We report here an overview of the contents of the TB genotyping network fingerprint database, including the distribution of isolates at sentinel surveillance sites, genotype patterns that occurred with high frequency, the extent of previously described genotype families, and new families of related fingerprints. This analysis should not be considered exhaustive but rather a summary of our observations and an introduction to the types of data that can be derived.

Methods for IS6110 fingerprinting, spoligotyping, and compiling the network databases are described elsewhere (1). The distribution of isolates by sentinel surveillance site, fingerprint pattern, and spoligotype (for isolates with six or fewer copies of IS6110) was derived from the Epi Info database. The spoligotype patterns are reported in octal code by the convention previously described (2). IS6110 fingerprint patterns start with the prefix FP and spoligotype patterns with SP.

We used the BioImage Whole Band Analyzer software package version 3.4 to analyze fingerprint patterns in the genotyping network fingerprint database. The bands in two patterns were compared at two levels. First, bands in two patterns were identified as matched bands if the size of the bands differed by <2.5%. Next, the interband spacing between matched bands in the two patterns was compared; a limit of 95% for variation in interband spacing was used. The Jaccard coefficient of similarity between two patterns, A and B, was used to calculate the percentage match between two patterns: 100 x number of matched bands /(number bands in A + number bands in B - number of matched bands).

Isolates from 10,883 patients from seven sentinel surveillance sites were fingerprinted by using the IS6110 restriction fragment length polymorphism (RFLP) method: Arkansas, 709; California, 2,514; Massachusetts, 986; Maryland, 1,180; Michigan, 1,471; New Jersey, 2,113; and Texas, 1,910. From these isolates, 6,128 distinct fingerprint patterns were identified and included in the final genotyping network database. Analysis of the IS6110 copy number of the isolates confirmed the previously described bimodal distribution (Figure 1) (3). This distribution has been used to separate isolates of M. tuberculosis into two groups: isolates with six or fewer copies of IS6110 are classified as low-copy isolates and those with more than six copies as high-copy isolates. The greatest numbers of patterns occurred in the 9–14 copy-number range (Figure 1). Clustering of isolates on the basis of matching fingerprint patterns is summarized in Table 1. Clustering was very high among the low-copy isolates, which supports the requirement for secondary typing of these isolates. Clustering decreased with increasing copy number; copy numbers 21 and 22, which included large outbreaks, were the exceptions.

The 8,245 isolates with more than six copies of IS6110 yielded 5,640 fingerprint patterns. Of these patterns, 4,846 (85.9%) were identified for a single isolate, and 3,399 isolates were grouped into 794 fingerprint-defined clusters. Of these clusters, 557 contained isolates from a single site. The clusters contained up to 105 isolates, but 683 (86.0%) of the clusters contained only two to five isolates. In fact, only 18 clusters contained 20 or more isolates. The distribution of isolates in these 18 clusters is shown in Table 2, and the fingerprint patterns are shown in Figure 2. For 11 of the 18 largest clusters, >90% of the isolates in the cluster were from a single site.

One of the largest clusters (FP 00237, 100 isolates) corresponds to M. tuberculosis strain 210, a member of the W-Beijing family that was shown in previous studies to be disseminated across the United States (3). In the network, FP 00237 was associated with large clusters in Arkansas and Texas and was also reported by Maryland and New Jersey. Two additional patterns associated with large clusters, FP 00027 (102 isolates in Michigan) and FP 01284 (46 isolates in Texas), were similar to FP 00237. The Beijing family of strains has received considerable attention because of its association with several large outbreaks, frequent association with multidrug resistance, and emergence in selected populations, particularly in the former Soviet Union (4,5). All Beijing isolates share a characteristic spoligotype (000000000003771); however, in this study, spoligotyping was not performed for high-copy isolates. Other molecular criteria that define W-Beijing strains include insertions of IS6110 in the dnaA-dnaN region (A1 insertion) and in the NTF region and an empirical fingerprint pattern that contains 15 to 24 bands and is similar to that of strain W (4). To estimate the occurrence of Beijing isolates in our study, all patterns with 16 to 24 bands were visually compared to FP 00237. The W fingerprint was easily identified among the patterns with 17 or more bands; however, we were less confident about identifying it in those with 16 bands and did not include them in this analysis. Of the 688 patterns analyzed, 497 (72.2%) were similar to FP 00237. Examples can be seen in Figure 3. Nearly all of the individual patterns, 480 (97%), were reported by a single site. These 497 patterns represent 946 isolates, 82% of all isolates with >17 copies of IS6110 and 9% of all isolates in the study (Arkansas, 3%; Maryland, 4%; New Jersey, 7%; Massachusetts, 9%; and California, Michigan, and Texas, 11%). The distribution of these isolates by site is reported in Table 3.

Because only one of the molecular criteria (overall fingerprint pattern) could be applied, isolates with these patterns cannot be definitively called W-Beijing. All of the insertion sites in strain 210, FP 00237, have been defined by sequencing (6). To identify conserved insertion sites, we determined the percentage of the 497 patterns that contained each of the bands in FP 00237 (Figure 4). Nine bands were found in >50% of the patterns, and two were present in >85%. A common feature of these fingerprint patterns is a group of smaller bands (1.0 to 1.5 kb) that are difficult to resolve. Variation in band identification resulted in some of the heterogeneity of the patterns in the database. W-Beijing strains likely account for a large portion of Beijing isolates, but other Beijing strains exist. FP 00242 (reported for 96 isolates in Texas; fingerprint pattern shown in Figure 2) shares only a few bands with FP 00237, but isolates with this pattern have the Beijing spoligotype (Teresa Quitugua, pers. comm.).

To identify other large families in the database, we analyzed all patterns having 6 to 15 bands (4,846 patterns). Since the BioImage software cannot create a dendrogram for more than 1,250 patterns, patterns were compared to each other by using an arbitrarily chosen matching threshold of 50% to identify those that matched a large number of other patterns. For a 50% match, two thirds of the bands in two patterns with equal band number must match. Six sets of related fingerprints, designated A through F, were defined; each consisted of six prototype patterns (Figure 5) along with all of the patterns that matched the prototypes. Data on these sets are summarized in Table 3. The isolates in each set appear widely dispersed across the sites, and the patterns likely represent endemic strains in the United States. Key bands in each set were determined in comparison to the common bands in the prototype patterns as described above for FP 00237 (Figure 4). Sequencing the IS6110 insertion sites corresponding to these key bands would allow isolates belonging to these sets to be rapidly identified with microarray techniques or the reverse dot-blot (“insite”) assay we have described previously (7).

The sets described here are certainly not the only sets of related patterns in the database, nor are they necessarily novel. The patterns in set A are similar to the patterns for M. tuberculosis strains H37Rv and H37Ra (8); the eight common bands in the prototype patterns for set A are also found in the patterns for these two laboratory strains. The patterns in set D appear similar to those of the Haarlem family (9). Interestingly, 1,404 (29.0%) of the patterns with 6 to 15 bands did not match any other pattern at the 50% matching threshold, suggesting a substantial number of orphan strains in this study.

The TB genotyping network database demonstrates the diversity of strains that cause TB in the United States. The 10,883 patients in the study represented approximately 11.6% of all new cases of TB in the United States from 1996 through 2000. The sentinel sites were reasonably representative of the geographic and demographic diversity in the United States. Compiling this database from results submitted from seven laboratories was a considerable undertaking, and analyzing such a large collection of fingerprint patterns is difficult. From our quality assurance program and personal experience, we know that, even under the most carefully controlled conditions, IS6110 fingerprinting results are not 100% reproducible. We are certain that some of the fingerprint patterns, which were classified as different and received different designations, would have been identical had they been run side by side on the same gel. Also, as we have described, some fingerprint patterns for low-copy isolates appear identical but do not represent the same IS6110 insertions and thus do not represent closely related strains. Some of these difficulties resulted from the application of a rigid standard for defining distinct patterns, a process that is often subjective.

Even though some individual results may have been questionable, several clear conclusions emerged. Large sets of strains with related fingerprint patterns, not previously recognized, are spread across the United States. Given the rather slow rate of change in fingerprints, these must represent endemic strains that have circulated in the United States for decades. Consistent with this conclusion is the presence in the database of fingerprint patterns resembling the pattern of the laboratory strain H37 that was originally isolated in New York in 1905 (8). Many of the patterns in these sets represent single isolates, which suggests that they are the result of reactivation of remote infections acquired years or decades earlier. Analysis of the demographic characteristics of the patients will be required to confirm this observation. Among these large sets, outbreak strains (patterns) were generally restricted to a single sentinel site, as were clustered isolates in general.

We conclude that a large-scale, prospective comparison of fingerprint patterns from wide geographic regions is useful for research studies but is of limited value for TB control purposes. Comparisons of isolates from smaller areas are not only more meaningful but also more feasible. This limitation does not mean that searching multiple databases for specific fingerprint patterns, for example the “W” strain, is not useful in some circumstances.

The difficulties in analyzing IS6110 fingerprint patterns and the often slow turnaround time for obtaining results limit the value of this procedure to TB control programs. As an alternative, rapid, polymerase chain reaction–based testing, such as spoligotyping or mycobacterial interspersed repetitive units variable number of tandem repeats (MIRU-VNTR) analysis, would be a logical first step for universal genotyping of isolates. These methods provide greater reproducibility and give digital results, which simplify analysis. However, this approach has the following limitations. Many common spoligotypes were seen among low-copy-number isolates, although even IS6110 fingerprinting does not greatly improve resolution with these isolates. We also found that 9% of the isolates have W-Beijing fingerprint patterns that are known to have the same spoligotype; all isolates yielding the Beijing spoligotype would require IS6110 typing. Sufficient data are not available to predict the discriminatory power of MIRU-VTNR. However, preliminary results suggest that the combination of spoligotyping and VNTR typing will provide adequate resolution for most uses, thus limiting the need for additional typing by IS6110 fingerprinting.