Predicting community dynamics of antibiotic-sensitive and -resistant species in fluctuating environments (article)

This is the author accepted manuscript. The final version is available from the Royal Society via the DOI in this recordThe dataset associated with this article is available in ORE: https://doi.org/10.24378/exe.2323Microbes occupy almost every niche within and on their human hosts. Whether colonizing the gut, mouth or bloodstream, microorganisms face temporal fluctuations in resources and stressors within their niche but we still know little of how environmental fluctuations mediate certain microbial phenotypes, notably antimicrobial-resistant ones. For instance, do rapid or slow fluctuations in nutrient and antimicrobial concentrations select for, or against, resistance? We tackle this question using an ecological approach by studying the dynamics of a synthetic and pathogenic microbial community containing two species, one sensitive and the other resistant to an antibiotic drug where the community is exposed to different rates of environmental fluctuation. We provide mathematical models, supported by experimental data, to demonstrate that simple community outcomes, such as competitive exclusion, can shift to coexistence and ecosystem bistability as fluctuation rates vary. Theory gives mechanistic insight into how these dynamical regimes are related. Importantly, our approach highlights a fundamental difference between resistance in single-species populations, the context in which it is usually assayed, and that in communities. While fast environmental changes are known to select against resistance in single-species populations, here we show that they can promote the resistant species in mixed-species communities. Our theoretical observations are verified empirically using a two-species Candida community.European Research Council (ERC)Engineering and Physical Sciences Research Council (EPSRC

Seeking patterns of antibiotic resistance in ATLAS, an open, raw MIC database with patient metadata

This is the final version. Available on open access from Nature Research via the DOI in this recordData availability: ATLAS is available following website registration*. Data and further information can be downloaded from the following links: Project overview: https://amr.theodi.org/project-overview Project description: https://wellcome.ac.uk/sites/default/files/antimicrobial-resistance-surveillance-sharing-industry-data.pdf Data download*: https://www.synapse.org/#!Synapse:syn17009517/wiki/585653 The same dataset is available from this link: https://s3-eu-west-1.amazonaws.com/amr-prototype-data/Open+Atlas_Reuse_Data.xlsx Data was extracted from the English Surveillance Programme for Antimicrobial Utilisation and Resistance (ESPAUR) report from years 2013-2018. These were downloaded from the following UK government website: https://www.gov.uk/government/publications/english-surveillance-programme-antimicrobial-utilisation-and-resistance-espaur-report ResistanceMap data is published by the Centre for Disease, Dynamics Economics and Policy28, it can be downloaded from https://github.com/gwenknight/empiricprescribing/tree/master/data, Data for the European Centre for Disease Prevention and Control (ECDC) can be downloaded from https://atlas.ecdc.europa.eu/public/index.aspx?Dataset=27#x00026;HealthTopic=4. The file we used in this paper can be downloaded from https://github.com/PabloCatalan/atlas/tree/master/data/europe_resistance_data.csv EUCAST data can only be obtained by contacting individuals named on their website https://www.eucast.org/mic_distributions_and_ecoffs/ and requesting access to MIC histograms, which we were granted.Code availability: Analysis codes66 written in Python 3.0 using pandas can be downloaded here: https://github.com/PabloCatalan/atlas or https://doi.org/10.5281/zenodo.6390565. Codes have been written to provide straightforward access to data so that figures from this manuscript can be reproduced and to help facilitate the development of new analyses. Interested readers are encouraged to seek assistance from corresponding authors in case it is not clear how those codes are used.Antibiotic resistance represents a growing medical concern where raw, clinical datasets are under-exploited as a means to track the scale of the problem. We therefore sought patterns of antibiotic resistance in the Antimicrobial Testing Leadership and Surveillance (ATLAS) database. ATLAS holds 6.5M minimal inhibitory concentrations (MICs) for 3,919 pathogen-antibiotic pairs isolated from 633k patients in 70 countries between 2004 and 2017. We show most pairs form coherent, although not stationary, timeseries whose frequencies of resistance are higher than other databases, although we identified no systematic bias towards including more resistant strains in ATLAS. We sought data anomalies whereby MICs could shift for methodological and not clinical or microbiological reasons and found artefacts in over 100 pathogen-antibiotic pairs. Using an information-optimal clustering methodology to classify pathogens into low and high antibiotic susceptibilities, we used ATLAS to predict changes in resistance. Dynamics of the latter exhibit complex patterns with MIC increases, and some decreases, whereby subpopulations' MICs can diverge. We also identify pathogens at risk of developing clinical resistance in the near future.Engineering and Physical Sciences Research Council (EPSRC)Ramón Areces Postdoctoral FellowshipMinisterio de Ciencia, Innovación y Universidades/FEDEREuropean Research Council (ERC)Biotechnology and Biological Sciences Research Council (BBSRC)David Phillips FellowshipNational Health and Medical Research Counci

Multiwavelength observations of nova SMCN 2016-10a --- one of the brightest novae ever observed

We report on multiwavelength observations of nova SMCN 2016-10a. The present observational set is one of the most comprehensive for any nova in the Small Magellanic Cloud, including: low, medium, and high resolution optical spectroscopy and spectropolarimetry from SALT, FLOYDS, and SOAR; long-term OGLE $V$- and $I$- bands photometry dating back to six years before eruption; SMARTS optical and near-IR photometry from $\sim$ 11 days until over 280 days post-eruption; $Swift$ satellite X-ray and ultraviolet observations from $\sim$ 6 days until 319 days post-eruption. The progenitor system contains a bright disk and a main sequence or a sub-giant secondary. The nova is very fast with $t_2 \simeq$ 4.0 $\pm$ 1.0 d and $t_3 \simeq$ 7.8 $\pm$ 2.0 d in the $V$-band. If the nova is in the SMC, at a distance of $\sim$ 61 $\pm$ 10 kpc, we derive $M_{V,\mathrm{max}} \simeq - 10.5$ $\pm$ 0.5, making it the brightest nova ever discovered in the SMC and one of the brightest on record. At day 5 post-eruption the spectral lines show a He/N spectroscopic class and a FWHM of $\sim$ 3500 kms$^{-1}$ indicating moderately high ejection velocities. The nova entered the nebular phase $\sim$ 20 days post-eruption, predicting the imminent super-soft source turn-on in the X-rays, which started $\sim$ 28 days post-eruption. The super-soft source properties indicate a white dwarf mass between 1.2 M$_{\odot}$ and 1.3 M$_{\odot}$ in good agreement with the optical conclusions

Swift follow-up observations of candidate gravitational-wave transient events

We present the first multi-wavelength follow-up observations of two candidate gravitational-wave (GW) transient events recorded by LIGO and Virgo in their 2009-2010 science run. The events were selected with low latency by the network of GW detectors and their candidate sky locations were observed by the Swift observatory. Image transient detection was used to analyze the collected electromagnetic data, which were found to be consistent with background. Off-line analysis of the GW data alone has also established that the selected GW events show no evidence of an astrophysical origin; one of them is consistent with background and the other one was a test, part of a "blind injection challenge". With this work we demonstrate the feasibility of rapid follow-ups of GW transients and establish the sensitivity improvement joint electromagnetic and GW observations could bring. This is a first step toward an electromagnetic follow-up program in the regime of routine detections with the advanced GW instruments expected within this decade. In that regime multi-wavelength observations will play a significant role in completing the astrophysical identification of GW sources. We present the methods and results from this first combined analysis and discuss its implications in terms of sensitivity for the present and future instruments.Comment: Submitted for publication 2012 May 25, accepted 2012 October 25, published 2012 November 21, in ApJS, 203, 28 ( http://stacks.iop.org/0067-0049/203/28 ); 14 pages, 3 figures, 6 tables; LIGO-P1100038; Science summary at http://www.ligo.org/science/Publication-S6LVSwift/index.php ; Public access area to figures, tables at https://dcc.ligo.org/cgi-bin/DocDB/ShowDocument?docid=p110003

The Ecology of Antibiotic Use in the ICU: Homogeneous Prescribing of Cefepime but Not Tazocin Selects for Antibiotic Resistant Infection

Background: Antibiotic homogeneity is thought to drive resistance but in vivo data are lacking. In this study, we determined the impact of antibiotic homogeneity per se, and of cefepime versus antipseudomonal penicillin/beta-lactamase inhibitor combinations (APP-beta), on the likelihood of infection or colonisation with antibiotic resistant bacteria and/or two commonly resistant nosocomial pathogens (methicillin-resistant Staphylococcus aureus and Pseudomonas aeruginosa). A secondary question was whether antibiotic cycling was associated with adverse outcomes including mortality, length of stay, and antibiotic resistance

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta