18S Amplicon Sequencing: A Powerful Tool for Microbial Community Analysis

Microbial communities are ubiquitous, found everywhere from soil and water bodies to within living organisms. They play an indispensable role in ecosystem material cycling, energy flow, and the maintenance of human health. However, traditional microbial identification methods, such as culture-based isolation and microscopic observation, have significant limitations. Culture-based methods can only detect cultivable microorganisms, yet the majority of microbes are difficult to culture under laboratory conditions. While microscopic observation allows direct visualisation of microbial morphology, it falls short in accurately classifying and quantifying these organisms. Against this backdrop, 18S Amplicon Sequencing technology has emerged.

This article provides a comprehensive introduction to 18S Amplicon Sequencing technology, covering its principles and workflows, multidisciplinary application cases, data analysis methods, challenges and solutions, as well as prospects for future development, offering practical references for relevant researchers.

What is 18S Amplicon Sequencing

To fully grasp how 18S Amplicon Sequencing technology propels microbial community research forward, it's essential to have a clear understanding of the underlying scientific principles and specific operational procedures. Below is a detailed introduction.

Overview of the 18S rRNA Gene

The 18S rRNA gene is a component of the small ribosomal subunit in eukaryotes and boasts unique structural characteristics. It contains both conserved and variable regions. The conserved regions are highly consistent across species, providing a solid foundation for designing specific primers. On the other hand, the variable regions exhibit differences among various species, enabling the differentiation of distinct microbial types. Due to its widespread presence in eukaryotes and relatively stable structure, the 18S rRNA gene has become a crucial molecular marker for the classification and identification of eukaryotic organisms, widely applied in microbial community analysis.

18S Amplicon Sequencing Workflow

Workflow of 18S Amplicon Sequencing

• Sample Collection and Processing: Sample collection is a pivotal step in ensuring the accuracy of research findings. During collection, it's vital to fully consider the representativeness and homogeneity of the samples while avoiding external contamination. For instance, when collecting soil samples, remove the surface soil and gather samples from a specific depth range to minimise interference from environmental factors. Process the collected samples promptly to prevent alterations in the microbial community structure. Processing methods include freezing for preservation and drying, with the choice depending on the sample type and research objectives.
• DNA Extraction and Purification: Common DNA extraction methods include the phenol-chloroform extraction method and commercial kit methods. Although the phenol-chloroform extraction method can yield high-quality DNA, it's complex, time-consuming, and involves the use of toxic chemicals. Commercial kits, in contrast, offer simplicity and speed, but the quality and yield of extracted DNA may vary depending on the kit brand and sample type. Regardless of the method chosen, DNA purification is of utmost importance. Purification removes impurities introduced during extraction, such as proteins and polysaccharides, enhancing DNA purity and providing a high-quality template for subsequent PCR amplification.
• PCR Amplification: Designing specific primers is the linchpin of PCR amplification. Primers should exhibit high specificity and conservatism to accurately amplify the target 18S rRNA gene fragments. When designing primers, refer to known 18S rRNA gene sequences and utilise bioinformatics software for analysis and selection. Optimising PCR amplification conditions is equally crucial, involving adjustments to parameters like annealing temperature, cycle number, and template concentration. Appropriate amplification conditions can boost the yield and specificity of amplicons while reducing non-specific amplification and primer dimer formation.
• Sequencing and Data Analysis: The choice of a high-throughput sequencing platform directly impacts the accuracy and reliability of sequencing results. Currently, commonly used platforms include Illumina MiSeq and HiSeq. The Illumina MiSeq platform offers advantages such as relatively long read lengths and short run times, making it suitable for sequencing smaller fragments. The HiSeq platform, on the other hand, features high throughput and low cost, ideal for large-scale sample sequencing. The basic data analysis workflow encompasses quality control, OTU clustering, and species annotation. Quality control enhances data reliability by eliminating low-quality sequences, adapter sequences, and chimaeras. OTU clustering groups similar sequences together, reducing data complexity. Species annotation then classifies and identifies OTUs based on known database information, providing precise species details.

Application Fields of 18S Amplicon Sequencing

Leveraging its unique advantages, 18S Amplicon Sequencing technology demonstrates immense application potential across various fields. Below, we delve into its practical applications in different areas.

Case study 1: Targeting METTL5-Mediated m6A Modifications in 18S rRNA for Hepatocellular Carcinoma Therapy

In a study focusing on hepatocellular carcinoma (HCC), Peng et al. discovered that the 18S rRNA m6A methyltransferase complex METTL5-TRMT112 exhibits upregulated expression across multiple cancers and correlates with poor prognosis. By analysing m6A modifications on 18S rRNA, they unveiled METTL5's pivotal role in HCC tumorigenesis. The absence of METTL5-mediated 18S rRNA m6A modifications impairs 80S ribosome assembly, subsequently affecting the translation of genes involved in fatty acid metabolism. Furthermore, they identified ACSL4's role in METTL5-mediated fatty acid metabolism and HCC progression, suggesting that targeting both ACSL4 and METTL5 could synergistically inhibit HCC tumorigenesis, offering novel molecular targets for HCC therapy.

Case study 2: Universal Eukaryotic-Specific Primers for Biodiversity Research and Metabarcoding

Hadziavdic et al. focused on the 18S rRNA gene to design and validate a pair of "universal eukaryotic-specific" amplification primers, addressing a critical need for biodiversity research tools. The team began by extracting 50,000 eukaryotic 18S sequences from the SILVA database, systematically comparing hypervariable regions like V2, V4, and V9 for their information density. After identifying the V4-V5 region as the optimal target, they employed 18S-amplicon sequencing (454 platform) to amplify and sequence DNA from three distinct Norwegian North Sea sediment types-fine sand, coarse sand, and clay-generating over 500,000 high-quality reads with an average length of 383 bp.

The results confirmed the primers' effectiveness: the F-566/R-1200 combination covered approximately 80% of eukaryotic database entries while showing negligible amplification of prokaryotic sequences. In practical testing, the primers successfully detected multiple phyla, including Acanthocephala and Haplosporidia, in environmental samples, proving their ability to reveal eukaryotic diversity in complex ecosystems. This breakthrough provides a universal tool for metabarcoding studies, streamlining biodiversity assessments and supporting advancements in fields like drug discovery, where understanding microbial communities can uncover novel bioactive compounds.

18S Amplicon Sequencing Unveils Eukaryotic Biodiversity (Taerum et al., 2021)

Data Analysis Methods for 18S Amplicon Sequencing

Accurate data analysis is pivotal to unlocking the full value of research findings from 18S Amplicon Sequencing technology. Below, we explore the relevant data analysis approaches.

Popular Software and Tools

QIIME and mothur stand out as two widely used data analysis software options. QIIME boasts a user-friendly interface and a comprehensive suite of functional modules, supporting data analysis across multiple sequencing platforms and covering the entire workflow from quality control to diversity analysis. Mothur, on the other hand, is renowned for its robust statistical analysis and visualisation capabilities, enabling in-depth data mining and exploration. When selecting data analysis tools, it's essential to consider research objectives, data types, and personal skill levels comprehensively.

Data Analysis Workflow

• Quality Control: Quality control software like FastQC and Trimmomatic offers a comprehensive evaluation and preprocessing of sequencing data. FastQC generates detailed quality reports, visually presenting information on sequence quality distribution, GC content, and more. Trimmomatic, guided by user-defined parameters, removes low-quality sequences, adapter sequences, and chimaeras, enhancing data quality and reliability.
• OTU Clustering and Species Annotation: Common OTU clustering methods include UPARSE and CD-HIT. The UPARSE algorithm employs an iterative clustering approach to group similar sequences with high accuracy and efficiency. For species annotation, databases like SILVA and Greengenes facilitate the determination of OTU taxonomic information through sequence similarity comparisons.
• Diversity Analysis: Alpha diversity analysis evaluates microbial community diversity within individual samples, utilising metrics such as the Shannon index and Simpson index. Beta diversity analysis compares microbial community differences across samples, employing methods like PCoA and NMDS analysis. These analytical techniques empower researchers to gain profound insights into microbial community structure and function.

Steps for Data Analysis

Result Interpretation

Take a study on gut microbial communities as an example. Data analysis revealed significant differences in gut microbial composition between healthy and obese individuals. Obese individuals exhibited a marked increase in certain energy metabolism-related microbes, coupled with a relative decrease in beneficial microbes. Based on these findings, researchers hypothesised that gut microbial community imbalance might contribute to obesity development, providing direction for further research and therapeutic interventions.

Challenges and Solutions in 18S Amplicon Sequencing

Sample contamination represents one of the most prevalent issues encountered in 18S Amplicon Sequencing technology. During sample collection, processing, and experimental operations, exogenous microorganisms can be inadvertently introduced, compromising result accuracy. Primer bias is another significant concern; due to inherent limitations in primer design, certain microorganisms may exhibit low amplification efficiency, failing to accurately reflect their true abundance in samples. Additionally, the complexity of data analysis poses challenges for researchers, as processing and interpreting massive datasets demand specialised knowledge and skills.

To address sample contamination, rigorous experimental design is essential, incorporating aseptic techniques and negative controls. For primer bias mitigation, optimizing primer sequences and adjusting amplification conditions can reduce discrepancies. When tackling data analysis complexity, leveraging advanced algorithms and software—such as machine learning approaches and deep learning models—enhances accuracy and efficiency.

Future Prospects

Looking ahead, 18S Amplicon Sequencing technology holds promise for integration with single-cell sequencing techniques, enabling precise analysis of individual microbial cells and deeper insights into functional interactions within microbial communities. The adoption of novel sequencing platforms will further enhance throughput and accuracy while reducing costs, supporting large-scale microbial community studies.

In environmental microbiology, this technology will advance our understanding of microbial ecosystem roles, providing scientific foundations for ecological restoration and conservation efforts. In medicine, it will drive personalized treatment approaches by analyzing patients' unique microbial profiles. For ecology, the technology offers critical tools for biodiversity protection and sustainable ecosystem management.

References:

1. Peng H, Chen B, Wei W, Guo S, Han H, Yang C, Ma J, Wang L, Peng S, Kuang M, Lin S. "N6-methyladenosine (m6A) in 18S rRNA promotes fatty acid metabolism and oncogenic transformation." Nat Metab. 2022; 4(8):1041-1054. https://doi.org/10.1038/s42255-022-00622-9
2. Hadziavdic K, Lekang K, Lanzen A, Jonassen I, Thompson EM, Troedsson C. "Characterization of the 18S rRNA gene for designing universal eukaryote specific primers." PLoS One. 2014; 9(2):e87624. https://doi.org/10.1371/journal.pone.0087624