DOI: 10.5061/dryad.tmpg4f55w
title: Dietary vitamin A modifies the gut microbiota and intestinal tissue transcriptome, impacting intestinal permeability and the release of inflammatory factors, thereby influencing Aβ pathology

description: This study aimed to investigate how dietary vitamin A affects the gut
 microbiota and intestinal tissue, influencing intestinal permeability,
 inflammatory factors, and Aβ pathology. The APP/PS1-AD mouse model was
 used, and mice were fed different vitamin A diets for 12 weeks. The groups
 included vitamin A-deficient (VAD), normal vitamin A (VAN), and vitamin
 A-supplemented (VAS). No significant changes in food intake and body
 weight were observed among the groups. However, the VAD and VAS groups
 showed reduced food intake compared to the VAN group at various time
 points. In terms of cognitive function, the VAN group performed better in
 the Morris Water Maze Test, indicating superior learning and memory
 abilities. The VAD and VAS groups exhibited impaired performance, with the
 VAS group performing relatively better than the VAD group. Serum vitamin A
 concentrations differed significantly among the groups, with the VAS group
 having the highest concentration. Aβ levels were significantly higher in
 the VAD group compared to both the VAN and VAS groups. Microbial analysis
 revealed that the VAS and VAN groups had higher microbial diversity than
 the VAD group, with specific taxa characterizing each group. The VAN group
 was characterized by taxa such as Actinohacteriota and
 Desulfovibrionaceae, while the VAD group was characterized by
 Parabacteroides and Tannerellaceae. The VAS group showed similarities with
 both VAN and VAD groups, with taxa like Desulfobacterota and
 Desulfovibrionaceae being present. The VAD vs. VAS, VAD vs. VAN,
 and VAS vs. VAN comparisons identified 571, 313, and 243 differentially
 expressed genes, respectively, which associated with cellular and
 metabolic processes, and pathway analysis revealed enrichment in pathways
 related to chemical carcinogenesis, drug metabolism, glutathione
 metabolism, and immune-related processes. The VAD group exhibited higher
 levels of D-lactate, diamine oxidase, and inflammatory cytokines (TNF-α,
 IL-1β, IL-6) compared to the VAN and VAS groups. In conclusion, dietary
 vitamin A modulates the gut microbiota, intestinal permeability,
 inflammatory factors, and Aβ protein formation, providing insights into AD
 and potential therapeutic avenues for further investigation.
description: <strong>Experimental design and collection of small
 intestine tissue samples：</strong> In this study,
 we utilized thirty male APP/PS1 mice (4 weeks old) and randomly allocated
 them into three groups based on their body weight: VAD, VAN, and VAS
 groups. The mice were fed with AIN93G diet supplemented with varying
 levels of vitamin A: 0 IU/g (VAD group), 4 IU/g (VAN group), or 15 IU/g
 (VAS group). Following a 12-week experimental period, the mice underwent a
 12-hour fasting period, followed by intraperitoneal injection of sodium
 pentobarbital for anesthesia, and subsequent blood collection from the
 eyeballs. Subsequently, the mice were euthanized, and intestinal tissues
 were collected. A 10-centimeter segment from the upper part of the small
 intestine was isolated and washed with PBS. These tissues were promptly
 frozen in liquid nitrogen and stored at -80°C for subsequent RNA
 sequencing and transcriptome analysis.
 <strong>Experimental procedure for transcriptome sequencing
 analysis:</strong> 1.The workflow of mRNA
 sequencing includes sample preparation, library construction, library
 quality control and sequencing. 1.1 RNA Quality
 Assessment Purity, concentration and integrity of RNA
 sample were examined by NanoDrop, Qubit 2.0, Agilent 2100, etc. Only RNA
 with good quality could move on to following procedures.
 1.2 Library Construction Qualified RNA were
 processed for library construction. The procedures are described as
 follow: (1) mRNA was isolated by Oligo(dT)-attached
 magnetic beads. (2) mRNA was then randomly fragmented
 in fragmentation buffer. (3) First-strand cDNA was
 synthesized with fragmented mRNA as template and random hexamers as
 primers, followed by second-strand synthesis with addition of PCR buffer,
 dNTPs, RNase H and DNA polymerase I. Purification of cDNA was processed
 with AMPure XP beads. (4) Double-strand cDNA was
 subjected to end repair. Adenosine was added to the end and ligated to
 adapters. AMPure XP beads were applied here to select fragments within
 size range of 300-400 bp. (5) cDNA library was obtained
 by certain rounds of PCR on cDNA fragments generated from step
 4. 1.3 Library Quality Control In
 order to ensure the quality of library, Qubit 2.0 and Agilent 2100 were
 used to examine the concentration of cDNA and insert size. Q-PCR was
 processed to obtain a more accurate library concentration. Library with
 concentration larger than 2 nM is acceptable. 1.4
 Sequencing The qualified library was pooled based on
 pre-designed target data volume and then sequenced on Illumina sequencing
 platform. 2. Clean data with high quality was obtained
 by filtering Raw data, which removes adapter sequence and reads with low
 quality. These clean data were further mapped to pre-defined reference
 genome generating mapped data. Assessment on insert size and sequencing
 randomness were processed on mapped data as library quality control. Basic
 analysis on mapped data included gene expression quantification,
 alternative splicing analysis, novel genes prediction and genes structure
 optimization. 3. Data Quality Control
 Based on sequencing-by-synthesis (Sequencing By Synthesis, SBS)
 technology, cDNA libraries were sequenced on Illumina high-throughput
 platform, generating significant amounts of high-quality data known as raw
 data. Raw data was saved in FASTQ format. Each sample has two FASTQ file,
 containing cDNA reads measured at both ends respectively.
 4.Sequencing Quality Control It is crucial to
 ensure the quality of the reads before moving onto following analysis. Raw
 data contains useless data such as primers, adapters, etc., which need to
 be removed before analysis. Procedures for data quality control were
 listed as follow: (1) Trim adapter
 contaminations (2) Remove nucleotides with low
 Quality-score. Data processed by above steps is named
 "Clean data". Clean data was provided in FASTQ format.
description: In our uploaded database, each sample has two FASTQ files. The
 corresponding group samples grouped into VAD, VAN, and VAS group names for
 the FASTQ files are as follows: **VAD Group:** \- VAD1
 (Unknown_BL563-01T0001) \- VAD2 (Unknown_BL563-01T0002) \- VAD3
 (Unknown_BL563-01T0003) \- VAD4 (Unknown_BL563-01T0004) \- VAD5
 (Unknown_BL563-01T0005) \- VAD6 (Unknown_BL563-01T0006) \- VAD7
 (Unknown_BL563-01T0007) \- VAD8 (Unknown_BL563-01T0008) \- VAD9
 (Unknown_BL563-01T0009) \- VAD10 (Unknown_BL563-01T0010) **VAN Group:** \-
 VAN1 (Unknown_BL563-01T0011) \- VAN2 (Unknown_BL563-01T0012) \- VAN3
 (Unknown_BL563-01T0013) \- VAN4 (Unknown_BL563-01T0014) \- VAN5
 (Unknown_BL563-01T0015) \- VAN6 (Unknown_BL563-01T0016) \- VAN7
 (Unknown_BL563-01T0017) \- VAN8 (Unknown_BL563-01T0018) \- VAN9
 (Unknown_BL563-01T0019) \- VAN10 (Unknown_BL563-01T0020) **VAS Group:** \-
 VAS1 (Unknown_BL563-01T0021) \- VAS2 (Unknown_BL563-01T0022) \- VAS3
 (Unknown_BL563-01T0023) \- VAS4 (Unknown_BL563-01T0024) \- VAS5
 (Unknown_BL563-01T0025) \- VAS6 (Unknown_BL563-01T0026) \- VAS7
 (Unknown_BL563-01T0027) \- VAS8 (Unknown_BL563-01T0028) \- VAS9
 (Unknown_BL563-01T0029) \- VAS10 (Unknown_BL563-01T0030) Note: A FASTQ
 file normally contains four lines: The first line begins with @ and is
 followed by sequence ID and an optional description. The second line is a
 series of single letters representing sequence. The third line begins with
 + and optional description. The last line is the corresponding quality
 value of the bases in the second line. The length of this line should be
 exactly the same as Line 2. Base quality score is calculated as ASCII-33.