Biology subjects

Telles, G. P.

Publications and source records attributed to Telles, G. P..

3 recordsLinked to original sources

bioRxiv2025

Single-cell proteomics workflow for characterizing heterogeneous cell populations in saliva and tear fluid

Single-cell proteomics (SCP) has advanced considerably but still is largely limited to homogeneous populations and distant from clinical applicability. We present an SCP workflow for assessing the cellular heterogeneity in saliva and tear fluid. Initially, benchmarks were established using a standard HeLa digestion curve, resulting in more than 5,463 protein groups (PGs) at 50 pg. For single HeLa cells, the workflow was improved to minimize contamination and increase quantitative performance, reaching a maximum of 3,785 PGs per single cell. Following, SCP was benchmarked across heterogenous populations of saliva and tear fluid, collected from 10 healthy individuals. By improving cell isolation, contamination control, and DIA-based search and quantitation, single cells from saliva (n=110) and tear fluid (n=149), with average diameters of 8 and 11 {micro}m, respectively, yielded a maximum of 700 PGs per single cell. Downstream analysis indicated overrepresented protein functions, distinct cluster markers and twenty-three validated therapeutic targets identified from single-cell data. Taken together, this study demonstrates the robustness of our SCP workflow applied to biofluids, driving the discovery of biomarkers and therapeutic targets in complex microenvironments.

molecular biology↗

bioRxiv2023

Saliva proteome-wide structural changes are associated with oral cancer aggressiveness

Diverse proteomics-based strategies have been applied to saliva to quantitatively identify diagnostic and prognostic targets for oral cancer. Considering that these potential diagnostic and prognostic factors may be regulated by events that do not imply variation in protein abundance levels, we investigated the hypothesis that changes in protein conformation can be associated with diagnosis and prognosis, revealing biological processes and novel targets of clinical relevance. For this, we employed limited proteolysis-mass spectrometry in saliva samples to explore structural alterations, comparing the proteome of healthy control and oral squamous cell carcinoma (OSCC) patients, with and without lymph node metastasis. Fifty-one proteins with potential structural rearrangements were associated with clinical patient features. Post-translational modifications, such as glycosylation, disulfide bond, and phosphorylation, were also investigated in our data using different search engines and in silico analysis indicating that they might contribute to structural rearrangements of the potential diagnostic and prognostic markers here identified. Altogether, this powerful approach allows for a deep investigation of complex biofluids, such as saliva, advancing the search for targets for oral cancer diagnosis and prognosis. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=187 SRC="FIGDIR/small/552034v1_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@1d0f97dorg.highwire.dtl.DTLVardef@ab9a2borg.highwire.dtl.DTLVardef@16baf1org.highwire.dtl.DTLVardef@4b4a37_HPS_FORMAT_FIGEXP M_FIG Oral cancer progression is associated with potential structural rearrangements. C_FIG

cancer biology↗

bioRxiv2017

CellNetVis: a web tool for visualization of biological networks using force-directed layout constrained by cellular components

BackgroundThe advent of \"omics\" science has brought new perspectives in contemporary biology through the high-throughput analyses of molecular interactions, providing new clues in protein/gene function and in the organization of biological pathways. Biomolecular interaction networks, or graphs, are simple abstract representations where the components of a cell (e.g. proteins, metabolites etc.) are represented by nodes and their interactions are represented by edges. An appropriate visualization of data is crucial for understanding such networks, since pathways are related to functions that occur in specific regions of the cell. The force-directed layout is an important and widely used technique to draw networks according to their topologies. Placing the networks into cellular compartments helps to quickly identify where network elements are located and, more specifically, concentrated. Currently, only a few tools provide the capability of visually organizing networks by cellular compartments. Most of them cannot handle large and dense networks. Even for small networks with hundreds of nodes the available tools are not able to reposition the network while the user is interacting, limiting the visual exploration capability.\n\nResultsHere we propose CellNetVis, a web tool to easily display biological networks in a cell diagram employing a constrained force-directed layout algorithm. The tool is freely available and open-source. It was originally designed for networks generated by the Integrated Interactome System and can be used with networks from others databases, like InnateDB.\n\nConclusionsCellNetVis has demonstrated to be applicable for dynamic investigation of complex networks over a consistent representation of a cell on the Web, with capabilities not matched elsewhere.

systems biology↗