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Ortea, I.

Publications and source records attributed to Ortea, I..

4 recordsLinked to original sources

Accessible and fast single-cell proteomics by DIA integrating Tecan UNO cell dispensing platform, Vanquish Neo LC and Exploris 480 MS

Recent technological advancements in high-sensitivity LC-MS platforms and MS acquisition strategies have addressed key analytical challenges in single-cell proteomics (SCP), paving the way for SCP to become a transformative tool in biology and medicine. Techniques such as MS2 DIA and HRMS1 DIA exploit wide isolation windows and high-resolution MS1 and MS2 spectra to maximize protein identifications, even from low-abundance signals. In parallel, improved data processing algorithms reduce missing values and enhance the reliability of SCP data. These advancements are complemented by automated cell isolation technologies, which ensure precise single-cell handling with minimal sample loss, and in some implementations enable integrated, automated downstream sample preparation steps. Despite this progress, practical, end-to-end best practices for MS-based SCP remain an active area of optimization. Severe sample limitation, adsorption-related losses, the need for robust quantification across hundreds to thousands of single cells, and the lack of comprehensive protocols that systematically integrate and compare critical workflow variables complicate method selection and SCP implementation. In this context, this study builds on recent LC-MS based SCP advancements by presenting a complete, optimized, minimum user operation SCP workflow that integrates the Tecan UNO cell dispensing platform, a Vanquish Neo LC system, and an Orbitrap Exploris 480 mass spectrometer, applied to human primary cells. The workflow is designed to minimize data/cell loss, ensure high reproducibility, and maximize identifications. We evaluate key parameters, including acquisition schemes and LC gradient and column, and distill practical recommendations. The resulting protocol provides a foundation for an easy and accessible routine SCP application in biology and medicine.

molecular biology↗

Comparison of TIMS-PASEF quantitative proteomics data-analysis workflows using FragPipe, DIA-NN, and Spectronaut from a user's perspective

Data-independent acquisition (DIA) methods have gained great popularity in bottom-up quantitative proteomics, as they overcome the irreproducibility and under-sampling limitations of data-dependent acquisition (DDA). diaPASEF, recently developed for the timsTOF Pro mass spectrometers, has brought improvements to DIA, providing additional ion separation (in the ion mobility dimension) and increasing sensitivity. Several studies have benchmarked different workflows for DIA quantitative proteomics, but mostly using instruments from Sciex and Thermo, and therefore, the results are not extrapolable to diaPASEF data. In this work, using a real-life sample set like the one that can be found in any proteomics experiment, we compared the results of analyzing PASEF data with different combinations of library-based and library-free analysis, combining the tools of the FragPipe suite, DIA-NN and including MS1-level LFQ with DDA-PASEF data, and also comparing with the workflows possible in Spectronaut. We verified that library-independent workflows, not so efficient not so long ago, have greatly improved in the recent versions of the software tools, and now perform as well or even better than librarybased ones. We report here information so that the user who is going to conduct a relative quantitative proteomics study using a timsTOF Pro mass spectrometer can make an informed decision on how to acquire (diaPASEF for DIA analysis, or DDA-PASEF for MS1-level LFQ) the samples, and what can be expected depending on the data analysis tool used, among the different alternatives offered by the recently optimized tools for TIMS-PASEF data analysis.

molecular biology↗

Re-analysis of SARS-CoV-2 infected host cell proteomics time-course data by impact pathway analysis and network analysis. A potential link with inflammatory response.

The disease known as coronavirus disease 19 (COVID-19), potentially caused by an outbreak of the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) in Wuhan, China, has hit the world hard, and has led to an unprecedent health and economic crisis. In order to develop treatment options able to stop or ameliorate SARS-CoV-2 effects, we need to understand the biology of the virus inside cells, but this kind of studies are still scarce. A recent study investigated translatome and proteome host cell changes induced in vitro by SARS-CoV-2. In the present study, we use the publicly available proteomics data from this study to re-analyze the mechanisms altered by the virus infection by impact pathways analysis and network analysis. Proteins linked to inflammatory response, but also proteins related to chromosome segregation during mitosis, were found to be regulated. The up-regulation of the inflammatory-related proteins observed could be linked to the propagation of inflammatory reaction and lung injury that is observed in advanced stages of COVID-19 patients.

molecular biology↗

Non-canonical aberrant DNA hypermethylation in glioma

Aberrant DNA hypermethylation is a hallmark of cancer although the underlying molecular mechanisms are still poorly understood. To study the possible role of 5-hydroxymethylcytosine (5hmC) in this process we analyzed the global and locus-specific genome-wide levels of 5hmC in primary samples from 54 gliomas and 72 colorectal cancer patients. Levels of 5hmC in colorectal cancer were very low and no consistent changes were detected between control tissues and tumors. As expected, levels of 5hmC in non-tumoral brain samples were high and significantly reduced at the 49,601 CpG sites in gliomas. Strikingly, hypo-hydroxymethylation at 4,627 (9.3%) of these CpG sites was associated with aberrant DNA hypermethylation. The DNA regions containing these CpG sites were enriched in H3K4me2, and presented a different genuine chromatin signature to that characteristic of the genes classically aberrantly hypermethylated in cancer. We conclude that this data identifies a novel 5hmC-dependent non-canonical class of aberrant DNA hypermethylation in glioma.

cancer biology↗