Discrimination between Streptococcus pneumoniae and Streptococcus mitis based on sorting of their MALDI mass spectra

Ikryannikova, Larisa N.; Filimonova, Alla V.; Malakhova, Maja V.; Savinova, Tatiana; Filimonova, O.Y.; Ilina, Elena N.; Dubovickaya, V.A.; Сидоренко, С. В.; Govorun, Vadim M.

doi:10.1111/1469-0691.12113

Cited by 71 publications

(55 citation statements)

References 30 publications

(45 reference statements)

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“…All classification algorithms that were generated and tested identified Hib among the H. influenzae isolates, with variations in sensitivity and specificity. The ClinProTools model had the best and most robust results, performing similarly to or better than models based on this software in previous studies (23)(24)(25).…”

Section: Discussionsupporting

confidence: 59%

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Identification of Haemophilus influenzae Type b Isolates by Use of Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

et al. 2015

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dHaemophilus influenzae type b (Hib) is, in contrast to non-type b H. influenzae, associated with severe invasive disease, such as meningitis and epiglottitis, in small children. To date, accurate H. influenzae capsule typing requires PCR, a time-consuming and cumbersome method. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) provides rapid bacterial diagnostics and is increasingly used in clinical microbiology laboratories. Here, MALDI-TOF MS was evaluated as a novel approach to separate Hib from other H. influenzae. PCR-verified Hib and non-Hib reference isolates were selected based on genetic and spectral characteristics. Mass spectra of reference isolates were acquired and used to generate different classification algorithms for Hib/non-Hib differentiation using both ClinProTools and the MALDI Biotyper software. A test series of mass spectra from 33 Hib and 77 non-Hib isolates, all characterized by PCR, was used to evaluate the algorithms. Several algorithms yielded good results, but the two best were a ClinProTools model based on 22 separating peaks and subtyping main spectra (MSPs) using MALDI Biotyper. The ClinProTools model had a sensitivity of 100% and a specificity of 99%, and the results were 98% reproducible using a different MALDI-TOF MS instrument. The Biotyper subtyping MSPs had a sensitivity of 97%, a specificity of 100%, and 93% reproducibility. Our results suggest that it is possible to use MALDI-TOF MS to differentiate Hib from other H. influenzae. This is a promising method for rapidly identifying Hib in unvaccinated populations and for the screening and surveillance of Hib carriage in vaccinated populations. Haemophilus influenzae type b (Hib) has been, and in some regions still is, the dominating cause of severe invasive disease associated with the species H. influenzae. More specifically, it is (or used to be) a feared cause of meningitis and epiglottitis in small children (1, 2). The conjugate vaccines against Hib that were introduced in the early 1990s have resulted in a steep decline in invasive Hib disease (1, 3-5). However, Hib still causes 5 to 10% of invasive H. influenzae disease in Sweden, and occasional cases of fully vaccinated children with invasive Hib disease have been reported in several countries (6, 7). Hib is estimated to cause a substantial number of infections and deaths among young children each year on a global basis (8). PCR is at present required for accurate Hib capsule typing (9-11) but is a relatively time-consuming and laborious method. Agglutination with antisera is an alternative method used for capsular typing. Even though this is a faster method than PCR, studies have shown that its accuracy is comparatively poor (12).Early studies have suggested that the Hib population consists of two genetically distinct clusters (13,14). This population structure was later confirmed using multilocus sequence typing (MLST), since practically all Hib isolates that had been submitted to the MLST database from all over the world cou...

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Section: Discussionsupporting

confidence: 59%

“…A few recent studies have also been published that use ClinProTools software for bacterial classification, for example, for the differentiation of Shigella species from E. coli and Streptococcus pneumoniae from Streptococcus mitis (23,24). These studies also used ethanol-formic acid extraction.…”

Section: Discussionmentioning

confidence: 99%

Identification of Haemophilus influenzae Type b Isolates by Use of Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

et al. 2015

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“…Among the three model generation algorithms available, models based on the genetic algorithm performed better for our study isolates than the other algorithms (Supervised Neural Network and QuickClassifier; data not shown). Two recent studies have used classification models generated using ClinProTools software for distinguishing between two Staphylococcus aureus strains (22) and between Streptococcus pneumoniae and S. mitis (23). The genetic algorithm was either the optimal algorithm for model generation or worked as well as the other options in both studies.…”

Section: Discussionmentioning

confidence: 99%

Novel Approach for Differentiating Shigella Species and Escherichia coli by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

2013

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bShigella species are so closely related to Escherichia coli that routine matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) cannot reliably differentiate them. Biochemical and serological methods are typically used to distinguish these species; however, "inactive" isolates of E. coli are biochemically very similar to Shigella species and thus pose a greater diagnostic challenge. We used ClinProTools (Bruker Daltonics) software to discover MALDI-TOF MS biomarker peaks and to generate classification models based on the genetic algorithm to differentiate between Shigella species and E. coli. Sixtysix Shigella spp. and 72 E. coli isolates were used to generate and test classification models, and the optimal models contained 15 biomarker peaks for genus-level classification and 12 peaks for species-level classification. We were able to identify 90% of E. coli and Shigella clinical isolates correctly to the species level. Only 3% of tested isolates were misidentified. This novel MALDI-TOF MS approach allows laboratories to streamline the identification of E. coli and Shigella species.

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“…MLSA assigns VGS strains to a species by comparing the concatenated partial sequences of seven housekeeping genes to a database of VGS strains, including type strains (3). Although this approach produces well-resolved species clusters, MLSA is not feasible in a routine clinical microbiology setting due to the time, workload, expense, and difficulty in reliably amplifying all the genes (10,31). Therefore, there is still a need for a simple and dependable method for identifying VGS strains to the species level.…”

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confidence: 99%

GyrB Polymorphisms Accurately Assign Invasive Viridans Group Streptococcal Species

et al. 2014

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Viridans group streptococci (VGS) are a heterogeneous group of medically important bacteria that cannot be accurately assigned to a particular species using conventional phenotypic methods. Although multilocus sequence analysis (MLSA) is considered the gold standard for VGS species-level identification, MLSA is not yet feasible in the clinical setting. Conversely, molecular methods, such as sodA and 16S rRNA gene sequencing, are clinically practical but not sufficiently accurate for VGS species-level identification. Here, we present data regarding the use of an ϳ400-nucleotide internal fragment of the gene encoding DNA gyrase subunit B (GyrB) for VGS species-level identification. MLSA, internal gyrB, sodA, full-length, and 5= 16S gene sequences were used to characterize 102 unique VGS blood isolates collected from 2011 to 2012. When using the MLSA species assignment as a reference, full-length and 5= partial 16S gene and sodA sequence analyses failed to correctly assign all strains to a species. Precise species determination was particularly problematic for Streptococcus mitis and Streptococcus oralis isolates. However, the internal gyrB fragment allowed for accurate species designations for all 102 strains. We validated these findings using 54 VGS strains for which MLSA, 16S gene, sodA, and gyrB data are available at the NCBI, showing that gyrB is superior to 16S gene and sodA sequence analyses for VGS species identification. We also observed that specific polymorphisms in the 133-amino acid sequence of the internal GyrB fragment can be used to identify invasive VGS species. Thus, the GyrB amino acid sequence may offer a more practical and accurate method for classifying invasive VGS strains to the species level.V iridans group streptococci (VGS) are a genetically heterogeneous group of commensal bacteria that cause a wide range of infections in humans, particularly in persons with hematologic disease or neutropenia as a result of chemotherapy (1, 2). Although Ͼ25 VGS species have been described, rapid and reliable identification to the species level eludes this group of organisms (3, 4). Accurate species identification is pertinent not only for epidemiological purposes but has potential implications for the clinical management of VGS infections. For example, recent studies show that Streptococcus mitis strains cause a higher incidence of severe clinical disease and have higher rates of resistance to penicillin and fluoroquinolones than do other VGS species (2, 4-6). Additionally, other VGS species have predilections to cause distinct types of infections, such as endocarditis by Streptococcus sanguinis and gastrointestinal infections by Streptococcus anginosus (2, 6).Routine tests and commercial kits used in clinical practice based on the phenotypic and biochemical traits of individual species, such as API Rapid ID32 Strep, Vitek 2, and Streptogram, have only a 30% to 80% accuracy rate for VGS, depending on the species (7-10). The inherent problems with these approaches lie in the variability of traits within V...

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Discrimination between Streptococcus pneumoniae and Streptococcus mitis based on sorting of their MALDI mass spectra

Cited by 71 publications

References 30 publications

Identification of Haemophilus influenzae Type b Isolates by Use of Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

Identification of Haemophilus influenzae Type b Isolates by Use of Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

Novel Approach for Differentiating Shigella Species and Escherichia coli by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

GyrB Polymorphisms Accurately Assign Invasive Viridans Group Streptococcal Species

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