Genetic diversity of Mycobacterium tuberculosis in Peru and exploration of phylogenetic associations with drug resistance.

BACKGROUND: There is limited available data on the strain diversity of M tuberculosis in Peru, though there may be interesting lessons to learn from a setting where multidrug resistant TB has emerged as a major problem despite an apparently well-functioning DOTS control programme. METHODS: Spoligotyping was undertaken on 794 strains of M tuberculosis collected between 1999 and 2005 from 553 community-based patients and 241 hospital-based HIV co-infected patients with pulmonary tuberculosis in Lima, Peru. Phylogenetic and epidemiologic analyses permitted identification of clusters and exploration of spoligotype associations with drug resistance. RESULTS: Mean patient age was 31.9 years, 63% were male and 30.4% were known to be HIV+. Rifampicin mono-resistance, isoniazid mono-resistance and multidrug resistance (MDR) were identified in 4.7%, 8.7% and 17.3% of strains respectively. Of 794 strains from 794 patients there were 149 different spoligotypes. Of these there were 27 strains (3.4%) with novel, unique orphan spoligotypes. 498 strains (62.7%) were clustered in the nine most common spoligotypes: 16.4% SIT 50 (clade H3), 12.3% SIT 53 (clade T1), 8.3% SIT 33 (LAM3), 7.4% SIT 42 (LAM9), 5.5% SIT 1 (Beijing), 3.9% SIT 47 (H1), 3.0% SIT 222 (clade unknown), 3.0% SIT1355 (LAM), and 2.8% SIT 92 (X3). Amongst HIV-negative community-based TB patients no associations were seen between drug resistance and specific spoligotypes; in contrast HIV-associated MDRTB, but not isoniazid or rifampicin mono-resistance, was associated with SIT42 and SIT53 strains. CONCLUSION: Two spoligotypes were associated with MDR particularly amongst patients with HIV. The MDR-HIV association was significantly reduced after controlling for SIT42 and SIT53 status; residual confounding may explain the remaining apparent association. These data are suggestive of a prolonged, clonal, hospital-based outbreak of MDR disease amongst HIV patients but do not support a hypothesis of strain-specific propensity for the acquisition of resistance-conferring mutations

Can the power of mobile phones be used to improve tuberculosis diagnosis in developing countries?

The low-cost Microscopic Observation Drug Susceptibility (MODS) assay is a non-proprietary test that delivers rapid and accurate diagnosis of tuberculosis (TB) and multidrug-resistant TB. Although methodologically straightforward, implementation is challenging in isolated settings where personnel trained in plate reading are lacking. One affordable strategy to address this shortfall is the use of mobile phones, first to transmit images captured by an inverted microscope to a remote site where pattern recognition is performed by trained personnel, and second to receive the resulting output of this analysis. Such a system could be used for training of laboratory personnel through distance learning, resolution of equivocal appearances and quality assurance

Brote de infección por norovirus del grupo II en un Centro de Entrenamiento Militar, Perú 2013

We report an outbreak of norovirus (NoV) which occurred at a military training center in Peru. Thirteen stool samples that were taken from initial cases turned out positive for NoV GII by RT-PCR. A case-control study was performed to determine factors associated with infection.164 probable cases (45.2% clinical attack rate) were identified. The only factor associated with infection was “having shared room with a case” (ORa = 1.7; 95% CI 1.1 to 2.7).Epidemiological findings suggest that the virus was spread person to person. Future investigations of outbreaks of diarrhea in Peru should consider the NoV as an etiologic agent.Reportamos un brote de norovirus (NoV) ocurrido en un centro de entrenamiento militar peruano. Trece muestras de heces tomadas de casos iniciales resultaron positivas a NoV GII por RT-PCR. Se realizó un estudio caso-control para determinar factores asociados a la infección. Se identificó 164 casos probables (tasa de ataque clínica: 45,2%). El único factor asociado a la infección fue el “haber compartido habitación con un caso” (ORa=1,7; IC95% 1,1 a 2,7). Los hallazgos epidemiológicos sugieren que el virus fue propagado persona a persona. Futuras investigaciones de brotes de diarrea en el Perú deberían considerar al NoV como un agente etiológico

Brote de infección por norovirus del Grupo II en un centro de entrenamiento militar, Perú 2013

Reportamos un brote de norovirus (NoV) ocurrido en un centro de entrenamiento militar peruano. Trece muestras de heces tomadas de casos iniciales resultaron positivas a NoV GII por RT-PCR. Se realizó un estudio caso-control para determinar factoresasociados a la infección. Se identificó 164 casos probables(tasa de ataqueclínica: 45,2%). El único factor asociado a la infecciónfue el "haber compartido habitación con un caso" (ORa=1,7; IC95% 1,1 a 2,7). Los hallazgos epidemiológicos sugieren que el virus fue propagado persona a persona. Futuras investigaciones de brotes de diarrea en el Perú deberían considerar al NoV como un agente etiológic

Brote de infección por norovirus del Grupo II en un centro de entrenamiento militar, Perú 2013

Reportamos un brote de norovirus (NoV) ocurrido en un centro de entrenamiento militar peruano. Trece muestras de heces tomadas de casos iniciales resultaron positivas a NoV GII por RT-PCR. Se realizó un estudio caso-control para determinar factoresasociados a la infección. Se identificó 164 casos probables(tasa de ataqueclínica: 45,2%). El único factor asociado a la infecciónfue el "haber compartido habitación con un caso" (ORa=1,7; IC95% 1,1 a 2,7). Los hallazgos epidemiológicos sugieren que el virus fue propagado persona a persona. Futuras investigaciones de brotes de diarrea en el Perú deberían considerar al NoV como un agente etiológic

Discrete spoligotypes relationships for all isolates (n = 794) presented through spoligoforest tree drawn as a “hierarchical layout” using the SpolTools software (available through

<p><a href="http://www.emi.unsw.edu.au/spolTools" target="_blank">http://www.emi.unsw.edu.au/spolTools</a><b>; Reyes et al. 2008 </b><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065873#pone.0065873-Zignol1" target="_blank">[<b>11</b>]</a><b>).</b> Each spoligotype pattern from the study is represented by a node with area size being proportional to the total number of isolates with that specific pattern. Changes (loss of spacers) are represented by directed edges between nodes, with the arrowheads pointing to descendant spoligotypes. In this representation, 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. Orphan isolates, indicated in cyan, are isolated strains without interconnections with the other strains. This presentation illustrates for example the parental links for PGG2/3 strains such as SIT53 and SIT42, showing how SIT53 may be considered as the precursor of all other modern PGG2/3 patterns. SIT53 leads to SIT50/H3 by the loss of spacer 31, and it leads to SIT42 by the loss of four spacers (spacers 21–24), which in turn leads to SIT1355/LAM via SIT64/LAM6 then SIT95/LAM6. Through other spacer deletions, SIT53 leads to SIT91/X3 via SIT119/X1 and SIT92/X3. Lastly, SIT222/Unknown has no parental SITs in our study.</p

Strain spoligotype (SIT) frequency by patient HIV status and strain MDR status.

1<p>12 of 794 isolates lacked either MDR or HIV status data, leaving 782 here as the denominator.</p>2<p>Percentage of SIT-specific isolates with MDR.</p

Description of clusters composed of predominant shared types (defined as SITs representing >2% strains, n = 16) in our study and their worldwide distribution in the SITVIT2 database.

*<p>Worldwide 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 (<a href="http://unstats.un.org/unsd/methods/m49/m49regin.htm" target="_blank">http://unstats.un.org/unsd/methods/m49/m49regin.htm</a>) 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 4 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.</p>**<p>The 3 letter country codes are according to <a href="http://en.wikipedia.org/wiki/ISO_3166-1_alpha-3" target="_blank">http://en.wikipedia.org/wiki/ISO_3166-1_alpha-3</a>; countrywide distribution is only shown for SITs with ≥3% of a given SITs as compared to their total number in the SITVIT2 database.</p

Description of 122 shared-types (SITs; n = 767 isolates) and corresponding spoligotyping defined lineages/sublineages starting from a total of 794 <i>M. tuberculosis</i> strains isolated from adults with pulmonary tuberculosis in Lima, Peru.

*<p>A total of 100/122 SITs (n = 718) matched a preexisting shared-type in the database, whereas 22/122 SITs (n = 49 isolates) were newly created either within the present study or after a match with an orphan in the database. A total of 66 SITs containing 711 isolates were clustered within this study (2 to 130 isolates per cluster), while 56 SITs contained a unique strain within this study.</p><p>Note that SITs followed by an asterisk indicates “newly created shared-type” (n = 22 containing 49 isolates) due to 2 or more strains belonging to an identical new pattern within this study or after a match with an orphan in the database. SIT designations followed by number of strains: 2961* this study (n = 2); 3000* this study (n = 3); 3001* this study (n = 8) and USA (n = 1); 3004* this study (n = 2); 3005* this study (n = 2); 3006* this study (n = 2) and South Africa (n = 1); 3007* this study (n = 1) and USA (n = 1); 3008* this study (n = 1) and USA (n = 1); 3009* this study (n = 2); 3010* this study (n = 1) and USA (n = 1); 3011* this study (n = 4); 3012* this study (n = 2); 3013* this study (n = 3) and USA (n = 1); 3014* this study (n = 1) and Argentina (n = 1); 3015* this study (n = 2); 3016* this study (n = 1) and Panama (n = 1); 3017* this study (n = 3); 3089* this study (n = 2) and Mexico (n = 1); 3168* this study n = 1, Sweden (n = 1); 3431* this study (n = 2); 3432* this study (n = 2); 3433* this study (n = 2), BRA (n = 1).</p>**<p>Lineage designations according to SITVIT2 using revised SpolDB4 rules; “Unknown” designates patterns with signatures that do not belong to any of the major clades described in the database.</p>***<p>Clustered 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” (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065873#pone-0065873-t001" target="_blank">Table 1</a>).</p

Associations with drug resistance.

<p>OR = odds ratio; 95% CI = 95% confidence interval; clustered SIT = in 9 most common SITs (accounting for 63% of all strains); bold type indicates statistically significant associations.</p>1<p>all adjusted ORs incorporate SIT42 and SIT53 and clustered SIT variable and into model.</p