Biomerieux, Inc.

Maud Arsac

Pierre-Jean Cotte-Pattat

Denis Desseree

Grégory Strubel

Francois Mallet

Pierre Mahe

Jean-Philippe Pichon

John D Walsh

Jones M Hyman

François Mallet

Victoria Girard

Bertrand Bonnaud

Parampal Deol

Valérie Monnin

Elizabeth Miller

Amber Gates

Sandrine Mailler

John Walsh

A method of identifying a microorganism by mass spectrometry, including acquiring at least one mass spectrum of said microorganism; for each acquired mass spectrum: detecting peaks of the spectrum in a predetermined mass range; generating a list of peaks identifying at most one peak in each interval of a predetermined subdivision of the range of mass-to-charge ratios, the width of the intervals of the subdivision logarithmically increasing along with the mass-to-charge ratio, and analyzing the list(s) of peaks obtained according to a knowledge base of previously-identified microorganisms and/or types of microorganisms.

Method for identifying microorganisms by mass spectrometry

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 by mass spectrometry an unknown microorganism subgroup among a set of reference subgroups, including a step of constructing one knowledgebase and one classifying model per associated subgroup on the basis of the acquisition of at least one set of learning spectra of microorganisms identified as belonging to the subgroups of a group and including: constructing an adjusting model allowing mass-to-charge offsets of the acquired spectra to be corrected on the basis of reference masses-to-charges that are common to the various subgroups; adjusting the masses-to-charges of all of the lists of peaks of the learning spectra and constructing one classifying model per subgroup and the associated knowledgebase on the basis of the adjusted learning spectra.

Method for identifying by mass spectrometry an unknown microorganism subgroup from a set of reference subgroups

The invention relates to a method for in vitro diagnosis or prognosis of testicular cancer which comprises a step of detecting the presence or absence of at least one expression product from at least one nucleic acid sequence selected from the sequences identified in SEQ ID NOS: 1 to 6 or from the sequences which exhibit at least 99% identity with one of the sequences identified in SEQ ID NOS: 1 to 6, to isolated nucleic acid sequences and to the use thereof as a testicular cancer marker.

Method for in vitro diagnosis or prognosis of testicular cancer

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

The present invention is directed to a method for inactivation and/or extraction of acid-fast bacteria (e.g.,or), the method comprising the following sequential steps: (a) acquiring a test sample known to contain or that may contain acid-fast bacteria and suspending the test sample in a container containing ethanol and beads; (b) bead beating and/or vortexing the container to break up clumps and/or disrupt acid-fast bacteria cells in the container; and (c) subsequently incubating the suspension for at least about 3 minutes at room temperature to inactivate any acid-fast bacteria contained in the test sample. In accordance with the present invention, the test sample can subsequently be pelleted by centrifugation, resuspended with formic acid, acetonitrile added, and subjected to mass spectrometry for characterization and/or identification of the acid-fast bacteria.

Methods for inactivation and extraction of acid-fast bacteria for characterization and/or identification using mass spectrometry

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Saint-Chamond, France

Maud Arsac