Enhanced differential expression statistics for data-independent acquisition proteomics

Suomi, Tomi; Elo, Laura L.

doi:10.1038/s41598-017-05949-y

Cited by 51 publications

(65 citation statements)

References 30 publications

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“…In a first step, the proteins that significantly interact with the bait were identified by calculating their differential expression in conditions expressing the Twin-Strep-tagged bait (PD-1-OST or BTLA-OST) as compared to conditions expressing the same levels of the corresponding untagged proteins (PD-1 and BTLA). A paired and reproducibility optimized test strategy was used from the R/Bioconductor package PECA ( Suomi and Elo, 2017 ). Proteins that showed a more than 3-fold (mouse CD4 + cells) or 6-fold (human Jurkat cells) higher abundance in the samples containing the bait versus control samples and an adjusted FDR of less than 0.01 across the 3 biological replicates of an experimental condition were considered as interactors.…”

Section: Methodsmentioning

confidence: 99%

Quantitative Interactomics in Primary T Cells Provides a Rationale for Concomitant PD-1 and BTLA Coinhibitor Blockade in Cancer Immunotherapy

et al. 2019

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Summary Deciphering how TCR signals are modulated by coinhibitory receptors is of fundamental and clinical interest. Using quantitative interactomics, we define the composition and dynamics of the PD-1 and BTLA coinhibitory signalosomes in primary effector T cells and at the T cell-antigen-presenting cell interface. We also solve the existing controversy regarding the role of the SHP-1 and SHP-2 protein-tyrosine phosphatases in mediating PD-1 coinhibition. PD-1 predominantly recruits SHP-2, but when absent, it recruits SHP-1 and remains functional. In contrast, BTLA predominantly recruits SHP-1 and to a lesser extent SHP-2. By separately analyzing the PD-1-SHP-1 and PD-1-SHP-2 complexes, we show that both dampen the TCR and CD28 signaling pathways equally. Therefore, our study illustrates how comparison of coinhibitory receptor signaling via quantitative interactomics in primary T cells unveils their extent of redundancy and provides a rationale for designing combinations of blocking antibodies in cancer immunotherapy on the basis of undisputed modes of action.

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Section: Methodsmentioning

confidence: 99%

Quantitative Interactomics in Primary T Cells Provides a Rationale for Concomitant PD-1 and BTLA Coinhibitor Blockade in Cancer Immunotherapy

et al. 2019

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“…( https://www.R-project.org/ ). For proteomics, the data was transformed using centered log-ratio transformation (CLR) and differentially expressed peptides between groups (samples with below or above median Bacteroides relative abundance according to 16S rRNA gene sequencing results) were assessed with ROPECA 43 using the modified t test with False discovery rate (FDR) cut-off set to 0.01 or 0.05. Heatmaps from the intensities of differentially expressed CAZy enzymes were generated using the Pretty Heatmaps R package.…”

Section: Methodsmentioning

confidence: 99%

A carbohydrate-active enzyme (CAZy) profile links successful metabolic specialization of Prevotella to its abundance in gut microbiota

Aakko

Pietilä

Toivonen

et al. 2020

Sci Rep

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Gut microbiota participates in diverse metabolic and homeostatic functions related to health and well-being. Its composition varies between individuals, and depends on factors related to host and microbial communities, which need to adapt to utilize various nutrients present in gut environment. We profiled fecal microbiota in 63 healthy adult individuals using metaproteomics, and focused on microbial CAZy (carbohydrate-active) enzymes involved in glycan foraging. We identified two distinct CAZy profiles, one with many Bacteroides-derived CAZy in more than one-third of subjects (n = 25), and it associated with high abundance of Bacteroides in most subjects. In a smaller subset of donors (n = 8) with dietary parameters similar to others, microbiota showed intense expression of Prevotella-derived CAZy including exo-beta-(1,4)-xylanase, xylan-1,4-beta-xylosidase, alpha-larabinofuranosidase and several other CAZy belonging to glycosyl hydrolase families involved in digestion of complex plant-derived polysaccharides. This associated invariably with high abundance of Prevotella in gut microbiota, while in subjects with lower abundance of Prevotella, microbiota showed no Prevotella-derived CAZy. Identification of Bacteroides-and Prevotella-derived cAZy in microbiota proteome and their association with differences in microbiota composition are in evidence of individual variation in metabolic specialization of gut microbes affecting their colonizing competence.

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“…Four proteins, P07724, Q921I1, P02768, and P02787, were removed due to the interference between the spiked-in proteins and the background of human proteins. The three replicates from group S8 were not used for statistical testing (28). Next, the data were filtered by FDR and intensity thresholds like the Spike-in-biol-var-OT dataset.…”

Section: Lc/ms Acquisition Of Spike-in-biol-var-ot Mp-lfc-ms1var-ot mentioning

confidence: 99%

Combining Precursor and Fragment Information for Improved Detection of Differential Abundance in Data Independent Acquisition

Huang

Bruderer

Muntel

et al. 2020

Molecular & Cellular Proteomics

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In bottom-up, label-free discovery proteomics, biological samples are acquired in a data-dependent (DDA) or data-independent (DIA) manner, with peptide signals recorded in an intact (MS1) and fragmented (MS2) form. While DDA has only the MS1 space for quantification, DIA contains both MS1 and MS2 at high quantitative quality. DIA profiles of complex biological matrices such as tissues or cells can contain quantitative interferences, and the interferences at the MS1 and the MS2 signals are often independent. When comparing biological conditions, the interferences can compromise the detection of differential peptide or protein abundance and lead to false positive or false negative conclusions.We hypothesized that the combined use of MS1 and MS2 quantitative signals could improve our ability to detect differentially abundant proteins. Therefore, we developed a statistical procedure incorporating both MS1 and MS2 quantitative information of DIA. We benchmarked the performance of the MS1-MS2-combined method to the individual use of MS1 or MS2 in DIA using four previously published controlled mixtures, as well as in two previously unpublished controlled mixtures. In the majority of the comparisons, the combined method outperformed the individual use of MS1 or MS2. This was particularly true for comparisons with low fold changes, few replicates, and situations where MS1 and MS2 were of similar quality. When applied to a previously unpublished investigation of lung cancer, the MS1-MS2-combined method increased the coverage of known activated pathways.Since recent technological developments continue to increase the quality of MS1 signals (e.g. using the BoxCar scan mode for Orbitrap instruments), the combination of the MS1 and MS2 information has a high potential for future statistical analysis of DIA data.

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Enhanced differential expression statistics for data-independent acquisition proteomics

Cited by 51 publications

References 30 publications

Quantitative Interactomics in Primary T Cells Provides a Rationale for Concomitant PD-1 and BTLA Coinhibitor Blockade in Cancer Immunotherapy

Quantitative Interactomics in Primary T Cells Provides a Rationale for Concomitant PD-1 and BTLA Coinhibitor Blockade in Cancer Immunotherapy

A carbohydrate-active enzyme (CAZy) profile links successful metabolic specialization of Prevotella to its abundance in gut microbiota

Combining Precursor and Fragment Information for Improved Detection of Differential Abundance in Data Independent Acquisition

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