Abstract
How microbes respond to variable environmental conditions? This is a fundamental question to understand regulating mechanisms of biogeochemical cycles in the ocean. High coverage expression profiling (HiCEP) is an RNA fingerprinting method able to analyze microbial metabolic responses to various environmental conditions. Although HiCEP has been applied to various types of single organisms and revealed their responses to targeted conditions, there have been no reports on the application of this method to gene expression profiling of microbial communities. The HiCEP method can provide a unique way of analysis in metatranscriptomics. In this chapter, we provide a guidance of the HiCEP method for applying it to the omics-study of natural ecosystems. We experimentally obtained HiCEP data of prokaryotic communities in coastal surface seawater to show the feasibility of this application, indicating its methodological advantages in the analysis of metatranscriptome. In addition to high accuracy and reproducibility, this method can evaluate gene expression using either peak patterns or compositions of sequence clusters without annotation information, which enables us to highlight previously undescribed but showing distinctive expression in particular environmental conditions. The HiCEP-sequencing method can be a powerful tool for meta-omics studies in various types of environmental settings.
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Araki R, Fukumura R, Sasaki N et al (2006) More than 40,000 transcripts, Including novel and noncoding transcripts, in mouse embryonic stem cells. Stem Cells 24:2522–2528. https://doi.org/10.1634/stemcells.2006-0005
Bollmann A, Conrad R (1998) Influence of O2 availability on NO and N2O release by nitrification and denitrification in soils. Glob Chang Biol 4:387–396. https://doi.org/10.1046/j.1365-2486.1998.00161.x
Booijink CCGM, Boekhorst J, Zoetendal EG et al (2010) Metatranscriptome analysis of the human fecal microbiota reveals subject-specific expression profiles, with genes encoding proteins involved in carbohydrate metabolism being dominantly expressed. Appl Environ Microbiol 76:5533–5540. https://doi.org/10.1128/AEM.00502-10
Camacho C, Coulouris G, Avagyan V et al (2009) BLAST+: architecture and applications. BMC Bioinformatics 10:421. https://doi.org/10.1186/1471-2105-10-421
Frias-Lopez J, Shi Y, Tyson GW et al (2008) Microbial community gene expression in ocean surface waters. Proc Natl Acad Sci U S A 105:3805–3810. https://doi.org/10.1073/pnas.0708897105
Fujimura R, Kim S-W, Sato Y et al (2016) Unique pioneer microbial communities exposed to volcanic sulfur dioxide. Sci Rep 6:19687. https://doi.org/10.1038/srep19687
Fukumura R, Takahashi H, Saito T et al (2003) A sensitive transcriptome analysis method that can detect unknown transcripts. Nucleic Acids Res 31:e94
Ganesh S, Parris DJ, DeLong EF, Stewart FJ (2014) Metagenomic analysis of size-fractionated picoplankton in a marine oxygen minimum zone. ISME J 8:187–211. https://doi.org/10.1038/ismej.2013.144
Gunasekera TS, Bowen LL, Zhou CE et al (2017) Transcriptomic analyses elucidate adaptive differences of closely related strains of Pseudomonas aeruginosa in fuel. Appl Environ Microbiol 83:e03249–e03216. https://doi.org/10.1128/AEM.03249-16
Komatsu S, Sakata K, Nanjo Y (2015) ‘ Omics ’ techniques and their use to identify how soybean responds to flooding. J Anal Sci Technol 6:1–8. https://doi.org/10.1186/s40543-015-0052-7
McCarren J, Becker JW, Repeta DJ et al (2010) Microbial community transcriptomes reveal microbes and metabolic pathways associated with dissolved organic matter turnover in the sea. Proc Natl Acad Sci U S A 107:16420–16427. https://doi.org/10.1073/pnas.1010732107
Mitani Y, Suzuki K, Kondo K et al (2006) Gene expression analysis using a modified HiCEP method applicable to prokaryotes: a study of the response of Rhodococcus to isoniazid and ethambutol. J Biotechnol 123:259–272. https://doi.org/10.1016/j.jbiotec.2005.11.004
Nakamori T, Fujimori A, Kinoshita K et al (2008) Application of HiCEP to screening of radiation stress-responsive genes in the soil microarthropod Folsomia candida (Collembola). Environ Sci Technol 42:6997–7002
Pertea G, Huang X, Liang F et al (2003) TIGR gene indices clustering tools (TGICL): a software system for fast clustering of large EST datasets. Bioinformatics 19:651–652. https://doi.org/10.1093/bioinformatics/btg034
Shi Y, Tyson GW, Eppley JM, DeLong EF (2011) Integrated metatranscriptomic and metagenomic analyses of stratified microbial assemblages in the open ocean. ISME J 5:999–1013. https://doi.org/10.1038/ismej.2010.189
Wagner GP, Kin K, Lynch VJ (2012) Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples. Theory Biosci 131:281–285. https://doi.org/10.1007/s12064-012-0162-3
Yuyama I, Watanabe T, Takei Y (2011) Profiling differential gene expression of symbiotic and aposymbiotic corals using a high coverage gene expression profiling (HiCEP) analysis. Mar Biotechnol 13:32–40. https://doi.org/10.1007/s10126-010-9265-3
Acknowledgments
We are very grateful to R. Araki and M. Sunayama for HiCEP analysis and their helpful comments regarding the manuscript and data analysis. We thank S. Asakawa and E. Tan for performing IonPGM sequencing analysis. We also thank K. Kogure and the Tohoku Ecosystem Associated Marine Sciences (TEAMS) for sea water samples obtained on the research cruise. Additionally, we thank the captains, crew members, and participants on the R/V Daisankaiyo-maru cruises for their cooperation. Computational analyses were partially performed by maze Inc. The Japan Science and Technology Agency (CREST) and JST-SENTAN Program supported this research.
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Fujimura, R., Yunokawa, H., Hamasaki, K. (2019). High Coverage Expression Profiling (HiCEP) of Microbial Community Genomes in the Ocean. In: Gojobori, T., Wada, T., Kobayashi, T., Mineta, K. (eds) Marine Metagenomics. Springer, Singapore. https://doi.org/10.1007/978-981-13-8134-8_4
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DOI: https://doi.org/10.1007/978-981-13-8134-8_4
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