Resolving Species Level Changes in a Representative Soil Bacterial Community Using Microfluidic Quantitative PCR

Abstract

Rapid advances in genome sequencing technologies enable determination of relative bacterial abundances and community composition, yet, changes at the species level remain difficult to detect despite importance for certain ecological inferences. We present a method for extraction and direct quantification of species composition of a predefined multispecies bacterial community using microfluidic-based quantitative real-time PCR (qPCR). We employ a nested PCR approach based on universal 16S rRNA gene pre-amplification followed by detection and quantification of absolute abundance of bacterial species using microfluidic array of parallel singleplex qPCR reactions. Present microfluidic qPCR supports 2,304 simultaneous reactions on a single chip, while automatic distribution of samples and reactants minimizes pipetting errors and technical variations. The utility of the method is illustrated using a synthetic soil bacterial community grown in two contrasting environments – sand microcosms and batch cultures. The protocol entails extraction of total nucleic acid, preparation of genomic DNA, and steps for qPCR assessment of bacterial community composition. This method provides specific and sensitive quantification of bacterial species requiring only 2 ng of community DNA. Optimized extraction protocol and preamplification step allow for rapid, quantitative, and simultaneous detection of candidate species with high throughput. The proposed method offers a simple and accurate alternative to present sequencing methods especially when absolute values of species abundance are required. Quantification of changes at the species level contributes to the mechanistic understanding of the roles of particular species in a bacterial community functioning.

Microbial association networks give relevant insights into plant pathobiomes

“…Absolute quantification can be performed by coupling metabarcoding community data with total abundance data (Dannemiller et al 2014;Vandeputte et al 2017;Props et al 2017), developing microfluidic quantitative chips targeting pathobiome members (Kleyer et al, 2017;Crane et al, 2018) and by using meta-genomic approaches (Karasov et al 2019). These approaches will improve the reliability of pathobiome networks because they help reduce compositionality bias, i.e.…”

A Quantitative Sequencing Framework for Absolute Abundance Measurements of Mucosal and Lumenal Microbial Communities

“…[19][20][21][22][23] These methods require a purified DNA sequence of known concentration from an organism not present in the sample and an estimate of the initial sample concentration to determine the amount of exogenous DNA to spike-in. Another group of anchoring methods, such as those that use flow cytometry 24 , total DNA 25 , or qPCR [26][27][28] , measure the total concentration of cells, DNA, or amplicons to transform the relative abundances to absolute numbers. These methods have already demonstrated the value of quantitative microbiome analysis, yet microbiome researchers have not yet uniformly adapted these methods.…”

Peer Review #2 of "SpeciesPrimer: a bioinformatics pipeline dedicated to the design of qPCR primers for the quantification of bacterial species (v0.1)"

“…However, in order to work efficiently high-throughput qPCR systems use identical PCR chemistry and PCR conditions for all reactions taking place on a single chip. Therefore, existing qPCR assays are often not suitable and new primers have to be designed (Hermann-Bank et al 2013;Ishii et al 2013;Kleyer et al 2017).…”