| Literature DB >> 26323435 |
Dan Wamala1,2, Moses Okee3, Edgar Kigozi4, David Couvin5, Nalin Rastogi6, Moses Joloba7, Gunilla Kallenius8.
Abstract
BACKGROUND: In Uganda, the emerging Uganda genotype of Mycobacterium tuberculosis is the most common cause of pulmonary tuberculosis (PTB), and accounts for up to 70% of isolates. Extrapulmonary TB (EPTB) is less studied in Uganda.Entities:
Mesh:
Year: 2015 PMID: 26323435 PMCID: PMC4556223 DOI: 10.1186/s13104-015-1362-y
Source DB: PubMed Journal: BMC Res Notes ISSN: 1756-0500
Description of 36 SITs and corresponding spoligotyping defined lineages/sublineages starting from a total of 121 M. tuberculosis strains isolated in Kampala, Uganda
aNewly created SITs are marked by lowercase alphabet a. Country distribution for newly created SITs was as follows: SIT4059a, n = 2 this study; SIT4060a, n = 1 this study, n = 1 PRT; SIT4061a n = 2 this study; SIT4062a n = 1 this study, n = 1 ZMB
bLineage designations according to SITVIT2; “unknown” designates patterns with signatures that do not belong to any of the major lineages described in the database
cClustered strains correspond to a similar spoligotype pattern shared by 2 or more strains “within this study”; as opposed to unique strains harboring a spoligotype pattern that does not match with another strain from this study. Unique strains matching a preexisting pattern in the SITVIT2 database are classified as SITs, whereas in case of no match, they are designated as “orphan”
Fig. 1Phylogenetical analysis illustrating evolutionary relationships between M. tuberculosis spoligotypes in Kampala, Uganda (n = 121 isolates). a Minimum Spanning Tree (MST) constructed on all isolates. Separations between the nodes represent the number of strains shared by a given spoligotype pattern. The links between nodes indicate the distance (darker and bolder lines mean a unique change whereas finer gray lines, continued, dotted or dashed, indicate more changes). b Spoligoforest tree drawn as a hierarchical layout; and c spoligoforest tree drawn using the Fruchterman–Reingold algorithm. Both spoligoforests were drawn using the spolTools software (http://www.emi.unsw.edu.au/spoltools/). Loss of spacers is represented by directed edges between nodes, and the arrowheads point to descendant spoligotypes. The heuristic used selects a single inbound edge with a maximum weight using a Zipf model. Solid black lines link patterns that are very similar, i.e. loss of one spacer only (maximum weight being 1.0), while dashed lines represent links of weight comprised between 0.5 and 1, and dotted lines a weight less than 0.5
Description of clusters observed in our study and their worldwide distribution in the SITVIT2 database
aWorldwide distribution is reported for regions with more than 3 % of a given SITs as compared to their total number in the SITVIT2 database. The definition of macro-geographical regions and sub-regions (http://unstats.un.org/unsd/methods/m49/m49regin.htm) is according to the United Nations; Regions: AFRI (Africa), AMER (Americas), ASIA (Asia), EURO (Europe), and OCE (Oceania), subdivided in: E (Eastern), M (Middle), C (Central), N (Northern), S (Southern), SE (South-Eastern), and W (Western). Furthermore, CARIB (Caribbean) belongs to Americas, while Oceania is subdivided in four sub-regions, AUST (Australasia), MEL (Melanesia), MIC (Micronesia), and POLY (Polynesia). Note that in our classification scheme, Russia has been attributed a new sub-region by itself (Northern Asia) instead of including it among rest of the Eastern Europe. It reflects its geographical localization as well as due to the similarity of specific TB genotypes circulating in Russia (a majority of Beijing genotypes) with those prevalent in Central, Eastern and South-Eastern Asia
bThe three letter country codes are according to http://en.wikipedia.org/wiki/ISO_3166-1_alpha-3; countrywide distribution is only shown for SITs with ≥3 % of a given SITs as compared to their total number in the SITVIT2 database. Note that FXX code designates Metropolitan France