Diverse Molecular Genotypes of Mycobacterium tuberculosis Complex Isolates Circulating in the Free State, South Africa

DM-PhyClus: a Bayesian phylogenetic algorithm for infectious disease transmission cluster inference

Background

Conventional phylogenetic clustering approaches rely on arbitrary cutpoints applied a posteriori to phylogenetic estimates. Although in practice, Bayesian and bootstrap-based clustering tend to lead to similar estimates, they often produce conflicting measures of confidence in clusters. The current study proposes a new Bayesian phylogenetic clustering algorithm, which we refer to as DM-PhyClus (Dirichlet-Multinomial Phylogenetic Clustering), that identifies sets of sequences resulting from quick transmission chains, thus yielding easily-interpretable clusters, without using any ad hoc distance or confidence requirement.

Results

Simulations reveal that DM-PhyClus can outperform conventional clustering methods, as well as the Gap procedure, a pure distance-based algorithm, in terms of mean cluster recovery. We apply DM-PhyClus to a sample of real HIV-1 sequences, producing a set of clusters whose inference is in line with the conclusions of a previous thorough analysis.

Conclusions

DM-PhyClus, by eliminating the need for cutpoints and producing sensible inference for cluster configurations, can facilitate transmission cluster detection. Future efforts to reduce incidence of infectious diseases, like HIV-1, will need reliable estimates of transmission clusters. It follows that algorithms like DM-PhyClus could serve to better inform public health strategies.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2347-3) contains supplementary material, which is available to authorized users.

Diversity of Mycobacterium tuberculosis Complex from Cattle Lymph Nodes in Eastern Cape Province

Tuberculosis (TB) remains a major health challenge in South Africa and the condition in humans has been well researched and documented. However, investigations on the circulating Mycobacterium tuberculosis complex (MTBC) strains from cattle in the Eastern Cape Province of South Africa are insufficient. This study delineated the diversity of MTBC isolates from cows' lymph nodes. A total of 162 MTBC isolates, collected over a one-year period from cattle lymph nodes from two abattoirs, were submitted to spoligotyping and 12 MIRU-VNTR typing. The spoligotyping results were matched with isolates in the universal spoligotyping database (SITVIT2). Our study identified 27 spoligotype patterns, with 10 shared types assigned to five lineages: the East-Asian (Beijing) was predominant, 17.9%, and East-Asian (Microti) and Latin-American-Mediterranean S were the least detected with 0.6%. Spoligotyping showed a higher clustering rate of 82.1%, with the lowest being the Hunter-Gaston Diversity Index (HGDI) of 0.485; 12 MIRU-VNTR resulted in a clustering rate of 64.8%, showing a higher HGDI of 0.671. The results of this study show a high diversity of MTBC strains in the Eastern Cape Province and clustering rate, which indicates ongoing transmission in the province.

Genetic diversity and distribution of Mycobacterium tuberculosis genotypes in Limpopo, South Africa

BACKGROUND

Tuberculosis remains a major health problem and knowledge of the diversity of Mycobacterium tuberculosis strains in specific geographical regions can contribute to the control of the disease. This study describes the genetic profile of M. tuberculosis in five districts of Limpopo Province.

METHODS

A total 487 isolates were collected from the National Health Laboratory Services from all regions/districts of Limpopo Province. Only 215 isolates were confirmed to be M. tuberculosis by Bactec Mycobacterium Growth Indicator Tube 960® and Rhodamine-Auramine staining. Isolates were subcultured on Löwenstein-Jensen medium agar slants to validate purity. They were spoligotyped and data analysed using the international spoligotyping database 4 (SpolDB4).

RESULTS

Of the 215 isolates, 134 (62.3%) were genotyped into 21 genotype families while 81 (37.7%) were orphans. The 81 orphans were further subjected to resolution employing SpolDB3/RIM. Overall, the study revealed a high diversity of strains of 32 predominantly the non-Beijing lineages: the LAM- LAM3 (9.8%), LAM9 (4.7%) and LAM11- ZWE (3.3%), the T-T1(15.0%), T2 (0.9%), T2-T3 (1.4%), the CAS-CAS1-Delhi 5 (1.9%) and CAS1-KILI (1.4%) the MANU2 (1.4%), U (0.5%), X-X1(1.4%), X3 (1.9%), S (9.8%), CAS (1.4%), LAM7(0.9%), T3(0.5%), LAM8(4.7%), T4(1.4%), X2(0.4%), AI5(1.9%), LAM1(0.5%), FAMILY33 (1.9%), EAI4(1.4%), M. microti (1.9%). The Beijing and Beijing-like families were (14.9%) and (0.9%), respectively. A total of 28(13%) clusters and 77(36%) unique cases were identified. Beijing strain (SIT 1) formed the biggest cluster constituting 14%, followed by LAM3 (SIT 33), T1 (SIT 53) and LAM4 (SIT 811) with 7%, 5.1% and 2.8%, respectively. The Beijing family was the only genotype found in all the five districts and was predominant in Mopani (18.8%), Sekhukhune (23.7%) and Vhembe (23.3%). Dominant genotypes in Capricorn and Waterberg were LAM3 (11.9%) and T1 (13.3%), respectively.

CONCLUSION

A wide diversity of lineages was demonstrated at district level. A high number of clusters per district provided evidence of on-going transmission in this Province.