A Causal Model of Ion Interference Enables Assessment and Correction of Ratio Compression in Multiplex Proteomics.

Multiplex proteomics using isobaric labeling tags has emerged as a powerful tool for the simultaneous relative quantification of peptides and proteins across multiple experimental conditions. However, the quantitative accuracy of the approach is largely compromised by ion interference, a phenomenon that causes fold changes to appear compressed. The degree of compression is generally unknown, and the contributing factors are poorly understood. In this study, we thoroughly characterized ion interference at the MS2 level using a defined two-proteome experimental system with known ground-truth. We discovered remarkably poor agreement between the apparent precursor purity in the isolation window and the actual level of observed reporter ion interference in MS2 scans-a discrepancy that we found resolved by considering cofragmentation of peptide ions hidden within the spectral "noise" of the MS1 isolation window. To address this issue, we developed a regression modeling strategy to accurately predict reporter ion interference in any dataset. Finally, we demonstrate the utility of our procedure for improved fold change estimation and unbiased PTM site-to-protein normalization. All computational tools and code required to apply this method to any MS2 TMT dataset are documented and freely available.

In Search of a Universal Method: A Comparative Survey of Bottom-Up Proteomics Sample Preparation Methods.

Robust, efficient, and reproducible protein extraction and sample processing is a key step for bottom-up proteomics analyses. While many sample preparation protocols for mass spectrometry have been described, selecting an appropriate method remains challenging since some protein classes may require specialized solubilization, precipitation, and digestion procedures. Here, we present a comprehensive comparison of the 16 most widely used sample preparation methods, covering in-solution digests, device-based methods, and commercially available kits. We find a remarkably good performance of the majority of the protocols with high reproducibility, little method dependency, and low levels of artifact formation. However, we revealed method-dependent differences in the recovery of specific protein features, which we summarized in a descriptive guide matrix. Our work thereby provides a solid basis for the selection of MS sample preparation strategies for a given proteomics project.

amica: an interactive and user-friendly web-platform for the analysis of proteomics data.

BACKGROUND: Quantitative proteomics has become an increasingly prominent tool in the study of life sciences. A substantial hurdle for many biologists are, however, the intricacies involved in the associated high throughput data analysis. RESULTS: In order to facilitate this task for users with limited background knowledge, we have developed amica, a freely available open-source web-based software that accepts proteomic input files from different sources. amica provides quality control, differential expression, biological network and over-representation analysis on the basis of minimal user input. Scientists can use amica's query interface interactively to compare multiple conditions and rapidly identify enriched or depleted proteins. They can visualize their results using customized output graphics, and ultimately export the results in a tab-separated format that can be shared with collaborators. The code for the application, input data and documentation can be accessed online at https://github.com/tbaccata/amica and is also incorporated in the web application. CONCLUSIONS: The strong emphasis on dynamic user interactions, the integration of various databases and the option to download processed data, facilitate the analysis of complex proteomic data for both first-time users and experienced bioinformaticians. A freely available version of amica is available at https://bioapps.maxperutzlabs.ac.at/app/amica .

The guanine nucleotide exchange factor Rin-like controls Tfh cell differentiation via CD28 signaling.

T follicular helper (Tfh) cells are essential for the development of germinal center B cells and high-affinity antibody-producing B cells in humans and mice. Here, we identify the guanine nucleotide exchange factor (GEF) Rin-like (Rinl) as a negative regulator of Tfh generation. Loss of Rinl leads to an increase of Tfh in aging, upon in vivo immunization and acute LCMV Armstrong infection in mice, and in human CD4+ T cell in vitro cultures. Mechanistically, adoptive transfer experiments using WT and Rinl-KO naïve CD4+ T cells unraveled T cell-intrinsic GEF-dependent functions of Rinl. Further, Rinl regulates CD28 internalization and signaling, thereby shaping CD4+ T cell activation and differentiation. Thus, our results identify the GEF Rinl as a negative regulator of global Tfh differentiation in an immunological context and species-independent manner, and furthermore, connect Rinl with CD28 internalization and signaling pathways in CD4+ T cells, demonstrating for the first time the importance of endocytic processes for Tfh differentiation.