Interactions between Streptococcus pneumoniae and influenza virus: a mutually beneficial relationship?

Host transcriptomics and machine learning for secondary bacterial infections in patients with COVID-19: a prospective, observational cohort study

BACKGROUND

Viral respiratory tract infections are frequently complicated by secondary bacterial infections. This study aimed to use machine learning to predict the risk of bacterial superinfection in SARS-CoV-2-positive individuals.

METHODS

In this prospective, multicentre, observational cohort study done in nine centres in six countries (Australia, Indonesia, Singapore, Italy, Czechia, and France) blood samples and RNA sequencing were used to develop a robust model of predicting secondary bacterial infections in the respiratory tract of patients with COVID-19. Eligible participants were older than 18 years, had known or suspected COVID-19, and symptoms of a recent respiratory infection. A control cohort of participants without COVID-19 who were older than 18 years and with no infection symptoms was also recruited from one Australian centre. In the pre-analysis phase, data were filtered to include only individuals with complete blood transcriptomics and patient data (ie, age, sex, location, and WHO severity score at the time of sample collection). The dataset was then divided randomly (4:1) into a training set (80%) and a test set (20%). Gene expression data in the training set and control cohort were used for differential expression analysis. Differentially expressed genes, along with WHO severity score, location, age, and sex, were used for feature selection with least absolute shrinkage and selection operator (LASSO) in the training set. For LASSO analysis, samples were excluded if gene expression data were not obtained at study admission, no longitudinal clinical information was available, a bacterial infection at the time of study admission was present, or a fungal infection in the absence of a bacterial infection was detected. LASSO regression was performed using three subsets of predictor variables: patient data alone, gene expression data alone, or a combination of patient data and gene expression data. The accuracy of the resultant models was tested on data from the test set.

FINDINGS

Between March, 2020, and October, 2021, we recruited 536 SARS-CoV-2-positive individuals and between June, 2013, and January, 2020, we recruited 74 participants into the control cohort. After prefiltering analysis and other exclusions, samples from 158 individuals were analysed in the training set and 47 in the test set. The expression of seven host genes (DAPP1, CST3, FGL2, GCH1, CIITA, UPP1, and RN7SL1) in the blood at the time of study admission was identified by LASSO as predictive of the risk of developing a secondary bacterial infection of the respiratory tract more than 24 h after study admission. Specifically, the expression of these genes in combination with a patient's WHO severity score at the time of study enrolment resulted in an area under the curve of 0·98 (95% CI 0·89-1·00), a true positive rate (sensitivity) of 1·00 (95% CI 1·00-1·00), and a true negative rate (specificity) of 0·94 (95% CI 0·89-1·00) in the test cohort. The combination of patient data and host transcriptomics at hospital admission identified all seven individuals in the training and test sets who developed a bacterial infection of the respiratory tract 5-9 days after hospital admission.

INTERPRETATION

These data raise the possibility that host transcriptomics at the time of clinical presentation, together with machine learning, can forward predict the risk of secondary bacterial infections and allow for the more targeted use of antibiotics in viral infection.

FUNDING

Snow Medical Research Foundation, the National Health and Medical Research Council, the Jack Ma Foundation, the Helmholtz-Association, the A2 Milk Company, National Institute of Allergy and Infectious Disease, and the Fondazione AIRC Associazione Italiana per la Ricerca contro il Cancro.

What Have We Learned by Resurrecting the 1918 Influenza Virus?

The 1918 Spanish influenza pandemic was one of the deadliest infectious disease events in recorded history, resulting in approximately 50-100 million deaths worldwide. The origins of the 1918 virus and the molecular basis for its exceptional virulence remained a mystery for much of the 20th century because the pandemic predated virologic techniques to isolate, passage, and store influenza viruses. In the late 1990s, overlapping fragments of influenza viral RNA preserved in the tissues of several 1918 victims were amplified and sequenced. The use of influenza reverse genetics then permitted scientists to reconstruct the 1918 virus entirely from cloned complementary DNA, leading to new insights into the origin of the virus and its pathogenicity. Here, we discuss some of the advances made by resurrection of the 1918 virus, including the rise of innovative molecular research, which is a topic in the dual use debate.

A Review on the Nasal Microbiome and Various Disease Conditions for Newer Approaches to Treatments

Introduction: Commensal bacteria have always played a significant role in the maintenance of health and disease but are being unravelled only recently. Studies suggest that the nasal microbiome has a significant role in the development of various disease conditions. Search engines were used for searching articles having a nasal microbiome and disease correlation. In olfactory dysfunction, dysbiosis of the microbiome may have a significant role to play in the pathogenesis. The nasal microbiome influences the phenotype of CRS and is also capable of modulating the immune response and plays a role in polyp formation. Microbiome dysbiosis has a pivotal role in the development of Allergic Rhinitis; but, yet known how is this role played. The nasal microbiome has a close association with the severity and phenotype of asthma. They contribute significantly to the onset, severity, and development of asthma. The nasal microbiome has a significant impact on the immunity and protection of its host. The nasal microbiome has been a stimulus in the development of Otitis Media and its manifestations. Studies suggest that the resident nasal microbiome is responsible for the initiation of neurodegenerative diseases like Parkinson's Disease.Materials and Methods: Literature search from PubMed, Medline, and Google with the Mesh terms: nasal microbiome AND diseases. Conclusion: With increasing evidence on the role of the nasal microbiome on various diseases, it would be interesting to see how this microbiome can be modulated by pro/pre/post biotics to prevent a disease or the severity of illness.

Influenza A virus modulation of Streptococcus pneumoniae infection using ex vivo transcriptomics in a human primary lung epithelial cell model reveals differential host glycoconjugate uptake and metabolism

Background

Streptococcus pneumoniae (Spn) is typically an asymptomatic colonizer of the nasopharynx but it also causes pneumonia and disseminated disease affecting various host anatomical sites. Transition from colonization to invasive disease is not well understood. Studies have shown that such a transition can occur as result of influenza A virus coinfection.

Methods

We investigated the pneumococcal (serotype 19F, strain EF3030) and host transcriptomes with and without influenza A virus (A/California/07 2009 pH1N1) infection at this transition. This was done using primary, differentiated Human Bronchial Epithelial Cells (nHBEC) in a transwell monolayer model at an Air-Liquid Interface (ALI), with multispecies deep RNA-seq.

Results

Distinct pneumococcal gene expression profiles were observed in the presence and absence of influenza. Influenza coinfection allowed for significantly greater pneumococcal growth and triggered the differential expression of bacterial genes corresponding to multiple metabolic pathways; in totality suggesting a fundamentally altered bacterial metabolic state and greater nutrient availability when coinfecting with influenza. Surprisingly, nHBEC transcriptomes were only modestly perturbed by infection with EF3030 alone in comparison to that resulting from Influenza A infection or coinfection, which had drastic alterations in thousands of genes. Influenza infected host transcriptomes suggest significant loss of ciliary function in host nHBEC cells.

Conclusions

Influenza A virus infection of nHBEC promotes pneumococcal infection. One reason for this is an altered metabolic state by the bacterium, presumably due to host components made available as result of viral infection. Influenza infection had a far greater impact on the host response than did bacterial infection alone, and this included down regulation of genes involved in expressing cilia. We conclude that influenza infection promotes a pneumococcal metabolic shift allowing for transition from colonization to disseminated disease.

The Two-Component System YesMN Promotes Pneumococcal Host-to-Host Transmission and Regulates Genes Involved in Zinc Homeostasis

The ability to sense and respond rapidly to the dynamic environment of the upper respiratory tract (URT) makes Streptococcus pneumoniae (Spn) a highly successful human pathogen. Two-component systems (TCSs) of Spn sense and respond to multiple signals it encounters allowing Spn to adapt and thrive in various host sites. Spn TCS have been implicated in their ability to promote pneumococcal colonization of the URT and virulence. As the disease state can be a dead-end for a pathogen, we considered whether TCS would contribute to pneumococcal transmission. Herein, we determined the role of YesMN, an understudied TCS of Spn, and observe that YesMN contributes toward pneumococcal shedding and transmission but is not essential for colonization. The YesMN regulon includes genes involved in zinc homeostasis and glycan metabolism, which are upregulated during reduced zinc availability in a YesMN-dependent fashion. Thus, we identified the YesMN regulon and a potential molecular signal it senses that lead to the activation of genes involved in zinc homeostasis and glycan metabolism. Furthermore, in contrast to Spn monoinfection, we demonstrate that YesMN is critical for high pneumococcal density in the URT during influenza A virus (IAV) coinfection. We attribute reduced colonization of the yesMN mutant possibly due to increased association with and clearance by the mucus covering the URT epithelial surface. Thus, our results highlight the dynamic interactions that occur between Spn and IAV in the URT, and the role that TCSs play in modulation of these interactions.

Pneumonia in the presentation of Kawasaki disease: The syndrome or a sequence of two diseases?

Two cases of Kawasaki disease (KD) presented as persistent lung consolidation associated with Group A Streptococcus and Influenza A co-infection, which resolved following intravenous immunoglobulin. Thus, pediatricians should consider the diagnosis of KD in the presence of pneumonia that is nonresponsive to antibiotic therapy with prolonged fever and inflammatory reactions.

Oral mitis group streptococci reduce infectivity of influenza A virus via acidification and H2O2 production

Members of the mitis group streptococci are the most abundant inhabitants of the oral cavity and dental plaque. Influenza A virus (IAV), the causative agent of influenza, infects the upper respiratory tract, and co-infection with Streptococcus pneumoniae is a major cause of morbidity during influenza epidemics. S. pneumoniae is a member of mitis group streptococci and shares many features with oral mitis group streptococci. In this study, we investigated the effect of viable Streptococcus oralis, a representative member of oral mitis group, on the infectivity of H1N1 IAV. The infectivity of IAV was measured by a plaque assay using Madin-Darby canine kidney cells. When IAV was incubated in growing culture of S. oralis, the IAV titer decreased in a time- and dose-dependent manner and became less than 100-fold, whereas heat-inactivated S. oralis had no effect. Other oral streptococci such as Streptococcus mutans and Streptococcus salivarius also reduced the viral infectivity to a lesser extent compared to S. oralis and Streptococcus gordonii, another member of the oral mitis group. S. oralis produces hydrogen peroxide (H2O2) at a concentration of 1–2 mM, and its mutant deficient in H2O2 production showed a weaker effect on the inactivation of IAV, suggesting that H2O2 contributes to viral inactivation. The contribution of H2O2 was confirmed by an inhibition assay using catalase, an H2O2-decomposing enzyme. These oral streptococci produce short chain fatty acids (SCFA) such as acetic acid as a by-product of sugar metabolism, and we also found that the inactivation of IAV was dependent on the mildly acidic pH (around pH 5.0) of these streptococcal cultures. Although inactivation of IAV in buffers of pH 5.0 was limited, incubation in the same buffer containing 2 mM H2O2 resulted in marked inactivation of IAV, which was similar to the effect of growing S. oralis culture. Taken together, these results reveal that viable S. oralis can inactivate IAV via the production of SCFAs and H2O2. This finding also suggests that the combination of mildly acidic pH and H2O2 at low concentrations could be an effective method to inactivate IAV.

The Contribution of Viral Proteins to the Synergy of Influenza and Bacterial Co-Infection

A severe course of acute respiratory disease caused by influenza A virus (IAV) infection is often linked with subsequent bacterial superinfection, which is difficult to cure. Thus, synergistic influenza-bacterial co-infection represents a serious medical problem. The pathogenic changes in the infected host are accelerated as a consequence of IAV infection, reflecting its impact on the host immune response. IAV infection triggers a complex process linked with the blocking of innate and adaptive immune mechanisms required for effective antiviral defense. Such disbalance of the immune system allows for easier initiation of bacterial superinfection. Therefore, many new studies have emerged that aim to explain why viral-bacterial co-infection can lead to severe respiratory disease with possible fatal outcomes. In this review, we discuss the key role of several IAV proteins-namely, PB1-F2, hemagglutinin (HA), neuraminidase (NA), and NS1-known to play a role in modulating the immune defense of the host, which consequently escalates the development of secondary bacterial infection, most often caused by Streptococcus pneumoniae. Understanding the mechanisms leading to pathological disorders caused by bacterial superinfection after the previous viral infection is important for the development of more effective means of prevention; for example, by vaccination or through therapy using antiviral drugs targeted at critical viral proteins.

Time-Dependent Increase in Susceptibility and Severity of Secondary Bacterial Infections During SARS-CoV-2

Secondary bacterial infections can exacerbate SARS-CoV-2 infection, but their prevalence and impact remain poorly understood. Here, we established that a mild to moderate infection with the SARS-CoV-2 USA-WA1/2020 strain increased the risk of pneumococcal (type 2 strain D39) coinfection in a time-dependent, but sex-independent, manner in the transgenic K18-hACE2 mouse model of COVID-19. Bacterial coinfection increased lethality when the bacteria was initiated at 5 or 7 d post-virus infection (pvi) but not at 3 d pvi. Bacterial outgrowth was accompanied by neutrophilia in the groups coinfected at 7 d pvi and reductions in B cells, T cells, IL-6, IL-15, IL-18, and LIF were present in groups coinfected at 5 d pvi. However, viral burden, lung pathology, cytokines, chemokines, and immune cell activation were largely unchanged after bacterial coinfection. Examining surviving animals more than a week after infection resolution suggested that immune cell activation remained high and was exacerbated in the lungs of coinfected animals compared with SARS-CoV-2 infection alone. These data suggest that SARS-CoV-2 increases susceptibility and pathogenicity to bacterial coinfection, and further studies are needed to understand and combat disease associated with bacterial pneumonia in COVID-19 patients.

Time-Dependent Increase in Susceptibility and Severity of Secondary Bacterial Infection during SARS-CoV-2 Infection.. [PMID: 35262077 PMCID: PMC8902874 DOI: 10.1101/2022.02.28.482305]

Secondary bacterial infections can exacerbate SARS-CoV-2 infection, but their prevalence and impact remain poorly understood. Here, we established that a mild to moderate SARS-CoV-2 infection increased the risk of pneumococcal coinfection in a time-dependent, but sex-independent, manner in the transgenic K18-hACE mouse model of COVID-19. Bacterial coinfection was not established at 3 d post-virus, but increased lethality was observed when the bacteria was initiated at 5 or 7 d post-virus infection (pvi). Bacterial outgrowth was accompanied by neutrophilia in the groups coinfected at 7 d pvi and reductions in B cells, T cells, IL-6, IL-15, IL-18, and LIF were present in groups coinfected at 5 d pvi. However, viral burden, lung pathology, cytokines, chemokines, and immune cell activation were largely unchanged after bacterial coinfection. Examining surviving animals more than a week after infection resolution suggested that immune cell activation remained high and was exacerbated in the lungs of coinfected animals compared with SARS-CoV-2 infection alone. These data suggest that SARS-CoV-2 increases susceptibility and pathogenicity to bacterial coinfection, and further studies are needed to understand and combat disease associated with bacterial pneumonia in COVID-19 patients.

Interactions among 17 respiratory pathogens: a cross-sectional study using clinical and community surveillance data

Background

Co-circulating respiratory pathogens can interfere with or promote each other, leading to important effects on disease epidemiology. Estimating the magnitude of pathogen-pathogen interactions from clinical specimens is challenging because sampling from symptomatic individuals can create biased estimates.

Methods

We conducted an observational, cross-sectional study using samples collected by the Seattle Flu Study between 11 November 2018 and 20 August 2021. Samples that tested positive via RT-qPCR for at least one of 17 potential respiratory pathogens were included in this study. Semi-quantitative cycle threshold (Ct) values were used to measure pathogen load. Differences in pathogen load between monoinfected and coinfected samples were assessed using linear regression adjusting for age, season, and recruitment channel.

Results

21,686 samples were positive for at least one potential pathogen. Most prevalent were rhinovirus (33·5%), Streptococcus pneumoniae (SPn, 29·0%), SARS-CoV-2 (13.8%) and influenza A/H1N1 (9·6%). 140 potential pathogen pairs were included for analysis, and 56 (40%) pairs yielded significant Ct differences (p < 0.01) between monoinfected and co-infected samples. We observed no virus-virus pairs showing evidence of significant facilitating interactions, and found significant viral load decrease among 37 of 108 (34%) assessed pairs. Samples positive with SPn and a virus were consistently associated with increased SPn load.

Conclusions

Viral load data can be used to overcome sampling bias in studies of pathogen-pathogen interactions. When applied to respiratory pathogens, we found evidence of viral-SPn facilitation and several examples of viral-viral interference. Multipathogen surveillance is a cost-efficient data collection approach, with added clinical and epidemiological informational value over single-pathogen testing, but requires careful analysis to mitigate selection bias.

Tumor hijacks macrophages and microbiota through extracellular vesicles

The tumor microenvironment (TME) is a biological system with sophisticated constituents. In addition to tumor cells, tumor-associated macrophages (TAMs) and microbiota are also dominant components. The phenotypic and functional changes of TAMs are widely considered to be related to most tumor progressions. The chronic colonization of pathogenic microbes and opportunistic pathogens accounts for the generation and development of tumors. As messengers of cell-to-cell communication, tumor-derived extracellular vesicles (TDEVs) can transfer various malignant factors, regulating physiological and pathological changes in the recipients and affecting TAMs and microbes in the TME. Despite the new insights into tumorigenesis and progress brought by the above factors, the crosstalk among tumor cells, macrophages, and microbiota remain elusive, and few studies have focused on how TDEVs act as an intermediary. We reviewed how tumor cells recruit and domesticate macrophages and microbes through extracellular vehicles and how hijacked macrophages and microbiota interact with tumor-promoting feedback, achieving a reciprocal coexistence under the TME and working together to facilitate tumor progression. It is significant to seek evidence to clarify those specific interactions and reveal therapeutic targets to curb tumor progression and improve prognosis.

Secondary streptococcal infection following influenza

Secondary bacterial infection following influenza A virus (IAV) infection is a major cause of morbidity and mortality during influenza epidemics. Streptococcus pneumoniae has been identified as a predominant pathogen in secondary pneumonia cases that develop following influenza. Although IAV has been shown to enhance susceptibility to the secondary bacterial infection, the underlying mechanism of the viral-bacterial synergy leading to disease progression is complex and remains elusive. In this review, cooperative interactions of viruses and streptococci during co- or secondary infection with IAV are described. IAV infects the upper respiratory tract, therefore, streptococci that inhabit or infect the respiratory tract are of special interest. Since many excellent reviews on the co-infection of IAV and S. pneumoniae have already been published, this review is intended to describe the unique interactions between other streptococci and IAV. Both streptococcal and IAV infections modulate the host epithelial barrier of the respiratory tract in various ways. IAV infection directly disrupts epithelial barriers, though at the same time the virus modifies the properties of infected cells to enhance streptococcal adherence and invasion. Mitis group streptococci produce neuraminidases, which promote IAV infection in a unique manner. The studies reviewed here have revealed intriguing mechanisms underlying secondary streptococcal infection following influenza. This article is protected by copyright. All rights reserved.

Effects of nasopharyngeal microbiota in respiratory infections and allergies

The human microbiome, which consists of a collective cluster of commensal, symbiotic, and pathogenic microorganisms living in the human body, plays a key role in host health and immunity. The human nasal cavity harbors commensal bacteria that suppress the colonization of opportunistic pathogens. However, dysbiosis of the nasal microbial community is associated with many diseases, such as acute respiratory infections including otitis media, sinusitis and bronchitis and allergic respiratory diseases including asthma. The nasopharyngeal acquisition of pneumococcus, which exists as a pathobiont in the nasal cavity, is the initial step in virtually all pneumococcal diseases. Although the factors influencing nasal colonization and elimination are not fully understood, the adhesion of opportunistic pathogens to nasopharyngeal mucosa receptors and the eliciting of immune responses in the host are implicated in addition to bacterial microbiota properties and colonization resistance dynamics. Probiotics or synbiotic interventions may show promising and effective roles in the adjunctive treatment of dysbiosis; however, more studies are needed to characterize how these interventions can be applied in clinical practice in the future.

Synbiotics Supplements Lower the Risk of Hand, Foot, and Mouth Disease in Children, Potentially by Providing Resistance to Gut Microbiota Dysbiosis

Background

Hand, foot and mouth disease (HFMD) is an acute enterovirus-induced disease. Gut microbiota dysbiosis has been identified as a factor that plays an important role in enteral virus infection, but the gut microbiota profile in hand, foot and mouth disease has rarely been studied in a large population.

Methods

A total of 749 children (HFMD: n = 262, healthy control: n = 487) aged 2 to 7 years were recruited from hospitals and communities in the period from May to July, 2017. Clinical and demographical information was collected by trained personnel, and fecal samples were collected and processed for 16S ribosomal RNA(rRNA) gene sequencing.

Results

We observed a significant alteration in the microbiota profile of children with HFMD compared with that of control children. Patients with enteroviruses A71(EV71) positive had more dysbiotic gut microbiota than those with coxsackievirus A16 (CAV16) positive. We found that Prevotella and Streptococcus were enriched in children with HFMD, whereas beneficial bacteria, including Bifidobacterium and Faecalibacterium, were depleted. Children with synbiotics supplements had lower risk of HFMD and we observed that the gut microbiota of HFMD patients who were administered synbiotics exhibited potential resistance to the dysbiosis detected in HFMD.

Conclusions

This study suggested that the gut microbiota of patients with hand, foot and mouth disease exhibits dysbiosis and that synbiotics supplements potentially helps maintain the homeostasis of the gut flora.

The Upper Airway Microbiota, Environmental Exposures, Inflammation, and Disease

Along with playing vital roles in pathogen exclusion and immune system priming, the upper airways (UAs) and their microbiota are essential for myriad physiological functions such as conditioning and transferring inhaled air. Dysbiosis, a microbial imbalance, is linked with various diseases and significantly impedes the quality of one’s life. Daily inhaled exposures and/or underlying conditions contribute to adverse changes to the UA microbiota. Such variations in the microbial community exacerbate UA and pulmonary disorders via modulating inflammatory and immune pathways. Hence, exploring the UA microbiota’s role in maintaining homeostasis is imperative. The microbial composition and subsequent relationship with airborne exposures, inflammation, and disease are crucial for strategizing innovating UA diagnostics and therapeutics. The development of a healthy UA microbiota early in life contributes to normal respiratory development and function in the succeeding years. Although different UA cavities present a unique microbial profile, geriatrics have similar microbes across their UAs. This lost community segregation may contribute to inflammation and disease, as it stimulates disadvantageous microbial–microbial and microbial–host interactions. Varying inflammatory profiles are associated with specific microbial compositions, while the same is true for many disease conditions and environmental exposures. A shift in the microbial composition is also detected upon the administration of numerous therapeutics, highlighting other beneficial and adverse side effects. This review examines the role of the UA microbiota in achieving homeostasis, and the impact on the UAs of environmental airborne pollutants, inflammation, and disease.

Quantification of bacteria by in vivo bioluminescence imaging in comparison with standard spread plate method and reverse transcription quantitative PCR (RT-qPCR)

In vivo bioluminescence imaging (BLI) offers a unique opportunity to analyze ongoing bacterial infections qualitatively and quantitatively in intact animals over time, leading to a reduction in the number of animals needed for a study. Since accurate determination of the bacterial burden plays an essential role in microbiological research, the present study aimed to evaluate the ability to quantify bacteria by non-invasive BLI technique in comparison to standard spread plate method and reverse transcription quantitative PCR (RT-qPCR). For this purpose, BALB/c mice were intranasally infected with 1 × 10⁵ CFU of bioluminescent Streptococcus pneumoniae A66.1. At day 1 post-infection, the presence of S. pneumoniae in lungs was demonstrated by spread plate method and RT-qPCR, but not by in vivo BLI. However, on the second day p.i., the bioluminescent signal was already detectable, and the photon flux values positively correlated with CFU counts and RT-qPCR data within days 2–6. Though in vivo BLI is valuable research tool allowing the continuous monitoring and quantification of pneumococcal infection in living mice, it should be kept in mind that early in the infection, depending on the infective dose, the bioluminescent signal may be below the detection limit.

Dynamic Pneumococcal Genetic Adaptations Support Bacterial Growth and Inflammation during Coinfection with Influenza

Streptococcus pneumoniae (pneumococcus) is one of the primary bacterial pathogens that complicates influenza virus infections. These bacterial coinfections increase influenza-associated morbidity and mortality through a number of immunological and viral-mediated mechanisms, but the specific bacterial genes that contribute to postinfluenza pathogenicity are not known. Here, we used genome-wide transposon mutagenesis (Tn-Seq) to reveal bacterial genes that confer improved fitness in influenza virus-infected hosts. The majority of the 32 genes identified are involved in bacterial metabolism, including nucleotide biosynthesis, amino acid biosynthesis, protein translation, and membrane transport. We generated mutants with single-gene deletions (SGD) of five of the genes identified, SPD1414, SPD2047 (cbiO1), SPD0058 (purD), SPD1098, and SPD0822 (proB), to investigate their effects on in vivo fitness, disease severity, and host immune responses. The growth of the SGD mutants was slightly attenuated in vitro and in vivo, but each still grew to high titers in the lungs of mock- and influenza virus-infected hosts. Despite high bacterial loads, mortality was significantly reduced or delayed with all SGD mutants. Time-dependent reductions in pulmonary neutrophils, inflammatory macrophages, and select proinflammatory cytokines and chemokines were also observed. Immunohistochemical staining further revealed altered neutrophil distribution with reduced degeneration in the lungs of influenza virus-SGD mutant-coinfected animals. These studies demonstrate a critical role for specific bacterial genes and for bacterial metabolism in driving virulence and modulating immune function during influenza-associated bacterial pneumonia.

Intranasal Vaccine Delivery Technology for Respiratory Tract Disease Application with a Special Emphasis on Pneumococcal Disease

This mini-review will cover recent trends in intranasal (IN) vaccine delivery as it relates to applications for respiratory tract diseases. The logic and rationale for IN vaccine delivery will be compared to methods and applications accompanying this particular administration route. In addition, we will focus extended discussion on the potential role of IN vaccination in the context of respiratory tract diseases, with a special emphasis on pneumococcal disease. Here, elements of this disease, including its prevalence and impact upon the elderly population, will be viewed from the standpoint of improving health outcomes through vaccine design and delivery technology and how IN administration can play a role in such efforts.

Virus-Induced Changes of the Respiratory Tract Environment Promote Secondary Infections With Streptococcus pneumoniae

Secondary bacterial infections enhance the disease burden of influenza infections substantially. Streptococcus pneumoniae (the pneumococcus) plays a major role in the synergism between bacterial and viral pathogens, which is based on complex interactions between the pathogen and the host immune response. Here, we discuss mechanisms that drive the pathogenesis of a secondary pneumococcal infection after an influenza infection with a focus on how pneumococci senses and adapts to the influenza-modified environment. We briefly summarize what is known regarding secondary bacterial infection in relation to COVID-19 and highlight the need to improve our current strategies to prevent and treat viral bacterial coinfections.

Relevance of angiotensin-(1-7) and its receptor Mas in pneumonia caused by influenza virus and post-influenza pneumococcal infection

Resolution failure of exacerbated inflammation triggered by Influenza A virus (IAV) prevents return of pulmonary homeostasis and survival, especially when associated with secondary pneumococcal infection. Therapeutic strategies based on pro-resolving molecules have great potential against acute inflammatory diseases. Angiotensin-(1-7) [Ang-(1-7)] is a pro-resolving mediator that acts on its Mas receptor (MasR) to promote resolution of inflammation. We investigated the effects of Ang-(1-7) and the role of MasR in the context of primary IAV infection and secondary pneumococcal infection and evaluated pulmonary inflammation, virus titers and bacteria counts, and pulmonary damage. Therapeutic treatment with Ang-(1-7) decreased neutrophil recruitment, lung injury, viral load and morbidity after a primary IAV infection. Ang-(1-7) induced apoptosis of neutrophils and efferocytosis of these cells by alveolar macrophages, but had no direct effect on IAV replication in vitro. MasR-deficient (MasR-/-) mice were highly susceptible to IAV infection, displaying uncontrolled inflammation, increased viral load and greater lethality rate, as compared to WT animals. Ang-(1-7) was not protective in MasR-/- mice. Interestingly, Ang-(1-7) given during a sublethal dose of IAV infection greatly reduced morbidity associated with a subsequent S. pneumoniae infection, as seen by decrease in the magnitude of neutrophil influx, number of bacteria in the blood leading to a lower lethality. Altogether, these results show that Ang-(1-7) is highly protective against severe primary IAV infection and protects against secondary bacterial infection of the lung. These effects are MasR-dependent. Mediators of resolution of inflammation, such as Ang-(1-7), should be considered for the treatment of pulmonary viral infections.

Effect of Vitamin A Deficiency in Dysregulating Immune Responses to Influenza Virus and Increasing Mortality Rates After Bacterial Coinfections

BACKGROUND

Secondary bacterial coinfections are ranked as a leading cause of hospitalization and morbid conditions associated with influenza. Because vitamin A deficiency (VAD) and insufficiency are frequent in both developed and developing countries, we asked how VAD influences coinfection severity.

METHODS

VAD and control mice were infected with influenza virus for evaluation of inflammatory cytokines, cellular immune responses, and viral clearance. Influenza-infected mice were coinfected with Streptococcus pneumoniae to study weight loss and survival.

RESULTS

Naive VAD mouse lungs exhibited dysregulated immune function. Neutrophils were enhanced in frequency and there was a significant reduction in RANTES (regulated on activation of normal T cells expressed and secreted), a chemokine instrumental in T-cell homing and recruitment. After influenza virus infection, VAD mice experienced failures in CD4+ T-cell recruitment and B-cell organization into lymphoid structures in the lung. VAD mice exhibited higher viral titers than controls and slow viral clearance. There were elevated levels of inflammatory cytokines and innate cell subsets in the lungs. However, arginase, a marker of alternatively activated M2 macrophages, was rare. When influenza-infected VAD animals were exposed to bacteria, they experienced a 100% mortality rate.

CONCLUSION

Data showed that VAD dysregulated the immune response. Consequently, secondary bacterial infections were 100% lethal in influenza-infected VAD mice.

Association Between the Respiratory Microbiome and Susceptibility to Influenza Virus Infection

BACKGROUND

Previous studies suggest that the nose/throat microbiome may play an important role in shaping host immunity and modifying the risk of respiratory infection. Our aim is to quantify the association between the nose/throat microbiome and susceptibility to influenza virus infection.

METHODS

In this household transmission study, index cases with confirmed influenza virus infection and their household contacts were followed for 9-12 days to identify secondary influenza infections. Respiratory swabs were collected at enrollment to identify and quantify bacterial species via high-performance sequencing. Data were analyzed by an individual hazard-based transmission model that was adjusted for age, vaccination, and household size.

RESULTS

We recruited 115 index cases with influenza A(H3N2) or B infection and 436 household contacts. We estimated that a 10-fold increase in the abundance in Streptococcus spp. and Prevotella salivae was associated with 48% (95% credible interval [CrI], 9-69%) and 25% (95% CrI, 0.5-42%) lower susceptibility to influenza A(H3N2) infection, respectively. In contrast, for influenza B infection, a 10-fold increase in the abundance in Streptococcus vestibularis and Prevotella spp. was associated with 63% (95% CrI, 17-83%) lower and 83% (95% CrI, 15-210%) higher susceptibility, respectively.

CONCLUSIONS

Susceptibility to influenza infection is associated with the nose/throat microbiome at the time of exposure. The effects of oligotypes on susceptibility differ between influenza A(H3N2) and B viruses. Our results suggest that microbiome may be a useful predictor of susceptibility, with the implication that microbiome could be modulated to reduce influenza infection risk, should these associations be causal.

Hypercapnia Suppresses Macrophage Antiviral Activity and Increases Mortality of Influenza A Infection via Akt1

Hypercapnia (HC), elevation of the partial pressure of CO₂ in blood and tissues, is a risk factor for mortality in patients with severe acute and chronic lung diseases. We previously showed that HC inhibits multiple macrophage and neutrophil antimicrobial functions and increases the mortality of bacterial pneumonia in mice. In this study, we show that normoxic HC increases viral replication, lung injury, and mortality in mice infected with influenza A virus (IAV). Elevated CO₂ increased IAV replication and inhibited antiviral gene and protein expression in macrophages in vivo and in vitro. HC potentiated IAV-induced activation of Akt, whereas specific pharmacologic inhibition or short hairpin RNA knockdown of Akt1 in alveolar macrophages blocked HC's effects on IAV growth and the macrophage antiviral response. Our findings suggest that targeting Akt1 or the downstream pathways through which elevated CO₂ signals could enhance macrophage antiviral host defense and improve clinical outcomes in hypercapnic patients with advanced lung disease.

The Microbiome of the Nose-Friend or Foe?

Recently, multiple studies regarding the human microbiota and its role on the development of disease have emerged. Current research suggests that the nasal cavity is a major reservoir for opportunistic pathogens, which can then spread to other sections of the respiratory tract and be involved in the development of conditions such as allergic rhinitis, chronic rhinosinusitis, asthma, pneumonia, and otitis media. However, our knowledge of how nasal microbiota changes originate nasopharyngeal and respiratory conditions is still incipient. Herein, we describe how the nasal microbiome in healthy individuals varies with age and explore the effect of nasal microbiota changes in a range of infectious and immunological conditions. We also describe the potential health benefits of human microbiota modulation through probiotic use, both in disease prevention and as adjuvant therapy. Current research suggests that patients with different chronic rhinosinusitis phenotypes possess distinct nasal microbiota profiles, which influence immune response and may be used in the future as biomarkers of disease progression. Probiotic intervention may also have a promising role in the prevention and adjunctive treatment of acute respiratory tract infections and allergic rhinitis, respectively. However, further studies are needed to define the role of probiotics in the chronic rhinosinusitis.

Application of Optimal Control to Influenza Pneumonia Coinfection with Antiviral Resistance

Influenza and pneumonia independently lead to high morbidity and mortality annually among the human population globally; however, a glaring fact is that influenza pneumonia coinfection is more vicious and it is a threat to public health. Emergence of antiviral resistance is a major impediment in the control of the coinfection. In this paper, a deterministic mathematical model illustrating the transmission dynamics of influenza pneumonia coinfection is formulated having incorporated antiviral resistance. Optimal control theory is then applied to investigate optimal strategies for controlling the coinfection using prevalence reduction and treatment as the system control variables. Pontryagin's maximum principle is used to characterize the optimal control. The derived optimality system is solved numerically using the Runge-Kutta-based forward-backward sweep method. Simulation results reveal that implementation of prevention measures is sufficient to eradicate influenza pneumonia coinfection from a given population. The prevention measures could be social distancing, vaccination, curbing mutation and reassortment, and curbing interspecies movement of the influenza virus.

Examining the Complex Relationship Between Tuberculosis and Other Infectious Diseases in Children

Millions of children are exposed to tuberculosis (TB) each year, many of which become infected with Mycobacterium tuberculosis. Most children can immunologically contain or eradicate the organism without pathology developing. However, in a minority, the organism overcomes the immunological constraints, proliferates and causes TB disease. Each year a million children develop TB disease, with a quarter dying. While it is known that young children and those with immunodeficiencies are at increased risk of progression from TB infection to TB disease, our understanding of risk factors for this transition is limited. The most immunologically disruptive process that can happen during childhood is infection with another pathogen and yet the impact of co-infections on TB risk is poorly investigated. Many diseases have overlapping geographical distributions to TB and affect similar patient populations. It is therefore likely that infection with viruses, bacteria, fungi and protozoa may impact on the risk of developing TB disease following exposure and infection, although disentangling correlation and causation is challenging. As vaccinations also disrupt immunological pathways, these may also impact on TB risk. In this article we describe the pediatric immune response to M. tuberculosis and then review the existing evidence of the impact of co-infection with other pathogens, as well as vaccination, on the host response to M. tuberculosis. We focus on the impact of other organisms on the risk of TB disease in children, in particularly evaluating if co-infections drive host immune responses in an age-dependent way. We finally propose priorities for future research in this field. An improved understanding of the impact of co-infections on TB could assist in TB control strategies, vaccine development (for TB vaccines or vaccines for other organisms), TB treatment approaches and TB diagnostics.

Pathogenesis and prevention of risk of cardiovascular events in patients with pneumococcal community-acquired pneumonia

It is now well recognized that cardiovascular events (CVE) occur quite commonly, both in the acute phase and in the long-term, in patients with community-acquired pneumonia (CAP). CVE have been noted in up to 30% of patients hospitalized with all-cause CAP. One systematic review and meta-analysis of hospitalized patients with all-cause CAP noted that the incidence rates for overall cardiac events were 17.7%, for incident heart failure were 14.1%, for acute coronary syndromes were 5.3% and for incident cardiac arrhythmias were 4.7%. In the case of pneumococcal CAP, almost 20% of patients studied had one or more of these cardiac events. Recent research has provided insights into the pathogenesis of the acute cardiac events occurring in pneumococcal infections. With respect to the former, key involvements of the major pneumococcal protein virulence factor, pneumolysin, are now well documented, whilst systemic platelet-driven neutrophil activation may also contribute. However, events involved in the pathogenesis of the long-term cardiovascular sequelae remain largely unexplored. Emerging evidence suggests that persistent antigenaemia may predispose to the development of a systemic pro-inflammatory/prothrombotic phenotype underpinning the risk of future cardiovascular events. The current manuscript briefly reviews the occurrence of cardiovascular events in patients with all-cause CAP, as well as in pneumococcal and influenza infections. It highlights the close interaction between influenza and pneumococcal pneumonia. It also includes a brief discussion of mechanisms of the acute cardiac events in CAP. However, the primary focus is on the prevalence, pathogenesis and prevention of the longer-term cardiac sequelae of severe pneumococcal disease, particularly in the context of persistent antigenaemia and associated inflammation.

"Epidemiology and aetiology of influenza-like illness among households in metropolitan Vientiane, Lao PDR": A prospective, community-based cohort study

Respiratory diseases are a major contributor to morbidity and mortality in many tropical countries, including Lao PDR. However, little has been published regarding viral or bacterial pathogens that can contribute to influenza-like illness (ILI) in a community setting. We report on the results of a community-based surveillance that prospectively monitored the incidence of ILI and its causative pathogens in Vientiane capital in Lao PDR. A cohort of 995 households, including 4885 study participants, were followed-up between May 2015 and May 2016. Nasopharyngeal swabs, throat swabs, and sputum specimens were collected from ILI cases identified through active case-finding. Real-Time PCR was used to test nasopharyngeal swabs for 21 respiratory pathogens, while throat and sputum samples were subjected to bacterial culture. Generalized linear mixed models were used to assess potential risk factors for associations with ILI. In total, 548 episodes of ILI were reported among 476 (9.7%) of the study participants and 330 (33.2%) of the study households. The adjusted estimated incidence of ILI within the study area was 10.7 (95%CI: 9.4-11.9) episodes per 100 person-years. ILI was significantly associated with age group (p<0.001), sex (p<0.001), and number of bedrooms (p = 0.04) in multivariate analysis. In 548 nasopharyngeal swabs, the most commonly detected potential pathogens were Streptococcus pneumoniae (17.0%), Staphylococcus aureus (11.3%), influenza A (11.1%; mostly subtype H3N2), rhinovirus (7.5%), and influenza B (8.0%). Streptococci were isolated from 42 (8.6%) of 536 throat swabs, most (27) of which were Lancefield Group G. Co-infections were observed in 132 (24.1%) of the 548 ILI episodes. Our study generated valuable data on respiratory disease burden and patterns of etiologies associated with community-acquired acute respiratory illness Laos. Establishment of a surveillance strategy in Laos to monitor trends in the epidemiology and burden of acute respiratory infections is required to minimize their impact on human health.

Dynamics between infectious diseases with two susceptibility conditions: A mathematical model

This paper presents a novel epidemiological transmission model of a population affected by two different susceptible-infected-susceptible infectious diseases. For each disease, individuals fall into one of the two susceptibility conditions in which one of the diseases has the highest occurrence level. This model is unique in assuming that: (a) if an individual is infected by one disease, their susceptibility to the other disease is increased; (b) when an individual recovers from a disease they become less susceptible to it, i.e. they acquire partial immunity. The model captures these two assumptions by utilizing a coupled system of differential equations. Dynamic analysis of the system is based on basic reproductive number theory, and pattern visualization was performed using numerical simulation.

An Infant Mouse Model of Influenza Virus Transmission Demonstrates the Role of Virus-Specific Shedding, Humoral Immunity, and Sialidase Expression by Colonizing Streptococcus pneumoniae

The pandemic potential of influenza A viruses (IAV) depends on the infectivity of the host, transmissibility of the virus, and susceptibility of the recipient. While virus traits supporting IAV transmission have been studied in detail using ferret and guinea pig models, there is limited understanding of host traits determining transmissibility and susceptibility because current animal models of transmission are not sufficiently tractable. Although mice remain the primary model to study IAV immunity and pathogenesis, the efficiency of IAV transmission in adult mice has been inconsistent. Here we describe an infant mouse model that supports efficient transmission of IAV. We demonstrate that transmission in this model requires young age, close contact, shedding of virus particles from the upper respiratory tract (URT) of infected pups, the use of a transmissible virus strain, and a susceptible recipient. We characterize shedding as a marker of infectiousness that predicts the efficiency of transmission among different influenza virus strains. We also demonstrate that transmissibility and susceptibility to IAV can be inhibited by humoral immunity via maternal-infant transfer of IAV-specific immunoglobulins and modifications to the URT milieu, via sialidase activity of colonizing Streptococcus pneumoniae Due to its simplicity and efficiency, this model can be used to dissect the host's contribution to IAV transmission and explore new methods to limit contagion.IMPORTANCE This study provides insight into the role of the virus strain, age, immunity, and URT flora on IAV shedding and transmission efficiency. Using the infant mouse model, we found that (i) differences in viral shedding of various IAV strains are dependent on specific hemagglutinin (HA) and/or neuraminidase (NA) proteins, (ii) host age plays a key role in the efficiency of IAV transmission, (iii) levels of IAV-specific immunoglobulins are necessary to limit infectiousness, transmission, and susceptibility to IAV, and (iv) expression of sialidases by colonizing S. pneumoniae antagonizes transmission by limiting the acquisition of IAV in recipient hosts. Our findings highlight the need for strategies that limit IAV shedding and the importance of understanding the function of the URT bacterial composition in IAV transmission. This work reinforces the significance of a tractable animal model to study both viral and host traits affecting IAV contagion and its potential for optimizing vaccines and therapeutics that target disease spread.

Back to the Future: Lessons Learned From the 1918 Influenza Pandemic

2018 marks the 100-year anniversary of the 1918 influenza pandemic, which killed ~50 million people worldwide. The severity of this pandemic resulted from a complex interplay between viral, host, and societal factors. Here, we review the viral, genetic and immune factors that contributed to the severity of the 1918 pandemic and discuss the implications for modern pandemic preparedness. We address unresolved questions of why the 1918 influenza H1N1 virus was more virulent than other influenza pandemics and why some people survived the 1918 pandemic and others succumbed to the infection. While current studies suggest that viral factors such as haemagglutinin and polymerase gene segments most likely contributed to a potent, dysregulated pro-inflammatory cytokine storm in victims of the pandemic, a shift in case-fatality for the 1918 pandemic toward young adults was most likely associated with the host's immune status. Lack of pre-existing virus-specific and/or cross-reactive antibodies and cellular immunity in children and young adults likely contributed to the high attack rate and rapid spread of the 1918 H1N1 virus. In contrast, lower mortality rate in in the older (>30 years) adult population points toward the beneficial effects of pre-existing cross-reactive immunity. In addition to the role of humoral and cellular immunity, there is a growing body of evidence to suggest that individual genetic differences, especially involving single-nucleotide polymorphisms (SNPs), contribute to differences in the severity of influenza virus infections. Co-infections with bacterial pathogens, and possibly measles and malaria, co-morbidities, malnutrition or obesity are also known to affect the severity of influenza disease, and likely influenced 1918 H1N1 disease severity and outcomes. Additionally, we also discuss the new challenges, such as changing population demographics, antibiotic resistance and climate change, which we will face in the context of any future influenza virus pandemic. In the last decade there has been a dramatic increase in the number of severe influenza virus strains entering the human population from animal reservoirs (including highly pathogenic H7N9 and H5N1 viruses). An understanding of past influenza virus pandemics and the lessons that we have learnt from them has therefore never been more pertinent.

Host-pathogen kinetics during influenza infection and coinfection: insights from predictive modeling

Influenza virus infections are a leading cause of morbidity and mortality worldwide. This is due in part to the continual emergence of new viral variants and to synergistic interactions with other viruses and bacteria. There is a lack of understanding about how host responses work to control the infection and how other pathogens capitalize on the altered immune state. The complexity of multi-pathogen infections makes dissecting contributing mechanisms, which may be non-linear and occur on different time scales, challenging. Fortunately, mathematical models have been able to uncover infection control mechanisms, establish regulatory feedbacks, connect mechanisms across time scales, and determine the processes that dictate different disease outcomes. These models have tested existing hypotheses and generated new hypotheses, some of which have been subsequently tested and validated in the laboratory. They have been particularly a key in studying influenza-bacteria coinfections and will be undoubtedly be useful in examining the interplay between influenza virus and other viruses. Here, I review recent advances in modeling influenza-related infections, the novel biological insight that has been gained through modeling, the importance of model-driven experimental design, and future directions of the field.

Molecular diagnosis of microbial copathogens with influenza A(H1N1)pdm09 in Oaxaca, Mexico

Background

Multiple factors have been associated with the severity of infection by influenza A(H1N1)pdm09. These include H1N1 cases with proven coinfections showing clinical association with bacterial contagions.

Purpose

The objective was to identify H1N1 and copathogens in the Oaxaca (Mexico) population. A cross-sectional survey was conducted from 2009 to 2012. A total of 88 study patients with confirmed H1N1 by quantitative RT-PCR were recruited.

Methods

Total nucleic acid from clinical samples of study patients was analyzed using a TessArray RPM-Flu microarray assay to identify other respiratory pathogens.

Results

High prevalence of copathogens (77.3%; 68 patients harbored one to three pathogens), predominantly from Streptococcus, Haemophilus, Neisseria, and Pseudomonas, were detected. Three patients (3.4%) had four or five respiratory copathogens, whereas others (19.3%) had no copathogens. Copathogenic occurrence with Staphylococcus aureus was 5.7%, Coxsackie virus 2.3%, Moraxella catarrhalis 1.1%, Klebsiella pneumoniae 1.1%, and parainfluenza virus 3 1.1%. The number of patients with copathogens was four times higher to those with H1N1 alone (80.68% and 19.32%, respectively). Four individuals (4.5%; two males, one female, and one infant) who died due to H1N1 were observed to have harbored such copathogens as Streptococcus, Staphylococcus, Haemophilus, and Neisseria.

Conclusion

In summary, copathogens were found in a significant number (>50%) of cases of influenza in Oaxaca. Timely detection of coinfections producing increased acuity or severity of disease and treatment of affected patients is urgently needed.

Comparison of the nasopharynx microbiome between influenza and non-influenza cases of severe acute respiratory infections: A pilot study

AIMS

Influenza A virus (IAV) can cause severe acute respiratory infection (SARI), and disease outcome may be associated with changes in the microbiome of the nasopharynx. This is a pilot study to characterize the microbiome of the nasopharynx in patients hospitalized with SARI, infected and not infected by IAV.

METHODS AND RESULTS

Using target sequencing of the 16S rRNA gene, we assessed the bacterial community of nasopharyngeal aspirate samples and compared the microbiome of patients infected with IAV with the microbiome of patients who were negative for IAV. We observed differences in the relative abundance of Proteobacteria and Firmicutes between SARI patients, with Streptococcus being enriched and Pseudomonas underrepresented in IAV patients compared with patients who were not infected with IAV.

CONCLUSION

Pseudomonas taxon seems to be in high frequency on the nasopharynx of SARI patients with non-IAV infection and might present a negative association with Streptococcus taxon. Microbial profile appears to be different between SARI patients infected or not infected with IAV.

Influenza interaction with cocirculating pathogens and its impact on surveillance, pathogenesis, and epidemic profile: A key role for mathematical modelling

Evidence is mounting that influenza virus interacts with other pathogens colonising or infecting the human respiratory tract. Taking into account interactions with other pathogens may be critical to determining the real influenza burden and the full impact of public health policies targeting influenza. This is particularly true for mathematical modelling studies, which have become critical in public health decision-making. Yet models usually focus on influenza virus acquisition and infection alone, thereby making broad oversimplifications of pathogen ecology. Herein, we report evidence of influenza virus interactions with bacteria and viruses and systematically review the modelling studies that have incorporated interactions. Despite the many studies examining possible associations between influenza and Streptococcus pneumoniae, Staphylococcus aureus, Haemophilus influenzae, Neisseria meningitidis, respiratory syncytial virus (RSV), human rhinoviruses, human parainfluenza viruses, etc., very few mathematical models have integrated other pathogens alongside influenza. The notable exception is the pneumococcus-influenza interaction, for which several recent modelling studies demonstrate the power of dynamic modelling as an approach to test biological hypotheses on interaction mechanisms and estimate the strength of those interactions. We explore how different interference mechanisms may lead to unexpected incidence trends and possible misinterpretation, and we illustrate the impact of interactions on public health surveillance using simple transmission models. We demonstrate that the development of multipathogen models is essential to assessing the true public health burden of influenza and that it is needed to help improve planning and evaluation of control measures. Finally, we identify the public health, surveillance, modelling, and biological challenges and propose avenues of research for the coming years.

CXCR1/2 Antagonism Is Protective during Influenza and Post-Influenza Pneumococcal Infection

Rationale

Influenza A infections are a leading cause of morbidity and mortality worldwide especially when associated with secondary pneumococcal infections. Inflammation is important to control pathogen proliferation but may also cause tissue injury and death. CXCR1/2 are chemokine receptors relevant for the recruitment of neutrophils. We investigated the role of CXCR1/2 during influenza, pneumococcal, and post-influenza pneumococcal infections.

Methods

Mice were infected with influenza A virus (IAV) or Streptococcus pneumoniae and then treated daily with the CXCR1/2 antagonist DF2162. To study secondary pneumococcal infection, mice were infected with a sublethal inoculum of IAV then infected with S. pneumoniae 14 days later. DF2162 was given in a therapeutic schedule from days 3 to 6 after influenza infection. Lethality, weight loss, inflammation, virus/bacteria counts, and lung injury were assessed.

Results

CXCL1 and CXCL2 were produced at high levels during IAV infection. DF2162 treatment decreased morbidity and this was associated with decreased infiltration of neutrophils in the lungs and reduced pulmonary damage and viral titers. During S. pneumoniae infection, DF2162 treatment decreased neutrophil recruitment, pulmonary damage, and lethality rates, without affecting bacteria burden. Therapeutic treatment with DF2162 during sublethal IAV infection reduced the morbidity associated with virus infection and also decreased the magnitude of inflammation, lung damage, and number of bacteria in the blood of mice subsequently infected with S. pneumoniae.

Conclusion

Modulation of the inflammatory response by blocking CXCR1/2 improves disease outcome during respiratory influenza and pneumococcal infections, without compromising the ability of the murine host to deal with infection. Altogether, inhibition of CXCR1/2 may be a valid therapeutic strategy for treating lung infections caused by these pathogens, especially controlling secondary bacterial infection after influenza.

Streptococcus pneumoniae and chronic endobronchial infections in childhood

Streptococcus pneumoniae (pneumococcus) is the main cause of bacterial pneumonia worldwide and has been studied extensively in this context. However, its role in chronic endobronchial infections and accompanying lower airway neutrophilic infiltration has received little attention. Severe and recurrent pneumonia are risk factors for chronic suppurative lung disease (CSLD) and bronchiectasis; the latter causes considerable morbidity and, in some populations, premature death in children and adults. Protracted bacterial bronchitis (PBB) is another chronic endobronchial infection associated with substantial morbidity. In some children, PBB may progress to bronchiectasis. Although nontypeable Haemophilus influenzae is the main pathogen in PBB, CSLD and bronchiectasis, pneumococci are isolated commonly from the lower airways of children with these diagnoses. Here we review what is known currently about pneumococci in PBB, CSLD and bronchiectasis, including the importance of pneumococcal nasopharyngeal colonization and how persistence in the lower airways may contribute to the pathogenesis of these chronic pulmonary disorders. Antibiotic treatments, particularly long-term azithromycin therapy, are discussed together with antibiotic resistance and the impact of pneumococcal conjugate vaccines. Important areas requiring further investigation are identified, including immune responses associated with pneumococcal lower airway infection, alone and in combination with other respiratory pathogens, and microarray serotyping to improve detection of carriage and infection by multiple serotypes. Genome wide association studies of pneumococci from the upper and lower airways will help identify virulence and resistance determinants, including potential therapeutic targets and vaccine antigens to treat and prevent endobronchial infections. Much work is needed, but the benefits will be substantial.

The Unexpected Impact of Vaccines on Secondary Bacterial Infections Following Influenza

Influenza virus infections remain a significant health burden worldwide, despite available vaccines. Factors that contribute to this include a lack of broad coverage by current vaccines and continual emergence of novel virus strains. Further complicating matters, when influenza viruses infect a host, severe infections can develop when bacterial pathogens invade. Secondary bacterial infections (SBIs) contribute to a significant proportion of influenza-related mortality, with Streptococcus pneumoniae, Staphylococcus aureus, Streptococcus pyogenes, and Haemophilus influenzae as major coinfecting pathogens. Vaccines against bacterial pathogens can reduce coinfection incidence and severity, but few vaccines are available and those that are, may have decreased efficacy in influenza virus-infected hosts. While some studies indicate a benefit of vaccine-induced immunity in providing protection against SBIs, a comprehensive understanding is lacking. In this review, we discuss the current knowledge of viral and bacterial vaccine availability, the generation of protective immunity from these vaccines, and the effectiveness in limiting influenza-associated bacterial infections.

Use of mathematical modelling to assess the impact of vaccines on antibiotic resistance

Antibiotic resistance is a major global threat to the provision of safe and effective health care. To control antibiotic resistance, vaccines have been proposed as an essential intervention, complementing improvements in diagnostic testing, antibiotic stewardship, and drug pipelines. The decision to introduce or amend vaccination programmes is routinely based on mathematical modelling. However, few mathematical models address the impact of vaccination on antibiotic resistance. We reviewed the literature using PubMed to identify all studies that used an original mathematical model to quantify the impact of a vaccine on antibiotic resistance transmission within a human population. We reviewed the models from the resulting studies in the context of a new framework to elucidate the pathways through which vaccination might impact antibiotic resistance. We identified eight mathematical modelling studies; the state of the literature highlighted important gaps in our understanding. Notably, studies are limited in the range of pathways represented, their geographical scope, and the vaccine-pathogen combinations assessed. Furthermore, to translate model predictions into public health decision making, more work is needed to understand how model structure and parameterisation affects model predictions and how to embed these predictions within economic frameworks.

Synthesis of biotinylated bivalent zanamivir analogs as probes for influenza viruses

The synthesis of a biotinylated bivalent zanamivir analog as a probe for influenza viruses is reported. The compound was used in a ‘glycan’ based sandwich assay; where glycans were immobilized on glass slides to capture strains of influenza A H1N1, A/Brisbane/59/2007 virus; the biotinylated bivalent zanamivir analog-labeled streptavidin complex was used as reporter. This research strongly suggests that glycans can be used for capturing and reporting influenza viruses and the biotinylated compounds can be used as probes for capturing and isolating influenza viruses from complex mixtures.

An agent-based model simulation of influenza interactions at the host level: insight into the influenza-related burden of pneumococcal infections

BACKGROUND

Host-level influenza virus-respiratory pathogen interactions are often reported. Although the exact biological mechanisms involved remain unelucidated, secondary bacterial infections are known to account for a large part of the influenza-associated burden, during seasonal and pandemic outbreaks. Those interactions probably impact the microorganisms' transmission dynamics and the influenza public health toll. Mathematical models have been widely used to examine influenza epidemics and the public health impact of control measures. However, most influenza models overlooked interaction phenomena and ignored other co-circulating pathogens.

METHODS

Herein, we describe a novel agent-based model (ABM) of influenza transmission during interaction with another respiratory pathogen. The interacting microorganism can persist in the population year round (endemic type, e.g. respiratory bacteria) or cause short-term annual outbreaks (epidemic type, e.g. winter respiratory viruses). The agent-based framework enables precise formalization of the pathogens' natural histories and complex within-host phenomena. As a case study, this ABM is applied to the well-known influenza virus-pneumococcus interaction, for which several biological mechanisms have been proposed. Different mechanistic hypotheses of interaction are simulated and the resulting virus-induced pneumococcal infection (PI) burden is assessed.

RESULTS

This ABM generates realistic data for both pathogens in terms of weekly incidences of PI cases, carriage rates, epidemic size and epidemic timing. Notably, distinct interaction hypotheses resulted in different transmission patterns and led to wide variations of the associated PI burden. Interaction strength was also of paramount importance: when influenza increased pneumococcus acquisition, 4-27% of the PI burden during the influenza season was attributable to influenza depending on the interaction strength.

CONCLUSIONS

This open-source ABM provides new opportunities to investigate influenza interactions from a theoretical point of view and could easily be extended to other pathogens. It provides a unique framework to generate in silico data for different scenarios and thereby test mechanistic hypotheses.

Influenza Virus and Glycemic Variability in Diabetes: A Killer Combination?

Following the 2009 H1N1 influenza virus pandemic, numerous studies identified the striking link between diabetes mellitus and influenza disease severity. Typically, influenza virus is a self-limiting infection but in individuals who have a pre-existing chronic illness, such as diabetes mellitus, severe influenza can develop. Here, we discuss the latest clinical and experimental evidence for the role of diabetes in predisposing the host to severe influenza. We explore the possible mechanisms that underlie this synergy and highlight the, as yet, unexplored role that blood glucose oscillations may play in disease development. Diabetes is one of the world’s fastest growing chronic diseases and influenza virus represents a constant and pervasive threat to human health. It is therefore imperative that we understand how diabetes increases influenza severity in order to mitigate the burden of future influenza epidemics and pandemics.

Effect of early measles vaccine on pneumococcal colonization: A randomized trial from Guinea-Bissau

BACKGROUND

Measles vaccine (MV) may have non-specific beneficial effects for child health and particularly seems to prevent respiratory infections. Streptococcus pneumoniae is the leading cause of bacterial pneumonia among children worldwide, and nasopharyngeal colonization precedes infection.

OBJECTIVE

We investigated whether providing early MV at 18 weeks of age reduced pneumococcal colonization and/or density up to 9 months of age.

METHOD

The study was conducted in 2013-2014 in Guinea-Bissau. Pneumococcal vaccine was not part of the vaccination program. Infants aged 18 weeks were block-randomized 2:1 to early or no early MV; at age 9 months, all children were offered MV as per current policy. Nasopharyngeal swabs were taken at baseline, age 6.5 months, and age 9 months. Pneumococcal density was determined by q-PCR. Prevalence ratios of pneumococcal colonization and recent antibiotic treatment (yes/no) by age 6.5 months (PR6.5) and age 9 months (PR9) were estimated using Poisson regression with robust variance estimates while the pneumococcal geometric mean ratio (GMR6.5 and GMR9) was obtained using OLS regression.

RESULTS

Analyses included 512 children; 346 early MV-children and 166 controls. At enrolment, the pneumococcal colonization prevalence was 80% (411/512). Comparing early MV-children with controls, the PR6.5 was 1.02 (95%CI = 0.94-1.10), and the PR9 was 1.04 (0.96-1.12). The GMR6.5 was 1.02 (0.55-1.89), and the GMR9 was 0.69 (0.39-1.21). Early MV-children tended to be less frequently treated with antibiotics prior to follow up (PR6.5 0.60 (0.34-1.05) and PR9 0.87 (0.50-1.53)). Antibiotic treatment was associated with considerably lower colonization rates, PR6.5 0.85 (0.71-1.01) and PR9 0.66 (0.52-0.84), as well as lower pneumococcal density, GMR6.5 0.32 (0.12-0.86) and GMR9 0.52 (0.18-1.52).

CONCLUSION

Early MV at age 18 weeks had no measurable effect on pneumococcal colonization prevalence or density. Higher consumption of antibiotics among controls may have blurred an effect of early MV.

TRIAL REGISTRATION

clinicaltrials.gov NCT01486355.

Highly specific and rapid glycan based amperometric detection of influenza viruses

Rapid and precise detection of influenza viruses in a point of care setting is critical for applying appropriate countermeasures. Current methods such as nucleic acid or antibody based techniques are expensive or suffer from low sensitivity, respectively. We have developed an assay that uses glucose test strips and a handheld potentiostat to detect the influenza virus with high specificity. Influenza surface glycoprotein neuraminidase (NA), but not bacterial NA, cleaved galactose bearing substrates, 4,7di-OMe N-acetylneuraminic acid attached to the 3 or 6 position of galactose, to release galactose. In contrast, viral and bacterial NA cleaved the natural substrate, N-acetylneuraminic acid attached to the 3 or 6 position of galactose. The released galactose was detected amperometrically using a handheld potentiostat and dehydrogenase bearing glucose test strips. The specificity for influenza was confirmed using influenza strains and different respiratory pathogens that include Streptococcus pneumoniae and Haemophilus influenzae; bacteria do not cleave these molecules. The assay was also used to detect co-infections caused by influenza and bacterial NA. Viral drug susceptibility and testing with human clinical samples was successful in 15 minutes, indicating that this assay could be used to rapidly detect influenza viruses at primary care or resource poor settings using ubiquitous glucose meters.

A Critical, Nonlinear Threshold Dictates Bacterial Invasion and Initial Kinetics During Influenza

Secondary bacterial infections increase morbidity and mortality of influenza A virus (IAV) infections. Bacteria are able to invade due to virus-induced depletion of alveolar macrophages (AMs), but this is not the only contributing factor. By analyzing a kinetic model, we uncovered a nonlinear initial dose threshold that is dependent on the amount of virus-induced AM depletion. The threshold separates the growth and clearance phenotypes such that bacteria decline for dose-AM depletion combinations below the threshold, stay constant near the threshold, and increase above the threshold. In addition, the distance from the threshold correlates to the growth rate. Because AM depletion changes throughout an IAV infection, the dose requirement for bacterial invasion also changes accordingly. Using the threshold, we found that the dose requirement drops dramatically during the first 7d of IAV infection. We then validated these analytical predictions by infecting mice with doses below or above the predicted threshold over the course of IAV infection. These results identify the nonlinear way in which two independent factors work together to support successful post-influenza bacterial invasion. They provide insight into coinfection timing, the heterogeneity in outcome, the probability of acquiring a coinfection, and the use of new therapeutic strategies to combat viral-bacterial coinfections.

Co-colonization by Streptococcus pneumoniae and Staphylococcus aureus in the throat during acute respiratory illnesses

Pneumonia due to either Streptococcus pneumoniae (Sp) or Staphylococcus aureus (Sa) accounts for most mortality after influenza and acute respiratory illness (ARI). Because carriage precedes infection, we estimated Sp and Sa carriage to examine the co-colonization dynamics between Sp, Sa and respiratory viruses in the presence of ARI in the oropharynx. We tested oropharyngeal specimens of community subjects (aged ⩾2 years) with ARI for the presence of influenza A and B, 11 other common respiratory viruses, Sp and Sa, using real-time PCR. A total of 338 participants reported 519 ARI episodes of which 119 (35%) carried Sp, 52 (13%) carried Sa and 25 (7%) carried both. Thirty-five subjects tested positive for influenza, of which 14 (40%) carried Sp and six (17%) carried Sa, significantly more than in the influenza-negative group (P = 0·03 and P = 0·04, respectively). In subjects infected by any virus compared to those with no virus, Sp carriage (39·2% vs. 27·9%, P = 0·03) but not Sa carriage (11·6% vs. 14%, P = 0·6) was more frequent. For children, when Sa was present, Sp carriage tended to be less frequent than expected given the presence of viral infection, but not significantly [observed relative risk 1·14, 95% confidence interval (CI) 0·4-3·1; with a relative excess risk due to interaction of -0·11]. Independent of age, Sp carriers were more likely to return that season with subsequent ARI (odds ratio 2·14, 95% CI 1·1-4·3, P = 0·03). Both Sp and Sa carriage rates in the oropharynx increase during influenza infection in children. However, no negative interaction between Sp and Sa was observed. Sp carriers are more likely to suffer subsequent ARI episodes than non-carriers.

Quantifying the therapeutic requirements and potential for combination therapy to prevent bacterial coinfection during influenza

Secondary bacterial infections (SBIs) exacerbate influenza-associated disease and mortality. Antimicrobial agents can reduce the severity of SBIs, but many have limited efficacy or cause adverse effects. Thus, new treatment strategies are needed. Kinetic models describing the infection process can help determine optimal therapeutic targets, the time scale on which a drug will be most effective, and how infection dynamics will change under therapy. To understand how different therapies perturb the dynamics of influenza infection and bacterial coinfection and to quantify the benefit of increasing a drug's efficacy or targeting a different infection process, I analyzed data from mice treated with an antiviral, an antibiotic, or an immune modulatory agent with kinetic models. The results suggest that antivirals targeting the viral life cycle are most efficacious in the first 2 days of infection, potentially because of an improved immune response, and that increasing the clearance of infected cells is important for treatment later in the infection. For a coinfection, immunotherapy could control low bacterial loads with as little as 20 % efficacy, but more effective drugs would be necessary for high bacterial loads. Antibiotics targeting bacterial replication and administered 10 h after infection would require 100 % efficacy, which could be reduced to 40 % with prophylaxis. Combining immunotherapy with antibiotics could substantially increase treatment success. Taken together, the results suggest when and why some therapies fail, determine the efficacy needed for successful treatment, identify potential immune effects, and show how the regulation of underlying mechanisms can be used to design new therapeutic strategies.