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182                       Xie et al. | Journal of Clinical and Translational Research 2024; 10(3): 180-190
        for 30 s, with a final extension at 72°C for 5 min. The amplified   Quantitative values are expressed as the mean ± standard deviation
        products from gallstones, bile, gallbladder mucosa, and feces   (M ± SD). Two-sample independent t-test and the Wilcoxon rank-
        samples  were  verified  by  gel  electrophoresis  with  a  1.5%   sum test were used between the two groups. For multi-group
        agarose gel, a mixture of 3 μL PCR product and 3 μL 3× loading   comparison, one-way analysis of variance and the Kruskal–Wallis
        buffer, and 3 μL 100 bp ladder marker (Yingwei Jieji Trading,   rank-sum test were used. Statistical significance was set at P < 0.05.
        China) at 100V voltage over 35 – 40 min.
          Agencourt  AMPure XP (Beijing  Huaruikang  Technology,   3. Results
        China) was used to purify the 16S V3-V4 amplicons to be free   3.1. Study population characteristics
        of primers and primer-dimer species. The second PCR reaction
        was performed  in  a  25  μL mixture  containing  5  μL 5×  GC   This study investigated  the relationship between gallstone
        buffer, 0.75 μL KAPA dNTP mix, 0.5 μL KAPA HiFi HotStart   formation  and bacteria  in the bile, gallbladder  mucosa, and
        DNA polymerase, 1.5 μL barcode F (10 pM), 1.5 μL barcode R   feces of 21 gallstone patients (eight males and 11 females; age
        (10 pM), 5 μL purified product, and 10.75 μL retinoblastoma.   range: 32 – 73 years old). From the gallstone group, we obtained
        The  purified  product  was  amplified  by  PCR  using  primers,   13 gallstone specimens (S1 – S13), nine bile specimens (Z1 –
        where the barcode is an eight-base sequence unique to each   Z9), 13 gallbladder mucosa specimens (N1 – N13), and 17 feces
        sample. Denaturation, annealing, elongation, and cycling were   specimens (F1 – F17). Meantime, we collected 20 feces (HF1
        the same as the first PCR amplification. The amplicons were   –  HF17)  samples  from  the  control  group.  We  rejected  three
        subsequently purified by AMPure XP beads to clean up the final   samples  due  to  amplification  failure;  one  from  the  gallstone
        library before quantification. Finally, purified amplicons were   specimens, one from the gallstone patients’ feces specimens, and
        pooled in equimolar and paired-end sequences (2 × 250) on an   one from the healthy subjects’ feces specimens. The average age
        Illumina MiSeq platform according to the standard protocols.  and BMI of the patients in the gallstone group were higher than
                                                               that of the control group (P = 0.004). There were no statistically
        2.4. Bioinformatics analysis of sequencing data        significant differences in gender and cholesterol levels between
                                                               the gallstone and control groups (Table 1).
          Fast length adjustment of short reads was used to merge
        paired-end  reads  from  next-generation  sequencing  [15]. Low-  3.2. Bacterial diversity of sample species under different
        quality  reads  were  filtered  by  fastq_quality_filter  (−p  90  −q   sequencing quantities and OTUs dilution curve
        25  −Q  33)  in  FASTX Toolkit  0.0.14,  and  chimera  reads  were   In this study, we identified a total of 23427 OTUs (340 ±
        removed by USEARCH 64-bit version 8.0.1517. The number of   93)  based  on  the  conventional  criterion  of  97%  sequence
        reads for each sample was normalized based on the smallest size   similarity, with 4095 OTUs in gallstones, 3065 OTUs in bile,
        of samples by random subtraction. The final optimized sequence   4687 in gallbladder mucosa, 5203 OTUs in patients’ feces, and
        was obtained to ensure the reliability of the effective sequence   6377 OTUs in normal feces. There was no significant difference
        used as operational taxonomic units (OTUs). OTUs were aligned   in the intestinal microbiota diversity based on the feces of the
        by the Uclust algorithm with a 97% identity and taxonomically   gallstone  and control groups.  There was also no statistical
        classified  using  the  Silva16S  rRNA  database  (https://www.  difference in the bacterial diversity between gallstones, bile, and
        arbsilva.de/documentation/release-128/).  From  the  levels  of   gallbladder mucosa in the gallstone group (P > 0.05). The gut
        phylum and genus, the dominant bacteria obtained by sequencing   microbiota was reportedly diverse in gallstones (P = 0.004), bile
        in each group were statistically analyzed. The α-diversity reflects a   (P = 0.045), and gallbladder mucosa (P = 0.008). In addition,
        comprehensive indicator of microbial evenness and abundance in   the gut microbiota was more diverse in the gallstone group than
        a single sample and mainly includes the abundance index Chao1,   the control group (Table 2).
        Shannon’s index, and Simpson’s index. In contrast, β-diversity   When the number of sequences increased,  the diversity
        is a comparative analysis of microbial community composition   index did not increase significantly, indicating that the number
        among different groups. Both α- and β-diversities were generated   of  sequences  was  sufficient  to  reflect  the  overall  community
        in the Quantitative Insights Into Microbial Ecology (QIIME)   structure (Figure 1). In addition, the increase in the number of
        software and  calculated based  on weighted and  unweighted   sequences did not generate new OTUs.
        Unifrac  distance  matrices  [16].  Venn diagram selects OTUs
        with a similarity level of 97% and displays the number of OTUs   Table 1. Clinical data of the gallstone and control groups
        shared by multiple groups, reflecting the similarity and overlap of   Clinical parameter  Group    P‑value
        environmental samples. The linear discriminant analysis (LDA)
        coupled with effect size measurement (LefSe) method was used                Gallstone   Control
        to identify metagenomic biomarkers that exhibited statistically   Gender (males/females)  8/13  11/9  0.278
        significant differential abundances among groups [17].  Age (years)         52.8±14.4   40.1±12.4   0.004
                                                               BMI (kg/cm )         24.4±2.4    22.8±2.1    0.032
                                                                       2
        2.5. Statistical analysis                              Cholesterol (mmol/L)  1.6±0.7     1.3±0.5    0.126
          SPSS 22, GraphPad Prism7, and QIIME were used for statistical   Notes: Gender and cholesterol were analyzed with a Chi-square test; age and BMI were
                                                                analyzed with a two-sample independent t-test.
        analysis.  The Chi-square test was used for categorical data.   Abbreviation: BMI: body mass index
                                               DOI: https://doi.org/10.36922/jctr.23.00118
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