shutterstock_19456234Where in the world is Martin Hornshaw?

If you are reading this a few days after the day of publication I will be in a beautiful old hilltop town in Italy called Matera. Now I didn’t write this article to tell you about my vacation. This is not that. The reason for my being so lucky as to be in Matera is to attend a conference which I have every expectation will be a marvellous experience for someone who loves mass spectrometry. I am in Matera to join the European Fourier Transform Mass Spectrometry conference. This is an opportunity to hear from some of the best and brightest working with super-high resolution mass spectrometry today. Some of us know the name of Fourier; a famous scientist and mathematician known for, among other things, his ‘Fourier Transform,’ which is mathematics used to convert frequency information (ultimately) into a mass spectrum. What perhaps you may not have heard is that Fourier is also credited with being the discoverer of the Greenhouse effect when he noted that an object the size of the earth at its distance from the sun should be cooler than it actually is if only heated by the sun. He postulated that the atmosphere might serve as an insulator. How right he was.

FTICR and the Orbitrap

Back to mass spectrometry. Ion cyclotron resonance in an FT-ICR mass spectrometer and electrostatic orbital trapping in an orbitrap mass spectrometer both create frequencies as part of the process of measuring mass, albeit different ones, which can be measured very accurately and converted into mass spectra. Mass spectra tell you what something is and how much of it there is. For these types of mass spectrometer this is at least in part done with the Fourier Transform. I have already outlined how an orbitrap mass analyser measures mass (sounds like the start of a tongue twister: how much mass can a mass analyser measure when it measures mass) in 2 articles I wrote last year (Why Is the Orbitrap so Amazing? and Little Piggies, Lego Blocks & the Orbitrap Mass Spectrometer) so I won’t go in to detail about that.

Resolution, resolution, resolution!

What is the most fundamental property of these kinds of mass analysers? In one word: ‘resolution.’ Most of everything else, in terms of accuracy, sensitivity, etc., descends from that. Very, very, very high resolution leads to some very, very, very nice performance indeed. Let me describe three examples of performance dependent on high resolution orbitrap mass analysis in the area of proteomics. These particular examples of high impact research all relied on orbitrap-based mass spectrometers of different kinds.

The one hour yeast proteome’ by the group of Prof. Josh Coon, University of Wisconsin-Madison, published in Molecular and Cellular Proteomics in 2014.

This is an awesome paper. I got in touch with a lot of my colleagues and told them about the ‘Wow Paper’ as I called it. It describes a novel type of mass spectrometer which combined together three types of mass analyser: quadrupole, orbitrap and ion trap (in the mass spec vernacular this is abbreviated to Q-OT-qIT) to produce an ingenious mass spectrometric architecture capable of great speed, resolution and sensitivity. This was used to analyse the yeast proteome comprehensively in just over 1 hour of instrument acquisition time. This was fairly mind-blowing at the time because it indicated that a proteome could be well characterised in a relatively small amount of time demonstrating the possibility for high throughput proteomics. The ability to measure differences in protein expression, using proteomics, has become key to understanding biological phenomena. Transcriptomics, the broad-based measurement of mRNA, is often used as a proxy due to its relatively low cost and speed. However, mRNA is not protein but the intermediary between DNA and protein and tells nothing, for example, about post-translational modifications which are often essential to regulatory processes. The development of mass spec technology and other technologies key to proteomics has been swift in the last several years. This kind of work has been performed on human samples also.

Proteogenomic characterization of human colon and rectal cancer’ published in Nature in 2014

In this paper, Zhang et al.2, describe an approach to characterizing cancers, combining genomics, proteomics and other data. The authors analysed proteomes of colon and rectal tumours which had been previously characterized by ‘The Cancer Genome Atlas’, TCGA, and integrated together the various OMICs data to perform proteogenomic analysis. Protein abundance could not be reliably predicted from DNA or RNA measurements. This has been observed on many occasions. The proteomics data identified five subtypes in the TCGA cohort, two of which overlapped with the TCGA ‘microsatellite instability/CpG island methylation phenotype’ transcriptomic subtype but, and here’s the biggy, had ‘distinct mutation, methylation and protein expression patterns associated with different clinical outcomes.’ From this we can conclude that proteomics data in this set of colon and rectal cancer (CRC) tumours enabled prioritization of candidate driver genes. Another direct quote from the paper: ‘Proteomics identified CRC subtypes similar to those detectable by transcriptomic profiles, but further captured features not detectable in transcript profiles… After validation in independent cohorts, protein subtype signatures could be directly translated into laboratory tests for tumour classification.’ In short, proteomics is a tool that might be used for diagnosis of cancer type. However, to put this into a time-realistic context, proteomics technology needs further development to be routinely used in oncology.

Plasma proteome profiling to assess human health and disease’ led by Prof. Matthias Mann, published in 2016 in Cell Systems

In typical clinical practice protein levels of importance are measured in individual immunoassays. In this paper, a rapid, high-throughput and robust pipeline for ‘plasma proteome profiling’ using a simple mass spectrometry approach (without significant up-front sample prep), with 1 microlitre of sample from a finger prick, taking only 3 hours in total was able to quantitate inflammatory proteins, apolipoproteins and nearly 50 FDA-approved biomarkers. Thus, for example, cardiovascular and metabolic health state might be assessed using this approach after further testing and proper validation. With a longer approach more than 1,000 proteins could be reproducibly quantified.

Like what you are learning?

Sign up to stay connected with all Thermo Scientific resources, applications, blog posts and promotions.
Keep Me Informed!

The authors concluded that their plasma proteome profiling research approach delivered an informative portrait of a person’s health state. The authors postulated that routine sampling of an individual’s blood to produce regular plasma proteome profiles might be possible given the low resource requirements of their approach. With further study and validation, these profiles might be used to monitor health, indicate disease risk, impact of lifestyle change or pharmacological intervention. Thus proteomics could well be used in a large-scale but personalised approach to medicine

This plot depicts the number of publications over time in which Orbitrap mass spectrometers were used in the Nature and Science family of journals.

 

OrbitrapInScienceNature

Why am I going to Matera?

So with this kind of science being enabled by very high resolution mass spectrometry with the orbitrap mass analyser I am particularly excited to be heading to Matera to learn more.

Anyway, if you are not in the vicinity of Matera in the next few days (pity) may I suggest that you  visit planetorbitrap and learn more about high resolution mass spectrometry and how it is changing the face of life science research and even expanding in to how we perform modern medicine.

Further Reading

  • Hebert et al., 2014, The one hour yeast proteome Cell. Proteomics 13, 339-347
  • Zhang et al., 2014, Proteogenomic characterization of human colon and rectal cancer Nature 513, 382-387
  • Geyer et al., 2016, Plasma proteome profiling to assess human health and disease Cell Systems 2, 185-195