#TalkProteomics – Catch up on the mini-Spotlight Twitter chat

Written by Lucy Cliff (Future Science Group)

As part of our mini-Spotlight on proteomics, we hosted a Twitter chat (#TalkProteomics) on February 22nd, where we questioned John Wilson (ProtiFi; NY, USA), Ben Orsburn (National Cancer Institute; MD, USA), Matthias Trost (Newcastle University; UK) and Eduardo Chicano Gálvez (Maimónides Biomedical Research Institute of Córdoba; Spain) about all things proteomics – from mass spectrometry to drug discovery.

The experts dedicated an hour of their time to answer questions and share their opinions on the field of proteomics. We take a look at some of the highlights below:

Applications in drug discovery

Proteomic techniques can directly contribute to the discovery and development of novel drugs for the treatment for various illnesses and diseases. As highlighted by our panel, mass spectrometry imaging – an essential tool in proteomics – has the ability to trace and localize candidate drug molecules over tissues whilst also being able to perform pharmacokinetic studies.

and of course high-throughput MALDI TOF and acoustic mass spec. but I don’t necessarily see them as proteomics but more mass spec tools. 2/2 #TalkProteomics

More than just an analytical tool

The panel also took the opportunity to dispel any theories suggesting that proteomics in merely a tool to direct further research by highlighting its ability to answer important biological questions and produce highly quantitative data.

when a protein has been quantified on >4 peptides, I would always think the quantitation will be extremely accurate, more linear than Western Blot and not dependent on antibody specificity. but hey, we get there… 2/2 #TalkProteomics

Challenges to overcome

The panel shared their thoughts on current challenges hindering proteomics research, with a lack of training programs and qualified personnel to fill the growing number of positions, being raised as common concerns. Additionally, it was highlighted that reaching genomics levels of sensitivity and standardization can be particularly problematic when applying proteomics to the clinic.

A move towards machine learning?

In recent years, machine learning and artificial intelligence have progressed rapidly with applications in areas including robotics, speech recognition and medical diagnosis regularly seen in the news. Looking to the future, the panel hypothesized that the trend in machine learning may be applied to predicting mass spectrometry spectra thereby creating libraries that can be quickly and easily searched.

Future outlook – a nod to clinical application

And finally, the panel shared their perspectives on the future of proteomics research and development with clinical use highlighted as a major milestone to be met.

Thank you again to our panelists for giving up their time to share their knowledge in proteomics research and development – we had some fantastic, varied perspectives highlighting some of the challenges hindering research and how these may be overcome to progress the field.

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