Biology subjects

Bianchi, G.

Publications and source records attributed to Bianchi, G..

8 recordsLinked to original sources

bioRxiv2026

Extracellular Matrix Stiffness Controls Actin Cytoskeletal Tension

Mechanical properties of the extracellular matrix (ECM) regulate cell behavior and strongly impact the cytoskeleton, yet direct measurements of actin tension across different ECM stiffnesses are lacking. Using a genetically encoded FRET-based actin tension sensor, we show that cells cultured on stiffer substrates exhibit increased spreading, reduced multicellular aggregation, and higher molecular tension within filamentous actin. Complementary measurements using an -actinin tension sensor support increased cytoskeletal mechanical loading. These results provide direct evidence that ECM stiffness modulates intracellular actin tension during mechanotransduction.

biophysics↗

bioRxiv2026

Generative AI designs functional thiolation domains for reprogramming non-ribosomal peptide synthetases

Large language models and generative protein design promise to accelerate biotechnology, but it remains unclear whether they can engineer dynamic megasynth(et)ases whose activity depends on transient, context-specific domain interfaces. Non-ribosomal peptide synthetases (NRPSs) are an especially demanding target, yet a high-value one because they produce many clinically important natural products and offer a route to analogs that are often difficult or impractical to access by chemical synthesis. Here we integrate pretrained generative models (ESM3, ProteinMPNN and EvoDiff) with design-build-test-learn cycles and data-guided prioritization to generate 76 de novo thiolation (T) domains. We built and tested 578 recombinant NRPS variants in vivo spanning minimal, full-length and hybrid assembly lines. AI-designed T-domains supported product formation across architectures, enabled catalytically active hybrids at recombined junctions and increased yields by up to [~]3-fold relative to NRPSs carrying the native T-domain. A representative design showed improved soluble expression, refolding, and a 12 {degrees}C higher melting temperature, while molecular dynamics simulations indicated preserved global stability but reshaped, state-dependent interdomain contact networks. Together, these results establish generative design as an effective route to context-conditioned optimization and reprogramming of biosynthetic assembly lines.

synthetic biology↗

bioRxiv2022

Characterizing dry mass and volume changes in human multiple myeloma cells upon treatment with proteotoxic and genotoxic drugs

Multiple myeloma (MM) is a cancer of terminally differentiated plasma cells. MM remains incurable, but overall survival of patients has progressively increased over the past two decades largely due to novel agents such as proteasome inhibitors (PI) and the immunomodulatory agents. While these therapies are highly effective, MM patients can be de novo resistant and acquired resistance with prolonged treatment is inevitable. There is growing interest in early, accurate identification of responsive versus non-responsive patients, however limited sample availability and need for rapid assays are limiting factors. Here, we test dry mass and volume as label-free biomarkers to monitor early response of MM cells to treatment with bortezomib, doxorubicin, and ultraviolet light. For the dry mass measurement, we use two types of phase-sensitive optical microscopy techniques: digital holographic tomography and computationally-enhanced quantitative phase microscopy. We show that human MM cell lines (RPMI8226, MM.1S, KMS20, and AMO1) increase dry mass upon bortezomib treatment. This dry mass increase after bortezomib treatment occurs as early as 1 hour for sensitive cells and 4 hours for all tested cells. We further confirm this observation using primary multiple myeloma cells derived from patients and show that a correlation exists between increase in dry mass and sensitivity to bortezomib, supporting the use of dry mass as a biomarker. The volume measurement using Coulter counter shows a more complex behavior; RPMI8226 cells increase the volume at an early stage of apoptosis, but MM.1S cells show the volume decrease typically observed with apoptotic cells. Altogether, this cell study presents complex kinetics of dry mass and volume at an early stage of apoptosis, which may serve as a basis for the detection and treatment of MM cells.

systems biology↗

bioRxiv2021

Long Noncoding RNA RROL Provides Chromatin Scaffold for MYC-WDR82 Interaction to Impact Lipid Metabolism and Tumor Cell Growth in Multiple Myeloma

Long noncoding RNAs (lncRNA) can drive the tumorigenesis and be susceptible to therapeutic intervention. To define the landscape of therapeutically actionable lncRNA dependencies in multiple myeloma (MM), we coupled our extensive lncRNA transcriptomic profile with lncRNA targeted CRISPR interference viability screen and identified RNA Regulator of Lipogenesis (RROL) as a leading lncRNA dependency in MM. RROL shares its origin with the microRNA locus MIR17HG, however supports the proliferation and survival of MM cells in a microRNA- and DROSHA- independent manner. We found that RROL provides a chromatin scaffold for the functional interaction between c-MYC and WDR82 to promote the regulation of the lipogenic pathways via the transcriptional control of the rate-limiting enzyme ACC1 in MM cells. Inhibition of RROL with clinically applicable antisense molecules disrupts its transcriptional and functional activities causing potent anti-tumor effects both in vitro and in vivo in two pre-clinical animal models. This study establishes lncRNA RROL as a therapeutically actionable dependency with a unique mechanism of action in support of myeloma cell growth.

cancer biology↗

bioRxiv2021

Istaroxime metabolite PST3093 selectively stimulates SERCA2a and reverses disease-induced changes in cardiac function

BackgroundHeart failure (HF) therapeutic toolkit would strongly benefit from the availability of ino-lusitropic agents with a favorable pharmacodynamics and safety profile. Istaroxime is a promising agent, which combines Na+/K+ pump inhibition with SERCA2a stimulation; however, it has a very short half-life and extensive metabolism to a molecule, named PST3093. The present work aims to investigate whether PST3093, still retains the pharmacodynamic and pharmacokinetic properties of its parent compound. MethodsWe studied PST3093 for its effects on SERCA2a and Na+/K+ ATPase activities, Ca2+ dynamics in isolated myocytes and hemodynamic effects in an in-vivo rat model of diabetic (streptozotocin (STZ)-induced) cardiomyopathy. ResultsIstaroxime infusion in HF patients led to accumulation of PST3093 in the plasma; clearance was substantially slower for PST3093 than for istaroxime. In cardiac rat preparations PST3093 did not inhibit the Na+/K+ ATPase activity, but retained SERCA2a stimulatory activity. In in-vivo echocardiographic assessment, PST3093 improved overall cardiac performance and reversed most STZ-induced abnormalities. PST3093 i.v. toxicity was considerably lower than that of istaroxime and it failed to significantly interact with 50 off-targets. ConclusionsOverall, PST3093 is a "selective" SERCA2a activator, the prototype of a novel pharmacodynamic category with a potential in the ino-lusitropic approach to HF with prevailing diastolic dysfunction. Its pharmacodynamics are peculiar and its pharmacokinetics are suitable to prolong the cardiac beneficial effect of istaroxime infusion. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=137 SRC="FIGDIR/small/455204v3_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@bc9220org.highwire.dtl.DTLVardef@1d7a6eorg.highwire.dtl.DTLVardef@1510c71org.highwire.dtl.DTLVardef@7f037_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2020

A myosin II-based nanomachine devised for the study of Ca2+-dependent mechanisms of muscle regulation

The emergent properties of the array arrangement of the molecular motor myosin II in the sarcomere of the striated muscle, generation of steady force and shortening, can be studied in vitro with a synthetic nanomachine, made by an ensemble of eight HMM myosin fragments from rabbit psoas muscle carried on a piezoelectric nanopositioner and brought to interact with a properly oriented actin filament attached via gelsolin (a Ca2+-regulated actin binding protein) to a bead trapped by a Dual Laser Optical Tweezers. The application of the original version of the nanomachine to investigation of the Ca2+-dependent regulation mechanisms of the other sarcomeric (regulatory or cytoskeleton) proteins, adding them on at a time, was anyway prevented by the impossibility to preserve Ca2+ as a free parameter. Here the nanomachine is implemented by assembling the bead-attached actin filament with the Ca2+-insensitive gelsolin fragment TL40. The performance of the nanomachine is determined either in the absence or in the presence of 0.1 mM Ca2+ (the concentration required for BTA preparation with gelsolin). The nanomachine exhibits a maximum power output of 5.4 aW, independently of [Ca2+], opening the possibility for future studies of the Ca2+-dependent function/dysfunction of regulatory and cytoskeletal proteins.

biophysics↗

bioRxiv2020

A numerical study about the flight of the dragonfly: 2D gliding and 3D hovering regimes

The dragonflys ability of gliding and performing dexterous maneuvers during flight attracts the interest of scientists and engineers who aim at replicating its performances in micro air vehicles. The great efficiency of its flight is achieved thanks to the vortices generated by wing movements and thanks to the corrugations on their surfaces. The high freedom of control of each wing has been proved to be the secret behind the dragonfly capability to carry out incredible flight manoeuvers. The study presented in this paper analyzes two of the most common flight regimes of the dragonfly. Firstly, some CFD simulations of gliding are performed and drag and lift coefficients have been calculated, showing a good match with experimental data found in literature. Then, hovering has been studied using a methodology inspired to the Blade Element Momentum (BEM) theory, which is usually applied in the context of wind turbines design. The lift force calculated with this simulation corresponds to the weight of dragonfly, suggesting the correctness of this analysis.

bioengineering↗

bioRxiv2019

Intercostal Space Prediction Using Deep Learning In Fully Endoscopic Mitral Valve Surgery

ObjectiveAbout 10 million people in Europe suffer from mitral valve incompetence. Majority of these entity is mitral valve prolapse in developed countries. Endoscopic mitral valve surgery is a relatively new procedure and preparation in the right intercostal space are crucial for success completion of the procedure. We aimed to explore clinical variables and chest X-rays in order to build most performant model that can predict the right intercostal space for thoracotomy.\n\nMethodsOverall 234 patients underwent fully endoscopic mitral valve surgery. All patients had preoperative two projection radiography. Intercostal space for right thoracotomy was decided by expert cardiac surgeons taking in consideration the height, weight, chest radiography, anatomical position of skin incision, nipple position and the sex. In order to predict the right intercostal space we have used clinical data and we have collected all radiographies and feed it to deep neural network algorithm. We have spitted the whole data-set into two subsets: training and testing data-sets. We have used clinical data and build an algorithm (Random Forest) in order to have reference model.\n\nResultsThe best-performing classifier was GoogLeNet neural network (now on we will reffera as Deep Learning) and had an AUC of 0.956. Algorithm based on clinical data (Random Forest) had AUC of 0.529 using only chest x-rays. The deep leaning algorithm predicted correctly in all cases the correct intercostal space on the training datasest except two ladies (96.08% ; with sensitivity of 97.06% and specificity 94.12 %, where the Random Forest was capable to predict right intercostal space in 60.78% cases with sensitivity of 93.33% and specificity 14.29 % (only clinical data).\n\nConclusionArtificial intelligence can be helpful to program the minimally invasive cardiac operation, for right intercostal space selection for thoracotomy, especially in non optimal thoraxes (example, obese short ladies). It learned from the standard imaging (thorax x-ray) which is easy, do routinely to every patient.

bioinformatics↗