Biology subjects

Costa Cruz, M.

Publications and source records attributed to Costa Cruz, M..

3 recordsLinked to original sources

bioRxiv2026

Fluid shear stress modulates endocytic pathways and junctional targeting of tumor-derived extracellular vesicles in endothelial cells

Breast cancer is the most common malignancy in women, with triple-negative breast cancer (TNBC) representing the most aggressive subtype and carrying a poor metastatic prognosis. Metastasis requires tumor cells to cross the endothelial barrier, a process facilitated by tumor-derived extracellular vesicles (EVs), which can disrupt vascular integrity. Fluid shear stress (FSS), generated by blood flow, shapes endothelial physiology and may influence EV uptake, yet the mechanisms underlying TNBC-derived small EV (sEV) internalization remain unclear. Here, we investigated TNBC sEV-endothelial interactions using combined in silico and in vitro approaches. Human umbilical vein endothelial cells (HUVECs) were cultured under static or FSS conditions (20 dyn/cm{superscript 2}), followed by proteomic profiling and protein-protein interaction analyses with sEV proteomes. Uptake assays employed pharmacological inhibition (Dynasore, M{beta}CD, Pitstop2), Caveolin-1 (CAV-1) and Clathrin Heavy Chain (CLHC), siRNA-mediated knockdown, and junctional interaction analyses via confocal microscopy and co-immunoprecipitation. FSS downregulated proliferation- and angiogenesis-associated proteins while upregulating adhesion and cytoskeletal regulators assessed by proteomics. Network analysis identified clathrin- and caveolin-mediated endocytosis (CME and CavME), integrins, and early endosomes as central mediators of sEV uptake. Functionally, uptake was reduced by Pitstop2, M{beta}CD, and CAV-1/CLHC knockdown under static conditions, but silencing paradoxically enhanced uptake under FSS, suggesting compensatory flow-dependent pathways. Notably, under FSS, sEVs accumulated at endothelial junctions, colocalizing with VE-CAD and associating with CLDN5, indicating a potential disruption mechanism of adherens and tight junctions and consequent endothelial permeability. These findings identify CME and CavME as key uptake routes while underscoring FSS as a critical determinant of endothelial-tumor EV interactions. By revealing junctional targeting of sEVs, this work provides new mechanistic insight into vascular remodeling during metastasis and highlights EV pathways as potential therapeutic targets in TNBC. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/721946v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@f91c5org.highwire.dtl.DTLVardef@2b4dc8org.highwire.dtl.DTLVardef@ff94f1org.highwire.dtl.DTLVardef@18b714b_HPS_FORMAT_FIGEXP M_FIG C_FIG Uptake and localization of sEVs on HUVEC under (a) static and (b) fluid shear-stress conditions. sEVs: Small Extracellular Vesicles. CME: Clathrin-mediated Endocytosis. CavME: Caveolin-mediated Endocytosis. CLDN5: Claudin-5. VE-CAD: Vascular Endothelial Cadherin. FSS: Fluid shear-stress.

cancer biology↗

bioRxiv2024

Cellpose as a reliable method for single-cell segmentation of autofluorescence microscopy images

Autofluorescence microscopy uses intrinsic sources of molecular contrast to provide cellular-level information without extrinsic labels. However, traditional cell segmentation tools are often optimized for high signal-to-noise ratio (SNR) images, such as fluorescently labeled cells, and unsurprisingly perform poorly on low SNR autofluorescence images. Therefore, new cell segmentation tools are needed for autofluorescence microscopy. Cellpose is a deep learning network that is generalizable across diverse cell microscopy images and automatically segments single cells to improve throughput and reduce inter-human biases. This study aims to validate Cellpose for autofluorescence imaging, specifically from multiphoton intensity images of NAD(P)H. Manually segmented nuclear masks of NAD(P)H images were used to train new Cellpose models. These models were applied to PANC-1 cells treated with metabolic inhibitors and patient-derived cancer organoids (across 9 patients) treated with chemotherapies. These datasets include co-registered fluorescence lifetime imaging microscopy (FLIM) of NAD(P)H and FAD, so fluorescence decay parameters and the optical redox ratio (ORR) were compared between masks generated by the new Cellpose model and manual segmentation. The Dice score between repeated manually segmented masks was significantly lower than that of repeated Cellpose masks (p<0.0001) indicating greater reproducibility between Cellpose masks. There was also a high correlation (R2>0.9) between Cellpose and manually segmented masks for the ORR, mean NAD(P)H lifetime, and mean FAD lifetime across 2D and 3D cell culture treatment conditions. Masks generated from Cellpose and manual segmentation also maintain similar means, variances, and effect sizes between treatments for the ORR and FLIM parameters. Overall, Cellpose provides a fast, reliable, reproducible, and accurate method to segment single cells in autofluorescence microscopy images such that functional changes in cells are accurately captured in both 2D and 3D culture.

bioengineering↗

bioRxiv2024

A Postdoctoral Training Program in Bioimage Analysis

We herein describe a postdoctoral training program designed to train biologists with microscopy experience in bioimage analysis. We detail the rationale behind the program, the various components of the training program, and outcomes in terms of works produced and the career effects on past participants. We analyze the results of an anonymous survey distributed to past and present participants, indicating overall high value of all 12 rated aspects of the program, but significant heterogeneity in which aspects were most important to each participant. Finally, we propose this model as a template for other programs which may want to train experts in professional skill sets, and discuss the important considerations when running such a program. We believe that such programs can have extremely positive impact for both the trainees themselves and the broader scientific community.

cell biology↗