Automatic identification of mixed bacterial species fingerprints in a MALDI-TOF mass-spectrum.
BACKGROUND
Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry has been broadly adopted by routine clinical microbiology laboratories for bacterial species identification. An isolated colony of the targeted microorganism is the single prerequisite. Currently, MS-based microbial identification directly from clinical specimens can not be routinely performed, as it raises two main challenges: (i) the nature of the sample itself may increase the level of technical variability and bring heterogeneity with respect to the reference database and (ii) the possibility of encountering polymicrobial samples that will yield a 'mixed' MS fingerprint. In this article, we introduce a new method to infer the composition of polymicrobial samples on the basis of a single mass spectrum. Our approach relies on a penalized non-negative linear regression framework making use of species-specific prototypes, which can be derived directly from the routine reference database of pure spectra.


RESULTS
A large spectral dataset obtained from in vitro mono- and bi-microbial samples allowed us to evaluate the performance of the method in a comprehensive way. Provided that the reference matrix-assisted laser desorption/ionization time-of-flight mass spectrometry fingerprints were sufficiently distinct for the individual species, the method automatically predicted which bacterial species were present in the sample. Only few samples (5.3%) were misidentified, and bi-microbial samples were correctly identified in up to 61.2% of the cases. This method could be used in routine clinical microbiology practice.
BioMérieux SA, Unit Innovation and Systems, Marcy l'Etoile, 69280, France and BioMérieux SA, Unit Microbiology, R&D Microbiology, La Balme Les Grottes, 38390, France.
Pierre
P
Mahé
Maud
M
Arsac
Sonia
S
Chatellier
Valérie
V
Monnin
Nadine
N
Perrot
Sandrine
S
Mailler
Victoria
V
Girard
Mahendrasingh
M
Ramjeet
Jérémy
J
Surre
Bruno
B
Lacroix
Alex
A
van Belkum
Jean-Baptiste
JB
Veyrieras
D001331:Automation; D030541:Databases, Genetic; D006090:Gram-Negative Bacteria / Q000737:chemistry* / Q000302:isolation & purification; D006094:Gram-Positive Bacteria / Q000302:isolation & purification*; D016014:Linear Models; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*