The pH-dependence of lipid-mediated antimicrobial peptide resistance in a model Staphylococcal plasma membrane: a two-for-one mechanism of epithelial defence circumvention.

The mechanisms of membrane defence by lysylphosphatidylglycerol (LPG), were investigated using synthetic biomimetic mono- and bilayer models of methicillin resistant S. aureus ST239 TW, based on its lipid composition in both pH 7.4 (28% LPG) and pH 5.5 (51% LPG) cultures. These models incorporated a stable synthetic analogue of LPG (3adLPG) to facilitate long-duration biophysical studies, which were previously limited by the lability native LPG. Both increased 3adLPG content and full headgroup ionization at pH 5.5, increased bilayer order and dampened overall charge, via the formation of neutral ion pairs with anionic lipids. Ion pair formation in air/liquid interface lipid monolayers elicited a significant condensing effect, which correlated with the inhibition of subphase-injected magainin 2 F5W partitioning. In fluid phase lipid vesicles, increasing the proportion of 3adLPG from 28 to 51 mol% completely inhibited the adoption of the membrane-active ?-helical conformation of the peptide, without the need for full headgroup ionization. Neutron reflectivity measurements performed on biomimetic PG/3adLPG fluid floating bilayers, showed a significant ordering effect of mild acidity on a bilayer containing 30 mol% 3adLPG, whilst peptide binding/partitioning was only fully inhibited in a bilayer with 55 mol% 3adLPG at pH 5.5. These findings are discussed with respect to the roles of LPG in resistance to human epithelial defences in S. aureus and the continued evolution of this opportunistic pathogen’s virulence

Evaluation of the Antimicrobial Activity of Cationic Polymers against Mycobacteria: Toward Antitubercular Macromolecules.

Antimicrobial resistance is a global healthcare problem with a dwindling arsenal of usable drugs. Tuberculosis, caused by Mycobacterium tuberculosis, requires long-term combination therapy and multi- and totally drug resistant strains have emerged. This study reports the antibacterial activity of cationic polymers against mycobacteria, which are distinguished from other Gram-positive bacteria by their unique cell wall comprising a covalently linked mycolic acid-arabinogalactan-peptidoglycan complex (mAGP), interspersed with additional complex lipids which helps them persist in their host. The present study finds that poly(dimethylaminoethyl methacrylate) has particularly potent antimycobacterial activity and high selectivity over two Gram-negative strains. Removal of the backbone methyl group (poly(dimethylaminoethyl acrylate)) decreased antimycobacterial activity, and poly(aminoethyl methacrylate) also had no activity against mycobacteria. Hemolysis assays revealed poly(dimethylaminoethyl methacrylate) did not disrupt red blood cell membranes. Interestingly, poly(dimethylaminoethyl methacrylate) was not found to permeabilize mycobacterial membranes, as judged by dye exclusion assays, suggesting the mode of action is not simple membrane disruption, supported by electron microscopy analysis. These results demonstrate that synthetic polycations, with the correctly tuned structure are useful tools against mycobacterial infections, for which new drugs are urgently required

Niche and local geography shape the pangenome of wastewater- and livestock-associated Enterobacteriaceae

Escherichia coli and other Enterobacteriaceae are diverse species with “open” pangenomes, where genes move intra- and interspecies via horizontal gene transfer. However, most analyses focus on clinical isolates. The pangenome dynamics of natural populations remain understudied, despite their suggested role as reservoirs for antimicrobial resistance (AMR) genes. Here, we analyze near-complete genomes for 827 Enterobacteriaceae (553 Escherichia and 274 non-Escherichia spp.) with 2292 circularized plasmids in total, collected from 19 locations (livestock farms and wastewater treatment works in the United Kingdom) within a 30-km radius at three time points over a year. We find different dynamics for chromosomal and plasmid-borne genes. Plasmids have a higher burden of AMR genes and insertion sequences, and AMR-gene-carrying plasmids show evidence of being under stronger selective pressure. Environmental niche and local geography both play a role in shaping plasmid dynamics. Our results highlight the importance of local strategies for controlling the spread of AMR

Bi-allelic Loss-of-Function CACNA1B Mutations in Progressive Epilepsy-Dyskinesia.

The occurrence of non-epileptic hyperkinetic movements in the context of developmental epileptic encephalopathies is an increasingly recognized phenomenon. Identification of causative mutations provides an important insight into common pathogenic mechanisms that cause both seizures and abnormal motor control. We report bi-allelic loss-of-function CACNA1B variants in six children from three unrelated families whose affected members present with a complex and progressive neurological syndrome. All affected individuals presented with epileptic encephalopathy, severe neurodevelopmental delay (often with regression), and a hyperkinetic movement disorder. Additional neurological features included postnatal microcephaly and hypotonia. Five children died in childhood or adolescence (mean age of death: 9 years), mainly as a result of secondary respiratory complications. CACNA1B encodes the pore-forming subunit of the pre-synaptic neuronal voltage-gated calcium channel Cav2.2/N-type, crucial for SNARE-mediated neurotransmission, particularly in the early postnatal period. Bi-allelic loss-of-function variants in CACNA1B are predicted to cause disruption of Ca2+ influx, leading to impaired synaptic neurotransmission. The resultant effect on neuronal function is likely to be important in the development of involuntary movements and epilepsy. Overall, our findings provide further evidence for the key role of Cav2.2 in normal human neurodevelopment.MAK is funded by an NIHR Research Professorship and receives funding from the Wellcome Trust, Great Ormond Street Children's Hospital Charity, and Rosetrees Trust. E.M. received funding from the Rosetrees Trust (CD-A53) and Great Ormond Street Hospital Children's Charity. K.G. received funding from Temple Street Foundation. A.M. is funded by Great Ormond Street Hospital, the National Institute for Health Research (NIHR), and Biomedical Research Centre. F.L.R. and D.G. are funded by Cambridge Biomedical Research Centre. K.C. and A.S.J. are funded by NIHR Bioresource for Rare Diseases. The DDD Study presents independent research commissioned by the Health Innovation Challenge Fund (grant number HICF-1009-003), a parallel funding partnership between the Wellcome Trust and the Department of Health, and the Wellcome Trust Sanger Institute (grant number WT098051). We acknowledge support from the UK Department of Health via the NIHR comprehensive Biomedical Research Centre award to Guy's and St. Thomas' National Health Service (NHS) Foundation Trust in partnership with King's College London. This research was also supported by the NIHR Great Ormond Street Hospital Biomedical Research Centre. J.H.C. is in receipt of an NIHR Senior Investigator Award. The research team acknowledges the support of the NIHR through the Comprehensive Clinical Research Network. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, Department of Health, or Wellcome Trust. E.R.M. acknowledges support from NIHR Cambridge Biomedical Research Centre, an NIHR Senior Investigator Award, and the University of Cambridge has received salary support in respect of E.R.M. from the NHS in the East of England through the Clinical Academic Reserve. I.E.S. is supported by the National Health and Medical Research Council of Australia (Program Grant and Practitioner Fellowship)

Comparison of the first whole genome sequence of ‘Haemophilus quentini’ with two new strains of ‘Haemophilus quentini’ and other species of Haemophilus

Comparison of the genome of the Gram negative human pathogen Haemophilus quentini MP1 with other Haemophilus species revealed that, although it is more closely related to Haemophilus haemolyticus than Haemophilus influenzae, the pathogen is in fact genetically distinct, a finding confirmed by phylogenetic analysis using the H. influenzae multilocus sequence typing genes. Further comparison with two other H. quentini strains recently identified in Canada revealed that these three genomes are more closely related than any other Haemophilus species, however there is still some sequence variation. There was no evidence of acquired antimicrobial resistance within the H. quentini MP1 genome nor any mutations within the DNA gyrase or topoisomerase IV genes known to confer resistance to fluoroquinolones, which has been previously identified in other H. quentini isolates. We hope by presenting the annotation and genetic comparison of the H. quentini MP1 genome it will aid the future molecular detection of this potentially emerging pathogen via the identification of unique genes that differentiate it from other Haemophilus species.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19

Data availability: Downloadable summary data are available through the GenOMICC data site (https://genomicc.org/data). Summary statistics are available, but without the 23andMe summary statistics, except for the 10,000 most significant hits, for which full summary statistics are available. The full GWAS summary statistics for the 23andMe discovery dataset will be made available through 23andMe to qualified researchers under an agreement with 23andMe that protects the privacy of the 23andMe participants. For further information and to apply for access to the data, see the 23andMe website (https://research.23andMe.com/dataset-access/). All individual-level genotype and whole-genome sequencing data (for both academic and commercial uses) can be accessed through the UKRI/HDR UK Outbreak Data Analysis Platform (https://odap.ac.uk). A restricted dataset for a subset of GenOMICC participants is also available through the Genomics England data service. Monocyte RNA-seq data are available under the title ‘Monocyte gene expression data’ within the Oxford University Research Archives (https://doi.org/10.5287/ora-ko7q2nq66). Sequencing data will be made freely available to organizations and researchers to conduct research in accordance with the UK Policy Framework for Health and Social Care Research through a data access agreement. Sequencing data have been deposited at the European Genome–Phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGAS00001007111.Extended data figures and tables are available online at https://www.nature.com/articles/s41586-023-06034-3#Sec21 .Supplementary information is available online at https://www.nature.com/articles/s41586-023-06034-3#Sec22 .Code availability: Code to calculate the imputation of P values on the basis of SNPs in linkage disequilibrium is available at GitHub (https://github.com/baillielab/GenOMICC_GWAS).Acknowledgements: We thank the members of the Banco Nacional de ADN and the GRA@CE cohort group; and the research participants and employees of 23andMe for making this work possible. A full list of contributors who have provided data that were collated in the HGI project, including previous iterations, is available online (https://www.covid19hg.org/acknowledgements).Change history: 11 July 2023: A Correction to this paper has been published at: https://doi.org/10.1038/s41586-023-06383-z. -- In the version of this article initially published, the name of Ana Margarita Baldión-Elorza, of the SCOURGE Consortium, appeared incorrectly (as Ana María Baldion) and has now been amended in the HTML and PDF versions of the article.Copyright © The Author(s) 2023, Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).GenOMICC was funded by Sepsis Research (the Fiona Elizabeth Agnew Trust), the Intensive Care Society, a Wellcome Trust Senior Research Fellowship (to J.K.B., 223164/Z/21/Z), the Department of Health and Social Care (DHSC), Illumina, LifeArc, the Medical Research Council, UKRI, a BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070 and BBS/E/D/30002275) and UKRI grants MC_PC_20004, MC_PC_19025, MC_PC_1905 and MRNO2995X/1. A.D.B. acknowledges funding from the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z), the Edinburgh Clinical Academic Track (ECAT) programme. This research is supported in part by the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant MC_PC_20029). Laboratory work was funded by a Wellcome Intermediate Clinical Fellowship to B.F. (201488/Z/16/Z). We acknowledge the staff at NHS Digital, Public Health England and the Intensive Care National Audit and Research Centre who provided clinical data on the participants; and the National Institute for Healthcare Research Clinical Research Network (NIHR CRN) and the Chief Scientist’s Office (Scotland), who facilitate recruitment into research studies in NHS hospitals, and to the global ISARIC and InFACT consortia. GenOMICC genotype controls were obtained using UK Biobank Resource under project 788 funded by Roslin Institute Strategic Programme Grants from the BBSRC (BBS/E/D/10002070 and BBS/E/D/30002275) and Health Data Research UK (HDR-9004 and HDR-9003). UK Biobank data were used in the GSMR analyses presented here under project 66982. The UK Biobank was established by the Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government and the Northwest Regional Development Agency. It has also had funding from the Welsh Assembly Government, British Heart Foundation and Diabetes UK. The work of L.K. was supported by an RCUK Innovation Fellowship from the National Productivity Investment Fund (MR/R026408/1). J.Y. is supported by the Westlake Education Foundation. SCOURGE is funded by the Instituto de Salud Carlos III (COV20_00622 to A.C., PI20/00876 to C.F.), European Union (ERDF) ‘A way of making Europe’, Fundación Amancio Ortega, Banco de Santander (to A.C.), Cabildo Insular de Tenerife (CGIEU0000219140 ‘Apuestas científicas del ITER para colaborar en la lucha contra la COVID-19’ to C.F.) and Fundación Canaria Instituto de Investigación Sanitaria de Canarias (PIFIISC20/57 to C.F.). We also acknowledge the contribution of the Centro National de Genotipado (CEGEN) and Centro de Supercomputación de Galicia (CESGA) for funding this project by providing supercomputing infrastructures. A.D.L. is a recipient of fellowships from the National Council for Scientific and Technological Development (CNPq)-Brazil (309173/2019-1 and 201527/2020-0)