ITS Amplicon Sequencing: Technique, Workflow & Fungal Applications

Fungi play a pivotal role in ecosystems and human health, yet traditional identification methods—reliant on cultivation and morphological observation—often fail to detect "unculturable microorganisms" and struggle to classify closely related species accurately. ITS Amplicon Sequencing, targeting the Internal Transcribed Spacer (ITS) region of fungal ribosomal DNA (rDNA) and leveraging high-throughput sequencing, enables rapid, cultivation-free analysis of fungal communities at species/subspecies resolution, making it the global standard.

This article explores the biological properties of the ITS region, outlines the entire workflow from sample collection to data analysis, and demonstrates its applications through agricultural, medical, and industrial case studies. We compare leading analytical software tools, propose a standardized data interpretation framework, and discuss the potential of third-generation sequencing and AI to advance fungal research, emphasizing how multi-omics integration will drive holistic fungal studies.

What Is ITS Amplicon Sequencing?

Fungi, as indispensable decomposers and symbionts in ecosystems, directly influence carbon cycling efficiency, soil fertility, and plant health. In human health, they serve as vital industrial organisms (e.g., yeast) and pathogenic agents (e.g., Candida, Aspergillus). However, traditional fungal identification methods relying on morphology and cultivation face two critical limitations:

• Unculturable species blind spots: Most fungi cannot be isolated via pure culture, leading to underdetection. For instance, soil studies using traditional approaches detect just 1–5% of fungal diversity, despite the presence of tens of thousands of species.
• Morphological ambiguity: Closely related species exhibit similar traits, making species/subspecies-level classification challenging.

These bottlenecks underscore the urgent need for high-throughput, high-precision molecular tools.

The Revolutionary Breakthrough of ITS Amplicon Sequencing

ITS Amplicon Sequencing revolutionizes fungal community research by targeting the ITS1 and ITS2 regions within fungal rDNA. Combined with high-throughput sequencing platforms, it offers three key advantages:

• Cultivation-free: DNA extraction directly from environmental samples enables detection of all fungi, including unculturable species.
• Species-level resolution: Distinguishes closely related taxa, resolving classification gaps left by traditional methods.
• Scalability: Processes hundreds of samples per run, identifying thousands of operational taxonomic units (OTUs).

Today, this technique is the gold standard for fungal community analysis, applied across environmental science, agroecology, and medical microbiology.

In-Depth Explanation of ITS Amplicon Sequencing Technology

The ITS region serves as a "molecular fingerprint" for fungal classification due to its unique sequence variations, while the Amplicon Sequencing workflow standardizes operations to convert this molecular marker into quantifiable data. Together, they form a complete technical chain from sample collection to species-level resolution. Below, we systematically explore the biological foundations and experimental workflow of this technology.

ITS Region Overview

The Internal Transcribed Spacer (ITS) region, nestled within fungal ribosomal RNA (rRNA) gene clusters, serves as a cornerstone for modern fungal taxonomy due to its unique blend of evolutionary conservation and variability. Structurally, it comprises two subregions—ITS1 (spanning the gap between 18S and 5.8S rRNA genes) and ITS2 (located between 5.8S and 28S rRNA genes)—with lengths typically ranging from 100 to 1,000 base pairs, depending on the species. This duality makes it an ideal molecular marker: the flanking 18S, 5.8S, and 28S rRNA genes evolve slowly, providing stable anchor points for primer design during PCR amplification, while the intervening ITS1 and ITS2 regions accumulate mutations rapidly, reflecting recent speciation events.

ITS Amplicon Sequencing Workflow

• Sample Collection and Processing: Sample collection must align with research objectives, selecting appropriate matrices like soil, plant tissue, or water. For soil fungal studies, surface soil is typically collected, sieved through a 2 mm mesh after removing plant debris to minimize particulate interference. To isolate root-associated fungi, the "root-shaking method" effectively separates rhizosphere soil from root surface microbes. During processing, maintain strict temperature control and time efficiency to prevent DNA degradation.
• DNA Extraction and Purification: DNA extraction is critical for successful analysis. Commercial fungal DNA kits leverage chemical lysis and silica-membrane purification to efficiently remove inhibitors like humic acids, yielding high-purity DNA. For challenging samples, combine liquid nitrogen grinding with CTAB extraction to physically break cell walls and improve yield.
• PCR Amplification: ITS amplification uses fungal-specific primers targeting the ITS1 or ITS2 regions, covering most fungal taxa. Optimize key parameters: annealing temperature affects specificity, cycle number determines yield, and Mg²⁺ concentration regulates enzyme activity.
• Sequencing and Data Analysis: Purified amplicons undergo paired-end sequencing on Illumina MiSeq/NovaSeq platforms, generating millions of raw reads. The analysis pipeline includes quality filtering, OTU clustering, species annotation, and diversity metrics.

Process of ITS Amplicon Sequencing

Applications of ITS Amplicon Sequencing

ITS Amplicon Sequencing has proven indispensable in fields ranging from agriculture to clinical diagnostics, offering unparalleled precision in fungal community analysis. Below, three case studies demonstrate its transformative potential.

White et al. employed ITS amplicon sequencing to characterize fungal microbiome diversity. By analyzing ITS data from human gastric fluid samples via the CloVR-ITS pipeline, they identified Candida quercitrusa (present in all samples) and Aspergillus spp. (detected in select samples), confirming the method's ability to distinguish dominant fungal taxa. As a cloud-compatible tool, CloVR-ITS streamlines automated analysis, making comprehensive fungal community studies more accessible.

Utilizing ITS Amplicon Sequencing for Analyzing Fungal Microbial Communities (White et al., 2022)

Sommermann and colleagues analyzed agricultural soil fungal communities using ITS amplicon sequencing to assess how tillage methods, fertilization levels, and crop rotation patterns influenced fungal diversity. Their study revealed that sequencing both ITS1 and ITS2 regions detected 296 fungal genera and 3,398 operational taxonomic units (OTUs), with ITS1 showing higher OTU richness. Results indicated that tillage strategies significantly altered fungal community structures, while fertilization had a weaker, statistically insignificant impact. For instance, the genus Fusarium was strongly enriched under intensive fertilization in conservation tillage systems with preceding corn crops, whereas Phoma was associated with conventional tillage and preceding rapeseed crops. Additionally, many beneficial fungi, such as arbuscular mycorrhizal fungi (AMF), exhibited distinct responses to tillage practices. These findings provide a scientific basis for optimizing soil biodiversity management in agricultural ecosystems.

Applying ITS Amplicon Sequencing in Research on Fungal Communities in Agricultural Soils (Sommermann et al., 2021)

Data Analysis Methods for ITS Amplicon Sequencing

Raw data from high-throughput sequencing requires quality control, species annotation, and diversity analysis to transform nucleotide sequences into biologically meaningful community metrics. Below, we outline key tools and logical frameworks for effective data interpretation.

Analytical Approaches for Data from ITS Amplicon Sequencing

Popular Software and Tools: Functional Comparison and Selection Strategies

QIIME2 and mothur dominate as two leading analysis platforms. QIIME2 stands out for its user-friendly interface, supporting modular workflows (DADA2 denoising, Phyloseq visualization), ideal for beginners. In contrast, mothur offers flexible command-line operations, enabling customization of parameters like OTU clustering algorithms, catering to advanced users. For fungal data, combining USEARCH (for rapid OTU clustering) with the UNITE database (for species-level annotation) enhances both efficiency and accuracy.

Data Analysis Workflow: From Raw Data to Biological Insights

• Quality Control: Start by assessing raw read quality with FastQC, then trim low-quality bases (Q<20) and adapter sequences using Trimmomatic. In soil microbiome studies, this step typically raises the proportion of usable reads from 85% to 95%, ensuring reliable data for downstream analysis.
• OTU Clustering and Species Annotation: Employ DADA2 or UPARSE for OTU clustering. DADA2 generates amplicon sequence variants (ASVs) through denoising, achieving single-nucleotide resolution, while UPARSE clusters OTUs at 97% similarity for broader compatibility. Species annotation relies on UNITE's "Species Hypothesis" framework, accurately assigning over 90% of ITS sequences to species-level taxonomy.
• Diversity Analysis: Use alpha diversity indices (e.g., Shannon, Chao1) to measure species richness and evenness within samples, and beta diversity tools (e.g., Bray-Curtis distance, PCoA plots) to compare microbial communities across samples. For instance, in forest restoration research, beta diversity analysis revealed significant differences in fungal community structure between secondary and primary forests (R²=0.65, p<0.01), primarily driven by soil pH and organic matter content.

Result Interpretation: Translating Data into Biological Context

Interpret diversity metrics alongside environmental factors. High Shannon values often indicate ecologically stable systems, such as healthy soils with balanced microbial communities, while low Chao1 scores may signal species loss in polluted environments. Validate OTU annotations functionally—for example, correlate elevated abundances of pathogenic fungi like Fusarium with crop disease records, or link increased presence of beneficial arbuscular mycorrhizal fungi (AMF) with improved plant nutrient uptake.

Conclusion

With the rise of third-generation sequencing technologies like PacBio, ITS amplicon sequencing is transitioning from short-read (Illumina) to long-read (PacBio HiFi) approaches, resolving ITS sequence length variations and improving assembly accuracy. AI-driven tools, such as deep learning models, are optimizing long-read alignment and chimera removal, lowering technical barriers. Future advancements will integrate ITS sequencing with metagenomics and metabolomics, creating a "multi-omics" framework for fungal research. This holistic approach will provide deeper insights into ecological conservation, sustainable agriculture, and human health, addressing global challenges like climate change, food security, and infectious disease control.

ITS amplicon sequencing has become the gold standard for fungal community studies due to its high throughput and precision. From environmental monitoring to medical diagnostics, and from agricultural applications to industrial processes, this technology is propelling fungal research into the molecular era, offering critical solutions to worldwide issues.

References:

1. White JR, Maddox C, et al. "CloVR-ITS: Automated internal transcribed spacer amplicon sequence analysis pipeline for the characterization of fungal microbiota." Microbiome. 2013; 1(1):6. https://doi.org/10.1186/2049-2618-1-6
2. Sommermann L, Geistlinger J, et al. "Fungal community profiles in agricultural soils of a long-term field trial under different tillage, fertilization and crop rotation conditions analyzed by high-throughput ITS-amplicon sequencing." PLoS One. 2018; 13(4):e0195345. https://doi.org/10.1371/journal.pone.0195345