bs_bs_banner Environmental Microbiology (2014) 16(3), 643–657 doi:10.1111/1462-2920.12365 Systematic evaluation of bias in microbial community profiles induced by whole genome amplification Susana O. L. Direito,1† Egija Zaura,2 Miranda Little,1 that pWGA is the most promising method for charac- Pascale Ehrenfreund3,4 and Wilfred F. M. Röling1* terization of microbial communities in low-biomass 1Molecular Cell Physiology, Faculty of Earth and Life environments and for currently planned astro- Sciences, VU University Amsterdam, Amsterdam, The biological missions to Mars. Netherlands. 2Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam (ACTA), University of Introduction Amsterdam and VU University Amsterdam, Amsterdam, Advances in molecular techniques have revolutionized The Netherlands. microbial ecology since the 1980s (Pace et al., 1986). 3 Leiden Institute of Chemistry, Leiden, The Netherlands. Polymerase chain reaction (PCR)-based culture- 4 Space Policy Institute, Elliott School of International independent sequence analysis of 16S rRNA genes has Affairs, Washington, Washington, DC, USA. become the most widely used method to determine the phylogenetic composition of microbial communities, cir- Summary cumventing the problem that most microorganisms cannot be cultured (Hawkins et al., 2002). It contributed to Whole genome amplification methods facilitate the the description of microbial communities in low-biomass, detection and characterization of microbial communi- extreme environments with resemblance to Mars (e.g. ties in low biomass environments. We examined the Drees et al., 2006; Pointing et al., 2009; Direito et al., extent to which the actual community structure is 2011). reliably revealed and factors contributing to bias. One More recently, the field of microbial ecology has moved widely used [multiple displacement amplification from the PCR-based analysis of single genes towards the (MDA)] and one new primer-free method [primase- analysis of metagenomes and functional capabilities of based whole genome amplification (pWGA)] were microbial communities through metagenomics (e.g. Tyson compared using a polymerase chain reaction (PCR)- et al., 2004) and community-wide functional microarrays based method as control. Pyrosequencing of an envi- (e.g. He et al., 2007). However, obtaining sufficient DNA ronmental sample and principal component analysis for these analyses can be an issue, especially for low- revealed that MDA impacted community profiles more biomass environments (Abulencia et al., 2006). Conven- strongly than pWGA and indicated that this related to tional PCR (Mullis et al., 1986) is not practical to generate species GC content, although an influence of DNA sufficient DNA template as it requires prior sequence integrity could not be excluded. Subsequently, biases information to define primers that target specific by species GC content, DNA integrity and fragment sequences. Multiple displacement amplification (MDA) size were separately analysed using defined mixtures has been used to amplify whole genomes from low- of DNA from various species. We found significantly biomass environments for use as template in meta- less amplification of species with the highest GC genomics (Abulencia et al., 2006). Functional microarrays content for MDA-based templates and, to a lesser are often hybridized with DNA that is first amplified by extent, for pWGA. DNA fragmentation also interfered MDA (Wu et al., 2006). severely: species with more fragmented DNA Whole genome amplification (WGA) methods, like were less amplified with MDA and pWGA. pWGA MDA, offer yet another advantage over PCR in describing was unable to amplify low molecular weight DNA microbial communities in low-biomass, extreme Mars < ( 1.5 kb), whereas MDA was inefficient. We conclude analogues, and possibly even astrobiology missions to Mars; the random amplification of DNA by WGA methods Received 24 August, 2013; revised 10 December, 2013; accepted 17 may aid the detection of life, as even on Earth rRNA December, 2013. *For correspondence. E-mail wilfred.roling@ gene-directed PCR can miss species (e.g. Huber et al., falw.vu.nl; Tel. +31 20 5987192; Fax +31 20 5987223. †Present address: School of Physics and Astronomy, University of Edinburgh, 2002). Furthermore, virus-like entities might be present Edinburgh, Midlothian EH9 3JZ, Scotland. on other planets, as viral entities are very primordial © 2013 Society for Applied Microbiology and John Wiley & Sons Ltd 644 S. O. L. Direito et al. (Forterre, 2006). WGA methods enable obtaining suffi- Results cient DNA for the analysis of viral communities (Kim and The effect of two WGA methods, MDA and pWGA on 16S Bae, 2011). rRNA gene-based community profiling was examined and MDA requires Bacillus subtilis bacteriophage phi29 compared with a control for which the DNA template was DNA polymerase and a mixture of random exonuclease- not subjected to WGA. Throughout the Results and Dis- resistant primers (hexamers) to perform isothermal cussion sections, ‘MDA’ and ‘pWGA’ sources refer to the amplification at low temperature (30°C) (Dean et al., use of template that was generated by these WGA 2002). MDA provides a more complete genomic cover- methods. ‘Control’ refers to the control, in which only PCR age and less biased amplification compared with other was used to generate community profiles. WGA methods (Lasken and Egholm, 2003; Vora et al., 2004). However, also MDA is subject to biases (prefer- ential amplification of certain sequences or genetic loci). Evaluation of WGA of an environmental sample The observed biases have been suggested to relate to DNA fragment length (Abulencia et al., 2006), GC The impact of MDA and pWGA on community represen- content (Bredel et al., 2005; Pugh et al., 2008; Yilmaz tation in a Cu-impacted soil sample was already evident et al., 2010), chromosome position (Lage et al., 2003; after principle coordinate analysis (Fig. 1A) and cluster Pugh et al., 2008) and stochastic effects originated analysis on denaturing gradient gel electrophoresis by amplifying from very low amounts of template (DGGE) profiles (Supporting Information Fig. S1A). As (Raghunathan et al., 2005). The causes for bias are still triplicates were highly reproducible (Control > 94%, MDA poorly understood and have not been systematically > 92% and pWGA > 82% similarity), two independently studied in a microbial ecology context, where the genetic derived DNA sources per treatment were subjected to composition of samples can be very complex due to the high-resolution profiling by pyrosequencing. After quality in general large diversity in species and the genes they filtering, a total of 8247 reads [1375 average per sample, contain. standard deviation = 985, range: 620–3204] with 615 Another drawback of MDA is that it can give rise to unique sequences were obtained, corresponding to 564 false-positive results because of contaminating exog- different operational taxonomic units (OTUs). Control enous DNA or endogenous template-independent samples (not subjected to WGA) and samples first sub- primer-primer interactions (Zhang et al., 2006). A recent jected to WGA (MDA and pWGA) revealed a similar primase-based WGA (pWGA) method is truly primer- species richness (Table 1); the numbers of OTUs [analy- independent, which would aid in diminishing false-positive sis of variance (ANOVA), F = 5.0, P = 0.11] and Chao1 results for low-biomass environments. pWGA employs species richness estimator based on incidence data bacteriophage T7 gene 4 protein (gp4) primase to synthe- (ANOVA, F = 0.27, P = 0.78) did not differ significantly. size primers on-template, excluding the need of adding However, the Shannon diversity index (which combines synthetic primers (Li et al., 2008). Gp4 has both primase species richness and abundances) did (ANOVA, F = 87.2, and helicase activity; the helicase opens the DNA double P = 0.002), with a slightly decreased index for pWGA, strand for both priming and polymerization, thereby compared with the control, and lowest value for MDA removing the need for a denaturing step (Vincent et al., (Table 1). 2004), and the primase generates the primers by recog- Reads were classified into 26 different phyla, and only nizing the sequences 3′-CTGG(G/T)-5′ or 3′-CTGTG-5′ a very small fraction remained unclassified (Control = (Li et al., 2008). So far only a few pWGA studies have 0.2% ± 0.1%, MDA = 0.6% ± 0.0% and pWGA = 0.1 been performed (Li et al., 2008; Schaerli et al., 2010; Tate ± 0.1%). Acidobacteria, Actinobacteria, Bacteroidetes, et al., 2012), all unrelated to microbial ecology. Chloroflexi, Firmicutes and Proteobacteria were the most Here, we systematically evaluated and compared represented phyla and an examination at the phyla level biases in microbial community profiles generated by MDA revealed an impact of WGA on the relative abundances of and pWGA. Species with lower GC content might be phyla. Samples subjected only to PCR (Control samples) over-represented after amplification because DNA with highlighted more Acidobacteria (21.9% ± 1.0%) than did higher GC content is more stable and difficult to denature pWGA- and MDA-based DNA sources (14.3% ± 1.3% and (Marmur and Doty, 1959). Excessive fragmentation of 12.7 ± 1.3% respectively) and also more Actinobacteria Gram-negative bacteria DNA can occur as these cells are (23.7% ± 2.5%) than did pWGA (16.5 ± 0.2%) and MDA easier to break during mechanic cell lysis than Gram- (3.1% ± 1.0%), while MDA strongly favoured the amplifi- positives (Schneegurt et al., 2003). Fragmented DNA is cation of Bacteroidetes (25.7% ± 0.4%) as compared with possibly more difficult to amplify. We present a detailed the control (1.9% ± 0.0%), and pWGA (4.3% ± 1.1%) and investigation of the MDA and pWGA methods for influence Firmicutes (24.4% ± 1.9%) as compared with the control of GC content, DNA fragmentation and DNA size. (10.0% ± 0.3%) and pWGA (21.2% ± 5.4%). © 2013 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology, 16, 643–657 Evaluation of bias induced by whole genome amplification 645 Fig. 1. Impact of WGA approaches on bacterial community representation for a Cu-polluted soil sample from the Wildekamp, the Netherlands.