BGI Genomics offers proteomics, biologics characterization, metabolomics and multi-omics services to accelerate your life science research program. Our portfolio of end-to-end LC-MS services leverages BGI’s strengths in managing large scale computing infrastructure and pioneering innovative bioinformatics technologies.
Our mass spectrometry laboratory is comprised of scientists with extensive experience in liquid chromatography and mass spectrometry-based analytical methods. This state-of-the-art facility is designed to support a broad range of metabolite research applications.
We can help simplify your research challenge. BGI can provide workflow customization and consultation services to address unique project requirements. Turnaround time is approximately 4 weeks for all of our services.
We offer solutions for measuring the expression of proteins and post-translational modifications such as phosphorylation, glycosylation, and acetylation.
BGI provides global and targeted solutions for protein quantitation1,2. We can flexibly adapt our Label-Free DIA and Isobaric Label services to best fit your experimental strategies3,4,5. For screening applications, we provide a highly specific targeted peptide quantitation using multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) scanning using Q Exactive HF/HF-X and QTRAP 6500-based MS detection6.
We offer services for large scale Proteome Profiling and can provide sample pre-fractionation using our off-line HPLC platform. Our laboratory can also perform Protein Identification services using solution samples or gel-isolated samples.
All of our proteomics services can be customized to meet your protein discovery project needs.
BGI scientists in San Jose, California, provide analytical services and downstream support for biopharmaceutical and biotechnology industry customers. Our goal is to provide you with detailed knowledge about the molecular composition of your biologic sample using innovative analytical methods optimized for dynamic range and sensitivity.
Our state-of-the-art LC-MS platform can support diverse biologic characterization projects, including highly complex samples such as bi-/multi-specific antibodies, ADCs, and Fc-fusion protein drugs. Additionally, our scientific team at the San Jose Mass Spectrometry Center have pioneered native LC-MS technology which can preserve non-covalent binding and is compatible with medium-high sample throughput7,8,9.
We can provide broad support for drug discovery and other biologic-related proteomics services, including phosphoproteomics, CAR-T interactomics, and trans-omics projects involving proteomic and transcriptomic (DNBSEQ) analyses.
We offer solutions for measuring the expression of metabolites.
BGI provides global and targeted solutions for metabolite quantitation10,11,12. We can flexibly adapt our Untargeted Metabolomics and Lipidomics Profiling services to best fit your experimental strategies. For screening applications, we provide a highly specific targeted metabolite quantitation using multiple reaction monitoring (MRM) scanning using QTRAP 6500 and Waters Xevo TQ-S-based MS detection.
All of our metabolomics services can be customized to meet your metabolite discovery project needs.
Multi-omics is the integrative biological analysis of different data sets from single omics areas for new insight. An integrated multi-omics approach to research enables a more comprehensive understanding of genotypic, phenotypic and environmental relationships and their association to disease and health of an organism.
BGI offers multi-omics services to look across genomics, transcriptomics, epigenomics, proteomics and metabolomics, with the flexibility to customize solutions that meet your specific needs10,13,14. All projects are supported by a bioinformatics infrastructure that is second to none.
 Xun Z, Shangbo X et al. Tissue-specific Proteogenomics Analysis of Plutella xylostella Larval Midgut Using a Multialgorithm Pipeline. Mol Cell Proteomics. 2016; 15(6): 1791-1807. doi: 10.1074/mcp.M115.050989.  Zhen C, Bo W et al. Quantitative proteomics reveals the temperature-dependent proteins encoded by a series of cluster genes in thermoanaerobacter tengcongensis. Mol Cell Proteomics. 2013; 12(8): 2266-2277. doi: 10.1074/mcp.M112.025817.  Wong, J. W. H., & Cagney, G. (2009). An Overview of Label-Free Quantitation Methods in Proteomics by Mass Spectrometry. Proteome Bioinformatics, 273–283.doi:10.1007/978-1-60761-444-9_18.  Searle BC, Pino LK, Egertson JD, Ting YS, Lawrence RT, MacLean BX, Villén J, MacCoss MJ. Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry. Nat Commun. 2018 Dec 3;9(1):5128. doi: 10.1038/s41467-018-07454-w.  Kelstrup CD, Bekker-Jensen DB, Arrey TN, Hogrebe A, Harder A, Olsen JV. Performance Evaluation of the Q Exactive HF-X for Shotgun Proteomics. J Proteome Res. 2018 Jan 5;17(1):727-738. doi: 10.1021/acs.jproteome.7b00602.  Bourmaud A, Gallien S, Domon B. Parallel reaction monitoring using quadrupole-Orbitrap mass spectrometer: Principle and applications. Proteomics. 2016 Aug;16(15-16):2146-59. doi: 10.1002/pmic.201500543.  Schachner L, Han G, Dillon M, Zhou J, McCarty L, Ellerman D, Yin Y, Spiess C, Lill JR, Carter PJ, Sandoval W. Characterization of Chain Pairing Variants of Bispecific IgG Expressed in a Single Host Cell by High-Resolution Native and Denaturing Mass Spectrometry. Anal Chem. 2016 Dec 20;88(24):12122-12127. doi:10.1021/acs.analchem.6b02866.  Bailey AO, Han G, Phung W, Gazis P, Sutton J, Josephs JL, Sandoval W. Charge variant native mass spectrometry benefits mass precision and dynamic range of monoclonal antibody intact mass analysis. MAbs. 2018 Nov-Dec;10(8):1214-1225. doi: 10.1080/19420862.2018.1521131.  Ren C, Bailey AO, VanderPorten E, Oh A, Phung W, Mulvihill MM, Harris SF, Liu Y, Han G, Sandoval W. Quantitative Determination of Protein-Ligand Affinity by Size Exclusion Chromatography Directly Coupled to High-Resolution Native Mass Spectrometry. Anal Chem. 2019 Jan 2;91(1):903-911. doi:10.1021/acs.analchem.8b03829.  Liu R., et al., Gut microbiome and serum metabolome alterations in obesity and after weight-loss intervention. Nat Med, 2017. 23(7): p. 859-868. doi: 10.1038/nm.4358.  Zhong H, et al., Lipidomic profiling reveals distinct differences in plasma lipid composition in healthy, prediabetic, and type 2 diabetic individuals. Gigascience, 2017 07 01; 67(7). doi:10.1093/gigascience/gix036.  Wen, B., et al., metaX: a flexible and comprehensive software for processing metabolomics data. BMC Bioinformatics, 2017. 18(1): p. 183. doi: 10.1186/s12859-017-1579-y.  Dai F, Wang Z. et al. Transcriptomic and proteomic analyses of mulberry (Motus atropurpurea) fruit response to Ciboria carunculoides. J Proteomics. 2019 Feb 20; 193: 142-153. doi: 10.1016/j.jprot.2018.10.004  Gao H Y. et al. Transcriptomics and metabolomics analyses reveal the differential accumulation of phenylpropanoids between Cinnamomum cassia Presl and Cinnamomum cassia Presl var. macrophyllum Chu. Industrial Crops and Products, Volume 148, 2020, 112282, ISSN 0926-6690, doi: 10.1016/j.indcrop.2020.112282.