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org/10.1128/JCM.00025-15
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In Silico prediction of antibiotic resistance in
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Med Hyg 97(3):810–814. https://doi.org/
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179. Benjak A, Avanzi C, Singh P, Loiseau C,
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MAC, Filho FB, Barreto JG, Nery JAC,
Buhrer-Sekula S, Lupien A, Al-Samie AR,
Al-Qubati Y, Alkubati AS, Bretzel G, VeraCabrera L, Sakho F, Johnson CR, Kodio M,
Fomba A, Sow SO, Gado M, Konate O, Stefani MMA, Penna GO, Suffys PN, Sarno EN,
Moraes MO, Rosa PS, Baptista I, Spencer JS,
Aseffa A, Matsuoka M, Kai M, Cole ST
(2018) Phylogenomics and antimicrobial
resistance of the leprosy bacillus Mycobacterium leprae. Nat Commun 9(1):352.
https://doi.org/10.1038/s41467-01702576-z
454
Marco A. Riojas et al.
https://doi.org/10.1016/j.cmi.2017.10.
030
168. Ezewudo M, Borens A, Chiner-Oms A,
Miotto P, Chindelevitch L, Starks AM,
Hanna D, Liwski R, Zignol M, Gilpin C,
Niemann S, Kohl TA, Warren RM, Crook D,
Gagneux S, Hoffner S, Rodrigues C,
Comas I, Engelthaler DM, Alland D,
Rigouts L, Lange C, Dheda K, Hasan R,
McNerney R, Cirillo DM, Schito M, Rodwell
TC, Posey J (2018) Integrating standardized
whole genome sequence analysis with a global
Mycobacterium tuberculosis antibiotic resistance knowledgebase. Sci Rep 8(1):15382.
https://doi.org/10.1038/s41598-01833731-1
169. Kohl TA, Utpatel C, Schleusener V, De
Filippo MR, Beckert P, Cirillo DM, Niemann
S (2018) MTBseq: a comprehensive pipeline
for whole genome sequence analysis of Mycobacterium tuberculosis complex isolates. PeerJ
6:e5895.
https://doi.org/10.7717/peerj.
5895
170. Ngo TM, Teo YY (2019) Genomic prediction
of tuberculosis drug-resistance: benchmarking existing databases and prediction algorithms. BMC Bioinformatics 20(1):68.
https://doi.org/10.1186/s12859-0192658-z
171. Schleusener V, Koser CU, Beckert P,
Niemann S, Feuerriegel S (2017) Mycobacterium tuberculosis resistance prediction and
lineage classification from genome sequencing: comparison of automated analysis tools.
Sci Rep 7:46327. https://doi.org/10.1038/
srep46327
172. Hunt M, Bradley P, Lapierre SG, Heys S,
Thomsit M, Hall MB, Malone KM,
Wintringer P, Walker TM, Cirillo DM,
Comas I, Farhat MR, Fowler P, Gardy J,
Ismail N, Kohl TA, Mathys V, Merker M,
Niemann S, Omar SV, Sintchenko V,
Smith G, van Soolingen D, Supply P,
Tahseen S, Wilcox M, Arandjelovic I, Peto
TEA, Crook DW, Iqbal Z (2019) Antibiotic
resistance prediction for Mycobacterium
tuberculosis from genome sequence data with
Mykrobe. Wellcome Open Res 4:191.
https://doi.org/10.12688/
wellcomeopenres.15603.1
173. Phelan JE, O’Sullivan DM, Machado D,
Ramos J, Oppong YEA, Campino S,
O’Grady J, McNerney R, Hibberd ML,
Viveiros M, Huggett JF, Clark TG (2019)
Integrating informatics tools and portable
sequencing technology for rapid detection of
resistance to anti-tuberculous drugs. Genome
Med 11(1):41. https://doi.org/10.1186/
s13073-019-0650-x
174. Feuerriegel S, Schleusener V, Beckert P, Kohl
TA, Miotto P, Cirillo DM, Cabibbe AM,
Niemann S, Fellenberg K (2015) PhyResSE:
a web tool delineating Mycobacterium tuberculosis antibiotic resistance and lineage from
whole-genome sequencing data. J Clin
Microbiol 53(6):1908–1914. https://doi.
org/10.1128/JCM.00025-15
175. Macedo R, Nunes A, Portugal I, Duarte S,
Vieira L, Gomes JP (2018) Dissecting wholegenome sequencing-based online tools for
predicting resistance in Mycobacterium tuberculosis: can we use them for clinical decision
guidance? Tuberculosis 110:44–51. https://
doi.org/10.1016/j.tube.2018.03.009
176. Lipworth S, Hough N, Leach L, Morgan M,
Jeffery K, Andersson M, Robinson E, Smith
EG, Crook D, Peto T, Walker T (2019)
Whole-genome sequencing for predicting
clarithromycin resistance in Mycobacterium
abscessus. Antimicrob Agents Chemother 63
(1):e01204–e01218.
https://doi.org/10.
1128/AAC.01204-18
177. Gupta SK, Drancourt M, Rolain JM (2017)
In Silico prediction of antibiotic resistance in
Mycobacterium ulcerans Agy99 through
whole genome sequence analysis. Am J Trop
Med Hyg 97(3):810–814. https://doi.org/
10.4269/ajtmh.16-0478
178. Lavania M, Singh I, Turankar RP, Gupta AK,
Ahuja M, Pathak V, Sengupta U (2018)
Enriched whole genome sequencing identified compensatory mutations in the RNA
polymerase gene of rifampicin-resistant Mycobacterium leprae strains. Infect Drug Resist
11:169–175.
https://doi.org/10.2147/
IDR.S152082
179. Benjak A, Avanzi C, Singh P, Loiseau C,
Girma S, Busso P, Fontes ANB,
Miyamoto Y, Namisato M, Bobosha K, Salgado CG, da Silva MB, Bouth RC, Frade
MAC, Filho FB, Barreto JG, Nery JAC,
Buhrer-Sekula S, Lupien A, Al-Samie AR,
Al-Qubati Y, Alkubati AS, Bretzel G, VeraCabrera L, Sakho F, Johnson CR, Kodio M,
Fomba A, Sow SO, Gado M, Konate O, Stefani MMA, Penna GO, Suffys PN, Sarno EN,
Moraes MO, Rosa PS, Baptista I, Spencer JS,
Aseffa A, Matsuoka M, Kai M, Cole ST
(2018) Phylogenomics and antimicrobial
resistance of the leprosy bacillus Mycobacterium leprae. Nat Commun 9(1):352.
https://doi.org/10.1038/s41467-01702576-z
454
Marco A. Riojas et al.