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The combination of DNA/RNA extraction with qPCR provides a fast, accurate, relatively cost-effective method for the sensitive quantification of gene and transcript abundances from a range of environmental samples, such as coastal sediments.
The initial nucleic acid extraction is the critical step to ensure a representative view of the microbial community present is achieved22. A number of limitations need to be considered for the extraction protocol: a) the achievement of total cell lysis, b) co-extraction of inhibitory compounds (e.g., humic acids or polyphenolics), c) contaminating DNA in the RNA fraction, d) rapid degradation of extracted nucleic acids when stored. Precautions must be taken in order to circumvent these limitations. For example, particular care has to be taken to ensure that the extraction of nucleic acids is optimized for the sample type (e.g., sediments, soil, wastewater, etc.). Significant improvements in nucleic acid yield and quality for both DNA and RNA can be achieved by carrying out preliminary experiments23. To minimize the effect of inhibitory compounds on PCR-based applications24, test a range of dilutions from the extracted DNA and RNA. To circumvent the rapid degradation of the extracted DNA/RNA from multiple freeze-thaw cycles and avoid possible loss of genetic information, store multiple small volume aliquots at -80 °C.
When carefully designed, qPCR is a robust, highly reproducible and sensitive method. Notably, the methods for amplification and standard curve construction outlined in this protocol can be adapted for any gene target of interest, including other phylogenetic markers (i.e., archaeal 16S rRNA, fungal 18S rRNA) or genes involved in important functions in the environment. Known limitations in the use of qPCR are: a) the generation of reproducible high-quality standard curve for absolute quantification, b) the choice of primer/probes and optimization of q-PCR assay conditions, c) the use of low quality/sheared nucleic acids, d) the choice of the working dilution of DNA/RNA to avoid inhibition. Moreover, it has to be considered that qPCR technique provides gene/transcript abundances which may not equate to cell counts: this is particularly the case when 16S and 18S rRNA genes are targeted, as microorganisms have different copy numbers of the ribosomal gene in their genome25.
Poor quality standard curves will result in inaccurate quantification of the gene of interest. It is good practice to store a stock of high concentration standards in small aliquots from which fresh standard curves can be made. Do not store standard curves, always make fresh dilutions from a stock of the highest concentration each time. For accurate quantification of environmental samples ensure the range of concentrations of the standard curve spans the expected Cp values of the unknown samples. When quantifying transcripts, construct the standard curve from RNA not double stranded DNA. When possible, quantification of samples to be directly compared should be completed within a single assay to avoid inter-assay variation20. This may not always be possible. Therefore, to compare gene abundances generated between assays it is advisable to have a random sub-set of samples replicated between assays. A wide selection of primer and probe sets are currently available for qPCR targeting microbial taxa and functional groups15. Careful consideration is needed when selecting these to ensure both maximal coverage and specificity for the target group. If the reaction efficiency of a qPCR assay is not satisfactory, troubleshooting starts with testing different thermal cycling conditions (as annealing time and/or temperature) and/or reaction conditions, e.g., varying primer-probe concentrations. Once the q-PCR assay and reaction conditions are optimized, always conduct an initial test of a range of DNA/cDNA dilutions to determine the appropriate template concentration. Select the dilution range resulting in the highest copy number as the optimal template dilution for further assays.
Currently, next-generation sequencing technologies efficiently shed light on microbial community structure and functions in a plethora of environments26,27,28. However, these datasets are often based on end-point PCR amplicon libraries and therefore provide only semi-quantitative assessments of the abundance of particular taxa. Hence, the capability of real time PCR-based technique to target specific taxonomic markers (from higher domain down to strain level) allows efficient validation of the results obtained by next-generation sequencing. Moreover, qPCR has been successfully used in combination with other microbial ecology molecular methods such as stable isotope probing (SIP) or phylogenetic/functional microarrays. Combined with the former tool, qPCR can be used to quantify the metabolically active community29,30. When combined with microarray analysis, qPCR provides key quantitative interpretation of phylogenetic marker-based and functional gene surveys of environments31,32.
Therefore, whether used alone or in combination with other (often process-based) assessments of ecosystem function, quantitative PCR is an essential tool for microbial ecologists in the exploration of the elusive link between microbial communities and ecosystem functions.