Label-Free Multi Parameter Optical Interrogation of Endothelial Activation in Single Cells using a Lab on a Disc Platform

Alpha-synuclein dynamics bridge Type-I Interferon response and SARS-CoV-2 replication in peripheral cells

BACKGROUND

Increasing evidence suggests a double-faceted role of alpha-synuclein (α-syn) following infection by a variety of viruses, including SARS-CoV-2. Although α-syn accumulation is known to contribute to cell toxicity and the development and/or exacerbation of neuropathological manifestations, it is also a key to sustaining anti-viral innate immunity. Consistently with α-syn aggregation as a hallmark of Parkinson's disease, most studies investigating the biological function of α-syn focused on neural cells, while reports on the role of α-syn in periphery are limited, especially in SARS-CoV-2 infection.

RESULTS

Results herein obtained by real time qPCR, immunofluorescence and western blot indicate that α-syn upregulation in peripheral cells occurs as a Type-I Interferon (IFN)-related response against SARS-CoV-2 infection. Noteworthy, this effect mostly involves α-syn multimers, and the dynamic α-syn multimer:monomer ratio. Administration of excess α-syn monomers promoted SARS-CoV-2 replication along with downregulation of IFN-Stimulated Genes (ISGs) in epithelial lung cells, which was associated with reduced α-syn multimers and α-syn multimer:monomer ratio. These effects were prevented by combined administration of IFN-β, which hindered virus replication and upregulated ISGs, meanwhile increasing both α-syn multimers and α-syn multimer:monomer ratio in the absence of cell toxicity. Finally, in endothelial cells displaying abortive SARS-CoV-2 replication, α-syn multimers, and multimer:monomer ratio were not reduced following exposure to the virus and exogenous α-syn, suggesting that only productive viral infection impairs α-syn multimerization and multimer:monomer equilibrium.

CONCLUSIONS

Our study provides novel insights into the biology of α-syn, showing that its dynamic conformations are implicated in the innate immune response against SARS-CoV-2 infection in peripheral cells. In particular, our results suggest that promotion of non-toxic α-syn multimers likely occurs as a Type-I IFN-related biological response which partakes in the suppression of viral replication. Further studies are needed to replicate our findings in neuronal cells as well as animal models, and to ascertain the nature of such α-syn conformations.

Enhancing the Yield of a Lab-on-a-Disk-Based Single-Image Parasite Quantification Device

The recently proposed single-image parasite quantification (SIMPAQ) platform based on a Lab-on-a-Disc (LOD) device was previously successfully tested in field conditions, demonstrating its efficiency in soil-transmitted helminth (STH) egg detection and analysis on the level delivered by the current state-of-the-art methods. Furthermore, the SIMPAQ provides relatively quick diagnostics and requires small amounts of sample and materials. On the other hand, in a recent related study, it was revealed that the performance of the SIMPAQ method can be limited due to the action of the tangential Euler and Coriolis forces, and the interaction of the moving eggs with the walls of the LOD chamber. Here, we propose a new improved design that allows us to overcome these limitations and enhance the yield of the SIMPAQ LOD device, as demonstrated in experiments with a synthetic particle model system and real parasite eggs. Despite the simplicity, the proposed design modification is demonstrated to allow a substantial improvement in the yield of the SIMPAQ device, i.e., above 90% of parasite eggs and 98% of synthetic model particles were transported to the field of view. The new design proposed here will be further examined in the new generation of SIMPAQ devices within ongoing research on STH egg detection in field conditions.

Computational approaches in rheumatic diseases - Deciphering complex spatio-temporal cell interactions

Inflammatory arthritis, including rheumatoid (RA), and psoriatic (PsA) arthritis, are clinically and immunologically heterogeneous diseases with no identified cure. Chronic inflammation of the synovial tissue ushers loss of function of the joint that severely impacts the patient's quality of life, eventually leading to disability and life-threatening comorbidities. The pathogenesis of synovial inflammation is the consequence of compounded immune and stromal cell interactions influenced by genetic and environmental factors. Deciphering the complexity of the synovial cellular landscape has accelerated primarily due to the utilisation of bulk and single cell RNA sequencing. Particularly the capacity to generate cell-cell interaction networks could reveal evidence of previously unappreciated processes leading to disease. However, there is currently a lack of universal nomenclature as a result of varied experimental and technological approaches that discombobulates the study of synovial inflammation. While spatial transcriptomic analysis that combines anatomical information with transcriptomic data of synovial tissue biopsies promises to provide more insights into disease pathogenesis, in vitro functional assays with single-cell resolution will be required to validate current bioinformatic applications. In order to provide a comprehensive approach and translate experimental data to clinical practice, a combination of clinical and molecular data with machine learning has the potential to enhance patient stratification and identify individuals at risk of arthritis that would benefit from early therapeutic intervention. This review aims to provide a comprehensive understanding of the effect of computational approaches in deciphering synovial inflammation pathogenesis and discuss the impact that further experimental and novel computational tools may have on therapeutic target identification and drug development.

The peripheral Epac1/p-Cav-1 pathway underlies the disruption of the vascular endothelial barrier following skin/muscle incision and retraction-induced chronic postsurgical pain

Background

Vascular endothelial barrier disruption is pivotal in the development of acute and chronic pain. Here, we demonstrate a previously unidentified molecular mechanism in which activation of the peripheral Epac1/p-Cav-1 pathway accelerated the disruption of the vascular endothelial barrier, thereby promoting chronic postsurgical pain (CPSP).

Methods

We established a rat model of CPSP induced by skin/muscle incision and retraction (SMIR). Pain behaviors were assessed by the mechanical withdrawal threshold (MWT) at different times. Local muscle tissues around the incision were isolated to detect the vascular permeability and the expression of Epac1 and Cav-1. They were assessed by western blot and immunofluorescence staining.

Results

SMIR increased vascular endothelial permeability and the number of macrophages and endothelial cells in the muscle tissues around the incision. The peripheral upregulation of Epac1 was macrophage-derived, whereas that of p-Cav-1 was both macrophage and endothelial cell-derived in the SMIR model. Moreover, the Epac1 agonist 8-pCPT could induce mechanical sensitivity, increase the expression of p-Cav-1, and disrupt vascular endothelial barrier in normal rats. The Epac1 inhibitor CE3F4 attenuated established SMIR-induced mechanical hyperalgesia, the upregulation of p-Cav-1 and vascular endothelial barrier. Finally, we showed that intrathecal injection of Cav-1siRNA relieved SMIR-induced mechanical allodynia, but had no effects of the expression of Epac1.

Conclusions

Collectively, these results revealed a molecular mechanism for modulating CPSP through the peripheral Epac1/Cav-1 pathway. Importantly, targeting Epac1/Cav-1 signaling might be a potential treatment for CPSP.

Label-free morphological sub-population cytometry for sensitive phenotypic screening of heterogenous neural disease model cells

Label-free image analysis has several advantages with respect to the development of drug screening platforms. However, the evaluation of drug-responsive cells based exclusively on morphological information is challenging, especially in cases of morphologically heterogeneous cells or a small subset of drug-responsive cells. We developed a novel label-free cell sub-population analysis method called “in silico FOCUS (in silico analysis of featured-objects concentrated by anomaly discrimination from unit space)” to enable robust phenotypic screening of morphologically heterogeneous spinal and bulbar muscular atrophy (SBMA) model cells. This method with the anomaly discrimination concept can sensitively evaluate drug-responsive cells as morphologically anomalous cells through in silico cytometric analysis. As this algorithm requires only morphological information of control cells for training, no labeling or drug administration experiments are needed. The responses of SBMA model cells to dihydrotestosterone revealed that in silico FOCUS can identify the characteristics of a small sub-population with drug-responsive phenotypes to facilitate robust drug response profiling. The phenotype classification model confirmed with high accuracy the SBMA-rescuing effect of pioglitazone using morphological information alone. In silico FOCUS enables the evaluation of delicate quality transitions in cells that are difficult to profile experimentally, including primary cells or cells with no known markers.

Migration Behavior of Low-Density Particles in Lab-on-a-Disc Devices: Effect of Walls

The effect of the lateral walls of a Lab-On-a-Disc device on the dynamics of a model system of particles with a density lower than that of the solvent (modelling parasites eggs) is analyzed theoretically and experimentally. In the absence of lateral walls, a particle always moves in the direction of the centrifugal force, while its trajectory is deflected in the tangential direction by the inertial Coriolis and Euler forces. Lateral walls, depending on the angle forming with the radial direction, can guide the particle either in the same or in the opposite direction to the centrifugal force, thus resulting in unusual particle trajectories including zig-zag or backwards particle motion. The effect is pronounced in the case of short operation times when the acceleration of the angular rotation, and thus the Euler force, is considerable. The predicted unusual motion is demonstrated by numerically solving the equation of motion in the presence of lateral walls and verified in the experiment with particles of density lower than that of the solvent. Our analysis is useful for design and operational considerations of Lab-On-a-Disc devices aiming for or involving (bio)particle handling.

Cellular lensing and near infrared fluorescent nanosensor arrays to enable chemical efflux cytometry

Nanosensors have proven to be powerful tools to monitor single cells, achieving spatiotemporal precision even at molecular level. However, there has not been way of extending this approach to statistically relevant numbers of living cells. Herein, we design and fabricate nanosensor array in microfluidics that addresses this limitation, creating a Nanosensor Chemical Cytometry (NCC). nIR fluorescent carbon nanotube array is integrated along microfluidic channel through which flowing cells is guided. We can utilize the flowing cell itself as highly informative Gaussian lenses projecting nIR profiles and extract rich information. This unique biophotonic waveguide allows for quantified cross-correlation of biomolecular information with various physical properties and creates label-free chemical cytometer for cellular heterogeneity measurement. As an example, the NCC can profile the immune heterogeneities of human monocyte populations at attomolar sensitivity in completely non-destructive and real-time manner with rate of ~600 cells/hr, highest range demonstrated to date for state-of-the-art chemical cytometry.

Disease-Relevant Single Cell Photonic Signatures Identify S100β Stem Cells and their Myogenic Progeny in Vascular Lesions

A hallmark of subclinical atherosclerosis is the accumulation of vascular smooth muscle cell (SMC)-like cells leading to intimal thickening and lesion formation. While medial SMCs contribute to vascular lesions, the involvement of resident vascular stem cells (vSCs) remains unclear. We evaluated single cell photonics as a discriminator of cell phenotype in vitro before the presence of vSC within vascular lesions was assessed ex vivo using supervised machine learning and further validated using lineage tracing analysis. Using a novel lab-on-a-Disk(Load) platform, label-free single cell photonic emissions from normal and injured vessels ex vivo were interrogated and compared to freshly isolated aortic SMCs, cultured Movas SMCs, macrophages, B-cells, S100β⁺ mVSc, bone marrow derived mesenchymal stem cells (MSC) and their respective myogenic progeny across five broadband light wavelengths (λ465 - λ670 ± 20 nm). We found that profiles were of sufficient coverage, specificity, and quality to clearly distinguish medial SMCs from different vascular beds (carotid vs aorta), discriminate normal carotid medial SMCs from lesional SMC-like cells ex vivo following flow restriction, and identify SMC differentiation of a series of multipotent stem cells following treatment with transforming growth factor beta 1 (TGF- β1), the Notch ligand Jagged1, and Sonic Hedgehog using multivariate analysis, in part, due to photonic emissions from enhanced collagen III and elastin expression. Supervised machine learning supported genetic lineage tracing analysis of S100β⁺ vSCs and identified the presence of S100β⁺vSC-derived myogenic progeny within vascular lesions. We conclude disease-relevant photonic signatures may have predictive value for vascular disease.