Geospatial distribution of Mycobacterium tuberculosis genotypes in Africa

Abstract

Objective: To investigate the distribution of Mycobacterium tuberculosis genotypes across Africa.

Methods: The SITVIT2 global repository and PUBMED were searched for spoligotype and published genotype data respectively, of M. tuberculosis from Africa. M. tuberculosis lineages in Africa were described and compared across regions and with those from 7 European and 6 South-Asian countries. Further analysis of the major lineages and sub-lineages using Principal Component analysis (PCA) and hierarchical cluster analysis were done to describe clustering by geographical regions. Evolutionary relationships were assessed using phylogenetic tree analysis.

Results: A total of 14727 isolates from 35 African countries were included in the analysis and of these 13607 were assigned to one of 10 major lineages, whilst 1120 were unknown. There were differences in geographical distribution of major lineages and their sub-lineages with regional clustering. Southern African countries were grouped based on high prevalence of LAM11-ZWE strains; strains which have an origin in Portugal. The grouping of North African countries was due to the high percentage of LAM9 strains, which have an origin in the Eastern Mediterranean region. East African countries were grouped based on Central Asian (CAS) and East-African Indian (EAI) strain lineage possibly reflecting historic sea trade with Asia, while West African Countries were grouped based on Cameroon lineage of unknown origin. A high percentage of the Haarlem lineage isolates were observed in the Central African Republic, Guinea, Gambia and Tunisia, however, a mixed distribution prevented close clustering.

Conclusions: This study highlighted that the TB epidemic in Africa is driven by regional epidemics characterized by genetically distinct lineages of M. tuberculosis. M. tuberculosis in these regions may have been introduced from either Europe or Asia and has spread through pastoralism, mining and war. The vast array of genotypes and their associated phenotypes should be considered when designing future vaccines, diagnostics and anti-TB drugs.

Fig 1. Geospatial distribution of M. tuberculosis lineages in Africa.

Each pie chart segment reflects the relative proportion of M. tuberculosis isolates belonging to respective major lineages for each country (see colour chart for the respective major lineages). Each country has been shaded according to the number of isolates contributed to the analysis (see colour intensity chart). Country codes (http://www.worldatlas.com/aatlas/ctycodes.htm).

Fig 2. Clustering of countries according the proportion of M. tuberculosis isolates present in a specific lineage.

Only data from the Beijing, Cameroon, CAS, EAI, H, LAM, Manu, and S lineages was included. Country codes according to (http://www.worldatlas.com/aatlas/ctycodes.htm). (A) Principle component analysis: African countries in the PCA plot are coloured based on their most dominant lineage: CAS (red), Cameroon (green), H (purple), LAM (brown), Manu (blue), and EAI (yellow). European and Asian countries are shown in black. Overlapping country codes in the PCA plot indicate a similar distribution of M. tuberculosis lineages in the respective countries. (B) pvclust analysis: The clusters edges are numbered in grey and the AU p-values are shown in black. Strongly supported clusters with AU greater than 95% are highlighted with a dotted line.

Fig 3. Geospatial distribution of M. tuberculosis isolates belonging to the LAM sub-lineage.

Country specific spoligotype data was only included if the country had >100 M. tuberculosis isolates and ≥15% of these isolates were from the LAM lineage. The sizes of the pie chart segments depict the proportion of isolates belonging to the different LAM sub-lineages (see colour chart for the respective sub-lineages). Each country has been shaded according to the proportion of LAM lineages isolates present in that country (see colour intensity chart). Country codes (http://www.worldatlas.com/aatlas/ctycodes.htm).

Fig 4. Clustering oof countries according the proportion of M. tuberculosis isolates belonging to different LAM sub-lineages.

(A) Principle component analysis: African countries in the PCA plot are coloured based on their most dominant LAM sub-lineage: LAM1 (blue), LAM3 (blown), LAM9 (purple), LAM11-ZIM (red). PCA plot axes have been labelled with an “L” to indicate LAM followed by the sub-lineage number. European and Asian countries are shown in black. Overlapping country codes in the PCA plot (Morocco and Italy, Tunisia and France) indicate a similar distribution of LAM sub-lineages in the respective countries. (B) pvclust analysis: The clusters edges are numbered in grey and the AU p-values are shown in black. Strongly supported clusters with AU greater than 95% are highlighted with a dotted line. Country codes (http://www.worldatlas.com/aatlas/ctycodes.htm).

Fig 5. Geospatial distribution of M. tuberculosis isolates belonging to the T sub-lineages.

Country specific spoligotype data was only included if the country had >100 M. tuberculosis isolates and ≥15% of these isolates were from the T lineage. The sizes of the pie chart segments depict the proportion of isolates belonging to the different T sub-lineages (see colour chart for the respective sub-lineages). Each country has been shaded according to the proportion of T sub-lineages isolates present in that country (see colour intensity chart). Country codes (http://www.worldatlas.com/aatlas/ctycodes.htm).

Fig 6. Clustering of countries according the proportion of M. tuberculosis isolates belonging to the T sub-lineages.

(A) Principle component analysis: African countries in the PCA plot are coloured based on their most dominant T sub-lineage: T1 (green), T2 (red), T2-Uganda (purple), T3-Ethiopia (turquoise). European and Asian countries are shown in black. Overlapping country codes in the PCA plot (South Africa and Madagascar, Gambia and Guinea Bissau, Egypt and Guinea) indicate a similar distribution of T sub-lineages in the respective countries. (B) pvclust analysis: The clusters edges are numbered in grey and the AU p-values are shown in black. Strongly supported clusters with AU greater than 95% are highlighted with a dotted line. Country codes (http://www.worldatlas.com/aatlas/ctycodes.htm).