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Within patient microevolution of Mycobacterium tuberculosis correlates with heterogeneous responses to treatment.

Liu Q, Via LE, Luo T, Liang L, Liu X, Wu S, Shen Q, Wei W, Ruan X, Yuan X, Zhang G, Barry CE, Gao Q - Sci Rep (2015)

Bottom Line: Differential mutation patterns in known resistance alleles indicated these sub-clones had different drug-resistance patterns, which may explain the heterogeneous treatment responses between lesions.Our results showed clear evidence of branched microevolution of MTB in vivo, which led to a diverse bacterial community.These findings indicated that complex sub-populations of MTB might coexist within patient and contribute to lesions' disparate responses to antibiotic treatment.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Medical Molecular Virology of Ministries of Education and Health, Institutes of Biomedical Sciences and Institute of Medical Microbiology, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China.

ABSTRACT
Genetic heterogeneity of Mycobacterium tuberculosis (MTB) within a patient has caused great concern as it might complicate antibiotic treatment and cause treatment failure. But the extent of genetic heterogeneity has not been described in detail nor has its association with heterogeneous treatment response. During treatment of a subject with MDR-TB, serial computed tomography (CT) scans showed this subject had six anatomically discrete lesions and they responded to treatment with disparate kinetics, suggesting heterogeneous MTB population may exist. To investigate this heterogeneity, we applied deep whole genome sequencing of serial sputum isolates and discovered that the MTB population within this patient contained three dominant sub-clones differing by 10 ~ 14 single nucleotide polymorphisms (SNPs). Differential mutation patterns in known resistance alleles indicated these sub-clones had different drug-resistance patterns, which may explain the heterogeneous treatment responses between lesions. Our results showed clear evidence of branched microevolution of MTB in vivo, which led to a diverse bacterial community. These findings indicated that complex sub-populations of MTB might coexist within patient and contribute to lesions' disparate responses to antibiotic treatment.

No MeSH data available.


Related in: MedlinePlus

Treatment information of the subject and the trunk-branch genetic structure of the three sub-clones.(A) the first arrow shows treatment regimens, H, Isoniazid; R, Rifampicin; Z, Pyrazinamide; E, Ethambutol; AMK, Amikacin; LFX, Levofloxacin; PAS, Para-aminosalicylic acid. Drugs in green represent effective drugs. The second arrow contains the sputum smear microscopy results at each time point. ‘−’ represents smear negative; a number (such as 5, 8) represents the actual bacilli number that observed in 300 visual fields; ‘+’ represents 3 ~ 9 bacilli per 100 visual fields; ‘++’ represents 1 ~ 9 bacilli per 10 visual fields. The pie charts refer to the sub-clones identified through single colonies genotyping and the percentage of each chart represents the relative frequency of each sub-clone detected SNPs in deep sequencing data. (B) detailed phylogeny of the three sub-clones with common SNPs mapped to the trunk and heterogeneous SNPs mapped to the branches. Drug-resistant mutations are shown in bold and parallel mutations are highlighted in green. murA-rrs (M1) refers to SNP 1471660 G-C while murA-rrs (M2) refers to SNP 1471656 G-C. Rv0749 (M3) and Rv0749(M4) refer to two different SNPs in Rv0749.
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f2: Treatment information of the subject and the trunk-branch genetic structure of the three sub-clones.(A) the first arrow shows treatment regimens, H, Isoniazid; R, Rifampicin; Z, Pyrazinamide; E, Ethambutol; AMK, Amikacin; LFX, Levofloxacin; PAS, Para-aminosalicylic acid. Drugs in green represent effective drugs. The second arrow contains the sputum smear microscopy results at each time point. ‘−’ represents smear negative; a number (such as 5, 8) represents the actual bacilli number that observed in 300 visual fields; ‘+’ represents 3 ~ 9 bacilli per 100 visual fields; ‘++’ represents 1 ~ 9 bacilli per 10 visual fields. The pie charts refer to the sub-clones identified through single colonies genotyping and the percentage of each chart represents the relative frequency of each sub-clone detected SNPs in deep sequencing data. (B) detailed phylogeny of the three sub-clones with common SNPs mapped to the trunk and heterogeneous SNPs mapped to the branches. Drug-resistant mutations are shown in bold and parallel mutations are highlighted in green. murA-rrs (M1) refers to SNP 1471660 G-C while murA-rrs (M2) refers to SNP 1471656 G-C. Rv0749 (M3) and Rv0749(M4) refer to two different SNPs in Rv0749.

Mentions: Considering the history of tuberculosis and the disease severity, the doctor prescribed an intensive treatment with seven anti-tuberculosis drugs (Fig. 2A). The drug susceptibility testing of this subjects’ MTB isolate at week 0 showed isoniazid and rifampin resistance making it formally multidrug-resistant (MDR-TB). In addition the isolate was also resistant to the injectable aminoglycoside amikacin making it “pre-extensively drug resistant” (pre-XDR). Thus although this subject received seven agents her isolate was only formally sensitive to ethambutol (E), levofloxacin (LFX) and para-amino salicylic acid (PAS). During the treatment, the sputum bacillary load as indicated by sputum smear score was low from week 0 to week 4 but showed a dramatic increase at week 6 (Fig. 2A). Then, sputum bacillary load decreased at week 8 under the same treatment regimens.


Within patient microevolution of Mycobacterium tuberculosis correlates with heterogeneous responses to treatment.

Liu Q, Via LE, Luo T, Liang L, Liu X, Wu S, Shen Q, Wei W, Ruan X, Yuan X, Zhang G, Barry CE, Gao Q - Sci Rep (2015)

Treatment information of the subject and the trunk-branch genetic structure of the three sub-clones.(A) the first arrow shows treatment regimens, H, Isoniazid; R, Rifampicin; Z, Pyrazinamide; E, Ethambutol; AMK, Amikacin; LFX, Levofloxacin; PAS, Para-aminosalicylic acid. Drugs in green represent effective drugs. The second arrow contains the sputum smear microscopy results at each time point. ‘−’ represents smear negative; a number (such as 5, 8) represents the actual bacilli number that observed in 300 visual fields; ‘+’ represents 3 ~ 9 bacilli per 100 visual fields; ‘++’ represents 1 ~ 9 bacilli per 10 visual fields. The pie charts refer to the sub-clones identified through single colonies genotyping and the percentage of each chart represents the relative frequency of each sub-clone detected SNPs in deep sequencing data. (B) detailed phylogeny of the three sub-clones with common SNPs mapped to the trunk and heterogeneous SNPs mapped to the branches. Drug-resistant mutations are shown in bold and parallel mutations are highlighted in green. murA-rrs (M1) refers to SNP 1471660 G-C while murA-rrs (M2) refers to SNP 1471656 G-C. Rv0749 (M3) and Rv0749(M4) refer to two different SNPs in Rv0749.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
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f2: Treatment information of the subject and the trunk-branch genetic structure of the three sub-clones.(A) the first arrow shows treatment regimens, H, Isoniazid; R, Rifampicin; Z, Pyrazinamide; E, Ethambutol; AMK, Amikacin; LFX, Levofloxacin; PAS, Para-aminosalicylic acid. Drugs in green represent effective drugs. The second arrow contains the sputum smear microscopy results at each time point. ‘−’ represents smear negative; a number (such as 5, 8) represents the actual bacilli number that observed in 300 visual fields; ‘+’ represents 3 ~ 9 bacilli per 100 visual fields; ‘++’ represents 1 ~ 9 bacilli per 10 visual fields. The pie charts refer to the sub-clones identified through single colonies genotyping and the percentage of each chart represents the relative frequency of each sub-clone detected SNPs in deep sequencing data. (B) detailed phylogeny of the three sub-clones with common SNPs mapped to the trunk and heterogeneous SNPs mapped to the branches. Drug-resistant mutations are shown in bold and parallel mutations are highlighted in green. murA-rrs (M1) refers to SNP 1471660 G-C while murA-rrs (M2) refers to SNP 1471656 G-C. Rv0749 (M3) and Rv0749(M4) refer to two different SNPs in Rv0749.
Mentions: Considering the history of tuberculosis and the disease severity, the doctor prescribed an intensive treatment with seven anti-tuberculosis drugs (Fig. 2A). The drug susceptibility testing of this subjects’ MTB isolate at week 0 showed isoniazid and rifampin resistance making it formally multidrug-resistant (MDR-TB). In addition the isolate was also resistant to the injectable aminoglycoside amikacin making it “pre-extensively drug resistant” (pre-XDR). Thus although this subject received seven agents her isolate was only formally sensitive to ethambutol (E), levofloxacin (LFX) and para-amino salicylic acid (PAS). During the treatment, the sputum bacillary load as indicated by sputum smear score was low from week 0 to week 4 but showed a dramatic increase at week 6 (Fig. 2A). Then, sputum bacillary load decreased at week 8 under the same treatment regimens.

Bottom Line: Differential mutation patterns in known resistance alleles indicated these sub-clones had different drug-resistance patterns, which may explain the heterogeneous treatment responses between lesions.Our results showed clear evidence of branched microevolution of MTB in vivo, which led to a diverse bacterial community.These findings indicated that complex sub-populations of MTB might coexist within patient and contribute to lesions' disparate responses to antibiotic treatment.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Medical Molecular Virology of Ministries of Education and Health, Institutes of Biomedical Sciences and Institute of Medical Microbiology, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China.

ABSTRACT
Genetic heterogeneity of Mycobacterium tuberculosis (MTB) within a patient has caused great concern as it might complicate antibiotic treatment and cause treatment failure. But the extent of genetic heterogeneity has not been described in detail nor has its association with heterogeneous treatment response. During treatment of a subject with MDR-TB, serial computed tomography (CT) scans showed this subject had six anatomically discrete lesions and they responded to treatment with disparate kinetics, suggesting heterogeneous MTB population may exist. To investigate this heterogeneity, we applied deep whole genome sequencing of serial sputum isolates and discovered that the MTB population within this patient contained three dominant sub-clones differing by 10 ~ 14 single nucleotide polymorphisms (SNPs). Differential mutation patterns in known resistance alleles indicated these sub-clones had different drug-resistance patterns, which may explain the heterogeneous treatment responses between lesions. Our results showed clear evidence of branched microevolution of MTB in vivo, which led to a diverse bacterial community. These findings indicated that complex sub-populations of MTB might coexist within patient and contribute to lesions' disparate responses to antibiotic treatment.

No MeSH data available.


Related in: MedlinePlus