Harvard Chan Advanced Multi-omics Platform (ChAMP)
The Harvard Chan Advanced Multi-omics Platform (ChAMP) in the Department of Molecular Metabolism at the Harvard T.H. Chan School of Public Health is focused on promoting collaboration and supporting the advancement of research. The platform aims to provide mass spectrometry support and partnership to collaborators from both Harvard Schools and external institutions and facilitates user training and education in mass spectrometry methodology and analysis.
665 Huntington Ave, SPH2 Room 108
Boston, MA 02115
What We Do
ChAMP is committed to supporting platform users with ongoing projects, exploring early ideas and preliminary experiments, facilitating funding applications for research grants, and fostering interdisciplinary research. The platform has the capacity to measure metabolomics and lipidomics. ChAMP seeks to immerse its collaborators in the methodology and analysis necessary to collect mass spectrometry data and additionally assists in interpreting data. Throughout the entirety of the collaboration, the platform provides insight into experimental design and effective analysis.
Our Platform
Pricing
With continuous support from the Harvard T.H. Chan School of Public Health, ChAMP currently operates under the approved pricing model below.
Services for the partnership include:
- Targeted metabolomics
- Untargeted metabolomics
- Lipidomics
ChAMP currently does not accept samples under the fee-for-service model. Please inquire if your sample type does not appear in the table below.
ChAMP Fee Structure:
| Category | Name of Service | Unit of measure (hours, each, per sample, etc) | Cost per unit internal* ($) | Cost/unit external** ($) |
| Sample Processing | Blood samples | Per sample | $10 | $15.95 |
| Tissue or cell samples | Per sample | $20 | $31.90 | |
| Prepared own sample | Per sample | $0.00 | $0.00 | |
| MS analysis run | Metabolomics (positive + negative mode) | Per sample | $50 | $79.75 |
| Lipidomics (positive) | Per sample | $50 | $79.75 | |
| Lipidomics (both positive and negative) | Per sample | $100 | $159.50 | |
| Data Processing | Metabolomics MS data processing- targeted (default) and untargeted | Per order | $200 | $319.00 |
** External – Anyone else within the Harvard network and beyond.
Ordering Process
- Email (champ@hsph.harvard.edu) — with your project overview and intended need
- Submit an account creation request to set up an account with PPMS CHAMP (if you don’t already have one)
- Create/Submit a project request in the system- “ChAMP Basic Project Request Form“ (this must be done before you have authorization/access to order)
- Order service by completing the prompted fields/form (make sure you attach files for your respective samples — .csv file format preferred
- Contact the ChAMP Team to ascertain the correct techniques for extraction and storing
- Next Steps: Arrange a time for when/how the samples will be delivered with ChAMP Admin (champ@hsph.harvard.edu)
Director
The Hui laboratory aims to answer fundamental questions of energy metabolism and the related diseases: How do individual tissues coordinate their metabolism to achieve overall energy balance of the body? Why can this balance be disrupted by certain perturbations, exhibiting as metabolic diseases (e.g., high-fat diet induces obesity and cancer causes cachexia)? What manipulations can we do to restore the energy balance thus reversing and preventing these diseases?
To answer these questions, we take the approach of in vivo flux quantification by integrating animal experiments, mass spectrometry, and quantitative modeling. Fluxes are the most fundamental functional property of metabolism. Their systematic quantitation holds the potential to transform the field of mammalian physiology. This approach, however, poses two key challenges: (i) need for diverse expertise: animal experiments, analytical chemistry, and mathematical modeling; and (ii) multiple time and length scales involved, from enzymes and their reaction kinetics up to the level of tissue and animal physiology. The lab is unique in having the combination of mathematical and biological skills to successfully tackle these challenges.