Identification of mycobacterium spp. and nocardia spp. from solid and liquid cultures by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS).

Identification of microorganisms by MALDI-TOF MS has been widely accepted in clinical microbiology. However, for Mycobacterium spp. and Nocardia spp. such identification has not yet reached the optimal level of routine testing. Here we describe the development of an identification tool for 49 and 15 species of Mycobacterium spp. and Nocardia spp., respectively. During database construction, a number of ambiguous reference identifications were revealed and corrected via molecular analyses. Eventually, more than 2000 individual mass spectra acquired from 494 strains were included in a reference database and subjected to bio-statistical analyses. This led to correct species identification and correct combination of species into several complexes or groups, such as the Mycobacterium tuberculosis complex. With the Advanced Spectrum Classifier algorithm, class-specific bin weights were determined and tested by cross-validation experiments with good results. When challenged with independent isolates, overall identification performance was 90% for identification of Mycobacterium spp. and 88% for Nocardia spp. However, for a number of Mycobacterium sp. isolates, no identification could be achieved and in most cases, this could be attributed to the production of polymers that masked the species-specific protein peak patterns. For the species where >20 isolates were tested, correct identification reached 95% or higher. With the current spectral database, the identification of Mycobacterium spp. and Nocardia spp. by MALDI-TOF MS can be performed in routine clinical diagnostics although in some complicated cases verification by sequencing remains mandatory.

Microbial typing by matrix-assisted laser desorption ionization-time of flight mass spectrometry: do we need guidance for data interpretation?

The integration of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) in clinical microbiology has revolutionized species identification of bacteria, yeasts, and molds. However, beyond straightforward identification, the method has also been suggested to have the potential for subspecies-level or even type-level epidemiological analyses. This minireview explores MALDI-TOF MS-based typing, which has already been performed on many clinically relevant species. We discuss the limits of the method's resolution and we suggest interpretative criteria allowing valid comparison of strain-specific data. We conclude that guidelines for MALDI-TOF MS-based typing can be developed along the same lines as those used for the interpretation of data from pulsed-field gel electrophoresis (PFGE).

Matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry using the Vitek MS system for rapid and accurate identification of dermatophytes on solid cultures.

The objective of this research was to extend the Vitek MS fungal knowledge base version 2.0.0 to allow the robust identification of clinically relevant dermatophytes, using a variety of strains, incubation times, and growth conditions. First, we established a quick and reliable method for sample preparation to obtain a reliable and reproducible identification independently of the growth conditions. The Vitek MS V2.0.0 fungal knowledge base was then expanded using 134 well-characterized strains belonging to 17 species in the genera Epidermophyton, Microsporum, and Trichophyton. Cluster analysis based on mass spectrum similarity indicated good species discrimination independently of the culture conditions. We achieved a good separation of the subpopulations of the Trichophyton anamorph of Arthroderma benhamiae and of anthropophilic and zoophilic strains of Trichophyton interdigitale. Overall, the 1,130 mass spectra obtained for dermatophytes gave an estimated identification performance of 98.4%. The expanded fungal knowledge base was then validated using 131 clinical isolates of dermatophytes belonging to 13 taxa. For 8 taxa all strains were correctly identified, and for 3 the rate of successful identification was >90%; 75% (6/8) of the M. gypseum strains were correctly identified, whereas only 47% (18/38) of the African T. rubrum population (also called T. soudanense) were recognized accurately, with a large quantity of strains misidentified as T. violaceum, demonstrating the close relationship of these two taxa. The method of sample preparation was fast and efficient and the expanded Vitek MS fungal knowledge base reliable and robust, allowing reproducible dermatophyte identifications in the routine laboratory.

Automatic identification of mixed bacterial species fingerprints in a MALDI-TOF mass-spectrum.

MOTIVATION: 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.

Microarray for hepatitis B virus genotyping and detection of 994 mutations along the genome.

Genome analysis of hepatitis B virus (HBV) in patient sera is helpful for monitoring treatment. We developed an improved version of a DNA microarray to identify HBV genotypes and to detect mutations of interest in the S, Pol, Core, and X genes. It includes an automated software analysis of fluorescence values for simpler, more robust data interpretation. In this version, probes were added to identify genotype H, to analyze 155 additional positions, and to detect 561 additional polymorphisms. Sequences were added to the alignments to resolve hybridization problems due to natural polymorphisms in the vicinity of important codons. The duplex PCR protocol allowed whole-genome analysis in a single tube. An alternative nested-PCR protocol allowed genotyping and mutations in S and reverse transcriptase (rt) genes in patients with low viral loads, as demonstrated in patients with less than 400 HBV genome copies/ml. Reproducibility was high, with variation coefficients lower than 3%. Only 0.57% of 20,771 codons from 253 samples could not be identified. The concordance with Sanger sequencing for the identification of codons improved from 92.8% to 95.7% with the improved version. Concordance was higher than 91% for codons associated with resistance to lamivudine, emtricitabine, telbivudine, famciclovir, entecavir, and tenofovir with vaccine escape and for pre-Core mutants. Concordance was lower for adefovir resistance mutations (68.6%) and mutations in the basal core promoter (60.3%), probably because hybridization efficiency was affected by the low GC content of the probes. A concordance of 93.7% with sequencing for genotype identification was observed in 190 specimens, lower than that obtained with the first version, possibly due to mixed virus populations.

Custom human endogenous retroviruses dedicated microarray identifies self-induced HERV-W family elements reactivated in testicular cancer upon methylation control.

Endogenous retroviruses (ERVs) are an inherited part of the eukaryotic genomes, and represent approximately 400,000 loci in the human genome. Human endogenous retroviruses (HERVs) can be divided into distinct families, composed of phylogenetically related but structurally heterogeneous elements. The majority of HERVs are silent in most physiological contexts, whereas a significant expression is observed in pathological contexts, such as cancers. Owing to their repetitive nature, few of the active HERV elements have been accurately identified. In addition, there are no criteria defining the active promoters among HERV long-terminal repeats (LTRs). Hence, it is difficult to understand the HERV (de)regulation mechanisms and their implication on the physiopathology of the host. We developed a microarray to specifically detect the LTR-containing transcripts from the HERV-H, HERV-E, HERV-W and HERV-K(HML-2) families. HERV transcriptome was analyzed in the placenta and seven normal/tumoral match-pair samples. We identified six HERV-W loci overexpressed in testicular cancer, including a usually placenta-restricted transcript of ERVWE1. For each locus, specific overexpression was confirmed by quantitative RT-PCR, and comparison of the activity of U3 versus U5 regions suggested a U3-promoted transcription coupled with 5'R initiation. The analysis of DNA from tumoral versus normal tissue revealed that hypomethylation of U3 promoters in tumors is a prerequisite for their activation.