QIAseq 16S/ITS Index Kits

High quality of reads and bases

Sequencing single amplicon libraries often yields results of low quality due to the reduced diversity in base composition in the primer regions (figure QIAseq 16S/ITS Panels employ phased primers to increases base diversity and quality scores, A and C). To overcome this issue, QIAseq 16S/ITS Panels use a "phased primer" approach (figure Structure of phased primers used in QIAseq 16S/ITS Panels), which incorporates 0–11 additional bases to the 5’-end of the 16S rRNA or ITS primer. The use of "phased primers"results ina shift in nucleotide balance and increases base diversity, leading to an increase in quality scores (figure QIAseq 16S/ITS Panels employ phased primers to increases base diversity and quality scores, B and D).

Efficient use of flow cell throughput

Because of the "phased primer" approach, libraries produced with QIAseq 16S/ITS Panels are sufficiently complex to eliminate the need for PhiX spike-in, thereby enabling the efficient utilization of flow cell throughput.

Low background noise

Bacterial DNA is present in every corner of our daily lives, resulting in an increased risk of contamination during handling and processing of biological samples. Furthermore, manufacturing and processing of enzymes and reagents can introduce exogenousbacterialDNAto the samples being studied. This contamination background decreases the robustness of bacterial profiling. QIAseq 16S/ITS Panels use low-bioburden reagents, which show very low levels of exogenous bacterial contamination in NTC runs (figure The QIAseq 16S/ITS Panels have very low levels of background contamination due to the use of reagents with low bioburden).

Low DNA input

QIAseq 16S/ITS Panels can be used with abacterial DNA inputranging from 1 pg to 1 ng, allowing users to profile bacterial communities in samples with low biomass (figure The QIAseq 16S/ITS Panels can be used with as little as 1 pg of input DNA). For profiling fungal communities/species, QIAseq 16S/ITS Panelscan detect0.01 ng of fungal DNA in a background of 1 ng of E. coli DNA.

Multiplexing

Each panel can be used to multiplex up to 96 samples on an IlluminaMiSeq run using the V3 sequencing chemistry at 2x300. The appropriate index kit is necessary to multiplex the required number of samples.

Data analysis

Aftersequencing, data is analyzed using QIAGEN Bioinformatics CLC Genomic Workbench and Microbial Genomics Pro Suite Module. A custom workflow, which can be further edited as needed, is availablefor automatingFASTQ file import, sample library demultiplexing, quality controlled filtering and trimming, OUT clustering and secondary bioinformatics analysis.QIAGEN Bioinformatics CLC Genomics Workbench with the Microbial Genomics Pro Suite Module enables researchers toproduce standardized reports on sample library quality metrics andorganism abundance tables, providing numerous options for downstream interactive analysis of microbiome profiles and reporting on experimental results. The Microbial Genomics Pro Suite Module also includes tools for calculating diversity metrics and for comparing the microbial profiles of different samples. CLC Genomics Workbench produces publication quality figures in formats that are readily useable for researchers to present their results.

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Introduction

The most common method used forprofiling microbial communities is sequencing the 16S ribosomal RNA (rRNA) gene and Internal Transcribed Spacer (ITS) regions for bacteria and fungi, respectively. Because of the universal distribution and conserved nature of the 16S rRNA and ITS genes, they are well-established genetic markers used for bacterial and fungal identification and classification.

16S and ITS genes

The 16S rRNA gene consists of both highly conserved and hypervariable regions (figure Structure of the bacterial 16S rRNA gene [top] and the fungal ITS region [bottom]). The conserved regions serve as primer binding sites for PCR amplification of the variable regions and the variable regions contain sequences that can be used for bacterial identification and classification.

The ITS region is situated between the small and large ribosomal RNA (rRNA) subunits. In eukaryotes, there are two ITS regions: ITS1 is located between the 18S rRNA and 5.8S rRNA genes, while ITS2 is located between the 5.8S rRNA and 28S rRNA genes (figure Structure of the bacterial 16S rRNA gene [top] and the fungal ITS region [bottom]). ITS regions have been shown to have the highest probability of successful identification for the broadest range of fungi.

Benefits of NGS for 16S rRNA gene and ITS sequencing

NGS provides a culture-free method for analyzing the microbial community within a biological sample. As the throughput of modern NGS systems has increased, it is not uncommon for libraries from multiple biological samples to be multiplexed on the same sequencing run, which has in turn enabled microbiology researchers to cost-effectively analyze hundreds of microbial communities in parallel. Determining the sequence of universal marker genes such as the 16S rRNA gene and ITS with NGS is a powerful method for surveying microbial communities as it can be used to:

1. Profile the majority of bacterial taxa residing in a sample in a single analysis
2. Execute comparative studies of different bacterial communities
3. Characterize bacteria that cannot be cultured
4. Classify microbes more quickly and accurately than traditional methods
5. Multiplex samples on the same sequencing run, providing a more cost-effective solution
6. Study complex microbiomes

Current challenges with 16S rRNA and ITS sequencing

Difficulties with NGS of 16S rRNA genes and ITS regions include:

1. Poor read and base calling quality as a result of reduced library complexity
2. Inefficient use of available throughput per library due to the requirement of considerable PhiX DNA
3. Reduced classification specificity for many bacterial taxa caused by the incomplete coverage of all 16S rRNA variable regions
4. High background noise because of contaminated reagents

Smart Control

QIAseq 16S/ITS Smart Control is a synthetic DNA that can be used as a positive control for library construction steps as it contains the primer binding sites from Escherichia coli. The hypervariable 16S rRNA region between the primer binding sequencesis replacedwithartificial sequences originating from Arabidopsis thaliana (figure Structure of the QIAseq 16S/ITS Smart Control DNA). The artificial sequences cannot be classified as bacterial or fungal, therefore any sequences that are classified are due to environmental contamination introduced during library construction.

QIAseq 16S/ITS Panels utilize a 2-stage PCR workflow. Starting with extracted DNA from bacterial communities, the 16SrRNA variable and ITS regions are enriched in the first-stage PCR using the phased primers. After a round of bead clean up, library adapters are added onto the ends of amplicons in the second-stage PCR. A second round of bead clean up generates libraries that can be quantified and sequenced (figure Workflow of the QIAseq 16S/ITS Panels). The recommended sequencing chemistry is V3 2x300.

Robust detection of bacterial species

The composition of a bacterial community, as based on the 16S rRNA gene, depends on the variable region analyzed. For example, Streptococcus mutans cannot be identified by sequencing variable regions V1V2, V2V3, V3V4 and V4V5. However, the comprehensive profiling of all variable regions with the QIAseq 16S/ITS Screening Panel enables the detection of this bacteria (figure Screening a panel of variable regions provides more robust bacterial profiling compared to screening only individual variable regions).