The central conserved region (CCR) of respiratory syncytial virus (RSV) G protein modulates host miRNA expression and alters the cellular response to infection

Respiratory Syncytial Virus (RSV) infects respiratory epithelial cells and deregulates host gene expression by many mechanisms including expression of RSV G protein (RSV G). RSV G protein encodes a central conserved region (CCR) containing a CX3C motif that functions as a fractalkine mimic. Disruption of the CX3C motif (a.a. 182–186) located in the CCR of the G protein has been shown to affect G protein function in vitro and the severity of RSV disease pathogenesis in vivo. We show that infection of polarized Calu3 respiratory cells with recombinant RSV having point mutations in Cys173 and 176 (C173/176S) (rA2-GC12), or Cys186 (C186S) (rA2-GC4) is associated with a decline in the integrity of polarized Calu-3 cultures and decreased virus production. This is accompanied with downregulation of miRNAs let-7f and miR-24 and upregulation of interferon lambda (IFNλ), a primary antiviral cytokine for RSV in rA2-GC12/rA2-GC4 infected cells. These results suggest that residues in the cysteine noose region of RSV G protein can modulate IFN λ expression accompanied by downregulation of miRNAs, and are important for RSV G protein function and targeting

The Leishmania donovani Ortholog of the Glycosylphosphatidylinositol Anchor Biosynthesis Cofactor PBN1 Is Essential for Host Infection

Visceral leishmaniasis is a deadly infectious disease caused by Leishmania donovani, a kinetoplastid parasite for which no licensed vaccine is available. To identify potential vaccine candidates, we systematically identified genes encoding putative cell surface and secreted proteins essential for parasite viability and host infection. We identified a protein encoded by LdBPK_061160 which, when ablated, resulted in a remarkable increase in parasite adhesion to tissue culture flasks. Here, we show that this phenotype is caused by the loss of glycosylphosphatidylinositol (GPI)-anchored surface molecules and that LdBPK_061160 encodes a noncatalytic component of the L. donovani GPI-mannosyltransferase I (GPI-MT I) complex. GPI-anchored surface molecules were rescued in the LdBPK_061160 mutant by the ectopic expression of both human genes PIG-X and PIG-M, but neither gene could complement the phenotype alone. From further sequence comparisons, we conclude that LdBPK_061160 is the functional orthologue of yeast PBN1 and mammalian PIG-X, which encode the noncatalytic subunits of their respective GPI-MT I complexes, and we assign LdBPK_061160 as LdPBN1. The LdPBN1 mutants could not establish a visceral infection in mice, a phenotype that was rescued by constitutive expression of LdPBN1. Although mice infected with the null mutant did not develop an infection, exposure to these parasites provided significant protection against subsequent infection with a virulent strain. In summary, we have identified the orthologue of the PBN1/PIG-X noncatalytic subunit of GPI-MT I in trypanosomatids, shown that it is essential for infection in a murine model of visceral leishmaniasis, and demonstrated that the LdPBN1 mutant shows promise for the development of an attenuated live vaccine

Syndromic surveillance to assess the potential public health impact of the Icelandic volcanic ash plume across the United Kingdom, April 2010

The Eyjafjallajökull volcano in Iceland erupted on 14 April 2010 emitting a volcanic ash plume that spread across the United Kingdom and mainland Europe. The Health Protection Agency and Health Protection Scotland used existing syndromic surveillance systems to monitor community health during the incident: there were no particularly unusual increases in any of the monitored conditions. This incident has again demonstrated the use of syndromic surveillance systems for monitoring community health in real time

Editorial: Small cetacean conservation: Current challenges and opportunities

Dolphins (oceanic and river dolphins; Delphinidae, Iniidae, Lipotidae, Pontoporiidae, Platanistidae) and porpoises (Phocoenidae) are the smallest members of the odontocete suborder. These species have colonized most aquatic ecosystems globally, from rivers to deep oceanic habitats, and from tropical to polar waters. Due to their habitat preferences, high metabolic rates, foraging behaviors, and diets, small cetaceans exhibit a wide range of ecological roles and functions across ecosystems where they occur and have the potential to affect communities via multiple pathways (top-down, bottom-up effects, and a range of behavior-mediated processes, Kiszka et al.). Dolphins and porpoises have also generated significant interest from the scientific community and more broadly by human societies since antiquity, with research on these animals increasing exponentially over the past 40-50 years. Despite protection by a range of international conventions (e.g., Convention on Migratory Species, Convention on the Trade of Endangered Species) and national legislation in most countries, some species are at increasing risk of decline and extirpation in aquatic habitats worldwide, with losses driven by a range of direct and indirect impacts from human activities. Today, more than 20% of species of oceanic dolphins, half of all species of porpoise, and all river dolphins are threatened with extinctionFil: Kiszka, Jeremy J.. Florida International University; Estados UnidosFil: Bejder, Lars. University of Hawaii at Manoa; Estados UnidosFil: Davis, Randall. Texas A&M University; Estados UnidosFil: Harcourt, Rob. Macquarie University; AustraliaFil: Meekan, Mark. University of Western Australia; AustraliaFil: Rodriguez, Diego Horacio. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Stockin, Karen A.. Massey University; Nueva Zeland

Predicting Clinical Deteriorations using Wearable Sensors

Introduction Acutely-ill hospitalised patients are at risk of clinical deteriorations such as cardiac arrest, admission to intensive care, or unexpected death. Currently, patients are manually assessed every 4-6 hours to determine the likelihood of subsequent deterioration. However, this is limited to intermittent assessments, delaying time-sensitive interventions. Wearable sensors, combined with an alerting system, could provide continuous automated assessments of the likelihood of deteriorations. To be suitable for hospital use, wearable sensors must be unobtrusive and provide reliable measurements of key vital signs including breathing rate (BR), a key predictor of deteriorations. The aims of this work were: (i) to develop a technique for monitoring BR unobtrusively using wearable sensors, and (ii) to assess whether wearable sensors provide reliable predictions of deteriorations when using this technique. Monitoring breathing rate (BR) unobtrusively Current methods for monitoring BR using wearable sensors are obtrusive. An alternative approach is to estimate BR from electrocardiogram or pulse oximeter signals, which are already acquired by wearable sensors to monitor heart rate and blood oxygen levels. Both signals are subtly modulated by breathing, providing opportunity to use them to monitor BR. I assessed the performance of previously proposed signal processing techniques for estimating BR from these signals in both healthy and hospitalised subjects. Although some techniques were precise enough for use with healthy subjects in the laboratory, they were imprecise when used with hospital patients. Therefore, I developed a novel technique, combining the strengths of time- and frequency-domain techniques. Its performance was assessed on data from 264 subjects. In hospital patients, the technique provided highly precise BRs 86% of the time, which exceeds the performance of manual observation, the current clinical standard. Assessing the reliability of wearable sensors for predicting deteriorations I implemented methods for rejecting unreliable sensor data, and for fusing continuous multiparametric data, to predict deteriorations. These were used alongside the novel technique for monitoring BR to predict deteriorations using wearable sensors. The system was assessed in a clinical trial of 184 hospital patients, conducted in collaboration with clinicians. The reliability of the system was assessed by comparing its predictions against documented deteriorations. Its predictive value was similar to that of the routine manual assessments (AUROCs of 0.78 vs 0.79). Crucially it provided continuous assessment, potentially providing predictions of deteriorations hours earlier than routine practice. Conclusion This work has demonstrated the potential for wearable sensors to reliably and unobtrusively predict deteriorations, when coupled with a novel technique for monitoring BR. This could improve patient outcomes, and reduce costs. Further work should investigate which patients would benefit most from this technology, and whether it could reduce clinical workload. In the future the technology could potentially be used with consumer wearables to improve patient safety in the community, where clinical expertise is less readily available.This poster was displayed at the STEM for Britain event, held in the Houses of Parliament (London, UK) on 12th March 2018

Respiratory rate monitoring to detect deteriorations using wearable sensors

This poster provides an overview of the work described in: P. H. Charlton, "Continuous respiratory rate monitoring to detect clinical deteriorations using wearable sensors," Ph.D. Thesis, King’s College London, 2017.This poster was first presented at the Bioengenuity Keynotes Conference, held on Monday 6th March at the University of Oxford