Integrated Profiles of Transcriptome and mRNA m6A Modification Reveal the Intestinal Cytotoxicity of Aflatoxin B1 on HCT116 Cells
Highlights
- We investigated the cytotoxicity and potential toxicological effects of AFB1 on HCT116 cells.
- The toxicological mechanism by which AFB1 induces intestinal structural damage and dysfunction may be associated with the m6A modification of mRNA.
- Our study provides evidence that elucidates the intestinal toxic mechanism of AFB1 and the potential epigenetic regulation of mRNA via m6A modification.
Abstract
:1. Introduction
2. Materials and Methods
2.1. Chemical Reagent and Cell Culture
2.2. Cell Viability
2.3. RNA Preparation and m6A MeRIP-Seq of HCT116
2.4. Bioinformatic Analysis
2.5. Molecular Docking
2.6. Intracellular ROS Accumulation
2.7. Quantitative Real-Time PCR
2.8. Western Blotting
2.9. Statistical Analysis
3. Results
3.1. Cell Viability and ROS Accumulation
3.2. Transcriptome-Wide MeRIP-Seq Reveals m6A Modification Pattern after AFB1 Treatment of HCT116 Cells
3.3. Analysis of m6A Modification Distribution
3.4. Differentially Expressed Genes (DEGs) and Differentially Methylated Genes
3.5. Biological Pathways of DEGs and Differentially m6A-Modified mRNAs
3.6. Conservation and Disease Association of m6A-Modified Genes
3.7. Genes Expression and Their Potential m6A Regulators
3.8. Proteins Expression Levels
3.9. Potential RNA m6A Regulators of Differentially Methylated Genes
3.10. Interactions between AFB1 and m6A Regulators
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Marchese, S.; Polo, A.; Ariano, A.; Velotto, S.; Costantini, S.; Severino, L. Aflatoxin B1 and M1: Biological Properties and Their Involvement in Cancer Development. Toxins 2018, 10, 214. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ismail, A.; Gonçalves, B.L.; de Neeff, D.V.; Ponzilacqua, B.; Coppa, C.; Hintzsche, H.; Sajid, M.; Cruz, A.G.; Corassin, C.H.; Oliveira, C.A.F. Aflatoxin in foodstuffs: Occurrence and recent advances in decontamination. Food Res. Int. 2018, 113, 74–85. [Google Scholar] [CrossRef] [PubMed]
- Gruber-Dorninger, C.; Jenkins, T.; Schatzmayr, G. Global Mycotoxin Occurrence in Feed: A Ten-Year Survey. Toxins 2019, 11, 375. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rushing, B.R.; Selim, M.I. Aflatoxin B1: A review on metabolism, toxicity, occurrence in food, occupational exposure, and detoxification methods. Food. Chem. Toxicol. 2019, 124, 81–100. [Google Scholar] [CrossRef] [PubMed]
- Marin, S.; Ramos, A.J.; Cano-Sancho, G.; Sanchis, V. Mycotoxins: Occurrence, toxicology, and exposure assessment. Food. Chem. Toxicol. 2013, 60, 218–237. [Google Scholar] [CrossRef]
- Neal, G.E.; Eaton, D.L.; Judah, D.J.; Verma, A. Metabolism and toxicity of aflatoxins M1 and B1 in human-derived in vitro systems. Toxicol. Appl. Pharmacol. 1998, 151, 152–158. [Google Scholar] [CrossRef] [PubMed]
- Harrison, J.C.; Carvajal, M.; Garner, R.C. Does aflatoxin exposure in the United Kingdom constitute a cancer risk? Environ. Health Perspect. 1993, 99, 99–105. [Google Scholar] [CrossRef]
- Wu, J.M.; Gan, Z.D.; Zhuo, R.H.; Zhang, L.L.; Wang, T.; Zhong, X. Resveratrol Attenuates Aflatoxin B(1)-Induced ROS Formation and Increase of m(6)A RNA Methylation. Animals 2020, 10, 677. [Google Scholar] [CrossRef] [Green Version]
- Zhang, Y.X.; Huang, D.Y.; Wei, Z.; Chen, K.Q. Primary sequence-assisted prediction of m(6)A RNA methylation sites from Oxford nanopore direct RNA sequencing data. Methods 2022, 203, 62–69. [Google Scholar] [CrossRef]
- Xiong, X.S.; Li, X.Y.; Yi, C.Q. N(1)-methyladenosine methylome in messenger RNA and non-coding RNA. Curr. Opin. Chem. Biol. 2018, 45, 179–186. [Google Scholar] [CrossRef]
- Ma, J.J.; Song, B.W.; Wei, Z.; Huang, D.Y.; Zhang, Y.X.; Su, J.L.; de Magalhães, J.P.; Rigden, D.J.; Meng, J.; Chen, K.Q. m5C-Atlas: A comprehensive database for decoding and annotating the 5-methylcytosine (m5C) epitranscriptome. Nucleic Acids Res. 2022, 50, D196–D203. [Google Scholar] [CrossRef] [PubMed]
- Adams, J.M.; Cory, S. Modified nucleosides and bizarre 5’-termini in mouse myeloma mRNA. Nature 1975, 255, 28–33. [Google Scholar] [CrossRef] [PubMed]
- Song, B.W.; Tang, Y.J.; Chen, K.Q.; Wei, Z.; Rong, R.; Lu, Z.L.; Su, J.L.; de Magalhães, J.P.; Rigden, D.J.; Meng, J. m7GHub: Deciphering the location, regulation and pathogenesis of internal mRNA N7-methylguanosine (m7G) sites in human. Bioinformatics 2020, 36, 3528–3536. [Google Scholar] [CrossRef] [PubMed]
- Xie, S.S.; Chen, W.W.; Chen, K.H.; Chang, Y.X.; Yang, F.; Lin, A.F.; Shu, Q.; Zhou, T.H.; Yan, X.Y. Emerging roles of RNA methylation in gastrointestinal cancers. Cancer Cell Int. 2020, 20, 585. [Google Scholar] [CrossRef] [PubMed]
- Chen, Y.M.; Zhou, C.X.; Sun, Y.Y.; He, X.Z.; Xue, D. m(6)A RNA modification modulates gene expression and cancer-related pathways in clear cell renal cell carcinoma. Epigenomics 2020, 12, 87–99. [Google Scholar] [CrossRef]
- Wu, Y.J.; Chen, X.Y.; Bao, W.Q.; Hong, X.Y.; Li, C.T.; Lu, J.T.; Zhang, D.C.; Zhu, A. Effect of humantenine on mRNA m6A modification and expression in human colon cancer cell line HCT116. Genes 2022, 13, 781. [Google Scholar] [CrossRef] [PubMed]
- Paramasivam, A.; Priyadharsini, J.V. Epigenetic modifications of RNA and their implications in antiviral immunity. Epigenetics 2020, 12, 1673–1675. [Google Scholar] [CrossRef] [PubMed]
- Meyer, K.D.; Saletore, Y.; Zumbo, P.; Elemento, O.; Mason, C.E.; Jaffrey, S.R. Comprehensive analysis of mRNA methylation reveals enrichment in 3’ UTRs and near stop codons. Cell 2012, 149, 1635–1646. [Google Scholar] [CrossRef] [Green Version]
- Kim, D.; Paggi, J.M.; Park, C.; Bennett, C.; Salzberg, S.L. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat. Biotechnol. 2019, 37, 907–915. [Google Scholar] [CrossRef]
- Pertea, M.; Kim, D.; Pertea, G.M.; Leek, J.T.; Salzberg, S.L. Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown. Nat. Protoc. 2016, 11, 1650–1667. [Google Scholar] [CrossRef]
- Love, M.I.; Huber, W.; Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014, 15, 550. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Meng, J.; Cui, X.D.; Rao, M.K.; Chen, Y.D.; Huang, Y.F. Exome-based analysis for RNA epigenome sequencing data. Bioinformatics 2013, 29, 1565–1567. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Tang, Y.J.; Chen, K.Q.; Song, B.W.; Ma, J.M.; Wu, X.Y.; Xu, Q.R.; Wei, Z.; Su, J.L.; Liu, G.; Rong, R.; et al. m6A-Atlas: A comprehensive knowledgebase for unraveling the N6-methyladenosine (m6A) epitranscriptome. Nucleic Acids Res. 2021, 49, D134–D143. [Google Scholar] [CrossRef] [PubMed]
- Bailey, T.L. STREME: Accurate and versatile sequence motif discovery. Bioinformatics 2021, 37, 2834–2840. [Google Scholar] [CrossRef]
- Wang, Y.; Chen, K.Q.; Wei, Z.; Coenen, F.; Su, J.; Meng, J. MetaTX: Deciphering the distribution of mRNA-related features in the presence of isoform ambiguity, with applications in epitranscriptome analysis. Bioinformatics 2021, 37, 1285–1291. [Google Scholar] [CrossRef]
- Song, B.W.; Huang, D.Y.; Zhang, Y.X.; Wei, Z.; Su, J.L.; Pedro de Magalhães, J.; Rigden, D.J.; Meng, J.; Chen, K.Q. m6A-TSHub: Unveiling the Context-specific m(6)A Methylation and m6A-affecting Mutations in 23 Human Tissues. Genom. Proteom. Bioinf. 2022, S1672-0229, 00114-0. [Google Scholar] [CrossRef]
- Jiao, X.L.; Sherman, B.T.; da Huang, W.; Stephens, R.; Baseler, M.W.; Lane, H.C.; Lempicki, R.A. DAVID-WS: A stateful web service to facilitate gene/protein list analysis. Bioinformatics 2012, 28, 1805–1806. [Google Scholar] [CrossRef] [Green Version]
- Song, B.W.; Chen, K.Q.; Tang, Y.J.; Wei, Z.; Su, J.L.; de Magalhães, J.P.; Rigden, D.J.; Meng, J. ConsRM: Collection and large-scale prediction of the evolutionarily conserved RNA methylation sites, with implications for the functional epitranscriptome. Brief. Bioinform. 2021, 22, bbab088. [Google Scholar] [CrossRef]
- Song, B.W.; Wang, X.; Liang, Z.M.; Ma, J.M.; Huang, D.Y.; Wang, Y.; de Magalhães, J.P.; Rigden, D.J.; Meng, J.; Liu, G.; et al. RMDisease V2.0: An updated database of genetic variants that affect RNA modifications with disease and trait implication. Nucleic Acids Res. 2022, gkac750. [Google Scholar] [CrossRef]
- Li, J.H.; Liu, S.; Zhou, H.; Qu, L.H.; Yang, J.H. starBase v2.0: Decoding miRNA-ceRNA, miRNA-ncRNA and protein-RNA interaction networks from large-scale CLIP-Seq data. Nucleic Acids Res. 2014, 42, D92–D97. [Google Scholar] [CrossRef]
- Jumper, J.; Evans, R.; Pritzel, A.; Green, T.; Figurnov, M.; Ronneberger, O.; Tunyasuvunakool, K.; Bates, R.; Žídek, A.; Potapenko, A.; et al. Highly accurate protein structure prediction with AlphaFold. Nature 2021, 596, 583–589. [Google Scholar] [CrossRef] [PubMed]
- Gao, H.; Zhang, L.; Zhu, A.; Liu, X.Y.; Wang, T.X.; Wan, M.Q.; Yang, X.W.; Zhang, Y.T.; Zhang, Y.B. Metabolic Profiling of Nuciferine In Vivo and In Vitro. J. Agr. Food Chem. 2020, 68, 14135–14147. [Google Scholar] [CrossRef] [PubMed]
- Sun, Y.Q.; Zhang, X.; Shen, X.F.; Wang, S.; Wang, Q.; Yang, X.W. Computational and experimental characterization of isomers of escin-induced renal cytotoxicity by inhibiting heat shock proteins. Eur. J. Pharmacol. 2021, 908, 174372. [Google Scholar] [CrossRef] [PubMed]
- Zhu, A.; Sun, Y.Q.; Zhong, Q.W.; Yang, J.L.; Zhang, T.; Zhao, J.W.; Wang, Q. Effect of euphorbia factor L1 on oxidative stress, apoptosis, and autophagy in human gastric epithelial cells. Phytomedicine 2019, 64, 152929. [Google Scholar] [CrossRef]
- Dominissini, D.; Moshitch-Moshkovitz, S.; Schwartz, S.; Salmon-Divon, M.; Ungar, L.; Osenberg, S.; Cesarkas, K.; Jacob-Hirsch, J.; Amariglio, N.; Kupiec, M.; et al. Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq. Nature 2012, 485, 201–206. [Google Scholar] [CrossRef]
- Wu, C.Q.; Gao, Y.N.; Li, S.L.; Huang, X.; Bao, X.Y.; Wang, J.Q.; Zheng, N. Modulation of intestinal epithelial permeability and mucin mRNA (MUC2, MUC5AC, and MUC5B) expression and protein secretion in Caco-2/HT29-MTX co-cultures exposed to aflatoxin M1, ochratoxin A, and zearalenone individually or collectively. Toxicol. Lett. 2019, 309, 1–9. [Google Scholar] [CrossRef]
- Akbari, P.; Braber, S.; Varasteh, S.; Alizadeh, A.; Garssen, J.; Fink-Gremmels, J. The intestinal barrier as an emerging target in the toxicological assessment of mycotoxins. Arch. Toxicol. 2017, 91, 1007–1029. [Google Scholar] [CrossRef] [Green Version]
- Wang, W.J.; Xu, Z.L.; Yu, C.; Xu, X.H. Effects of aflatoxin B1 on mitochondrial respiration, ROS generation and apoptosis in broiler cardiomyocytes. Anim. Sci. J. 2017, 88, 1561–1568. [Google Scholar] [CrossRef]
- Yuan, S.B.; Wu, B.Y.; Yu, Z.Q.; Fang, J.; Liang, N.; Zhou, M.Q.; Huang, C.; Peng, X. The mitochondrial and endoplasmic reticulum pathways involved in the apoptosis of bursa of Fabricius cells in broilers exposed to dietary aflatoxin B1. Oncotarget 2016, 7, 65295–65306. [Google Scholar] [CrossRef] [Green Version]
- Paschen, W.; Frandsen, A. Endoplasmic reticulum dysfunction--a common denominator for cell injury in acute and degenerative diseases of the brain? J. Neurochem. 2001, 79, 719–725. [Google Scholar] [CrossRef]
- Niwa, M. A cell cycle checkpoint for the endoplasmic reticulum. BBA Mol. Cell Res. 2020, 1867, 118825. [Google Scholar] [CrossRef] [PubMed]
- Yin, H.; Jiang, M.; Peng, X.; Cui, H.M.; Zhou, Y.; He, M.; Zuo, Z.C.; Ouyang, P.; Fan, J.; Fang, J. The molecular mechanism of G2M cell cycle arrest induced by AFB1 in the jejunum. Oncotarget 2016, 7, 35592–35606. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Li, H.; Guan, K.; Zuo, Z.C.; Wang, F.Y.; Peng, X.; Fang, J.; Cui, H.M.; Zhou, Y.; Ouyang, P.; Su, G.; et al. Effects of aflatoxin B(1) on the cell cycle distribution of splenocytes in chickens. J. Toxicol. Pathol. 2019, 32, 27–36. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Liu, Y.; Du, M.; Zhang, G.Y. Proapoptotic activity of aflatoxin B(1) and sterigmatocystin in HepG2 cells. Toxicol. Rep. 2014, 1, 1076–1086. [Google Scholar] [CrossRef] [Green Version]
- Bravo-Sagua, R.; Rodriguez, A.E.; Kuzmicic, J.; Gutierrez, T.; Lopez-Crisosto, C.; Quiroga, C.; Díaz-Elizondo, J.; Chiong, M.; Gillette, T.G.; Rothermel, B.A.; et al. Cell death and survival through the endoplasmic reticulum-mitochondrial axis. Curr. Mol. Med. 2013, 13, 317–329. [Google Scholar] [CrossRef]
- Dlamini, M.B.; Gao, Z.Y.; Hasenbilige; Jiang, L.; Geng, C.Y.; Li, Q.J.; Shi, X.X.; Liu, Y.; Cao, J. The crosstalk between mitochondrial dysfunction and endoplasmic reticulum stress promoted ATF4-mediated mitophagy induced by hexavalent chromium. Environ. Toxicol. 2021, 36, 1162–1172. [Google Scholar] [CrossRef] [PubMed]
- Liu, H.; Wang, Z.; Nowicki, M.J. Caspase-12 mediates carbon tetrachloride-induced hepatocyte apoptosis in mice. World J. Gastroenterol. 2014, 20, 18189–18198. [Google Scholar] [CrossRef]
- Wu, R.F.; Jiang, D.H.; Wang, Y.Z.; Wang, X.X. N (6)-Methyladenosine (m(6)A) Methylation in mRNA with A Dynamic and Reversible Epigenetic Modification. Mol. Biotechnol. 2016, 58, 450–459. [Google Scholar] [CrossRef]
- Huang, D.Y.; Chen, K.Q.; Song, B.W.; Wei, Z.; Su, J.L.; Coenen, F.; de Magalhães, J.P.; Rigden, D.J.; Meng, J. Geographic encoding of transcripts enabled high-accuracy and isoform-aware deep learning of RNA methylation. Nucleic Acids Res. 2022, 50, 10290–10310. [Google Scholar] [CrossRef]
- Zhang, Y.X.; Jiang, J.; Ma, J.M.; Wei, Z.; Wang, Y.; Song, B.W.; Meng, J.; Jia, G.F.; de Magalhães, J.P.; Rigden, D.J.; et al. DirectRMDB: A database of post-transcriptional RNA modifications unveiled from direct RNA sequencing technology. Nucleic Acids Res. 2022, gkac1061. [Google Scholar] [CrossRef]
- Vermeulen, K.; Berneman, Z.N.; Van Bockstaele, D.R. Cell cycle and apoptosis. Cell Prolif. 2003, 36, 165–175. [Google Scholar] [CrossRef] [PubMed]
- Zhang, H.; Zhang, X.; Li, X.; Meng, W.B.; Bai, Z.T.; Rui, S.Z.; Wang, Z.F.; Zhou, W.C.; Jin, X.D. Effect of CCNB1 silencing on cell cycle, senescence, and apoptosis through the p53 signaling pathway in pancreatic cancer. J. Cell. Physiol. 2018, 234, 619–631. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kruse, R.; Vind, B.F.; Petersson, S.J.; Kristensen, J.M.; Højlund, K. Markers of autophagy are adapted to hyperglycaemia in skeletal muscle in type 2 diabetes. Diabetologia 2015, 58, 2087–2095. [Google Scholar] [CrossRef]
- Le Grand, J.N.; Chakrama, F.Z.; Seguin-Py, S.; Fraichard, A.; Delage-Mourroux, R.; Jouvenot, M.; Boyer-Guittaut, M. GABARAPL1 (GEC1): Original or copycat? Autophagy 2011, 7, 1098–1107. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mizushima, N.; Yoshimori, T. How to interpret LC3 immunoblotting. Autophagy 2007, 3, 542–545. [Google Scholar] [CrossRef]
- Guzel, E.; Basar, M.; Ocak, N.; Arici, A.; Kayisli, U.A. Bidirectional interaction between unfolded-protein-response key protein HSPA5 and estrogen signaling in human endometrium. Biol. Reprod. 2011, 85, 121–127. [Google Scholar] [CrossRef] [Green Version]
- Li, P.P.; Zhang, M.H.; Zou, Y.; Sun, Z.L.; Sun, C.; Geng, Z.M.; Xu, W.M.; Wang, D.Y. Interaction of heat shock protein 90 B1 (Hsp90B1) with liposome reveals its potential role in protection the integrity of lipid membranes. Int. J. Biol. Macromol. 2018, 106, 1250–1257. [Google Scholar] [CrossRef]
Gene | log2 Fold Change | p adj | Writer | Reader | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|
VIRMA | METTL5 | RBM15B | ZC3H13 | IGF2BP3 | YTHDF3 | YTHDC1 | YTHDC2 | ||||
Cell cycle | MYC | −0.4058 | 4.49 × 10−7 | N | N | Y | N | Y | Y | Y | Y |
CCNB1 | −0.3427 | 5.27 × 10−5 | N | N | Y | N | Y | Y | Y | N | |
CDC25C | −0.6666 | 5.73 × 10−4 | N | N | Y | N | N | N | Y | N | |
ATM | −0.2175 | 4.34 × 10−2 | N | N | Y | N | Y | Y | Y | N | |
CHEK2 | −0.2822 | 1.36 × 10−1 | N | N | Y | N | N | N | Y | N | |
Protein processing in ER | PDIA3 | −0.4593 | 1.74 × 10−11 | N | N | Y | N | Y | N | Y | Y |
HSPA5 | −0.3711 | 1.57 × 10−7 | N | N | Y | N | Y | Y | Y | Y | |
P4HB | −0.2804 | 2.17 × 10−7 | N | N | Y | N | Y | Y | Y | Y | |
HSP90B1 | −0.2779 | 4.57 × 10−3 | N | N | Y | N | Y | Y | Y | Y | |
CANX | −0.2316 | 6.81 × 10−2 | N | N | N | N | N | N | N | N | |
Tight junction | MYH9 | 0.5887 | 6.34 × 10−15 | N | N | Y | N | Y | Y | Y | Y |
ACTB | 0.3106 | 6.87 × 10−9 | N | N | Y | N | Y | Y | Y | Y | |
ACTG1 | 0.3115 | 4.92 × 10−7 | N | N | Y | N | Y | Y | Y | Y | |
ACTR2 | 0.2744 | 2.34 × 10−2 | N | N | Y | N | Y | Y | Y | Y | |
SRC | 0.2087 | 6.32 × 10−2 | N | N | Y | N | Y | Y | Y | Y | |
Mitophagy-animal | BECN1 | 0.4214 | 1.08 × 10−8 | N | N | Y | N | Y | N | Y | N |
MFN2 | 0.2190 | 7.00 × 10−4 | N | N | Y | N | Y | Y | Y | Y | |
GABARAPL1 | 0.1765 | 9.41 × 10−3 | N | N | Y | N | Y | N | Y | N | |
MAP1LC3B | 0.1570 | 3.93 × 10−2 | N | N | Y | N | Y | Y | Y | N | |
SQSTM1 | 0.1098 | 7.02 × 10−2 | N | N | N | N | N | N | N | N |
Protein | PDB ID | Total Score | Crash | Polar | H-Bond Number | Residues Involved in H-Bond Formation | Hydrophobic Contacts Number | Residues Involved in Hydrophobic Contacts |
---|---|---|---|---|---|---|---|---|
VIRMA | 7VF5 | 6.8256 | −0.4059 | 4.9085 | 3 | Lys709, Arg1007 (2 Hydrogen bonds) | 7 | Ser862, Asp864, Ser861, His814, Ser863, Asp1056, Ser1055 |
IGF2BP3 | 6FQR | 5.527 | −0.7161 | 2.0492 | 1 | Lys3 | 6 | Phe41, Ser73, Tyr39, Lys36, Leu34, Gln143 |
METTL5 | 6H2V | 5.6646 | −1.2471 | 2.1114 | 2 | Lys132, Thr137 | 7 | Pg0302, Thr131, Gln14, Glu10, Leu25, Leu26, Ile82 |
RBM15B | Predicted by AlphaFold | 5.2143 | −1.1279 | 2.3631 | 2 | Lys729, Arg819 | 6 | Tyr827, Phe733, Leu824, Asn823, Leu728, Ser731 |
YTHDF3 | Predicted by AlphaFold | 5.3677 | −0.9188 | 2.2975 | 1 | Lys498 | 4 | Thr441, Glu442, Trp497, Lys496 |
YTHDC1 | 6SZT | 6.123 | −1.5099 | 2.2817 | 2 | Trp377, Asn383 | 12 | Ser378, Asn363, Leu430, Trp428, Met434, Asn367, Pro431, Lys361, Leu380, Ile360, Asp476, Thr379 |
YTHDC2 | 6K6U | 6.4879 | −1.0525 | 1.4697 | 1 | Lys1370 | 8 | Ser1349, Ser1328, Glu1372, Arg1347, Arg1347, Glu1372, Ser1349, Phe1324 |
ZC3H13 | 7VF2 | 4.1247 | −0.6071 | 0.8869 | 1 | Ser1583 | 4 | Leu1576, Leu1575, Leu1528, Glu1579 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Wu, Y.; Bao, W.; Ren, J.; Li, C.; Chen, M.; Zhang, D.; Zhu, A. Integrated Profiles of Transcriptome and mRNA m6A Modification Reveal the Intestinal Cytotoxicity of Aflatoxin B1 on HCT116 Cells. Genes 2023, 14, 79. https://doi.org/10.3390/genes14010079
Wu Y, Bao W, Ren J, Li C, Chen M, Zhang D, Zhu A. Integrated Profiles of Transcriptome and mRNA m6A Modification Reveal the Intestinal Cytotoxicity of Aflatoxin B1 on HCT116 Cells. Genes. 2023; 14(1):79. https://doi.org/10.3390/genes14010079
Chicago/Turabian StyleWu, Yajiao, Wenqiang Bao, Jinjin Ren, Chutao Li, Mengting Chen, Dongcheng Zhang, and An Zhu. 2023. "Integrated Profiles of Transcriptome and mRNA m6A Modification Reveal the Intestinal Cytotoxicity of Aflatoxin B1 on HCT116 Cells" Genes 14, no. 1: 79. https://doi.org/10.3390/genes14010079
APA StyleWu, Y., Bao, W., Ren, J., Li, C., Chen, M., Zhang, D., & Zhu, A. (2023). Integrated Profiles of Transcriptome and mRNA m6A Modification Reveal the Intestinal Cytotoxicity of Aflatoxin B1 on HCT116 Cells. Genes, 14(1), 79. https://doi.org/10.3390/genes14010079