Differential response of gel-forming mucins to pathogenic middle ear bacteria

Abstract

Objective

To assess the differential response of the secretory gel forming mucins (GFM) to the most common bacterial pathogens causing otitis media, Streptococcus pneumoniae (SP), nontypeable Haemophilus influenza (NTHi), and Moraxella catarrhalis (Mcat), in a culture model of human middle ear epithelium (HMEEC).

Methods

In vitro cultured HMEEC was exposed to 5µg/ml of bacterial whole cell lysate (WCL). RNA was extracted to generate cDNA. The expression levels of each of the targeted mucin transcripts, MUC2, MUC5AC, MUC5B and MUC19, were detected by quantitative PCR.

Results

The submerged HMEEC exposed to NTHi-86028NP WCL demonstrated a significant increase of MUC2, MUC5AC and MUC5B as compared to the control non treated cells while MUC19 transcript level remained unchanged. WCL of additional major OM pathogens significantly increase the transcription of these three mucin genes as well. A combination of NTHi and SP further synergistically induced MUC2 and MUC5AC gene expression however, not all NTHi strains synergized with SP in the induction. Addition of Mcat WCL to the synergized combination of NTHi and SP did not participate in the synergistic response of mucins.

Conclusion

The specific pathogen combinations were important in determining the degree of synergistic effects to GFM expression. The current data are substantive in guiding future work to extend our understanding of OM pathogens and GFMs.

INTRODUCTION

Although otitis media (OM) is a prevalent condition responsible for conductive hearing loss in the pediatric population and substantial health care costs totaling several billion dollars annually in the United States, knowledge deficits persist regarding OM pathogenesis. Particularly important is the interaction between various pathogens and the middle ear epithelium (MEE) as it relates to mucin gene expression and mucin production. It has been well-documented by our laboratory and others that pathogenic bacteria and viruses in the middle ear lead to inflammatory processes, cytokine activation and an increase in the MEE production of mucins [1–4]. These events leading to an increase in mucin production provide protection to the MEE from the invading pathogens and inflammatory events and assist in clearance of pathogens from the ME. However, mucins are also the primary components which persist in the ME following these infectious events, leading to thickened secretions and hearing loss associated with OM.

With this knowledge, a next logical step in understanding the pathogenesis involved in OM is a more thorough elucidation of the specific pathogen and mucin responses. The mucins which primarily lead to this hearing loss are the secretory, gel-forming mucins (GFM) found in the MEE which include the glycoproteins from mucin genes 2 (MUC2), 5AC (MUC5AC), 5B (MUC5B) and 19 (MUC19). These mucins have been demonstrated in a number of studies, including from our laboratory, to be the primary gel-forming mucins of the MEE [5–8]. In addition, these gel-forming mucins are conserved in the MEE across multiple species including human, rat, mouse and chinchilla [9,10]. Each of these mucins have been shown to be up-regulated in response to non-specific cytokine inflammatory responses [11,12]. However, specific mucin gene and protein responses to common OM bacterial pathogens have not been investigated. The objective of this current investigation was to assess the differential response of these gel-forming mucin genes to the most common OM bacterial pathogens of Streptococcus pneumoniae (SP), nontypeable Haemophilus influenzae (NTHi) and Moraxella catarrhalis (Mcat).

MATERIALS AND METHODS

Bacterial strains and growth

Bacteria utilized in this study were Nontypeable Haemophilus influenzae (strain 86028NP and 2019), Streptococcus pneumoniae (strain TIGR4 and D39), and Moraxella catarrhalis (strain 7169). All bacteria were grown on brain heart infusion (BHI) agar plates with exception of NTHi which requires the supplement of hemin and nicotinamide adenine dinucleotide (sBHI) at 37°C with 5% CO₂. The 12 hour bacterial culture was harvested. The pellet was suspended and sonicated in phosphate buffered saline as previously described [13]. The whole cell lysate (WCL) was collected and stored at −80°C. The bacterial WCL was selected to simulate the clinical condition where most of OM pathogens undergo spontaneous or antibiotic-induced autolysis in vivo [14].

Cell culture

A culture model of human middle ear epithelium (HMEEC, provided by Dr. David J Lim) was an immortalized cell line whose primary characterization regarding transformation and growth properties have been published [15]. The culture was maintained in a humidified atmosphere at 37°C with 5% CO₂, in full growth media containing a 1:1 ratio mixture of Dulbecco’s Modified Eagle Medium (Life Technologies) and Bronchial Epithelial Cell Basal Medium (Lonza), 10% Fetal Bovine Serum (FBS), 1% antibiotic/antimycotic, and supplemented with one BEGM Singlequots (Lonza) for every 500ml portion of the media. The cells were grown in the presence of 1µM retinoic acid (RA) for 5 days prior to treatment. The culture was serum starved overnight and subsequently treated with 5µg/ml of bacterial WCL, a minimal concentration that provided optimal response of mucin (data not shown), in basal media containing supplements and 1µM RA at 2, 4, and 6 hours. Cell lysate was harvested at the end of exposure time.

Quantitative PCR

Total RNA from experimental cultures was prepared after the indicated treatments using TriZol reagent. cDNA was synthesized using the SuperScript III First-Strand Synthesis System (Life Technologies). Each cDNA reaction prepared for MUC2, MUC5AC and MUC19 experiments was started with 400ng total RNA while a 1.5µg starting total RNA was required for a detection of MUC5B. Quantitative PCR (qPCR) was carried out on a ViiA7 by Life Technologies using their commercially available TaqMan primer-probes for MUC2, MUC5AC, MUC5B, MUC19 and HPRT1. Samples were analyzed in triplicates and a no template control was included for each gene. The expression levels of each of the targeted mucin genes detected by qPCR were normalized to the mRNA level of the house keeping gene HPRT1. The relative fold change of mucin gene was calculated using 2^−ΔΔCt methodology [16].

Statistics

All experiments were performed in triplicate. The results were presented as mean ± standard error of means. Data of GFM response to single OM pathogen were analyzed by student’s t-test. Differences in GFM synergistic response to multiple OM pathogens were determined by one-way ANOVA followed by Tukey’s Post-hoc. All statistical analyses were performed using Prism software version 5.01 (GraphPad Software, Inc).

RESULTS

NTHi strain 86028NP whole cell lysate up regulated transcript expression of gel forming mucins in immortalized human middle ear epithelium cells (HMEEC)

To assess changes in gel forming mucin gene expression due to stimulation of bacterial whole cell lysate, HMEEC were exposed to 5 µg/ml NTHi-86028NP WCL at various time points (Figure 1). The submerged HMEEC exposed to NTHi WCL demonstrated 1.5–2 fold increase of MUC2 as compared to the control non treated cells. The significant increase was observed at every time point tested (p < 0.05). Increase of MUC5AC was also detected in similar a pattern at 5–7 fold increase over the level detected in non-treated cells (p <0.05). The change in MUC5B mucin expression required a longer stimulation. The significant 2-fold increase of MUC5B mRNA level is observed after a 6 hour exposure (p = 0.007). MUC19 transcript level remained unchanged in WCL treated HMEEC cells.

Figure 1. NTHi strain 86028NP whole cell lysate (WCL) up-regulated transcript expression of gel forming mucins in immortalized human middle ear epithelium cells (HMEEC).

NTHi treatment of submerged HMEEC significantly increased the mRNA level of MUC2 and MUC5AC at all time-points tested. MUC5B required a longer stimulation showing a significant change at 6 hour after exposure. MUC19 remained unchanged at all time-points tested. The x-axis shows the hours (hr) during which the cells were exposed to 5µg/ml of NTHi-86028NP WCL. The y-axis represents the relative fold induction obtained from qPCR on total RNA extracted from the cells. Asterisk (*) designated significant difference from control group (pvalue < 0.05).

Whole cell lysate of additional major OM pathogens stimulated transcription of gel forming mucin genes

The assessment of the impact on GFMs of an additional strain of NTHi (NTHi-2019) demonstrated increase of MUC2, MUC5AC and MUC5B with significant p value of 0.0014, 0.0001, and 0.0116, respectively (Figure 2). Similar induction was observed when cells were exposed to SP-D39 with the highest fold change of MUC5AC (p < 0.0001), about 3-fold change of MUC5B (p < 0.0001) and almost 1.5 fold change of MUC2 (p = 0.0028). Exposure to SP-TIGR4 increased MUC5AC (p < 0.0001) and MUC5B (p = 0.0042) at comparable levels, but not MUC2 (p = 0.1989). Mcat-7169 significantly induced MUC2 (p < 0.0001) and MUC5AC (p < 0.0001) but not MUC5B (p = 0.1243). Both MUC2 and MUC5AC demonstrated a more robust response to NTHi and Mcat than SP. A more robust response of MUC5B to SP was observed.

Figure 2. Stimulation of gel forming mucin genes by major OM pathogens (NTHi, SP and Mcat).

The relative fold increase of mRNA level of MUC2 and MUC5AC were detected at 4 hours after exposure to single strain bacterial WCL. There was significant increase of MUC2 in cells exposed to all but TIGR4. MUC5AC also demonstrated a significant increase after exposure to all bacterial WCL tested. At 6 hour exposure, MUC5B demonstrated the significant increase in all but Mcat. Asterisk (*) designated significant difference from control group (pvalue < 0.05).

Synergistic effect between NTHi and SP further up-regulated GFM gene expression in in vitro HMEEC model

To assess impact of multiple microbial WCL on gel forming mucin expression, HMEEC were exposed to the combination of OM pathogens (Figure 3). Single bacterial strain WCL of NTHi and SP induced significant changes in levels of each mucin gene. A combination of NTHi and SP further synergistically induced MUC2 and MUC5AC mRNA expression in HMEEC. A similar synergistic effect was not observed in the induction of MUC5B level. Note that not all NTHi strains (86028NP and 2019) synergized with SP (TIGR4 and D39) in the induction of expression. While all combinations of NTHi and SP (NTHi-86028NPD39; NTHi-86028NPTIGR4; NTHi-2019D39; and NTHi-2019TIGR4) further induced MUC5AC (p-value of <0.0001, 0.0004, 0.0005, and <0.0001, respectively), only a combined NTHi-2019 and D39 synergized the expression of MUC2 (p = 0.0002). The addition of Mcat WCL to the synergized combination of NTHi-2019 and SP-D39 (Figure 4) did not participate in the synergistic response and demonstrated a reduction of MUC2 response (p = 0.0042) to the same level as that of Mcat alone. A similar result of non-synergized Mcat was observed in MUC5AC response (p = 0.9673).

Figure 3. Synergistic effect between NTHi and SP induce the expression of gel forming mucin gene in HMEEC.

Single bacterial strain WCL of NTHi and SP induced significant changes in levels of each mucin gene. Combination of NTHi and SP further synergistically induced MUC2 and MUC5AC mRNA expression but not MUC5B. Note that not all NTHi strains (86028NP and 2019) synergized with SP (TIGR4 and D39) in the induction of expression. Asterisk (*) indicated the significant synergistic effect between NTHi and SP in the up-regulation of GFM expression.

Figure 4. Impact of multiple microbial whole cell lysate on gel forming mucin expression.

HMEEC were exposed to the combination of NTHi and SP that displayed synergistic effect on mucin expression together with Mcat WCL. The addition of Mcat WCL did not participate in the synergistic effect between NTHi and SP but demonstrated a trend of reduction of synergistic response of both MUC2 (p= 0.0042) and MUC5AC (p=0.9673) to that of the response to Mcat alone.

DISCUSSION

Pathogen-specific influences on mucin production and particularly the development of chronic OME remains an area of significant knowledge deficit. Streptococcus pneumoniae, non-typeable Haemophilus influenza and Moraxella catarrhalis are recognized as primary pathogens identified in the middle ear of children with OME [17–18]. Studies have demonstrated that chronic OM is often a polymicrobial disease, with two or more of these most common OM pathogens participating in a middle ear infectious process at the same time [1,17,19].

Experimental evidence has accumulated revealing that these concurrent pathogens have symbiotic relationships enhancing their pathogenicity. This includes sharing of genetic information to acquire antimicrobial resistance and collaborative molecular process to improve persistence in the middle ear [20–23] However, there exists little molecular data elucidating which of these pathogens is most likely to predispose patients to the development of pathology such as middle ear epithelial (MEE) changes and up-regulation of gel forming mucins (GFM), or data examining potential synergistic effects on mucin production by common OM pathogens. The data which does exist are conflicting and hampered, in many cases, by a study design that does not account for the inadequacy of traditional culture techniques for identification of viable pathogens or an understanding of the frequency of polymicrobial infections in OM [1,24–26]. Given these areas of knowledge deficit this current data set was constructed to address the compelling question of what is the differential impact of common OM bacterial pathogens on middle ear epithelial GFM production. This work assessed this aspect of GFM response between bacterial species and within species in the controlled environment of the cell culture.

The bacterial isolates utilized in this study, NTHi-86028NP, NTHi2019, SP-D39, SPTIGR4 and Mcat-7126, were selected based upon availability of genomic sequence and co-infection data published previously [27–28]. Initial testing was completed with NTHi-86028NP and demonstrated up-regulation of transcript expression for each of the GFMs tested, MUC2, MUC5AC and MUC5B except MUC19. These experiments also showed that there was a differential response of these GFM to this pathogen with MUC5AC demonstrating a 6 to 7-fold increase compared to the doubling of expression for MUC2 and MUC5B. Understanding these differential expressions is critical in deciphering the pathophysiology of OM as each of these mucins not only plays a protective role in the underlying epithelium, but with hyper-secretion can lead to mucous-stasis and resulting hearing loss. Understanding these specific pathophysiologic events is also critical in attempting to design strategies to ameliorate the impact of increased GFM on hearing in children following inflammatory events. Similarly, the temporal relationships to bacterial exposure also demonstrate that there are difference in the regulation of these genes with MUC2 and MUC5AC demonstrating up-regulation more quickly than MUC5B. The data is also substantive in that we have identified a more robust MEE up-regulation of GFMs MUC2, MUC5AC and MUC5B compared with MUC19 using inflammatory cytokines in a previous publication [11]. Despite its large size, this relatively passive response by MUC19 to inflammatory cytokines in our previous studies, and pathogens in this current work, would suggest that other mechanistic and pathway investigations are needed to elucidate the function and interaction this GFM plays in middle ear physiology and pathophysiology.

An important objective of this current investigation was to assess the differential response of MEE GFMs to a variety of pathogens within families and between species. Our previous investigations had primarily examined the root inflammatory cytokines which are ubiquitous in infection and inflammation (TNF-α, IL-1β, IL-6, and IL-8) rather than specific pathogens [11–12, 29–32]. It is well-known that pathogens have differential infectious virulence. There have been a variety of mechanisms proposed for this virulence including ability to stimulate inflammatory pathways or escape immunologic eradication [33–34]. However, specific examinations of these pathogenic responses to mucin response have not been investigated. Given the role of GFMs in protecting underlying mucosa the experiments performed in this investigation are critical to better understand the pathogenesis of OM. The results demonstrated that of the two strains of NTHi investigated, there was a similar MUC5AC response in comparison to MUC2 and MUC5B with MUC5AC demonstrating a far greater up-regulation. And MUC5AC also demonstrated the most robust response across the spectrum of all pathogens tested. However, between families of pathogens differences were also noted with SP having a less robust up-regulation of MUC5AC and MUC2 than either NTHi or Mcat but having a more robust up-regulation of MUC5B than either NTHi or Mcat. An additional important finding was that within a family, “virulence”, at least as it pertains to mucin up-regulation, was similar in the NTHi organisms tested with NTHi-86028NP consistently having a more robust response than NTHi-2019 for MUC2 and MUC5AC. As for SP, SP-D39 demonstrated a more robust response than SP-TIGR4 for all of the mucin genes tested. These data represent a critical early understanding of the specific pathogen-host responses which exist in mucin pathophysiology. With the significant strain and serotype diversity among organism it is apparent that a single set of assumptions may not hold across a family and this may have important implications when designing therapeutic interventions. Examining across all of the data sets it was also evident that among the three bacterial species, NTHi and Mcat had the most significant impact on MUC5AC and MUC2 whereas SP demonstrated the most significant effect on MUC5B response. Given the variety of responses from various strains/serotypes a sweeping generalization cannot be made from these data. However, clinically, it has been observed that infections with Mcat have demonstrated an increased incidence of OME following infection and there is some evidence in this data set that Mcat may indeed play an important role in greater mucin gene up-regulation with potential downstream implications on hearing [35]. The data in this current investigation is the first to provide some controlled evidence experimentally to support these previous clinical observations.

We also explored the synergistic effect of polymicrobial exposure on GFM expression when combining different NTHi and SP pathogens. There has been some study of the impact of multiple bacteria showing an up-regulation of MUC5AC. This investigation demonstrated MUC2 also displayed increased gene expression due to synergistic interactions among multiple pathogens. However, it is critical to note that the specific pathogen combinations were important in determining the degree of synergistic effects. Again, these results are substantive in guiding future work which will require not only an assessment of potential pathways, alternative pathway signaling systems and feedback mechanisms within MEE but also pathogen-specific investigations related to mucin regulation and virulence factor characterization specifically aimed at investigating the mucin affect. Similar to the single pathogen experiments, there existed differential up-regulation of GFM with exposure to multiple pathogens and MUC5AC demonstrating the most significant synergistic up-regulation with all pathogen combinations tested. Although Mcat demonstrated robust up-regulation of both MUC2 and MUC5AC compared with other pathogens tested, it did not participate in the synergistic impact noted for NTHi and SP. Further studies to elucidate additional synergistic interactions and mechanisms involved are ongoing.

The current data, generated in an in vitro environment, provides a critical environment to rapidly and inexpensively test our hypotheses regarding mucin gene regulation and bacterial pathogens, using multiple different pathogens and combinations. However, this model lacks a well- developed submucosal or goblet cell formation and certainly lacks the immunologic components which are critical in directing pathogens and setting up pathogen-host interactions. Further in vivo animal experiments are currently underway utilizing the data obtained in these experiments to extend our understanding of pathogens and GFMs.