Metabolism platforms

Agios Pharmaceuticals

•  Metabolome provides opportunity for novel therapeutics in cancer and rare genetic disease

•  Personalized targeted therapies

•  Apply metabolism studies at very early stage in each programs (establish early stage biomarkers) –  Untargeted metabolomics, fluxomics,

mutli-omics

–  Translational research

–  Target ID and validation

–  Patient stratification

•  2-hydroxyglutarate in IDHm cancers

•  Ex vivo glycolytic flux measurement in pyruvate kinase disease patients

WT   PKD  

2,3-­‐DPG    

ATP  Primary  metabolic  consequences  are  

known  

Deep,  quan?ta?ve  understanding  of  affected  pathway  

Metabolic  consequences  are  unknown  

Specific, Translatable human blood

Layers  of  valida?on  in  vitro  

and  in  vivo  

Secondary  consequences  of  lesion,  &  modula4on  with    target  engagement  are  

unknown  

Analytical approaches to understanding metabolism in disease

Biology and metabolism: a symbiotic relationship

• In  vitro,  in  vivo,  pa4ent  samples  

• Model  development  • Target  valida4on  

Biology  

• Mul4-­‐omics  plaBorms  • Metabolism,  lipidomics,  metabolomics  

• Targeted  assays  • Biomarker  iden4fica4on  

Analy4cal  • Automated  data  analysis  • Metabolomics  (targeted  and  untargeted)  

• Flux  Analysis  • Pathway  analysis  

Informa4cs  

Agios Metabolism Platform: Tools and Technology Automation and Mass Informatics Workflows (scale reflects effort)

proteomis  

Metabolite  and  Lipid  Extrac6on  &  Harvest  robo6cs  

Integrated  so<ware,  analysis  

Metabolite-­‐Centric  Data  Processing  

Visualiza6on,  data  analysis,  Informa6cs  tools  

Automated  data  analysis  and  informa6cs  workflows  

Mass  Spectra  

Data  QC,  Correc6on,  Transforma6on  

Hypothesis  genera6on  

Kine6c  Flux  Labeling  

Transcriptomics,  Proteomics,  Lipidomics…  

Isotope  Tracing  

MS  

Metabolomics  

•  3  QEs  •  Xevo  TQS  • AB  4000  •  Thermo  GC-­‐QQQ  

•  Fusion  • Agilent  QTOF  

Agios Metabolism Platform: Tools and Technology

ü  High  mass  resolu4on  and  accuracy  ~  20ppm  ü  Fast  rela4ve  quan4ta4on    (1  min/assay)  

ü  Broad  &  untargeted  coverage  of  intracellular  small  molecules    

ü  (2000-­‐4000  ions  detected  per  sample)  

FIA  –  QToF  Profiling   Q  Exac?ve  LCMS    

Agilent  6500  QTOF  

Lipidomics  +/-­‐  mode  

Metabolomics  -­‐  mode   +  mode  

ü  High  mass  resolu4on  and  accuracy  ~  5ppm  ü  Both  targeted  and  untargeted  broad  profiling  

ü  UPLC  separa4on  of  analytes  for  ID  confirma4on    

Library  of  ~700  metabolites  annotated  with  m/z  and  RT  

HRAM  spectra  on  a  QExac?ve  at  140k  resolu?on  

15N  

Neutron  

13C  

Δm = 0.0063  amu  arginine  

LC-MS/MS Lipidomics

Waters  iClass  Aquity  w/  Thermo  QExac4ve  

Extract   HRMS+MS/MS    (pos/neg)  

Signals  automa4cally  

annotated  using  MS/MS  and  assembled  for  

sta4s4cal  analysis  

Observed  >800  lipids  from  biological  samples  •  Phosphoglycerolipids  •  Glycerolipids  •  Sphingolipids  •  Cholesterol  esters  •  Free  fady  acids    

Limited  coverage  on  sterols,  prenols,  polyke7des  

Comprehensive  data  analysis/interpreta4on  to  iden4fy  metabolic  perturba4ons  

Analy4cal  plaBorm  

R e te n tio n T im e (m in )

Ion

In

ten

sit

y

0 1 0 2 0 3 00

5 .0´1 0 8

1 .0´1 0 9

1 .5´1 0 9

2 .0´1 0 9

2 .5´1 0 9

LPC  (int  std)  

PC,  PE,  SM  

TAGs  

1        2        3      4        5  

Summary of platforms

Proteomics

NEW!

ThermoFusion

PTM analysis

Combine data

Lipidomics

QExactive

LC-MS/MS based

Identify >800 lipid species in 30 m analysis

Building informatic toolbox to interpret data (pathway mapping)

Metabolomics

QQQ, QToF, QExactive

LCMS + GCMS (NEW!)

Identify ~600 metabolites from known library

Isotopic labeling studies

Informa4cs  

Informatics analysis

•  Combi-Omics –  Metabolism-transcript

–  Protein-transcript

–  Metabolism-protein-transcript

•  Flux analysis

•  MIDA analysis

•  Automated workflows –  FIA-TOF

–  Peak annotation

–  Statistical characterization

Gaps in the process

•  Agios process –  Experiments design

(BiologyàLIMS)

–  Execution (mostly automated)

–  Conversion to mzXML (auto)

–  Peak ID via MAVEN (manual or auto)

–  Nat. abundance isotope correction, quantitation (custom software)

–  Flux analysis, data visualization, multi-omicsàmetadata preserved (SpotFire)

•  Gaps –  LIMS and metadata

•  Customize older LIMS softwares

–  Vendor neutral peak picking software to identify stable isotope labels

•  Maven works, but can be slow with automatic workflow

–  Lipid pathway analysis tools (not well annotated in KEGG)

–  Multi-omics pathway analysis

–  Data repository of unknowns