Publications

Viability and vitality assays play a crucial role in assessing the effectiveness of novel therapeutic approaches, with stain-based methods providing speed and objectivity. However, their application in yeast research lacks consensus. This study aimed to assess the performance of four common dyes on C. parapsilosis planktonic cells as well as sessile cells that form well-structured biofilms (treated and not treated with amphotericin B). Viability assessment employed Syto-9 (S9), thiazole orange (TO), and propidium iodide (PI). Metabolic activity was determined using fluorescein diacetate (FDA) and FUN-1. Calcofluor white (CW) served as the cell visualization control. Viability/vitality percentage of treated samples were calculated for each dye from confocal images and compared to crystal violet and PrestoBlue results. Heterogeneity in fluorescence intensity and permeability issues were observed with S9, TO, and FDA in planktonic cells and biofilms. This variability, influenced by cell morphology, resulted in dye-dependent viability/vitality percentages. Notably, PI and FUN-1 exhibited robust C. parapsilosis staining, with FUN-1 vitality results comparable to PrestoBlue. Our finding emphasizes the importance of evaluating dye permeability in yeast species beforehand, incorporating cell visualization controls. An improper dye selection may lead to misinterpreting treatment efficacy.

JTD Keywords: Albicans,quantification,biomass,image,aci, Biofilms,microscopy,imaging,amphotericin b,stain-based methods,yeast staining,fluorescence,live and dea

Pathogenic bacteria form biofilms during infection, and polymicrobial biofilms are the most frequent manifestation. Biofilm attachment, maturation, and/or antibiotic sensitivity are mainly evaluated with microtiter plate assays, in which bacteria are stained to enable the quantification of the biomass by optical absorbance or fluorescence emission. However, using these methods to distinguish different species in dual-species or polymicrobial biofilms is currently impossible. Colony-forming unit counts from homogenized dual-species biofilms on selective agar medium allow species differentiation but are time-consuming for a high-throughput screening. Thus, reliable, feasible, and fast methods are urgently needed to study the behavior of polymicrobial and dual-species communities. This study shows that Pseudomonas aeruginosa and Burkholderia cenocepacia strains expressing specific fluorescent or bioluminescent proteins permit the more efficient study of dual-species biofilms compared to other methods that rely on measuring the total biomass. Combining fluorescence and bioluminescence measurements allows an independent analysis of the different microbial species within the biofilm, indicating the degree of presence of each one over time during a dual-species biofilm growth. The quantitative strategies developed in this work are reproducible and recommended for dual-species biofilm studies with high-throughput microtiter plate approaches using strains that can constitutively express fluorescent or bioluminescent proteins.

JTD Keywords: biomass quantification, burkholderia cenocepacia, burkholderia-cepacia, crystal violet, cystic-fibrosis, dual-species biofilms, pseudomonas aeruginosa, quantification, Biomass quantification, Burkholderia cenocepacia, Crystal violet, Dual-species biofilms, Pseudomonas aeruginosa, Pseudomonas-aeruginosa

Introduction: There is evidence that sample treatment of blood-based biosamples may affect integral signals in nuclear magnetic resonance-based metabolomics. The presence of macromolecules in plasma/serum samples makes investigating low-molecular-weight metabolites challenging. It is particularly relevant in the targeted approach, in which absolute concentrations of selected metabolites are often quantified based on the area of integral signals. Since there are a few treatments of plasma/serum samples for quantitative analysis without a universally accepted method, this topic remains of interest for future research. Methods: In this work, targeted metabolomic profiling of 43 metabolites was performed on pooled plasma to compare four methodologies consisting of Carr-Purcell-Meiboom-Gill (CPMG) editing, ultrafiltration, protein precipitation with methanol, and glycerophospholipid solid-phase extraction (g-SPE) for phospholipid removal; prior to NMR metabolomics analysis. The effect of the sample treatments on the metabolite concentrations was evaluated using a permutation test of multiclass and pairwise Fisher scores. Results: Results showed that methanol precipitation and ultrafiltration had a higher number of metabolites with coefficient of variation (CV) values above 20%. G-SPE and CPMG editing demonstrated better precision for most of the metabolites analyzed. However, differential quantification performance between procedures were metabolite-dependent. For example, pairwise comparisons showed that methanol precipitation and CPMG editing were suitable for quantifying citrate, while g-SPE showed better results for 2-hydroxybutyrate and tryptophan. Discussion: There are alterations in the absolute concentration of various metabolites that are dependent on the procedure. Considering these alterations is essential before proceeding with the quantification of treatment-sensitive metabolites in biological samples for improving biomarker discovery and biological interpretations. The study demonstrated that g-SPE and CPMG editing are effective methods for removing proteins and phospholipids from plasma samples for quantitative NMR analysis of metabolites. However, careful consideration should be given to the specific metabolites of interest and their susceptibility to the sample treatment procedures. These findings contribute to the development of optimized sample preparation protocols for metabolomics studies using NMR spectroscopy.Copyright © 2023 Madrid-Gambin, Oller, Marco, Pozo, Andres-Lacueva and Llorach.

JTD Keywords: binding, h-1-nmr spectroscopy, human serum, lactate, metabolites, nuclear magnetic resonance, plasma, protein, quantification, quantitative analysis, sample treatment, Metabolomics, Nuclear magnetic resonance, Nuclear-magnetic-resonance, Plasma, Quantification, Quantitative analysis, Sample treatment

Characterization of the number and distribution of biological molecules on 2D surfaces is of foremost importance in biology and biomedicine. Synthetic surfaces bearing recognition motifs are a cornerstone of biosensors, while receptors on the cell surface are critical/vital targets for the treatment of diseases. However, the techniques used to quantify their abundance are qualitative or semi-quantitative and usually lack sensitivity, accuracy, or precision. Detailed herein a simple and versatile workflow based on super-resolution microscopy (DNA-PAINT) was standardized to improve the quantification of the density and distribution of molecules on synthetic substrates and cell membranes. A detailed analysis of accuracy and precision of receptor quantification is presented, based on simulated and experimental data. We demonstrate enhanced accuracy and sensitivity by filtering out non-specific interactions and artifacts. While optimizing the workflow to provide faithful counting over a broad range of receptor densities. We validated the workflow by specifically quantifying the density of docking strands on a synthetic sensor surface and the densities of PD1 and EGF receptors (EGFR) on two cellular models.

JTD Keywords: binding, biosensors, cancer, expression, kinetics, localization microscopy, quantification, receptors, single-molecule, super-resolution microscopy, Biosensors, Dna-paint, Quantification, Receptors, Single-molecule, Super-resolution microscopy, Superresolution microscopy

Conventionally, odours emitted by different sources present in wastewater treatment plants (WWTPs) are measured by dynamic olfactometry, where a human panel sniffs and analyzes air bags collected from the plant. Although the method is considered the gold standard, the process is costly, slow, and infrequent, which does not allow operators to quickly identify and respond to problems. To better monitor and map WWTP odour emissions, here we propose a small rotary-wing drone equipped with a lightweight (1.3-kg) electronic nose. The "sniffing drone" sucks in air via a ten-meter (33-foot) tube and delivers it to a sensor chamber where it is analyzed in real-time by an array of 21 gas sensors. From the sensor signals, machine learning (ML) algorithms predict the odour concentration that a human panel using the EN13725 methodology would report. To calibrate and validate the predictive models, the drone also carries a remotely controlled sampling device (compliant with EN13725:2022) to collect sample air in bags for post-flight dynamic olfactometry. The feasibility of the proposed system is assessed in a WWTP in Spain through several measurement campaigns covering diverse operating regimes of the plant and meteorological conditions. We demonstrate that training the ML algorithms with dynamic (transient) sensor signals measured in flight conditions leads to better performance than the traditional approach of using steady-state signals measured in the lab via controlled exposures to odour bags. The comparison of the electronic nose predictions with dynamic olfactometry measurements indicates a negligible bias between the two measurement techniques and 95 % limits of agreement within a factor of four. This apparently large disagreement, partly caused by the high uncertainty of olfactometric measurements (typically a factor of two), is more than offset by the immediacy of the predictions and the practical advantages of using a drone-based system.Copyright © 2022. Published by Elsevier B.V.

JTD Keywords: calibration, chemical sensors, drone, dynamic olfactometry, electronic nose, odourquantification, olfaction, volatile organic-compounds, wwtp, Calibration, Chemical sensors, Drone, Dynamic olfactometry, Electronic nose, Environmental monitoring, Odour quantification, Olfaction, Variable selection methods, Wwtp

Identification of asymptomatic patients at higher risk for suffering cardiac events remains controversial and challenging in Brugada syndrome (BS). In this work, we proposed an ECG-based classifier to predict BS-related symptoms, by merging the most predictive electrophysiological features derived from the ventricular depolarization and repolarization periods, along with autonomic-related markers. The initial feature space included local and dynamic ECG markers, assessed during a physical exercise test performed in 110 BS patients (25 symptomatic). Morphological, temporal and spatial properties quantifying the ECG dynamic response to exercise and recovery were considered. Our model was obtained by proposing a two-stage feature selection process that combined a resampled-based regularization approach with a wrapper model assessment for balancing, simplicity and performance. For the classification step, an ensemble was constructed by several logistic regression base classifiers, whose outputs were fused using a performance-based weighted average. The most relevant predictors corresponded to the repolarization interval, followed by two autonomic markers and two other makers of depolarization dynamics. Our classifier allowed for the identification of novel symptom-related markers from autonomic and dynamic ECG responses during exercise testing, suggesting the need for multifactorial risk stratification approaches in order to predict future cardiac events in asymptomatic BS patients.

JTD Keywords: brugada syndrome, depolarization disorders, ensemble classifier, heart-rate recovery, Acute myocardial-ischemia, Autonomics, Brugada syndrome, Brugadum syndrome, Cardiac death, Depolarization, Depolarization disorder, Depolarization disorders, Dynamic ecg, Electrocardiography, Electrophysiology, Ensemble classifier, Ensemble-classifier, Events, Exercise, Forecasting, Heart, Heart-rate, Heart-rate recovery, Prognosis, Qrs, Quantification, Recovery, Repolarization, Sudden cardiac death

Liver fibrosis staging is a key element driving the prognosis of patients with chronic liver disease. Currently, biopsy is the only technique capable of diagnosing liver fibrosis in patients with alcohol-related liver disease (ArLD) and non-alcoholic fatty liver disease (NAFLD) unequivocally. Non-invasive (e.g. plasma-based) biomarker assays are attractive tools to diagnose and stage disease, yet must prove that they are reliable and sensitive to be used clinically. Here we demonstrate 1 H nuclear magnetic resonance as a method to rapidly quantify the endogenous concentration of ammonium ions from human plasma extracts and show their ability to report upon early and advanced stages of ArLD and NAFLD. We show that, irrespective of the disease aetiology, ammonium concentration is a more robust and informative marker of fibrosis stage than current clinically assessed blood hepatic biomarkers. Subject to validation in larger cohorts, the study indicates that the method can provide accurate and rapid staging of ArLD and NAFLD without need for an invasive biopsy.This article is protected by copyright. All rights reserved.

JTD Keywords: ammonium quantification, blood biomarkers, chronic liver disease, disease biomarkers, hepatic dysfunction, nmr, pathogenesis, Ammonium quantification, Hepatic dysfunction, Hepatic-encephalopathy

Nanoparticles represent a promising class of material for nanomedicine and molecular biosensing. The formation of a protein corona due to nonspecific particle-protein interactions is a determining factor for the biological fate of nanoparticles in vivo and strongly impacts the performance of nanoparticles when used as biosensors. Nonspecific interactions are usually highly heterogeneous, yet little is known about the heterogeneity of the protein corona that may lead to inter- and intraparticle differences in composition and protein distribution. Here, we present a super-resolution microscopic approach to study the protein corona on single silica nanoparticles and subsequent cellular interactions using multicolor stimulated emission depletion (STED) microscopy. We demonstrate that STED resolves structural features of protein corona on single particles including the distribution on the particle surface and the degree of protein internalization in porous particles. Using multicolor measurements of multiple labeled protein species, we determine the composition of the protein corona at the single-particle level. We quantify particle-to-particle differences in the composition and find that the composition is considerably influenced by the particle geometry. In a subsequent cellular uptake measurement, we demonstrate multicolor STED of protein corona on single particles internalized by cells. Our study shows that STED microscopy opens the window toward mechanistic understanding of protein coronas and aids in the rational design of nanoparticles as nanomedicines and biosensors.

JTD Keywords: insights, multicolor microscopy, nanoparticles, protein corona, quantification, size, sted microscopy, Fluorescence, Quantification, Sted microscopy

During development, organs reach precise shapes and sizes. Organ morphology is not always obtained through growth; a classic counterexample is the condensation of the nervous system during Drosophila embryogenesis. The mechanics underlying such condensation remain poorly understood. Here, we characterize the condensation of the embryonic ventral nerve cord (VNC) at both subcellular and tissue scales. This analysis reveals that condensation is not a unidirectional continuous process but instead occurs through oscillatory contractions. The VNC mechanical properties spatially and temporally vary, and forces along its longitudinal axis are spatially heterogeneous. We demonstrate that the process of VNC condensation is dependent on the coordinated mechanical activities of neurons and glia. These outcomes are consistent with a viscoelastic model of condensation, which incorporates time delays and effective frictional interactions. In summary, we have defined the progressive mechanics driving VNC condensation, providing insights into how a highly viscous tissue can autonomously change shape and size.

JTD Keywords: actomyosin, central nervous system, drosophila, glia, mechanics, morphogenesis, neuron, ventral nerve cord, Actomyosin, Animals, Central nervous system, Collagen-iv, Contraction, Drosophila, Embryonic development, Forces, Gene, Glia, Glial-cells, Mechanics, Migration, Morphogenesis, Neuroglia, Neuron, Neurons, Quantification, System, Tissue, Ventral nerve cord, Viscolelastic model

Gene editing methods are an attractive therapeutic option for Duchenne muscular dystrophy, and they have an immediate application in the generation of research models. To generate myoblast cultures that could be useful in in vitro drug screening, we have optimised a CRISPR/Cas9 gene edition protocol. We have successfully used it in wild type immortalised myoblasts to delete exon 52 of the dystrophin gene, modelling a common Duchenne muscular dystrophy mutation; and in patient’s immortalised cultures we have deleted an inhibitory microRNA target region of the utrophin UTR, leading to utrophin upregulation. We have characterised these cultures by demonstrating, respectively, inhibition of dystrophin expression and overexpression of utrophin, and evaluating the expression of myogenic factors (Myf5 and MyH3) and components of the dystrophin associated glycoprotein complex (α-sarcoglycan and β-dystroglycan). To demonstrate their use in the assessment of DMD treatments, we have performed exon skipping on the DMDΔ52-Model and have used the unedited DMD cultures/ DMD-UTRN-Model combo to assess utrophin overexpression after drug treatment. While the practical use of DMDΔ52-Model is limited to the validation to our gene editing protocol, DMD-UTRN-Model presents a possible therapeutic gene edition target as well as a useful positive control in the screening of utrophin overexpression drugs.

JTD Keywords: expression, in-vitro, mouse model, muscle, mutations, phenotype, quantification, sarcolemma, therapy, 3' untranslated regions, Cells, cultured, Crispr-cas systems, Cytoskeletal proteins, Drug discovery, Dystroglycans, Dystrophin, Gene editing, Hek293 cells, Humans, Muscular dystrophy, duchenne, Myoblasts, Myogenic regulatory factor 5, Primary cell culture, Sarcoglycans, Utrophin, Utrophin up-regulation

The functionalization of nanoparticles with functional moieties is a key strategy to achieve cell targeting in nanomedicine. The interplay between size and ligand number is crucial for the formulation performance and needs to be properly characterized to understand nanoparticle structure-activity relations. However, there is a lack of methods able to measure both size and ligand number at the same time and at the single particle level. Here, we address this issue by introducing a correlative light and electron microscopy (CLEM) method combining super-resolution microscopy (SRM) and transmission electron microscopy (TEM) imaging. We apply our super-resCLEM method to characterize the relationship between size and ligand number and density in PLGA-PEG nanoparticles. We highlight how heterogeneity found in size can impact ligand distribution and how a significant part of the nanoparticle population goes completely undetected in the single-technique analysis. Super-resCLEM holds great promise for the multiparametric analysis of other parameters and nanomaterials.

JTD Keywords: cellular uptake, correlative light and electron microscopy (clem), density, electron microscopy (em), functionalization, heterogeneity, nanomedicine, nanoparticles, pegylation, plga, progress, quantification, size, Correlative light and electron microscopy (clem), Electron microscopy (em), Heterogeneity, Nanomedicine, Nanoparticles, Physicochemical characterization, Super-resolution microscopy (srm)

Cell membrane proteins are involved in a variety of biochemical pathways and therefore constitute important targets for therapy and development of new drugs. Bioanalytical platforms and binding assays using these membrane protein receptors for drug screening or diagnostic require the construction of well-characterized liposome and lipid bilayer arrays that act as support to prevent protein denaturation during biochip processing. Quantification of the protein receptors in the lipid membrane arrays is a key issue in order to produce reproducible and well-characterized chips. Herein, we report a novel immunochemical analytical approach for the quantification of membrane proteins (i.e., G-protein-coupled receptor, GPCR) in nanovesicles (NVs). The procedure allows direct determination of tagged receptors (i.e., c-myc tag) without any previous protein purification or extraction steps. The immunochemical method is based on a microplate ELISA format and quantifies this tag on proteins embedded in NVs with detectability in the picomolar range, using protein bioconjugates as reference standards. The applicability of the method is demonstrated through the quantification of the c-myc-olfactory receptor (OR, c-myc-OR1740) in the cell membrane NVs. The reported method opens the possibility to develop well-characterized drug-screening platforms based on G-coupled proteins embedded on membranes.

JTD Keywords: Bioelectronic nose, Competitive ELISA, G-protein-coupled receptors quantification, Natural vesicles, Olfactory receptors, Transmembrane proteins

Abstract Definitions of the limit of detection (LOD) based on the probability of false positive and/or false negative errors have been proposed over the past years. Although such definitions are straightforward and valid for any kind of analytical system, proposed methodologies to estimate the LOD are usually simplified to signals with Gaussian noise. Additionally, there is a general misconception that two systems with the same LOD provide the same amount of information on the source regardless of the prior probability of presenting a blank/analyte sample. Based upon an analogy between an analytical system and a binary communication channel, in this paper we show that the amount of information that can be extracted from an analytical system depends on the probability of presenting the two different possible states. We propose a new definition of LOD utilizing information theory tools that deals with noise of any kind and allows the introduction of prior knowledge easily. Unlike most traditional LOD estimation approaches, the proposed definition is based on the amount of information that the chemical instrumentation system provides on the chemical information source. Our findings indicate that the benchmark of analytical systems based on the ability to provide information about the presence/absence of the analyte (our proposed approach) is a more general and proper framework, while converging to the usual values when dealing with Gaussian noise.

JTD Keywords: Limit of detection, Information theory, Mutual information, Heteroscedasticity, False positive/negative errors, Gas discrimination and quantification

A numerical analysis of the polarization force between a sharp conducting probe and a dielectric film of finite lateral dimensions on a metallic substrate is presented with the double objective of (i) determining the conditions under which the film can be approximated by a laterally infinite film and (ii) proposing an analytical model valid in this limit. We show that, for a given dielectric film, the critical diameter above which the film can be modeled as laterally infinite depends not only on the probe geometry, as expected, but mainly on the film thickness. In particular, for films with intermediate to large thicknesses (>100 nm), the critical diameter is nearly independent from the probe geometry and essentially depends on the film thickness and dielectric constant following a relatively simple phenomenological expression. For films that can be considered as laterally infinite, we propose a generalized analytical model valid in the thin-ultrathin limit (<20-50 nm) that reproduces the numerical calculations and the experimental data. Present results provide a general framework under which accurate quantification of electrostatic force microscopy measurements on dielectric films on metallic substrates can be achieved.

JTD Keywords: Dielectric constant, Dielectric films, Electrostatic force microscopy, Quantification, Analytical models, Electric force microscopy, Electrostatic force, Film thickness, Permittivity, Probes, Substrates, Ultrathin films, Accurate quantifications, Electrostatic force microscopy, Finite size effect, Lateral dimension, Metallic substrate, Numerical calculation, Polarization forces, Quantification, Dielectric films

Bistable molecules that behave as switches in solution have long been known. Systems that can be reversibly converted between two stable states that differ in their physical properties are particularly attractive in the development of memory devices when immobilized in substrates. Here, we report a highly robust surface-confined switch based on an electroactive, persistent organic radical immobilized on indium tin oxide substrates that can be electrochemically and reversibly converted to the anion form. This molecular bistable system behaves as an extremely robust redox switch in which an electrical input is transduced into optical as well as magnetic outputs under ambient conditions. The fact that this molecular surface switch, operating at very low voltages, can be patterned and addressed locally, and also has exceptionally high long-term stability and excellent reversibility and reproducibility, makes it a very promising platform for non-volatile memory devices.

JTD Keywords: Self-assembled monolayers, Chromophore-based monolayers, Ultrathin platinum films, Carbon free-radicals, Per-million levels, Polychlorotriphenylmethyl radicals, Electron-transfer, Surface, Logic, Quantification

Cellular microarray developments and its applications are the next step after DNA and protein microarrays. The choice of the surface chemistry of the substrates used for the implementation of this technique, that must favor proper protein immobilization while avoiding cell adhesion on the nonspotted areas, presents a complex challenge. This is a key issue since usually the best nonfouling surfaces are also the ones that retain immobilized the smallest amounts of printed protein. To quantitatively assess the amount of protein immobilization, in this study several combinations of fluorescently labeled fibronectin (Fn*) and streptavidin (SA*) were microspotted, with and without glycerol addition in the printing buffer, on several substrates suitable for cellular microarrays. The substrates assayed included chemically activated surfaces as well as Poly ethylene oxide (PEO) films that are nonfouling in solution but accept adhesion of proteins in dry conditions. The results showed that the spotted Fn* was retained by all the surfaces, although the PEO surface did show smaller amounts of immobilization. The SA*, on the other hand, was only retained by the chemically activated surfaces. The inclusion of glycerol in the printing buffer significantly reduced the immobilization of both proteins. The results presented in this article provide quantitative evidence of the convenience of using a chemically activated surface to immobilize proteins relevant for cellular microarray applications, particularly when ECM proteins are cospotted with smaller factors which are more difficult to be retained by the surfaces.

JTD Keywords: Protein immobilization, Quantification, Microarray, Substrate, Surface chemistry

Purpose: 123I-labelled radioligands are commonly used for single-photon emission computed tomography (SPECT) imaging of the dopaminergic system to study the dopamine transporter binding. The aim of this work was to compare the quantitative capabilities of two different SPECT systems through Monte Carlo (MC) simulation. Methods: The SimSET MC code was employed to generate simulated projections of a numerical phantom for two gamma cameras equipped with a parallel and a fan-beam collimator, respectively. A fully 3D iterative reconstruction algorithm was used to compensate for attenuation, the spatially variant point spread function (PSF) and scatter. A post-reconstruction partial volume effect (PVE) compensation was also developed. Results: For both systems, the correction for all degradations and PVE compensation resulted in recovery factors of the theoretical specific uptake ratio (SUR) close to 100%. For a SUR value of 4, the recovered SUR for the parallel imaging system was 33% for a reconstruction without corrections (OSEM), 45% for a reconstruction with attenuation correction (OSEM-A), 56% for a 3D reconstruction with attenuation and PSF corrections (OSEM-AP), 68% for OSEM-AP with scatter correction (OSEM-APS) and 97% for OSEM-APS plus PVE compensation (OSEM-APSV). For the fan-beam imaging system, the recovered SUR was 41% without corrections, 55% for OSEM-A, 65% for OSEM-AP, 75% for OSEM-APS and 102% for OSEM-APSV. Conclusion: Our findings indicate that the correction for degradations increases the quantification accuracy, with PVE compensation playing a major role in the SUR quantification. The proposed methodology allows us to reach similar SUR values for different SPECT systems, thereby allowing a reliable standardisation in multicentric studies.

JTD Keywords: Brain SPECT, Monte Carlo methods, Receptor imaging, Reconstruction quantification, SPECT instrumentation and algorithms