Biology subjects

Botrugno, O. A.

Publications and source records attributed to Botrugno, O. A..

3 recordsLinked to original sources

bioRxiv2025

3D printing and bioprinting for miniaturized and scalable hanging-drop organoids culture

Three-dimensional (3D) cell culture systems rely on the manipulation of a biologically derived matrix, typically soluble Basement Membrane Extract (sBME), in which cells or cellular aggregates, such as organoids, are suspended. This matrix provides mechanobiological support, promoting cellular processes. However, the handling of sBME-based matrices containing cellular constructs poses significant challenges due to their rheological properties. We developed an integrated bioprinting system to surpass the conventional pipetting, seeding and culture in multiwell plates. The system combines a fluidic cartridge with innovative 3D-printed biocompatible culture tools designed to host and preserve high-throughput microcultures of Patient-Derived Organoids (PDOs) in sBME. The miniaturized hanging-drop configuration enables extended culture periods and high-throughput imaging screenings. This comprehensive approach overcomes common issues associated with sBME, including sedimentation of cellular aggregates, premature gelation, and structural collapse, which negatively impact culture quality and reproducibility throughout the entire 3D culture workflow, from seeding to culture maintenance, and post-culture analyses. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/678315v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@19f976eorg.highwire.dtl.DTLVardef@8eeefcorg.highwire.dtl.DTLVardef@1ebe6c7org.highwire.dtl.DTLVardef@7c4403_HPS_FORMAT_FIGEXP M_FIG C_FIG Highlights- Miniaturized 3D hanging-drop matrix-embedded organoid culture in a 384-well plate - Custom cartridge enables homogeneous bioprinting of organoids in sBME-based matrix - 3D-printed tools support compact, scalable multiwell culture systems - System suited for miniaturized culture organoids for high-throughput drug screening - Scalable miniaturized culture system for extended periods of time

bioengineering↗

bioRxiv2024

Development of a high-throughput 3D culture microfluidic platform for multi-parameter phenotypic and omics profiling of patient-derived organoids

Patient-derived organoids (PDOs) are poised to become central tools both in clinical practice, to preemptively identify patient optimal treatments, and in drug discovery, overcoming the limitations of cancer cell lines. However, the use of PDOs in these settings has been hampered by several bottlenecks, including sample requirements, assay time, and handling in the context of high-throughput assays. We developed a Microfluidic Platform for Organoids culture (MPO) that miniaturises and simplifies PDOs cultures in a 384-plate format. Both retrospective and prospective clinical studies demonstrate MPO predictive value and the straightforward implementation in the clinical setting. MPO allows subcellular phenotypic screenings, as imaging-based applications like Cell Painting, target engagement analyses, alongside the comprehensive definition of PDOs genomic, transcriptomic, proteomic, lipidomic, and metabolomic landscapes. Harnessing the pleiotropic capabilities of MPO, we uncovered the role of EZH2 inhibitors to prevent the long-term emergence of resistance to RAS inhibitors in metastatic colon cancer. In all, we demonstrate the potential of MPO to impact clinical practice, alongside exploration of the mechanisms underlying compound response and resistance.

cancer biology↗

bioRxiv2023

Scalable Integration of Multiomic Single Cell Data Using Generative Adversarial Networks

Single cell profiling has become a common practice to investigate the complexity of tissues, organs and organisms. Recent technological advances are expanding our capabilities to profile various molecular layers beyond the transcriptome such as, but not limited to, the genome, the epigenome and the proteome. Depending on the experimental procedure, these data can be obtained from separate assays or from the very same cells. Despite development of computational methods for data integration is an active research field, most of the available strategies have been devised for the joint analysis of two modalities and cannot accommodate a high number of them. To solve this problem, we here propose a multiomic data integration framework based on Wasserstein Generative Adversarial Networks (MOWGAN) suitable for the analysis of paired or unpaired data with high number of modalities (>2). At the core of our strategy is a single network trained on all modalities together, limiting the computational burden when many molecular layers are evaluated. Source code of our framework is available at https://github.com/vgiansanti/MOWGAN.

bioinformatics↗