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NGS-Based Microbial Identification


Overview

CD Genomics provides high-resolution microbial identification using NGS technologies. Our service employs 16S/18S/ITS and metagenomic sequencing to accurately identify and characterize diverse microbial communities, including bacteria, archaea, fungi, and viruses. Advanced sequencing platforms ensure precise results and comprehensive analysis.

Our Advantages:
  • Allow to identify and characterize bacteria, eukaryotes, fungi, viruses, and mycoplasma.
  • Powerful microbial identification platforms utilizing multiple methods like NGS, MLST, Rep-PCR, and MicroSEQ®.
  • Efficient workflow and fast turnaround times.
  • Extensive experience in handling various samples.

What is the Use of NGS in Microbiology

Next-Generation Sequencing (NGS) ushers in a transformative era for microbiology by enabling a comprehensive analysis of microbial communities. This technology bypasses traditional methods, providing a direct and detailed view of microbial DNA without the need for extensive culturing processes.

  • Direct Sequencing of Microbial DNA: NGS bypasses culturing by sequencing genetic material directly from samples, enabling the detection of hard-to-culture microorganisms, including those in extreme environments.
  • In-Depth Microbial Profiling: NGS provides a detailed view of microbial diversity by sequencing whole genomes or specific genes like 16S rRNA, capturing a wide range of microorganisms including bacteria, viruses, fungi, and archaea.
  • Insights into Antibiotic Resistance and Pathogens: NGS identifies antibiotic resistance genes and pathogenic strains, revealing resistance mechanisms and pathogen profiles often missed by traditional methods.

What is NGS Bacterial Identification

NGS revolutionizes the realm of bacterial identification, unveiling the intricate tapestry of microbial species within a sample. Leveraging the robust analytical capabilities of the 16S rRNA gene, a highly conserved genetic marker ubiquitous in bacteria, NGS facilitates precise differentiation among a diverse array of bacterial taxa.

  • 16S rRNA Gene sequencing: The 16S rRNA gene serves as a pivotal molecular marker ubiquitous across all bacteria, thereby playing a crucial role in bacterial identification. NGS capitalizes on this gene, enabling direct extraction and sequencing of genetic material from samples. By comparing these sequences against comprehensive databases, NGS achieves high accuracy in identifying both known and novel bacterial species with remarkable precision.
  • Metagenomic sequencing: Metagenomic sequencing (mNGS) provides a comprehensive overview by sequencing the entire genetic content present within a sample. This approach extends beyond bacterial identification, encompassing the full spectrum of microorganisms, including viruses and fungi, while quantifying their relative abundances. Whether targeting elusive bacterial species or detecting unexpected non-bacterial pathogens, mNGS offers an exhaustive and detailed view of microbial communities.

The Pros and Cons of NGS in Microbial Identification

Pros

  • Comprehensive and High-Resolution Analysis: NGS reveals a wide variety of microorganisms, including those hard to culture, with high-resolution data on microbial diversity.
  • Rapid and Efficient: NGS speeds up microbial identification by allowing the sequencing of millions of DNA molecules simultaneously, crucial in clinical diagnostics.
  • Antibiotic Resistance Detection: NGS identifies antibiotic resistance genes directly from microbial DNA, aiding in treatment decisions and resistance management.

Cons

  • Cost and Complexity: High expenses related to sequencing equipment, reagents, and data analysis, making NGS financially demanding compared to traditional methods.
  • Interpretation Challenges: Complex interpretation of NGS data, especially in mixed samples, making it hard to identify the disease-causing pathogen.
  • Limited RNA Virus Detection: NGS struggles with RNA virus detection, requiring additional steps like reverse transcription, complicating the identification process.

Applications of NGS-Based Microbial Identification

The applications of NGS-based microbial identification include, but are not limited to, the following areas:

  • Environmental Monitoring: NGS serves as a powerful tool for scrutinizing microbial communities within environmental samples—be it soil, water, or air—providing a granular view of ecological interactions and biodiversity.
  • Public Health Surveillance: Within public health, NGS emerges as a critical instrument for outbreak monitoring and the surveillance of infectious disease dissemination, offering detailed genetic insights that facilitate swift and precise response measures.
Service Specifications

Introduction to Our NGS-Based Microbial Identification Service

CD Genomics offers advanced NGS-based microbial identification services, utilizing 16S/18S/ITS sequencing and shotgun metagenomic sequencing. Our services deliver precise taxonomic classification of microbial species in diverse communities and facilitate evolutionary and network analysis.

16S/18S/ITS sequencing provides high-resolution species identification for bacteria, archaea, and fungi, leveraging long-read sequencing technologies like PacBio SMRT and nanopore sequencing for detailed strain-level resolution.

Metagenomics enables comprehensive profiling by analyzing all microbial genomes in a sample, including bacteria, eukaryotes, viruses, and pathogens. This approach surpasses traditional 16S/18S/ITS sequencing in sensitivity, ensuring accurate detection of even rare microbial members.

NGS-Based Microbial Identification Workflow

The Workflow of NGS-Based Microbial Identification.

Technical Parameters

  • MiSeq PE300/PE250 or HiSeq PE250
  • PacBio's SMRT technology
  • 30,000 -100,000 tags per sample

Bioinformatics Analysis

16S/18S/ITS sequencing data analysis includes the following:

  • Data preprocessing
  • Species classification
  • Diversity analysis
  • Species difference analysis
  • Functional Analysis

Metagenomics sequencing data analysis mainly includes the following:

  • Sequencing data quality assessmentSpecies classification
  • Gene prediction
  • Species
  • Functional notes
  • CAG/MLG analysis
  • CNV analysis

Note: The above content includes only a portion of the bioinformatics analysis. For more information or to customize the analysis, please contact us directly.

16S/18S/ITS sequencing data analysis pipeline:

The Bioinformatics Analysis of NGS-Based Microbial Identification-16S/18S/ITS sequencing.

Metagenomics sequencing data analysis pipeline:

The Bioinformatics Analysis of NGS-Based Microbial Identification- metagenomics sequencing.

Sample Requirement

For 16S/18S/ITS sequencing:

  • Genomic DNA≥ 100 ng, Concentration≥1 ng/µL

For metagenomics sequencing:

  • Metagenome DNA≥ 500 ng, Concentration≥5 ng/µL
  • 1.8 < OD260/280 < 2.0, no degradation or contamination

Note: If you wish to obtain more accurate and detailed information regarding sample requirements, please feel free to contact us directly.

Deliverables

  • Raw sequencing data (FASTQ)
  • Clean data
  • Trimmed and stitched sequences (FASTA)
  • Quality-control dashboard
  • Statistic data
  • Your designated bioinformatics result report
Demo

Demo

Partial results of our NGS-based microbial identification service are shown below:

The NGS-Based Microbial Identification Results Display.

FAQs

NGS-Based Microbial Identification FAQ

Case Study

Case Study

Customer Case

Nutrient structure dynamics and microbial communities at the water–sediment interface in an extremely acidic lake in northern Patagonia
Journal: Frontiers in Microbiology
Impact factor: 4.0
Published: 12 February 2024

Find out more

Background

Bacterial communities in aquatic systems are vital for nutrient cycling and energy flow. They affect organic matter decomposition and element cycling at the sediment-water interface. Freshwater sediments, with high microbial biomass and diversity, play a key role in nutrient transformation. This study used 16S rRNA gene sequencing and metagenomic sequencing to analyze microbial diversity and nutrient dynamics in Lake Caviahue, focusing on bacterial roles in phosphorus cycling and community variations across different lake strata.

Materials & Methods

Sample preparation:

  • Water
  • Sediments
  • DNA extraction

Method:

  • NGS
  • Illumina HiSeq

Data Analysis:

  • Sequence quality and processing
  • De novo assembly
  • Diversity analysis

Results

In acidic Lake Caviahue, microbial biomass and diversity are higher in the bottom strata compared to the upper layers. The average microbial abundance was significantly greater in the metalimnion and bottom layer than in the epilimnion. Using targeted metagenomic analysis, it was found that microbial diversity increases from the top to the bottom strata. A microcosm bioassay showed that sediment and pore water bacteria contribute to nutrient retention and release, with significant differences in microbial community structure and diversity between test and control columns. Despite initial differences in microbial load, both columns showed increased microbial growth and similar trends in nutrient utilization over time.

Figure 1. Role of sediment and pore water bacterial communities in nutrient recirculation in Lake Caviahue. (Cuevas et al., 2024) Figure 1. Contribution of sediment and pore water bacterial community to nutrient recirculation of Lake Caviahue.

Figure 2. Conceptual model illustrating the biogeochemical cycling of nutrients, sulfur, and iron at the sediment-water interface in Lake Caviahue. (Cuevas et al., 2024)Figure 2. Conceptual model of the biogeochemical cycling of nutrients, sulfur, and iron at the sediment-water interphase of Lake Caviahue.

Conclusions

In Lake Caviahue, bacterial abundance and diversity are highest in the bottom strata and peak in autumn. Seasonal changes affect pH, temperature, and nutrient levels. Both bacteria and algae influence nutrient cycling, with a significant syntrophic relationship between them. Sediment microorganisms play a key role in nutrient utilization and mobilization.

References

  1. Petrosino J F, Highlander S, Luna R A, et al. Metagenomic pyrosequencing and microbial identification. Clinical chemistry, 2009, 55(5): 856-866.
  2. Cuevas M, Francisco I, Díaz-González F, et al. Nutrient structure dynamics and microbial communities at the water–sediment interface in an extremely acidic lake in northern Patagonia. Frontiers in Microbiology. 2024, 15:1335978.
* For Research Use Only. Not for use in diagnostic procedures or other clinical purposes.



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