A Large Scale Metagenomic Analysis of the Faecal Microbiota in Preterm Infants Developing Necrotising Enterocolitis

Necrotising enterocolitis (NEC) is an inflammatory intestinal disorder affecting premature infants. Despite the worldwide improvement of health care practices and facilities raising the survival rates of neonatal premature infants, there has not been any improvement in treatment options or mortality rates for NEC. There has been an extensive volume of research into NEC, though to date there has not been any evidence to directly associate a causal agent to this devastating disease, nor have there been any conclusive observations of NEC prior to birth. The only key prognostic signal for NEC is that onset and severity of the disease are significantly associated with the prematurity of the neonatal infant. During the process of birth, the infant transitions from the near sterile conditions of the womb to the outside environment teeming with bacteria. Only then does the infant develop a symbiotic relationship as a host to beneficial bacteria. Upon this transition the community of gut microbes develops and aids in a range of host functions, namely digestion and absorption of nutrients, as well as the immune response. It is also at this time that NEC can begin to develop in the lower gastrointestinal tract. This coinciding of factors implicates the colonisation of the gut with bacteria in the development of NEC, however studies to date have failed to provide consistent reports of a causative pathogen or a characteristic gut microbiome structure associated with NEC. The purpose of this study was to characterise the structure of the bacterial community in the gastrointestinal tract of infants with and without NEC in order to identify a community distinctive to infants with NEC. This was addressed using non-invasive faecal sampling of premature infants in a large, prospectively enrolled cohort from across England, sampled over a twenty-day window spanning ten days prior to and ten days following the onset of NEC. Using established V4 16S rRNA protocols, bacterial taxa within environmental samples could be characterised without relying on classic culture dependent methods. With this amplification technique it was possible to utilise small amounts of bacterial DNA isolated from infant faecal samples while at the same time mitigating the selection bias associated with culture-based techniques. Short read sequencing (illumina MiSeq) was performed on a total of 656 faecal samples from 132 infants spanning eight neonatal intensive care units across England. All infants had gestational durations of less than 35 weeks. 44 infants had NEC (225 samples) and 88 were assigned as controls (431 samples) according to key risk factors defined by medical practitioners. Taxonomic abundances assigned with the QIIME informatics pipeline were normalised using non-reductive negative binomial normalisation. Local contributions to beta-diversity (LCBD) scores were used to quantify taxonomic changes in the community structure through subset regression. Non-metric multidimensional scaling (NMDS) was used to establish risk factors that best described NEC and control samples. The Random Forest machine learning algorithm was used to establish taxa that best discriminated between NEC and control infants, as well as to identify any conserved pathogens. Subset regression identified feeding regime, mode of delivery and age at sampling as significant discriminating factors for the NEC status of infants based on sample LCBD values. However, NMDS plots of sample LCBD values showed no clear clustering of samples according to NEC status. Canonical correlation analysis (CCA) indicated that this variability was due to inter-individual differences. Of the risk factors that could be accounted for, feeding regime was the most effective in differentiating community structures of NEC and control infant samples. There was also evidence that initial communities were influenced by delivery method. Three subgroups of infants based on these influential risk factors and with sufficient sampling depth were established and analysed separately in addition to collective, population-scale analysis. Random Forest analysis demonstrated that reduced abundance of the genus Bifidobacterium was significantly associated with NEC across all sub-groups of infants. Additionally, this method of analysis indicated no clear pathogenic taxa that consistently spanned the population. For infants with NEC that were delivered by caesarean section and fed both formula and breast milk, there was increased abundance of the genus Dialister when sampled shortly after birth. Infants that did not develop NEC, who were delivered vaginally and fed both formula and breast milk were seen to have a significantly greater abundance of the genus Veillonella over time, relative to NEC subjects. There were no additional taxonomic differences that could be ascertained in the sub-group of infants who were vaginally delivered and fed breast milk exclusively. Overall, the unique nature of the microbiome and the high degree of inter-individual variation within the community made direct comparisons between NEC and non-NEC subjects difficult. However, by accounting for factors that were significantly associated with NEC status it was possible to observe consistent association of increased bifidobacterial abundance in infants that did not develop NEC. This highlights the importance of large scale studies and case-control assignment when analysing complex community structures such as that of the human gastrointestinal tract, as well as the powerful, deep analytical analysis provided by machine learning algorithms. Further work should look to establish the impact and role of Bifidobacteria in the human gut community to inform early interventions in healthcare settings for infants at risk of NEC, focussing specifically on encouraging the development of a community structure reflective of that observed in premature infants that do not develop NEC

Oral iron exacerbates colitis and influences the intestinal microbiome

Inflammatory bowel disease (IBD) is associated with anaemia and oral iron replacement to correct this can be problematic, intensifying inflammation and tissue damage. The intestinal microbiota also plays a key role in the pathogenesis of IBD, and iron supplementation likely influences gut bacterial diversity in patients with IBD. Here, we assessed the impact of dietary iron, using chow diets containing either 100, 200 or 400 ppm, fed ad libitum to adult female C57BL/6 mice in the presence or absence of colitis induced using dextran sulfate sodium (DSS), on (i) clinical and histological severity of acute DSS-induced colitis, and (ii) faecal microbial diversity, as assessed by sequencing the V4 region of 16S rRNA. Increasing or decreasing dietary iron concentration from the standard 200 ppm exacerbated both clinical and histological severity of DSS-induced colitis. DSS-treated mice provided only half the standard levels of iron ad libitum (i.e. chow containing 100 ppm iron) lost more body weight than those receiving double the amount of standard iron (i.e. 400 ppm); p<0.01. Faecal calprotectin levels were significantly increased in the presence of colitis in those consuming 100 ppm iron at day 8 (5.94-fold) versus day-10 group (4.14-fold) (p<0.05), and for the 400 ppm day-8 group (8.17-fold) versus day-10 group (4.44-fold) (p<0.001). In the presence of colitis, dietary iron at 400 ppm resulted in a significant reduction in faecal abundance of Firmicutes and Bacteroidetes, and increase of Proteobacteria, changes which were not observed with lower dietary intake of iron at 100 ppm. Overall, altering dietary iron intake exacerbated DSS-induced colitis; increasing the iron content of the diet also led to changes in intestinal bacteria diversity and composition after colitis was induced with DSS

Investigation of faecal volatile organic compounds as biomarkers for the diagnosis of necrotising enterocolitis

Necrotising enterocolitis (NEC) is the most prevalent and harmful illness in the neonatal intensive care unit. It primarily affects premature babies, with higher incidence in low birthweight patients. NEC usually occurs in the early days of life and may develop rapidly. Its diagnosis is based on medical observation because no early diagnostic tool is currently available. Over the last two decades, developments in analytical chemistry have allowed scientists to perform untargeted investigation of biological samples. Biomarkers are being sought, for a range of disorders, by investigating volatile organic compounds (VOCs) in bio-fluids. For the analysis of gas samples, solid phase micro-extraction (SPME) is a suitable technique to preconcentrate volatile compounds prior to analysis using devices such as gas chromatography – mass spectrometry (GC–MS). Recently, much attention has been directed towards the development of sensors and electronic noses to be used as diagnostic tools in hospitals, as they are generally more compact than a GC-MS and do not require specialised personnel. The work presented here is based on the hypothesis that faeces from patients suffering from necrotising enterocolitis show a specific pattern of volatile organic compounds in the days prior to diagnosis when compared with faeces from healthy patients. The objectives of this work were to develop two methods for the analysis of premature faeces using headspace–SPME–GC–MS and headspace – gas chromatography – sensor (HS–GC–Sensor), to analyse samples from healthy premature infants and premature infants affected by NEC using both instruments and to analyse the data collected. Methods were developed individually for each analytical technique. Two pipelines were applied for mass spectrometric data analysis while classification models were exclusively built using sensor data. Results obtained from HS–SPME–GC–MS data showed that the age at sampling had an influence on the number of compounds identified and on their intensities or relative abundance. Heptanal, 2-E-pentenal, hexanal and 2-methylbutanoic acid were identified as relevant compounds. Classifiers were built at days 1 to 6 prior to diagnosis. Accuracy, sensitivity and specificity of up to 74%, 62% and 79%, respectively, were obtained one day prior to diagnosis based on mass spectrometric data, while accuracy, sensitivity and specificity of 100% were obtained based on sensor data at two days prior to diagnosis. Therefore, classification of samples based on headspace analysis of faeces might have potential for the early diagnosis of necrotising enterocolitis

A Symbiotic Supramolecular Approach to the Design of Novel Amphiphiles with Antibacterial Properties Against MSRA

Herein, we identify Supramolecular Self-associating Amphiphiles (SSAs) as a novel class of antibacterials with activity towards Methicillin-resistant Staphylococcus aureus. Structure-activity relationships have been identified in the solid, solution and gas phases. Finally, we show that when supplied in combination, SSAs exhibit increased antibacterial efficacy against these clinically relevant microbes

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p&lt;0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p&lt;0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

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

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

Recurrent SARS-CoV-2 mutations in immunodeficient patients

Long-term severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in immunodeficient patients are an important source of variation for the virus but are understudied. Many case studies have been published which describe one or a small number of long-term infected individuals but no study has combined these sequences into a cohesive dataset. This work aims to rectify this and study the genomics of this patient group through a combination of literature searches as well as identifying new case series directly from the COVID-19 Genomics UK (COG-UK) dataset. The spike gene receptor-binding domain and N-terminal domain (NTD) were identified as mutation hotspots. Numerous mutations associated with variants of concern were observed to emerge recurrently. Additionally a mutation in the envelope gene, T30I was determined to be the second most frequent recurrently occurring mutation arising in persistent infections. A high proportion of recurrent mutations in immunodeficient individuals are associated with ACE2 affinity, immune escape, or viral packaging optimisation.There is an apparent selective pressure for mutations that aid cell–cell transmission within the host or persistence which are often different from mutations that aid inter-host transmission, although the fact that multiple recurrent de novo mutations are considered defining for variants of concern strongly indicates that this potential source of novel variants should not be discounted. © The Author(s) 2022. Published by Oxford University Press

Genomic reconstruction of the SARS-CoV-2 epidemic in England.

The evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus leads to new variants that warrant timely epidemiological characterization. Here we use the dense genomic surveillance data generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of subepidemics that peaked in early autumn 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. The Alpha variant grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed the Alpha variant and eliminated nearly all other lineages in early 2021. Yet a series of variants (most of which contained the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. However, by accounting for sustained introductions, we found that the transmissibility of these variants is unlikely to have exceeded the transmissibility of the Alpha variant. Finally, B.1.617.2/Delta was repeatedly introduced in England and grew rapidly in early summer 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on 26 June 2021