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Metagenomic Sequencing -NGS

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Metagenome refers to a collection of the total genetic material of a mixed community of organisms, such as environmental and human metagenomes. It contains genomes of both cultivatable and uncultivatable microorganisms. Shotgun metagenomic sequencing with NGS enables the study of these intricate genomic landscapes embedded in environmental samples by providing more than taxonomic profiling, giving also granular insights into species diversity, abundance dynamics, and complex population structures. Beyond taxonomic studies, shotgun metagenomics also offers a functional genomics perspective, enabling the exploration of encoded genes and their putative roles in ecological processes. Finally, the establishment of correlation networks between genetic elements and environmental factors contributes to a holistic understanding of the intricate interplay between microbial communities and their ecological background. In conclusion, metagenomic sequencing stands as a pivotal instrument for unravelling the genomic intricacies of diverse microbial communities, illuminating the multifaceted relationships between genetics and ecology within these complexecosystems.s

Platforms: Illumina NovaSeq and DNBSeq T7


Service Details

Bioinformatics

Demo Results

Featured publications

Service Advantages

●  Isolation and cultivation-free method for microbial community profiling: enabling sequencing of genetic material from uncultivable organisms.

●  High resolution: in detecting low-abundance species in environmental samples.

●  Comprehensive bioinformatics analysis: focused not only on taxonomic diversity but also on the functional diversity of the community.

●  Extensive experience: with a track record of successfully closing multiple metagenomics projects in various research domains and processing over 10,000 samples, our team brings a wealth of experience to every project.

Service Specifications

Sequencing platform

Sequencing Strategy

Data recommended

Quality control

Illumina NovaSeq or DNBSeq T7

PE150

6-20Gb

Q30≥85%

Service Requirements

Concentration (ng/µL)

Total amount (ng)

Volume (µL)

OD260/280

≥1

≥30

≥20

1.6-2.5

● Soil/sludge: 2-3g
● Intestinal content-animal: 0.5-2g
● Intestinal contents-insect: 0.1-0.25g
● Plant surface (enriched sediment): 0.5-1g
● Fermentation broth enriched sediment): 0.2-0.5g
● Faeces (large animals): 0.5-2g
● Faeces (mouse): 3-5grains
● Pulmonary alveolar lavage fluid: filter paper
● Vaginal swab: 5-6 swabs
● Skin/genital swab/saliva/oral soft tissue/pharyngeal swab/rectal swab: 2-3 swabs
● Surface microorganism: 5-6 swabs
● Waterbody/air/biofilm: filter paper
● Endophytes: 2-3g
● Dental Plaque: 0.5-1g

Service Work Flow

sample delivery

Sample delivery

Library Preparation

Library construction

Sequencing

Sequencing

Data analysis

Data analysis

After sale Services

After-sale services


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    Includes the following analysis:

    ●  Sequencing data quality control

    ●  Metagenome assembly and gene prediction

    ●  Gene annotation

    ●  Taxonomic alpha diversity analysis

    ●  Functional analysis of the community: biological function, metabolic, antibiotic resistance

    ●  Analysis on both functional and taxonomic diversity:

                        Beta diversity analysis

                        Inter-group analysis

                        Correlation analysis: between environmental factors and OUT composition and diversity

     

    Functional analysis: CARD antibiotic resistance

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    Differential analysis of KEGG metabolic pathways: heatmap of significant pathways

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    Alpha diversity of taxonomic distribution: ACE index

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    Beta diversity of taxonomic distribution: PCoA

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    Explore the advancements facilitated by BMKGene’s metagenome sequencing services with Illumina through a curated collection of publications.

    Hai, Q. et al. (2023) ‘Metagenomic and metabolomic analysis of changes in intestinal contents of rainbow trout (Oncorhynchus mykiss) infected with infectious hematopoietic necrosis virus at different culture water temperatures’, Frontiers in Microbiology, 14, p. 1275649. doi: 10.3389/FMICB.2023.1275649.

    Mao, C. et al. (2023) ‘Microbial communities, resistance genes, and resistome risks in urban lakes of different trophic states: Internal links and external influences’, Journal of Hazardous Materials Advances, 9, p. 100233. doi: 10.1016/J.HAZADV.2023.100233.

    Su, M. et al. (2022) ‘Metagenomic Analysis Revealed Differences in Composition and Function Between Liquid-Associated and Solid-Associated Microorganisms of Sheep Rumen’, Frontiers in Microbiology, 13, p. 851567. doi: 10.3389/FMICB.2022.851567.

    Yin, J. et al. (2023) ‘Obese Ningxiang pig-derived microbiota rewires carnitine metabolism to promote muscle fatty acid deposition in lean DLY pigs’, The Innovation, 4(5), p. 100486. doi: 10.1016/J.XINN.2023.100486.

    Zhao, X. et al. (2023) ‘Metagenomic insights into the potential risks of representative bio/non-degradable plastic and non-plastic debris in the upper and lower reaches of Haihe Estuary, China’, Science of The Total Environment, 887, p. 164026. doi: 10.1016/J.SCITOTENV.2023.164026.

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