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Integrating microbiome, transcriptome and metabolome data to investigate gastric disease pathogenesis: a concise review

Published online by Cambridge University Press:  16 August 2021

Dalla Doohan
Affiliation:
Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia
Yudith Annisa Ayu Rezkitha
Affiliation:
Faculty of Medicine, University of Muhammadiyah Surabaya, Surabaya, Indonesia
Langgeng Agung Waskito
Affiliation:
Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia
Ratha-korn Vilaichone
Affiliation:
Gastroenterology Unit, Department of Medicine, Thammasat University Hospital, Pathum Thani, Thailand
Yoshio Yamaoka*
Affiliation:
Department of Environmental and Preventive Medicine, Faculty of Medicine, Oita University, Yufu, Japan Division of Gastroentero-Hepatology, Department of Internal Medicine, Faculty of Medicine, Dr Soetomo Teaching Hospital, Universitas Airlangga, Surabaya, Indonesia
Muhammad Miftahussurur*
Affiliation:
Division of Gastroentero-Hepatology, Department of Internal Medicine, Faculty of Medicine, Dr Soetomo Teaching Hospital, Universitas Airlangga, Surabaya, Indonesia Institute of Tropical Disease, Universitas Airlangga, Surabaya, Indonesia
*
Authors for correspondence: Muhammad Miftahussurur, E-mail: muhammad-m@fk.unair.ac.id; Yoshio Yamaoka, E-mail: yyamaoka@oita-u.ac.jp
Authors for correspondence: Muhammad Miftahussurur, E-mail: muhammad-m@fk.unair.ac.id; Yoshio Yamaoka, E-mail: yyamaoka@oita-u.ac.jp

Abstract

Microbiome, the study of microbial communities in specific environments, has developed significantly since the Human Microbiome Project began. Microbiomes have been associated with changes within environmental niches and the development of various diseases. The development of high-throughput technology such as next-generation sequencing has also allowed us to perform transcriptome studies, which provide accurate functional profiling data. Metabolome studies, which analyse the metabolites found in the environment, are the most direct environmental condition indicator. Although each dataset provides valuable information on its own, the integration of multiple datasets provides a deeper understanding of the relationship between the host, agent and environment. Therefore, network analysis using multiple datasets might give a clearer understanding of disease pathogenesis.

Type
Review
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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References

Qin, J et al. (2010) A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464, 5965.CrossRefGoogle ScholarPubMed
Eloe-Fadrosh, EA and Rasko, DA (2013) The human microbiome: from symbiosis to pathogenesis. Annual Review of Medicine 64, 145163.10.1146/annurev-med-010312-133513CrossRefGoogle ScholarPubMed
Nardone, G and Compare, D (2015) The human gastric microbiota: is it time to rethink the pathogenesis of stomach diseases? United European Gastroenterology Journal 3, 255260.10.1177/2050640614566846CrossRefGoogle ScholarPubMed
Petra, CV, Rus, A and Dumitraşcu, DL (2017) Gastric microbiota: tracing the culprit. Clujul Medical (1957) 90, 369376.Google ScholarPubMed
Warren, J and Marshall, B (1983) Unidentified curved bacilli on gastric epithelium in active chronic gastritis. Lancet (London, England) 1(8336), 12731275.Google ScholarPubMed
Marshall, B and Warren, J (1984) Unidentified curved bacilli in the stomach of patients with gastritis and peptic ulceration. Lancet (London, England) 1(8390), 13111315.10.1016/S0140-6736(84)91816-6CrossRefGoogle ScholarPubMed
Ayazi, S et al. (2009) Measurement of gastric pH in ambulatory esophageal pH monitoring. Surgical Endoscopy 23, 19681973.10.1007/s00464-008-0218-0CrossRefGoogle ScholarPubMed
McLauchlan, G et al. (1989) Comparison of gastric body and antral pH: a 24 hour ambulatory study in healthy volunteers. Gut 30, 573578.CrossRefGoogle ScholarPubMed
Berg, RD (1996) The indigenous gastrointestinal microflora. Trends in Microbiology 4, 430435.10.1016/0966-842X(96)10057-3CrossRefGoogle ScholarPubMed
Sekirov, I et al. (2010) Gut microbiota in health and disease. Physiological Reviews 90, 859904.10.1152/physrev.00045.2009CrossRefGoogle ScholarPubMed
O'Hara, AM and Shanahan, F (2006) The gut flora as a forgotten organ. EMBO Reports 7, 688693.10.1038/sj.embor.7400731CrossRefGoogle ScholarPubMed
Sanduleanu, S et al. (2001) Non-Helicobacter pylori bacterial flora during acid-suppressive therapy: differential findings in gastric juice and gastric mucosa. Alimentary Pharmacology & Therapeutics 15, 379388.10.1046/j.1365-2036.2001.00888.xCrossRefGoogle ScholarPubMed
Ryan, KA et al. (2008) Isolation of lactobacilli with probiotic properties from the human stomach. Letters in Applied Microbiology 47, 269274.10.1111/j.1472-765X.2008.02416.xCrossRefGoogle ScholarPubMed
Khosravi, Y et al. (2014) Culturable bacterial microbiota of the stomach of Helicobacter pylori positive and negative gastric disease patients. The Scientific World Journal 2014, 610421.CrossRefGoogle ScholarPubMed
Peterson, J et al. (2009) The NIH human microbiome project. Genome Research 19, 23172323.Google ScholarPubMed
Osman, MA et al. (2018) 16S rRNA gene sequencing for deciphering the colorectal cancer gut microbiome: current protocols and workflows. Frontiers in Microbiology 9, 767.10.3389/fmicb.2018.00767CrossRefGoogle ScholarPubMed
Bharti, R and Grimm, DG (2021) Current challenges and best-practice protocols for microbiome analysis. Briefings in Bioinformatics 22, 178193.10.1093/bib/bbz155CrossRefGoogle ScholarPubMed
Miftahussurur, M et al. (2020) Gastric microbiota and Helicobacter pylori in Indonesian population. Helicobacter 25, e12695.10.1111/hel.12695CrossRefGoogle ScholarPubMed
Ferreira, RM et al. (2018) Gastric microbial community profiling reveals a dysbiotic cancer-associated microbiota. Gut 67, 226236.CrossRefGoogle ScholarPubMed
Leiva-Gea, I et al. (2018) Gut microbiota differs in composition and functionality between children with type 1 diabetes and MODY2 and healthy control subjects: a case-control study. Diabetes Care 41, 23852395.10.2337/dc18-0253CrossRefGoogle ScholarPubMed
Jo, HJ et al. (2016) Analysis of gastric microbiota by pyrosequencing: minor role of bacteria other than Helicobacter pylori in the gastric carcinogenesis. Helicobacter 21, 364374.10.1111/hel.12293CrossRefGoogle ScholarPubMed
Edgar, RC et al. (2011) UCHIME improves sensitivity and speed of chimera detection. Bioinformatics (Oxford, England) 27, 21942200.10.1093/bioinformatics/btr381CrossRefGoogle ScholarPubMed
Jackson, MA et al. (2016) Proton pump inhibitors alter the composition of the gut microbiota. Gut 65, 749756.CrossRefGoogle ScholarPubMed
Sharpton, TJ (2014) An introduction to the analysis of shotgun metagenomic data. Frontiers in Plant Science 5, 209.10.3389/fpls.2014.00209CrossRefGoogle ScholarPubMed
Hong, S et al. (2009) Polymerase chain reaction primers miss half of rRNA microbial diversity. The ISME Journal 3, 13651373.10.1038/ismej.2009.89CrossRefGoogle ScholarPubMed
Schloss, PD (2010) The effects of alignment quality, distance calculation method, sequence filtering, and region on the analysis of 16S rRNA gene-based studies. PLoS Computational Biology 6, e1000844.10.1371/journal.pcbi.1000844CrossRefGoogle ScholarPubMed
Jovel, J et al. (2016) Characterization of the gut microbiome using 16S or shotgun metagenomics. Frontiers in Microbiology 7, 459.CrossRefGoogle ScholarPubMed
Rausch, P et al. (2019) Comparative analysis of amplicon and metagenomic sequencing methods reveals key features in the evolution of animal metaorganisms. Microbiome 7, 133.CrossRefGoogle ScholarPubMed
Willis, AD (2019) Rarefaction, alpha diversity, and statistics. Frontiers in Microbiology 10, 2407.CrossRefGoogle ScholarPubMed
Prehn-Kristensen, A et al. (2018) Reduced microbiome alpha diversity in young patients with ADHD. PLoS One 13, e0200728.10.1371/journal.pone.0200728CrossRefGoogle ScholarPubMed
Navas-Molina, JA et al. (2013) Advancing our understanding of the human microbiome using QIIME. Methods in Enzymology 531, 371444.10.1016/B978-0-12-407863-5.00019-8CrossRefGoogle ScholarPubMed
Goodrich, JK et al. (2014) Conducting a microbiome study. Cell 158, 250262.10.1016/j.cell.2014.06.037CrossRefGoogle ScholarPubMed
Johnson, JS et al. (2019) Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis. Nature Communications 10, 5029.10.1038/s41467-019-13036-1CrossRefGoogle ScholarPubMed
Rao, MS et al. (2018) Comparison of RNA-Seq and microarray gene expression platforms for the toxicogenomic evaluation of liver from short-term Rat toxicity studies. Frontiers in Genetics 9, 636.10.3389/fgene.2018.00636CrossRefGoogle ScholarPubMed
Burcham, ZM et al. (2020) Patterns of oral microbiota diversity in adults and children: a crowdsourced population study. Scientific Reports 10, 2133.10.1038/s41598-020-59016-0CrossRefGoogle ScholarPubMed
Caufield, PW et al. (2015) Oral lactobacilli and dental caries: a model for niche adaptation in humans. Journal of Dental Research 94, 110s118s.CrossRefGoogle Scholar
Bik, EM et al. (2006) Molecular analysis of the bacterial microbiota in the human stomach. Proceedings of the National Academy of Sciences of the United States of America 103, 732737.CrossRefGoogle ScholarPubMed
Nam, YD et al. (2011) Comparative analysis of Korean human gut microbiota by barcoded pyrosequencing. PLoS One 6, e22109.10.1371/journal.pone.0022109CrossRefGoogle ScholarPubMed
Delgado, S et al. (2013) Microbiological survey of the human gastric ecosystem using culturing and pyrosequencing methods. Microbial Ecology 65, 763772.10.1007/s00248-013-0192-5CrossRefGoogle ScholarPubMed
Vesper, BJ et al. (2009) The effect of proton pump inhibitors on the human microbiota. Current Drug Metabolism 10, 8489.10.2174/138920009787048392CrossRefGoogle ScholarPubMed
Theisen, J et al. (2000) Suppression of gastric acid secretion in patients with gastroesophageal reflux disease results in gastric bacterial overgrowth and deconjugation of bile acids. Journal of Gastrointestinal Surgery 4, 5054.CrossRefGoogle ScholarPubMed
Imhann, F et al. (2016) Proton pump inhibitors affect the gut microbiome. Gut 65, 740748.10.1136/gutjnl-2015-310376CrossRefGoogle ScholarPubMed
He, C et al. (2018) High-fat diet induces dysbiosis of gastric microbiota prior to gut microbiota in association with metabolic disorders in mice. Frontiers in Microbiology 9, 639.10.3389/fmicb.2018.00639CrossRefGoogle ScholarPubMed
Kechagia, M et al. (2013) Health benefits of probiotics: a review. ISRN Nutrition 2013, 481651.CrossRefGoogle ScholarPubMed
Igarashi, M et al. (2017) Alteration in the gastric microbiota and its restoration by probiotics in patients with functional dyspepsia. BMJ Open Gastroenterology 4, e000144.10.1136/bmjgast-2017-000144CrossRefGoogle ScholarPubMed
Thorell, K et al. (2017) In vivo analysis of the viable microbiota and Helicobacter pylori transcriptome in gastric infection and early stages of carcinogenesis. Infection and Immunity 85(10), 115.CrossRefGoogle ScholarPubMed
Aguiar-Pulido, V et al. (2016) Metagenomics, metatranscriptomics, and metabolomics approaches for microbiome analysis. Evolutionary Bioinformatics Online 12, 516.Google ScholarPubMed
Wolf, JB (2013) Principles of transcriptome analysis and gene expression quantification: an RNA-seq tutorial. Molecular Ecology Resources 13, 559572.10.1111/1755-0998.12109CrossRefGoogle ScholarPubMed
Wang, Z, Gerstein, M and Snyder, M (2009) RNA-seq: a revolutionary tool for transcriptomics. Nature Reviews Genetics 10, 5763.CrossRefGoogle ScholarPubMed
Kamminga, T et al. (2020) Combined transcriptome sequencing of mycoplasma hyopneumoniae and infected pig lung tissue reveals up-regulation of bacterial F1-like ATPase and down-regulation of the P102 cilium adhesin in vivo. Frontiers in Microbiology 11, 1679.CrossRefGoogle ScholarPubMed
Robbe-Saule, M et al. (2017) An optimized method for extracting bacterial RNA from mouse skin tissue colonized by Mycobacterium ulcerans. Frontiers in Microbiology 8, 512.10.3389/fmicb.2017.00512CrossRefGoogle ScholarPubMed
Jorth, P et al. (2013) Probing bacterial metabolism during infection using high-resolution transcriptomics. Journal of Bacteriology 195, 49914998.10.1128/JB.00875-13CrossRefGoogle ScholarPubMed
Rawla, P and Barsouk, A (2019) Epidemiology of gastric cancer: global trends, risk factors and prevention. Przeglad Gastroenterologiczny 14, 2638.Google ScholarPubMed
GBD 2017 Stomach Cancer Collaborators (2020) The global, regional, and national burden of stomach cancer in 195 countries, 1990–2017: a systematic analysis for the Global Burden of Disease study 2017. The Lancet Gastroenterology and Hepatology 5, 4254.10.1016/S2468-1253(19)30328-0CrossRefGoogle Scholar
Uemura, N et al. (2001) Helicobacter pylori infection and the development of gastric cancer. New England Journal of Medicine 345, 784789.CrossRefGoogle ScholarPubMed
Kumar, S et al. (2020) Risk factors and incidence of gastric cancer after detection of Helicobacter pylori infection: a large cohort study. Gastroenterology 158, 527536.e527.CrossRefGoogle ScholarPubMed
Lee, CW et al. (2008) Helicobacter pylori eradication prevents progression of gastric cancer in hypergastrinemic INS-GAS mice. Cancer Research 68, 35403548.10.1158/0008-5472.CAN-07-6786CrossRefGoogle ScholarPubMed
Lofgren, JL et al. (2011) Lack of commensal flora in Helicobacter pylori-infected INS-GAS mice reduces gastritis and delays intraepithelial neoplasia. Gastroenterology 140, 210220.10.1053/j.gastro.2010.09.048CrossRefGoogle ScholarPubMed
Zhang, W et al. (2018) Transcriptome sequencing identifies key pathways and genes involved in gastric adenocarcinoma. Molecular Medicine Reports 18, 36733682.Google ScholarPubMed
Ren, F et al. (2020) Transcriptome analysis reveals GPNMB as a potential therapeutic target for gastric cancer. Journal of Cellular Physiology 235, 27382752.10.1002/jcp.29177CrossRefGoogle ScholarPubMed
Li, XX et al. (2009) Bacterial microbiota profiling in gastritis without Helicobacter pylori infection or non-steroidal anti-inflammatory drug use. PLoS One 4, e7985.10.1371/journal.pone.0007985CrossRefGoogle ScholarPubMed
Nookaew, I et al. (2013) Transcriptome signatures in Helicobacter pylori-infected mucosa identifies acidic mammalian chitinase loss as a corpus atrophy marker. BMC Medical Genomics 6, 41.CrossRefGoogle ScholarPubMed
Gu, J et al. (2016) Metabolomic analysis reveals altered metabolic pathways in a rat model of gastric carcinogenesis. Oncotarget 7, 6005360073.10.18632/oncotarget.11049CrossRefGoogle Scholar
Wishart, DS (2016) Emerging applications of metabolomics in drug discovery and precision medicine. Nature Reviews. Drug Discovery 15, 473484.CrossRefGoogle ScholarPubMed
Tuyiringire, N et al. (2018) Application of metabolomics to drug discovery and understanding the mechanisms of action of medicinal plants with anti-tuberculosis activity. Clinical and Translational Medicine 7, 29.CrossRefGoogle ScholarPubMed
Pan, Z and Raftery, D (2007) Comparing and combining NMR spectroscopy and mass spectrometry in metabolomics. Analytical and Bioanalytical Chemistry 387, 525527.CrossRefGoogle ScholarPubMed
Huang, S et al. (2020) A systematic review of metabolomic profiling of gastric cancer and esophageal cancer. Cancer Biology & Medicine 17, 181198.CrossRefGoogle ScholarPubMed
Coker, OO et al. (2018) Mucosal microbiome dysbiosis in gastric carcinogenesis. Gut 67, 10241032.10.1136/gutjnl-2017-314281CrossRefGoogle ScholarPubMed
Parsons, BN et al. (2017) Comparison of the human gastric microbiota in hypochlorhydric states arising as a result of Helicobacter pylori-induced atrophic gastritis, autoimmune atrophic gastritis and proton pump inhibitor use. PLoS Pathogens 13, e1006653.10.1371/journal.ppat.1006653CrossRefGoogle ScholarPubMed
Castaño-Rodríguez, N et al. (2017) Dysbiosis of the microbiome in gastric carcinogenesis. Scientific Reports 7, 15957.10.1038/s41598-017-16289-2CrossRefGoogle ScholarPubMed
Liu, X et al. (2019) Alterations of gastric mucosal microbiota across different stomach microhabitats in a cohort of 276 patients with gastric cancer. EBioMedicine 40, 336348.CrossRefGoogle Scholar
Gantuya, B et al. (2019) Gastric microbiota in Helicobacter pylori-negative and -positive gastritis among high incidence of gastric cancer area. Cancers (Basel) 11(4), 112.CrossRefGoogle ScholarPubMed
Chen, XH et al. (2019) Mucosa-associated microbiota in gastric cancer tissues compared with non-cancer tissues. Frontiers in Microbiology 10, 1261.CrossRefGoogle ScholarPubMed
Gantuya, B et al. (2020) Gastric mucosal microbiota in a Mongolian population with gastric cancer and precursor conditions. Alimentary Pharmacology & Therapeutics 51, 770780.CrossRefGoogle Scholar
Wang, Z et al. (2020) Changes of the gastric mucosal microbiome associated with histological stages of gastric carcinogenesis. Frontiers in Microbiology 11, 997.10.3389/fmicb.2020.00997CrossRefGoogle ScholarPubMed
Dicksved, J et al. (2009) Molecular characterization of the stomach microbiota in patients with gastric cancer and in controls. Journal of Medical Microbiology 58, 509516.CrossRefGoogle ScholarPubMed
Maldonado-Contreras, A et al. (2011) Structure of the human gastric bacterial community in relation to Helicobacter pylori status. The ISME Journal 5, 574579.10.1038/ismej.2010.149CrossRefGoogle ScholarPubMed
Gunathilake, MN et al. (2019) Association between the relative abundance of gastric microbiota and the risk of gastric cancer: a case-control study. Scientific Reports 9, 13589.10.1038/s41598-019-50054-xCrossRefGoogle ScholarPubMed