The IROATM
methodology was developed to
automate and simplify metabolomics so that
investigators can achieve clear and rel...
media-free
cells
Wash
Culture
Biological
A. The use of a pooled biological population at the outset of the experiment
will...
Composite
media-free
12
cells
+
media-free
13
cells
Total Ion
Data
Analytical
The IROA™ Analysis
C. After the experimental...
E. Artifacts are discarded; the respective areas for control-derived
and experimentally-derived compounds are identified (...
IROA Software data flow
Normalized
Ratio
0
-5.0
5.0
108
datapoints (mostly noise)
B.
C.
A.
5X102
datapoints (pure data)
Va...
IROA Software data flow
Normalized
Ratio
0
-5.0
5.0
108
datapoints (mostly noise)
B.
C.
A.
5X102
datapoints (pure data)
Va...
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How the IROA Technology Works

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How the IROA Technology Works

  1. 1. The IROATM methodology was developed to automate and simplify metabolomics so that investigators can achieve clear and reliable results easily. It only requires suitable isotopically-paired media and software to extract and process the mass spectrometer raw data files. The following slides describe an IROA experiment in its simplest form. This basic methodology may be just as easily applied to simple experimental systems or much more complex experimental systems, only a change in cell medium is required. IROA™: Isotopic Ratio Outlier Analysis
  2. 2. media-free cells Wash Culture Biological A. The use of a pooled biological population at the outset of the experiment will reduce biological variance. The pooled biological population is divided into two and each of these is placed in separate isotopically defined media. B. The control and experimental cells are each allowed to grow through enough divisions to dilute out the natural abundance carbon and replace it with the characteristic isotopic distributions of their particular media. This gives each and every molecule a unique “label”, definitive to source. The experimental conditions are applied to the experimental population, and vehicle to the control population. The IROA™ Analysis 95% 12 C and 5% 13 C media control Experimental TreatIncubate Experimental 95% 13 C and 5% 12 C media drug etc. Add toxin,
  3. 3. Composite media-free 12 cells + media-free 13 cells Total Ion Data Analytical The IROA™ Analysis C. After the experimentally defined period the experimental and control cells are mixed. D. The mixed sample, containing both control and experimental populations in one sample, is prepared and analyzed by mass spectrometry as a single sample. The number of samples to be analyzed is reduced by half. As all of the molecules from each population are distinguishable from one another AND from artifactual molecules, it is possible to look at any peak and understand its origin. In addition, since the control and experimental populations share the same handling- induced variances compound–by-compound (i.e. error or losses), there is no variance between or within them. This “noise-free” environment is a unique feature of IROA TM , and is the most significant reason for its success.
  4. 4. E. Artifacts are discarded; the respective areas for control-derived and experimentally-derived compounds are identified (by isotopic signature) and compared (by ratio). F. The distribution of ratios is analyzed for outliers. Compounds with abnormal ratios are molecules affected by the experimental stressor, (toxin, drug etc.) allowing for clear interpretation. Normalized Ratio 0 -5.0 5.0 The IROA™ Analysis
  5. 5. IROA Software data flow Normalized Ratio 0 -5.0 5.0 108 datapoints (mostly noise) B. C. A. 5X102 datapoints (pure data) Variance control, Data reduction, Noise removal, Data definition Fully automated data reduction of complex raw data to concise, high value information. The IROATM software is capable of interpreting these datasets, and will allow for a very dramatic reduction in data size as it easily sorts through the dataset removing irrelevant data. No other system can do this as efficiently or consistently.
  6. 6. IROA Software data flow Normalized Ratio 0 -5.0 5.0 108 datapoints (mostly noise) B. C. A. 5X102 datapoints (pure data) Variance control, Data reduction, Noise removal, Data definition Fully automated data reduction of complex raw data to concise, high value information. The IROATM software is capable of interpreting these datasets, and will allow for a very dramatic reduction in data size as it easily sorts through the dataset removing irrelevant data. No other system can do this as efficiently or consistently.

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