Biomerieux, Inc.

Biomerieux Sa

Pierre Mahe

Maud Arsac

Pierre-Jean Cotte-Pattat

Denis Desseree

Grégory Strubel

Maud Tournoud

Denis Leroux

Philippine Barlas

Rony Midahuen

Mahendrasingh Ramjeet

Gaël Kaneko

Margaux Chapel

Stéphane Schicklin

Eric Laloum

Ghislaine Guigon

Etienne Ruppe

Kevin Vervier

Jean-Baptiste Veyrieras

Maragux Chapel

An identification by mass spectrometry of a microorganism from among reference microorganisms represented by reference data sets includes: determining a set of data of the microorganism according to a spectrum; for each reference microorganism, calculating a distance between the determined and reference sets; and calculating a probability ƒ(m) according to relation where: m is the distance calculated for the reference microorganism; N(m|μ,σ) is the value, for m, of a random variable modeling the distance between a reference microorganism to be identified and the reference microorganism, when the microorganism is the reference microorganism; N(m|,) is the value, for m, of a random variable modeling the distance between a microorganism to be identified and the reference microorganism, when the microorganism is not the reference microorganism; and p is a scalar in the range from 0 to 1.

Method for identifying microorganisms by mass spectrometry and score normalization

A method for identifying a pathogen contained in a metagenomic sample and for identifying pathogenic markers in the genome of the pathogen includes: processing the sample to extract DNA from pathogens, sequencing the extracted DNA, thereby producing a set of reads, comparing the reads to a database of genomes of known pathogens to assign reads to the pathogens; producing a pool of reads and assembling them to produce contigs, comparing the contigs to a second database of markers to check whether they contain a marker. The method further includes the step of comparing the reads to the second database to assign reads to the markers, a read being assigned to a marker if it falls entirely into or is astride the marker, and the pool also includes the reads assigned to the markers, the contigs thereby being assembled from reads assigned to a pathogen and reads assigned to markers.

Identification and antibiotic characterization of pathogens in metagenomic sample

A method for quantifying the sensibility of a test microorganism to a concentration of an antimicrobial agent includes: preparing two liquid samples including the microorganism, one having the antimicrobial agent and one without; for each sample acquiring, by a flow cytometer, a digital set values including a fluorescence, forward, or side scatter distribution, and computing: a first coordinate value corresponding to the acquired distribution main mode and an acquired distribution first area for values greater than the first coordinate value, and a second coordinate value, greater than the first, for which an acquired distribution second area between the values equals a first area predefined percentage over 50%; computing a ratio according to: where Mode(ATB) and QT(ATB) are the first and second coordinate values with the antimicrobial agent concentration, and Mode(no ATB) and QT(no ATB) are respectively the first and second coordinate values without the antimicrobial agent concentration.

Flow cytometry data processing for antimicrobial agent sensibility prediction

A method for determining a quantity Gquantifying the inhibitory capacity of a molecule on a type of microorganism includes: preparing a plurality of samples, including microorganisms of the type, a nutrient medium for the microorganism and an initial amount of the molecule per microorganism increasing in a range [Q,Q] as a function of a classification of the samples; measuring the growth of the microorganisms in the samples as a function of time; and determining the quantity Gas a function of the measurements of the growth. Determination of the quantity Gincludes: for each sample, calculating a value reflecting the growth of the microorganism of said type based on measurements of growth; classifying the values calculated for the samples as a function of the classification of the samples; and determining the quantity Gas a function of the variation of the classified values.

Method and device for characterizing the inhibitory capacity of a molecule on a microorganism

A detection of the Gram type of a bacterial strain includes: illumination, in the wavelength range 415 nm-440 nm, of at least one bacterium of said strain having a natural electromagnetic response in said range; acquisition, in the range 415 nm-440 nm, of a light intensity reflected by, or transmitted through, said illuminated bacterium; and determination of the Gram type of the bacterial strain as a function of the light intensity acquired in the range 415 nm-440 nm.

Process and system for identifying the gram type of a bacterium

An identification by mass spectrometry of a microorganism from among reference microorganisms represented by reference data sets includes: determining a set of data of the microorganism according to a spectrum; for each reference microorganism, calculating a distance between the determined and reference sets; and calculating a probability f(m) according to relation where: m is the distance calculated for the reference microorganism; N(m|&#x3bc;,&#x3c3;) is the value, for m, of a random variable modeling the distance between a reference microorganism to be identified and the reference microorganism, when the microorganism is the reference microorganism; N(m|,) is the value, for m, of a random variable modeling the distance between a microorganism to be identified and the reference microorganism, when the microorganism is not the reference microorganism; and p is a scalar in the range from 0 to 1.

Method for identifying microorganisms via mass spectrometry and score normalization

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Pierre Mahe