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Nuno Bandeira: Missing Nothing With Mass Spec


Title: Assistant professor, University of California, San Diego
Education: PhD, University of California, San Diego, 2007
Recommended by: Pavel Pevzner, University of California, San Diego

Nuno Bandeira's lab is trying to catch bioinformatics methods up to the task of sorting through the masses of data that are the results of advances in mass spectrometry technologies. Bandeira is specifically focused on developing algorithmic and statistical approaches to better identify and quantify proteins, post-translational modifications, protein structure features, and protein-protein interactions. "Nowadays the mass spec instruments are so good that the problem becomes digital. ... In a typical proteomics experiment, we only identify about a quarter of everything, because we don't have good ways to identify the spectra," Bandeira says. "This even gets worse when we go to types of samples like [those from] the Human Microbiome Project or environmental proteomics samples. … A lot of stuff is being missed simply because many of the algorithms fail to identify what's in the data."

To help tackle this problem, Bandeira developed the spectral networks database analysis method. He says it is a departure from previous approaches that interpret each spectrum in isolation, since it takes advantage of spectral pairs to greatly reduce the number of noise peaks and generate a small number of peptide reconstructions that are likely to contain the correct one, resulting in fast pattern-matching mass spec database searches.

Looking ahead

Bandeira says that in the next five to 10 years, he would like to see proteomics catch up to genomics in terms of effective identification methodologies. "I think that the challenge facing us today is to have the ability to take any proteomics sample and to have 100 percent identification rates every single time," he says. "Genomics has come a lot closer to that than mass spec, and if we could get to the point where investigating any sample we can be as thorough in our identification as genomics and quantify what is in there, I think that would be great."

Publications of note

In 2009, Bandeira published "Dereplication and de novo sequencing of nonribosomal peptides" in Nature Methods, which details an approach for high-throughput non-ribosomal peptides de-replication and sequencing using multistage mass spectrometry with spectral alignment algorithms to sequence cyclic non-ribosomal peptides. He and his team were also able to establish similarities between newly isolated and previously identified similar but non-identical non-ribosomal peptides through the development of a new algorithm, thereby significantly reducing de-replication efforts.

And the Nobel goes to ...

Bandeira says that if he could one day win the Nobel Prize he would like it to be for developing an algorithm that would enable researchers to identify every protein and peptide in a single proteomics experiment. "That would certainly be something that would have [a] huge impact in the field because [we] would then be able to characterize potential biomarkers with much more accuracy," he says. "If we could make a substantial contribution to that, it would be awesome."

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