By default, most of our peptide mapping workflows rely only on MS2 identified peptides for quantification. Occasionally you may find you want to quantify peptides with no MS2 spectra identified. In Protein Metrics’ software you can accomplish this with in-silico peptides. In the broadest sense, in-silico is a way to generate an XIC for any peptide. This allows consistent quantitation of peptides even when MS2 spectra are absent or of poor quality. Any added in-silico peptides can be easily distinguished from their MS2 based neighbors by a “Yes” in the “In Silico” column. Five distinct methods exist to create in-silico peptides, each targeted for a different need:
- Automated In-silico Generation via a Theoretical Digest: During project creation, a configurable in-silico digest may be performed that will create entries for all expected peptides. There are also methods that allow you to see and edit the list of mods from your theoretical digest.
- CSV In-silico Import: Either during or after creation, a CSV list of in-silico peptides may be imported into the project.
- Add Missing via Existing: Automatically generates in-silico entries for missing peptides found in only some of the files within a project.
- Create New Peptide from Current: Creates an in-silico entry modeled on an existing peptide; useful for adding additional charge states or isomeric modifications.
- With the introduction of our new Feature Finder tool: You can now also annotate previously unknown features with In-silico identifications.
To turn on a theoretical digest in one of your PTM projects, do so in the "Processing nodes" tab of the workflow. Look for the section called "In-silico options" and set the "Enable In-Silico" line to "Yes". Next, set up the conditions for which you would like to see theoretical peptides by setting the digest type, number of cleavages and peptide mass ranges. Finally, add just the key modifications you are looking for, as you will get an XIC for every permutation you enter.
Alternatively, you can create and edit a list of in-silico peptides and add them via the "In-Silico Peptides CSV" instead (in this case, you would set the "Enable In-Silico" to "No", but include a csv file.) There are a couple of ways to generate the in-silico file. The easiest is to go to an MS2 based inspection project in Byos/Byologic that has the species you want and export it using the "Edit"/"In-silico Peptides"/"Export in-silico to CSV". A second work-around for generating a theoretical CSV is to go to native Byologic or Byomap and hit the new project icon. On the popup that appears, add a sequence in the "Protein input" tab, then on the "In-silico options" tab check the In-silico check box and select the "Use table" radio button and finally click the "Generate peptides by digesting proteins" button. This will pop up another box where you can configure the theoretical digest; do so and then click the "Generate" button.
Following the steps above will produce a table of in-silico peptides which you can edit within Byos or export to CSV and edit there. To export the table, right click on any row and select the "Export table to CSV" and select the “formatted” option when prompted.
A third method of adding in-silico peptides is helpful in multi-file projects when you have an MS2 identified species in one file and want to get MS1 quantification of that species in another file. To do so, you can use the "Edit"/"In-silico Peptides"/"Add missing via existing peptides" option. This will look at the species found in each file and if that species is missing in another file, it will automatically add an MS1 only XIC to that file. One caveat is that when using this option, you need to make sure the "peptide grouping method" is set to "Separate charge states".
Method four for adding in-silico peptides is via the “Create new peptide from current” function which makes a copy of the current peptide. This function is commonly used to add charge states or allow XIC plots to be split into separate integrations. To use the function, right click on the peptide in the “Peptides” table. From the menu that appears, select the “Create new peptide from current” option. The analyst can then edit the start and end times and the charge of the peptide before the copy is created:
The final and newest method of adding in-silico entries is via the “Intersect In-silico Peptides with CSV Library” function. Our new Feature Finder option allows the addition of unknown MS1 only features to a Byologic project. However once they are added, you may find the masses and retention times match knowns you identified through another method (for example common HCPs, contaminants or through a secondary focused search of your data). In these cases, you may now update these identifications by providing an in-silico CSV file with matching masses and retention times. To use the new function, select “Edit”, “In-silico Peptides”, “Intersect Peptides with CSV Library” and on the screen that pops up, navigate to the CSV file and specify appropriate time- and mass-tolerance criteria.
One last bit of advice: If you plan on using in-silico peptides in a project, it is a good idea to turn on the "XIC alignment for In-silico peptides" feature. This feature permits the time alignment of in-silico peptides from both the "add in-silico peptides from CSV file" as well as "add missing via existing peptides" options. The feature allows you to specify a retention time or XIC width shift. The feature will automatically adjust in-silico XICs to the data and the analyst will not have to manually adjust in-silico XIC windows. To activate the feature, simply add the following advanced commands. Note, these commands do not need to be applied at project creation.
FeatureCenterTolerance=0.5
FeatureDurationTolerance=0.1
The “FeatureCenterTolerance” is the tolerance (in minutes) of feature center for aligning the in-silico feature while the “FeatureDurationTolerance” is the tolerance (in minutes) of feature duration for aligning the in-silico feature.
As of Byos v5.4, users can replace the above advanced commands with a single command to enable multiple improvements.
[InSilicoAlign]
Enabled=true