Browsing by Author "Ah Tow, Lemese"

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    The house dust microbiota in the Drakenstein Child Health Study
    (2015) Duyver, Menna; Nicol, Mark; Ah Tow, Lemese
    Introduction: The indoor home environment comprises many niches that are occupied by bacterial communities. The composition of these bacterial communities may be influenced by numerous factors such as number of occupants, pets, season and location. Understanding the house dust microbial community is vital to understanding its' influence on human respiratory health. Aims: The aims of the studies described in this MSc dissertation were to: 1) evaluate the performance of ten commercial nucleic acid extraction kits on dust samples; 2) optimise dust removal from electrostatic dustfall collectors (EDC); 3) determine the bacterial composition of house dust using 16S rRNA gene sequencing and 4) determine those factors influencing the bacterial composition of house dust by performing bioinformatic and data analysis on the sequenced dust samples. Methods: In order to study the microbial content of house dust, an efficient DNA extraction protocol was required. Ten commercial nucleic acid purification protocols were evaluated on their ability to efficiently extract good quality DNA from very low quantities (20 mg) of wet bulk house dust. For the purpose of this study, EDCs were used to collect settled dust from homes of participants in the Drakenstein Child Health Study (DCHS). Electrostatic Dustfall Collectors were placed twice within the same household, approximately 6 months apart, spanning two seasons. The Z/R Fungal/Bacterial DNA MicroprepTM (ZMC) protocol was used to extract DNA from dust removed from EDCs. The V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq platform to determine the bacterial taxonomic composition of the house dust samples. A custom python wrapper that meshes a set of tools integrated into a computationally efficient workflow, known as the YAP pipeline was used to classify 16S rRNA sequences into bacterial taxonomies. Based on 97% sequence similarity, the pre-processed sequences were assigned to Operational Taxonomic Units (OTU). R software together with RStudio software was used for all statistical analysis and graphical representations of the data.
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    Respiratory microbes present in the nasopharynx of children hospitalised with suspected pulmonary tuberculosis in Cape Town, South Africa
    (2016) Dube, Felix S; Kaba, Mamadou; Robberts, F J Lourens; Ah Tow, Lemese; Lubbe, Sugnet; Zar, Heather J; Nicol, Mark P
    Abstract Background Lower respiratory tract infection in children is increasingly thought to be polymicrobial in origin. Children with symptoms suggestive of pulmonary tuberculosis (PTB) may have tuberculosis, other respiratory tract infections or co-infection with Mycobacterium tuberculosis and other pathogens. We aimed to identify the presence of potential respiratory pathogens in nasopharyngeal (NP) samples from children with suspected PTB. Method NP samples collected from consecutive children presenting with suspected PTB at Red Cross Children’s Hospital (Cape Town, South Africa) were tested by multiplex real-time RT-PCR. Mycobacterial liquid culture and Xpert MTB/RIF was performed on 2 induced sputa obtained from each participant. Children were categorised as definite-TB (culture or qPCR [Xpert MTB/RIF] confirmed), unlikely-TB (improvement of symptoms without TB treatment on follow-up) and unconfirmed-TB (all other children). Results Amongst 214 children with a median age of 36 months (interquartile range, [IQR] 19–66 months), 34 (16 %) had definite-TB, 86 (40 %) had unconfirmed-TB and 94 (44 %) were classified as unlikely-TB. Moraxella catarrhalis (64 %), Streptococcus pneumoniae (42 %), Haemophilus influenzae spp (29 %) and Staphylococcus aureus (22 %) were the most common bacteria detected in NP samples. Other bacteria detected included Mycoplasma pneumoniae (9 %), Bordetella pertussis (7 %) and Chlamydophila pneumoniae (4 %). The most common viruses detected included metapneumovirus (19 %), rhinovirus (15 %), influenza virus C (9 %), adenovirus (7 %), cytomegalovirus (7 %) and coronavirus O43 (5.6 %). Both bacteria and viruses were detected in 73, 55 and 56 % of the definite, unconfirmed and unlikely-TB groups, respectively. There were no significant differences in the distribution of respiratory microbes between children with and without TB. Using quadratic discriminant analysis, human metapneumovirus, C. pneumoniae, coronavirus 043, influenza virus C virus, rhinovirus and cytomegalovirus best discriminated children with definite-TB from the other groups of children. Conclusions A broad range of potential respiratory pathogens was detected in children with suspected TB. There was no clear association between TB categorisation and detection of a specific pathogen. Further work is needed to explore potential pathogen interactions and their role in the pathogenesis of PTB.