Using Scaffold OHRI Proteomics Core Facility

This presentation is intended for Core Facility internal training purposes only

Contents 1. What is Scaffold? 2. Key points and pitfalls 3. Overview of Main Features 4. Outline of Additional Features

What are Mascot and Scaffold? Scaffold is a software for interactively viewing proteomics results. ◦Scaffold gets its data from Mascot. Mascot is a software for matching observed mass spectra to peptide sequences by refering to a database of known proteins. ◦Mascot does NOT ‘sequence’ the proteins, it MATCHES observed spectra to predicted spectra based on a reference genome The Core Facility will send your results as a Scaffold file.

Downloading Scaffold Viewer Scaffold Viewer is free Download it from: PC, Mac or Linux versions available

Run Scaffold Viewer The default Scaffold view is a list of identified proteins

Key Points and Pitfalls 1. BIO vs. MS mode 2. Thresholds 3. Display Options 4. Normalization

1. BIO vs MS modes MS mode shows each MS analysis separately. BIO mode groups all MS samples that belong to the same “Biosample”. For gels, a biosample often corresponds to a lane and the MS samples correspond to the individual gel bands.

Scaffold organizes data using 3 classifications untreated treated Categories Biosamples MS samples (in this example, there are two indepedent biological samples in each category) A biosample can contain multiple MS samples; e.g. bands from a lane or fractions from an HPLC separation.

2. Thresholds Scaffold defaults to requiring 2 or more peptides to consider a protein identification valid. For some projects, such as PTM enrichment experiments, you should change Min # of Peptides to 1. The other thresholds can also be adjusted depending on your required stringency.

3. Display Options You can set the “Display Options” pulldown to different choices, such as: ◦Protein identification probability ◦Total spectrum count (a proxy for protein abundance) ◦Quantitative Value (see the Experiment: Quantitative Analysis... Menu to change how the quantitative value is determined)

4. Normalization Normalization mode is very important!! If your samples have mostly similar levels of protein with only some proteins differing, then normalization should be ON. Scaffold will normalize the counts by assuming that most proteins should be the same abundance across all samples. If your samples are expected to have mostly different abundances of proteins, then normalization should be OFF. To change modes you can: (a) Check or uncheck the Normalization checkbox in the Experiment: Quantitative Analysis... menu (b) Choose a normalized or non-normalized value from the “Display Options” pull-down on the main results screen. Important: Scaffold defaults to Normalization ON!

Overview of Scaffold Highlights of the main features

Samples mode shows all proteins that were identified Uncheck the ‘visible’ boxed to hide irrelevant proteins such as keratins The “Display Options” pulldown controls what value is reported for each protein across each sample Results for each sample are reported in this table. See your Proteomics Service Report for sample names and numbers Double-click a protein name to get detailed observations for that protein (switches to Proteins mode)

Proteins mode shows what peptides were identified for that protein These tables shows which samples contained which peptides, and the evidence supporting each identification (e.g. Mascot score) Select a protein from this pulldown box, or by double-clicking on a protein name in one of the other modes This table shows matched peptides relative to the reference protein sequence.

Quantify mode can be used to make some basic figures You can graph the spectral count across different samples Venn diagram of the proteins absent/present in different categories Plot spectral counts for each protein according to sample categories. Make sure you have set the correct normalization mode! Scaffold can plot the abundance of GO terms associated with the identified proteins (optional)

Additional Features Some features are only available in the full paid version of Scaffold You can request these features from the Core Facility, for example ◦Plot GO terms ◦Statistical tests of significance comparing spectral counts between categories (requires multiple biosamples per category) ◦Change the categories or sample groupings

Additional Features Scaffold Q+S ◦can be used to view SILAC or iTRAQ data ◦Note: SILAC requires additional data processing via MaxQuant or other SILAC software Scaffold PTM ◦can be used to study data on post-translational modifications ◦PTMs are NOT searched for unless requested! The Core Facility can import your data into these modules

IMPORTANT! By default, Scaffold uses spectral counts as a measure of protein abundance, and there is good evidence supporting their use, however... The standard proteomics service uses a qualitative method intended for efficient and sensitive protein identification; it is NOT a quantitative method. Technical variation between LC-MS/MS runs can be high. Avoid over-interpreting from low numbers of spectral counts (e.g. 1 count vs. 2 counts interpreted as a 2x fold change ). Accurate quantification requires special techniques such as iTRAQ, SILAC, ICAT or AQUA.