Institutional permission to conduct the study was obtained from the Faculty Research and Ethics Committee of Makerere University Medical School (institutional ethics board of the Medical School). Informed consent to participate in the study as well as permission to use isolates from samples provided were obtained from all enrolled participants.

Patients were recruited from sputum smear positive residents in Rubaga attending four main TB clinics in the division. Sample processing, confirmatory microscopy and culture and susceptibility testing were performed at the National Tuberculosis and Reference Laboratory (NTRL); molecular assays were run at Makerere Medical School, and data analysis for spoligotyping was done at the Swedish Institute for Infectious Disease Control, Stockholm.

This was a cross sectional study in which all consecutive newly-presenting Ziehl-Neelsen (ZN) smear-positive patients between February and November 2006 aged 18 years and above were enrolled. The patient recruitment and sample collection process was done as described in our previous report 14. Briefly, all patients underwent a standardized interview and three consecutive sputum samples (spot, early morning and spot) were taken from each patient. Only the sample with the highest ZN smear grade was further analyzed for each patient. Samples were stored at 4°C at the recruitment clinics, in any case for not more than 48 hours, until transported in a cold box to the NTRL for processing, confirmatory fluorescent microscopy and culture.

Specimens (2.5–10 ml) were processed by the standard N-acetyl L-cystein (NALC)-NaOH method 15 and concentrated at 4000 × g for 15 minutes. The sediment, irrespective of the original sample volume, was reconstituted to 2.5 ml with phosphate buffer pH 6.8, to make the inoculum for the smears and cultures.

Two Lowenstein-Jensen slants, one containing 0.75% glycerol and the other containing 0.6% pyruvate, were inoculated with the sediment and incubated at 37°C. Cultures were considered negative when no colonies were seen after 8 weeks incubation. Isolates were harvested, DNA extracted using a standardized protocol 16 and confirmed as MTC by an in-house PCR 17.

Drug susceptibility testing (DST) was performed by the indirect proportion method on Lowenstein-Jensen media at the following final drug concentrations: rifampicin, 40 μg/ml and isoniazid, 0.2 μg/ml, as recommended elsewhere 18. Multi-drug resistance (MDR) was defined in accordance with standard criteria of resistance to at least isoniazid and rifampicin.

For all test panels, drug susceptible strain (H37Rv) and specific drug resistant strains (TMC 303 for isoniazid and TMC 331 for rifampicin) internal controls were included.

The NTRL successfully participates in two annual external proficiency testing programmes organized by Centers for Disease Control and Prevention (CDC) and the Supra national laboratory net work.

Standard spoligotyping 19 was done generally as described by Kamerbeek and colleagues using a commercially available kit (Isogen Bioscience BV, Maarssen, The Netherlands).

HIV-1 rapid testing was performed according to the Ministry of Health, Uganda, algorithm. Anticoagulated whole blood was immediately used for HIV rapid testing at the clinics of enrolment. Two rapid HIV tests, Unigold Recombinant HIV (Trinity Biotech, Wicklow, Ireland) and Determine HIV-1/2 (Abbott, Tokyo, Japan), were run sequentially. Samples were tested first with Abbot Determine and reported only when negative. Positive samples were confirmed with Unigold, while discordant results were resolved by a third rapid test kit, HIV-1/2 Stat-Pak (ChemBio, Medford, NY). All tests were performed and interpreted according to the manufacturers' instructions.

Spoligotypes were analysed by a BioNumerics software, version 5.0 (Applied Maths, Kortrijk, Belgium) as character types. The obtained signatures were compared in binary format with the international spoligotyping database of the Pasteur Institute of Guadeloupe. The SpolDB4 database 20 (an online version is available on http://www.pasteur-guadeloupe.fr:8081/SITVITDemo) provides information on the spoligotype international type (SIT) distributions of M. tuberculosis spoligotypes worldwide. Labels for major phylogenetic clades were assigned according to signatures provided in SpolDB4. Statistical associations between strain types, drug susceptibility data and HIV sero-status were generated by Stata 8.0 using the Pearson's chi-square test. Odds ratios were estimated at 95% confidence intervals, and a P value of < 0.05 was considered evidence of a significant difference.

Between February and November 2006, 2639 TB suspects from Rubaga division, Kampala, were screened at 4 division TB clinics. The population of Rubaga division is mainly low to middle income, and the clinics chosen are the subsidized mission founded hospitals at which a majority of the residents seek medical care. Only 386 of these suspects were sputum smear positive and enrolled. Extra samples from randomly selected patients were taken for internal quality control as generally described in our previous report 14. The demographic information of the patients shows that 163 (47.4%) of the isolates were from female patients while 181 (52.6%) were male. The sample median age was 32 with a range of 18 to 62 years. The median age among female subjects was 30 (SD 8.3) with a range of 18 to 60 years while that of the males was 34 (SD 8.6) with a range of 18–62 years. Stratification according to age showed that 267 (77.7%) of the patients were between 18 and 39 years old while 75 (22%) were between 40 and 60 years. Only 1 (0.3%) patient was over 60 years of age.

To determine the strain lineages present in the sample, the 344 isolates were spoligotyped and binary outcomes compared with those existing in SpolDB4 so as to assign spoligotype international type (SIT) designations. A total of 320 isolates, or 93% of our sample, were grouped into 33 clusters (2 to 49 isolates per cluster), while the remaining 24 (7%) of the strains did not cluster. Of these 24 strains that did not cluster, 21 did not exist in the SpolDB4.0 data base, hence represented the true orphans in the study sample. The remaining 3 of the unclustered isolates included one M. bovis strain and were all present in SpolDB4 with labels SIT 34 (S), SIT 61 (LAM10-CAM), and SIT 482 (BOV1) for the M. bovis strain.

Among the 33 clusters, seven included more than ten isolates each and were defined as major spoligotypes, while minor spoligotypes, on the other hand, were defined as spoligotype international types (SITs) that contained two to ten isolates per cluster (Figure 1). Analysis of the frequency of the spoligotypes in our study with SpolDB4.0 allowed differentiation between ubiquitous types (SIT 1, SIT 4, SIT 21, SIT 26, SIT 42, SIT 52, SIT 59, SIT 78, SIT 356, and SIT 288) and those believed to be endemic in Uganda (SIT 125, SIT 128, SIT 135, and SIT 590). Furthermore, up to 14 clusters ranging from two to seventeen isolates per cluster formed a total of 100 strains and were not yet defined in SpolDB4.0. These were labeled UGA1 (17 isolates) to UGA14 (2 isolates) (Figure 1). Seventy percent (241/344) of the isolates lacked hybridization to either spacer 40 or both 40 and 43, and these were characteristic of strains that were previously classified as M. africanum genotypes Uganda II and I respectively 21. Most (227/241) of the Uganda genotype strains formed 16 clusters (ranging 5 to 49 isolates) with 80 strains being genotype I while 147 were genotype II (Figure 1). Only 14 Uganda genotype strains did not cluster.

Overall, 4 Beijing strains (SIT 1) were identified, making 1.2% of the sample. The six major shared spoligotypes in our sample were SIT 128 or T2 with 49 isolates, SIT 135 (T2-Uganda) with 38 isolates, SIT 52 (T2) with 26 isolates, SIT 590 (T2) with 15 isolates, SIT 21 (CAS1-Kili) with 12 isolates and SIT 125 (T2) with 11 isolates. Additionally, one other major cluster of 17 isolates with a characteristic lack of hybridization to spacers 15–17 and 19–43 is not yet defined in SpolDB4.0 and was labeled UGA 1 (figure 1).

In the current sample, 92 patients (26.7%) were HIV sero-positive, 176 (51.2%) sero-negative, while 76 (22.1%) did not consent to HIV testing hence their status unknown. There was no significant difference (P = 0.116) in sero-status between female and male patients in the sample. An analysis of the predominant spoligotypes in HIV sero-positive and sero-negative patients showed that 53/92 (57.6%) of sero-positive individuals carried strains of the T2 family, while only 6.5% carried the CAS strains, 3.3% LAM3/S, and 4.3% carried unique strains. Furthermore, 138/176 (78.4%) of the HIV sero-negative individuals and 50/76 (65.8%) of those who did not consent carried the T2 family of strains. The other patients carried either minor spoligotypes or those not yet defined in SpolDB4.

Susceptibility testing results for the two key anti-tuberculosis drugs (isoniazid and rifampicin) showed that resistance to isoniazid was 28/344 (8.1%), that to rifampicin was 15/344 (4.4%), and all the rifampicin resistant isolates were also MDR, being defined as resistance to both isoniazid and rifampicin. 13 strains, including 1 Beijing genotype, were monoresistant to isoniazid. Five patients were recruited with recurrent TB, but all the isolates were susceptible. There was no relationship (p = 0.80) between MDR and HIV sero-positivity. A summary of patient demographic characteristics and associated drug susceptibility pattern is shown in Table 1.

Regarding cluster analysis in drug resistant isolates, SIT 52 (T2) had four of the 15 MDR isolates; SIT 128 (T2) three MDR isolates, while SIT 135 (T2-Uganda) had two MDR isolates. The other 6 MDR isolates were distributed as follows: one LAM9 (SIT 42), one UGA7 (T2), one UGA18 and three unique (T2) isolates. Although strains of the T2 family accounted for 13 of the fifteen MDR strains in the sample, there was no statistical relationship (p = 0.25) between this strain type and MDR. The relationship between the different spoligotypes and resistance to rifampicin, isoniazid or both is summarized in Table 2.