Independent Validation of Differential Abundance Patterns from Illumina Miseq Analysis Using Quantitative PCR Techniques on the Selective Primer for Chitinophaga

Spencer Debenport¹, Laura Mason² and Richard P Dick^2,

¹Department of Plant Pathology, The Ohio State University-OARDC, Wooster, OH

²School of Environment and Natural Resources, The Ohio State University, Columbus, OH, USA

Cite this paper

Spencer Debenport, Laura Mason and Richard P Dick. Independent Validation of Differential Abundance Patterns from Illumina Miseq Analysis Using Quantitative PCR Techniques on the Selective Primer for Chitinophaga. Journal of Applied & Environmental Microbiology. 2023; 11(1):1-10. doi: 10.12691/JAEM-11-1-1

Abstract

A criticism of amplicon sequencing is the potential for bias during PCR amplification. Quantitative PCR (qPCR) is an independent validation that can estimate taxon abundance and confirm patterns observed in amplicon sequencing patterns. Therefore, the objective was to design primers based on NGS sequencing and test qPCR primers to validate abundance patterns of bacterial and fungal OTUs on soils from the Optimized Shrub-intercropping System (OSS) or Sole Cropping in the Sahel. The results showed that quantitative PCR (qPCR) independently validated patterns observed in high throughput sequencing (HTS) analyses. Specific sub-genus level OTU clusters were found to be significantly enriched in intercropped millet plants in an experiment using the Ilumina MiSeq platform. These OTU sequences were used to design primers to independently validate the trends observed in that study. A total of seven OTU clusters were targeted in the Aspergillus, Chitinophaga, Fusarium, Lasiodiplodia, and Penicillium genera. The majority of those primers showed poor specificity for their intended targets, while the Chitinophaga specific primer set showed clear amplification with a single band at the expected size. This primer was used for qPCR analysis of the same DNA templates used for the Illumina MiSeq study. Quantitative PCR shows significant (P < 0.05) enrichment of Chitinophaga marker DNA that match the previously observed patterns. MiSeq analysis showed two times higher fold change differences in markers than observed in the qPCR study. These results demonstrate that selective primers can be designed from OTU sequence data and that qPCR analysis can be utilized to independently validate trends observed in HTS studies.

Keywords

Optimized Shrub-intercropping System (OSS), Operational Taxonomic Unit (OTU), Quantitative Polymerase Chain Reaction (qPCR), High-throughput Sequencing (HTS), Plant Growth Promoting Rhizobacteria (PGPR)

Copyright

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References

[1]	Fierer N., Strickland M.S, Liptz, D., Bradford M.A., and Cleveland, C.C, “Global patterns in belowground communities,” Ecology Letters, 12, 1238-1249. 2009.
[2]	Berendsen R.L., Pieterse C.M.J., and Bakker P.A.H.M, “The rhizosphere microbiome and plant health,” Trends in Plant Science 17, 478-486. 2012.
[3]	Erlacher A., Cardinale M., Grosch R., Grube M., and Berg G,”The impact of the pathogen Rhizoctonia solani and its beneficial counterpart Bacillus amyloliquefasciens on the indigenous lettuce microbiome,” Frontiers in Microbiology. 5, 1-8. 2014.
[4]	Lee C.K, Herbold C.W., Polson, S,W., Wommack K.E., Williamson, S.J., McDonald, I.R., and Cary S.C, ”Ground truthing next-gen sequencing for microbial ecology-biases and errors in community structure estimates from PCR amplicon pyrosequencing,” PLoS ONE 7,e44224, 2012.
[5]	Jian C., Luukkonen P., Yki-Järvinen H., Salonen A., and Korpela K, “Quantitative PCR provides a simple and accessible method for quantitative microbiota profiling,” PLoS ONE 15(1), e0227285, 2020.
[6]	Kwak M., Kong H., Choi K., S-K., Ju Yeon Song, Lee J., Lee P.A., Choi S.Y., Seo M., Lee H.J., Jung E.J., Park H., Roy N., Kim H., Lee M.M., Kim J.f., Rubin E.M., and Lee S-W, “Rhizosphere microbiome structure alters to enable wilt resistance in tomato,” Nature Biotechnology, 36, 1100-1109, 2018.
[7]	Borneman J., Becker J.O., Bent E., Lanoil B., McSpadden Gardener B., Olatinwo R., Presley L., Scupham A.J., Valinsky L., and Yin B, “Identifying microorganisms involved in specific in situ functions: Experimental design considerations for rRNA gene-based population studies and sequence-selective PCR assays,” in Hurst CJ, Crawford RL, Garland JL, Lipson D.A., Mills A.L., Stetzenbach L.D. (eds.), Manual Environmental Microbiology (3rd Ed.). American Society for Microbiology, Ch 61, 748-757, 2007.
[8]	Bustin S. A., Benes, V., Garson, J.A., Hellemans, J., Huggett, J., Kubista, M., Mueller, R., Nolan, T., Pfaffl, M.W., Shipley, G.L., Vandesompele, J., and Wittwer, C.T, “The MIQE Guidelines: Minimum Information for Publication of Quantitative Real-Time PCR Experiments,” Clinical Chemistry. 55, (4) 611-622. 2011.
[9]	Kuang J., Yan X., Genders A.J., Granata C., and Bishop D.J, “An overview of technical considerations when using quantitative real-time PCR analysis of gene expression in human exercise research,” PLoS ONE, 13(5):e0196438. Published 2018 May 10. 2018.
[10]	Yang, J.I., Reugger, P.M., McKenry, M.V., Becker, O., and Borneman J, “Correlations between root-associated microorganisms and peach replant disease symptoms in a California soil,” PLoS ONE, 7, e46420, 2012.
[11]	Debenport S.J., Assigbetse K., Bayala R., Chapuis-Lydie L., Dick, R.P., and McSpadden Gardener B.B, “Shifting populations in the root-zone microbiome of millet associated with enhanced crop productivity in the Sahel,” Applied and Environmental Microbiology 8, 2841-2851, 2015.
[12]	Bright, M., Diedhiou, I., Bayala, R., Assigbetse, K., Chapuis-Lardy, L., Ndour, Y., and Dick, R.P, “Long-term Piliostigma reticulatum intercropping in the Sahel: Crop productivity, carbon sequestration, nutrient cycling, and soil quality,” Agriculture, Ecosystems. and Environment, 242, 9-22, 2017.
[13]	Bright, M., Diedhiou, I., Bayala, R., Nathaniel Bogie, Chapuis-Lardy, L., Ghezzehei, T.A.,Chapuis-Lardy, L..A., Jourdan, C., Moucty Sambou, D., Badiane Ndour, Y., Cournac,L., and Dick, R.P, “An overlooked local resource: Shrub-intercropping for food production, drought resistance and ecosystem restoration in the Sahel,” Agriculture, Ecosystems. and Environment. 319, 2021.
[14]	Caporaso, J.G., Kuczynski J., Stombaugh J., Bittinger K, Bushman F.D., Costello E.K., Fierer N., Gonzalez Pena A., Goodrich J.K., Gordon J.I., Huttley G.A., Kelley S.T., Knights D., Koenig J.E., Ley R.E., Lozupone C.A., McDonald D., Muegge B.D., Pirrung M., Reeder J., Sevinsky J.R., Turnbaugh P.J., Walters W.A., Widmann J., Yatsunenko T., Zaneveld J., and Knight R. “QIIME allows analysis of high-throughput community sequencing data,” Nature Methods, 7, 335-336, 2010.
[15]	R Core Team. “R: a language and environment for statistical computing,” R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org, 2014.
[16]	McMurdie P.J., Holmes S. “phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data,” PLoS ONE. 8(4): e61217. 2013.
[17]	Love M.I., Huber W., and Anders S, “Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2,” Genome Biology, 15, 550. 2014.
[18]	Thompson J.D, Higgins D.G., and Gibson T.J, “CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice, Nucleic Acids Research 22(22), 4673-4680, 1994.
[19]	Caporaso, J.G., Lauber C.L., Walters, W.A., Berg-Lyons, D., Huntley, J., Fierer, N, Owens S.M., Betley J., Fraser L., Bauer M., Gormley N, Gilbert J.A., Smith G., and Knight R, ”Ultrahigh-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms,” The ISME Journal, 6, 1621-1624, 2012.
[20]	Gardes M., and Bruns T.D., “ITS primers with enhanced specificity for basidiomycetes – application to the identification of mycorrhizae and rusts,” Molecular Ecology 2, 113-118, 1993.
[21]	Klymus, K.E., Merkes, C.M., Allison, M.J., Goldberg, C., Helbin, C., Hunter, M., Jackson, C., Lance, R., Mangan, A., Monroe, E., Piagio, A., Stokdyk, J., Wilson, C., and Richter, C, “Reporting the limits of detection and quantification for environmental DNA assays”, Environmental DNA 2, 271-282, 2020.
[22]	Larsen, D.A., Wigginton, K.R, Tracking COVID-19 with wastewater, Biotechnology, 38, 1151-1153. 2020.
[23]	Alteio, L.V., Séneca, J., Canarini, A., Angel,R., Jansa, J., Guseva, K., Kaiser, C., Richter, A. and Schmidt, H, “A critical perspective on interpreting amplicon sequencing data in soil ecological research,” Soil Biology and Biochemistry, 160, 2021.
[24]	Dreier M., Meola M., Berthoud H., Shani N., Wechsler D., and Junier P, “High-throughput qPCR and 16S rRNA gene amplicon sequencing as complementary methods for the investigation of the cheese microbiota,’ BMC Microbiology. 7; 22(1): 48. 2022.
[25]	Saingam, P., Li, B., and Yan, T, “Use of amplicon sequencing to improve sensitivity in PCR-based detection of microbial pathogen in environmental samples,” J. Microbiology Methods, 149: 73-79, 2018.
[26]	Pompanon F., Deagle, B.E., Symondson, W.O.C., Brown, D.S., Jarman, S.N., and Taberlet, P,” Who is eating what: Diet assessment using next generation sequencing,” Molecular Ecology 21, 1931-1950, 2012.
[27]	Westaway J.A.F., Huerlimann R., Miller C.M., Kandasamy Y., Norton R,, and Rudd D, ”Methods for exploring the faecal microbiome of premature infants: a review,” Maternal Health, Neonatology and erinatology i7(1), 11. 2018.
[28]	Poretsky, R., Rodriguez-R. L.M., Luo C., Tsementzi D., Konstantinidis K.T, “Strengths and limitations of 16S rRNA gene amplicon sequencing in revealing temporal microbial community dynamics,” PLoS ONE. 9(4): e93827.
[29]	Wilpiszeski, R.L., Aufrecht, J.A., Retterer S.T., Sullivan, M.B., Graham, D.E., Pierce, E.M., Zablocki, O.D., Palumbo, A.V., and Elias, E.A, “Soil aggregate microbial communities: towards understanding microbiome interactions at biologically relevant scales,” Applied and Environmental Microbiology, 85:e00324-19, 2019.
[30]	Bogie N.A., Bayala, R., Diedhiou, I., Conklin M.H., Fogel, M.L., Dick R.P., and Ghezzehei, T.A, Hydraulic Redistribution by Native Sahelian Shrubs: Bioirrigation to Resist In-Season Drought. Frontiers of Environmental Science, 6. 2018.
[31]	Mason, L.M., Delay, C.L., Debenport, S.J., Diedhiou, I., McSpadden Gardener, B., Assigbetse, K., Rich, V.I., and Dick, R.P, “Microbial community shifts in pearl millet root zone soils with Guiera senegalensis intercropping along a rainfall and soil type gradient in the Sahel” Soil Science Society of America Journal.
[32]	Rilling J.I., Acuña J.J., Sadowsky M.J., and Jorquera M.A, “Putative Nitrogen-fixing bacteria associated with the rhizosphere and root endosphere of wheat plants grown in an Andisol from Southern Chile,” Frontiers of Microbiology, Vol. 9. 2018.
[33]	Wiam, A., Maged, S.M., and Heribert, H, “Desert Microbes for Boosting Sustainable Agriculture in Extreme Environments, Frontiers of Microbiology, 11, 2020.
[34]	Andersen, S.C., Fachmann M.S.R., Kiil K., Møller Nielsen E., and Hoorfar J. “Gene-Based Pathogen Detection: Can We Use qPCR to Predict the Outcome of Diagnostic Metagenomics?” Genes 8(11): 332. 2017.