Novogene Origin Real Test Data Debut: Full Process Monitoring of 16S Sequencing, Initiating the Establishment of Amplified Sequencing Standard Management Specifications and a New Perspective on Traceability

Introduction

Amplicon sequencing is a vital technique used for studying microbial communities in diverse environmental samples, ranging from soil and water to gastrointestinal contents. This method, which involves PCR amplification on target regions (16S, 18S, ITS) and subsequent analysis of sequenced PCR products, plays a crucial role in exploring microbial diversity and community composition differences. Its applications extend to environmental monitoring, health, ecology, species evolution, and various other fields.

Notably, Novogene, a genetic technology product and service provider founded in China 12 years ago, continues to serve scientists globally. With sequencing laboratories distributed worldwide, including overseas labs in the United States, the United Kingdom, Singapore, Germany and Japan, Novogene offers professional and comprehensive sequencing and technical support services. Upholding its values of "Professionalism, Innovation, Integrity, and Partnership" Novogene is committed to providing high-quality genetic technology products and services in the future as showcased with latest development of amplicon full process monitoring which will be described in depth in this blog.

Latest Development of Amplicon Sequencing Monitoring in Novogene

In the experimental process of amplicon sequencing, the meticulous assurance of contamination absence in reagents and operational steps is paramount. This precautionary measure is essential for preventing false negatives or false positives, ensuring a more accurate reflection of sample community composition and structure. It significantly enhances the repeatability and reliability of experiments.

Currently, many companies implement controls solely at the initiation of the amplification stage, lacking the capability to identify negative and positive controls for detecting exogenous microbial contamination or operational process issues. Addressing this gap, Novogene introduces sample internal control quality management tools in the amplicon experiment process. Each production batch is independently matched with negative and positive controls, beginning from the PCR amplification stage. This comprehensive approach accompanies client project samples through the entire process, including amplification, library construction, sequencing, and bioinformatics analysis. It ensures real-time data monitoring, contamination source identification, and data quality assurance, providing the highest quality and reliable amplicon sequencing and data analysis services.

1. Introduction to Indicators

For accurate results, it’s advisable to conduct the experiment with multiple biological replicates while simultaneously incorporating positive and negative controls. These controls play a pivotal role throughout the entire experiment and bioinformatics analysis alongside regular samples, serving as essential benchmarks to evaluate the standardization of the amplicon sequencing process.

Fig 1. Each batch includes independent negative and positive controls

The typical process for amplicon projects involves DNA extraction, PCR amplification, library construction, and sequencing. Here’s a breakdown of the detailed steps:

Fig 2. Amplicon sequencing workflow

(1) DNA extraction:

We kick off the process by employing targeted extraction methods on various customer-sent samples, such as plant tissues, animal tissues, intestinal contents, feces, and environmental samples. This ensures the acquisition of genomic DNA.

(2) PCR amplification:

After extracting DNA from the samples, we set up a PCR system for the amplification process. Following a thorough quality check of the PCR products, we proceed with purification and quantification steps. The samples are then blended in equal proportions based on the concentration of PCR products. Subsequently, we conduct gel electrophoresis using agarose gel to detect and recover the target bands.

(3) Library construction and sequencing:

Moving forward, we construct libraries. After quantification using Qubit and qPCR, the qualified libraries undergo sequencing using Illumina NovaSeq.

1.1 Positive Control

In Novogene’s original amplicon workflow, we choose the positive control from artificially synthesized microbial community standard products. The taxonomic status and proportions of all species undergo thorough quantification and determination. For instance, one of the positive control standards employed in the current process is the Microbial Community DNA Standard II (ZymoBIOMICS, Catalog No. D6311), widely recognized in mainstream literature. This standard encompasses 9-10 microbial species and is applicable for both 16S rRNA gene sequencing and 18S rRNA gene sequencing. The specific species composition and proportions are outlined in the table below.

Fig 3. 16S rRNA and 18S rRNA gene composition among specific species

The calculation formula for positive control species is as follows:

Adding a positive control offers several advantages:

(1) Species deviation calculation:

In microbial research, the primary goal is to identify the microbial composition in a given sample. Following wet lab experiments and bioinformatics data analysis, the proportions of various species in the annotation results are compared with the composition of standard controls. This process allows for the calculation of species deviations.

(2) Ensuring high-quality deliverables:

Thanks to the exceptionally high purity of standard controls, any foreign species identified in the analysis results with a proportion exceeding 0.01% triggers an investigation into the workflow [1]. This prompt investigation facilitates the swift identification of the cause, ensuring the quality of deliverables.

(3) Clearly identifiable sources of contamination for traceability and investigation:

Significant deviations between the calculated proportions of species and the theoretical composition indicate potential sources of contamination. These may include contamination during the sample preparation process, the generation of chimeras, errors during sequencing, or issues in the bioinformatics workflow. Based on the specific deviations observed for each species, a targeted identification of the source can be conducted.

1.2 Negative Control

In the negative control, a low proportion of raw read output signals manageable contamination in the current workflow. This aligns with baseline results obtained when no measurable positive outcomes are generated.

The calculation formula for negative control output is as follows:

In most cases, negative control values are considered background values. Accurate sequencing results that reflect the true species composition of the samples are achievable only when background noise is minimal.

Currently, several studies have integrated both positive and negative controls. For example, the Scripps Institution of Oceanography conducted a study involving 384 amplicon sequencing samples targeting the 16S V4 region. They used Zymo’s standard as a positive control, performing amplification and library sequencing alongside fish tissues, seawater, and sediment samples to ensure the accuracy of the library sequencing process [1-2]. Similar studies on the rumen microbiome [3], gut microbiome [4], etc., incorporated positive controls to guarantee that the analysis results accurately reflect the true species composition. Likewise, various amplicon studies incorporated negative controls into the experimental process, considering them a crucial criterion for evaluating data accuracy [5-8].

2. Debut of Internal Control Metrics Real Test Data from Novogene

Employing an integrated workflow featuring internal negative and positive controls, Novogene has carried out a comprehensive six-month series of data tests, delivering exceptionally impressive results. The following illustrates an example of monthly monitoring data:

Fig 4. Proportion of species in positive control standard

Fig 5. Negative control raw reads output situation

Fig 6. 142 negative control and 142 positive control samples situation

The chart above presents a total of 142 negative control and 142 positive control samples. Among them, the positive control standard shows an average species proportion of 99.7 %, with a median of 99.8 %. Conversely, the negative control averages a raw reads output of 96, with a median of 1.

In essence, incorporating laboratory standard negative and positive control samples throughout the entire sample sequencing process enables the continuous monitoring of potential contamination in reagents, materials, and human operations. It also ensures the detection of any potential cross-contamination between samples. Novogene’s laboratory adheres to stringent operating procedures, maintains clean instruments and equipment following SOPs, and regularly trains laboratory personnel on operational procedures. The existing processes undergo continuous optimization to accurately pinpoint potential sources of sample contamination, thereby ensuring the precision of experimental results and upholding the credibility of scientific research.

Reference

[1] ZymoBIOMICS Microbial Community DNA Standard II (Log Distribution). (n.d.). Zymo Research International. https://zymoresearch.eu/products/zymobiomics-microbial-community-dna-standard-ii-log-distribution#:~:text=ZymoBIOMICS%20Microbial%20Community%20DNA%20Standard%20II%20%28Log%20Distribution%29,extracted%20from%20pure%20cultures%20of%20the%20ten%20microbial

[2] Minich, J. J., Humphrey, G., Benitez, R. A. S., Sanders, J., Swafford, A., Allen, E. E., & Knight, R. (2018). High-Throughput Miniaturized 16S rRNA Amplicon Library Preparation Reduces Costs while Preserving Microbiome Integrity. mSystems, 3(6), e00166-18. https://doi.org/10.1128/mSystems.00166-18

[3] McGovern, E., Waters, S. M., Blackshields, G., & McCabe, M. S. (2018). Evaluating Established Methods for Rumen 16S rRNA Amplicon Sequencing With Mock Microbial Populations. Frontiers in microbiology, 9, 1365. https://doi.org/10.3389/fmicb.2018.01365

[4] Arfken, A. M., Frey, J. F., Carrillo, N. I., Dike, N. I., Onyeachonamm, O., Rivera, D. N., Davies, C. P., & Summers, K. L. (2023). Porcine fungal mock community analyses: Implications for mycobiome investigations. Frontiers in cellular and infection microbiology, 13, 928353. https://doi.org/10.3389/fcimb.2023.928353

[5] Pjevac, P., Hausmann, B., Schwarz, J., Kohl, G., Herbold, C. W., Loy, A., & Berry, D. (2021). An Economical and Flexible Dual Barcoding, Two-Step PCR Approach for Highly Multiplexed Amplicon Sequencing. Frontiers in microbiology, 12, 669776. https://doi.org/10.3389/fmicb.2021.669776

[6] Pjevac, P., Hausmann, B., Schwarz, J., Kohl, G., Herbold, C. W., Loy, A., & Berry, D. (2021). An Economical and Flexible Dual Barcoding, Two-Step PCR Approach for Highly Multiplexed Amplicon Sequencing. Frontiers in microbiology, 12, 669776. https://doi.org/10.3389/fmicb.2021.669776

[7] Brandt, J., & Albertsen, M. (2018). Investigation of Detection Limits and the Influence of DNA Extraction and Primer Choice on the Observed Microbial Communities in Drinking Water Samples Using 16S rRNA Gene Amplicon Sequencing. Frontiers in microbiology, 9, 2140. https://doi.org/10.3389/fmicb.2018.02140

[8] Frau, A., Kenny, J. G., Lenzi, L., Campbell, B. J., Ijaz, U. Z., Duckworth, C. A., Burkitt, M. D., Hall, N., Anson, J., Darby, A. C., & Probert, C. S. J. (2019). DNA extraction and amplicon production strategies deeply inf luence the outcome of gut mycobiome studies. Scientific reports, 9(1), 9328. https://doi.org/10.1038/s41598-019-44974-x