1,594

GCMS Based Detection of Lipid Biomarkers of Mycobacterium tuberculosis in the Serum Specimen

Anish Zacharia Joseph, Anubhav Jain, Mukul Pachauri, Ajay Kumar, G.B.K.S Prasad, P.S. Bisen

Anish Zacharia Joseph, G.B.K.S Prasad, School of Studies in Biochemistry, Jiwaji University, Gwalior 474011, India
Anish Zacharia Joseph, Sun Pharmaceutical Industries Limited, Tandalja, Vadodara 390 020, India
Anubhav Jain, Mukul Pachauri, P.S. Bisen, School of Studies in Biotechnology, Jiwaji University, Gwalior 474011, India
Ajay Kumar, Advanced Instrumentation Research Facility, Jawaharlal Nehru University, New Delhi 110067, India
P.S. Bisen, School of Life Sciences, Jaipur National University, Jagatpura, Jaipur 302017, India

Correspondence to: P.S. Bisen, Professor, School of Studies in Biotechnology, Jiwaji University, Gwalior, India – 474 011, & School of Life Sciences, Jaipur National University, Jagatpura, Jaipur 302017, India.
Email: psbisen@gmail.com
Telephone: ++91-751-2462500
Received: March 5, 2016
Revised: May 20, 2016
Accepted: May 27, 2016
Published online: June 18, 2016

ABSTRACT

AIM: The present study is focused on the identification of high abundant and low abundant biomarkers of Mycobacterium tuberculosis from serum specimen using Gas chromatography and Mass spectroscopy.

METHODS: The TB positive and negative sera were screened on the basis of sputum smear microscopy and the in house developed liposome based antibody detection kit. The lipid fraction was isolated from the collected sera and derivatized. In GCMS analysis, the derivatized lipid samples were analyzed through Gas Chromatograph Mass spectrometer (Shimadzu QP-2010 plus with Thermal Desorption system TD 20). Split or splitless mode of sample injection was performed to identify the high abundant and low abundant biomarkers of tuberculosis.

RESULTS: The study identified lipid biomarkers specific for M. tuberculosis in the serum of tuberculosis positive subjects. The study revealed that lipids like C17 H34, C21H52O6, C29H60, C34H70, C44H90 was identified in the split mode of sample injection, whereas C29H60, C34H70, C44H90, C14H23BrO, C11H24O2, C18H44O5, C14H30O3S and C24H39N were identified in the splitless mode of sample injection. Under split injection mode of analysis, C17H34, C21H52O6 and C34H70 lipids were identified as low abundant lipids. The molecules like C14H23BrO, C11H24O2, C18H44O5 and C22H39N were identified as low abundant lipids even after the splitless mode of analysis.

DISCUSSIONS: The GCMS analysis revealed the presence of lipid biomarkers of Mycobacterial tuberculosis in the circulation of selected tb positive sera samples. The study further identified the low abundant and high abundant biomarkers of tuberculosis. The detection of characterized low abundant biomarkers may help in identifying the disease in sputum smear negative cases.

© 2016 The Author. Published by ACT Publishing Group Ltd.

Key words: Lipid biomarker; GCMS detection; VOC (volatile organic compound); MTB (Mycobacterium tuberculosis)

Joseph AZ, Jain A, Pachauri M, Kumar A, Prasad GBKS, Bisen PS. GCMS Based Detection of Lipid Biomarkers of Mycobacterium tuberculosis in the Serum Specimen. Journal of Respiratory Research 2016; 2(2): 47-55 Available from: URL: http://www.ghrnet.org/index.php/jrr/article/view/1630

INTRODUCTION

Mycobacterium tuberculosis is the causative pathogen of tuberculosis (TB) in more than 90% of the infected persons. These bacteria remain in a dormant state in granulomas for life with the ability to persist in host tissue referred to as latency, is central to the disease. The Mycobacterium tuberculosis possess cell wall lipid molecules which are responsible for the pathogenesis, virulence and invasiveness. Gas chromatography is being used for the analysis of cellular fatty acids and alcohols of Mycobacterial species. It is already known that isolates of Mycobacterial complex had a relatively high concentration of hexacosanoic acid (1-13%) and low level of tetracosanoic acid (0.1-3%)[1]. Enzymes are being used in the sample to enhance the microbial growth and generate higher volatiles in the head space of analysis tube. The fingerprint analysis of the volatile lipids in the enzyme enriched samples is normally used for the confirmation of diagnosis of tuberculosis. More than 100 volatile biomarkers of tuberculosis were detected in the head space in Mycobacterium avium subsp Paratuberculosis with variation in the release in different mycobacterium species[2]. GC-MS based method was used to identify the VOC (volatile organic compound pattern) linked with the disease conditions. Nano Artificial NOSE (NA-NOSE) was developed to detect M. bovis infection in cattle based on the volatile lipid pattern[3-4]. The other commonly used methods for the detection of Mycobacterium sp using VOC are gas chromatography with mass spectrometry (GCMS), proton transfer reaction mass spectrometry (PTR-MS), selected ion flow tube mass spectrometry (SIFT-MS), laser spectrometry, ion mobility spectrometry (IMS) or differential ion mobility spectrometry (DMS)[5]. The highly stable hydrophobic waxes of cell wall components of Mycobacterium like Phthiocerol dimycocerosates (PDIMs) are also being explored for diagnostic purpose[6]. Several analogues of major PDIMs such as C34 and C36 viz. phthiocerols, phthiodiolone, phthiocerolone, pthiotriol, mycolic acid and ester of phthiocerol form mycocerosate have been identified[7-8]. The physical property of mycocerosic acid is analogous to the 2, 4, 6, trimethyl nonacosonate. Thermochemolysis GC-EI/MS have been employed for analyzing mycocerosic acid components of the phthiocerol dimycocerosate (PDIM) family of lipids to study for diagnosis of tuberculosis in sputum[9]. Although several volatile lipid moieties specific for mycobacterium have been identified in the culture, and sputum of the infected subject. However, the present study is unique by itself in identifying high and low abundant lipid biomarkers of tuberculosis in the circulation of the tuberculosis infected subjects.

MATERIALS AND METHODS

Ethical approval

The study was approved by the Research Ethical Committee at the Gajra Raja Medical College in Gwalior, M.P. India. Written consent was obtained from all the studied patients for sample collection and subsequent analysis.

Sample collection

The sera samples were collected from tuberculosis patients (n = 10 samples) at a minimal volume of 0.5 mL) from the primary health centre of Madhya Pradesh region of India. The patients were clinically diagnosed by sputum smear and culture with pulmonary tuberculosis. None of the patients had taken antibiotics before sampling. The sera samples of healthy cases were also collected from the same region (n = 10). For spiking experiments, sera specimens were obtained from patients with pulmonary infection (but free of TB), who were treated at Gajra Raja Medical College, Gwalior.

Spiking of negative samples

The spiking of negative sample with MTB is performed as per method described earlier[10] with minor modifications having final concentration of 1 × 106 mycobacteria/mL sera.

Extraction of lipids from serum

Briefly, 1 mL of normal human serum was added to 10 mL of chloroform-methanol 2:1 (v/v). The mixture was agitated in a orbitol shaker at 70 rpm for 12 hours. The organic extract was filtered through the 0.2 µ syringe filter and the lipid extract was evaporated to dryness. The lipids were derivatized for GCMS analysis.

Culturing of M. tuberculosis

M. tuberculosis strain H37Rv (ATCC27294) was cultured in a Lowenstein-Jansen agar culture medium (2 × 10 CFU/mL)[11]. The cells were then harvested by centrifugation (10,000 g × 20 min × 4℃). The cell pellet was isolated and washed with 100 mL of PBS at pH 7.2 followed by resuspending it in TNF buffer. The M. tuberculosis cells were heat inactivated and lyophilized.

Extraction and isolation of lipid antigen(s) from M. tuberculosis

Heat inactivated mycobacterial cell (5 g) was placed into a glass reagent bottle, and 100 mL of organic solvent of chloroform-methanol mixture (2:1) was added to it. This mixture was stirred at a temperature of 25℃ for 60 minutes and filtered through Whatman number 1 filter paper. The organic phase was dried by evaporating the solvent in a rotary solvent evaporator at 45℃. Neutral lipids were removed from the dried mixture by adding 50 mL of chilled acetone while the mixture was vortexed for 10 min and then filtered through Whatman no. 1 filter paper. This step was repeated 3 times. The contents of the flask were filtered through Whatman filter paper no. 1, and the filtrate was discarded. The lipids present on the filter paper were dissolved with chloroform-methanol (2:1) and transferred to a round-bottom flask. The solvent was evaporated on a rotary evaporator under reduced pressure at 45℃. The crude preparation of lipid mixture was reconstituted in 10 mL of chloroform-methanol (2:1) and stored at a temperature of -20℃ for further use[11].

Derivatization

The lipid samples were mixed with 20 µL of -obis (trimethylsilyl) -trifluoroacetamide (BSTFA) (Fluka). The samples are capped, wrapped with Teflon tape, and heated at 45℃ for 12 hours to convert the targeted analytes to their trimethylsilyl derivatives. The samples were further reconstituted in hexane and GCMC profiling was performed.

GCMS method

The lipid samples were analyzed through Gas Chromatograph Mass spectrometer (Shimadzu QP-2010 plus with Thermal Desorption system TD 20). The column used was Rtx-5MS, cross bonded with 5% diphenyl and 95% dimethyl polysiloxane (30 m, 0.25 mm ID, 0.25 µm) and had minimal bleed even at a temperature range of 350℃-33℃. The column was conditioned with a temperature 150℃ and injection temperature was optimized at 260℃. The carrier gas Helium was purged at a flow rate of 16.3 mL/min and 1.21 mL/min flow was maintained in the column was conditioned in the column. The column oven was programmed at 150℃ (hold time, 5 min) at rate of 15℃/min to 310℃ (hold time 8 min). The sample injection was programmed at either split/splitless mode. The GC run time was optimized to 25 min. The analytes were analyzed through FTD detectors. The mass spectrum of the molecules was analyzed through QP 2010 plus programmed for data acquisition from 5-23.6 min. The ion source temperature was equilibrated to 230℃ and the interface temperature was maintained at 280℃. The data acquisition was set a speed of 1,250 with a rise time of 0.5 sec. The mass fragmentation acquisition was set at a range of m/z 40– m/z 650. The mass spectrometric results were recorded.

Data mining and logical analysis

The mass spectrometry data were matched with the NIST Database, Wiley and the relative hits according to the retention time and mass fragmentation pattern was recorded. The data were compared with the lipid molecules of Mycobacterium tuberculosis cell lipids and further compared with the sera lipids of the healthy individuals. The molecules which were very specific to tuberculosis were used as biomarker.

RESULTS

The biomarkers of tuberculosis were identified by in the sera samples of tuberculosis confirmed cases by GC-MS. Sera samples were extracted with organic solvents, lipid fraction was subjected to GCMS analysis and molecules were identified through mass spectrometric databases and respective controls like sera of healthy individuals, M. tuberculosis cell lipids. The biomarkers specific for the tuberculosis infection were identified.

Identification of potential biomarkers of tuberculosis

The initial study identified and characterized the lipids of mycobacterium origin in the sera of the suspected individuals. The injection volume of the sample was only 1 µL. The sample was analyzed in the split mode of 1/10 ratio or split less mode. The mass spectrum of the individual lipid molecule separated in the Gas chromatograph and the mass spectrum of the individual molecule was determined. The molecules were identified using mass spectrometric databases.

The split mode of injection in GCMS analysis lead to the detection of C17H34 lipids in TB positive sera, however, this lipid was not detected in the Mycobacterium tuberculosis cell wall extracts (Figure 1a, 1b) and Table 1 and 2. Another biomarker with a molecular formula C21H52O6 was detected in the sera of the TB positive subjects. This molecule had a similar mass fragmentation pattern of hexopyranose. The Mycobacterium tuberculosis cell wall extract also showed the presence of a molecule with hexopyranoside unit in it (Figure 2a-d and Tables 1, 2). The sera of the TB positive cases showed the presence of higher alkane, C34H70. This molecule had a similar mass fragmentation pattern of tetratriacontane lipids. These lipids are also found in the cell wall extract of M. tuberculosis. The higher alkanes are found to be the building blocks of Phthiocerol lipids (Figure 3a-3d) and Table 1. The other higher alkanes like C29H60 and C44H90 were also identified in the sera of the TB infected cases. These molecules serve as building blocks of phthiocerol lipids (Figure 4a-4d) and Table 1, 2; (Figure 5a- 5d) and Table 1, 2. To the best of our knowledge this is the first report of above mentioned biomarkers from tuberculosis sera hence considered as novel in nature. Another lipid C22H39N was detected in the sera of TB infected cases (Figure. 6a-d). This molecule had a close similarity with hexadecylaniline.

The splitless mode of injection in GCMS showed the presence of C18H44O5 (Figure 7a, b). This molecule is similar to the mannopyranose, however, the molecule was not detected in the lipid extract of Mycobacterium tuberculosis under the identical GCMS conditions. In splitless mode, biomarkers C14H23BrO (figure not shown), C11H24O2 (figure not shown) and C14H30O3S (figure not shown) were detected. In splitless mode of injection, molecules like C18H44O5, C13H20, C22H39N were identified. To the best of our knowledge this is the first report of these biomarkers in the sera of tuberculosis infected cases and the method is novel in isolating and identifying the low abundant and high abundant lipid biomarkers.

Identification of high abundant and low abundant biomarkers of tuberculosis

The high abundant and low abundant biomarkers of Mycobacterium tuberculosis were identified from the sample injected and analysis was performed under split and splitless mode. Under split mode of analysis the high abundant lipids like C29H60 and C44H60 lipids were identified at a level of 50.02% and 29.15%, respectively whereas low abundant molecules like C21H52O6, C17H34, C34H70 and C21H44 were identified in the sera of the infected at a level of 0.76%, 1.46%, 2.98 and 4.74% of total lipid content (Table 3, 4). Under splitless mode injection, the molecules like C13H20, C12H16O, C18H44O5, C22H46, C19H29ClO, C24H50, C22H39N, C14H23BrO, C11H24O2 and C14H303S were found in the sera of the infected at a level of 0.2%, 0.57%, 0.69%, 1.87%, 2.54%, 5.22%, 4.6%, 1.85%, 1.07% and 1.1%, respectively (Table 3 and Table 5). We identified the lipid biomarkers of Mycobacterial tuberculosis and further characterized its distribution in the circulation in the selected tb positive sera sample.







DISCUSSION

Tuberculosis (TB) remains one of the world’s deadliest communicable diseases with 9.6 million people fell ill and 1.5 million died in 2014 from the disease[12].

In 2013, about 64% of the estimated 9 million people who developed TB were notified as newly diagnosed cases. This is estimated to have left about 3 million cases that were either not diagnosed, or diagnosed, but not reported to national TB programmes (NTPs)[12]. The present investigation relates to the identification of few lipid molecules of Mycoabcterium sp. origin in the sera specimen of the tuberculosis infected cases. The metabolomics based approach was used to characterize and identify the biomarkers from sera specimen.

Earlier studies revealed that Gas chromatography combined with mass spectrometry (GC/MS) could offer a more rapid test for the diagnosis of TB by detecting lipid markers of Mycobacterium tuberculosis in biological matrices like sputum, bone, and tissue. The present study showed the presence of long carbon chain molecules in the sera of infected subjects, however, none of these molecules have been reported in the sera or any other tissue speciemen. Tuberculostearic acid (TBSA) lipid was widely studied as biomarker from culture and sputum specimens and other members of actinomycetes[13-20].

The other long chain carbon molecules detected in the tuberculosis positive sera was C34H70, C29H60, and C34H90. The presence of these molecules could be attributed to presence of PDIMs. Gas chromatographic–mass spectrometric (GC–MS) analysis has proven to be successful for the TB diagnosis by detecting M. tuberculosis PDIMs biomarkers in sputum[9,21,22]. This PDIM has an exceptionally low polarity hence it is an advantage to separate these molecules from other host specific lipids. The lipid extract of TB positive sera showed the presence of hexopyranose units. The mannopyranose units were also detected in the sera of tuberculosis infected cases. In Mycobacterium, the lipoarabinomannan structure is composed of mannopyranosyl branches[22,23]. The presence of mannopyranose unit in the sera confirms the presence of Mycobacterium sp in the host. These lipids mainly produce the mycocerosic acid methyl esters C29, C30 and C32, with molecular masses of 452, 466, and 494 Da, respectively[24]. It was identified from the previous research that drug resistance has close influence on the PDIM biosynthesis[25,26]. The rifampicin mutation was found to have up regulation in the polyketide synthase genes which are involved in the phenolpthiocerol biosynthesis[27]. The present study identifies the PDIM lipids as high abundant biomarkers. These high abundant biomarkers are easily detected even at split mode of analysis.

The splitless mode of detection identifies biomarkers like C14H23BrO, C11H24O2, C18H44O5, C14H30O3S, C24H39N in the sera of infected cases. The lipids are high volatile and detected as low abundant molecules in the splitless mode of analysis.

There are no reports available on these low abundant biomarkers in the circulation of tuberculosis infected cases.

The overall study concludes the presence of several biomarkers in the circulation of tuberculosis infections. These biomarkers are the truncated fragments of larger cell lipid rafts. Based on the availability of these lipids in the specimen, they have been further characterized as high abundant and low abundant lipids. The presence of these lipids can also be correlated with the state of infection like active infection and drug resistance. Hence these biomarkers could be explored further at various other diagnostic platform for detection of tuberculosis infection.

Acknowledgement

The authors are thankful to Grand Challenges Canada (S4 025301) for financial support under bold ideas for humanity, and Vikrant Institute of Technology & Management, Gwalior, India for partial financial support. The authors also thank AIRF facility, JNU campus, New Delhi, India for GC-MS analysis.

CONFLICT OF INTERESTS

The authors declare that they do not have conflict of interests.

REFERENCES

1Jantzen E, Tangen T, Eng J. Gas chromatography of mycobacterial fatty acids and alcohols: Diagnostic applications. APMIS 1989; 97: 1037-1045.

2Trefz P, Koehler H, Klepik K, Moebius P, Reinhold P, Schubert JK, Miekisch W. Volatile Emissions from Mycobacterium avium subsp.paratuberculosis Mirror Bacterial Growth and Enable Distinction of Different Strains. PloS One 2013; 8: e76868.

3Pavlou AK, Magana N, Jones JM, Brown J, Klatser P, Turner APF. Detection of Mycobacterium tuberculosis (TB) in vitro and in situ using an electronic nose in combination with a neural network system. Biosensors and Bioelectronics 2004; 20: 538-544.

4Peleda N, Ionescub R, Nolc P, Barash O ,McCollum M, VerCauteren K, Koslowa M, Stahl R, Rhyan J, Haick H. Detection of volatile organic compounds in cattle naturally infected with Mycobacterium bovis. Sensors and Actuators B 2012; 171-172: 588- 594.

5Purkhart R, Kohler H, Tenorio EL, Meyer M, Becher G, Kikowatz A, Reinhold P. Chronic intestinal Mycobacteria infection:discrimination via VOC analysis in exhaled breath and headspace of feces using differential ion mobility spectrometry. J Breath Res 2011; 5: 027103

6 Onwueme KC, Vos CJ, Zurita J, Ferreras JA, Quadr LEN. The dimycocerosate ester polyketide virulence factors of mycobacteria. Prog Lip. Res 2005; 44: 259-302

7Demarteau-Ginsburg H, Lederer E, Ryhage R, Ställberg-Stenhagen S, Stenhagen E. Structure of phthiocerol. Nature 1959; 153: 1117-1119.

8Minnikin DE, Polgar N. Studies relating to phthiocerol. Part VII. Phthiodiolone. Am J Chem Soc 1967; (C): 803-807.

9O'Sullivan DM, Nicoara SC, Mutetwa R, Mungofa S, Lee OY, Minnikin DE, Bardwell MW, Corbett EL, McNerney R, Morgan GH. Detection of Mycobacterium tuberculosis in sputum by gas chromatography-mass spectrometry of methyl mycocerosates released by thermochemolysis. PLoS One 2012; 7: e32836.

10Dang NA, Mourão M, Kuijper S, Walters E, Janssen HG, Kolk AH. Direct detection of Mycobacterium tuberculosis in sputum using combined solid phase extraction-gas chromatography-mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci 2015; 986-987: 115-122.

11Tiwari RP, Tiwari D, Garg SK, Chandra R, Bisen PS. Glycolipids of Mycobacterium tuberculosis Strain H37Rv Are Potential Serological Markers For Diagnosis of Active Tuberculosis. Clinical Diagnostic Laboratory Immunology 2005; 12: 465-473.

12 WHO. Global Tuberculosis Report 2015.

13Standards for TB Care in India. Geneva: World Health Organization Country Office for India; 2014 (http://www.tbcindia.nic.in/pdfs/STCI%20 Book_Final% 20% 200 60 514.pdf) accessed: 4 June 2014.

14Mayakova TI, Kuznetsova EE, Kovaleva MG, Plyusin SA. Gas chromatographic-mass spectrometric study of lipids and rapid diagnosis of Mycobacterium tuberculosis. J Chromatogr. B Biomed Appl 1995; 672: 133.

15 French GL, Chan CY, Cheung SW, Oo KT. Diagnosis of pulmonary tuberculosis by detection of tuberculostearic acid in sputum by using gas chromatography–mass spectrometry with selected ion monitoring. J Infect Dis 1987; 156: 356.

16Odham G, Larsson L, Mardh PA. Demonstration of tuberculostearic acid in sputum from patients with pulmonary tuberculosis by selected ion monitoring. J Clin Invest 1979; 63: 813.

17Larsson L, Odham G, Westerdahl G, Olsson B. Diagnosis of pulmonary tuberculosis by selected-ion monitoring: improved analysis of tuberculostearate in sputum using negative-ion mass spectrometry. J Clin Microbiol 1987; 25: 893.

18Kaal E, Kolk AH, Kuijper S, Janssen H.G. A fast method for the identification of Mycobacterium tuberculosis in sputum and cultures based on thermally assisted hydrolysis and methylation followed by gas chromatography–mass spectrometry. J Chromatogr A 2009; 1216: 6319.

19Nicoara SC, O’Sullivan DM, McNerney R, Corbett EL, Mutetwa R, Minnikin DE, Gilmour MA, Morgan GH. A study on offline and online methylation of tuberculostearicacid-a biomarker for tuberculosis. 29th Informal Meeting on Mass Spectrometry Book of Abstracts 2011; 87 ISBN: 978-88-89884-19-5.

20Nicoara SC, Turner NW, Minnikin DE, Lee OY, O'Sullivan DM, McNerney R, Mutetwa R, Corbett LE, Morgan GH. Development of sample cleanup methods for the analysis of Mycobacterium tuberculosis methyl mycocerosate biomarkers in sputum extracts by gas chromatography-mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci 2015; 986-987: 135-42.

21Nicoara SC, Minnikin DE, Lee OC, O'Sullivan DM, McNerney R, Pillinger CT, Wright IP, Morgan GH. Development and optimization of a gas chromatography/mass spectrometry method for the analysis of thermochemolytic degradation products of phthiocerol dimycocerosate waxes found in Mycobacterium tuberculosis. Rapid Commun Mass Spectrom 2013; 27:2374-2382.

22Appelmelk BJ,Dunnen JD, Driessen NN, Ummels R, Pak M, Nigou J, Larrouy-Maumus G, Gurcha SS,Movahedzadeh F, Geurtsen J, Brown EJ,Eysink Smeets MM, Besra GS, Willemsen PT, Lowary TL, van Kooyk Y, Maaskant JJ, Stoker NG, van der Ley P, Puzo G, Vandenbroucke-Grauls CM, Wieland CW, van der Poll T, Geijtenbeek TB, van der Sar AM, Bitter W. The mannose cap of mycobacterial does not dominate the Mycobacterium–host interaction. Cell Microbiol 2008; 10: 930-944.

23Guérardel Y, Maes E, Elass E, Leroy Y, Timmerman P, Besra GS, Locht C, Strecker G, Kremer L. Structural study of lipomannan and lipoarabinomannan from Mycobacterium chelonae. Presence of unusual components with α 1,3-mannopyranose side chains. J Biol Chem 2003; 277: 30635-30648.

24Drayson FK, Lewis JW, Polgar N. Experiments relating to phthiocerol. Part III. Degradative studies of a C11 oxidation product of phthiocerol. J Chem Soc 1958, 430-433.

25Farhat MR, Shapiro BJ, Kieser KJ, Sultana R, Jacobson KR, Victor TC, Warren RM, Streicher EM, Calver A, Sloutsky A, Kaur D, Posey JE, Plikaytis B, Oggioni MR, Gardy JL, Johnston JC, Rodrigues M, Tang PK, Kato-Maeda M, Borowsky ML, Muddukrishna B, Kreiswirth BN, Kurepina N, Galagan J, Gagneux S, Birren B, Rubin EJ, Lander ES, Sabeti PC, Murray M. Genomic analysis identifies targets of convergent positive selection in drug-resistant Mycobacterium tuberculosis. Nat Genet 2013; 45: 1183-9.

26Forrellad MA, Klepp LI, Gioffré A, Sabio y García J, Morbidoni HR, de la Paz Santangelo M, Cataldi AA, Bigi F. Virulence factors of the Mycobacterium tuberculosis complex. Virulence. 2013; 4: 3-66.

27Bisson GP, Mehaffy C, Broeckling C, Prenni J, Rifat D, Lun DS, Burgos M, Weissman D, Karakousis PC, Dobos K. Upregulation of the phthiocerol dimycocerosate biosynthetic pathway by rifampin-resistant, rpoB mutant Mycobacterium tuberculosis. J Bacteriol 2012; 194: 6441-6452.

Peer reviewer: Masoud Shamaei, National Research Institute of Tuberculosis and Lung Disease (NRITLD), Masih Daneshvari University Hospital, Tehran, Iran.

Refbacks

  • There are currently no refbacks.