Data from: Effects of fermented vegetables on the gut microbiota for prevention of cardiovascular disease
Data files
Oct 09, 2024 version files 5.07 MB
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ASV_table_dryad.xlsx
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Inflammatory_markers.csv
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README.md
Abstract
This study investigated the impact of regular consumption of fermented vegetables on inflammation and the composition of the gut microbiota in adults at increased risk for cardiovascular disease. Eighty-seven adults ages 35-64 were randomized into a Fermented Vegetable (FV) group, who consumed 100g fermented vegetables daily at least 5x/wk for eight weeks, or a Usual Diet (UD) group. Blood and stool samples were obtained before and after the intervention. Dependent samples t-tests and adjusted linear models were used for within and between group comparisons. Mean age and BMI of participants were 45 years and 30 kg/m2, and 80% were female. Bloating or gas was the most common side effect reported (19.3% FV group vs 9.4% UD group). There were no changes in C-Reactive Protein, oxidized LDL-receptor 1, angiopoietin-like protein 4, trimethylamine oxide, and lipopolysaccharide binding protein or bacterial alpha diversity between groups. Our findings indicate that consuming 100g of fermented vegetables at least five days per week for eight weeks does not change inflammatory biomarkers or microbial alpha diversity as measured by the Shannon index. It is possible that higher doses of fermented vegetables are necessary to elicit a significant response by gut bacteria.
README: Effects of Fermented Vegetables on the Gut Microbiota for Prevention of Cardiovascular Disease
Access this dataset on Dryad
This dataset includes data on amplicon sequence variants (ASVs) derived from next-generation sequencing of the V4 region of 16S rRNA isolated from human stool samples. Sequencing was performed in a pair-end modality on the Illumina MiSeq 500 platform rendering 2 x 150 bp paired-end sequences. These data were obtained from subjects who were either randomized into a fermented vegetable group, consuming 100 g of fermented vegetables on at least 5 days per week for 8 weeks, or a control group who were asked to not change anything in their diet. All subjects had at least one risk factor for cardiovascular disease and ages ranged from 35 to 60 years of age.
Description of the data and file structure
File name: ASV_table_dryad.xlsx
File description: This file contains the output from next-generation sequencing using the Illumina MiSeq platform. It contains data on microbial alpha and beta diversity, as well as amplicon sequencing variants (ASVs).
The file includes the following data:
- Column A: subject ID
- Column B: Timepoint – 1 is for baseline and 2 is for follow up (8 weeks later)
- Column C: Treatment – 1 = control and 2 = fermented vegetable
- Column D: Observed features – number of ASVs detected
- Column E: Chao1 – indicator of species richness (total number of species in a sample)
- Column F: Simpson – indicator of species evenness (proportional distribution of the number of each species in a sample)
- Columns G, H, I: Bray Curtis index PCOA plot distances
- Columns J, K, L: Jaccard index PCOA plot distances
- Columns M, N, O: Weighted unifrac PCOA plot distances
- Columns P, Q, R: Unweighted unifrac PCOA plot distances
- All other columns: Amplicon sequence variants (ASVs)
Subjects in this study collected three stool samples at baseline and three stool samples at 8 weeks, therefore, there are six rows per person.
File name: Inflammatory_markers
File description: This file contains data on inflammatory markers measured in serum collected from study participants at baseline (time point 1) and at week 8 (time point 2).
The file includes the following data:
- Column A: subject ID
- Column B: TMAO_1ngmL - Serum Trimethylamine oxide (ng/mL) at time point 1
- Column C: TMAO_2ngmL - Serum Trimethylamine oxide (ng/mL) at time point 2 (8 weeks later)
- Column D: LBP1_ngmL - Serum Lipopolysaccharide binding protein (ng/mL) at time point 1
- Column E: LBP2_ngmL - Serum Lipopolysaccharide binding protein (ng/mL) at time point 2 (8 weeks later)
- Column F: Ferr1_ngmL - Serum Ferritin (ng/mL) at time point 1
- Column G: Ferr2_ngmL - Serum Ferritin (ng/mL) at time point 2 (8 weeks later)
- Column H: CRP1_ngmL - Serum C-reactive protein (ng/mL) at time point 1
- Column I: CRP2_ngmL - Serum C-reactive protein (ng/mL) at time point 2 (8 weeks later)
- Column J: LOX1_pgmL - Serum Oxidized LDL Receptor (pg/mL) at time point 1
- Column K: LOX2_pgmL - Serum Oxidized LDL Receptor (pg/mL) at time point 2 (8 weeks later)
- Column L: Fiaf1_ngmL - Serum angiopoietin-like protein 4 at time point 1
- Column M: Fiaf2_ngmL - Serum angiopoietin-like protein 4 at time point 2 (8 weeks later)
Cells marked with a '.' indicate a missing value
Methods
Participants received stool collection kits prior to their clinic visits and were instructed to collect three stool samples on three separate days on two timepoints (week 0 and week 8). Each stool collection kit contained three flushable stool collection sheets, three DNA/RNA Shield Fecal Collection tubes (Zymo Research, Irvine, CA) one biohazard bag, and detailed instructions for stool collection. Participants were asked to record the date and time of stool collection on each tube and store the tubes at room temperature until their clinic visit appointments. The time between collection of stool samples and the clinic visits ranged between one and six days.
DNA was extracted from the frozen stool samples with the DNeasy PowerLyzer PowerSoil Kit (Qiagen, Germantown, MD, USA) per manufacturer’s protocol. A NanoDrop One (Thermo Fisher Scientific, Madison, WI, USA) was used to measure DNA concentration and diluted to 10 ng/μL. Next-generation sequencing of the V4 region of the 16S rRNA gene was performed. Amplicon PCR was performed on the V4 region of 16S rRNA using the forward (5′-GTGCCAGCMGCCGCGGTAA-3′) and reverse (5′-GACTACHVGGGTWTCTAAT-3′) primers. PCR amplicons were barcoded and pooled in equal concentrations using the SequalPrep Normalization Plate Kit (Invitrogen, Carlsbad, CA, USA). qPCR was used to quantify and consolidate libraries using the Kappa Library Quantification Kit (Roche, Indianapolis, IN, USA), and the quality of the library will be determined by an Agilent 2100 Bioanalyzer (Agilent, Santa Clara, CA, USA). Positive and negative controls were sequenced for quality control. The ZymoBIOMICS™ Microbial Community Standard (Zymo Research, Irvine, CA, USA) were used to provide a commercial community DNA for a positive control, and DNA extraction and PCR amplification provided the negative controls. Sequencing was performed in a pair-end modality on the Illumina MiSeq 500 platform rendering 2 x 150 bp paired-end sequences (Illumina, San Diego, CA, USA)). Sequencing reads after quality control were denoised using Deblur integrated with QIIME2 (2022.02 released), alignment against a 16S reference database (SILVA v132), and clustering into amplicon sequence variants (ASVs) with 100% identity threshold. A total of 515 fecal samples were extracted for DNA and processed into QIIME2 pipeline. After filtering and denoising, 484 samples were retained for microbiome analysis.
All biological samples were processed and stored at -70C until analysis. Blood was collected in two 8-mL tubes and left at room temperature for 30 minutes before centrifugation at 25C for 10 minutes at 1400 rpm. Serum was transferred to 1.5 mL cryogenic tubes in 1-mL aliquots. C-reactive protein (CRP) (RandD Systems, Minneapolis, MN - Cat#DCRP00), Angiopoetin-like protein 4 (ANGPTL4) also known as Fiaf (RandD Systems, Minneapolis, MN - Cat#DY3485), Oxidized low density lipoprotein receptor 1 (LOX-1) (RandD Systems, Minneapolis, MN – Cat#DY1798) and trimethylamine oxide (TMAO) (AFG Bioscience, Northbrook, IL - Cat#EK715704) were measured with commercial ELISA kits. Lipopolysaccharide Binding Protein (LBP) was measured by a Pierce LAL chromogenic endotoxin quantitation kit (Cat#88282, ThermoFisher Scientific, Waltham, MA). All analyses were conducted in the laboratory of Dr. Arikawa at the University of North Florida.