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16S/18S/ITS Amplicon Metagenomic Sequencing

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 Specifications

Applications

  • 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


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Sample Type Amount Volume Purity
Genomic DNA
≥ 200ng
≥ 12μL
OD260/280=1.8-2.0

Primer List of Amplicons

Types Region Fragment Length Primer 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
  • Data quality control
  • OTUs cluster and phylogenetic relationship construction
  • Species annotation
  • Alpha diversity analysis
  • Beta diversity analysis
  • Ternaryplot
  • NMDS analysis
  • LefSE analysis
  • Metastats analysis
  • Species T-test analysis
  • MRPP, Anosim, Adonis, Amova analysis
  • Comparative analysis of alpha diversity indices
  • Comparative analysis of beta diversity indices

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 and annotation analysis


Species abundance heatmap


Venn diagrams


Taxonomy tree for single sample


Rarefaction curves & rank abundance curves by individual samples


Beta-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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