Setting our sights on infectious diseases

In May 2019, the Wellcome Centre for Anti-Infectives Research (WCAIR) at the University of Dundee, UK, held an international conference with the aim of discussing some key questions around discovering new medicines for infectious diseases and a particular focus on diseases affecting Low and Middle Income Countries. There is an urgent need for new drugs to treat most infectious diseases. We were keen to see if there were lessons that we could learn across different disease areas and between the preclinical and clinical phases with the aim of exploring how we can improve and speed up the drug discovery, translational, and clinical development processes. We started with an introductory session on the current situation and then worked backward from clinical development to combination therapy, pharmacokinetic/pharmacodynamic (PK/PD) studies, drug discovery pathways, and new starting points and targets. This Viewpoint aims to capture some of the learnings

MMASS: an optimized array-based method for assessing CpG island methylation

We describe an optimized microarray method for identifying genome-wide CpG island methylation called microarray-based methylation assessment of single samples (MMASS) which directly compares methylated to unmethylated sequences within a single sample. To improve previous methods we used bioinformatic analysis to predict an optimized combination of methylation-sensitive enzymes that had the highest utility for CpG-island probes and different methods to produce unmethylated representations of test DNA for more sensitive detection of differential methylation by hybridization. Subtraction or methylation-dependent digestion with McrBC was used with optimized (MMASS-v2) or previously described (MMASS-v1, MMASS-sub) methylation-sensitive enzyme combinations and compared with a published McrBC method. Comparison was performed using DNA from the cell line HCT116. We show that the distribution of methylation microarray data is inherently skewed and requires exogenous spiked controls for normalization and that analysis of digestion of methylated and unmethylated control sequences together with linear fit models of replicate data showed superior statistical power for the MMASS-v2 method. Comparison with previous methylation data for HCT116 and validation of CpG islands from PXMP4, SFRP2, DCC, RARB and TSEN2 confirmed the accuracy of MMASS-v2 results. The MMASS-v2 method offers improved sensitivity and statistical power for high-throughput microarray identification of differential methylation

Quantifying Cost-Effectiveness of Controlling Nosocomial Spread of Antibiotic-Resistant Bacteria: The Case of MRSA

BACKGROUND: The costs and benefits of controlling nosocomial spread of antibiotic-resistant bacteria are unknown. METHODS: We developed a mathematical algorithm to determine cost-effectiveness of infection control programs and explored the dynamical interactions between different epidemiological variables and cost-effectiveness. The algorithm includes occurrence of nosocomial infections, attributable mortality, costs and efficacy of infection control and how antibiotic-resistant bacteria affect total number of infections: do infections with antibiotic-resistant bacteria replace infections caused by susceptible bacteria (replacement scenario) or occur in addition to them (addition scenario). Methicillin-resistant Staphylococcus aureus (MRSA) bacteremia was used for illustration using observational data on S. aureus bacteremia (SAB) in our hospital (n = 189 between 2001-2004, all being methicillin-susceptible S. aureus [MSSA]). RESULTS: In the replacement scenario, the costs per life year gained range from 45,912 euros to 6590 euros for attributable mortality rates ranging from 10% to 50%. Using 20,000 euros per life year gained as a threshold, completely preventing MRSA would be cost-effective in the replacement scenario if attributable mortality of MRSA is > or = 21%. In the addition scenario, infection control would be cost saving along the entire range of estimates for attributable mortality. CONCLUSIONS: Cost-effectiveness of controlling antibiotic-resistant bacteria is highly sensitive to the interaction between infections caused by resistant and susceptible bacteria (addition or replacement) and attributable mortality. In our setting, controlling MRSA would be cost saving for the addition scenario but would not be cost-effective in the replacement scenario if attributable mortality would be < 21%

A Multi-Center Randomized Trial to Assess the Efficacy of Gatifloxacin versus Ciprofloxacin for the Treatment of Shigellosis in Vietnamese Children

The bacterial genus Shigella is the most common cause of dysentery (diarrhea containing blood and/or mucus) and the disease is common in developing countries with limitations in sanitation. Children are most at risk of infection and frequently require hospitalization and antimicrobial therapy. The WHO currently recommends the fluoroquinolone, ciprofloxacin, for the treatment of childhood Shigella infections. In recent years there has been a sharp increase in the number of organisms that exhibit resistance to nalidixic acid (an antimicrobial related to ciprofloxacin), corresponding with reduced susceptibility to ciprofloxacin. We hypothesized that infections with Shigella strains that demonstrate resistance to nalidixic acid may prevent effective treatment with ciprofloxacin. We performed a randomized controlled trial to compare 3 day ciprofloxacin therapy with 3 days of gatifloxacin, a newer generation fluoroquinolone with greater activity than ciprofloxacin. We measured treatment failure and time to the cessation of individual disease symptoms in 249 children with dysentery treated with gatifloxacin and 245 treated with ciprofloxacin. We could identify no significant differences in treatment failure between the two groups or in time to the cessation of individual symptoms. We conclude that, in Vietnam, ciprofloxacin and gatifloxacin are similarly effective for the treatment of acute dysentery

From old organisms to new molecules: integrative biology and therapeutic targets in accelerated human ageing

Understanding the basic biology of human ageing is a key milestone in attempting to ameliorate the deleterious consequences of old age. This is an urgent research priority given the global demographic shift towards an ageing population. Although some molecular pathways that have been proposed to contribute to ageing have been discovered using classical biochemistry and genetics, the complex, polygenic and stochastic nature of ageing is such that the process as a whole is not immediately amenable to biochemical analysis. Thus, attempts have been made to elucidate the causes of monogenic progeroid disorders that recapitulate some, if not all, features of normal ageing in the hope that this may contribute to our understanding of normal human ageing. Two canonical progeroid disorders are Werner’s syndrome and Hutchinson-Gilford progeroid syndrome (also known as progeria). Because such disorders are essentially phenocopies of ageing, rather than ageing itself, advances made in understanding their pathogenesis must always be contextualised within theories proposed to help explain how the normal process operates. One such possible ageing mechanism is described by the cell senescence hypothesis of ageing. Here, we discuss this hypothesis and demonstrate that it provides a plausible explanation for many of the ageing phenotypes seen in Werner’s syndrome and Hutchinson-Gilford progeriod syndrome. The recent exciting advances made in potential therapies for these two syndromes are also reviewed

Observation of the Resonant Character of the Z(4430)(-) State

Resonant structures in B-0 -> psi'pi K--(+) decays are analyzed by performing a four-dimensional fit of the decay amplitude, using pp collision data corresponding to 3 fb(-1) collected with the LHCb detector. The data cannot be described with K+pi(-) resonances alone, which is confirmed with a model-independent approach. A highly significant Z(4430)(-) -> psi'pi(-) component is required, thus confirming the existence of this state. The observed evolution of the Z(4430)(-) amplitude with the psi'pi(-) mass establishes the resonant nature of this particle. The mass and width measurements are substantially improved. The spin parity is determined unambiguously to be 1(+)

Measurement of the CKM angle γ using<i> B</i>^± → <i>DK</i>^± with D → K _S ⁰ π⁺π⁻, K _S ⁰ K⁺K⁻ decays

A binned Dalitz plot analysis of $B^\pm \to D K^\pm$ decays, with $D\to K_\text{S}^0\pi^+\pi^-$ and $D\to K_\text{S}^0K^+K^-$, is used to perform a measurement of the CP-violating observables $x_{\pm}$ and $y_{\pm}$, which are sensitive to the Cabibbo-Kobayashi-Maskawa angle $\gamma$. The analysis is performed without assuming any $D$ decay model, through the use of information on the strong-phase variation over the Dalitz plot from the CLEO collaboration. Using a sample of proton-proton collision data collected with the LHCb experiment in 2015 and 2016, and corresponding to an integrated luminosity of 2.0$\,\text{fb}^{-1}$, the values of the CP violation parameters are found to be $x_- = ( 9.0 \pm 1.7 \pm 0.7 \pm 0.4) \times 10^{-2}$, $y_- = ( 2.1 \pm 2.2 \pm 0.5 \pm 1.1) \times 10^{-2}$, $x_+ = (- 7.7 \pm 1.9 \pm 0.7 \pm 0.4) \times 10^{-2}$, and $y_+ = (- 1.0 \pm 1.9 \pm 0.4 \pm 0.9) \times 10^{-2}$. The first uncertainty is statistical, the second is systematic, and the third is due to the uncertainty on the strong-phase measurements. These values are used to obtain \gamma = \left(87\,^{+11}_{-12}\right)^\circ, $r_B = 0.086^{+ 0.013}_{-0.014}$, and $\delta_B = (101 \pm 11)^\circ$, where $r_B$ is the ratio between the suppressed and favoured $B$-decay amplitudes and $\delta_B$ is the corresponding strong-interaction phase difference. This measurement is combined with the result obtained using 2011 and 2012 data collected with the \lhcb experiment, to give \gamma = \left(80\,^{+10}_{\,-9}\right)^\circ, $r_B = 0.080 \pm 0.011$, and $\delta_B = (110 \pm 10)^\circ$.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://lhcbproject.web.cern.ch/lhcbproject/Publications/LHCbProjectPublic/LHCb-PAPER-2018-017.html. Version 2 includes minor changes made during journal revie

The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC