Single Molecule In Vivo Analysis of Toll-Like Receptor 9 and CpG DNA Interaction

Toll-like receptor 9 (TLR9) activates the innate immune system in response to oligonucleotides rich in CpG whereas DNA lacking CpG could inhibit its activation. However, the mechanism of how TLR9 interacts with nucleic acid and becomes activated in live cells is not well understood. Here, we report on the successful implementation of single molecule tools, constituting fluorescence correlation/cross-correlation spectroscopy (FCS and FCCS) and photon count histogram (PCH) with fluorescence lifetime imaging (FLIM) to study the interaction of TLR9-GFP with Cy5 labeled oligonucleotide containing CpG or lacking CpG in live HEK 293 cells. Our findings show that i) TLR9 predominantly forms homodimers (80%) before binding to a ligand and further addition of CpG or non CpG DNA does not necessarily increase the proportion of TLR9 dimers, ii) CpG DNA has a lower dissociation constant (62 nM±9 nM) compared to non CpG DNA (153 nM±26 nM) upon binding to TLR9, suggesting that a motif specific binding affinity of TLR9 could be an important factor in instituting a conformational change-dependant activation, and iii) both CpG and non CpG DNA binds to TLR9 with a 1∶2 stoichiometry in vivo. Collectively, through our findings we establish an in vivo model of TLR9 binding and activation by CpG DNA using single molecule fluorescence techniques for single cell studies

Evaluation of a Multiparametric Immunofluorescence Assay for Standardization of Neuromyelitis Optica Serology

Background: Neuromyelitis optica (NMO) is a severely disabling autoimmune disorder of the central nervous system, which predominantly affects the optic nerves and spinal cord. In a majority of cases, NMO is associated with antibodies to aquaporin-4 (AQP4) (termed NMO-IgG). Aims: In this study, we evaluated a new multiparametric indirect immunofluorescence (IIF) assay for NMO serology. Methods: Sera from 20 patients with NMO, 41 patients with multiple sclerosis (MS), 30 healthy subjects, and a commercial anti-AQP4 IgG antibody were tested in a commercial composite immunofluorescence assay ("Neurology Mosaic 17"; Euroimmun, Germany), consisting of five different diagnostic substrates (HEK cells transfected with AQP4, non-transfected HEK cells, primate cerebellum, cerebrum, and optic nerve tissue sections). Results: We identified AQP4 specific and non-specific fluorescence staining patterns and established positivity criteria. Based on these criteria, this kit yielded a high sensitivity (95%) and specificity (100%) for NMO and had a significant positive and negative likelihood ratio (LR+ = ∞, LR- = 0.05). Moreover, a 100% inter- and intra-laboratory reproducibility was found. Conclusions: The biochip mosaic assay tested in this study is a powerful tool for NMO serology, fast to perform, highly sensitive and specific for NMO, reproducible, and suitable for inter-laboratory standardization as required for multi-centre clinical trials

Mediated Plastid RNA Editing in Plant Immunity

[EN] Plant regulatory circuits coordinating nuclear and plastid gene expression have evolved in response to external stimuli. RNA editing is one of such control mechanisms. We determined the Arabidopsis nuclear-encoded homeodomain-containing protein OCP3 is incorporated into the chloroplast, and contributes to control over the extent of ndhB transcript editing. ndhB encodes the B subunit of the chloroplast NADH dehydrogenase-like complex (NDH) involved in cyclic electron flow (CEF) around photosystem I. In ocp3 mutant strains, ndhB editing efficiency decays, CEF is impaired and disease resistance to fungal pathogens substantially enhanced, a process recapitulated in plants defective in editing plastid RNAs encoding NDH complex subunits due to mutations in previously described nuclear-encoded pentatricopeptide-related proteins (i.e. CRR21, CRR2). Furthermore, we observed that following a pathogenic challenge, wild type plants respond with editing inhibition of ndhB transcript. In parallel, rapid destabilization of the plastidial NDH complex is also observed in the plant following perception of a pathogenic cue. Therefore, NDH complex activity and plant immunity appear as interlinked processes.This work was supported by the Spanish MICINN (CONSOLIDER and BFU2012 to PV), and Generalitat Valenciana (Prometeo2010/020 to PV). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.García-Andrade Serrano, J.; Ramirez Garcia, V.; López Sánchez, A.; Vera Vera, P. (2013). Mediated Plastid RNA Editing in Plant Immunity. PLoS Pathogens. 9(10):1003713-1003713. https://doi.org/10.1371/ journal.ppat.1003713S1003713100371391

Fungal G-protein-coupled receptors::mediators of pathogenesis and targets for disease control

G-protein signalling pathways are involved in sensing the environment, enabling fungi to coordinate cell function, metabolism and development with their surroundings, thereby promoting their survival, propagation and virulence. G-protein-coupled receptors (GPCRs) are the largest class of cell surface receptors in fungi. Despite the apparent importance of GPCR signalling to fungal biology and virulence, relatively few GPCR–G-protein interactions, and even fewer receptor-binding ligands, have been identified. Approximately 40% of current pharmaceuticals target human GPCRs, due to their cell surface location and central role in cell signalling. Fungal GPCRs do not belong to any of the mammalian receptor classes, making them druggable targets for antifungal development. This Review Article evaluates developments in our understanding of fungal GPCR-mediated signalling, while substantiating the rationale for considering these receptors as potential antifungal targets. The need for insights into the structure–function relationship of receptor–ligand interactions is highlighted, which could facilitate the development of receptor-interfering compounds that could be used in disease control

Kinetic and kinematic analysis of ACL reconstruction in association with lateral-extrarticular tenodesis of the knee in revision surgery: A pilot study

Background. Anterior cruciate ligament reconstructions are a very frequent surgery. The key role of the anterolateral ligament in the knee rotational stability has been undelighted in recent years. Extra-articular tenodesis in association with ACL reconstructions, serves to eliminate anterolateral rotatory instability. The aim of our study is to compare treated knees with the contralateral uninjured knee in those cases whom been treated with ACL arthroscopic reconstruction and lateral extra-articular tenodesis in revision surgery, and evaluate clinical results with kinematic and kinetic examinations methods. Materials and methods. Sixteen patients (10 males and 6 females) with ages from 21 to 37 had been treated at the Orthopaedic Clinic of Udine for failure of previous ACL reconstruction. In all patients was performed ACL arthroscopic reconstruction with the association of a lateral extra-articular tenodesis (Coker-Arnold). We have decided to asses the patients at one year after surgery with GNRB arthrometer and Bioval inertial sensor system. Results. All patients treated with arthroscopic ACL reconstruction and lateral extra-articular tenodesis have regained pre-injury sagittal knee stability and gait dynamics. Conclusions. Clinical and instrumental evaluation showed how a combination of procedures can restore the kinematic and stability of a joint, even if the procedures performed are not anatomical. These are only preliminary data. (www.actabiomedica.it)

Performance of deep learning restoration methods for the extraction of particle dynamics in noisy microscopy image sequences

Particle tracking in living systems requires low light exposure and short exposure times to avoid phototoxicity and photobleaching and to fully capture particle motion with high-speed imaging. Low-excitation light comes at the expense of tracking accuracy. Image restoration methods based on deep learning dramatically improve the signal-to-noise ratio in low-exposure data sets, qualitatively improving the images. However, it is not clear whether images generated by these methods yield accurate quantitative measurements such as diffusion parameters in (single) particle tracking experiments. Here, we evaluate the performance of two popular deep learning denoising software packages for particle tracking, using synthetic data sets and movies of diffusing chromatin as biological examples. With synthetic data, both supervised and unsupervised deep learning restored particle motions with high accuracy in two-dimensional data sets, whereas artifacts were introduced by the denoisers in three-dimensional data sets. Experimentally, we found that, while both supervised and unsupervised approaches improved tracking results compared with the original noisy images, supervised learning generally outperformed the unsupervised approach. We find that nicer-looking image sequences are not synonymous with more precise tracking results and highlight that deep learning algorithms can produce deceiving artifacts with extremely noisy images. Finally, we address the challenge of selecting parameters to train convolutional neural networks by implementing a frugal Bayesian optimizer that rapidly explores multidimensional parameter spaces, identifying networks yielding optimal particle tracking accuracy. Our study provides quantitative outcome measures of image restoration using deep learning. We anticipate broad application of this approach to critically evaluate artificial intelligence solutions for quantitative microscopy