mass spec

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Prof. Josh Elias (left) of Stanford University receives a thank-you gift from David Chiang after his talk.

Ever wondered about target-decoy searching? Want to gain a better understanding and realistic expectation of this effective tool? SageNResearch’s video “Addressing Peptide Identification Signal-to-noise With Target-Decoy Searching”, given by Professor Josh Elias of Stanford University at our “Translational Proteomics 2.0″ meeting, can help. Dr. Elias is an Assistant Professor in Chemical and Systems Biology at Stanford University, and was part of the Steven Gygi Lab at Harvard Medical School before that. His lab is keenly interested in developing and applying methods to meet the current challenges facing scientists engaged in large scale proteome characterization.

Josh kicked off his talk with a stunning and very powerful visual to hit home the concept of what target-decoy database searching can do — you’ll never look at coffee beans in quite the same way. With this talk, you’ll know how to better find a happy medium for thresholds, smarter ways of designing your filtering criteria, when not to even consider using the method, how to get the most out of (really easy) decoy searching in SORCERER, and what’s so good about partial tryptic searches.

The 30-minute presentation is available at: http://www.scivee.tv/node/15544
To view slides, I recommend using the “full screen” mode. The slide set can also be downloaded as a Powerpoint file.

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by David.Chiang@SageNResearch.com

Proteomics mass spectrometry is finally sensitive and specific enough for robust translational medicine (at least in capable hands), and holds tremendous promise to revolutionize biology and medicine. For some, it holds the key to incredible research power for decades to come.

However, there is a chasm that continues to grow between the productive and unproductive labs, because too many proteomics practitioners focus too early on low-level issues (i.e. cost, automation, ease-of-use) without first resolving high-level ones (i.e. sensitivity in presence of noise, quality of results, algorithmic suitability).

For many researchers experimenting with a new high-resolution instrument, the most common scenario is to select a workflow based on running a simple protein solution, usually a purified BSA solution or a commercial protein mixture.

Since different workflows will give basically identical protein IDs results for these simple test cases, they may conclude that all search engines are equivalent. While true when there is almost no signal noise, it is largely irrelevant in translational research. In fact, the exact same test will likely show that low-resolution and high-resolution mass specs are equivalent, the lowest quality reagents will suffice, or maybe you don’t have to clean your glassware as often. These are also true when there is little or no signal noise, but again, that is irrelevant for real-world research.

Seeing that there is little difference in protein IDs, some focus on using protein coverage as the sole metric for evaluating search engines. However, this is actually the opposite of what is needed for sensitive discovery proteomics. For example, if you are hunting for new protein biomarkers (especially a “one-hit wonder”), you do not want the protein inference engine tuned to assigning any ambiguous peptides to already found proteins, thereby hiding them from further study.

Not surprisingly, a workflow selected based on low-noise experiments and focused on protein coverage will excel for simple mixtures, but is not sensitive enough to analyze complex mixtures with wide dynamic range, such as in translational research. Scientists will be able to see the abundant peptides and proteins, but probably little else. That is roughly what most proteomics researchers find today, nothing meaningful, but enough of the obvious to not change their methodologies.

The result is that most labs are not getting the value commensurate with their investments in proteomics mass spectrometry. Under the current economic environment, this is both wasteful and dangerous.

Within the academic world, while many proteomics researchers have trouble getting any interest, a select few are swamped and have to turn away collaborators. Within drug discovery firms, while many are staring at their mostly idle mass spectrometers, a select few are running multiple mass spectrometers 24/7 sieving productively through millions of peptides.

So why are the majority of the proteomics research not producing high-value results?

With our access into the world’s top academic and drug discovery proteomics labs, we have a unique bird’s eye view into the answer. (However, like attorneys, we never give out client-specific information.)

Please allow me to share some secrets to your future success.

Read the rest of this entry »

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N-linked protein glycosylation is a common post-translational modification (PTMs) in many cellular processes. Atwood et al (RCMS 2005) describe a tandem mass spec-based methodology to analyze N-linked glycopeptides.

Enriched glycopeptides are treated with peptide N-glycosidase F, which removes the carbohydrate moieties from the peptide backbone. Deglycosylated peptides are analyzed with a tandem mass spec. The resulting MS/MS spectra are searched against a modified protein sequence database that allows only PTMs on N’s within the consensus sequence N-x-y, where x is any residue other than proline, and y is either serine or threonine.

To analyze this PTM on the deglycosylated peptides on SORCERER, we need to search for a monoisotopic mass shift of 0.9840 Da on N’s only in the {N[^P][ST]} consensus sequence.

To search this PTM on the SORCERER, we do the following 2 steps:

1) Create a new protein sequence database that replaces ‘N’ with ‘J’ in the consensus sequence.

2) Prepare this new sequence database for searching by defining ‘J’ to have the same mass as ‘N’ using a static modification setting on ‘J’.

3) Submit a search on SORCERER with a variable modification search on ‘J’ with a mass shift of +0.9840 Da.

Create New Protein Database

Use the MUSE script ‘nlinkglyco-fasta.mu’ (part of SORCERER PE v3.5) to create a new protein sequence database that replaces each N in the consensus sequence with J.

Simply log onto SORCERER, go to directory ‘/home/sorcerer/fasta/’ where the protein sequences are, and create a new fasta file from an existing one (for example, create ‘ipi.human_n2j.fasta’ from ‘ipi.HUMAN.fasta’) . Then use prepare this new fasta file for searching as you would any other protein sequence file.

Once you log onto the SORCERER, and type the following 2 commands (do not type the ‘sorc$’ which is the SORCERER prompt):

   sorc$ cd /home/sorcerer/fasta/

   sorc$ nlinkglyco-fasta.mu < ipi.HUMAN.fasta > ipi.human_n2j.fasta

The latter command literally means to run the MUSE script using “standard input” from file ipi.HUMAN.fasta (after the ‘<’ symbol) and sending the “standard output” to the new file ipi.human_n2j.fasta (after the ‘>’ symbol).

(The script may be easily copied and modified for another consensus sequence. Contact TechTeam for details.)

Prepare Database for Searching

When the new protein sequence database is prepared for searching, assign a static modification ‘MakeN’ of -9885.95707256 Da. This will cause the final ‘J’ mass to be the monoisotopic mass of 114.04292744 Da. (The normally unused codes ‘J’ and ‘U’ are set at 10,000 Da to flag any inadvertent usage.) The resulting peptide database will be used for subsequent searching.

SORCERER Search

The search can now be submitted by creating a user-defined variable modification ‘Nlinkglyco’ with mass of 0.9840 Da on the residue ‘N’ against the new peptide database.

 

We thank Dr. Rebekah Gundry from the Van Eyk Lab at Johns Hopkins for bringing this SORCERER application to our attention!

Reference: Atwood et al (Rapid Comm Mass Spec 2005; 19: 3002-3006 DOI: 10.1002/rcm.2162)

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Dr. John Yates from the Scripps Research Institute gave the talk “Driving Biological Discovery using Quantitative Mass Spectrometry” at the 2008 Proteomics 2.0 Meeting hosted by Sage-N Research.

 

The audio MP3 file is available by download here (click to play, right click to download):

   SageN002_JYates_2008Jun_57m.mp3

The complete slideset is available by download in 5 parts here (click to view, right click to download):

  SageN002_JYates_2008Jun_part1.pdf

   SageN002_JYates_2008Jun_part2.pdf

   SageN002_JYates_2008Jun_part3.pdf

   SageN002_JYates_2008Jun_part4.pdf

   SageN002_JYates_2008Jun_part5.pdf

The meeting was held on June 1, 2008 in Denver, just before the ASMS conference.
 

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