Clinical Streptococcus pneumoniae isolates induce differing CXCL8 responses from human nasopharyngeal epithelial cells which are reduced by liposomes

BACKGROUND: Streptococcus pneumoniae causes several human diseases, including pneumonia and meningitis, in which pathology is associated with an excessive inflammatory response. A major inducer of this response is the cholesterol dependent pneumococcal toxin, pneumolysin. Here, we measured the amount of inflammatory cytokine CXCL8 (interleukin (IL)-8) by ELISA released by human nasopharyngeal epithelial (Detroit 562) cells as inflammatory response to a 24 h exposure to different pneumococcal strains. RESULTS: We found pneumolysin to be the major factor influencing the CXCL8 response. Cholesterol and sphingomyelin-containing liposomes designed to sequester pneumolysin were highly effective at reducing CXCL8 levels from epithelial cells exposed to different clinical pneumococcal isolates. These liposomes also reduced CXCL8 response from epithelial cells exposed to pneumolysin knock-out mutants of S. pneumoniae indicating that they also reduce the CXCL8-inducing effect of an unidentified pneumococcal virulence factor, in addition to pneumolysin. CONCLUSION: The results indicate the potential of liposomes in attenuating excessive inflammation as a future adjunctive treatment of pneumococcal diseases

Stochastic IMT (insulator-metal-transition) neurons: An interplay of thermal and threshold noise at bifurcation

Artificial neural networks can harness stochasticity in multiple ways to enable a vast class of computationally powerful models. Electronic implementation of such stochastic networks is currently limited to addition of algorithmic noise to digital machines which is inherently inefficient; albeit recent efforts to harness physical noise in devices for stochasticity have shown promise. To succeed in fabricating electronic neuromorphic networks we need experimental evidence of devices with measurable and controllable stochasticity which is complemented with the development of reliable statistical models of such observed stochasticity. Current research literature has sparse evidence of the former and a complete lack of the latter. This motivates the current article where we demonstrate a stochastic neuron using an insulator-metal-transition (IMT) device, based on electrically induced phase-transition, in series with a tunable resistance. We show that an IMT neuron has dynamics similar to a piecewise linear FitzHugh-Nagumo (FHN) neuron and incorporates all characteristics of a spiking neuron in the device phenomena. We experimentally demonstrate spontaneous stochastic spiking along with electrically controllable firing probabilities using Vanadium Dioxide (VO$_2$) based IMT neurons which show a sigmoid-like transfer function. The stochastic spiking is explained by two noise sources - thermal noise and threshold fluctuations, which act as precursors of bifurcation. As such, the IMT neuron is modeled as an Ornstein-Uhlenbeck (OU) process with a fluctuating boundary resulting in transfer curves that closely match experiments. As one of the first comprehensive studies of a stochastic neuron hardware and its statistical properties, this article would enable efficient implementation of a large class of neuro-mimetic networks and algorithms.Comment: Added sectioning, Figure 6, Table 1, and Section II.E Updated abstract, discussion and corrected typo

Nasopharyngeal Microbiota in Infants With Acute Otitis Media

Background. Interspecies interactions of the nasopharyngeal microbiota are likely to be involved in the pathogenesis of acute otitis media (AOM). Capturing the breadth of microbial interactions requires a detailed description of the microbiota during health and AOM. Methods. The nasopharyngeal microbiota of 163 infants with (n = 153) or without (n = 10) AOM was characterized using nasopharyngeal swabs and multiplexed pyrosequencing of 16S rRNA. Nasopharyngeal swab specimens were collected during 4 winter seasons from 2004 through 2010 for infants with AOM and during 2010 for controls. Results. Fifty-eight bacterial families were identified, of which Moraxellaceae, Streptococcaceae, and Pasteurellaceae were the most frequent. Commensal families were less prevalent in infants with AOM than in controls. In infants with AOM, prior exposure to antimicrobials and administration of the heptavalent conjugated pneumococcal polysaccharide vaccine (PCV7) were also associated with reduced prevalence of distinct commensal families (Streptococcaceae and Corynebacteriaceae). In addition, antimicrobial exposure increased the prevalence of Enterobacteriaceae and the abundance of Pasteurellaceae. Other factors, such as age, sex, day care, and a history of recurrent AOM, did not influence the microbiota. Conclusions. Infants' nasopharyngeal microbiota undergoes significant changes during AOM and after exposure to antimicrobials and PCV7, which is mainly attributable to reduced prevalence of commensal bacterial familie

Transmission Dynamics of Extended-Spectrum β-lactamase-Producing Enterobacteriaceae in the Tertiary Care Hospital and the Household Setting

Transmission of extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae in households outweighs nosocomial dissemination in the non-outbreak setting. Importation of ESBL producers into the hospitals is as frequent as transmission during hospital stay. ESBL-Klebsiella pneumoniae might be more efficiently transmitted within the hospital than ESBL-Escherichia col

Peptide Ligands of AmiA, AliA, and AliB Proteins Determine Pneumococcal Phenotype

The Ami-AliA/AliB oligopeptide permease of Streptococcus pneumoniae has been suggested to play a role in environmental sensing and colonisation of the nasopharynx by this human bacterial pathogen by binding peptides derived from bacterial neighbours of other species in the microbiota. Here, we investigated the effects of the peptide ligands of the permease’s substrate binding proteins AmiA, AliA, and AliB on pneumococcal phenotype. AmiA and AliA ligands reduced pneumococcal growth, increased biofilm production and reduced capsule size. In contrast, AliB ligand increased growth and greatly increased bacterial chain length. A decrease in transformation rate was observed in response to all three peptides. Changes in protein expression were also observed, particularly those associated with metabolism and cell wall synthesis. Understanding interspecies bacterial communication and its effect on development of colonising versus invasive phenotypes has the potential to reveal new targets to tackle and prevent pneumococcal infections

Multiple Colonization with S. pneumoniae before and after Introduction of the Seven-Valent Conjugated Pneumococcal Polysaccharide Vaccine

Simultaneous carriage of more than one strain of Streptococcus pneumoniae promotes horizontal gene transfer events and may lead to capsule switch and acquisition of antibiotic resistance. We studied the epidemiology of cocolonization with S. pneumoniae before and after introduction of the seven-valent conjugated pneumococcal vaccine (PCV7)

Identification of regulatory variants associated with genetic susceptibility to meningococcal disease.

Non-coding genetic variants play an important role in driving susceptibility to complex diseases but their characterization remains challenging. Here, we employed a novel approach to interrogate the genetic risk of such polymorphisms in a more systematic way by targeting specific regulatory regions relevant for the phenotype studied. We applied this method to meningococcal disease susceptibility, using the DNA binding pattern of RELA - a NF-kB subunit, master regulator of the response to infection - under bacterial stimuli in nasopharyngeal epithelial cells. We designed a custom panel to cover these RELA binding sites and used it for targeted sequencing in cases and controls. Variant calling and association analysis were performed followed by validation of candidate polymorphisms by genotyping in three independent cohorts. We identified two new polymorphisms, rs4823231 and rs11913168, showing signs of association with meningococcal disease susceptibility. In addition, using our genomic data as well as publicly available resources, we found evidences for these SNPs to have potential regulatory effects on ATXN10 and LIF genes respectively. The variants and related candidate genes are relevant for infectious diseases and may have important contribution for meningococcal disease pathology. Finally, we described a novel genetic association approach that could be applied to other phenotypes

Plasma lipid profiles discriminate bacterial from viral infection in febrile children

Fever is the most common reason that children present to Emergency Departments. Clinical signs and symptoms suggestive of bacterial infection are often non-specific, and there is no definitive test for the accurate diagnosis of infection. The 'omics' approaches to identifying biomarkers from the host-response to bacterial infection are promising. In this study, lipidomic analysis was carried out with plasma samples obtained from febrile children with confirmed bacterial infection (n = 20) and confirmed viral infection (n = 20). We show for the first time that bacterial and viral infection produces distinct profile in the host lipidome. Some species of glycerophosphoinositol, sphingomyelin, lysophosphatidylcholine and cholesterol sulfate were higher in the confirmed virus infected group, while some species of fatty acids, glycerophosphocholine, glycerophosphoserine, lactosylceramide and bilirubin were lower in the confirmed virus infected group when compared with confirmed bacterial infected group. A combination of three lipids achieved an area under the receiver operating characteristic (ROC) curve of 0.911 (95% CI 0.81 to 0.98). This pilot study demonstrates the potential of metabolic biomarkers to assist clinicians in distinguishing bacterial from viral infection in febrile children, to facilitate effective clinical management and to the limit inappropriate use of antibiotics

Plasma lipid profiles discriminate bacterial from viral infection in febrile children

Fever is the most common reason that children present to Emergency Departments. Clinical signs and symptoms suggestive of bacterial infection ar

Impact of infection on proteome-wide glycosylation revealed by distinct signatures for bacterial and viral pathogens

Mechanisms of infection and pathogenesis have predominantly been studied based on differential gene or protein expression. Less is known about posttranslational modifications, which are essential for protein functional diversity. We applied an innovative glycoproteomics method to study the systemic proteome-wide glycosylation in response to infection. The protein site-specific glycosylation was characterized in plasma derived from well-defined controls and patients. We found 3862 unique features, of which we identified 463 distinct intact glycopeptides, that could be mapped to more than 30 different proteins. Statistical analyses were used to derive a glycopeptide signature that enabled significant differentiation between patients with a bacterial or viral infection. Furthermore, supported by a machine learning algorithm, we demonstrated the ability to identify the causative pathogens based on the distinctive host blood plasma glycopeptide signatures. These results illustrate that glycoproteomics holds enormous potential as an innovative approach to improve the interpretation of relevant biological changes in response to infection