Real-time observation of antigen¿antibody association using a low-cost biosensing system based on photonic bandgap structures

This paper was published in OPTICS LETTERS and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: http://dx.doi.org/10.1364/OL.37.003684. Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under law[EN] In this letter, we present experimental results of antibody detection using a biosensor based on photonic bandgap structures, which are interrogated using a power-based readout technique. This interrogation method allows a realtime monitoring of the association process between the antigen probes and the target antibodies, allowing the instantaneous observation of any interaction event between molecules. because etunable lasers and optical spectrum analyzers are avoided for the readout, a drastic reduction of the final cost of the platform is obtained. Furthermore, the performance of the biosensing system is significantly enhanced due to the large number of data values obtained per second.This work was partially funded by the European Commission under contract FP7-295043-BELERA, from the Spanish Ministerio de Ciencia e Innovacion (MICINN) under contracts TEC2008-06333 and CTQ2010-15943 (subprogram BQU), and from Generalitat Valenciana through the PROMETEO grants 2010-008 and 2012-087.García Castelló, J.; Toccafondo, V.; Escorihuela Fuentes, J.; Bañuls Polo, MJ.; Maquieira Catala, Á.; García-Rupérez, J. (2012). Real-time observation of antigen¿antibody association using a low-cost biosensing system based on photonic bandgap structures. Optics Letters. 37(17):3684-3686. https://doi.org/10.1364/OL.37.003684S368436863717Luchansky, M. S., & Bailey, R. C. (2011). High-Q Optical Sensors for Chemical and Biological Analysis. Analytical Chemistry, 84(2), 793-821. doi:10.1021/ac2029024Qavi, A. J., & Bailey, R. C. (2010). Multiplexed Detection and Label-Free Quantitation of MicroRNAs Using Arrays of Silicon Photonic Microring Resonators. Angewandte Chemie International Edition, 49(27), 4608-4611. doi:10.1002/anie.201001712García-Rupérez, J., Toccafondo, V., Bañuls, M. J., Castelló, J. G., Griol, A., Peransi-Llopis, S., & Maquieira, Á. (2010). Label-free antibody detection using band edge fringes in SOI planar photonic crystal waveguides in the slow-light regime. Optics Express, 18(23), 24276. doi:10.1364/oe.18.024276Toccafondo, V., García-Rupérez, J., Bañuls, M. J., Griol, A., Castelló, J. G., Peransi-Llopis, S., & Maquieira, A. (2010). Single-strand DNA detection using a planar photonic-crystal-waveguide-based sensor. Optics Letters, 35(21), 3673. doi:10.1364/ol.35.003673Claes, T., Molera, J. G., De Vos, K., Schacht, E., Baets, R., & Bienstman, P. (2009). Label-Free Biosensing With a Slot-Waveguide-Based Ring Resonator in Silicon on Insulator. IEEE Photonics Journal, 1(3), 197-204. doi:10.1109/jphot.2009.2031596Scullion, M. G., Di Falco, A., & Krauss, T. F. (2011). Slotted photonic crystal cavities with integrated microfluidics for biosensing applications. Biosensors and Bioelectronics, 27(1), 101-105. doi:10.1016/j.bios.2011.06.023Zlatanovic, S., Mirkarimi, L. W., Sigalas, M. M., Bynum, M. A., Chow, E., Robotti, K. M., … Grot, A. (2009). Photonic crystal microcavity sensor for ultracompact monitoring of reaction kinetics and protein concentration. Sensors and Actuators B: Chemical, 141(1), 13-19. doi:10.1016/j.snb.2009.06.007Sepúlveda, B., Río, J. S. del, Moreno, M., Blanco, F. J., Mayora, K., Domínguez, C., & Lechuga, L. M. (2006). Optical biosensor microsystems based on the integration of highly sensitive Mach–Zehnder interferometer devices. Journal of Optics A: Pure and Applied Optics, 8(7), S561-S566. doi:10.1088/1464-4258/8/7/s41Claes, T., Bogaerts, W., & Bienstman, P. (2011). Vernier-cascade label-free biosensor with integrated arrayed waveguide grating for wavelength interrogation with low-cost broadband source. Optics Letters, 36(17), 3320. doi:10.1364/ol.36.003320Zinoviev, K. E., Gonzalez-Guerrero, A. B., Dominguez, C., & Lechuga, L. M. (2011). Integrated Bimodal Waveguide Interferometric Biosensor for Label-Free Analysis. Journal of Lightwave Technology, 29(13), 1926-1930. doi:10.1109/jlt.2011.2150734Densmore, A., Vachon, M., Xu, D.-X., Janz, S., Ma, R., Li, Y.-H., … Schmid, J. H. (2009). Silicon photonic wire biosensor array for multiplexed real-time and label-free molecular detection. Optics Letters, 34(23), 3598. doi:10.1364/ol.34.003598Castelló, J. G., Toccafondo, V., Pérez-Millán, P., Losilla, N. S., Cruz, J. L., Andrés, M. V., & García-Rupérez, J. (2011). Real-time and low-cost sensing technique based on photonic bandgap structures. Optics Letters, 36(14), 2707. doi:10.1364/ol.36.002707Krishnamoorthy, G., Bianca Beusink, J., & Schasfoort, R. B. M. (2010). High-throughput surface plasmon resonance imaging-based biomolecular kinetic screening analysis. Analytical Methods, 2(8), 1020. doi:10.1039/c0ay00112

Characterization of SARS-CoV-2 nucleocapsid protein reveals multiple functional consequences of the C-terminal domain

Nucleocapsid (N) encoded by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) plays key roles in the replication cycle and is a critical serological marker. Here, we characterize essential biochemical properties of N and describe the utility of these insights in serological studies. We define N domains important for oligomerization and RNA binding and show that N oligomerization provides a high-affinity RNA-binding platform. We also map the RNA-binding interface, showing protection in the N-terminal domain and linker region. In addition, phosphorylation causes reduction of RNA binding and redistribution of N from liquid droplets to loose coils, showing how N-RNA accessibility and assembly may be regulated by phosphorylation. Finally, we find that the C-terminal domain of N is the most immunogenic, based on antibody binding to patient samples. Together, we provide a biochemical description of SARS-CoV-2 N and highlight the value of using N domains as highly specific and sensitive diagnostic markers

Understanding the Potential Impact of Different Drug Properties On SARS-CoV-2 Transmission and Disease Burden: A Modelling Analysis

Background The public health impact of the COVID-19 pandemic has motivated a rapid search for potential therapeutics, with some key successes. However, the potential impact of different treatments, and consequently research and procurement priorities, have not been clear. Methods Using a mathematical model of SARS-CoV-2 transmission, COVID-19 disease and clinical care, we explore the public-health impact of different potential therapeutics, under a range of scenarios varying healthcare capacity, epidemic trajectories; and drug efficacy in the absence of supportive care. Results The impact of drugs like dexamethasone (delivered to the most critically-ill in hospital and whose therapeutic benefit is expected to depend on the availability of supportive care such as oxygen and mechanical ventilation) is likely to be limited in settings where healthcare capacity is lowest or where uncontrolled epidemics result in hospitals being overwhelmed. As such, it may avert 22% of deaths in high-income countries but only 8% in low-income countries (assuming R=1.35). Therapeutics for different patient populations (those not in hospital, early in the course of infection) and types of benefit (reducing disease severity or infectiousness, preventing hospitalisation) could have much greater benefits, particularly in resource-poor settings facing large epidemics. Conclusions Advances in the treatment of COVID-19 to date have been focussed on hospitalised-patients and predicated on an assumption of adequate access to supportive care. Therapeutics delivered earlier in the course of infection that reduce the need for healthcare or reduce infectiousness could have significant impact, and research into their efficacy and means of delivery should be a priority

Understanding the potential impact of different drug properties on SARS-CoV-2 transmission and disease burden : a modelling analysis

Q1Q1Background The unprecedented public health impact of the COVID-19 pandemic has motivated a rapid search for potential therapeutics, with some key successes. However, the potential impact of different treatments, and consequently research and procurement priorities, have not been clear. Methods and Findings develop a mathematical model of SARS-CoV-2 transmission, COVID-19 disease and clinical care to explore the potential public-health impact of a range of different potential therapeutics, under a range of different scenarios varying: i) healthcare capacity, ii) epidemic trajectories; and iii) drug efficacy in the absence of supportive care. In each case, the outcome of interest was the number of COVID-19 deaths averted in scenarios with the therapeutic compared to scenarios without. We find the impact of drugs like dexamethasone (which are delivered to the most critically-ill in hospital and whose therapeutic benefit is expected to depend on the availability of supportive care such as oxygen and mechanical ventilation) is likely to be limited in settings where healthcare capacity is lowest or where uncontrolled epidemics result in hospitals being overwhelmed. As such, it may avert 22% of deaths in highincome countries but only 8% in low-income countries (assuming R=1.35). Therapeutics for different patient populations (those not in hospital, early in the course of infection) and types of benefit (reducing disease severity or infectiousness, preventing hospitalisation) could have much greater benefits, particularly in resource-poor settings facing large epidemics. Conclusions There is a global asymmetry in who is likely to benefit from advances in the treatment of COVID-19 to date, which have been focussed on hospitalised-patients and predicated on an assumption of adequate access to supportive care. Therapeutics that can feasibly be delivered to those earlier in the course of infection that reduce the need for healthcare or reduce infectiousness could have significant impact, and research into their efficacy and means of delivery should be a priorityRevista Internacional - Indexad

Domain-specific biochemical and serological characterization of SARS-CoV-2 nucleocapsid protein

Nucleocapsid proteins are essential for SARS-CoV-2 life cycle. Here, we describe protocols to gather domain-specific insights about essential properties of nucleocapsids. These assays include dynamic light scattering to characterize oligomerization, fluorescence polarization to quantify RNA binding, hydrogen-deuterium exchange mass spectrometry to map RNA binding regions, negative-stain electron microscopy to visualize oligomeric species, interferon reporter assay to evaluate interferon signaling modulation, and a serology assay to reveal insights for improved sensitivity and specificity. These assays are broadly applicable to RNA-encapsidated nucleocapsids. For complete details on the use and execution of this protocol, please refer to Wu et al. (2021)

Sofosbuvir and daclatasvir compared with standard of care in the treatment of patients admitted to hospital with moderate or severe coronavirus infection (COVID-19): a randomized controlled trial

BACKGROUND: Currently no effective antiviral therapy has been found to treat COVID-19. The aim of this trial was to assess if the addition of sofosbuvir and daclatasvir improved clinical outcomes in patients with moderate or severe COVID-19. METHODS: This was an open-label, multicentre, randomized controlled clinical trial in adults with moderate or severe COVID-19 admitted to four university hospitals in Iran. Patients were randomized into a treatment arm receiving sofosbuvir and daclatasvir plus standard care, or a control arm receiving standard care alone. The primary endpoint was clinical recovery within 14 days of treatment. The study is registered with IRCT.ir under registration number IRCT20200128046294N2. RESULTS: Between 26 March and 26 April 2020, 66 patients were recruited and allocated to either the treatment arm (n = 33) or the control arm (n = 33). Clinical recovery within 14 days was achieved by 29/33 (88%) in the treatment arm and 22/33 (67%) in the control arm (P = 0.076). The treatment arm had a significantly shorter median duration of hospitalization [6 days (IQR 4-8)] than the control group [8 days (IQR 5-13)]; P = 0.029. Cumulative incidence of hospital discharge was significantly higher in the treatment arm versus the control (Gray's P = 0.041). Three patients died in the treatment arm and five in the control arm. No serious adverse events were reported. CONCLUSIONS: The addition of sofosbuvir and daclatasvir to standard care significantly reduced the duration of hospital stay compared with standard care alone. Although fewer deaths were observed in the treatment arm, this was not statistically significant. Conducting larger scale trials seems prudent