Each month, our microbiome team at QIAGEN presents a series of webinars on microbial sample preparation, antibiotic resistance, microbiome research methods and host-pathogen interactions. We zeroed in on our microbiome webinar series to find the most commonly asked questions, and answered them for you.
What sample types can I use?
Whether you are working with microbial qPCR detection or next-generation sequencing (NGS), you can use a variety of sample types and metagenomics samples. The main decision you have to make is which isolation kit to use for your particular sample type. You must take into account any inhibitors that might be present in your sample and thus complicate your PCR reaction, or contaminating host DNA that could waste your sequencing capacity.
For more information, download our webinar on microbial sample isolation.
Is the gut the most extensive human microbiome? If not, what is?
Based on the 18 body sites studied in the Human Microbiome Project (HMP), you could say that the gut has the most abundant amount of species compared to other sites. Huse, Ye, Zhou and Fodor (2012) followed those 18 body sites from 200 individuals and found that tested stool samples had the highest richness of any body site, with oral sites coming in second.
When should I use qPCR over NGS, or vice versa?
This depends on the scope of your project. If you are attempting to identify unknown or novel bacteria, then 16S or shotgun metagenomic sequencing is the best option. Once you have a sequence, you can develop a qPCR assay for easier, more rapid detection at a lower cost.
How can you measure qPCR assay sensitivity in regards to microbial detection?
There are two methods you can use to define assay sensitivity, the Limit of Detection (LOD) or the Lower Limit of Quantification (LLOQ). With LOD, you are finding the lowest amount of template that can be detected compared to no analyte. With LLOQ, you are looking at the standard curve and finding the lowest concentration of template that is within the linear range of the assay. This gives you the number of gene copies that an assay can quantitatively detect.
QIAGEN uses the LLOQ to define the assay sensitivity. The majority of our assays have sensitivity below 100 gene copies, but you can find the sensitivity of any specific assay or array on the product page or array sheet.
How many antibiotic resistance gene targets can the arrays detect?
The Antibiotic Resistance Genes Microbial DNA qPCR Array includes assays to detect 87 antibiotic resistance genes belonging to aminoglycoside, β-lactam, erythromycin, fluoroquinolone, macrolide-lincosamide-streptogramin B, tetracycline, vancomycin and multidrug resistance classifications. If you’d like to learn more about how this array can help you effectively detect antibiotic resistance genes in your research samples, view this slide deck:
- Does the antibiotic resistance genes array have a good coverage of multiple gene subtypes too?
This array has good coverage of multiple gene subtypes, and you can get more information such as which gene each assay is detecting, what subtypes are also detected, and each assay’s sensitivity and cross-reactivity by downloading the assay table. You can find the assay table for any array on the microbial array page.
What is the difference between microbial identification and profiling?
Identification is determining the microbe’s presence or absence in your sample which requires running a No Template Control (NTC) during your analysis. Profiling is determining the microbe’s relative expression in two or more experimental conditions, for which you will need to run a reference sample and a normalizer.
What types of controls are included with the microbial arrays?
The arrays have integrated controls for measuring the presence of bacteria and fungi, to detect host DNA and to measure the PCR reaction itself. The controls occupy 6 wells per plate per sample:
- The Host1/Host2 assays measure the human or mouse gDNA in your sample, which can be used to normalize for relative microbial quantification.
- The Pan A/C – or Pan-Aspergillus/Candida – assay is used to look for the presence of fungal rRNA in your sample.
- The PanB1 and PanB2 assays are included to detect a broad range of species to confirm that bacterial DNA is present in a sample. For this, we designed the assay to evolutionarily-conserved regions of the 16S rRNA gene.
- The last control assay is the positive PCR control, or the PPC. This is meant to monitor the efficiency of the PCR reaction and to find if any inhibitors are present. On each array, the PPC is a reaction between an artificial DNA sequence and the corresponding primer.
If you are performing an identification experiment, you also want to run an NTC along with your test samples.
Do you have an array for my research area?
Currently, there are 18 cataloged arrays available with pre-curated content based on research areas such as health, food testing and environmental sample analysis. You can review the species or gene lists for all 18 arrays below:
If you cannot find an array that applies to your area of interest, you can also design a custom array to include the species or genes of your choice. The one recommendation we make is to include the controls on your custom design that are already integrated into the cataloged arrays. Contact us for more information on creating your custom array.
Can the qPCR arrays and assays be used across various hosts?
Yes, this is a possibility. The assays are not specific to the host species, but to the microbial species or antibiotic resistance or virulence factor gene.
Do you have any recommendations for metagenomic NGS data analysis?
Yes, if you are doing metagenomic sequencing, you can use the QIAGEN Microbial Genomics Pro Suite, which expands upon the CLC Genomics Workbench.
Have any additional questions about microbiome research? Ask us in the comments section!
One additional – and also the most common – request from our webinar attendees is for a copy of the microbial assays list, which includes a comprehensive portfolio of the 580+ assays offered for microbial detection. You can download the complete list here:
- Huse SM1, Ye Y, Zhou Y, Fodor AA. (2012). A core human microbiome as viewed through 16S rRNA sequence clusters. PLoS One. 7, e34242. (Link)