16S rRNA gene sequencing is an amplicon-based sequencing method that is used to identify and classify bacteria present in bulk and complex biological samples. This method uses the highly conserved nature of the 16S ribosomal RNA (rRNA) gene present in all prokaryotes that also contains variable regions that differentiate between species. The use of 16S rRNA was first introduced by Carl Woese and George E. Fox in 1977.
Traditional culture-based methods require laborious and time-consuming isolation processes to identify species in bulk samples which can detect only a small fraction of microbial species. The development of 16S rRNA as markers for the identification of organisms along with the development of next-generation sequencing (NGS) techniques has allowed efficient and rapid study of numerous samples. Many sequences from previously uncultured species have been identified using 16S rRNA sequencing.
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What is the 16S rRNA Gene?
- 16S rRNA gene sequence is the most commonly used genetic marker for studying bacterial taxonomy and phylogeny.
- Ribosomes are biological structures involved in protein synthesis that contain two subunits made up of proteins and ribosomal RNA (rRNA). rRNA translates the information in mRNA (messenger RNA) into the proteins.
- In prokaryotes, ribosomes are composed of a 30S subunit and a 50S subunit which forms a complete 70S ribosome. S is the Svedberg unit which is a measure of sedimentation rate. The 30S subunit contains 16S rRNA and 21 proteins.
- The 16S rRNA gene is about 1500 base pairs long and contains variable regions scattered between conserved regions. The conserved regions allow for universal amplification, while the variable regions allow distinction between specific microorganisms. These regions are particularly useful for identifying and classifying bacteria.
- Conserved regions are similar across different bacterial species, making them ideal targets for universal primers that can amplify the 16S rRNA gene from a wide range of bacteria.
- Variable regions exhibit sequence diversity among different species which allows the differentiation and identification of bacteria within different microbial environments. They are used for the phylogenetic classification of different microbial populations. The 16S rRNA gene has nine hypervariable regions (V1-V9).
Principle of 16S rRNA Gene Sequencing
The principle of 16S rRNA gene sequencing is based on amplicon sequencing that targets specific regions of the genome. 16S rRNA gene sequencing uses the genetic information in the 16S rRNA gene to identify and classify bacterial and archaeal species. This gene can be used as a marker for identifying these microorganisms. All bacteria and archaea contain the 16S rRNA gene which is highly conserved. The process of 16S rRNA gene sequencing involves DNA extraction, PCR amplification of the 16S rRNA gene, sequencing, and bioinformatics analysis.
Steps Involved in 16S rRNA Gene Sequencing
The 16S rRNA gene sequencing involves the following 5 steps:
1. Sample Collection
- At first, the microbial samples are collected from the environment of interest including sources such as soil, water, or biological samples like the gut microbiome.
- Different samples are collected using different procedures. Sample collection and processing should be done in a way to prevent contamination.
- Before the isolation of DNA, contaminants should be removed using several pretreatment methods including the use of enzymes, heat, or physical methods.
2. DNA Extraction
- Once samples are collected, microbial DNA is extracted using several extraction methods.
- DNA extraction involves the use of several chemical and physical methods to isolate the DNA. This involves physical disruption methods like sonication, chemical lysis using detergents and enzymes, and purification steps.
3. PCR and Library Construction
- This includes preparing the DNA for sequencing.
- At first, the 16S rRNA gene is amplified using polymerase chain reaction (PCR). Optimizing PCR conditions and selecting appropriate primers is crucial to prevent non-specific amplification and ensure accurate results.
- After amplification, the DNA is processed to create a library for sequencing. This involves fragmenting the DNA into shorter segments and attaching adaptors to the fragments.
- The library is then purified to remove excess adaptors and primers, ensuring uniform fragment size for sequencing.
4. Sequencing
- The library undergoes high-throughput sequencing using platforms such as Illumina, Ion Torrent, Oxford Nanopore, or PacBio.
- DNA libraries are amplified and sequenced, generating millions of short DNA sequences simultaneously. The raw sequence data will go through quality control and bioinformatics analysis to identify and classify the microbial communities present in the sample.
5. Data Analysis
- After sequencing, the next step is data analysis. The sequencing data is processed using bioinformatics tools to analyze the data.
- This includes steps such as trimming reads to ensure quality, removing sequences not belonging to the target domain, clustering reads into Operational Taxonomic Units (OTUs), aligning OTUs with a reference database, and assigning taxonomic identities to the OTUs.
- Tools like QIIME, MOTHUR, and USEARCH-UPARSE are commonly used. These pipelines provide tutorials and user-friendly interfaces.
- Once the sequencing results are matched to the databases, statistical methods are used to find patterns and relationships between different samples.
Advantages of 16S rRNA Gene Sequencing
- The 16S rRNA gene is conserved among bacteria and archaea but exhibits enough sequence variation to distinguish between species. This makes it a powerful tool for identifying and comparing microbial communities.
- Unlike traditional culture-based techniques, 16S rRNA gene sequencing can study microbial communities directly from environmental samples, including those with unculturable microbes.
- High-throughput sequencing technologies allow for the simultaneous sequencing of thousands of 16S rRNA gene fragments. This allows large-scale analyses of microbial communities.
- Traditional laboratory culture methods depend on phenotypic characteristics and reactions which can be subjective and are prone to contamination. 16S rRNA gene sequencing protocols include quality control procedures and validated bioinformatics pipelines to ensure accurate results.
Limitations of 16S rRNA Gene Sequencing
- The 16S rRNA gene can only differentiate bacteria to certain taxonomic levels. Closely related bacterial species often share high sequence similarity in their 16S rRNA genes making it difficult to distinguish them accurately. It fails to accurately resolve species-level differences.
- High sequence similarity in the 16S rRNA gene does not necessarily imply accurate species identification.
- Processing and analyzing complex sequencing data requires bioinformatics tools and knowledge.
- This method generally provides lower taxonomic resolution compared to shotgun sequencing.
- Since 16S rRNA gene sequencing targets only a single gene, it cannot identify the functions of the microbial community.
Applications of 16S rRNA Gene Sequencing
- 16S rRNA gene sequencing can be used to determine the species composition and community structure of microbial populations within complex biological samples. This helps us study microbial diversity and identify how microbial communities interact within their ecosystems.
- In clinical microbiology, 16S rRNA gene sequencing is used to study microbial communities related to diseases. This helps in understanding disease mechanisms and developing targeted treatments.
- It can be used to identify and classify microorganisms in various environmental samples such as soil and water.
- It can also be used to study microorganisms in fermented foods and identify food-borne pathogens. It helps ensure food safety by identifying microbial communities in food products.
- It can be used in agriculture to improve crop health by studying the microbial communities associated with soil and plants.
- It is used to study the human microbiome to understand microbial diversity and its impact on health.
- Comparison of the bacterial 16S rRNA sequence can also be used to discover novel species.
- Examples of 16S rRNA gene sequencing applications include the Human Microbiome Project for characterizing human-associated microbial communities, the Global Ocean Sampling Expedition for exploring oceanic microbial diversity, soil microbiome studies, studying antibiotic resistance in hospitals, and tracking microbial communities in wastewater treatment.
References
- 16S and ITS rRNA Sequencing | Identify bacteria & fungi with NGS (illumina.com)
- 16S rRNA Gene Sequencing for identification, classification and quantitation of microbes – LC Sciences – Technologies for Genomics & Proteomics Discoveries
- 16S rRNA Sequencing Guide (microbiomeinsights.com)
- 16S rRNA: Gene, Sequencing and Importance – Genetic Education
- 16s_sequencing.pdf (uab.cat)
- D’Amore, R., Ijaz, U.Z., Schirmer, M. et al. A comprehensive benchmarking study of protocols and sequencing platforms for 16S rRNA community profiling. BMC Genomics 17, 55 (2016). https://doi.org/10.1186/s12864-015-2194-9
- Mastering 16S rRNA Sequencing: A Comprehensive Guide to Techniques and Applications – Omics tutorials
- Muhamad Rizal, N. S., Neoh, H. M., Ramli, R., A/L K Periyasamy, P. R., Hanafiah, A., Abdul Samat, M. N., Tan, T. L., Wong, K. K., Nathan, S., Chieng, S., Saw, S. H., & Khor, B. Y. (2020). Advantages and Limitations of 16S rRNA Next-Generation Sequencing for Pathogen Identification in the Diagnostic Microbiology Laboratory: Perspectives from a Middle-Income Country. Diagnostics (Basel, Switzerland), 10(10), 816. https://doi.org/10.3390/diagnostics10100816
- Pichler, M., Coskun, Ö. K., Ortega-Arbulú, A. S., Conci, N., Wörheide, G., Vargas, S., & Orsi, W. D. (2018). A 16S rRNA gene sequencing and analysis protocol for the Illumina MiniSeq platform. MicrobiologyOpen, 7(6), e00611. https://doi.org/10.1002/mbo3.611
- Sanschagrin, S., & Yergeau, E. (2014). Next-generation sequencing of 16S ribosomal RNA gene amplicons. Journal of visualized experiments: JoVE, (90), 51709. https://doi.org/10.3791/51709