Characterising virulence factors from pathogenic bacteria using fluorescent reporters

Protein translocation systems are invaluable to pathogenic bacteria, facilitating the display of virulence factors on their surface or their release into the extracellular environment. Some protein export systems are ubiquitous and essential to cell survival whereas others are horizontally acquired on prophages or pathogenicity islands (PAI), in many cases providing the bacterium with pathogenic advantages. For the majority of the known protein export systems, their structure, function and secreted substrates have been characterised, yet some proteins have been identified that are secreted via unknown mechanisms. Enterohaemorrhagic Escherichia coli (EHEC) O157:H7 is an important cause of human foodborne disease worldwide. The pathogenesis of this bacterium is mainly attributed to the secretion of toxins and the presence of a Type III Secretion System (T3SS). The T3SS can translocate bacterial proteins, known as effectors, into the host cell which mediate an effect culminating in the formation of a characteristic attaching and effacing (A/E) lesion. This system is encoded on a horizontally acquired PAI termed the locus of enterocyte effacement (LEE). The LEE not only encodes the T3SS apparatus but also several effectors secreted by the system and transcription factors which regulate its expression. However, it was recently found that T3SS not only secretes LEE encoded effectors but can also secrete proteins encoded on other prophages present in the EHEC genome. Characterisation of these non-LEE encoded effectors is ongoing and this study investigates the expression, regulation and function of non-LEE encoded effector H1 (NleH1) and H2 (NleH2). NleH1 and NleH2 are secreted by the T3SS but are encoded on different prophages. This study demonstrates that expression of NleH1 and NleH2 is induced in the same in vitro conditions which stimulate the expression of the LEE but is diminished upon initial host cell contact in vitro. Transcription of nleH1 and nleH2 is dependant upon factors specific to E. coli O157:H7 and these factors are regulated by LEE encoded regulators Ler and GrlA, as they have a positive effect on nleH transcription. NleH1 and H2 are predicted serine/threonine protein kinases and are able to autophosphorylate. Yeast two hybrid screening and 2D differential gel electrophoresis did not elucidate a eukaryotic protein binding partner of NleH1 or NleH2. Transfection assays show that they do not have a significant effect upon NF-κB activation in vitro. Determining the expression, regulation and function of non-LEE encoded effectors contributes towards further understanding of how this pathogen causes disease. Streptococcus pneumoniae, also known as the pneumococcus, is another globally important human pathogen. It is a very diverse pathogen, with over 90 capsular serotypes and is naturally competent for DNA uptake. Pneumococcal pathogenesis is facilitated by the production of a pore-forming toxin, pneumolysin. Pneumolysin’s activities in pneumococcal pathogenesis extend beyond its cytolytic function as it can also activate the complement pathway and modulate the host cytoskeleton. Pneumolysin is a member of a conserved family of toxins known as the cholesterol dependant cytolysins but differs due to the lack of a secretion signal peptide within its sequence. This indicates that it is not secreted from the bacterium however it has been reported that some strains can release pneumolysin in a cell lysis-independent manner. Additional to this, pneumolysin can also localise to the cell wall, and this localisation is not strain dependent. This study characterised codon-optimised N-terminally labelled pneumolysin constructs and applied them to assess the localisation of pneumolysin. In addition, the importance of autolysin and genes which are co-transcribed with Ply upon the localisation/secretion of pneumolysin was investigated by construction of a pneumococcal strain carrying an autolysin-pneumolysin fusion which naturally occurs in equine strains. These genes were not required for the translocation of pneumolysin or its association with the cell wall. Growth of this strain, and its isogenic parent, in vitro at a low density and low temperature resulted in the pneumolysin being detected in the broth culture. This indicates that pneumolysin can be released from the cell wall and that this action is not dependant upon the genes which were deleted in the mutant. The distribution of pneumolysin on the pneumococcal surface was assessed with immunofluorescence, and LumioTM substrate fluorescence, microscopy and found to have a general distribution. As a contribution to future pneumococcal research, codon-optimised fluorescent protein reagents were developed and can be used as reporters for gene expression and protein localisation

Dataset of Escherichia coli O157 : H7 genes enriched in adherence to spinach root tissue

A high-throughput positive-selection approach was taken to generate a dataset of Shigatoxigenic Escherichia coli (STEC) O157:H7 genes enriched in adherence to plant tissue. The approach generates a differential dataset based on BAC clones enriched in the output, after adherence, compared to the inoculum used as the input. A BAC clone library derived from STEC isolate 'Sakai' was used since this isolate is associated with a very large-scale outbreak of human disease from consumption of contaminated fresh produce; white radish sprouts. Spinach was used for the screen since it is associated with STEC outbreaks, and the roots provide a suitable site for bacterial colonisation. Four successive of rounds of Sakai BAC clone selection and amplification were applied for spinach root adherence, in parallel to a non-plant control. Genomic DNA was obtained from a total of 7.17 x 108 cfu/ml of bacteria from the plant treatment and 1.13 x 109 cfu/ml of bacteria from the no-plant control. Relative gene abundance of the output compared to the input pools was obtained using an established E. coli DNA microarray chip for STEC. The dataset enables screening for genes enriched under the treatment condition and informs on genes that may play a role in plant-microbe interactions

Escherichia coli Common Pilus (ECP) Targets Arabinosyl Residues in Plant Cell Walls to Mediate Adhesion to Fresh Produce Plants

International audienceBackground: Bacterial fimbriae mediate binding to host tissue through specific interactions. Results: ECP interacts with arabinosyl residues in pectin and other plant cell wall components. Conclusion: ECP-arabinan interactions facilitate binding of E. coli to plant hosts. Significance: The prevalence of arabinan targets in produce plants together with ECP expression may explain the association of pathogenic bacteria in edible plants

Network memory in the movement of hospital patients carrying antimicrobial-resistant bacteria

Hospitals constitute highly interconnected systems that bring into contact an abundance of infectious pathogens and susceptible individuals, thus making infection outbreaks both common and challenging. In recent years, there has been a sharp incidence of antimicrobial-resistance amongst healthcare-associated infections, a situation now considered endemic in many countries. Here we present network-based analyses of a data set capturing the movement of patients harbouring drug-resistant bacteria across three large London hospitals. We show that there are substantial memory effects in the movement of hospital patients colonised with drug-resistant bacteria. Such memory effects break first-order Markovian transitive assumptions and substantially alter the conclusions from the analysis, specifically on node rankings and the evolution of diffusive processes. We capture variable length memory effects by constructing a lumped-state memory network, which we then use to identify overlapping communities of wards. We find that these communities of wards display a quasi-hierarchical structure at different levels of granularity which is consistent with different aspects of patient flows related to hospital locations and medical specialties

Informing antimicrobial management in the context of COVID-19:Understanding the longitudinal dynamics of C-reactive protein and procalcitonin

Background: To characterise the longitudinal dynamics of C-reactive protein (CRP) and Procalcitonin (PCT) in a cohort of hospitalised patients with COVID-19 and support antimicrobial decision-making. Methods: Longitudinal CRP and PCT concentrations and trajectories of 237 hospitalised patients with COVID-19 were modelled. The dataset comprised of 2,021 data points for CRP and 284 points for PCT. Pairwise comparisons were performed between: (i) those with or without significant bacterial growth from cultures, and (ii) those who survived or died in hospital. Results: CRP concentrations were higher over time in COVID-19 patients with positive microbiology (day 9: 236 vs 123 mg/L, p < 0.0001) and in those who died (day 8: 226 vs 152 mg/L, p < 0.0001) but only after day 7 of COVID-related symptom onset. Failure for CRP to reduce in the first week of hospital admission was associated with significantly higher odds of death. PCT concentrations were higher in patients with COVID-19 and positive microbiology or in those who died, although these differences were not statistically significant. Conclusions: Both the absolute CRP concentration and the trajectory during the first week of hospital admission are important factors predicting microbiology culture positivity and outcome in patients hospitalised with COVID-19. Further work is needed to describe the role of PCT for co-infection. Understanding relationships of these biomarkers can support development of risk models and inform optimal antimicrobial strategies

The role of l-arabinose metabolism for <i>Escherichia coli</i> O157:H7 in edible plants

International audienceArabinose is a major plant aldopentose in the form of arabinans complexed in cell wall polysaccharides or glycoproteins (AGP), but comparatively rare as a monosaccharide. l -arabinose is an important bacterial metabolite, accessed by pectolytic micro-organisms such as Pectobacterium atrosepticum via pectin and hemicellulose degrading enzymes. However, not all plant-associated microbes encode cell-wall-degrading enzymes, yet can metabolize l -arabinose, raising questions about their use of and access to the glycan in plants. Therefore, we examined l -arabinose metabolism in the food-borne pathogen Escherichia coli O157:H7 (isolate Sakai) during its colonization of plants. l -arabinose metabolism ( araBA ) and transport ( araF ) genes were activated at 18 °C in vitro by l -arabinose and expressed over prolonged periods in planta . Although deletion of araBAD did not impact the colonization ability of E. coli O157:H7 (Sakai) on spinach and lettuce plants (both associated with STEC outbreaks), araA was induced on exposure to spinach cell-wall polysaccharides. Furthermore, debranched and arabinan oligosaccharides induced ara metabolism gene expression in vitro , and stimulated modest proliferation, while immobilized pectin did not. Thus, E. coli O157:H7 (Sakai) can utilize pectin/AGP-derived l -arabinose as a metabolite. Furthermore, it differs fundamentally in ara gene organization, transport and regulation from the related pectinolytic species P. atrosepticum , reflective of distinct plant-associated lifestyles

riboSeed:leveraging prokaryotic genomic architecture to assemble across ribosomal regions

The vast majority of bacterial genome sequencing has been performed using Illumina short reads. Because of the inherent difficulty of resolving repeated regions with short reads alone, only similar to 10% of sequencing projects have resulted in a closed genome. The most common repeated regions are those coding for ribosomal operons (rDNAs), which occur in a bacterial genome between 1 and 15 times, and are typically used as sequence markers to classify and identify bacteria. Here, we exploit the genomic context in which rDNAs occur across taxa to improve assembly of these regions relative to de novo sequencing by using the conserved nature of rDNAs across taxa and the uniqueness of their flanking regions within a genome. We describe a method to construct targeted pseudocontigs generated by iteratively assembling reads that map to a reference genome's rDNAs. These pseudocontigs are then used to more accurately assemble the newly sequenced chromosome. We show that this method, implemented as riboSeed, correctly bridges across adjacent contigs in bacterial genome assembly and, when used in conjunction with other genome polishing tools, can assist in closure of a genome

Prediction of hospital-onset COVID-19 infections using dynamic networks of patient contact: an international retrospective cohort study.

BackgroundReal-time prediction is key to prevention and control of infections associated with health-care settings. Contacts enable spread of many infections, yet most risk prediction frameworks fail to account for their dynamics. We developed, tested, and internationally validated a real-time machine-learning framework, incorporating dynamic patient-contact networks to predict hospital-onset COVID-19 infections (HOCIs) at the individual level.MethodsWe report an international retrospective cohort study of our framework, which extracted patient-contact networks from routine hospital data and combined network-derived variables with clinical and contextual information to predict individual infection risk. We trained and tested the framework on HOCIs using the data from 51 157 hospital inpatients admitted to a UK National Health Service hospital group (Imperial College Healthcare NHS Trust) between April 1, 2020, and April 1, 2021, intersecting the first two COVID-19 surges. We validated the framework using data from a Swiss hospital group (Department of Rehabilitation, Geneva University Hospitals) during a COVID-19 surge (from March 1 to May 31, 2020; 40 057 inpatients) and from the same UK group after COVID-19 surges (from April 2 to Aug 13, 2021; 43 375 inpatients). All inpatients with a bed allocation during the study periods were included in the computation of network-derived and contextual variables. In predicting patient-level HOCI risk, only inpatients spending 3 or more days in hospital during the study period were examined for HOCI acquisition risk.FindingsThe framework was highly predictive across test data with all variable types (area under the curve [AUC]-receiver operating characteristic curve [ROC] 0·89 [95% CI 0·88-0·90]) and similarly predictive using only contact-network variables (0·88 [0·86-0·90]). Prediction was reduced when using only hospital contextual (AUC-ROC 0·82 [95% CI 0·80-0·84]) or patient clinical (0·64 [0·62-0·66]) variables. A model with only three variables (ie, network closeness, direct contacts with infectious patients [network derived], and hospital COVID-19 prevalence [hospital contextual]) achieved AUC-ROC 0·85 (95% CI 0·82-0·88). Incorporating contact-network variables improved performance across both validation datasets (AUC-ROC in the Geneva dataset increased from 0·84 [95% CI 0·82-0·86] to 0·88 [0·86-0·90]; AUC-ROC in the UK post-surge dataset increased from 0·49 [0·46-0·52] to 0·68 [0·64-0·70]).InterpretationDynamic contact networks are robust predictors of individual patient risk of HOCIs. Their integration in clinical care could enhance individualised infection prevention and early diagnosis of COVID-19 and other nosocomial infections.FundingMedical Research Foundation, WHO, Engineering and Physical Sciences Research Council, National Institute for Health Research (NIHR), Swiss National Science Foundation, and German Research Foundation