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Susceptibility

A Rapid Unraveling of the Activity and Antibiotic Susceptibility of Mycobacteria

A. Mustazzolu, L. Venturelli, S. Dinarelli, K. Brown, R. A. Floto, G. Dietler, L. Fattorini, S. Kasas, M. Girasole, G. Longo
A. Mustazzolu
aIstituto Superiore di Sanità, Rome, Italy
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L. Venturelli
bLPMV–IPHYS, Ecole Polytechnique Fédérale Lausanne, Lausanne, Switzerland
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S. Dinarelli
cIstituto di Struttura della Materia, Consiglio Nazionale delle Ricerche, Rome, Italy
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K. Brown
dMolecular Immunity Unit, University of Cambridge, Cambridge, United Kingdom
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R. A. Floto
dMolecular Immunity Unit, University of Cambridge, Cambridge, United Kingdom
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G. Dietler
bLPMV–IPHYS, Ecole Polytechnique Fédérale Lausanne, Lausanne, Switzerland
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L. Fattorini
aIstituto Superiore di Sanità, Rome, Italy
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S. Kasas
bLPMV–IPHYS, Ecole Polytechnique Fédérale Lausanne, Lausanne, Switzerland
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M. Girasole
cIstituto di Struttura della Materia, Consiglio Nazionale delle Ricerche, Rome, Italy
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G. Longo
cIstituto di Struttura della Materia, Consiglio Nazionale delle Ricerche, Rome, Italy
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DOI: 10.1128/AAC.02194-18
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    FIG 1

    Control experiments involving BCG and M. abscessus. Typical data patterns (performed minimally in triplicates) of BCG (a) and M. abscessus (b) in MGIT medium. The fluctuations are present for more than 200 min.

  • FIG 2
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    FIG 2

    Nanomotion experiments on BCG exposed to an over-MIC dose of INH. (Top) Typical 10-min segments of the sensor’s fluctuations before the exposure to INH (left), immediately after the exposure to INH at 2 μg/ml (center), and 20 min after the exposure to INH, when the movement reduction has stabilized. (Bottom) Histogram of the corresponding variance of the fluctuations. The graph is representative of minimally 5 independent experiments which produced similar results. The error bars represent SDs of the fluctuations during the corresponding 10-min time periods.

  • FIG 3
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    FIG 3

    Nanomotion experiments on BCG exposed to an over-MIC dose of RIF. (Top) Typical 20-min segments of the sensor’s fluctuations before the exposure to RIF (left), immediately after the exposure to RIF at 0.7 μg/ml (center), and 80 min after the exposure to RIF, when the movement reduction has stabilized. (Bottom) Histogram of the corresponding variance of the fluctuations. The graph is representative of 3 independent experiments which produced similar results. The error bars represent SDs of the fluctuations during the corresponding 20-min time periods.

  • FIG 4
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    FIG 4

    Dose dependence experiments. (a) Normalized variance calculated from the deflections collected by exposing BCG to different INH concentrations. (b) Normalized variance calculated from the deflections collected by exposing BCG to different RIF concentrations. (c) Normalized variance calculated from the deflections collected by exposing M. abscessus to different AK concentrations. The concentration values can be well fitted with a sigmoid function, which is comparable with the antibiogram plots obtained using conventional microbiological techniques. The MIC and MBC toward the bacterial species can be obtained by calculating the tangents of the sigmoid fits at half height (black dashed lines). Each data point represents the average from a minimum of 3 independent experiments performed using the same drug concentration. The error bars represent the variability of the different experiments performed at the same concentration. In each graph, the experiments involving sub-MIC drug concentrations are represented as a single data point, which summarizes all these experiments.

  • FIG 5
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    FIG 5

    Nanomotion experiments on BCG exposed to a sub-MIC doses of INH and RIF. (a, top) Typical 20-min segments of the sensor’s fluctuations before the exposure to INH (left), immediately after the exposure to INH at 0.025 μg/ml (center), and 140 min after the exposure to INH, when the movement has stabilized. (Bottom) Histogram of the corresponding variance of the fluctuations. (b, top) Typical 20-min segments of the sensor’s fluctuations before the exposure to RIF (left), immediately after the exposure to RIF at 0.07 μg/ml (center), and 95 min after the exposure to RIF, when the movement has stabilized. (Bottom) Histogram of the corresponding variance of the fluctuations. Each graph is representative of minimally 3 independent experiments which produced similar results. The error bars represent SDs of the fluctuations during the corresponding 20-min time periods.

  • FIG 6
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    FIG 6

    Time-resolved analysis of the BCG response to INH. Typical data pattern of the response of BCG to a bactericidal dose of INH (1 μg/ml). Over a 140-min period, the fluctuations increase and decrease in amplitude, highlighting the bacterial response to the antibiotic pressure. The graph is representative of 3 independent experiments in which this feature was evidenced.

  • FIG 7
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    FIG 7

    Nanomotion experiments on M. abscessus exposed to AK. (a, top) Typical 20-min segments of the sensor’s fluctuations exposed to an over-MIC dose of AK before the exposure to AK (left), immediately after the exposure to AK at 10 μg/ml (center), and 50 min after the exposure to AK, when the movement has stabilized. (Bottom) Histogram of the corresponding variance of the fluctuations. (b, top) Typical 20-min segments of the sensor’s fluctuations exposed to a sub-MIC dose of AK before the exposure to AK (left), 30 min after the exposure to AK at 1 μg/ml (center), and 90 min after the exposure to AK, when the movement has recovered and stabilized. (Bottom) Histogram of the corresponding variance of the fluctuations. Each graph is representative of at least 3 independent experiments which produced similar results. The error bars represent SDs of the fluctuations during the corresponding 20-min time periods.

  • FIG 8
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    FIG 8

    Optical images of bacterium-bearing sensors. Typical optical images of rectangular (left panels) and triangular sensors (right panels) bearing BCG (a) and M. abscessus (b). The optical images show the BCG clumping. Scale bars, 50 μm.

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A Rapid Unraveling of the Activity and Antibiotic Susceptibility of Mycobacteria
A. Mustazzolu, L. Venturelli, S. Dinarelli, K. Brown, R. A. Floto, G. Dietler, L. Fattorini, S. Kasas, M. Girasole, G. Longo
Antimicrobial Agents and Chemotherapy Feb 2019, 63 (3) e02194-18; DOI: 10.1128/AAC.02194-18

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A Rapid Unraveling of the Activity and Antibiotic Susceptibility of Mycobacteria
A. Mustazzolu, L. Venturelli, S. Dinarelli, K. Brown, R. A. Floto, G. Dietler, L. Fattorini, S. Kasas, M. Girasole, G. Longo
Antimicrobial Agents and Chemotherapy Feb 2019, 63 (3) e02194-18; DOI: 10.1128/AAC.02194-18
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  • Article
    • ABSTRACT
    • INTRODUCTION
    • RESULTS
    • DISCUSSION
    • MATERIALS AND METHODS
    • ACKNOWLEDGMENTS
    • FOOTNOTES
    • REFERENCES
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KEYWORDS

antibiotic response
collective movements
fast characterization
metabolic activity
mycobacteria
nanomotion sensor
susceptibility

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