Bacterial and Eukaryotic Small-Subunit Amplicon Data Do Not Provide a Quantitative Picture of Microbial Communities, but They Are Reliable in the Context of Ecological Interpretations
Jazyk angličtina Země Spojené státy americké Médium electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
32132159
PubMed Central
PMC7056804
DOI
10.1128/msphere.00052-20
PII: 5/2/e00052-20
Knihovny.cz E-zdroje
- Klíčová slova
- CARD-FISH, amplicon sequencing, bacterial communities, bacterial community structure, bacterial dynamics, eukaryotic communities, eukaryotic community structure, eukaryotic dynamics, microbial abundance, microbial communities, microbial community structure, microbial dynamics,
- MeSH
- Bacteria klasifikace MeSH
- Eukaryota klasifikace MeSH
- fluorescenční mikroskopie MeSH
- fylogeneze MeSH
- mikrobiota * MeSH
- mořská voda mikrobiologie MeSH
- reprodukovatelnost výsledků MeSH
- RNA ribozomální 16S genetika MeSH
- sekvenční analýza DNA MeSH
- statistické modely MeSH
- vysoce účinné nukleotidové sekvenování * MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- RNA ribozomální 16S MeSH
High-throughput sequencing (HTS) of gene amplicons is a preferred method of assessing microbial community composition, because it rapidly provides information from a large number of samples at high taxonomic resolution and low costs. However, mock community studies show that HTS data poorly reflect the actual relative abundances of individual phylotypes, casting doubt on the reliability of subsequent statistical analysis and data interpretation. We investigated how accurately HTS data reflect the variability of bacterial and eukaryotic community composition and their relationship with environmental factors in natural samples. For this, we compared results of HTS from three independent aquatic time series (n = 883) with those from an established, quantitative microscopic method (catalyzed reporter deposition-fluorescence in situ hybridization [CARD-FISH]). Relative abundances obtained by CARD-FISH and HTS disagreed for most bacterial and eukaryotic phylotypes. Nevertheless, the two methods identified the same environmental drivers to shape bacterial and eukaryotic communities. Our results show that amplicon data do provide reliable information for their ecological interpretations. Yet, when studying specific phylogenetic groups, it is advisable to combine HTS with quantification using microscopy and/or the addition of internal standards.IMPORTANCE High-throughput sequencing (HTS) of amplified fragments of rRNA genes provides unprecedented insight into the diversity of prokaryotic and eukaryotic microorganisms. Unfortunately, HTS data are prone to quantitative biases, which may lead to an erroneous picture of microbial community composition and thwart efforts to advance its understanding. These concerns motivated us to investigate how accurately HTS data characterize the variability of microbial communities, the relative abundances of specific phylotypes, and their relationships with environmental factors in comparison to an established microscopy-based method. We compared results obtained by HTS and catalyzed reporter deposition-fluorescence in situ hybridization (CARD-FISH) from three independent aquatic time series for both prokaryotic and eukaryotic microorganisms (almost 900 data points, the largest obtained with both methods so far). HTS and CARD-FISH data disagree with regard to relative abundances of bacterial and eukaryotic phylotypes but identify similar environmental drivers shaping bacterial and eukaryotic communities.
Centre Algatech Institute of Microbiology Czech Academy of Sciences Třeboň Czech Republic
Faculty of Science University of South Bohemia České Budějovice Czech Republic
Institute of Hydrobiology Biology Centre Czech Academy of Sciences České Budějovice Czech Republic
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Venter JC, Remington K, Heidelberg JF, Halpern AL, Rusch D, Eisen JA, Wu DY, Paulsen I, Nelson KE, Nelson W, Fouts DE, Levy S, Knap AH, Lomas MW, Nealson K, White O, Peterson J, Hoffman J, Parsons R, Baden-Tillson H, Pfannkoch C, Rogers YH, Smith HO. 2004. Environmental genome shotgun sequencing of the Sargasso Sea. Science 304:66–74. doi:10.1126/science.1093857. PubMed DOI
Lundin D, Severin I, Logue JB, Ostman O, Andersson AF, Lindstrom ES. 2012. Which sequencing depth is sufficient to describe patterns in bacterial alpha- and beta-diversity? Environ Microbiol Rep 4:367–372. doi:10.1111/j.1758-2229.2012.00345.x. PubMed DOI
de Vargas C, Tara Oceans Coordinators, Audic S, Henry N, Decelle J, Mahé F, Logares R, Lara E, Berney C, Le Bescot N, Probert I, Carmichael M, Poulain J, Romac S, Colin S, Aury J-M, Bittner L, Chaffron S, Dunthorn M, Engelen S, Flegontova O, Guidi L, Horák A, Jaillon O, Lima-Mendez G, Lukeš J, Malviya S, Morard R, Mulot M, Scalco E, Siano R, Vincent F, Zingone A, Dimier C, Picheral M, Searson S, Kandels-Lewis S, Acinas SG, Bork P, Bowler C, Gorsky G, Grimsley N, Hingamp P, Iudicone D, Not F, Ogata H, Pesant S, Raes J, Sieracki ME, Speich S, Stemmann L, Sunagawa S, Weissenbach J, Wincker P, Karsenti E. 2015. Eukaryotic plankton diversity in the sunlit ocean. Science 348:1261605. doi:10.1126/science.1261605. PubMed DOI
Ramirez KS, Knight CG, de Hollander M, Brearley FQ, Constantinides B, Cotton A, Creer S, Crowther TW, Davison J, Delgado-Baquerizo M, Dorrepaal E, Elliott DR, Fox G, Griffiths RI, Hale C, Hartman K, Houlden A, Jones DL, Krab EJ, Maestre FT, McGuire KL, Monteux S, Orr CH, van der Putten WH, Roberts IS, Robinson DA, Rocca JD, Rowntree J, Schlaeppi K, Shepherd M, Singh BK, Straathof AL, Bhatnagar JM, Thion C, van der Heijden MGA, de Vries FT. 2018. Detecting macroecological patterns in bacterial communities across independent studies of global soils. Nat Microbiol 3:189–196. doi:10.1038/s41564-017-0062-x. PubMed DOI
Zhang B, Xu X, Zhu L. 2017. Structure and function of the microbial consortia of activated sludge in typical municipal wastewater treatment plants in winter. Sci Rep 7:17930. doi:10.1038/s41598-017-17743-x. PubMed DOI PMC
Williams CL, Dill-McFarland KA, Sparks DL, Kouba AJ, Willard ST, Suen G, Brown AE. 2018. Dietary changes during weaning shape the gut microbiota of red pandas (Ailurus fulgens). Conserv Physiol 6:cox075. doi:10.1093/conphys/cox075. PubMed DOI PMC
Halfvarson J, Brislawn CJ, Lamendella R, Vázquez-Baeza Y, Walters WA, Bramer LM, D'Amato M, Bonfiglio F, McDonald D, Gonzalez A, McClure EE, Dunklebarger MF, Knight R, Jansson JK. 2017. Dynamics of the human gut microbiome in inflammatory bowel disease. Nat Microbiol 2:17004. doi:10.1038/nmicrobiol.2017.4. PubMed DOI PMC
Sirová D, Bárta J, Šimek K, Posch T, Pech J, Stone J, Borovec J, Adamec L, Vrba J. 2018. Hunters or farmers? Microbiome characteristics help elucidate the diet composition in an aquatic carnivorous plant. Microbiome 6:225. doi:10.1186/s40168-018-0600-7. PubMed DOI PMC
Weiss S, Van Treuren W, Lozupone C, Faust K, Friedman J, Deng Y, Xia LC, Xu ZZ, Ursell L, Alm EJ, Birmingham A, Cram JA, Fuhrman JA, Raes J, Sun F, Zhou J, Knight R. 2016. Correlation detection strategies in microbial data sets vary widely in sensitivity and precision. ISME J 10:1669–1681. doi:10.1038/ismej.2015.235. PubMed DOI PMC
Martin-Laurent F, Philippot L, Hallet S, Chaussod R, Germon JC, Soulas G, Catroux G. 2001. DNA extraction from soils: old bias for new microbial diversity analysis methods. Appl Environ Microbiol 67:2354–2359. doi:10.1128/AEM.67.5.2354-2359.2001. PubMed DOI PMC
Hansen MC, Tolker-Nielsen T, Givskov M, Molin S. 1998. Biased 16S rDNA PCR amplification caused by interference from DNA flanking the template region. FEMS Microbiol Ecol 26:141–149. doi:10.1111/j.1574-6941.1998.tb00500.x. DOI
Klindworth A, Pruesse E, Schweer T, Peplies J, Quast C, Horn M, Glöckner FO. 2013. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res 41:e1. doi:10.1093/nar/gks808. PubMed DOI PMC
McGovern E, Waters SM, Blackshields G, McCabe MS. 2018. Evaluating established methods for rumen 16S rRNA amplicon sequencing with mock microbial populations. Front Microbiol 9:1365. doi:10.3389/fmicb.2018.01365. PubMed DOI PMC
Yeh YC, Needham DM, Sieradzki ET, Fuhrman JA. 2018. Taxon disappearance from microbiome analysis reinforces the value of mock communities as a standard in every sequencing run. mSystems 3:9. doi:10.1128/mSystems.00023-18. PubMed DOI PMC
Smith KF, Kohli GS, Murray SA, Rhodes LL. 2017. Assessment of the metabarcoding approach for community analysis of benthic-epiphytic dinoflagellates using mock communities. N Z J Marine Freshwater Res 51:555–576. doi:10.1080/00288330.2017.1298632. DOI
Lee Z-P, Bussema C 3rd, Schmidt TM. 2009. rrnDB: documenting the number of rRNA and tRNA genes in bacteria and archaea. Nucleic Acids Res 37:D489–D493. doi:10.1093/nar/gkn689. PubMed DOI PMC
Gong J, Dong J, Liu X, Massana R. 2013. Extremely high copy numbers and polymorphisms of the rDNA operon estimated from single cell analysis of oligotrich and peritrich ciliates. Protist 164:369–379. doi:10.1016/j.protis.2012.11.006. PubMed DOI
Zhu F, Massana R, Not F, Marie D, Vaulot D. 2005. Mapping of picoeucaryotes in marine ecosystems with quantitative PCR of the 18S rRNA gene. FEMS Microbiol Ecol 52:79–92. doi:10.1016/j.femsec.2004.10.006. PubMed DOI
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. doi:10.1038/nmeth.3869. PubMed DOI PMC
Schaechter M. 2015. A brief history of bacterial growth physiology. Front Microbiol 6:289. doi:10.3389/fmicb.2015.00289. PubMed DOI PMC
Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski RA, Oakley BB, Parks DH, Robinson CJ, Sahl JW, Stres B, Thallinger GG, Van Horn DJ, Weber CF. 2009. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75:7537–7541. doi:10.1128/AEM.01541-09. PubMed DOI PMC
Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Peña AG, Goodrich JK, Gordon JI, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widmann J, Yatsunenko T, Zaneveld J, Knight R. 2010. QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7:335–336. doi:10.1038/nmeth.f.303. PubMed DOI PMC
Wendeberg A, Pernthaler J, Amann R. 2004. Sensitive multi-color fluorescence in situ hybridization for the identification of environmental microorganisms. Mol Microb Ecol Manual 3:711–726.
Amann R, Fuchs BM. 2008. Single-cell identification in microbial communities by improved fluorescence in situ hybridization techniques. Nat Rev Microbiol 6:339–348. doi:10.1038/nrmicro1888. PubMed DOI
Eilers H, Pernthaler J, Amann R. 2000. Succession of pelagic marine bacteria during enrichment: a close look at cultivation-induced shifts. Appl Environ Microbiol 66:4634–4640. doi:10.1128/aem.66.11.4634-4640.2000. PubMed DOI PMC
Salcher MM, Pernthaler J, Frater N, Posch T. 2011. Vertical and longitudinal distribution patterns of different bacterioplankton populations in a canyon-shaped, deep prealpine lake. Limnol Oceanogr 56:2027–2039. doi:10.4319/lo.2011.56.6.2027. DOI
Shabarova T, Kasalický V, Šimek K, Nedoma J, Znachor P, Posch T, Pernthaler J, Salcher MM. 2017. Distribution and ecological preferences of the freshwater lineage LimA (genus Limnohabitans) revealed by a new double hybridization approach. Environ Microbiol 19:1296–1309. doi:10.1111/1462-2920.13663. PubMed DOI
Piwosz K, Kownacka J, Ameryk A, Zalewski M, Pernthaler J. 2016. Phenology of cryptomonads and the CRY1 lineage in a coastal brackish lagoon (Vistula Lagoon, Baltic Sea). J Phycol 52:626–637. doi:10.1111/jpy.12424. PubMed DOI
Massana R, Guillou L, Terrado R, Forn I, Pedrós-Alió C. 2006. Growth of uncultured heterotrophic flagellates in unamended seawater incubations. Aquat Microb Ecol 45:171–180. doi:10.3354/ame045171. DOI
Not F, Latasa M, Scharek R, Viprey M, Karleskind P, Balagué V, Ontoria-Oviedo I, Cumino A, Goetze E, Vaulot D, Massana R. 2008. Protistan assemblages across the Indian Ocean, with a specific emphasis on the picoeukaryotes. Deep-Sea Res Part I Oceanogr Res Pap 55:1456–1473. doi:10.1016/j.dsr.2008.06.007. DOI
Piwosz K, Shabarova T, Tomasch J, Šimek K, Kopejtka K, Kahl S, Pieper DH, Koblížek M. 2018. Determining lineage-specific bacterial growth curves with a novel approach based on amplicon reads normalization using internal standard (ARNIS). ISME J 12:2640–2654. doi:10.1038/s41396-018-0213-y. PubMed DOI PMC
Stern R, Kraberg A, Bresnan E, Kooistra W, Lovejoy C, Montresor M, Morán XAG, Not F, Salas R, Siano R, Vaulot D, Amaral-Zettler L, Zingone A, Metfies K. 2018. Molecular analyses of protists in long-term observation programmes—current status and future perspectives. J Plankton Res 40:519–536. doi:10.1093/plankt/fby035. DOI
Giner CR, Forn I, Romac S, Logares R, de Vargas C, Massana R. 2016. Environmental sequencing provides reasonable estimates of the relative abundance of specific picoeukaryotes. Appl Environ Microbiol 82:4757–4766. doi:10.1128/AEM.00560-16. PubMed DOI PMC
Ibarbalz FM, Perez MV, Figuerola ELM, Erijman L. 2014. The bias associated with amplicon sequencing does not affect the quantitative assessment of bacterial community dynamics. PLoS One 9:e99722. doi:10.1371/journal.pone.0099722. PubMed DOI PMC
Monchy S, Grattepanche JD, Breton E, Meloni D, Sanciu G, Chabe M, Delhaes L, Viscogliosi E, Sime-Ngando T, Christaki U. 2012. Microplanktonic community structure in a coastal system relative to a Phaeocystis bloom inferred from morphological and tag pyrosequencing methods. PLoS One 7:e39924. doi:10.1371/journal.pone.0039924. PubMed DOI PMC
Gao W, Chen Z, Li Y, Pan Y, Zhu J, Guo S, Hu L, Huang J. 2018. Bioassessment of a drinking water reservoir using plankton: high throughput sequencing vs. traditional morphological method. Water 10:82. doi:10.3390/w10010082. DOI
Herlemann DPR, Woelk J, Labrenz M, Jürgens K. 2014. Diversity and abundance of “Pelagibacterales” (SAR11) in the Baltic Sea salinity gradient. Syst Appl Microbiol 37:601–604. doi:10.1016/j.syapm.2014.09.002. PubMed DOI
Bergen B, Herlemann DP, Labrenz M, Jürgens K. 2014. Distribution of the verrucomicrobial clade Spartobacteria along a salinity gradient in the Baltic Sea. Environ Microbiol Rep 6:625–630. doi:10.1111/1758-2229.12178. PubMed DOI
Okazaki Y, Fujinaga S, Tanaka A, Kohzu A, Oyagi H, Nakano SI. 2017. Ubiquity and quantitative significance of bacterioplankton lineages inhabiting the oxygenated hypolimnion of deep freshwater lakes. ISME J 11:2279–2293. doi:10.1038/ismej.2017.89. PubMed DOI PMC
Pitsch G, Bruni EP, Forster D, Qu Z, Sonntag B, Stoeck T, Posch T. 2019. Seasonality of planktonic freshwater ciliates: are analyses based on V9 regions of the 18S rRNA gene correlated with morphospecies counts?. Front Microbiol 10:248. doi:10.3389/fmicb.2019.00248. PubMed DOI PMC
Carr A, Diener C, Baliga NS, Gibbons SM. 2019. Use and abuse of correlation analyses in microbial ecology. ISME J 13:2647–2655. doi:10.1038/s41396-019-0459-z. PubMed DOI PMC
Bland JM, Altman DG. 1986. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1:307–310. doi:10.1016/S0140-6736(86)90837-8. PubMed DOI
Bakenhus I, Wemheuer B, Akyol P, Giebel H-A, Dlugosch L, Daniel R, Simon M. 2019. Distinct relationships between fluorescence in situ hybridization and 16S rRNA gene- and amplicon-based sequencing data of bacterioplankton lineages. Syst Appl Microbiol 42:126000. doi:10.1016/j.syapm.2019.06.005. PubMed DOI
Graneli E, Edvardsen B, Roelke DL, Hagstrom JA. 2012. The ecophysiology and bloom dynamics of Prymnesium spp. Harmful Algae 14:260–270. doi:10.1016/j.hal.2011.10.024. DOI
Jovel J, Patterson J, Wang W, Hotte N, O'Keefe S, Mitchel T, Perry T, Kao D, Mason AL, Madsen KL, Wong GK-S. 2016. Characterization of the gut microbiome using 16S or shotgun metagenomics. Front Microbiol 7:459–459. doi:10.3389/fmicb.2016.00459. PubMed DOI PMC
Piwosz K. 2019. Weekly dynamics of abundance and size structure of specific nanophytoplankton lineages in coastal waters (Baltic Sea). Limnol Oceanogr 64:2172–2186. doi:10.1002/lno.11177. DOI
Gohl DM, Vangay P, Garbe J, MacLean A, Hauge A, Becker A, Gould TJ, Clayton JB, Johnson TJ, Hunter R, Knights D, Beckman KB. 2016. Systematic improvement of amplicon marker gene methods for increased accuracy in microbiome studies. Nat Biotechnol 34:942–949. doi:10.1038/nbt.3601. PubMed DOI
Calus ST, Ijaz UZ, Pinto AJ. 2018. NanoAmpli-Seq: a workflow for amplicon sequencing for mixed microbial communities on the nanopore sequencing platform. Gigascience 7:16. doi:10.1093/gigascience/giy140. PubMed DOI PMC
Acharya K, Khanal S, Pantha K, Amatya N, Davenport RJ, Werner D. 2019. A comparative assessment of conventional and molecular methods, including MinION nanopore sequencing, for surveying water quality. Sci Rep 9:11. doi:10.1038/s41598-019-51997-x. PubMed DOI PMC
Luo C, Tsementzi D, Kyrpides N, Read T, Konstantinidis KT. 2012. Direct comparisons of Illumina vs. Roche 454 sequencing technologies on the same microbial community DNA sample. PLoS One 7:e30087. doi:10.1371/journal.pone.0030087. PubMed DOI PMC
Stoeck T, Bass D, Nebel M, Christen R, Jones MDM, Breiner H-W, Richards TA. 2010. Multiple marker parallel tag environmental DNA sequencing reveals a highly complex eukaryotic community in marine anoxic water. Mol Ecol 19:21–31. doi:10.1111/j.1365-294X.2009.04480.x. PubMed DOI
Quince C, Lanzen A, Davenport RJ, Turnbaugh PJ. 2011. Removing noise from pyrosequenced amplicons. BMC Bioinformatics 12:38. doi:10.1186/1471-2105-12-38. PubMed DOI PMC
Sherr BF, Sherr EB, Fallon RD. 1987. Use of monodispersed, fluorescently labeled bacteria to estimate in situ protozoan bacterivory. Appl Environ Microbiol 53:958–965. doi:10.1128/AEM.53.5.958-965.1987. PubMed DOI PMC
Grasshoff K, Ehrhardt M, Kremling K. 1976. Methods for sea water analysis. Verlag Chemie: 1–419.
Egge E, Bittner L, Andersen T, Audic S, de Vargas C, Edvardsen B. 2013. 454 Pyrosequencing to describe microbial eukaryotic community composition, diversity and relative abundance: a test for marine haptophytes. PLoS One 8:e74371. doi:10.1371/journal.pone.0074371. PubMed DOI PMC
Piwosz K, Pernthaler J. 2010. Seasonal population dynamics and trophic role of planktonic nanoflagellates in coastal surface waters of the Southern Baltic Sea. Environ Microbiol 12:364–377. doi:10.1111/j.1462-2920.2009.02074.x. PubMed DOI
Shabarova T, Villiger J, Morenkov O, Niggemann J, Dittmar T, Pernthaler J. 2014. Bacterial community structure and dissolved organic matter in repeatedly flooded subsurface karst water pools. FEMS Microbiol Ecol 89:111–126. doi:10.1111/1574-6941.12339. PubMed DOI
Edgar RC. 2010. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26:2460–2461. doi:10.1093/bioinformatics/btq461. PubMed DOI
Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R. 2011. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27:2194–2200. doi:10.1093/bioinformatics/btr381. PubMed DOI PMC
Guillou L, Bachar D, Audic S, Bass D, Berney C, Bittner L, Boutte C, Burgaud G, de Vargas C, Decelle J, del Campo J, Dolan JR, Dunthorn M, Edvardsen B, Holzmann M, Kooistra W, Lara E, Le Bescot N, Logares R, Mahe F, Massana R, Montresor M, Morard R, Not F, Pawlowski J, Probert I, Sauvadet AL, Siano R, Stoeck T, Vaulot D, Zimmermann P, Christen R. 2013. The Protist Ribosomal Reference database (PR2): a catalog of unicellular eukaryote small sub-unit rRNA sequences with curated taxonomy. Nucleic Acids Res 41:D597–D604. doi:10.1093/nar/gks1160. PubMed DOI PMC
Gabaldon C, Devetter M, Hejzlar J, Šimek K, Znachor P, Nedoma J, Seďa J. 2017. Repeated flood disturbance enhances rotifer dominance and diversity in a zooplankton community of a small dammed mountain pond. J Limnol 76:292–304. doi:10.4081/jlimnol.2016.1544. DOI
Porcal P, Kopáček J. 2018. Photochemical degradation of dissolved organic matter reduces the availability of phosphorus for aquatic primary producers. Chemosphere 193:1018–1026. doi:10.1016/j.chemosphere.2017.11.140. PubMed DOI
Brussaard C. 2004. Optimization of procedures for counting viruses by flow cytometry. Appl Environ Microbiol 70:1506–1513. doi:10.1128/aem.70.3.1506-1513.2004. PubMed DOI PMC
Beutler M, Wiltshire KH, Meyer B, Moldaenke C, Luring C, Meyerhofer M, Hansen UP, Dau H. 2002. A fluorometric method for the differentiation of algal populations in vivo and in situ. Photosynth Res 72:39–53. doi:10.1023/A:1016026607048. PubMed DOI
Nercessian O, Noyes E, Kalyuzhnaya MG, Lidstrom ME, Chistoserdova L. 2005. Bacterial populations active in metabolism of C-1 compounds in the sediment of Lake Washington, a freshwater lake. Appl Environ Microbiol 71:6885–6899. doi:10.1128/AEM.71.11.6885-6899.2005. PubMed DOI PMC
Sekar R, Pernthaler A, Pernthaler J, Warnecke F, Posch T, Amann R. 2003. An improved protocol for quantification of freshwater Actinobacteria by fluorescence in situ hybridization. Appl Environ Microbiol 69:2928–2935. doi:10.1128/aem.69.5.2928-2935.2003. PubMed DOI PMC
Salcher MM, Pernthaler J, Posch T. 2011. Seasonal bloom dynamics and ecophysiology of the freshwater sister clade of SAR11 bacteria ‘that rule the waves’ (LD12). ISME J 5:1242–1252. doi:10.1038/ismej.2011.8. PubMed DOI PMC
Edgar RC. 2013. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat Methods 10:996–998. doi:10.1038/nmeth.2604. PubMed DOI
Pruesse E, Quast C, Knittel K, Fuchs BM, Ludwig W, Peplies J, Glockner FO. 2007. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res 35:7188–7196. doi:10.1093/nar/gkm864. PubMed DOI PMC
R Core Team. 2015. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria: http://www.R-project.org/.
Wickham H. 2009. ggplot2: elegant graphics for data analysis. Springer-Verlag, New York, NY.
Anderson MJ, Legendre P. 1999. An empirical comparison of permutation methods for tests of partial regression coefficients in a linear model. J Stat Comput Simul 62:271–303. doi:10.1080/00949659908811936. DOI
Global freshwater distribution of Telonemia protists
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Cryptic and ubiquitous aplastidic cryptophytes are key freshwater flagellated bacterivores
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CARD-FISH in the Sequencing Era: Opening a New Universe of Protistan Ecology