Easy and accurate high-performance liquid chromatography retention prediction with different gradients, flow rates, and instruments by back-calculation of gradient and flow rate profiles Paul G. Boswell, Jonathan R. Schellenberg, Peter W. Carr, Jerry D. Cohen, Adrian D. Hegeman
An implementation and source code is available here.
".. This approach provides a simple way to correct for all
instrument-related factors affecting retention, allowing dramatically
streamlined and improved retention projection across gradients, flow
rates, and HPLC instruments."
And here are the limitations:
1) Solvent A must be 0.1% formic acid in water and solvent B must be pure acetonitrile
2) The column temperature must be set to 35 °C
3) The stationary phase must be Waters Acquity BEH C18 (1.7 μm, 130 Å)
4) The retention database only contains 35 compounds.
Thursday, October 20, 2011
Thursday, September 8, 2011
Dancing with the yeast cells
Some guys from New Zeland at the Centre for Microbial Innovation designed what I think is the funniest metabolomics experiment so far. They compared the metabolome of yeast cells growing in defined liquid medium exposed to music and silence. The biomass production was decreased by 14% when the cells were exposed to sonic stimuli, and the metabolite profile was also significantly different compared with silence.
http://www.springerlink.com/content/e6143q34160g633r/
Unfortunately, they didn't specify in their methods what kind of music they used. Was it Britney Spears or Enrique Iglesias? that might clearly explain the lower biomass production... I bet they also activated signaling for apoptosis.
Clearly, a great candidate paper for the Ig Nobel Prize ;-)
http://www.springerlink.com/content/e6143q34160g633r/
Unfortunately, they didn't specify in their methods what kind of music they used. Was it Britney Spears or Enrique Iglesias? that might clearly explain the lower biomass production... I bet they also activated signaling for apoptosis.
Clearly, a great candidate paper for the Ig Nobel Prize ;-)
Monday, August 29, 2011
Global Metabolomics Market to Reach $863.8 Million by 2017, According to a New Report by Global Industry Analysts, Inc
http://www.prweb.com/releases/metabolomics_metabonomics/biomarker_discovery/prweb8519517.htm
Monday, June 20, 2011
Announcing the Metabolomics Forum
We would like to invite you to use the Metabolomics Forum, which we created recently : http://metabolomics-forum.com/
The Metabolomics Forum is open to everyone for questions and discussions on the topic of metabolomics. Separate forum categories regarding hardware, software, sample preparation and identification topics have been created.
I'm looking forward to seeing you on the forum!
The Metabolomics Forum is open to everyone for questions and discussions on the topic of metabolomics. Separate forum categories regarding hardware, software, sample preparation and identification topics have been created.
I'm looking forward to seeing you on the forum!
Tuesday, May 31, 2011
LC/MS raw data conversion just got easier!
ProteoWizard's msconvert now supports the conversion of Agilent, Bruker, Thermo, Waters and AB Sciex file formats into mzML/mzXML - all the necessary vendor readers are included in the distribution. No additional software is needed.
Wednesday, April 13, 2011
Q-TOF
Friday, March 18, 2011
Interesting metabolomics review in Toxicological Sciences
Metabolomics in toxicology: preclinical and clinical applications.
Robertson DG, Watkins PB, Reily MD.
"... Experience has shown that when data analysis ends with colorful PCA or partial least squares plots, the real impact of a metabolomics study is not realized." :)
Robertson DG, Watkins PB, Reily MD.
"... Experience has shown that when data analysis ends with colorful PCA or partial least squares plots, the real impact of a metabolomics study is not realized." :)
Wednesday, March 2, 2011
Cryptogenic Disease and 'Omics Profiling
An interesting and exciting case report will be published in the March edition of Genetics in Medicine (Worthey et al., Genet Med. 2011 Mar, 13(3):255-262). This Brief Report describes the case of a 6-year old boy in Wisconsin suffering from multiple intestinal fistulas. Despite comprehensive clinical evaluations and a battery of tests, the boy's physicians were unable to arrive at a definitive diagnosis and were baffled at a syndrome that had not been seen before. Clinical management was limited, making it difficult for the boy to eat solid food. After over 100 surgeries the boy only grew sicker and the physicians were at a loss. It was at this point that they carried out whole-exome sequencing. It was discovered that the boy had a mutation in his XIAP gene, a mutation not previously associated with the boy's condition but that had been linked with another pathology which was curable by bone-marrow transplantation. The team performed a bone-marrow transplant (which they would not have considered without the sequencing) and saved the boy's life.
This report, as well as a couple of other recent examples from the literature, raises the question of the role of genomics, proteomics, and metabolomics in initiating treatment regimens for cryptogenic disease. Clearly, this is a striking example of the clinical benefit of sequencing a patient with a poorly understood syndrome. Here, sequencing led to treatment insights that would have been otherwise difficult to arrive at. In the context of this particular case study, it is unclear that proteomic and metabolomic profiling would have offered much clinical benefit. Although metabollite profiling may be useful in diagnosing diseases for which biomarkers have been elucidated, would metabolomics be useful to investigate rare cryptogenic cases such as those described here? At this time, it is difficult to imagine learning much interesting information by doing "metabolite profiling" on a single individual without appropriate controls and statistics. But perhaps this is something that may change with the evolution of our understanding of the human metabolome and the development of much more advanced metabolite databases. For now, metabolomics might be better suited for providing pathobiological insight when it comes to dealing with rare cryptogenic disease.
This report, as well as a couple of other recent examples from the literature, raises the question of the role of genomics, proteomics, and metabolomics in initiating treatment regimens for cryptogenic disease. Clearly, this is a striking example of the clinical benefit of sequencing a patient with a poorly understood syndrome. Here, sequencing led to treatment insights that would have been otherwise difficult to arrive at. In the context of this particular case study, it is unclear that proteomic and metabolomic profiling would have offered much clinical benefit. Although metabollite profiling may be useful in diagnosing diseases for which biomarkers have been elucidated, would metabolomics be useful to investigate rare cryptogenic cases such as those described here? At this time, it is difficult to imagine learning much interesting information by doing "metabolite profiling" on a single individual without appropriate controls and statistics. But perhaps this is something that may change with the evolution of our understanding of the human metabolome and the development of much more advanced metabolite databases. For now, metabolomics might be better suited for providing pathobiological insight when it comes to dealing with rare cryptogenic disease.
Tuesday, February 22, 2011
Subscribe to:
Posts (Atom)