.

35. Nueno-Palop C, Narbad A (2011) Probiotic assessment of Enterococcus faecalis CP58 isolated from human gut.

International Journal of Food Microbiology 145 (2–3):

390–394. doi: 10.1016/j.ijfoodmicro.2010.12.029.

36. Lee JH, Shin D, Lee B et al. (2017) Genetic diversity and antibiotic resistance of enterococcus faecalis isolates from traditional Korean fermented soybean foods.

Journal of Microbiology and Biotechnology 27 (5): 916–

924. doi: 10.4014/jmb.1612.12033.

37. Bachtiar BM, Bachtiar EW (2017) Proinflammatory MG- 63 cells response infection with Enterococcus faecalis

(11)

cps2 evaluated by the expression of TLR-2, IL-1β, and iNOS mRNA. BMC Research Notes 10 (1): 1–6. doi:

10.1186/s13104-017-2740-4.

38. Maeda Y, Takeda K (2017) Role of gut microbiota in rheumatoid arthritis. Journal of Clinical Medicine 6 (60):

1–7. doi: 10.3390/jcm6060060.

39. Lightfield J, Fram NR, Ely B (2011) Across bacterial phyla, distantly-related genomes with similar genomic GC content have similar patterns of amino acid usage.

PLoS One 6 (3): 1–12. doi:

10.1371/journal.pone.0017677.

40. Du MZ, Zhang C, Wang H et al. (2018) The GC content as a main factor shaping the amino acid usage during bacterial evolution process. Frontiers in Microbiology 9 1–12. doi: 10.3389/fmicb.2018.02948.

41. Bohlin J, Eldholm V, Brynildsrud O et al. (2018) Modeling of the GC content of the substituted bases in bacterial core genomes. BMC Genomics 19 (1): 1–6. doi:

10.1186/s12864-018-4984-3.

42. Nakayama H, Kurokawa K, Lee BL (2012) Lipoproteins in bacteria: Structures and biosynthetic pathways. FEBS Journal 279 (23): 4247–4268. doi: 10.1111/febs.12041.

43. Kurokawa K, Ryu KH, Ichikawa R et al. (2012) Novel bacterial lipoprotein structures conserved in low-GC content gram-positive bacteria are recognized by toll-like receptor 2. Journal of Biological Chemistry 287 (16):

13170–13181. doi: 10.1074/jbc.M111.292235.

44. El Arnaout T, Soulimane T (2019) Targeting lipoprotein biogenesis: considerations towards antimicrobials.

Trends in Biochemical Sciences 44 (8): 701–715. doi:

10.1016/j.tibs.2019.03.007.

45. Donaldson GP, Lee SM, Mazmanian SK (2016) Gut biogeography of the bacterial microbiota. Nature Reviews Microbiology 14 (1): 20–32. doi:

10.1038/nrmicro3552.

46. Scher JU, Sczesnak A, Longman RS et al. (2013) Expansion of intestinal Prevotella copri correlates with enhanced susceptibility to arthritis. eLife 2 1–20. doi:

10.7554/elife.01202.

47. Lappin DF, Apatzidou D, Quirke A-M et al. (2013) Influence of periodontal disease, Porphyromonas gingivalis and cigarette smoking on systemic anti- citrullinated peptide antibody titres. Journal of Clinical Periodontology 40 (10): 907–915. doi:

10.1111/jcpe.12138.

48. Zhang X, Zhang D, Jia H et al. (2015) The oral and gut microbiomes are perturbed in rheumatoid arthritis and partly normalized after treatment. Nature Medicine 21 (8): 895–905. doi: 10.1038/nm.3914.

49. Cao J, Yu Z, Liu W et al. (2020) Probiotic characteristics of Bacillus coagulans and associated implications for human health and diseases. Journal of Functional Foods

64 (2020): 1–11. doi: 10.1016/j.jff.2019.103643.

50. Cutting SM (2011) Bacillus probiotics. Food Microbiology 28 (2): 214–220. doi:

10.1016/j.fm.2010.03.007.

51. Honda H, Gibson GR, Farmer S et al. (2011) Use of a continuous culture fermentation system to investigate the effect of GanedenBC30 (Bacillus coagulans GBI-30, 6086) supplementation on pathogen survival in the human gut microbiota. Anaerobe 17 (1): 36–42. doi:

10.1016/j.anaerobe.2010.12.006.

52. Sudha, M. R., Jayanthi, N., Aasin, M., Dhanashri, R. D., Anirudh T (2018) Efficacy of Bacillus coagulans Unique IS2 in treatment of irritable bowel syndrome in children:

a double blind, randomised placebo controlled studyle.

Beneficial Microbes 9 (4): 563–572.

53. Majeed M, Natarajan S, Sivakumar A et al. (2016) Evaluation of anti-diarrhoeal activity of Bacillus coagulans MTCC 5856 and its effect on gastrointestinal motility in Wistar rats. International Journal of Pharma and Bio Sciences 7 (1): 311–316.

54. Keller D, Verbruggen S, Cash H et al. (2019) Spores of Bacillus coagulans GBI-30, 6086 show high germination, survival and enzyme activity in a dynamic, computer- controlled in vitro model of the gastrointestinal tract.

Beneficial Microbes 10 (1): 77–87. doi:

10.3920/BM2018.0037.

55. Nyangale EP, Farmer S, Keller D et al. (2014) Effect of prebiotics on the fecal microbiota of elderly volunteers after dietary supplementation of Bacillus coagulans GBI- 30, 6086. Anaerobe 30 75–81. doi:

10.1016/j.anaerobe.2014.09.002.

56. Abhari K, Shekarforoush SS, Hosseinzadeh S et al.

(2016) The effects of orally administered Bacillus coagulans and inulin on prevention and progression of rheumatoid arthritis in rats. Food and Nutrition Research 60 (1): 1–8. doi: 10.3402/fnr.v60.30876.

57. Haldar L, Gandhi DN (2016) Effect of oral administration of Bacillus coagulans B37 and Bacillus pumilus B9 strains on fecal coliforms, Lactobacillus and Bacillus spp.

in rat animal model. Veterinary World 9 (7): 766–772.

doi: 10.14202/vetworld.2016.766-772.

58. Grobler R, Visser C, Chessa S, van Marle-Köster E (2017) Genetic polymorphism of CSN1S2 in South African dairy goat populations. South African Journal of Animal Sciences 47 (1): 72–78. doi:

10.4314/sajas.v47i1.11.

59. Santos-Marcos JA, Perez-Jimenez F, Camargo A (2019) The role of diet and intestinal microbiota in the development of metabolic syndrome. Journal of Nutritional Biochemistry 70 1–27. doi:

10.1016/j.jnutbio.2019.03.017.

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