Respiratory infectious diseases are mainly caused by viruses or bacteria that often interact with one another. Although their presence is a prerequisite for subsequent infections, viruses and bacteria may be present in the nasopharynx without causing any respiratory symptoms. The upper respiratory tract hosts a vast range of commensals and potential pathogenic bacteria, which form a complex microbial community. This community is assumed to be constantly subject to synergistic and competitive interspecies interactions. Disturbances in the equilibrium, for instance due to the acquisition of new bacteria or viruses, may lead to overgrowth and invasion. A better understanding of the dynamics between commensals and pathogens in the upper respiratory tract may provide better insight into the pathogenesis of respiratory diseases. Here we review the current knowledge regarding specific bacterial–bacterial and viral–bacterial interactions that occur in the upper respiratory niche, and discuss mechanisms by which these interactions might be mediated. Finally, we propose a theoretical model to summarize and illustrate these mechanisms.

There are 91 known capsular serotypes of Streptococcus pneumoniae. The nasopharyngeal carriage prevalence of particular serotypes is relatively stable worldwide, but the host and bacterial factors that maintain these patterns are poorly understood. Given the possibility of serotype replacement following vaccination against seven clinically important serotypes, it is increasingly important to understand these factors. We hypothesized that the biochemical structure of the capsular polysaccharides could influence the degree of encapsulation of different serotypes, their susceptibility to killing by neutrophils, and ultimately their success during nasopharyngeal carriage. We sought to measure biological differences among capsular serotypes that may account for epidemiological patterns. Using an in vitro assay with both isogenic capsule-switch variants and clinical carriage isolates, we found an association between increased carriage prevalence and resistance to non-opsonic neutrophil-mediated killing, and serotypes that were resistant to neutrophil-mediated killing tended to be more heavily encapsulated, as determined by FITC-dextran exclusion. Next, we identified a link between polysaccharide structure and carriage prevalence. Significantly, non-vaccine serotypes that have become common in vaccinated populations tend to be those with fewer carbons per repeat unit and low energy expended per repeat unit, suggesting a novel biological principle to explain patterns of serotype replacement. More prevalent serotypes are more heavily encapsulated and more resistant to neutrophil-mediated killing, and these phenotypes are associated with the structure of the capsular polysaccharide, suggesting a direct relationship between polysaccharide biochemistry and the success of a serotype during nasopharyngeal carriage and potentially providing a method for predicting serotype replacement. Streptococcus pneumoniae, or pneumococcus, is an important pathogen worldwide and causes a wide range of diseases, mostly in young children and the elderly. There are 91 serotypes of pneumococcus, each of which produces a unique polysaccharide, called the capsule, that attaches to the bacterial surface and prevents it from being cleared by the host. The serotypes differ greatly in their prevalence in the human population. There is currently a vaccine, effective in infancy, which targets seven clinically important serotypes, but several types not covered by the vaccine are beginning to increase in carriage frequency. As a result, it is critical to understand why some serotypes are frequently carried in the human population while others are not. In this study, we find that the high-prevalence serotypes tend to be more heavily encapsulated and more resistant to killing by neutrophils. Significantly, we find that the biochemical properties of the different polysaccharides can be used to predict their carriage frequency both before and after introduction of the vaccine. These results provide a biologically plausible explanation for differences in prevalence between serotypes.

Acquired immunity toStreptococcus pneumoniae(pneumococcus) has long been assumed to depend on the presence of anticapsular antibodies. We found, however, that colonization with live pneumococci of serotypes 6B, 7F, or 14 protected mice against recolonization by any of the serotypes and that protection from acquisition of a heterologous or homologous strain did not depend on anticapsular antibody. Further, intranasal immunization by live pneumococcal colonization or by a killed, nonencapsulated whole-cell vaccine protected antibody-deficient mice against colonization, suggesting independence of antibodies to any pneumococcal antigens. Protection by intranasal immunization with whole-cell vaccine was completely abrogated in T cell-deficient mice, and in mice that were congenitally deficient in CD4⁺T cells or depleted of these cells at the time of challenge. In contrast, mice congenitally deficient in, or depleted of, CD8⁺T cells were fully protected. Protection in this model was observed beyond 2 months after immunization, arguing against innate or nonspecific immune mechanisms. Thus, we find that immunity to pneumococcal colonization can be induced in the absence of antibody, independent of the capsular type, and this protection requires the presence of CD4⁺T cells at the time of challenge.

Bacterial pneumonia is a major cause of morbidity and mortality in elderly. We hypothesize that dysbiosis between regular residents of the upper respiratory tract (URT) microbiome, that is balance between commensals and potential pathogens, is involved in pathogen overgrowth and consequently disease. We compared oropharyngeal microbiota of elderly pneumonia patients (n=100) with healthy elderly (n=91) by 16S-rRNA-based sequencing and verified our findings in young adult pneumonia patients (n=27) and young healthy adults (n=187). Microbiota profiles differed significantly between elderly pneumonia patients and healthy elderly (PERMANOVA, P<0.0005). Highly similar differences were observed between microbiota profiles of young adult pneumonia patients and their healthy controls. Clustering resulted in 11 (sub)clusters including 95% (386/405) of samples. We observed three microbiota profiles strongly associated with pneumonia (P<0.05) and either dominated by lactobacilli (n=11), Rothia (n=51) or Streptococcus (pseudo)pneumoniae (n=42). In contrast, three other microbiota clusters (in total n=183) were correlated with health (P<0.05) and were all characterized by more diverse profiles containing higher abundances of especially Prevotella melaninogenica, Veillonella and Leptotrichia. For the remaining clusters (n=99), the association with health or disease was less clear. A decision tree model based on the relative abundance of five bacterial community members in URT microbiota showed high specificity of 95% and sensitivity of 84% (89% and 73%, respectively, after cross-validation) for differentiating pneumonia patients from healthy individuals. These results suggest that pneumonia in elderly and young adults is associated with dysbiosis of the URT microbiome with bacterial overgrowth of single species and absence of distinct anaerobic bacteria. Whether the observed microbiome changes are a cause or a consequence of the development of pneumonia or merely coincide with disease status remains a question for future research.

A diverse collection of methicillin-resistant Staphylococcus aureus (MRSA) isolates resistant to tetracycline was screened by PCR for the presence of the resistance determinants tetK, tetL, tetM or tetO. Twenty-four of 66 isolates had tetM alone, 21 had tetK alone and 21 had both tetK and tetM (tetKM). All isolates were tetL- and tetO-negative. MICs of tetracycline, doxycycline and minocycline were evaluated for all isolates with or without preincubation in the presence of subinhibitory concentrations of tetracycline or minocycline. All isolates with one or more tetracycline resistance determinants were resistant to tetracycline 8 mg/L without induction of resistance. Some MRSA isolates of each of these three genotypes showed an unexpected lack of resistance to tetracyclines when the disc diffusion or agar dilution method was applied to uninduced cells. Resistance to tetracycline and doxycycline was greater (two- to four-fold) in tetK cells preincubated with tetracycline (tetK MRSA isolates were susceptible to minocycline ≤0.25 mg/L under all conditions tested). For isolates with tetM alone, preincubation with tetracycline or minocycline gave up to a four-fold increase in the level of resistance to doxycycline and minocycline. Induction of doxycycline and minocycline resistance was clearly observed for tetKM isolates when cells were preincubated with minocycline. This study suggests that, despite the results of susceptibility testing, all tetracycline-resistant S. aureus isolates should be treated as resistant to doxycycline, and all tetM-positive isolates should be treated as resistant to all tetracyclines. A double disc diffusion method has been developed to identify inducible resistance to minocycline and to distinguish between tetK, tetM and tetKM isolates.

Accurate analyses of microbiota composition of low-density communities (10³–10⁴ bacteria/sample) can be challenging. Background DNA from chemicals and consumables, extraction biases as well as differences in PCR efficiency can significantly interfere with microbiota assessment. This study was aiming to establish protocols for accurate microbiota analysis at low microbial density. To examine possible effects of bacterial density on microbiota analyses we compared microbiota profiles of serial diluted saliva and low (nares, nasopharynx) and high-density (oropharynx) upper airway communities in four healthy individuals. DNA was extracted with four different extraction methods (Epicentre Masterpure, Qiagen DNeasy, Mobio Powersoil and a phenol bead-beating protocol combined with Agowa-Mag-mini). Bacterial DNA recovery was analysed by 16S qPCR and microbiota profiles through GS-FLX-Titanium-Sequencing of 16S rRNA gene amplicons spanning the V5–V7 regions. Lower template concentrations significantly impacted microbiota profiling results. With higher dilutions, low abundant species were overrepresented. In samples of <10⁵ bacteria per ml, e.g. DNA <1 pg/µl, microbiota profiling deviated from the original sample and other dilutions showing a significant increase in the taxa Proteobacteria and decrease in Bacteroidetes. In similar low density samples, DNA extraction method determined if DNA levels were below or above 1 pg/µl and, together with lysis preferences per method, had profound impact on microbiota analyses in both relative abundance as well as representation of species. This study aimed to interpret microbiota analyses of low-density communities. Bacterial density seemed to interfere with microbiota analyses at < than 10⁶ bacteria per ml or DNA <1 pg/µl. We therefore recommend this threshold for working with low density materials. This study underlines that bias reduction is crucial for adequate profiling of especially low-density bacterial communities.