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Influence of the airway microbiome on immune responses and Pseudomonas aeruginosa infection in Cystic Fibrosis

Es gibt keine bekannte Lungenerkrankung, die eine so frühe, chronische und intensive Entzündungsreaktion hervorruft, wie sie in den Atemwegen von Patienten mit Mukoviszidose (CF) auftritt. CF ist die häufigste tödliche autosomal-rezessiv vererbte Krankheit in der kaukasischen Bevölkerung, die durch eine Mutation im CFTR-Gen (Cystic Fibrosis Transmembrane Conductance Regulator) verursacht wird, dass für das CFTR-Protein kodiert. Defekte in diesem Protein führen zu einer epithelialen Dysfunktion und betreffen mehrere Organe, aber die Lungenpathologie ist für über 85% der Morbidität und Mortalität bei CF verantwortlich. Die CF-Lungenpathologie konzentriert sich auf die Wechselwirkungen zwischen Wirt und Erreger, wobei die CFTR-Dysfunktion Infektionen begünstigt und die Infektionen in Verbindung mit einer dysfunktionalen Immunantwort einen anhaltenden Entzündungskreislauf in Gang setzen. Dieser Teufelskreis aus Infektion und Entzündung führt schließlich zu Lungenschäden, Atemversagen und letztlich zum Tod. Die vorherrschende Infektion bei Mukoviszidose ist die durch P. aeruginosa, wobei im europäischen Durchschnitt 41% der erwachsenen Patienten infiziert sind. Bemerkenswert ist, dass das Mikrobiom der Atemwege bei Mukoviszidose polymikrobieller Natur ist. Da frühere Studien einen positiven Zusammenhang zwischen einer hohen Mikrobiom-Diversität und einer verbesserten Lungenfunktion bei Mukoviszidose festgestellt haben, wurde die Hypothese aufgestellt, dass bestimmte Kommensalen vor einer Infektion mit P. aeruginosa in den CF-Atemwegen schützen könnten. Um dies genauer zu untersuchen wurden 105 kommensale Isolate aus 32 verschiedenen Arten von Sputumproben von Patienten mit Mukoviszidose isoliert und mit einem fluoreszierenden P. aeruginosa PA01-mcherry-Stamm auf antagonistische Wirkungen bei direkten Erreger-Kommensalen-Interaktionen untersucht. Diese Isolate wurden zusätzlich auf immunmodulatorische Effekte bei Kommensal-Wirt-Pathogen-Interaktionen, unter Verwendung von BEAS-2B-Bronchialepithelzelllinien, untersucht. Ausgewählte Isolate mit schützender Wirkung wurden anschließend auf immunmodulatorische Effekte unter Verwendung von CFBE41o ΔF508-Zellen und einem natürlicheren Lungen-Präzisionsschnitt-Modell (PCLS) untersucht und die produzierten Zytokine mittels ELISA sowie mit einem Multiplex-Zytokin-Assay gemessen. Genexpressionsanalysen wurden zudem mittels qRT-PCR durchgeführt. Die zugrundeliegenden Mechanismen wurden mittels transkriptomischer Analysen, Vergleiche der gesamten Genomsequenz (WGS) und mechanischer Studien einschließlich Stoffwechselanalysen mittels Hochleistungsflüssigkeitschromatographie untersucht. Es konnte gezeigt werden, dass ausgewählte Streptokokken-Kommensal-Isolate, insbesondere Vertreter von S. mitis, S. oralis, S. cristatus, S. gordonii, S. sanguinis und S. parasanguinis, starke antagonistische Effekte auf das Wachstum von P. aeruginosa in direkten Kokulturen haben. Ausgewählte Vertreter von S. mitis, S. oralis und S. cristatus verhinderten zudem das Wachstum anderer klinischer und nicht-klinischer Isolate von P. aeruginosa, sowie anderer typischer Mukoviszidose-Erreger wie Staphylococcus aureus, Burkholderia spp., Achromobacter xylosoxidans, Proteus mirabilis, Haemophilus influenzae, Stenotrophomonas maltophilia, Enterococcus faecalis und Klebsiella pneumoniae. Eine wirksame Mukoviszidose-Therapie sollte nicht nur die Infektion, sondern auch die damit einhergehende bösartige Entzündung bekämpfen. Im Gegensatz zu den Mitgliedern der gram-negativen Neisseria spp., die die IL-8-Produktion bei einer Monoinfektion signifikant stimulierten, taten dies alle gram-positiven Kommensalen-Isolate nicht. Ausgewählte Kommensalen regulierten auch die P. aeruginosa PA01- und LPS-induzierte Produktion mehrerer entzündlicher Zytokine in menschlichen Atemwegsepithelzellen (BEAS-2B sowie CFBE41o ΔF508 und korrigierte wtCFTR) und in PCLS der Maus. Diese Ergebnisse wurden auch durch Genexpressionsanalysen bestätigt, was darauf hindeutet, dass die Immunmodulation möglicherweise durch eine veränderte TLR-Signalübertragung vermittelt wird. Transkriptomische Analysen nach Koinfektion von S. mitis Isolat 4 (SM4) und PA01 auf PCLS zeigten eine signifikante Runterregulation von Entzündungsreaktionen wie mTOR und Toll-like-Rezeptor-Signalen. Ein WGS-Vergleich zeigte, dass mehr als die Hälfte der am stärksten angereicherten Genfunktionen bei hemmenden Streptokokken-Isolaten für den Kohlenhydrat-Transport und -Stoffwechsel verantwortlich waren, während sie bei den nicht hemmenden Streptokokken-Isolaten unter den am stärksten angereicherten Genfunktionen fehlten. Mechanische Untersuchungen zeigten, dass der glykolytische Signalweg für die antipseudomonische Wirkung entscheidend ist und dass hemmende Kommensalen hemmende Wirkungen vermitteln, indem sie den pH-Wert ihrer Wachstumsmedien < 5,0 senken und Acetat > 0,2 mg/ml produzieren. Es wurde nachgewiesen, dass Acetat signifikante immunmodulatorische Effekte gegen PA01- und LPS-induzierte Entzündungsreaktionen in BEAS-2B und PCLS vermittelt. Zusammenfassend lässt sich sagen, dass ausgewählte kommensale Bakterien Schutzwirkungen in den Atemwegen von Mukoviszidose-Patienten herbeiführen, indem sie Acetat produzieren, das antipseudomonale und immunmodulatorische Wirkungen vermittelt. Einserseits direkt, indem es durch Bakterien- und Wirtszellen diffundiert und so unmittelbare Auswirkungen hat, als auch indirekt, indem es Wirtszellen dazu anregt, Bakterien effizient zu beseitigen und Entzündungen zu kontrollieren. Da die Verwendung ganzer Bakterien als Probiotika bei immungeschwächten Patienten beispielsweise bei Mukoviszidose mit einigen Herausforderungen verbunden ist, stellt die Verwendung von bakteriellen Metaboliten wie Acetat eine sicherere, einfachere und praktischere Alternative dar.:List of Abbreviations (i)
Table of Contents (iv)
1. SUMMARY (1)
1.1 Zusammenfassung (1)
1.2 ABSTRACT (3)
2. INTRODUCTION (5)
2.1 Cystic fibrosis (5)
2.2 Development of the CF lung pathology (6)
2.3 The immune response (8)
2.3.1 Innate and adaptive immunity (8)
2.3.2 Toll-like receptors (TLRs) (9)
2.4 Inflammation in CF (11)
2.4.1 Neutrophils in CF (11)
2.4.2 Macrophages in CF (12)
2.4.3 Eicosanoid metabolites in CF (12)
2.4.4 Chemokines in CF (12)
2.5 Airway sampling for microbiome studies (13)
2.6 CF airway microbiome (14)
2.6.1 The healthy lung microbiome (14)
2.6.2 Pathogenic bacterial members of the CF microbiome and pulmonary exacerbations (15)
2.6.3 Pseudomonas aeruginosa in CF (16)
2.6.4 Anaerobic CF microbiota (17)
2.6.5 Fungal CF microbiota (17)
2.6.6 Virus CF microbiota (18)
2.6.7 Commensal-pathogen interactions in CF (18)
2.7 CFTR modulators (18)
2.8 Human epithelial cell lines and murine precision-cut lung slices (PCLS) as in vitro model systems (19)
2.9 Next-generation sequencing (NGS) in CF microbiome studies (20)
2.10 Objectives of this study (21)
3. MATERIALS AND METHODS (23)
3.1 Materials (23)
3.1.1 Devices and Instruments (23)
3.1.2 Software (24)
3.1.3 Consumables (25)
3.1.4 Chemicals, Reagents, Media, and Antibiotics (26)
3.1.5 Kits (29)
3.1.6 Buffers, Media, and Solutions (30)
3.1.7 qPCR Primers (32)
3.1.8 Cell lines (33)
3.1.9 Mouse strains (33)
3.1.10 Bacteria isolates (34)
3.2 Methods (37)
3.2.1 Isolation, identification, and storage of isolates (37)
3.2.2 Pathogens-Commensals direct cocultures (38)
3.2.3 HPLC of conditioned media from bacterial isolates (40)
3.2.4 Cell-Pathogen-Commensal cocultures (41)
3.2.5 PCLS cocultures (42)
3.2.6 RNA extraction, cDNA preparation, and quantitative RT-PCR (43)
3.2.7 RNA Sequencing and Transcriptome analysis (45)
3.2.8 Bacteria DNA extraction and Whole Genome Sequencing (46)
3.2.9 Biochemistry (47)
3.2.10 Statistical analyses (49)
4. RESULTS (50)
4.1 Analysis of direct commensal-pathogen interactions (50)
4.1.1 Several streptococcal isolates inhibit the growth of P. aeruginosa with inter- and intra-species variability in the antipseudomonal effect (51)
4.1.2 Further commensal isolates that do not inhibit the growth of P. aeruginosa (54)
4.1.3 The lack of antipseudomonal effect by noninhibitory isolates is not due to insufficient cell numbers (54)
4.1.4 Fungal CF isolates in this study do not possess antipseudomonal effects (56)
4.1.5 SCAPEs (Selected Commensals with strong Anti-Pseudomonal Effects) also inhibit other P. aeruginosa strains (58)
4.1.6 SCAPEs inhibit other non-pseudomonal pathogenic CF isolates (60)
4.1.7 Inhibitory effects mediated by SCAPEs do not extend to the fungal CF isolates in this study (63)
4.2 Analysis of commensal-host-pathogen interactions using human bronchial epithelial cell lines (63)
4.2.1 Some commensal isolates are able to modulate PA01-induced IL-8 release in BEAS-2B cells (64)
4.2.2 Commensal-mediated IL-8 modulation in BEAS-2B cells is not due to PA01 growth inhibition (67)
4.2.3 Selected commensal isolates also modulate LPS-induced IL-8 release in BEAS-2B cells (68)
4.2.4 Selected S. mitis isolates also modulate IL-8 release in BEAS-2B cells induced by other CF P. aeruginosa isolates (68)
4.2.5 Selected commensal isolates modulate PA01-induced IL-8 release in CFBE41o cells (70)
4.2.6 Protective commensals need to be metabolically active to exert immunomodulatory effects (72)
4.2.7 Hydrogen peroxide produced by peroxide-producing Streptococcus spp. affects the viability of human bronchial epithelial cells (72)
4.2.8 Selected peroxide-producing Streptococcus spp. possess immunomodulatory activity when peroxide-induced cell death is prevented (75)
4.3 Analysis of commensal-host-pathogen interactions using mouse PCLS (80)
4.3.1 PCLS is more resilient against peroxide-induced loss of viability (80)
4.3.2 Selected S. mitis isolates modulate PA01-induced inflammatory response in mouse PCLS (82)
4.3.3 Immunomodulation of PA01-induced response by SM4 in PCLS is not due to active PA01 growth inhibition (84)
4.4 Analysis of the underlying mechanisms behind the streptococcal-mediated effects via transcriptome and whole genome sequencing (84)
4.4.1 Transcriptomic analyses show that SM4 downregulates signalling pathways involved in PA01-induced inflammatory responses in mouse PCLS (84)
4.4.2 Whole genome sequence comparison shows that in inhibitory commensals, most of their genes are involved in carbohydrate transport and metabolism (87)
4.5 Uncovering the mechanisms behind the observed streptococcal-mediated antipseudomonal effects (89)
4.5.1 Conditioned medium (CM) from SCAPEs inhibits the growth of P. aeruginosa and other typical CF pathogens (89)
4.5.2 Inhibitory activity of SCAPEs CM is neither heat sensitive nor proteinaceous (91)
4.5.3 Iron competition and the arginolytic pathway are not responsible for the observed inhibitory effects (91)
4.5.4 Peroxide production may contribute but does not play a major role in the antipseudomonal effects (94)
4.5.5 Several members of Streptococcus spp. mediate antipseudomonal effects via the glycolytic pathway (94)
4.5.6 Low pH plays a major role in the observed inhibition (97)
4.5.7 SCAPEs and other selected commensal isolates can mediate antipseudomonal effects by simultaneously lowering the pH and secreting acetate (98)
4.5.8 Extracellular addition of 0.5 mg/ml acetate at pH 5.0 inhibits the growth of P. aeruginosa (100)
4.5.9 Other SCFAs like propionate and butyrate at pH 5.0 also inhibit P. aeruginosa isolates (102)
4.5.10 Acetate has better antipseudomonal activity than propionate and butyrate (103)
4.6 Commensals may mediate their protective effects via acetate production (104)
4.6.1 SCFAs modulate PA01- and LPS-induced IL-8 release in BEAS-2B cells (104)
4.6.2 SCFA levels used are well below cell toxicity levels (105)
4.6.3 Acetate modulates PA01 and LPS-induced immune response in mouse PCLS (107)
5. DISCUSSION (110)
5.1 SCAPEs mediate inhibitory effects in direct commensal-pathogen interactions against P. aeruginosa and other typical CF pathogens (110)
5.1.1 Members of Streptococcus spp. mediate inter- and intra-species variability in their antipseudomonal effects (111)
5.1.2 SCAPEs inhibit other clinical and nonclinical P. aeruginosa strains as well as other typical CF pathogens (113)
5.2 Selected commensals modulate PA01- and LPS-induced inflammatory response in human airway epithelial cells and mouse PCLS (115)
5.2.1 The gram-positive commensal isolates in this study do not significantly stimulate inflammatory response in human bronchial epithelial cells and mouse PCLS (115)
5.2.2 Selected gram-positive commensal isolates modulate P. aeruginosa-triggered inflammatory response in BEAS-2B cells with inter- and intra-species variation (117)
5.2.3 Selected commensal isolates modulate P. aeruginosa-triggered inflammatory response in CFBE41o ΔF508 (120)
5.2.4 Selected S. mitis isolates modulate P. aeruginosa-induced inflammatory response in mouse PCLS (121)
5.3 Commensals exert protective effects against P. aeruginosa infection via acetate production (124)
5.3.1 Conditioned medium (CM) from selected commensal isolates need to be acidic to mediate inhibition of growth of P. aeruginosa and other typical CF pathogens (125)
5.3.2 The glycolytic pathway is important for streptococcal-mediated antipseudomonal effects (127)
5.3.3 Commensal bacteria mediate growth inhibitory effects by simultaneously lowering the pH and producing acetate (128)
5.3.4 Acetate modulates PA01- and LPS-induced inflammation in bronchial epithelial cells and PCLS (131)
5.4 Conclusions and Outlook (134)
6. DECLARATIONS (158)
6.1 Statement of Authorship (158)
6.2 Declaration of compliance (160)
7. Acknowledgements (161) / There is no known lung disease that causes such a very early, chronic, and intense inflammatory reaction as seen in the airways of patients with cystic fibrosis (CF). CF is the most common lethal autosomal recessive genetic condition in the Caucasian population caused by a mutation in the cystic fibrosis transmembrane conductance regulator (CFTR) gene encoding for the CFTR protein. Defects in this protein result into epithelial dysfunction and affect several organs but lung pathology accounts for over 85% of CF morbidity and mortality. The CF lung pathology centers on the host-pathogen interactions where CFTR dysfunction predisposes to infections and the infections coupled with a dysfunctional immune response drive a sustained inflammatory cycle. This vicious cycle of infection and inflammation ultimately results in lung damage, respiratory failure and then, death. The most predominant infection in CF is by P. aeruginosa with an overall European average of 41.0% of adult patients infected. Of note, airway microbiome in CF is of polymicrobial nature. Given that previous studies have established positive correlations between a high microbiome diversity and improved lung function in CF, it was hypothesized that certain commensals may be protective against P. aeruginosa infection in the CF airways. Therefore, 105 commensal isolates from 32 different species were isolated from sputum samples of patients with CF and screened for antagonistic effects in direct pathogen-commensal interactions using a fluorescent P. aeruginosa PA01-mcherry strain. These isolates were also screened for immunomodulatory effects in commensal-host-pathogen interactions using BEAS-2B bronchial epithelial cell lines. Selected isolates with protective effects were subsequently screened for immunomodulatory effects using CFBE41o ΔF508 cells and a more natural precision-cut-lung-slices (PCLS) model and the produced cytokines were measured via ELISA as well as via a multiplex cytokine assay. Gene expression analyses were also conducted via qRT-PCR. Underlying mechanisms were explored via transcriptomic analyses, whole genome sequence (WGS) comparisons, and mechanistic studies including metabolic analyses via high-performance liquid chromatography. It was demonstrated that selected streptococcal commensal isolates, especially members belonging to S. mitis, S. oralis, S. cristatus, S. gordonii, S. sanguinis, and S. parasanguinis, mediate potent antagonistic effects against the growth of P. aeruginosa in direct cocultures. Selected members from S. mitis, S. oralis, and S. cristatus also prevented the growth of other P. aeruginosa clinical and nonclinical isolates as well as other typical CF pathogens including Staphylococcus aureus, Burkholderia spp., Achromobacter xylosoxidans, Proteus mirabilis, Haemophilus influenzae, Stenotrophomonas maltophilia, Enterococcus faecalis, and Klebsiella pneumoniae. An effective CF therapy should not only address infection but the accompanying vicious inflammation as well. Unlike the members of the gram-negative Neisseria spp. which significantly stimulated IL-8 production in mono-infection, all the gram-positive commensal isolates did not. Selected commensals also modulated P. aeruginosa PA01- and LPS-induced production of several inflammatory cytokines in human airway epithelial cells (BEAS-2B as well as CFBE41o ΔF508 and corrected wtCFTR) and in mouse PCLS. These findings were also confirmed via gene expression analyses indicating that the immunomodulation may be mediated by altered TLR signalling. Transcriptomic analyses after co-infection of S. mitis isolate 4 (SM4) and PA01 on PCLS revealed a significant downregulation of inflammatory responses such as mTOR and toll-like receptor signalling. WGS comparison showed that over half of the most enriched gene functions in inhibitory streptococcal isolates were responsible for carbohydrate transport and metabolism but were absent among the most enriched gene functions for the noninhibitory streptococcal isolates. Mechanistic investigations demonstrated that the glycolytic pathway was essential for antipseudomonal effects and that inhibitory commensals mediate inhibitory effects by lowering the pH of their growth media < 5.0 and producing acetate > 0.2 mg/ml. Acetate was demonstrated to mediate significant immunomodulatory effects against PA01- and LPS-induced inflammatory response in BEAS-2B and PCLS. In conclusion, selected commensal bacteria induce protective effects in the CF airway by producing acetate, which mediates antipseudomonal and immmunomodulatory activities both directly by diffusing across bacterial and host cells to mediate direct effects as well as indirectly by stimulating host cells to clear bacteria efficiently and control inflammation. Given that the use of whole bacteria as probiotics in immunocompromised patients like in CF possesses several challenges, the use of bacterial metabolites like acetate presents a safer, easier, and more practical alternative.:List of Abbreviations (i)
Table of Contents (iv)
1. SUMMARY (1)
1.1 Zusammenfassung (1)
1.2 ABSTRACT (3)
2. INTRODUCTION (5)
2.1 Cystic fibrosis (5)
2.2 Development of the CF lung pathology (6)
2.3 The immune response (8)
2.3.1 Innate and adaptive immunity (8)
2.3.2 Toll-like receptors (TLRs) (9)
2.4 Inflammation in CF (11)
2.4.1 Neutrophils in CF (11)
2.4.2 Macrophages in CF (12)
2.4.3 Eicosanoid metabolites in CF (12)
2.4.4 Chemokines in CF (12)
2.5 Airway sampling for microbiome studies (13)
2.6 CF airway microbiome (14)
2.6.1 The healthy lung microbiome (14)
2.6.2 Pathogenic bacterial members of the CF microbiome and pulmonary exacerbations (15)
2.6.3 Pseudomonas aeruginosa in CF (16)
2.6.4 Anaerobic CF microbiota (17)
2.6.5 Fungal CF microbiota (17)
2.6.6 Virus CF microbiota (18)
2.6.7 Commensal-pathogen interactions in CF (18)
2.7 CFTR modulators (18)
2.8 Human epithelial cell lines and murine precision-cut lung slices (PCLS) as in vitro model systems (19)
2.9 Next-generation sequencing (NGS) in CF microbiome studies (20)
2.10 Objectives of this study (21)
3. MATERIALS AND METHODS (23)
3.1 Materials (23)
3.1.1 Devices and Instruments (23)
3.1.2 Software (24)
3.1.3 Consumables (25)
3.1.4 Chemicals, Reagents, Media, and Antibiotics (26)
3.1.5 Kits (29)
3.1.6 Buffers, Media, and Solutions (30)
3.1.7 qPCR Primers (32)
3.1.8 Cell lines (33)
3.1.9 Mouse strains (33)
3.1.10 Bacteria isolates (34)
3.2 Methods (37)
3.2.1 Isolation, identification, and storage of isolates (37)
3.2.2 Pathogens-Commensals direct cocultures (38)
3.2.3 HPLC of conditioned media from bacterial isolates (40)
3.2.4 Cell-Pathogen-Commensal cocultures (41)
3.2.5 PCLS cocultures (42)
3.2.6 RNA extraction, cDNA preparation, and quantitative RT-PCR (43)
3.2.7 RNA Sequencing and Transcriptome analysis (45)
3.2.8 Bacteria DNA extraction and Whole Genome Sequencing (46)
3.2.9 Biochemistry (47)
3.2.10 Statistical analyses (49)
4. RESULTS (50)
4.1 Analysis of direct commensal-pathogen interactions (50)
4.1.1 Several streptococcal isolates inhibit the growth of P. aeruginosa with inter- and intra-species variability in the antipseudomonal effect (51)
4.1.2 Further commensal isolates that do not inhibit the growth of P. aeruginosa (54)
4.1.3 The lack of antipseudomonal effect by noninhibitory isolates is not due to insufficient cell numbers (54)
4.1.4 Fungal CF isolates in this study do not possess antipseudomonal effects (56)
4.1.5 SCAPEs (Selected Commensals with strong Anti-Pseudomonal Effects) also inhibit other P. aeruginosa strains (58)
4.1.6 SCAPEs inhibit other non-pseudomonal pathogenic CF isolates (60)
4.1.7 Inhibitory effects mediated by SCAPEs do not extend to the fungal CF isolates in this study (63)
4.2 Analysis of commensal-host-pathogen interactions using human bronchial epithelial cell lines (63)
4.2.1 Some commensal isolates are able to modulate PA01-induced IL-8 release in BEAS-2B cells (64)
4.2.2 Commensal-mediated IL-8 modulation in BEAS-2B cells is not due to PA01 growth inhibition (67)
4.2.3 Selected commensal isolates also modulate LPS-induced IL-8 release in BEAS-2B cells (68)
4.2.4 Selected S. mitis isolates also modulate IL-8 release in BEAS-2B cells induced by other CF P. aeruginosa isolates (68)
4.2.5 Selected commensal isolates modulate PA01-induced IL-8 release in CFBE41o cells (70)
4.2.6 Protective commensals need to be metabolically active to exert immunomodulatory effects (72)
4.2.7 Hydrogen peroxide produced by peroxide-producing Streptococcus spp. affects the viability of human bronchial epithelial cells (72)
4.2.8 Selected peroxide-producing Streptococcus spp. possess immunomodulatory activity when peroxide-induced cell death is prevented (75)
4.3 Analysis of commensal-host-pathogen interactions using mouse PCLS (80)
4.3.1 PCLS is more resilient against peroxide-induced loss of viability (80)
4.3.2 Selected S. mitis isolates modulate PA01-induced inflammatory response in mouse PCLS (82)
4.3.3 Immunomodulation of PA01-induced response by SM4 in PCLS is not due to active PA01 growth inhibition (84)
4.4 Analysis of the underlying mechanisms behind the streptococcal-mediated effects via transcriptome and whole genome sequencing (84)
4.4.1 Transcriptomic analyses show that SM4 downregulates signalling pathways involved in PA01-induced inflammatory responses in mouse PCLS (84)
4.4.2 Whole genome sequence comparison shows that in inhibitory commensals, most of their genes are involved in carbohydrate transport and metabolism (87)
4.5 Uncovering the mechanisms behind the observed streptococcal-mediated antipseudomonal effects (89)
4.5.1 Conditioned medium (CM) from SCAPEs inhibits the growth of P. aeruginosa and other typical CF pathogens (89)
4.5.2 Inhibitory activity of SCAPEs CM is neither heat sensitive nor proteinaceous (91)
4.5.3 Iron competition and the arginolytic pathway are not responsible for the observed inhibitory effects (91)
4.5.4 Peroxide production may contribute but does not play a major role in the antipseudomonal effects (94)
4.5.5 Several members of Streptococcus spp. mediate antipseudomonal effects via the glycolytic pathway (94)
4.5.6 Low pH plays a major role in the observed inhibition (97)
4.5.7 SCAPEs and other selected commensal isolates can mediate antipseudomonal effects by simultaneously lowering the pH and secreting acetate (98)
4.5.8 Extracellular addition of 0.5 mg/ml acetate at pH 5.0 inhibits the growth of P. aeruginosa (100)
4.5.9 Other SCFAs like propionate and butyrate at pH 5.0 also inhibit P. aeruginosa isolates (102)
4.5.10 Acetate has better antipseudomonal activity than propionate and butyrate (103)
4.6 Commensals may mediate their protective effects via acetate production (104)
4.6.1 SCFAs modulate PA01- and LPS-induced IL-8 release in BEAS-2B cells (104)
4.6.2 SCFA levels used are well below cell toxicity levels (105)
4.6.3 Acetate modulates PA01 and LPS-induced immune response in mouse PCLS (107)
5. DISCUSSION (110)
5.1 SCAPEs mediate inhibitory effects in direct commensal-pathogen interactions against P. aeruginosa and other typical CF pathogens (110)
5.1.1 Members of Streptococcus spp. mediate inter- and intra-species variability in their antipseudomonal effects (111)
5.1.2 SCAPEs inhibit other clinical and nonclinical P. aeruginosa strains as well as other typical CF pathogens (113)
5.2 Selected commensals modulate PA01- and LPS-induced inflammatory response in human airway epithelial cells and mouse PCLS (115)
5.2.1 The gram-positive commensal isolates in this study do not significantly stimulate inflammatory response in human bronchial epithelial cells and mouse PCLS (115)
5.2.2 Selected gram-positive commensal isolates modulate P. aeruginosa-triggered inflammatory response in BEAS-2B cells with inter- and intra-species variation (117)
5.2.3 Selected commensal isolates modulate P. aeruginosa-triggered inflammatory response in CFBE41o ΔF508 (120)
5.2.4 Selected S. mitis isolates modulate P. aeruginosa-induced inflammatory response in mouse PCLS (121)
5.3 Commensals exert protective effects against P. aeruginosa infection via acetate production (124)
5.3.1 Conditioned medium (CM) from selected commensal isolates need to be acidic to mediate inhibition of growth of P. aeruginosa and other typical CF pathogens (125)
5.3.2 The glycolytic pathway is important for streptococcal-mediated antipseudomonal effects (127)
5.3.3 Commensal bacteria mediate growth inhibitory effects by simultaneously lowering the pH and producing acetate (128)
5.3.4 Acetate modulates PA01- and LPS-induced inflammation in bronchial epithelial cells and PCLS (131)
5.4 Conclusions and Outlook (134)
6. DECLARATIONS (158)
6.1 Statement of Authorship (158)
6.2 Declaration of compliance (160)
7. Acknowledgements (161)

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:86083
Date19 June 2023
CreatorsTony-Odigie, Andrew
ContributorsDalpke, Alexander, Berner, Reinhard, Technische Universität Dresden
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageGerman
Typeinfo:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess
Relation10.3389/fcimb.2022.824101, 10.1101/2023.02.03.526996, info:eu-repo/grantAgreement/Mukoviszidose e. V./Research Projects to generate new knowledge relevant for CF-diagnosis and therapy/1805//Influence of the airway microbiome on immune responses and Pseudomonas aeruginosa infection in Cystic Fibrosis

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