Biology subjects

Kyriakidou, P.

Publications and source records attributed to Kyriakidou, P..

5 recordsLinked to original sources

bioRxiv2025

Improved peptide search for identification of SUMO and sequence-based modifications, in MaxSBM

Post-translational modifications (PTMs), such as SUMOylation and ubiquitination, regulate key cellular processes by covalently attaching to lysine residues. While mass spectrometry allows site-specific identification of PTMs, most existing search engines are optimized for small, non-fragmenting modifications and struggle to detect large, fragmenting protein-based modifiers. We refer to these as Sequence-Based Modifiers (SBMs). To overcome this limitation, we developed an SBM-specific search strategy within MaxQuant that accounts for the fragmentation behavior of SBMs during peptide identification. Using publicly available datasets, we validated our approach for SUMO2/3. Our analysis identified distinct diagnostic features and characteristic mass shifts associated with SBM fragmentation, referred to in this study as d-ions (diagnostic ions) and p-ions. By leveraging these features, our method improved the identification of SUMOylated peptides from human cell lines by 13%, SUMOylation sites in mouse embryonic cells by 18%, and in mouse adipocytes by 25%. Our search method improved spectral annotation of SBMs by up to 9% increase in the median Andromeda score. Taken together, we highlight the potential of our SBM search to enhance the discovery of protein-based modifications. HighlightsO_LIDevelopment of a MaxQuant module tailored for identifying Sequence-Based Modifiers (SBMs), including SUMO2/3 C_LIO_LIIncorporation of SBM-specific fragmentation patterns into search algorithms C_LIO_LIEnhanced biological discovery through improved PTM identification from mass spectrometry datasets C_LI In BriefHere, we introduce MaxSBM, an optimized framework for interpreting complex sequence-based modifiers (SBMs), particularly SUMO, within MaxQuant. Our approach incorporates SBM-specific d- and p-ion series into peptide scoring and annotation. By extending the theoretical spectral space to include fragments bearing partial SUMO (or other SBM) peptide remnants, MaxSBM provides a more comprehensive spectral annotation which enhances peptide scoring, resulting in increased identification rates at a higher confidence. Beyond methodological refinement, we validated MaxSBM via reanalysis of several physiological SUMO datasets, ultimately unlocking new insights via mapping of previously obscured modification sites.

bioinformatics↗

bioRxiv2024

Isobaric labeling update in MaxQuant

We present an update of the MaxQuant software for isobaric labeling data and evaluate its performance on benchmark datasets. Impurity correction factors can be applied to labels mixing C- and N-type reporter ions, such as TMT Pro. Application to a single-cell multi-species mixture benchmark shows high accuracy of the impurity-corrected results. TMT data recorded with FAIMS separation can be analyzed directly in MaxQuant without splitting the raw data into separate files per FAIMS voltage. Weighted median normalization, is applied to several datasets, including large-scale human body atlas data. In the benchmark datasets the weighted median normalization either removes or strongly reduces the batch effects between different TMT plexes and results in clustering by biology. In datasets including reference channels, we find that weighted median normalization performs as well or better when the reference channels are ignored and only the sample channel intensities are used, suggesting that the measurement of reference channels is unnecessary when using weighted median normalization in MaxQuant. We demonstrate that MaxQuant including the weighted median normalization performs well on multi-notch MS3 data, as well as on phosphorylation data. MaxQuant is freely available for any purpose and can be downloaded from https://www.maxquant.org/.

bioinformatics↗

bioRxiv2023

Enamel proteins reveal biological sex and genetic variability within southern African Paranthropus

The evolutionary relationships among extinct African hominin taxa are highly debated and largely unresolved, due in part to a lack of molecular data. Even within taxa, it is not always clear, based on morphology alone, whether ranges of variation are due to sexual dimorphism versus potentially undescribed taxonomic diversity. For Paranthropus robustus, a Pleistocene hominin found only in South Africa, both phylogenetic relationships to other taxa 1,2 and the nature of intraspecific variation 3-6 are still disputed. Here we report the mass spectrometric (MS) sequencing of enamel proteomes from four ca. 2 million year (Ma) old dental specimens attributed morphologically to P. robustus, from the site of Swartkrans. The identification of AMELY-specific peptides and semi-quantitative MS data analysis enabled us to determine the biological sex of all the specimens. Our combined molecular and morphometric data also provide compelling evidence of a significant degree of variation within southern African Paranthropus, as previously suggested based on morphology alone 6. Finally, the molecular data also confirm the taxonomic placement of Paranthropus within the hominin clade. This study demonstrates the feasibility of recovering informative Early Pleistocene hominin enamel proteins from Africa. Crucially, it also shows how the analysis of these proteins can contribute to understanding whether hominin morphological variation is due to sexual dimorphism or to taxonomic differences. We anticipate that this approach can be widely applied to geologically-comparable sites within South Africa, and possibly more broadly across the continent.

evolutionary biology↗

bioRxiv2021

Spectrum graph-based de-novo sequencing algorithm MaxNovo achieves high peptide identification rates in collisional dissociation MS/MS spectra

We describe MaxNovo, a novel spectrum graph-based peptide de-novo sequencing algorithm integrated into the MaxQuant software. It identifies complete sequences of peptides as well as sequence tags that are incomplete at one or both of the peptide termini. MaxNovo searches for the highest-scoring path in a directed acyclic graph representing the MS/MS spectrum with peaks as nodes and edges as potential sequence constituents consisting of single amino acids or pairs. The raw score is a sum of node and edge weights, plus several reward scores, for instance, for complementary ions or protease compatibility. For search-engine identified peptides, it correlates well with the Andromeda search engine score. We use a particular score normalization and the score difference between the first and second-best solution to define a combined score that integrates all available information. To evaluate its performance, we use a human cell line dataset and take as ground truth all Andromeda-identified MS/MS spectra with an Andromeda score of at least 100. MaxNovo outperforms other software in particular in the high-sensitivity range of precision-coverage plots. We also identify incomplete sequence tags and study their statistical properties. Next, we apply MaxNovo to ion mobility-coupled time of flight data. Here we achieve excellent performance as well, except for potential swaps of the two amino acids closest to the C-terminus, which are not well resolved due to the low end of the mass range in MS/MS spectra in this dataset. We demonstrate the applicability of MaxNovo to palaeoproteomics samples with a Late Pleistocene hominin proteome dataset that was generated using three proteases. Interestingly, we did not use any machine learning in the construction of MaxNovo, but implemented expert domain knowledge directly in the definition of the score. Yet, it performs as good as or better than the leading deep learning-based algorithm.

bioinformatics↗

bioRxiv2019

Single-Cell Signalling Analysis of Heterocellular Organoids

Organoids are powerful biomimetic tissue models. Despite their widespread adoption, methods to analyse cell-type specific post-translational modification (PTM) signalling networks in organoids are absent. Here we report multivariate single-cell analysis of cell-type specific signalling networks in organoids and organoid co-cultures. Simultaneous measurement of 28 PTMs in >1 million single small intestinal organoid cells by mass cytometry reveals cell-type and cell-state specific signalling networks in stem, Paneth, enteroendocrine, tuft, goblet cells, and enterocytes. Integrating single-cell PTM analysis with Thiol-reactive Organoid Barcoding in situ (TOBis) enables high-throughput comparison of signalling networks between organoid cultures. Multivariate cell-type specific PTM analysis of colorectal cancer tumour microenvironment organoids reveals that shApc, KrasG12D, and Trp53R172H cell-autonomously mimic signalling states normally induced by stromal fibroblasts and macrophages. These results demonstrate how standard mass cytometry workflows can be modified to perform high-throughput multivariate cell-type specific signalling analysis of healthy and cancerous organoids.

cell biology↗