Spritz: A Proteogenomic Database Engine

Abstract

Proteoforms are the workhorses of the cell, and subtle differences between their amino acid sequence or post-translational modifications (PTMs) can change their biological function. To most effectively identify and quantify proteoforms in genetically diverse samples by mass spectrometry (MS), it is advantageous to search the MS data against a sample-specific protein database that is tailored to the sample being analyzed, in that it contains the correct amino acid sequences and relevant PTMs for that sample. To this end, we have developed Spritz (https://smith-chem-wisc.github.io/Spritz/), an open-source software tool for generating protein databases annotated with sequence variations and PTMs. We provide a simple graphical user interface (GUI) for Windows and scripts that can be run on any operating system. Spritz automatically sets up and executes approximately 20 tools, which enable construction of a proteogenomic database from only raw RNA sequencing data. Sequence variations that are discovered in RNA sequencing data upon comparison to the Ensembl reference genome are annotated on proteins in these databases, and PTM annotations are transferred from UniProt. Modifications can also be discovered and added to the database using bottom-up mass spectrometry data and global PTM discovery in MetaMorpheus. We demonstrate that such sample-specific databases allow the identification of variant peptides, modified variant peptides, and variant proteoforms by searching bottom-up and top-down proteomic data from the Jurkat human T lymphocyte cell line and demonstrate the identification of phosphorylated variant sites with phosphoproteomic data from the U2OS human osteosarcoma cell line.

Immunopeptidogenomics: Harnessing RNA-Seq to Illuminate the Dark Immunopeptidome

“…, Refs. ( 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 )). The immunopeptidogenomics workflow presented here needs only sample-specific RNA-Seq data to produce a single customized DB incorporating conventional peptides, neopeptides from SNVs/polymorphisms and noncomplex indels, and cryptic peptides derived from noncanonical translation, such as alternative reading frames and noncoding RNA regions/transcripts.…”

Personalized Proteome: Comparing Proteogenomics and Open Variant Search Approaches for Single Amino Acid Variant Detection

“…There are considerable challenges still to face in their detection, particularly in noise/signal differentiation. This is especially complicated as variants often co-occur with other PTMs such as phosphorylation. , Current detection methods including ionbot cannot handle the complexity of two modifications on one site. However, deep neural networks show great promise with difficult peptide identifications .…”

“…A proteogenomics approach where only those variant peptides predicted from genome or transcriptome information are added to the peptide search databases can improve their detection. Proteogenomics pipelines have streamlined this process of incorporating personal genome information into a proteomic search database. − In addition, there is evidence that including correct sequence variant information, including often-overlooked sample-specific indels and frameshifts, improves variant peptide identification workflows . Yet, false discovery rate (FDR) correction is needed to compensate for the increase of database size and complexity. , When searching for evidence of specific peptides such as variant peptides, an additional subset-specific FDR correction should be made …”

Cloudy with a Chance of Peptides: Accessibility, Scalability, and Reproducibility with Cloud-Hosted Environments

“…Examples of free or open-source proteomic software that can run in a Linux environment include Crux 14 , EncyclopeDIA 15 , FragPipe 16,17 , ProteoWizard 18 , SearchGUI 19 , The OpenMS Proteomics Pipeline (referred to as OpenMS or TOPP) 20,21 , Trans-Proteomic Pipeline (TPP) 22,23 , and X!Tandem 24 . Other tools that run in Windows but can also be run via command line in a Linux environment include MaxQuant 25,26 , MetaMorpheus 27 , and Spritz 28 . In order to truly take advantage of the scalability of cloud environments, software that can work in a clustered environment is preferred.…”