ABSTRACT
Streptococcus pneumoniae, also known as the pneumococcus, is a major cause of life- threatening bloodstream infections, and may cross the blood-brain barrier and cause meningitis. Invasive pneumococcal disease (IPD) affects all age groups, but the populations highest at risk of infection are children, the elderly, and individuals with compromised immunity. Despite the implementation of childhood immunization programs and effective antimicrobial agents, child mortality from pneumococcal meningitis still imposes a huge disease burden, even in developed countries. This study aimed to understand the differences in patterns of Streptococcus pneumoniae genome evolution through gene loss and gain events, and their effect on the propensity to cause meningitis compared to bacteremia. Streptococcus pneumoniae isolate genomes of strains retrieved from human cerebrospinal fluid (CSF) were compared to those retrieved from human peripheral blood. The two datasets were first each analyzed separately, followed by comparisons across the two subsets. Briefly, the sequences in each data subset were first broadly compared using an All vs All BLAST comparison. The BLAST results were then more accurately clustered into orthologous groups using a hidden Markov chain model algorithm called OrthoMCL. The resultant orthologous map generated was then annotated and processed using Bacterial Makeup eXplorer (BMX) to generate annotated phyletic patterns highlighting gene presence and absence. The phyletic patterns were further analyzed using the Gene Loss Mapping Engine (GLOOME) to determine the probability of genes acquisition or loss along the length of each genome in the dataset under study. The results were then analyzed to make inference of the general direction of evolution, which is gene gain or loss events, which are associated with propensity to cause meningitis or not; when comparing the meningitis and bacteremia associated data subsets. Among the known virulence proteins, putative bacteriocin transporter C39 protease domain BlpA2 and pneumococcal histidine triad protein D (bvh-11-2) showed more gene loss events in the meningitis set. The immunity protein PncB, pncF, immunity protein PncK and bacteriocin BlpO displayed more gene loss events in the bacteremia set. More gene loss events were observed in both bacteremia and meningitis sets for putative immunity protein PncM and putative membrane protein BlpL. Also, more gene gain in both sets was observed for putative uncharacterized protein PncC. There was more gene gain in bacteremia set for cell surface choline binding protein PcpA. The overall findings suggests that meningitis genomes were more conserved compared to those generated from bacteremia isolates. They highlight mechanisms that determine differences in invasive ability during infection since gene loss and acquisition primarily contribute to how bacteria genetically adapt to novel environments and diverge to form separate, evolutionarily distinct species and strains. Genetic flux can radically and rapidly increase fitness or alter some aspects of lifestyle, such as multidrug non- susceptibility.
TABLE OF CONTENTS
DECLARATION ii
DEDICATION iii
ACKNOWLEDGEMENT iv
TABLE OF CONTENTS v
LIST OF TABLES ix
LIST OF FIGURES x
LIST OF APPENDICES xi
LIST OF ABBREVIATIONS xii
ABSTRACT xiii
CHAPTER 1
INTRODUCTION
1.1 Pneumococcal infections 1
1.2 Bacteriology of Streptococcus pneumoniae 4
1.2.1 Classification of the pneumococcus 4
1.2.2 Invasive pneumococcal diseases diagnosis 4
1.3 Epidemiology of the invasive pneumococcal diseases 4
1.3.1 Geographic distribution of the invasive pneumococcal diseases 4
1.3.2 The pneumococcal disease burden 5
1.4 Aim and Objectives 6
1.4.1 Aim 6
1.4.2 Hypothesis 6
1.4.3 Objectives 6
1.5 Justification 7
CHAPTER 2
LITERATURE REVIEW
2.1 Epidemiology of the pneumococcal diseases 8
2.2 Pathogenicity of the pneumococcus 10
2.3 The pneumococcal disease management 13
2.3.1 The use of antibiotics against Streptococcus pnuemoniae 13
2.3.2 Vaccines used against Streptococcus pneumoniae 15
2.4 Pneumococcal virulence factors and vaccine candidates 18
2.5 Pneumococcal genomics and reverse vaccinology 19
2.6 Protein antigens with promising medical intervention ability 20
2.6.1 ABC transporters 20
2.6.2 Autolysin 21
2.6.3 Bacteriocin 21
2.6.4 CAAX protease 22
2.6.5 Transcriptional regulator 23
2.6.6 Competence stimulating peptide 23
2.6.7 Regulatory proteins 25
2.6.8 Response regulator 25
2.6.9 Foldase protein PrsA precursor 26
2.6.10 Heat shock protein 26
2.6.11 Histidine kinase 26
2.6.12 NADH oxidase 27
2.6.13 Enolase 28
2.6.14 Sialidase A 29
2.6.15 Pneumolysin 29
2.6.16 Serine protease 30
2.6.17 Pyruvate oxidase 30
2.6.18 Sortase 31
2.6.19 Serine/ Threonine kinase protein 31
2.6.20 Iron-compound ABC transporter 32
2.6.21 Peptide pheromone 32
2.6.22 Pneumococcal histidine triad (D and E) 33
2.6.23 Pneumococcal surface protein A 33
CHAPTER 3
MATERIALS AND METHODS
3.1 Data retrieval and preprocessing 35
3.2 Data analysis 38
3.2.1 Annotation using a reference genome 40
3.2.2 Gain Loss Mapping Engine (GLOOME) analysis 43
3.3 Visualization of the GLOOME results 44
CHAPTER 4
RESULTS
4.1 Gene gain and loss events along Streptococcus pneumoniae genomes 45
4.2 Probability of Streptococcus pneumoniae gene gain and loss 46
4.2.1 Streptococcus pneumoniae virulence factors 48
4.2.2 Comparison of genetic flux within data subsets 50
CHAPTER 5
DISCUSSION
CHAPTER 6
CONCLUSION AND RECOMMENDATIONS
REFERENCES 57
APPENDICES 74
Appendix 1: Prioritized antigens during Streptococcus pneumoniae research 74
Appendix 2: Scripts used 78
Appendix 3: Gain Loss Mapping Engine (GLOOME) 88
Appendix 4: Meningitis strains metadata 95
Appendix 5: Bacteremia strains metadata 103
Appendix 6: Meningitis ortholog files part 133
Appendix 7: Bacteremia ortholog files part 139
LIST OF TABLES
Table 1: Occurrence of pneumococcal diseases from 1995 to 2015 as reported by the Center for Disease Control and Prevention 2
Table 2: Molecular mechanisms responsible for most observed cases of pneumococcal antibiotic resistance 14
Table 3: Pneumococcal vaccine approval dates, serotypes, and general effect on pneumococcal disease 16
Table 4: PPSV23 and PCV13 vaccination recommendations for children and adults aged between 5 to 64 years of age with medical conditions 17
Table 5: PCV13 vaccination catch-up dose recommendations for healthy children under 5 years of age 58
Table 6: OrthoMCL clusters demonstration and their respective genes 39
Table 7: OrthoMCL clusters and the respective binary representation of absence or presence of genes 41
Table 8: Transposed data with orthoMCL clusters and binary form of gene presence or absence 42
Table 9: Average probability of gene gain or loss events per site in unique and shared genes in bacteremia and meningitis strains 477
Table 10: Average probability of gene gain or loss events per site in 62 strains sets of meningitis and bacteremia genomes 48
LIST OF FIGURES
Figure 1: Worldwide distribution of children < 5 years old pneumococcal deaths per 100,000 children population 9
Figure 2: Streptococcus pneumoniae colonization… 10
Figure 3: The pneumococcus transmission from nasopharynx through blood to brain, by crossing the blood brain barrier (BBB) 12
Figure 4: Competence stimulating peptide (CSP) 24
Figure 5: National Center for Biotechnology Information (NCBI) assembly database page 36
Figure 6: Gene ID, product names and their respective protein sequences 37
Figure 7: All vs All BLAST 38
Figure 8: Binary FASTA arrangement demonstration 43
Figure 9: Colour-coded gene gain demonstration data produced from GLOOME. .45
Figure 10: Colour-coded gene loss demonstration data produced from GLOOME… 46
Figure 11: Important virrulence factors and their probability of gene gain or loss in the meningitis and bacteremia subsets 49
Figure 12: Cumulative expected number of events per site 52
Figure 13: Expected value of genetic flux events box plot 53
LIST OF APPENDICES
Appendix 1: Prioritized antigens during Streptococcus pneumoniae research… 76
Appendix 2: Scripts used… 80
Appendix 3: Gain Loss Mapping Engine (GLOOME)… 90
Appendix 4: Meningitis strains metadata… 97
Appendix 5: Bacteremia strains metadata… 105
Appendix 6: Meningitis ortholog files part… 135
Appendix 7: Bacteremia ortholog files part… 141
LIST OF ABBREVIATIONS
CSF: Cerebrospinal Fluid
NCBI: National Centre for Biotechnology Information
MCL Algorithm: Markov Cluster Algorithm
CEBIB: Centre for Biotechnology and Bioinformatics
IPD: Invasive Pneumococcal Disease (s)
PCV7: 7-valent pneumococcal conjugate vaccine
PCV13: 13-valent pneumococcal conjugate vaccine
PPSV23: 23-valent pneumococcal polysaccharide vaccine
HIV: Human Immunodeficiency Virus
CDC: Centre for Disease Control and Prevention
AT: Anti-Toxins
EMBL: European Molecular Biotechnology Laboratory
BLAST: Basic Local Alignment Search Tool
WGS: Whole Genome Shotgun
GLOOME: Gain Loss Mapping Engine
BMX: Bacterial Makeup eXplorer
FDA: Food and Drug Administration
PCR: Polymerase Chain Reaction
Ply: Pneumolysin
AIDS: Acquired Immunodeficiency Syndrome
CSP: Competence Stimulating Peptide
HSP: Heat Shock Protein
CHAPTER 1
INTRODUCTION
1.1 Pneumococcal infections
Pneumococcal invasive disease (IPD) results from Streptococcus pneumoniae invasion of a host normally sterile sites, which include lungs, blood, heart, inner ear, and brain (Li et al., 2019). The population most at risk of the IPD are the children under the age of 5 years, the elderly and immunocompromised individuals (Brooks & Mias, 2018). The immunity of children is not well developed, exposing them to the risk of getting infected. Young children also have a high frequency of pneumococcal colonization due to their nature of interaction at various enclosed institutions like schools and children daycare, hence they are considered as the most likely vectors for pneumococcal strains horizontal dissemination in the community (Xu, Almudervar, Casey, & Pichichero, 2013). Immunity of the elderly (>65 years) is waning over time, hence predisposing them to the infection (Berical et al., 2016). Immunocompromised individuals include people living with HIV/AIDS, functional or anatomical asplenia, genetic immune deficiencies and people with cancer among other chronic conditions. In the year 2015 the global prevalence and case fatality rate for IPD was 36.4/100,000 and 0.68/100,000 in children under 5 years, and 107.5/100000 and 19.89 in adults aged 50 years and above, respectively (Brooks & Mias, 2018) (Table 1).
Table 1: Occurrence of pneumococcal diseases from 1997 to 2015 as reported by the Center for Disease Control and Prevention. This table shows the morbidity and mortality rates from pneumococcal diseases among different age cohorts. Table reproduced from (Brooks & Mias, 2018).
|
Year
|
1997
|
2007
|
2012
|
2014
|
2015
|
|
Age
|
Case rate
|
Death rate
|
Case rate
|
Death rate
|
Case rate
|
Death rate
|
Case rate
|
Death rate
|
Case rate
|
Death rate
|
|
<1
|
142.9
|
4.02
|
40.51
|
0.9
|
15.7
|
0.24
|
15.9
|
0.48
|
18.4
|
0.24
|
|
1
|
178.7
|
0.9
|
32.39
|
0.23
|
13.6
|
0.24
|
10.3
|
0
|
12.9
|
0.24
|
|
2-4
|
31
|
0.15
|
13.03
|
0.08
|
5.9
|
0
|
6.3
|
0.08
|
5.1
|
0.16
|
|
5-17
|
4.8
|
0.14
|
2.19
|
0.14
|
1.9
|
0.14
|
1.4
|
0.05
|
1.3
|
0
|
|
18-347
|
9.3
|
0.52
|
4.19
|
0.22
|
2.8
|
0.1
|
2.7
|
0.18
|
2.5
|
0.08
|
|
35-49
|
18.9
|
1.65
|
11.89
|
0.98
|
7.5
|
0.6
|
6.6
|
0.7
|
6.7
|
0.5
|
|
50-64
|
23.5
|
2.72
|
20.59
|
2.33
|
15.9
|
1.53
|
15.1
|
1.64
|
15
|
1.53
|
|
65-74
|
61.7
|
11.02
|
39.26
|
6.37
|
29.6
|
4.24
|
19.1
|
2.41
|
18.2
|
2.3
|
|
75-84
|
|
|
|
|
|
|
28.2
|
3.46
|
29
|
4.5
|
|
≥85
|
|
|
|
|
|
|
42.6
|
8.01
|
45.3
|
11.56
|
Invasive pneumococcal diseases can be prevented through hygiene, healthy diet and vaccination against the pneumococcus. Hygiene involves regular hand washing, body cleanliness, and proper food and drinks handling as defined by the Food and Drug Administration (FDA) (The FDA Food Safety Modernization Act, 2011). Healthy diet is achieved through proper preparation and storage of food to ensure maximum preservation of the nutrients and prevention of food contaminants to help in boosting immunity (Magni et al., 2017). Antibiotics can be used to prevent pneumococcal infections through reduction of bacterial load by inhibiting growth of, or killing the bacteria (Bistrović et al., 2018). Penicillin was initially the preferred antibiotic against Streptococcus pneumoniae, discovered by Alexander Fleming in 1928, and paving way for development of other antibiotics (Berical et al., 2016). Pneumococci develop resistance to antibiotics with continued use and transmit the resistant genes with their progeny, creating a need for the development of novel antibiotics (van der Poll & Opal, 2009). Vaccination can also be used for prevention of pneumococcal diseases. There is a regimen for pneumococcal vaccines given to all children under 5 years incorporated in childhood immunization schedules. The seven-valent pneumococcal conjugate vaccine (PCV7) is among the vaccines developed and approved for children in the year 2000, with a marked improvement to disease depletion, showing 64% decrease in < 2 years old children and 54% decrease in > 65 years old adults by 2005 (Berical et al., 2016). The thirteen-valent pneumococcal conjugate vaccine (PCV13) was also approved in the year 2010 for use in children as young as 6 weeks. The continued vaccine evolution and development, led to an increase in occurrence of IPD by nonvaccine serotypes, which prompted for more readjustments and specifications in the childhood administration strategies of the vaccines (Gerdes, 2013; Plumptre et al., 2013).
1.2 Bacteriology of Streptococcus pneumoniae
1.2.1 Classification of the pneumococcus
Streptococcus pneumoniae is a gram-positive, facultative anaerobic bacteria and it’s common for its highly invasiveness nature (Tomos, n.d.). This bacterium is an alpha-hemolytic (α- hemolytic) pathogen when under aerobic conditions and beta-hemolytic (β-hemolytic) when under anaerobic conditions (Hajaj et al., 2012).
1.2.2 Invasive pneumococcal diseases diagnosis
In addition to clinical signs and symptoms, a Gram-positive stain and laboratory culture of a sample collected from the either peripheral blood, CSF, nasopharynx or middle ear is used to diagnose invasive pneumococcal diseases. Polymerase chain reaction (PCR) is among the most significant rapid methods to perform a molecular-based detection and differentiation of Streptococcus pneumoniae. However, PCR may be susceptible to contamination and inhibitors, which could lead to misdiagnosis (Yamamoto, 2002).
1.3 Epidemiology of the invasive pneumococcal diseases
1.3.1 Geographic distribution of the invasive pneumococcal diseases
IPD cover a wide geographical region affecting both developed and developing countries with Africa having the highest incidences (O’Brien et al., 2009). The incidence of IPD in Asia and Latin America is reported to be higher compared to North America and Europe. Children are the main carriers of Streptococcus pneumonia bacteria, especially in developing countries and among some indigenous societies of the developed countries (World Health Organization, 2019). The incidence of IPD and age distribution of cases among children may vary in different
countries depending on the socio-economic status. More specifically, the incidence of meningitis correlate with child mortality rate and varies geographically (O’Brien et al., 2009). Geographical region is among the factors associated with the prevalence of the known > 90 Streptococcus pneumonia serotypes, with less serotypes being associated with IPD morbidity over time, due to effective vaccines intervention (van der Poll & Opal, 2009; World Health Organization, 2019).
1.3.2 The pneumococcal disease burden
Globally, the prevalence of pneumococcal diseases is approximately 14 million cases annually (Benard Kulohoma, 2012; O’Brien et al., 2009) and approximately 300, 000 deaths each year in 0-59 months old children(Wahl et al., 2018). Despite the development of better interventions, that includes antibiotics and vaccines to prevent and manage IPD, there is still continuous need for novel IPD mitigating strategies. This is because of the antibiotic efficacy being challenged by increased antibiotics resistance (Brooks & Mias, 2018), and the bacteria are also able to escape the vaccine (Brueggemann et al., 2013).
1.4 Aim and Objectives
1.4.1 Aim
This study aimed to highlight differences in patterns of Streptococcus pneumoniae genome evolution associated with gene loss and gene gain that leads to the propensity to cause meningitis compared to bacteremia.
1.4.2 Hypothesis
Pneumococci with a propensity to cause meningitis display a different pattern of genetic flux compared to those that cause bacteremia.
1.4.3 Objectives
1. To establish the cumulative number of gene gain and loss events along the genomes of pneumococci associated with bacteremia compared to those associated with meningitis
2. To establish the probability of gene gain and loss for all genes, core genes and accessory genes in the genomes of pneumococci associated with bacteremia compared to those associated with meningitis
1.5 Justification
Streptococcus pneumoniae are commensal bacteria found on human nasopharynx of healthy individuals (Benard Kulohoma, 2012). However, this bacteria can invade the host’s normally sterile compartments (blood, middle ear, lungs and CSF) and lead to invasive pneumococcal diseases that comprise; bacteremia, pneumonia, otitis media and meningitis (Feldman & Anderson, 2014; Ogunniyi et al., 2012; Orihuela et al., 2004). Streptococcus pneumoniae display resistance to multiple antibiotics due its rapid genetic mutation hence prompting continuous research (Marks et al., 2012). Pneumococcal multidrug resistance threatens to reverse gains made in disease management and continuous analyses are required to understand mechanisms involved in development multiple lineages capable of circumventing current interventions (Pan et al., 2018). Although evolutionary biology and the population genetics of the pneumococcus is well understood, it remains unclear how some pneumococci are able to breach the blood-brain-barrier and cause meningitis, while others are not. Meningitis, a severe form of IPD, is associated with high mortality and permanent neurological impairment (Meichanetzidis et al., 2018). There is limited knowledge on the genetics of Streptococcus pneumoniae associated with the propensity to cause meningitis (Li et al., 2019). This study improves knowledge on Streptococcus pneumoniae genetic makeup as well as gene gain and gene loss events in bacteremia and meningitis causing strains, and their ability to facilitate breaching the blood-brain barrier. This study characterizes the gene gain and gene loss in a global collection of invasive Streptococcus pneumoniae isolate genomes. The findings highlight different patterns associated with mechanisms that determine differences in invasiveness during infection since gene loss and acquisition primarily contribute to how bacteria genetically adapt to novel environments and diverge to form separate, evolutionarily distinct species and strains.
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