EDCTP Alumni Network

Fostering excellence and collaboration in the next generation of researchers

Call Career Development Fellowship (CDF)
Programme EDCTP2
Start Date 2019-03-01
End Date 2021-12-31
Project Code TMA2017CDF-1914
Status Active


The longitudinal microbiome of South African tuberculosis patients, symptomatic culture-negative controls and healthy household contacts, and its association with treatment outcome (MOSAIC)

Host Organisation

Institution Country
Stellenbosch University South Africa

Students Supervised

Type Name Title University Start Date End Date
PhD Georgina Nyawo Ms Stellenbosch University 2017 2021
PhD Tinaye Chiyaka Mr Stellenbosch University 2020 2023

Current Organisation

Stellenbosch University

Current Job Title



2019 Vice-Rector Postdoc Top 20 Award
2020 L'Oreal-UNESCO For Women in Science South African Young Talent

Students Supervised

Type Name Title University Start Date End Date
Doctoral Georgina Nyawo Ms Stellenbosch University 2017 2020
Doctoral Tinaye Chiyaka Mr Stellenbosch University 2020 2023
Postdoctoral Happy Tshivhula Dr Stellenbosch University 2022


Role Committee/board Start Date End Date
Scientific Meetings Coordinator African Microbiome Institute 2017 2019
Member Research Strategy Task Team 2022


Institution Degree Year
University of KwaZulu Natal, South Africa PhD
University of KwaZulu Natal, South Africa BMedSc (Hons) 2010-12-15
University of KwaZulu Natal, South Africa BSc 2009-12-15

Areas Of Specialisation

Tuberculosis (TB) Microbiome


Grant Code:
Source of funding:
Principal Investigator
Start Date:
End Date:


Charissa C Naidoo , PhD
Manormoney Pillay , PhD
Journal of Genetics

While the acquisition of drug resistance is often accompanied by fitness costs, Mycobacterium tuberculosis has developed mechanisms to overcome these costs in the form of compensatory mutations. In an attempt to dissect strain-specific differences in biological fitness, 10 M. tuberculosis genomes, representing F15/LAM4/KZN, Beijing, F11 and F28 genotypes were sequenced on the Illumina MiSeq platform. Drug-susceptible F15/LAM4/KZN strains differed by 43 SNPs, demonstrating that heterogeneity exists even among closely-related strains. We found unique, nonsynonymous single-nucleotide polymorphisms (SNPs) in the sigA and grcC1 genes of multidrug resistant (MDR) and XDR F15/LAM4/KZN strains, respectively. The F28 MDR strain harboured a novel ubiA mutation in combination with its embB M306I mutation, which may be related to ethambutol resistance. In addition, it possessed a low-frequency rpoC mutation, suggesting that this strain was in the process of developing compensation. In contrast, no compensatory mutations were identified in Beijing and F11 MDR strains, corroborating its low in vitro fitness. Clinical strains also harboured unique SNPs in a number of important genes associated with virulence, highlighting the need for future studies which examine the correlation of genetic variations with phenotypic diversity. In summary, whole-genome sequencing revealed the presence of fitness-compensatory mutations in F15/LAM4/KZN and F28 genotypes which predominate in MDR and/or extensively drug resistant (XDR) forms in KwaZulu-Natal, South Africa.

Charissa C Naidoo , PhD
Manormoney Pillay , PhD
Clinical Microbiology and Infection

The role of fitness in transmission of drug-resistant strains has been explored in previous studies; but has not been established for F15/LAM4/KZN strains, which were responsible for the extensively drug-resistant tuberculosis (XDR-TB) outbreak in Tugela Ferry, South Africa. The biological fitness of 15 clinical strains representing the F15/LAM4/KZN, Beijing, F11 and F28 families was determined by growth, viability and competition assays and correlated with DNA sequencing of eight genes associated with drug resistance and putative compensatory mechanisms. Similar growth rates were observed among susceptible, multidrug-resistant (MDR) and XDR strains of the KZN and F28 genotypes. In contrast, Beijing and F11 MDR strains demonstrated significantly reduced fitness. Resistant strains exhibited heterogeneous fitness profiles in competition with different susceptible strains, suggesting strain dependence. In addition, co-culture growth rates were consistently higher than independent growth rates in 13/14 competition pairs. All 14 drug-resistant strains retained viability, at a low CFU/mL, when paired with susceptible strains. The persistence of such resistant strains could consequently support the acquisition of additional drug-resistance-conferring mutations and/or the evolution of compensatory mechanisms. Frequently occurring mutations were detected in KZN and F28 resistant strains whereas, the Beijing MDR strain harboured a less common katG mutation and the F11 MDR strain had no katG mutation. Contrary to drug-resistant Beijing and F11 strains, the successful transmission of KZN strains, particularly during the outbreak, may be attributed to the presence of drug-resistance-conferring mutations associated with little or no associated fitness costs. Amplified growth in co-culture may be suggestive of in vivo trans-complementation.

Naidoo CC , author
Pillay M , author
Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
Sulaiman I , author
Wu BG , author
Li Y , author
Scott AS , author
Malecha P , author
Scaglione B , author
Wang J , author
Basavaraj A , author
Chung S , author
Bantis K , author
Carpenito J , author
Clemente JC , author
Shen N , author
Bessich J , author
Segal LN , author
The European respiratory journal
Mishra H , PhD
Reeve B , PhD
Palmer Z , MSc
Caldwell J , MPH
Dolby T , DMM
Naidoo CC , PhD
Jackson J , PhD
Schumacher S , PhD
Denkinger C , MD
Diacon , MD
van Helden , PhD
Marx F , PhD
Warren R , PhD
Theron G , PhD
The Lancet Respiratory Medicine

Background: Xpert MTB/RIF Ultra (Ultra) is a new test for tuberculosis undergoing global roll-out. We assessed the
performance of Ultra compared with Xpert MTB/RIF (Xpert) in an HIV-endemic setting where previous tuberculosis
is frequent and current test performance is suboptimal.

Methods: In this two-cohort diagnostic accuracy study, we used sputum samples from patients in South Africa to
evaluate the accuracy of Ultra and Xpert against a single culture reference standard. For the first cohort (cohort A),
we recruited adults (aged ≥18 years) with symptoms of presumptive tuberculosis at Scottsdene clinic in Cape Town,
South Africa. We collected three sputum samples from each patient in cohort A, two at the first visit of which one
was tested using Xpert and the other was tested using culture, and one sample the next morning which was tested
using Ultra. In a separate cohort of patients with presumptive tuberculosis and recent previous tuberculosis
(≤2 years) who had submitted sputum samples to the National Health Laboratory Services (cohort B), decontaminated
sediments were, after processing, randomly allocated (1:1) for testing with Ultra or Xpert. For both cohorts we
calculated the sensitivity and specificity of Ultra and Xpert and evaluated the effects of different methods of
interpreting Ultra trace results.

Findings: Between Feb 6, 2016, and Feb 2, 2018, we recruited 302 people into cohort A, all of whom provided
sputum samples and 239 were included in the head-to-head analyses of Ultra and Xpert. For cohort B, we collected
sputum samples from eligible patients who had submitted samples between Dec 6, 2016, and Dec 21, 2017, to give
a cohort of 831 samples, of which 352 were eligible for inclusion in analyses and randomly assigned to Ultra
(n=173) or Xpert (n=179). In cohort A, Ultra gave more non-actionable results (not positive or negative) than did
Xpert (28 [10%] 275 vs 14 [5%] 301; p=0·011). In the head-to-head analysis, in smear-negative patients, sensitivity of
Ultra was 80% (95% CI 64–90) and of Xpert was 73% (57–85; p=0·45). Overall, specificity of Ultra was lower than
that of Xpert (90% [84–94] vs 99% [95–100]; p=0·001). In cohort B, overall sensitivity was 92% (81–98) for Xpert
versus 86% (73–95; p=0·36) for Ultra and overall specificity was 69% (60–77) for Ultra versus 84% (78–91; p=0·005)
for Xpert. Ultra specificity estimates improved after reclassification of results with the lowest Ultra-positive
semiquantitation category (trace) to negative (15% [8–22]). In cohort A, the positive predictive value (PPV) for
Ultra was 78% (67–87) and for Xpert was 96% (87–99; p=0·004); in cohort B, the PPV for Ultra was 50% (43–57)
and for Xpert was 70% (61–78; p=0·014). Ultra PPV estimates in previously treated patients were low: at 15%
tuberculosis prevalence, half of Ultra-positive patients with presumptive tuberculosis would be culture negative,
increasing to approximately 70% in patients with recent previous tuberculosis. In cohort B, 21 (28%) of 76 samples
that were Ultra positive were rifampicin indeterminate (all trace) and, like cohort A, most were culture negative
(19 [90%] of 21).

Interpretation: In a setting with a high burden of previous tuberculosis, Ultra generated more non-actionable results and
had diminished specificity compared with Xpert. In patients with recent previous tuberculosis, a quarter of Ultra-positive
samples were indeterminate for rifampicin resistance and culture negative, suggesting that additional drug-resistance
testing will probably be unsuccessful. Our data have implications for the handling of Ultra-positive results in patients
with previous tuberculosis in high burden settings.

Naidoo CC , author
Nyawo GR , author
Wu BG , author
Walzl G , author
Warren RM , author
Segal LN , author
Theron G , author
The Lancet. Respiratory medicine
Charissa C Naidoo , PhD
Georgina R Nyawo , MMedSc
Benjamin G Wu , MD
Gerhard Walzl , PhD
Robin M Warren , PhD
Leopoldo N Segal , MD
Grant Theron , PhD
The Lancet Respiratory Medicine

The diverse microbial communities within our bodies produce metabolites that modulate host immune responses. Even the microbiome at distal sites has an important function in respiratory health. However, the clinical importance of the microbiome in tuberculosis, the biggest infectious cause of death worldwide, is only starting to be understood. Here, we critically review research on the microbiome’s association with pulmonary tuberculosis. The research indicates five main points: (1) susceptibility to infection and progression to active tuberculosis is altered by gut Helicobacter co-infection, (2) aerosol Mycobacterium tuberculosis infection changes the gut microbiota, (3) oral anaerobes in the lung make metabolites that decrease pulmonary immunity and predict progression, (4) the increased susceptibility to reinfection of patients who have previously been treated for tuberculosis is likely due to the depletion of T-cell epitopes on commensal gut non-tuberculosis mycobacteria, and (5) the prolonged antibiotic treatment required for cure of tuberculosis has long-term detrimental effects on the microbiome. We highlight knowledge gaps, considerations for addressing these knowledge gaps, and describe potential targets for modifying the microbiome to control tuberculosis.

Sulaiman I
Li Y
Scott AS
Malecha P
Scaglione B
Wang J
Basavaraj A
Chung A
Bantis K
Carpenito J
Clemente JC
Shen N
Bessich J
Rafeq S
Michaud G
Donington J
Naidoo C
Theron G
Schattner G
Garofano S
Condos R
Kamelhar D
Addrizzo-Harris D
Segal LN
European Respiratory Journal

Aspiration is associated with nontuberculous mycobacterial (NTM) pulmonary disease and airway dysbiosis is associated with increased inflammation. We examined whether NTM disease was associated with a distinct airway microbiota and immune profile. 297 oral wash and induced sputum samples were collected from 106 participants with respiratory symptoms and imaging abnormalities compatible with NTM. Lower airway samples were obtained in 20 participants undergoing bronchoscopy. 16S rRNA gene and nested mycobacteriome sequencing approaches characterised microbiota composition. In addition, inflammatory profiles of lower airway samples were examined. The prevalence of NTM+ cultures was 58%. Few changes were noted in microbiota characteristics or composition in oral wash and sputum samples among groups. Among NTM+ samples, 27% of the lower airway samples were enriched with Mycobacterium. A mycobacteriome approach identified Mycobacterium in a greater percentage of samples, including some nonpathogenic strains. In NTM+ lower airway samples, taxa identified as oral commensals were associated with increased inflammatory biomarkers. The 16S rRNA gene sequencing approach is not sensitive in identifying NTM among airway samples that are culture-positive. However, associations between lower airway inflammation and microbiota signatures suggest a potential role for these microbes in the inflammatory process in NTM disease.


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