A new spike-in-based method for quantitative metabarcoding of soil fungi and bacteria

Bengtsson-Palme J, Ryberg M, Hartmann M, Branco S, Wang Z, Godhe A, De Wit P, Sánchez-García M, Ebersberger I, de Sousa F et al (2013) Improved software detection and extraction of ITS1 and ITS2 from ribosomal its sequences of fungi and other eukaryotes for analysis of environmental sequencing data. Methods Ecol Evol 4:914–919 Bonk F, Popp D, Harms H, Centler F (2018) PCR-based quantification of taxa-specific abundances in microbial communities: quantifying and avoiding common pitfalls. J Microbiol Methods 153:139–147 Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP (2016) DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods 13:581–583 Chen K, Hu Z, Xia Z, Zhao D, Li W, Tyler JK (2016) The overlooked fact: fundamental need for spike-in control for virtually all genome-wide analyses. Mol Cell Biol 36:662–667 Davis NM, Proctor DM, Holmes SP, Relman DA, Callahan BJ (2018) Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. Microbiome 6:226 Dopheide A, Xie D, Buckley TR, Drummond AJ, Newcomb RD (2019) Impacts of DNA extraction and PCR on DNA metabarcoding estimates of soil biodiversity. Methods Ecol Evol 10:120–133 Gloor GB, Macklaim JM, Pawlowsky-Glahn V, Egozcue JJ (2017) Microbiome datasets are compositional: and this is not optional. Front Microbiol 8:2224 Hardwick SA, Chen WY, Wong T, Kanakamedala BS, Deveson IW, Ongley SE, Santini NS, Marcellin E, Smith MA, Nielsen LK, Lovelock CE, Neilan BA, Mercer TR (2018) Synthetic microbe communities provide internal reference standards for metagenome sequencing and analysis. Nat Commun 9:1–10 Haro C, Anguita-Maeso M, Metsis M, Navas-Cortés JA, Landa BB (2021) evaluation of established methods for DNA extraction and primer pairs targeting 16S rRNA gene for bacterial microbiota profiling of olive xylem sap. Front Plant Sci 12:640829 Harrison JG, John Calder W, Shuman B, Alex Buerkle C (2021) The quest for absolute abundance: the use of internal standards for DNA-based community ecology. Mol Ecol Resour 21:30–43 Herlemann DP, Labrenz M, Jürgens K, Bertilsson S, Waniek JJ, Andersson AF (2011) Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. ISME J 5:1571–1579 Jones MB, Highlander SK, Anderson EL, Li W, Dayrit M, Klitgord N, Fabani MM, Seguritan V, Green J, Pride DT, Yooseph S, Biggs W, Nelson KE, Craig Venter J (2015) Library preparation methodology can influence genomic and functional predictions in human microbiome research. Proc Natl Acad Sci U S A 112:14024–14029 Kõljalg U, Nilsson HR, Schigel D, Tedersoo L, Larsson KH, May TW, Taylor AFS, Jeppesen TS, Frøslev TG, Lindahl BD, Põldmaa K, Saar I, Suija A, Savchenko A, Yatsiuk I, Adojaan K, Ivanov F, Piirmann T, Pöhönen R et al (2020) The taxon hypothesis paradigm - On the unambiguous detection and communication of taxa. Microorganisms 8:1–24 Kong J, Liu X, Wang L, Huang H, Ou D, Guo J, Laws EA, Huang B (2021) Patterns of relative and quantitative abundances of marine bacteria in surface waters of the subtropical Northwest Pacific Ocean estimated with high-throughput quantification sequencing. Front Microbiol. https://doi.org/10.3389/fmicb.2020.599614 Lin Y, Gifford S, Ducklow H, Schofield O, Cassar N (2019) towards quantitative microbiome community profiling using internal standards. Appl Environ Microbiol 85:1–14 Lindner DL, Banik MT (2011) Intragenomic variation in the ITS rDNA region obscures phylogenetic relationships and inflates estimates of operational taxonomic units in genus Laetiporus. Mycologia 103:731–740 Liu P, Yang S, Yang S (2022) KTU: K-mer taxonomic units improve the biological relevance of amplicon sequence variant microbiota data. Methods Ecol Evol 13:560–568 Lofgren LA, Uehling JK, Branco S, Bruns TD, Martin F, Kennedy PG (2019) Genome-based estimates of fungal rDNA copy number variation across phylogenetic scales and ecological lifestyles. Mol Ecol 28:721–730 Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal 17:10–12 McMurdie PJ, Holmes S (2013) Phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One. https://doi.org/10.1371/journal.pone.0061217 McMurdie PJ, Holmes S (2014) Waste not, want not: why rarefying microbiome data is inadmissible. PLoS Comput Biol. https://doi.org/10.1371/journal.pcbi.1003531 Morton JT, Marotz C, Washburne A, Silverman J, Zaramela LS, Edlund A, Zengler K, Knight R (2019) Establishing microbial composition measurement standards with reference frames. Nat Commun. https://doi.org/10.1038/s41467-019-10656-5 Murali A, Bhargava A, Wright ES (2018) IDTAXA: a novel approach for accurate taxonomic classification of microbiome sequences. Microbiome 6:140 O’Donnell K, Cigelnik E (1997) Two divergent intragenomic rDNA ITS2 types within a monophyletic lineage of the fungus Fusarium are non-orthologous. Mol Phylogenet Evol 7:103–116 Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, Minchin PR, O’Hara RB, Simpson GL, Solymos P, others (2020) Vegan: community ecology package. R package version 2.5-6. 2019 Paloi S, Luangsa-ard JJ, Mhuantong W, Stadler M, Kobmoo N (2022) Intragenomic variation in nuclear ribosomal markers and its implication in species delimitation, identification and barcoding in fungi. Fungal Biol Rev 42:1–33 Peres-Neto PR, Jackson DA (2001) How well do multivariate data sets match? The advantages of a procrustean superimposition approach over the Mantel test. Oecologia 129:169–178 Props R, Kerckhof FM, Rubbens P, De VJ, Sanabria EH, Waegeman W, Monsieurs P, Hammes F, Boon N (2017) Absolute quantification of microbial taxon abundances. ISME J 11:584–587 Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO (2012) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 41:D590–D596 Quinn TP, Erb I, Gloor G, Notredame C, Richardson MF, Crowley TM (2019) A field guide for the compositional analysis of any-omics data. GigaScience 8:1–14 R Core Team (2022) R: a language and environment for statistical computing Rodriguez-Mena S, Camacho M, de los Santos B, Miranda L, Camacho-Sanchez M (2022) Microbiota modulation in blueberry rhizosphere by biocontrol bacteria. Microbiol Res (Pavia) 13:809–824 Ruppert KM, Kline RJ, Rahman MS (2019) Past, present, and future perspectives of environmental DNA (eDNA) metabarcoding: a systematic review in methods, monitoring, and applications of global eDNA. Glob Ecol Conserv 17:e00547 Schoch CL, Seifert KA, Huhndorf S, Robert V, Spouge JL, Levesque CA, Chen W, Fungal Barcoding Consortium (2012) Nuclear ribosomal internal transcribed spacer (ITS) region as a universal DNA barcode marker for Fungi. Proc Natl Acad Sci USA 109:6241–6246 Shelton AO, Gold ZJ, Jensen AJ, D′Agnese E, Andruszkiewicz Allan E, Van Cise A, Gallego R, Ramón-Laca A, Garber-Yonts M, Parsons K, Kelly RP (2022) Toward quantitative metabarcoding. Ecology.: https://doi.org/10.1002/ecy.3906 Sidstedt M, Rådström P, Hedman J (2020) PCR inhibition in qPCR, dPCR and MPS-mechanisms and solutions. Anal Bioanal Chem 412:2009–2023 Smets W, Leff JW, Bradford MA, McCulley RL, Lebeer S, Fierer N (2016) A method for simultaneous measurement of soil bacterial abundances and community composition via 16S rRNA gene sequencing. Soil Biol Biochem 96:145–151 Stämmler F, Gläsner J, Hiergeist A, Holler E, Weber D, Oefner PJ, Gessner A, Spang R (2016) Adjusting microbiome profiles for differences in microbial load by spike-in bacteria. Microbiome 4:1–13 Stoddard SF, Smith BJ, Hein R, Roller BRK, Schmidt TM (2015) rrnDB: improved tools for interpreting rRNA gene abundance in bacteria and archaea and a new foundation for future development. Nucleic Acids Res 43:D593–D598 Taberlet P, Coissac E, Pompanon F, Brochmann C, Willerslev E (2012) Towards next-generation biodiversity assessment using DNA metabarcoding. Mol Ecol 21:2045–2050 Tedersoo L, Bahram M, Zinger L, Nilsson RH, Kennedy PG, Yang T, Anslan S, Mikryukov V (2022) Best practices in metabarcoding of fungi: from experimental design to results. Mol Ecol 31:2769–2795 Tsilimigras MCB, Fodor AA (2016) Compositional data analysis of the microbiome: fundamentals, tools, and challenges. Ann Epidemiol 26:330–335 White TJ, Bruns T, Lee S, Taylor J (1990) Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. PCR Protoc a Guid to methods Appl 18:315–322 Wright ES (2016) Using DECIPHER v2. 0 to analyze big biological sequence data in R. R J. 8:352–359 Yang L, Lou J, Wang H, Wu L, Xu J (2018a) Use of an improved high-throughput absolute abundance quantification method to characterize soil bacterial community and dynamics. Sci Total Environ 633:360–371 Yang R-H, Su J-H, Shang J-J, Wu Y-Y, Li Y, Bao D-P, Yao Y-J (2018b) Evaluation of the ribosomal DNA internal transcribed spacer (ITS), specifically ITS1 and ITS2, for the analysis of fungal diversity by deep sequencing. PLoS One 13:e0206428