Additional file 1 of Life-long microbiome rejuvenation improves intestinal barrier function and inflammaging in mice

Additional file 1. Fig S1. Bulk transcriptional adaptations to the microbiome rejuvenation in ileum tissue. Bulk RNA sequencing was performed on ileum tissue of 40- and 120-week-old yMB and iMB mice. A) Principal component plot. B) Genes which expression changes contributed to the observed variance attributed to timepoint or treatment model. C) Enriched functions among genes that were contributed to treatment explained variance. Fig S2. Principal component analysis for bulk RNAseq data.Canonical correlation of the relationship between the five first principal components and the particular groups of interest. “Treatment” corresponds to either iMB or yMB, “Timepoint” corresponds to the time of microbial transfer, “Reads” corresponds to a measure of library depth per sample, and “Genes” corresponds to a measure of library depth for genes present in all samples. Fig S3. Cell proportions as determined from single cell RNAseq data. A-B) Box plots of cell type proportions in epithelial cells (A) and immune cells (B) separated by treatment. iMB cell proportions are colored in blue and yMB in red. Cell proportions were calculated for each individual sample. Nonparametric t test statistics were used to compare the two treatments with corresponding p-value for each comparison. Fig S4. Antibiotic resistance gene counts do not differ among yMB and iMB. Counts of (A) total and (B) individual antibiotic resistance genes were determined in the metagenomic data from 72w and 120w samples of the yMB and iMB treatment groups. Table S1. Enriched KEGG pathways in fecal yMB and iMB metagenomes. Table S2. Enriched gene functions in bulk and single cell RNA sequencing data. The three worksheets contain (i) the legend with information on the terms and data and the enriched gene functions in (ii) bulk and (iii) single cell RNA sequencing data. Celltype = Cell type annotated for the single cell analysis. Signal = Gene down- or upregulated when compared between yMB and iMB interventition. ID = Gene ontology identification code. Description = Gene ontology description. We focused on Biological process. GeneRatio = Ratio of identified genes divided by all genes of the respective GO category. BgRatio = Ratio of the size of the geneset compared to all unique genes in entire collection. pvalue = Significance value. qvalue = FDR-adjusted p value. geneID = GeneIDs that contributed to the GO term. Count = Number of genes that contributed to the GO term. SYMBOL = Gene SYMBOL that contributed to the GO term. The table can be accessed via this permanent link: https://tinyurl.com/3az899d s. Table S3. Antibodies used for FACS analyses of isolated intestinal cells.

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Publication Details

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Figshare
Published
2025-01-01
DOI
https://doi.org/10.6084/m9.figshare.28720583
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Gut microbiota and health
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article
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article

Additional file 1 of Life-long microbiome rejuvenation improves intestinal barrier function and inflammaging in mice

Figshare
Gut microbiota and health
article

Additional file 1 of Life-long microbiome rejuvenation improves intestinal barrier function and inflammaging in mice

article en

Abstract

Additional file 1. Fig S1. Bulk transcriptional adaptations to the microbiome rejuvenation in ileum tissue. Bulk RNA sequencing was performed on ileum tissue of 40- and 120-week-old yMB and iMB mice. A) Principal component plot. B) Genes which expression changes contributed to the observed variance attributed to timepoint or treatment model. C) Enriched functions among genes that were contributed to treatment explained variance. Fig S2. Principal component analysis for bulk RNAseq data.Canonical correlation of the relationship between the five first principal components and the particular groups of interest. “Treatment” corresponds to either iMB or yMB, “Timepoint” corresponds to the time of microbial transfer, “Reads” corresponds to a measure of library depth per sample, and “Genes” corresponds to a measure of library depth for genes present in all samples. Fig S3. Cell proportions as determined from single cell RNAseq data. A-B) Box plots of cell type proportions in epithelial cells (A) and immune cells (B) separated by treatment. iMB cell proportions are colored in blue and yMB in red. Cell proportions were calculated for each individual sample. Nonparametric t test statistics were used to compare the two treatments with corresponding p-value for each comparison. Fig S4. Antibiotic resistance gene counts do not differ among yMB and iMB. Counts of (A) total and (B) individual antibiotic resistance genes were determined in the metagenomic data from 72w and 120w samples of the yMB and iMB treatment groups. Table S1. Enriched KEGG pathways in fecal yMB and iMB metagenomes. Table S2. Enriched gene functions in bulk and single cell RNA sequencing data. The three worksheets contain (i) the legend with information on the terms and data and the enriched gene functions in (ii) bulk and (iii) single cell RNA sequencing data. Celltype = Cell type annotated for the single cell analysis. Signal = Gene down- or upregulated when compared between yMB and iMB interventition. ID = Gene ontology identification code. Description = Gene ontology description. We focused on Biological process. GeneRatio = Ratio of identified genes divided by all genes of the respective GO category. BgRatio = Ratio of the size of the geneset compared to all unique genes in entire collection. pvalue = Significance value. qvalue = FDR-adjusted p value. geneID = GeneIDs that contributed to the GO term. Count = Number of genes that contributed to the GO term. SYMBOL = Gene SYMBOL that contributed to the GO term. The table can be accessed via this permanent link: https://tinyurl.com/3az899d s. Table S3. Antibodies used for FACS analyses of isolated intestinal cells.

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Universität Hamburg (DE), Christian-Albrechts-Universität zu Kiel (DE), University Medical Center Hamburg-Eppendorf (DE), University Hospital Schleswig-Holstein (DE), Universitätsmedizin Göttingen (DE), University of Lübeck (DE)
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Gut microbiota and health
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