Lipidomics Profiling

Service Description

Lipids are essential metabolites that have many key cellular functions and which can be analysed to gain insight into the metabolic state of cells. The number of lipid molecules in a cell, collectively called the lipidome, is estimated to be in the tens to hundreds of thousands.
According to the classification system proposed by the Lipid Metabolites and Pathways Strategy (LIPID MAPS) project, lipids are divided into eight classes: fatty acyls (FA), glycerolipids (GL), glycerophospholipids (GP), sphingolipids (SP), sterol lipids (ST), prenol lipids (PR), saccharolipids (SL), and polyketides (PK), covering a total of 43,413 lipid molecular species.

Combined with LipidSearch software and advanced algorithm analysis, BGI’s lipidomics profiling service enables confirmation of lipid structure characteristics such as lipid molecule head structure, fatty acid branch chain length and unsaturated double bond number by comparing the characteristic signals of precursor ions, MS2 fragments and neutral loss. LipidSearch is equipped with the largest lipids database, covering 8 categories of lipids, 300 lipid subclasses, and containing more than 1.7 million lipid ions and their predictive fragment ions information.

Mass Spectrometry Service Specification

Lipidomics Profiling services are performed using Waters ACQUITY UPLC and cutting-edge mass spectrometer (Q Exactive HF/HF-X).

Sample Preparation and Services

Increase metabolome depth of coverage using ACQUITY UPLC CSH C18 column

(+) and (-) ESI detection by a Q Exactive HF/HF-X mass spectrometer

Quality Standard

Summary includes all methods and data analysis

Reports provided in Excel or PDF format; RAW files available upon request

Turn Around Time

Typical 5-7 weeks after sample receipt for raw data delivery

Research Applications

• Disease biomarkers research
• Pathogenesis and prognosis study on diseases
• Drug target research
• Animal special behavior mechanism and food/medicinal value research
• Plant growth and development research
• Plant disease resistance and insect resistance research
• Microbial drug resistance mechanism

Service Advantages

State-of-the-art LC-MS/MS systems	Large scale and high volume sample experience	High-precision identification results	Strict quality control system
Thermo Q Exactive™ HF-X	Sample preparation at a capacity of up to 1000+ per day	LipidSearch database (1.7 million lipid ions)	Strict protocols governing the whole workflow
Resolution up to 24,000, ensuring high spectral quality and accurate results	Large scale project experience with 1000s of samples	100% identification is achieved through the standards	Double quality control prcoess of isotopic internal standard and QC samples
		Identification credibility rating

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Specifications

Increase metabolome depth of coverage using ACQUITY UPLC CSH C18 column
(+) and (-) ESI detection by a Q Exactive HF/HF-X mass spectrometer
Summary includes all methods and data analysis
Reports provided in Excel or PDF format; RAW files available upon request
Typical 5-7 weeks after sample receipt for raw data delivery

Sample Requirements

SAMPLE TYPE	RECOMMENDED SAMPLE AMOUNT	MINIMUM SAMPLE AMOUNT
Serum, plasma	≥ 300 µL	≥ 100 µL
Urine	≥ 300 µL	≥ 100 µL
Animal and clinical tissues	≥ 200 mg	≥ 25 mg
Feces and intestinal contents	≥ 200 mg	≥ 25 mg
Cell	1×10^7	5×10^6
Microorganism	≥ 200 mg	≥ 25 mg
Culture medium, fermentation medium	≥ 1 mL	≥ 100 µL
Milk	≥ 1 mL	≥ 100 µL
Other body fluids (amniotic fluid, saliva, hemolymph, cerebrospinal fluid, etc.)	≥ 300 µL	≥ 100 µL

Data Analysis

Data analysis performed with metaX1 and BGI library
T-test, PCA, PLS-DA, OPLS-DA for differential metabolic identification
Cluster analysis
Metabolite pathway annotation
ROC analysis
Metabolite correlation analysis

Lipidomics

Unique DNBSEQ™ Sequencing Technology

BGI’s RNA Sequencing services are typically executed with proprietary DNBSEQ™ sequencing technology platforms, for great sequencing data at some of the lowest costs in the industry. DNBSEQ™ offers advantages in terms of lower amplification error rates and much lower duplication rates. In addition, studies have shown the lower index hopping rate in DNBSEQ™ platforms.