Sharing of carbapenemase-encoding plasmids between Enterobacteriaceae in UK sewage uncovered by MinION sequencing

Dissemination of carbapenem resistance among pathogenic Gram-negative bacteria is a looming medical emergency. Efficient spread of resistance within and between bacterial species is facilitated by mobile genetic elements. We hypothesized that wastewater contributes to the dissemination of carbapenemase-producing Enterobacteriaceae (CPE), and studied this through a cross-sectional observational study of wastewater in the East of England. We isolated clinically relevant species of CPE in untreated and treated wastewater, confirming that waste treatment does not prevent release of CPE into the environment. We observed that CPE-positive plants were restricted to those in direct receipt of hospital waste, suggesting that hospital effluent may play a role in disseminating carbapenem resistance. We postulated that plasmids carrying carbapenemase genes were exchanged between bacterial hosts in sewage, and used short-read (Illumina) and long-read (MinION) technologies to characterize plasmids encoding resistance to antimicrobials and heavy metals. We demonstrated that different CPE species ($\textit{Enterobacter kobei}$ and $\textit{Raoultella ornithinolytica}$) isolated from wastewater from the same treatment plant shared two plasmids of 63 and 280 kb. The former plasmid conferred resistance to carbapenems ($bla_\text{OXA-48}$), and the latter to numerous drug classes and heavy metals. We also report the complete genome sequence for $\textit{Enterobacter kobei}$. Small, portable sequencing instruments such as the MinION have the potential to improve the quality of information gathered on antimicrobial resistance in the environment.This publication presents independent research supported by the Health Innovation Challenge Fund (WT098600, HICF-T5-342), a parallel funding partnership between the Department of Health, UK, and the Wellcome Trust. C. L. is a Wellcome Trust Sir Henry Postdoctoral Fellow (110243/Z/15/Z). T. G. is a Wellcome Trust Research Training Fellow (103387/Z/13/Z)

Peasants' Choices? Indian Agriculture and the Limits of Commercialization in Nineteenth-Century Bihar

The article attempts to distinguish and locate choices in agricultural production, with special reference to Bihar, India, during the nineteenth century. On the one hand, it considers closely managed and extensively irrigated areas, long involved in trade under the overall control of 'landlords', and, on the other hand, the expanding production of opium, and also of indigo and sugar (so-called 'forced' commercialization), identifying common features and continuities of production and marketing. Particular the importance of advance payments and local intermediaries is stressed. Thus, in contrast with the more usual evolutionary models, based on unitary categories and modes, the essay illustrates ecological, customary, collective, and local political constraints upon agricultural decisions; and this leads to the identification in turn of their different kinds and levels

Characterizing low affinity epibatidine binding to α4β2 nicotinic acetylcholine receptors with ligand depletion and nonspecific binding

<p>Abstract</p> <p>Background</p> <p>Along with high affinity binding of epibatidine (<it>K</it>_d1≈10 pM) to α4β2 nicotinic acetylcholine receptor (nAChR), low affinity binding of epibatidine (<it>K</it>_d2≈1-10 nM) to an independent binding site has been reported. Studying this low affinity binding is important because it might contribute understanding about the structure and synthesis of α4β2 nAChR. The binding behavior of epibatidine and α4β2 AChR raises a question about interpreting binding data from two independent sites with ligand depletion and nonspecific binding, both of which can affect equilibrium binding of [³H]epibatidine and α4β2 nAChR. If modeled incorrectly, ligand depletion and nonspecific binding lead to inaccurate estimates of binding constants. Fitting total equilibrium binding as a function of total ligand accurately characterizes a single site with ligand depletion and nonspecific binding. The goal of this study was to determine whether this approach is sufficient with two independent high and low affinity sites.</p> <p>Results</p> <p>Computer simulations of binding revealed complexities beyond fitting total binding for characterizing the second, low affinity site of α4β2 nAChR. First, distinguishing low-affinity specific binding from nonspecific binding was a potential problem with saturation data. Varying the maximum concentration of [³H]epibatidine, simultaneously fitting independently measured nonspecific binding, and varying α4β2 nAChR concentration were effective remedies. Second, ligand depletion helped identify the low affinity site when nonspecific binding was significant in saturation or competition data, contrary to a common belief that ligand depletion always is detrimental. Third, measuring nonspecific binding without α4β2 nAChR distinguished better between nonspecific binding and low-affinity specific binding under some circumstances of competitive binding than did presuming nonspecific binding to be residual [³H]epibatidine binding after adding a large concentration of cold competitor. Fourth, nonspecific binding of a heterologous competitor changed estimates of high and low inhibition constants but did not change the ratio of those estimates.</p> <p>Conclusions</p> <p>Investigating the low affinity site of α4β2 nAChR with equilibrium binding when ligand depletion and nonspecific binding are present likely needs special attention to experimental design and data interpretation beyond fitting total binding data. Manipulation of maximum ligand and receptor concentrations and intentionally increasing ligand depletion are potentially helpful approaches.</p

Heterogeneity of human adipose blood flow

BACKGROUND: The long time pharmacokinetics of highly lipid soluble compounds is dominated by blood-adipose tissue exchange and depends on the magnitude and heterogeneity of adipose blood flow. Because the adipose tissue is an infinite sink at short times (hours), the kinetics must be followed for days in order to determine if the adipose perfusion is heterogeneous. The purpose of this paper is to quantitate human adipose blood flow heterogeneity and determine its importance for human pharmacokinetics. METHODS: The heterogeneity was determined using a physiologically based pharmacokinetic model (PBPK) to describe the 6 day volatile anesthetic data previously published by Yasuda et. al. The analysis uses the freely available software PKQuest and incorporates perfusion-ventilation mismatch and time dependent parameters that varied from the anesthetized to the ambulatory period. This heterogeneous adipose perfusion PBPK model was then tested by applying it to the previously published cannabidiol data of Ohlsson et. al. and the cannabinol data of Johansson et. al. RESULTS: The volatile anesthetic kinetics at early times have only a weak dependence on adipose blood flow while at long times the pharmacokinetics are dominated by the adipose flow and are independent of muscle blood flow. At least 2 adipose compartments with different perfusion rates (0.074 and 0.014 l/kg/min) were needed to describe the anesthetic data. This heterogeneous adipose PBPK model also provided a good fit to the cannabinol data. CONCLUSION: Human adipose blood flow is markedly heterogeneous, varying by at least 5 fold. This heterogeneity significantly influences the long time pharmacokinetics of the volatile anesthetics and tetrahydrocannabinol. In contrast, using this same PBPK model it can be shown that the long time pharmacokinetics of the persistent lipophilic compounds (dioxins, PCBs) do not depend on adipose blood flow. The ability of the same PBPK model to describe both the anesthetic and cannabinol kinetics provides direct qualitative evidence that their kinetics are flow limited and that there is no significant adipose tissue diffusion limitation

Time to reach steady state and prediction of steady-state concentrations for drugs obeying Michaelis-Menten elimination kinetics

Using a numerical integration method, concentration-time data were simulated using the one-compartment open model both with bolus intravenous administration and oral administration (first-order absorption) after multiple doses administered at constant time intervals and for each model for five different doses. Constants used produced data very similar to those which have been reported for phenytoin in the literature. In the simulation of oral data, sufficient concentrations were recorded to allow estimation of the maximum (C n max ), average (¯) C n , and minimum (C n min ) concentrations during each dosage interval, but for the intravenous data only C n max and C n min values were recorded. The approach to steady state was monoexponential for low doses and biexponential for higher doses. The half-life of the final first-order approach to the steady-state concentration was approximately linearly related to the final steady-state concentration. For the intravenous data the number of doses required to reach 95% of C ss min was a linear function of 0.95 C ss min . A simple difference plot allows any given steady-state concentration of the three to be estimated from non-steady-state concentrations. When C n min values are measured, as in therapeutic drug monitoring, the fitting of C ss min vs. dose rate (D/τ) data leads to operationally useful parameters, V m app and K m app , which are not the true kinetic parameters, V m and K m , whereas fitting of ¯C ss vs d/τ data does lead to estimation of V m and K m .Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45075/1/10928_2005_Article_BF01312263.pd

The pharmacokinetics of the interstitial space in humans

BACKGROUND: The pharmacokinetics of extracellular solutes is determined by the blood-tissue exchange kinetics and the volume of distribution in the interstitial space in the different organs. This information can be used to develop a general physiologically based pharmacokinetic (PBPK) model applicable to most extracellular solutes. METHODS: The human pharmacokinetic literature was surveyed to tabulate the steady state and equilibrium volume of distribution of the solutes mannitol, EDTA, morphine-6-glucuronide, morphine-3-glucuronide, inulin and β-lactam antibiotics with a range of protein binding (amoxicillin, piperacillin, cefatrizine, ceforanide, flucloxacillin, dicloxacillin). A PBPK data set was developed for extracellular solutes based on the literature for interstitial organ volumes. The program PKQuest was used to generate the PBPK model predictions. The pharmacokinetics of the protein (albumin) bound β-lactam antibiotics were characterized by two parameters: 1) the free fraction of the solute in plasma; 2) the interstitial albumin concentration. A new approach to estimating the capillary permeability is described, based on the pharmacokinetics of the highly protein bound antibiotics. RESULTS: About 42% of the total body water is extracellular. There is a large variation in the organ distribution of this water – varying from about 13% of total tissue water for skeletal muscle, up to 70% for skin and connective tissue. The weakly bound antibiotics have flow limited capillary-tissue exchange kinetics. The highly protein bound antibiotics have a significant capillary permeability limitation. The experimental pharmacokinetics of the 11 solutes is well described using the new PBPK data set and PKQuest. CONCLUSIONS: Only one adjustable parameter (systemic clearance) is required to completely characterize the PBPK for these extracellular solutes. Knowledge of just this systemic clearance allows one to predict the complete time course of the absolute drug concentrations in the major organs. PKQuest is freely available

Geographical and temporal distribution of SARS-CoV-2 clades in the WHO European Region, January to June 2020

We show the distribution of SARS-CoV-2 genetic clades over time and between countries and outline potential genomic surveillance objectives. We applied three available genomic nomenclature systems for SARS-CoV-2 to all sequence data from the WHO European Region available during the COVID-19 pandemic until 10 July 2020. We highlight the importance of real-time sequencing and data dissemination in a pandemic situation. We provide a comparison of the nomenclatures and lay a foundation for future European genomic surveillance of SARS-CoV-2.Peer reviewe

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