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Page 4 of 16 Ding et al. Microbiome Res Rep 2024;3:16 https://dx.doi.org/10.20517/mrr.2023.64

HISTECH, Budapest, Hungary, Panoramic MIDI device.

Biochemical indicators measurement
Following a 10-minute centrifugation of whole blood at 3,500 g, serum samples were obtained.
Subsequently, 50 mg colon was homogenized with PBS and the supernatant was collected for further
analysis. The levels of IL-4, IFN-γ, IgE, and IgG2a in the serum and colon were assayed using ELISA kits
following the instructions [Supplementary Materials].

Quantitative real-time polymerase chain reaction analysis
Total RNA from PPs, colon, jejunum, and ileum tissue was extracted. Nanodrop was used to measure the
RNA concentration. Quantitative real-time polymerase chain reaction (qRT-PCR) was utilized for
amplification with SYBR green, and computed using the 2 -ΔΔCt technique, with β-actin serving as the internal
standard. The primer sequences were searched on NCBI and primer bank, which are listed in
Supplementary Table 1. qPCR conditions can be found in Supplementary Materials.

Analysis of 16S rRNA gene and Bifidobacterial groEL gene sequencing
The microbiota composition of fecal samples was sequenced by 16S rRNA V3-V4 region and the
bifidobacterial groEL gene, following established protocols . The amplified products were sequenced by
[24]
[25]
Illumina MiSeq (San Diego, CA, US) and raw data were filtered by DADA2 and analyzed by Qiime 2 .
PCR primers and conditions can be found in Supplementary Materials.

Western blot analysis
The Western blot procedure was carried out following a previously published method . The relative
[26]
expression of target proteins was quantified by β-actin with ImageJ software .
[27]

Statistical analyses
The results were performed as the mean ± standard error of the mean (SEM). Data of FCM was analyzed by
FlowJ (V10.06) . One-way ANOVA was used to compare the difference among groups of more than two
[28]
when the data met the criterion of normal distribution. Post hoc Tukey’s test was used to assess any
significant differences between groups. “Table.Qzv” provided the sample resampling depth [Supplementary
Materials], which is typically the minimal sample data amount or the data amount encompassing the great
majority of samples. QIIME2 computed this depth. Alpha diversity was analyzed in QIIME2. Beta diversity
was analyzed using PCoA (Principal Co-ordinates Analysis) based on the Bray-Curtis matrix conducted
using the R package (“vagan”, “ape” and “ggplot2”).

RESULTS
Effects of B. longum subsp. infantis on immune cells of mice
IF and flow cytometry were used to assess the effects of B. longum subsp. infantis on the innate immune
(CD11c-positive cells and macrophages, Supplementary Figures 2A and 3A) and adaptive immune cells (T
cells, B cells, and Th cells, Supplementary Figures 4 and 5). The results revealed that B. longum subsp.
infantis I4MI and B6MNI significantly increased the relative number of macrophages in female mice (P <
0.05, Supplementary Figure 2B). I2MI, I10TI, and B6MNI significantly increased the relative number of
CD11c-positive cells in female mice (P < 0.05, Supplementary Figure 2C), and I2MI, I4MI, I8TI, and B6MNI
significantly increased the relative number of macrophages in male mice (P < 0.05, Supplementary Figure 3B).
I2MI, I4MI, I5TI, I8TI, and B6MNI significantly increased the relative number of CD11c-positive cells in
male mice (P < 0.05, Supplementary Figure 3C). The positive peaks of T cells, B cells, and Th cells in female
and male mice were analyzed. For female mice [Figure 1A], B. longum subsp. infantis I4MI, I5TI, and I10TI
significantly increased the percentage of T cells (P < 0.05), I4MI, I10TI, and B6MNI significantly increased