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Microbial Metagenomics

Microbial Metagenomics

Overview

Our metagenomics platform aims to study novel genes, microbial pathway, microbial diversity, evolution, functional annotations, and correlation analysis by utilizing the next/third generation sequencing technology. Our scientists utilize this platform to obtain fast, accurate, and cost-effective results.

Our Advantages:

High Depth of Coverage: We provide sequencing with high coverage, enabling detailed species identification and functional gene analysis.
Integrated Functional Analysis: Our services include not just taxonomic profiling but also functional annotation, allowing you to explore metabolic pathways and interactions.
Diverse Sample Compatibility: We accept a wide range of sample types, including soil, water, and biological tissues, catering to various research fields.
User-Friendly Data Reports: Results are delivered in clear, actionable formats, making it easy for researchers to interpret and utilize the data in their studies.

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What is the Microbial Metagenome

The microbial metagenome represents the complete set of genetic material found in a particular environment, including a variety of microorganisms like bacteria, archaea, fungi, and viruses. Unlike traditional microbiology, which often relies on isolating and culturing individual species, metagenomics utilizes cutting-edge next-generation sequencing (NGS) to analyze DNA extracted directly from environmental samples. This method opens the door for researchers to investigate the complex web of interactions within microbial communities, shedding light on their diversity, functional roles, and contributions to ecosystem dynamics. By mapping out the metagenome, scientists can uncover how these microorganisms influence crucial processes such as nutrient cycling, disease mechanisms, and overall ecosystem health.

Why Perform Microbial Metagenomics

Conducting microbial metagenomics is vital because it allows scientists to sequence DNA from environmental samples directly, bypassing the tedious and often incomplete work of isolating individual strains. Traditional methods, such as 16S rRNA gene sequencing, provide only a limited view of the functional potential within microbial communities. In contrast, metagenomics captures a wider array of genetic information, offering a richer understanding of microbial diversity and their metabolic functions. This information plays a crucial role in various fields, from environmental monitoring to advancements in human health and biotechnology, facilitating improvements in diagnostics, therapeutic approaches, and bioremediation techniques.

What is the Difference Between Microbial Genomics and Metagenomics

Microbial genomics is primarily concerned with the genetic material of individual microbial species, often requiring the isolation of pure cultures for detailed genome sequencing. On the other hand, metagenomics examines the combined genomic content of entire microbial communities without needing to isolate specific organisms. While microbial genomics provides in-depth insights into the genetics and functions of particular species, metagenomics reveals the intricate relationships and interactions among diverse microorganisms in their natural environments. This distinction is important; metagenomics not only identifies which organisms are present but also explores their functional capabilities, leading to a more comprehensive understanding of microbial ecology.

Service Specifications

Introduction to Our Microbial Metagenomics PlatformOur Services

At CD Genomics, we pride ourselves on our advanced microbial metagenomics platform, which leverages cutting-edge NGS and long-read sequencing technologies, including PacBio SMRT and Oxford Nanopore. Our platform is designed to provide in-depth and accurate analyses of complex microbial communities, overcoming many limitations of traditional sequencing methods. NGS enhances base coverage and accuracy through continually updated reagents and algorithms, while PacBio SMRT and Nanopore technologies generate long, precise reads, addressing challenges related to repetitive DNA sequences and assembly issues. With our robust metagenomics analysis capabilities, we offer a range of services that facilitate comprehensive studies of microbial ecosystems without the need for cultivation.

Our services include:

Viral Metagenomics: This service focuses on identifying and characterizing viral communities in various samples, providing insights into viral diversity and potential interactions within microbiomes.
Metagenomic Shotgun Sequencing: This comprehensive approach captures the entire genetic content of microbial communities, enabling researchers to explore the functional potential and diversity of microorganisms in their natural environments.
Shallow Shotgun Metagenome Sequencing: Ideal for preliminary analyses, this service allows for quick assessments of microbial diversity and functional potential, paving the way for more in-depth studies.
Metagenomics Hi-C /3C Service: This specialized service investigates the spatial organization of microbial genomes, revealing insights into interactions and structural dynamics within complex communities.

Our platform supports a wide range of applications, including microbial community analysis, genetic diversity assessment, disease research, and biotechnological and pharmaceutical developments. By investigating samples from soil, feces, the gut, oral cavity, skin, and other environments, we unveil the adaptive mechanisms of microorganisms under various environmental stresses and explore their interactions, making our platform an invaluable resource for researchers across multiple disciplines.

Microbial Metagenomics Workflow

The Workflow of Microbial Metagenomics.

Technical Parameters

Illumina NovaSeq, HiSeq, MiSeq; Read Length: PE250; Data Volume: >1G clean data
PacBio SMRT, Library Type: 2 K; Data Volume: Approximately 3,000 to 40,000 CCS reads per sample; Number of SMRT Cells: 1-2 per sample
Oxford Nanopore, Read Length: Up to several megabases; Data Volume: Variable, can exceed 20 Gb per flow cell

Bioinformatics Analysis

Analysis content	Details
Data QC	Removal of low-quality sequences and adapter sequences
Microbial diversity analysis	Sequence alignment, species determination, microbial diversity analysis (α and β diversity analysis, meta-analysis)
Function annotations	KEGG, eggNOG
CAZy	Prediction of genes coding for carbohydrate-active enzyme and correlation analysis
CARD	Prediction of resistance genes and correlation analysis
CAG (co-abundance genes)/MLG (linkage groups) analysis	Study the association between disease and microbial strains CAG, co-abundance genes group MLG, metagenomic linkage groups
CNV	Correlation analysis between microbial copy number variation (CNV) and disease

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

Bioinformatics Analysis Pipeline of Microbial Metagenomics.

Sample Requirement

Service	Sample Type	Recommended Quantity	Minimum Quantity	Concentration
Viral Genome Sequencing	Genomic DNA	≥ 1 µg	500 ng	20 ng/µL
Metagenome Sequencing	Metagenome DNA	≥ 500 ng	20 ng	5 ng/µL
Shallow Shotgun Metagenome Sequencing	Metagenome DNA	≥ 100 ng	20 ng	5 ng/µL
Metagenomics Hi-C/3C Service	Genomic DNA	≥ 1 µg	500 ng	20 ng/µL
Long-Read Metagenomic Sequencing	Genomic DNA	≥ 2 µg
	Tissue	2 g
	Interstitial Fluid	6-10 mL, sediment 2g
	Environmental Samples	6 g
	Water filter membrane	6

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

Deliverables

Sequence Quality Control and Host Removal Information
Overall Species Annotation and Evaluation Related Information
Common Functional Database Annotation Related Information
Resistance Gene Annotation Related Information
Chart Folder for This Report
Delivery results may vary depending on the specific project. For more details, please feel free to contact us.

FAQs

Microbial Metagenomics FAQ

What is the Difference Between 16S Sequencing and Metagenomic Sequencing?
- 1. Sequencing Principles
  
  16S sequencing targets specific hypervariable regions (such as V4 or V3-V4) within the 16S rRNA gene. The microbial genomic DNA is extracted, and these regions are amplified using PCR. A sequencing library is then constructed for downstream sequencing. In contrast, metagenomic sequencing involves random fragmentation of the entire microbial genomic DNA into smaller pieces (300-500 bp), followed by the addition of sequencing adapters to both ends, allowing for comprehensive sequencing.
  
  2. Depth of Species Identification
  
  Sequences generated via 16S sequencing often lack the resolution to reliably annotate down to the species level. Metagenomic sequencing, on the other hand, can identify microorganisms at the species or even strain level, offering a higher resolution of microbial taxonomy.
  
  3. Research Objectives
  
  16S sequencing is primarily used to analyze community composition, evolutionary relationships among species, and overall community diversity. Metagenomic sequencing extends beyond these analyses to enable in-depth investigations at the gene and functional levels, facilitating studies in Gene Ontology and metabolic pathways.
How Long Does the Metagenomic Sequencing Process Take?
- The turnaround time for metagenomic sequencing can vary depending on the specific service and sample type, but generally, results are available within a few weeks post submission.
What is the Typical Output of Metagenomic Sequencing?
- Metagenomic sequencing typically yields a large dataset comprising millions of sequences. These sequences can be analyzed to determine species identification, functional gene content, and overall microbial community structure.
How is Data Quality Ensured in Metagenomic Sequencing?
- Data quality is maintained through rigorous quality control protocols during the sequencing process. This includes filtering out low-quality reads and employing validated bioinformatics pipelines to ensure accurate and reliable analysis.
Can I Compare Metagenomic Results Across Different Studies?
- Yes, metagenomic results can often be compared across different studies, provided that comparable methodologies and bioinformatics approaches are used. This facilitates a broader understanding of microbial diversity and functional capabilities across diverse environments.
What are the Benefits of Using Long-Read Sequencing Technologies?
- Long-read sequencing technologies, such as PacBio or Nanopore, enhance the assembly of complex genomes and provide better resolution of repetitive regions. This results in a richer and more comprehensive understanding of microbial diversity and genetic architecture.

Demo

Partial results of our microbial metagenomics service are shown below:

Bar chart depicting the distribution of species. Species Distribution Bar Chart

Heatmap visualization. Heatmap

Venn diagram representing the data. Venn Diagram

Bar chart of LEfSe analysis demonstrating LDA scores. LEfSe Analysis LDA Bar Chart

Bar chart showing the composition of enzyme activity gene sources by species. Enzyme Activity Gene Species Source Composition Bar Chart

Circos plot illustrating the distribution of Gene Ontology in various samples. Gene Ontology Distribution Circos Plot in Various Samples

Customer Case

Hydrogen-Oxidizing Bacteria Are Abundant in Desert Soils and Strongly Stimulated by Hydration
Journal: Msystems
Impact factor: 6.496
Published: 2020

Find out more

Backgrounds

Desert soils harbor diverse bacterial communities whose mechanisms for maintaining energy and carbon needs are widely debated. Traditionally, it is believed that bacteria in these environments rely on organic carbon synthesized by photoautotrophs after transient hydration events. However, recent studies, particularly focusing on Antarctic desert soils, have highlighted that certain bacteria can utilize atmospheric trace gases like hydrogen (H₂) to conserve energy and fix carbon independently of photosynthesis.

Materials & Methods

Sample preparation:

Desert soil samples
Hydration-desiccation cycle
DNA extraction
RNA extraction

Method:

Metagenomic sequencing
Metatranscriptomic sequencing
Illumina platform

Data Analysis

Functional genes identification
Beta diversity measures
Community composition testing
Differential abundance analysis

Results

1. Hydrogenase-encoding sequences were abundant in the metagenomes and metatranscriptomes, indicating active hydrogen metabolism.

2. These sequences were particularly found in actinobacterial, acidobacterial, and cyanobacterial metagenome-assembled genomes.

FIG 1 Alterations in phylum-level community composition of the Australian desert soil microcosms during hydration and desiccation. (Jordaan et al., 2020) FIG 1 Changes in phylum-level community composition of the Australian desert soil microcosms during hydration and desiccation.

FIG 2 Levels, expression, and distribution of metabolic marker genes in the Australian desert soil microcosms. (Jordaan et al., 2020) FIG 2 Abundance, expression, and distribution of metabolic marker genes in the Australian desert soil microcosms.

3. Dry soil samples exhibited native H₂ oxidation activity, which increased by 950-fold following wetting.

4. Oxygenic and anoxygenic phototrophs were indeed present but in lower abundances compared to hydrogen-oxidizing bacteria.

5. Hydration significantly boosted the H₂ oxidation rates, demonstrating that hydration events can strongly stimulate the activity of hydrogen-oxidizing bacteria in desert soils.

Conclusions

This study finds that hydrogen-oxidizing bacteria are abundant in desert soils and respond strongly to hydration. These bacteria utilize atmospheric hydrogen for energy and carbon, highlighting their role in biogeochemical cycles and providing an alternative to organic carbon-dependent processes. This research enhances our understanding of bacterial survival strategies in extreme environments and the ecological importance of hydrogen metabolism in desert ecosystems.

Reference

Jordaan K, Lappan R, Dong X, et al. Hydrogen-oxidizing bacteria are abundant in desert soils and strongly stimulated by hydration. Msystems, 2020, 5(6): 10.1128/msystems. 01131-20.

* For Research Use Only. Not for use in diagnostic procedures or other clinical purposes.