Overview
16S/18S/ITS amplicon metagenomic sequencing is frequently used to identify and differentiate microbial species. Short (<500 bp) hypervariable regions of conserved genes or intergenic regions, such as 16S of bacteria and archaea or 18S/ITS of fungi, are amplified by PCR and analyzed using next generation sequencing (NGS) technology. The resulting sequences are compared against microbial databases. Applications range from identifying a single species in pure culture and characterizing the microbiota of animals or plants, to comparing species diversity and population structure from various environmental sources or geographic regions. Our specialists can advise you on the appropriate analysis for your project.
Service SpecificationsApplications
- Species identification
- Gut microbial environment research
- Microbiota diversity
- Difference of species composition
Advantages
- Highly experienced: We have sequenced hundreds of thousands of samples, resulting in nearly 30 published articles.
- Outstanding service: We provide high-quality sequencing (with Q30 score ≥ 75%), an efficient standard workflow, fast turnaround time, and cost-effective bioinformatics analysis.
- Effective methodology: Our method features high amplification efficiency of sample DNA (> 95%).
- Comprehensive analysis: We provide expert bioinformatics analysis using the latest sequence databases and software, generating high-quality, publication-ready data.
Sample Requirements
| Sample Type | Amount | Volume | Purity |
|
Genomic DNA
|
≥ 200ng
|
≥ 12μL
|
OD260/280=1.8-2.0
|
Primer List of Amplicons
| Types | Region | Fragment Length | Primer sequences（5’- 3’） | |
| Bacterial 16S | V4 | 300 bp | 515F | GTGCCAGCMGCCGCGGTAA |
| 806R | GGACTACHVGGGTWTCTAAT | |||
| V3-V4 | 470 bp | 341F | CCTAYGGGRBGCASCAG | |
| 806R | GGACTACNNGGGTATCTAAT | |||
| V4-V5 | 450 bp | 515F | GTGCCAGCMGCCGCGGTAA | |
| 907R | CCGTCAATTCCTTTGAGTTT | |||
| V5-V7 (for endophytic) | 300-400 bp | 799F | AACMGGATTAGATACCCKG | |
| 1193R | ACGTCATCCCCACCTTCC | |||
| Archaeal 16S | V4-V5 | 400-500 bp | Arch519F | CAGCCGCCGCGGTAA |
| Arch915R | GTGCTCCCCCGCCAATTCCT | |||
| Archaeal 1106F | V8 | 300bp | 1106F | TTWAGTCAGGCAACGAGC |
| 1378R | TGTGCAAGGAGCAGGGAC | |||
| Fungal 18S | V4 | 350 bp | 528F | GCGGTAATTCCAGCTCCAA |
| 706R | AATCCRAGAATTTCACCTCT | |||
| V9 | 200 bp | 1380F | CCCTGCCHTTTGTACACAC | |
| 1510R | CCTTCYGCAGGTTCACCTAC | |||
| Fungal ITS* | ITS1 | 200-400 bp | ITS5-1737F | GGAAGTAAAAGTCGTAACAAGG |
| ITS2-2043R | GCTGCGTTCTTCATCGATGC | |||
| ITS2 | 380 bp | ITS3-2024F | GCATCGATGAAGAACGCAGC | |
| ITS4-2409R | TCCTCCGCTTATTGATATGC | |||
| ITS1-1F (for endophytic) | 200-400 bp | ITS1-1F-F | CTTGGTCATTTAGAGGAAGTAA | |
| ITS1-1F-R | GCTGCGTTCTTCATCGATGC |
Sequencing Parameter and Analysis Contents
| Platform Type | Illumina NovaSeq 6000 |
| Read Length | Paired-end 250 bp |
| Recommended Sequencing Depth | 30K/50K/100K raw reads |
| Standard Data Analysis |
|
Note: For detailed information, please refer to the Service Specifications and contact us for customized requests.
Project Workflow
Sampling
DNA from 49 healthy people, DNA from 50 people who has stable coronary artery disease (CHD) and 100 people who has ST segment elevation myocardial infarction (STEMI).
Sequencing Strategy:
Illumina platform, paired-end 250 bp
Conclusions:
- Intestinal-associated bacteria is enriched in systemic circulation. Because of the highest translocation products of intestinal bacteria in STEMI patients.
- Intestinal bacterial translocation products are associated with inflammation and left ventricular function.
- Intestinal flora translocation promotes cardiovascular events after STEMI.
References
Zhou X, Li J, Guo J, et al. Gut-dependent microbial translocation induces inflammation and cardiovascular events after ST-elevation myocardial infarction[J]. Microbiome, 2018, 6(1):66.
Plant growth and oil contamination alter the diversity and composition of bacterial communities in agricultural soils across China
Background:
The dynamics of microbial diversity in response to biotic and abiotic disturbances provide a sensitive indicator for evaluating the potential stability and degradation of soils in agro‐ecosystems. To determine the effect on soil bacterial communities of disturbances by plant growth (Robinia pseudoacacia) and oil contamination, we sequenced 16S rRNA genes using MiSeq technology. Abiotic and biotic disturbances, including treating the soils with sterile water, crude oil, and/or an invasive plant, altered the bacterial community structure in the soils, increased bacterial richness, and reduced bacterial dispersion.
Sampling
DNA extracted from twenty‐one soil samples collected from corn fields in 19 provinces of China.
Sequencing Strategy
Illumina platform, paired-end 250bp
Conclusions:
The microbial taxa exhibited differential responses to the plant growth and oil contamination, and the assembly of the core microbiome was changed. Moreover, the bacterial communities in the soils from warmer regions were more sensitive to the environmental changes.
The chemodiversity of paddy soil dissolved organic matter correlates with microbial community at continental scales
Background:
Paddy soil dissolved organic matter (DOM) represents a major hotspot for soil biogeochemistry, yet we know little about its chemodiversity let alone the microbial community that shapes it. Here, we leveraged ultrahigh-resolution mass spectrometry, amplicon, and metagenomic sequencing to characterize the molecular distribution of DOM and the taxonomic and functional microbial diversity in paddy soils across China. We hypothesized that variances in microbial community significantly associate with changes in soil DOM molecular composition.
Sampling
DNA extracted from soil samples that were collected from 88 flooded paddy sites across four typical Chinese rice-growing regions in 2014 and 2015.
Sequencing Strategy:
Illumina platform, paired-end 250 bp
Conclusions:
Our study demonstrates the continental-scale distribution of DOM is significantly correlated with the taxonomic profile and metabolic potential of the rice paddy microbiome. Abiotic factors that have a distinct effect on community structure can also influence the chemodiversity of DOM and vice versa.
Results of OTU Cluster & Annotation Analysis
Species Abundance Heatmap
Venn Diagram
Taxonomy Tree for A Single Sample
Rarefaction & Rank Abundance Curves by Individual Sample
β-diversity Heatmap
Principal Component Analysis (PCA) based in OTUs
UPGMA Cluster Tree based on Weighted Unifrac Distance
Cladogram of LEfSe Analysis
Relative Abundance on Phylum
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