| Literature DB >> 26302742 |
Robin Mesnage1, Matthew Arno2, Manuela Costanzo3, Manuela Malatesta3, Gilles-Eric Séralini4, Michael N Antoniou5.
Abstract
BACKGROUND: Glyphosate-based herbicides (GBH) are the major pesticides used worldwide. Converging evidence suggests that GBH, such as Roundup, pose a particular health risk to liver and kidneys although low environmentally relevant doses have not been examined. To address this issue, a 2-year study in rats administering 0.1 ppb Roundup (50 ng/L glyphosate equivalent) via drinking water (giving a daily intake of 4 ng/kg bw/day of glyphosate) was conducted. A marked increased incidence of anatomorphological and blood/urine biochemical changes was indicative of liver and kidney structure and functional pathology. In order to confirm these findings we have conducted a transcriptome microarray analysis of the liver and kidneys from these same animals.Entities:
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Year: 2015 PMID: 26302742 PMCID: PMC4549093 DOI: 10.1186/s12940-015-0056-1
Source DB: PubMed Journal: Environ Health ISSN: 1476-069X Impact factor: 5.984
Fig. 1Alterations in hepatocyte nuclear architecture in female Roundup-treated rats suggests transcriptional disturbances. Liver from control (C) and Roundup (R) treated female rats were subjected to an ultrastructural electron microscopic analysis to investigate subcellular architecture. a Quantification of morphometric analysis of hepatocytes revealing alterations in subnuclear (heterochromatin, dense fibrillar, granular) compartments indicative of a reduced transcriptional status. Morphometric parameters are represented by their mean and their standard deviation. A two-tailed unpaired t-test was used as a standard test for statistical comparisons (***, p <0.001). b Representative electron micrographs comparing hepatocytes from control (upper panel) and Roundup-treated (lower panel) rats showing a disruption of glycogen dispersion (G). N nucleus, R rough endoplasmic reticulum
Fig. 2Wide-scale transcriptome profile alteration in liver and kidneys of Roundup-treated female rats. Liver and kidneys from control rats and animals receiving 0.1 ppb Roundup (50 ng/L glyphosate equivalent dilution) in drinking water were subjected to a full transcriptome microarray analysis. a PCA analysis of transcript cluster expression profiles shows a distinct separation into groups of treated (red) and control (green) rats in both kidney and liver samples. Numbers by data points denote age at time of death in days. b Volcano plots of the liver and kidney transcriptome profiles showing the log 2 fold changes and the –log10 p-values in transcript cluster expression induced by Roundup exposure compared to controls. Data were selected at the cut off values p <0.01 and fold change >1.1. Red dots represent genes commonly disturbed between liver and kidney samples
Number of transcript clusters whose expression is disturbed at different cut-off threshold p-values
|
| Liver | Kidney | Random |
|---|---|---|---|
| 0.05 | 8606(0.21) | 8656(0.21) | 1835(0.98) |
| 0.01 | 4224(0.08) | 4447(0.08) | 380(0.96) |
| 0.001 | 1593(0.02) | 1894(0.02) | 31(0.95) |
| 0.0001 | 630(0.006) | 764(0.005) | 1(0.95) |
| 0.00001 | 230(0.002) | 219(0.002) | 0 |
The number in superscript parenthesis is the maximal q-value (calculated using Benjamini-Hochberg method according to corresponding to the number of genes found disturbed at increasing (0.05 to 0.00001) p-value stringency. A statistical analysis of simulated random samples was also performed to estimate effects that would be expected to arise by chance
Fig. 3Large spectrum of transcript cluster expression is commonly disturbed in liver and kidney by Roundup. Venn diagrams showing numbers of genes commonly disturbed in liver and kidneys as revealed by transcriptome analysis at cut off threshold values of p <0.01 and fold change >1.1 (a) and >2 (b)
Functional clustering of genes derived using the DAVID gene functional classification tool
| ES | Term in DAVID | n |
| FE |
|
|---|---|---|---|---|---|
| 4.2 | GO:0010558 ~ negative regulation of macromolecule biosynthetic process | 40 | 3.7E-05 | 2.0 | 7.9E-3 |
| GO:0031327 ~ negative regulation of cellular biosynthetic process | 40 | 6.0E-05 | 2.0 | 1.1E-2 | |
| GO:0009890 ~ negative regulation of biosynthetic process | 40 | 9.3E-05 | 1.9 | 1.6E-2 | |
| 3.8 | GO:0016279 ~ protein-lysine N-methyltransferase activity | 7 | 5.0E-05 | 9.7 | 5.1E-3 |
| GO:0016278 ~ lysine N-methyltransferase activity | 7 | 5.0E-05 | 9.7 | 5.1E-3 | |
| GO:0018024 ~ histone-lysine N-methyltransferase activity | 7 | 5.0E-05 | 9.7 | 5.1E-3 | |
| GO:0042054 ~ histone methyltransferase activity | 7 | 3.0E-04 | 7.2 | 2.3E-2 | |
| GO:0008276 ~ protein methyltransferase activity | 7 | 2.5E-03 | 5.0 | 7.7E-2 | |
| 3.3 | GO:0000377 ~ RNA splicing, via transesterification reactions with bulged adenosine as nucleophile | 15 | 4.8E-04 | 3.0 | 6.0E-2 |
| GO:0000375 ~ RNA splicing, via transesterification reactions | 15 | 4.8E-04 | 3.0 | 6.0E-2 | |
| GO:0000398 ~ nuclear mRNA splicing, via spliceosome | 15 | 4.8E-04 | 3.0 | 6.0E-2 | |
| 3.3 | IPR000504:RNA recognition motif, RNP-1 | 17 | 4.0E-04 | 2.8 | 3.1E-1 |
| SM00360:RRM | 17 | 5.1E-04 | 2.7 | 9.8E-2 | |
| IPR012677:Nucleotide-binding, alpha-beta plait | 17 | 6.1E-04 | 2.7 | 2.5E-1 | |
| 2.3 | GO:0006099 ~ tricarboxylic acid cycle | 6 | 1.7E-03 | 6.6 | 1.5E-1 |
| GO:0046356 ~ acetyl-CoA catabolic process | 6 | 2.1E-03 | 6.3 | 1.7E-1 | |
| GO:0009109 ~ coenzyme catabolic process | 6 | 3.7E-03 | 5.6 | 2.3E-1 | |
| GO:0009060 ~ aerobic respiration | 6 | 4.4E-03 | 5.4 | 2.5E-1 | |
| GO:0051187 ~ cofactor catabolic process | 6 | 8.1E-03 | 4.7 | 3.4E-1 | |
| rno00020:Citrate cycle (TCA cycle) | 6 | 9.2E-03 | 4.5 | 1.7E-1 | |
| GO:0006084 ~ acetyl-CoA metabolic process | 6 | 1.9E-02 | 3.8 | 4.7E-1 | |
| 2.2 | GO:0030964 ~ NADH dehydrogenase complex | 5 | 3.7E-03 | 7.5 | 7.1E-2 |
| GO:0045271 ~ respiratory chain complex I | 5 | 3.7E-03 | 7.5 | 7.1E-2 | |
| GO:0005747 ~ mitochondrial respiratory chain complex I | 5 | 3.7E-03 | 7.5 | 7.1E-2 | |
| GO:0005746 ~ mitochondrial respiratory chain | 5 | 4.3E-02 | 3.7 | 3.1E-1 | |
| 2.1 | GO:0016571 ~ histone methylation | 6 | 1.4E-03 | 6.9 | 1.3E-1 |
| GO:0008213 ~ protein amino acid alkylation | 6 | 1.9E-02 | 3.8 | 4.7E-1 | |
| GO:0006479 ~ protein amino acid methylation | 6 | 1.9E-02 | 3.8 | 4.7E-1 | |
| 2.1 | IPR001440:Tetratricopeptide TPR-1 | 9 | 4.5E-03 | 3.4 | 5.8E-1 |
| IPR019734:Tetratricopeptide repeat | 9 | 1.0E-02 | 2.9 | 7.2E-1 | |
| SM00028:TPR | 9 | 1.2E-02 | 2.8 | 5.7E-1 |
The rat genome was used as a background list to calculate the p-values of each term. A total of 868 genes were recognised. The p-values were calculated according to a modified Fisher’s exact test (EASE score). The q-values were calculated according to the Benjamini-Hochberg method. Cluster enrichment scores (ES) and fold enrichment (FE) rank overall importance (enrichment) of gene groups or the statistically most overrepresented (enriched) biological annotations. The highest classification stringency was used
Fig. 4Heatmaps of the three major ontologically enriched biological functions from transcriptome analysis of liver and kidneys. The ontologically enriched biological functions (Table 2) derived from the alteration in gene expression patterns commonly disturbed in liver and kidneys from Roundup treated female rats (Figs. 2 and 3) with respect relative to mRNA splicing via spliceosome (GO:0000398, in blue), histone modification (GO:0016570, in yellow) and cellular respiration and TCA cycle (GO:0045333 and GO:0006099, in pink), were grouped on organ-specific heatmaps using hierarchical clustering of samples (C, control; R, Roundup) and variables (gene symbols). A distinct separation based on direction (up- or down-regulation) of gene expression, biological function and organ between Roundup-treated and control animals is discernible
Fig. 5Toxicity ontology analysis of genes disturbed in liver and kidneys of Roundup-treated rats. List of top 10 scoring pathway and toxicity process networks revealed by MetaCore analysis of female liver and kidney transcriptome profiles receiving 0.1 ppb of Roundup in drinking water (p <0.01, fold changes >1.1). The p-values are determined by hyper-geometric calculation