Use of MALDI Biotyper plus ClinProTools mass spectra analysis for correct identification ofStreptococcus pneumoniaeandStreptococcus mitis/oralis

Taxonomic identification of Morocco scorpions using MALDI-MS fingerprints of venom proteomes and computational modeling

The venom of scorpions has been the subject of numerous studies. However, their taxonomic identification is not a simple task, leading to misidentifications. This study aims to provide a practical approach for identifying scorpions based on the venom molecular mass fingerprint (MFP). Specimens (251) belonging to fifteen species were collected from different regions in Morocco. Their MFPs were acquired using MALDI-MS. These were used as a training dataset to generate predictive models and a library of mean spectral profiles using software programs based on machine learning. The computational model achieved an overall recognition capability of 99 % comprising 32 molecular signatures. The models and the library were tested using a new dataset for external validation and to evaluate their capability of identification. We recorded an accuracy classification with an average of 97 % and 98 % for the computational models and the library, respectively. To our knowledge, this is the first attempt to demonstrate the potential of MALDI-MS and MFPs to generate predictive models capable of discriminating scorpions from family to species levels, and to build a library of species-specific spectra. These promising results may represent a proof of concept towards developing a reliable approach for rapid molecular identification of scorpions in Morocco. SIGNIFICANCE OF THE STUDY: With their clinical importance, scorpions may constitute a desirable study model for many researchers. The first step in studying scorpion is systematically identifying the species of interest. However, it can be a difficult task, especially for the non-experts. The taxonomy of scorpions is primarily based on morphometric characters. In Morocco, the high number of species and subspecies mainly endemic, and the morphological similarities between different species may result in false identifications. This was observed in many reports according to the scorpion experts. In this study, we describe a reliable practical approach for identifying scorpions based on the venom molecular mass fingerprints (MFPs). By using two software programs based on machine learning, we have demonstrated that these MFPs contains sufficient inter-specific variation to differentiate between the scorpion species mentioned in this study with a good accuracy. Using a drop of venom, this new approach could be a rapid, accurate and cost saving method for taxonomic identification of scorpions in Morocco.

Performance of Two Matrix-Assisted Laser Desorption Ionization-Time-of-Flight Mass Spectrometry (MALDI-TOF MS) Systems for Identification of the Viridans Group Streptococci

Background

Due to similar colony morphology among viridans group streptococci (VGS), the differentiation of VGS species remains difficult in routine clinical microbiology. Recently, matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) has been described as a fast method for identifying various bacteria at species level, and also for the VGS strains.

Methods

A total of 277 VGS isolates were identified with the two MALDI-TOF MS systems (VITEK MS and Bruker Biotyper). The tuf and rpoB gene sequencing was used as the reference identification method for comparison.

Results

Based on tuf and rpoB gene sequencing, 84 isolates were S. pneumoniae and 193 strains were other VGS isolates including S. anginosus group (n=91, 47.2%), S. mitis group (n=80, 41.5%), S. bovis group (n=11, 5.7%), S. salivarius group (n=10, 5.2%), and S. mutans group (n=1, 0.5%). VITEK MS and Bruker Biotyper accurately identified 94.6% and 89.9% of all VGS isolates, respectively. VITEK MS showed better identification results than Bruker Biotyper for S. mitis group including S. pneumoniae and S. bovis group, but for other VGS isolates, two MALDI-TOF MS systems showed comparable identification performance. However, VITEK MS was able to identify S. gallolyticus to the subspecies level with high-confidence (S. gallolyticus ssp. pasteurianus), while the Bruker Biotyper system could not. While Bruker Biotyper system could be able to correctly differentiate the subspecies of S. salivarius from S. vestibularis, VITEK MS poorly identify.

Conclusion

This study demonstrated that two MALDI-TOF MS systems allowed discrimination for most VGS isolates with different identification performance, but Bruker Biotyper could produce more misidentifications and VITEK MS system. It is crucial to be familiar with the performance of MALDI-TOF MS systems used in clinical microbiology.

Evaluation of the diagnostic value of serum-based proteomics for colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a highly malignant cancer with a high incidence and mortality in China. It is urgent to find a diagnostic marker with higher sensitivity and specificity than the traditional approaches for CRC diagnosis.

AIM

To provide new ideas for the diagnosis of CRC based on serum proteomics.

METHODS

Specimens from 83 healthy people, 62 colon polyp (CRP) patients, and 101 CRC patients were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The diagnostic value of the profiles of differentially expressed proteins was then analyzed.

RESULTS

Compared with the healthy control group, CRC patients had elevated expression of 5 proteins and reduced expression of 14 proteins. The area under the curve (AUC) for a differentially expressed protein with a mass-to-charge ratio of 2022.34 was the largest; the AUC was 0.843, which was higher than the AUC of 0.717 observed with carcinoembryonic antigen (CEA), and the sensitivity and specificity of this identified marker were 75.3% and 79.5%, respectively. After cross-validation, the accuracy of diagnosis using levels of this differentially expressed protein was 82.37%. Compared with the CRP group, the expression of 3 proteins in the serum of CRC patients was elevated and 11 proteins were expressed at reduced levels. Proteins possessing mass-to-charge ratio values of 2899.38 and 877.3 were selected to establish a classification tree model. The results showed that the accuracy of CRC diagnosis was 89.5%, the accuracy of CRP diagnosis was 81.6%, and the overall accuracy of this approach was 86.3%. The overall sensitivity and specificity of diagnosis using the proteomics approach were 81.8% and 66.75%, respectively. The sensitivities and specificities of diagnoses based on CEA and carbohydrate antigen 19-9 expression were 55.6% and 91.3% and 65.4% and 65.2%, respectively.

CONCLUSION

We demonstrated that serum proteomics may be helpful for the detection of CRC, and it may assist clinical practice for CRC diagnosis.

Streptococcus oriscaviae sp. nov. Infection Associated with Guinea Pigs

Pet bite-related infections are commonly caused by the pet's oral flora transmitted to the animal handlers through the bite wounds. In this study, we isolated a streptococcus, HKU75T, in pure culture from the purulent discharge collected from a guinea pig bite wound in a previously healthy young patient. HKU75T was alpha-hemolytic on sheep blood agar and agglutinated with Lancefield group D and group G antisera. API 20 STREP showed that the most likely identity for HKU75T was S. suis I with 85.4% confidence while Vitek 2 showed that HKU75T was unidentifiable. MALDI-TOF MS identified HKU75T as Streptococcus suis (score of 1.86 only). 16S rRNA gene sequencing showed that HKU75T was most closely related to S. parasuis (98.3% nucleotide identity), whereas partial groEL and rpoB gene sequencing showed that it was most closely related to S. suis (81.8% and 89.8% nucleotide identity respectively). Whole genome sequencing and intergenomic distance determined by ANI revealed that there was <85% identity between the genome of HKU75T and those of all other known Streptococcus species. Genome classification using concatenated sequences of 92 bacterial core genes showed that HKU75T belonged to the Suis group. groEL gene sequences identical to that of HKU75T could be directly amplified from the oral cavities of the two guinea pigs owned by the patient. HKU75T is a novel Streptococcus species, which we propose to be named S. oriscaviae. The oral cavity of guinea pigs is presumably a reservoir of S. oriscaviae. Some of the reported S. suis strains isolated from clinical specimens may be S. oriscaviae. IMPORTANCE We reported the discovery of a novel Streptococcus species, propose to be named Streptococcus oriscaviae, from the pus collected from a guinea pig bite wound in a healthy young patient. The bacterium was initially misidentified as S. suis/S. parasuis by biochemical tests, mass spectrometry. and housekeeping genes sequencing. Its novelty was confirmed by whole genome sequencing. Comparative genomic studies showed that S. oriscaviae belongs to the Suis group. S. oriscaviae sequences were detected in the oral cavities of the two guinea pigs owned by the patient, suggesting that the oral cavity of guinea pigs could be a reservoir of S. oriscaviae. Some of the reported S. suis strains may be S. oriscaviae. Further studies are warranted to refine our knowledge on this novel Streptococcus species.

Application and Perspectives of MALDI-TOF Mass Spectrometry in Clinical Microbiology Laboratories

Early diagnosis of severe infections requires of a rapid and reliable diagnosis to initiate appropriate treatment, while avoiding unnecessary antimicrobial use and reducing associated morbidities and healthcare costs. It is a fact that conventional methods usually require more than 24–48 h to culture and profile bacterial species. Mass spectrometry (MS) is an analytical technique that has emerged as a powerful tool in clinical microbiology for identifying peptides and proteins, which makes it a promising tool for microbial identification. Matrix assisted laser desorption ionization–time of flight MS (MALDI–TOF MS) offers a cost- and time-effective alternative to conventional methods, such as bacterial culture and even 16S rRNA gene sequencing, for identifying viruses, bacteria and fungi and detecting virulence factors and mechanisms of resistance. This review provides an overview of the potential applications and perspectives of MS in clinical microbiology laboratories and proposes its use as a first-line method for microbial identification and diagnosis.

Characteristics of the intestinal microbiota and metabolism in infants with extrauterine growth restriction

BACKGROUND

Infants with extrauterine growth restriction (EUGR) experience significant postnatal growth restriction in the first week after birth, which indicates a failure of energy absorption. This study aimed to determine the different intestinal microbial species and metabolites between infants with EUGR and those without EUGR.

METHODS

A total of 73 infants hospitalized in a neonatal intensive care unit were enrolled and divided into the EUGR group (n=50) and the non-EUGR group (n=23). Fecal samples were collected during hospitalization. Bacterial species and their relative abundance were identified with metagenome sequencing. The metabolites in the feces and blood were identified with a liquid chromatography-mass spectrometry (LC-MS) based non-targeted metabolome.

RESULTS

The intestinal microbiota of the EUGR group contained less Bacteroides vulgatus, Dorea unclassified, Lachnospiraceae bacterium 1_1_57FAA, and Roseburia unclassified compared to that of the non-EUGR group. More importantly, the intestinal microbiota of the EUGR group contained Streptococcus mitis_oralis_pneumoniae, while that of the non-EUGR group did not. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) prediction and a correlation analysis identified that the majority of different microbial species higher in the non-EUGR group were related to metabolism. The results of the non-targeted metabolome revealed that several metabolites in the feces and blood were much higher in either group, and some of which were related to the different microbial species.

CONCLUSIONS

This study identified several different intestinal microbial species and metabolites in the patients' feces and blood, which may provide evidence to identify the biomarkers of infants with EUGR.

Topological and kernel-based microbial phenotype prediction from MALDI-TOF mass spectra

MOTIVATION

Microbial species identification based on matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) has become a standard tool in clinical microbiology. The resulting MALDI-TOF mass spectra also harbour the potential to deliver prediction results for other phenotypes, such as antibiotic resistance. However, the development of machine learning algorithms specifically tailored to MALDI-TOF MS-based phenotype prediction is still in its infancy. Moreover, current spectral pre-processing typically involves a parameter-heavy chain of operations without analyzing their influence on the prediction results. In addition, classification algorithms lack quantification of uncertainty, which is indispensable for predictions potentially influencing patient treatment.

RESULTS

We present a novel prediction method for antimicrobial resistance based on MALDI-TOF mass spectra. First, we compare the complex conventional pre-processing to a new approach that exploits topological information and requires only a single parameter, namely the number of peaks of a spectrum to keep. Second, we introduce PIKE, the peak information kernel, a similarity measure specifically tailored to MALDI-TOF mass spectra which, combined with a Gaussian process classifier, provides well-calibrated uncertainty estimates about predictions. We demonstrate the utility of our approach by predicting antibiotic resistance of three clinically highly relevant bacterial species. Our method consistently outperforms competitor approaches, while demonstrating improved performance and security by rejecting out-of-distribution samples, such as bacterial species that are not represented in the training data. Ultimately, our method could contribute to an earlier and precise antimicrobial treatment in clinical patient care.

AVAILABILITY AND IMPLEMENTATION

We make our code publicly available as an easy-to-use Python package under https://github.com/BorgwardtLab/maldi_PIKE.

Evaluation of three sample preparation methods for the identification of clinical strains by using two MALDI-TOF MS systems

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has revolutionized the microbial identification, especially in the clinical microbiology laboratories. However, although numerous studies on the identification of microorganisms by MALDI-TOF MS have been reported previously, few studies focused on the effect of pretreatment on identification. Due to the sensitivity of MALDI-TOF MS, different preparation methods will lead to changes in microbial protein fingerprints. In this study, for evaluating a more appropriate preparation method for the clinical microbiology identification, we analyzed the performance of three sample preparation methods on two different MALDI-TOF MS systems. A total of 321 clinical isolates, 127 species, were employed in the comparative study of three different sample preparation methods including the direct colony transfer method (DCTM), the on-target extraction method (OTEM), and the in-tube extraction method (ITEM) compatible with MALDI-TOF MS. All isolates were tested on the Microflex LT and Autof ms1000 devices. The spectra were analyzed using the Bruker biotyper and the Autof ms1000 systems. The results were confirmed by 16/18S rRNA sequencing. Results reveal that the accuracies of isolates identification by Bruker biotyper successfully identified 83.8%, 96.0%, and 95.3% after performing the DCTM, OTEM, and ITEM, respectively, while the Autof ms1000 identified 97.5%, 100%, and 99.7%. These data suggested that the identification rates are comparable among the three preparation methods using the Autof ms1000 and Bruker microflex LT systems but the OTEM is more suitable and necessary for clinical application, owing to its key advantages of simplicity and accuracy.

Identification of Clinically Relevant Streptococcus and Enterococcus Species Based on Biochemical Methods and 16S rRNA, sodA, tuf, rpoB, and recA Gene Sequencing

Streptococci and enterococci are significant opportunistic pathogens in epidemiology and infectious medicine. High genetic and taxonomic similarities and several reclassifications within genera are the most challenging in species identification. The aim of this study was to identify Streptococcus and Enterococcus species using genetic and phenotypic methods and to determine the most discriminatory identification method. Thirty strains recovered from clinical samples representing 15 streptococcal species, five enterococcal species, and four nonstreptococcal species were subjected to bacterial identification by the Vitek^® 2 system and Sanger-based sequencing methods targeting the 16S rRNA, sodA, tuf, rpoB, and recA genes. Phenotypic methods allowed the identification of 10 streptococcal strains, five enterococcal strains, and four nonstreptococcal strains (Leuconostoc, Granulicatella, and Globicatella genera). The combination of sequencing methods allowed the identification of 21 streptococcal strains, five enterococcal strains, and four nonstreptococcal strains. The 16S rRNA and rpoB genes had the highest identification potential. Only a combination of several molecular methods was sufficient for unambiguous confirmation of species identity. This study will be useful for comparison of several identification methods, both those used as a first choice in routine microbiology and those used for final confirmation.

Differentiation between Streptococcus pneumoniae and other viridans group streptococci by matrix-assisted laser desorption/ionization time of flight mass spectrometry

OBJECTIVES

Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) is becoming the method of choice for bacterial identification. However, correct identification by MALDI-TOF of closely related microorganisms such as viridans streptococci is still cumbersome, especially in the identification of S. pneumoniae. By making use of additional spectra peaks for S. pneumoniae and other viridans group streptococci (VGS). We re-identified viridans streptococci that had been identified and characterized by molecular and phenotypic techniques by MALDI-TOF.

METHODS

VGS isolates (n = 579), 496 S. pneumoniae and 83 non-S. pneumoniae were analysed using MALDI-TOF MS and the sensitivity and specificity of MALDI-TOF MS was assessed. Hereafter, mass spectra analysis was performed. Presumptive identification of proteins represented by discriminatory peaks was performed by molecular weight matching and the corresponding nucleotides sequences against different protein databases.

RESULTS

Using the Bruker reference library, 495 of 496 S. pneumoniae isolates were identified as S. pneumoniae and one isolate was identified as non-S. pneumoniae. Of the 83 non-S. pneumoniae isolates, 37 were correctly identified as non-S. pneumoniae, and 46 isolates as S. pneumoniae. The sensitivity of the MALDI-TOF MS was 99.8% (95% confidence interval (CI) 98.9-100) and the specificity was 44.6% (95% CI 33.7-55.9). Eight spectra peaks were mostly present in one category (S. pneumoniae or other VGS) and absent in the other category and inversely. Two spectra peaks of these (m/z 3420 and 3436) were selected by logistic regression to generate three identification profiles. These profiles could differentiate between S. pneumoniae and other VGS with high sensitivity and specificity (99.4% and 98.8%, respectively).

CONCLUSIONS

Spectral peaks analysis based identification is a powerful tool to differentiate S. pneumoniae from other VGS species with high specificity and sensitivity and is a useful method for pneumococcal identification in carriage studies. More research is needed to further confirm our findings. Extrapolation of these results to clinical strains need to be deeply investigated.

Nanopore metagenomics enables rapid clinical diagnosis of bacterial lower respiratory infection

The gold standard for clinical diagnosis of bacterial lower respiratory infections (LRIs) is culture, which has poor sensitivity and is too slow to guide early, targeted antimicrobial therapy. Metagenomic sequencing could identify LRI pathogens much faster than culture, but methods are needed to remove the large amount of human DNA present in these samples for this approach to be feasible. We developed a metagenomics method for bacterial LRI diagnosis that features efficient saponin-based host DNA depletion and nanopore sequencing. Our pilot method was tested on 40 samples, then optimized and tested on a further 41 samples. Our optimized method (6 h from sample to result) was 96.6% sensitive and 41.7% specific for pathogen detection compared with culture and we could accurately detect antibiotic resistance genes. After confirmatory quantitative PCR and pathobiont-specific gene analyses, specificity and sensitivity increased to 100%. Nanopore metagenomics can rapidly and accurately characterize bacterial LRIs and might contribute to a reduction in broad-spectrum antibiotic use.

Identification of Streptococcus pneumoniae by a real-time PCR assay targeting SP2020

Real-time PCR targeting lytA (the major autolysin gene) and piaB (permease gene of the pia ABC transporter) are currently used as the gold-standard culture-independent assays for Streptococcus pneumoniae identification. We evaluated the performance of a new real-time PCR assay – targeting SP2020 (putative transcriptional regulator gene) – and compared its performance with the assays previously described. A collection of 150 pneumococci, 433 non-pneumococci and 240 polymicrobial samples (obtained from nasopharynx, oropharynx, and saliva; 80 from each site) was tested. SP2020 and lytA-CDC assays had the best performance (sensitivity of 100% for each compared to 95.3% for piaB). The specificity for lytA and piaB was 99.5% and for SP2020 was 99.8%. Misidentifications occurred for the three genes: lytA, piaB and SP2020 were found in non-pneumococcal strains; piaB was absent in some pneumococci including a serotype 6B strain. Combining lytA and SP2020 assays resulted in no misidentifications. Most polymicrobial samples (88.8%) yielded concordant results for the three molecular targets. The remaining samples seemed to contain non-typeable pneumococci (0.8%), and non-pneumococci positive for lytA (1.7%) or SP2020 (8.7%). We propose that combined detection of both lytA-CDC and SP2020 is a powerful strategy for the identification of pneumococcus either in pure cultures or in polymicrobial samples.

Clinical Mass Spectrometry in the Bioinformatics Era: A Hitchhiker's Guide

Mass spectrometry (MS) is a sensitive, specific and versatile analytical technique in the clinical laboratory that has recently undergone rapid development. From initial use in metabolic profiling, it has matured into applications including clinical toxicology assays, target hormone and metabolite quantitation, and more recently, rapid microbial identification and antimicrobial resistance detection by matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). In this mini-review, we first succinctly outline the basics of clinical mass spectrometry. Examples of hard ionization (electron ionization) and soft ionization (electrospray ionization, MALDI) are presented to demonstrate their clinical applications. Next, a conceptual discourse on mass selection and determination is presented: quadrupole mass filter, time-of-flight mass spectrometer and the Orbitrap; and MS/MS (tandem-in-space, tandem-in-time and data acquisition), illustrated with clinical examples. Current applications in (1) bacterial and fungal identification, antimicrobial susceptibility testing and phylogenetic classification, (2) general unknown urine toxicology screening and expanded new-born metabolic screening and (3) clinical metabolic profiling by gas chromatography are outlined. Finally, major limitations of MS-based techniques, including the technical challenges of matrix effect and isobaric interference; and novel challenges in the post-genomic era, such as protein molecular variants, are critically discussed from the perspective of service laboratories. Computer technology and structural biology have played important roles in the maturation of this field. MS-based techniques have the potential to replace current analytical techniques, and existing expertise and instrument will undergo rapid evolution. Significant automation and adaptation to regulatory requirements are underway. Mass spectrometry is unleashing its potentials in clinical laboratories.

Identification of Candida glabrata complex species: use of Vitek MS® RUO & Bruker ClinproTools®

AIM

Distinction of species within the Candida glabrata complex (i.e., C. glabrata sensu stricto, Candida nivariensis and Candida bracarensis) is relevant for epidemiological purposes and antifungal management.

MATERIALS & METHODS

Two commercial matrix-assisted laser desorption ionization-time of flight mass spectrometry systems were comprehensively evaluated for the identification of fungi within this complex.

RESULTS

None of the species (C. nivariensis and C. bracarensis) were identified correctly by Vitek mass spectrometry (MS^®) v2.0 In Vitro Diagnosis system and Bruker Biotyper MS^® v3.1, but all were correct by the Vitek MS^® Research Use Only system. The Bruker ClinProTools software showed 100% recognition capability and cross validation for the discrimination of C. nivariensis and C. bracarensis.

CONCLUSION

Using Vitek MS Research Use Only and Bruker ClinProTools can overcome limitations of the Vitek MS In Vitro Diagnosis and Bruker Biotyper databases in the identification of C. glabrata complex.

Rapid Differentiation of Haemophilus influenzae and Haemophilus haemolyticus by Use of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry with ClinProTools Mass Spectrum Analysis

Haemophilus influenzae is associated with severe invasive disease, while Haemophilus haemolyticus is considered part of the commensal flora in the human respiratory tract. Although the addition of a custom mass spectrum library into the matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) system could improve identification of these two species, the establishment of such a custom database is technically complicated and requires a large amount of resources, which most clinical laboratories cannot afford. In this study, we developed a mass spectrum analysis model with 7 mass peak biomarkers for the identification of H. influenzae and H. haemolyticus using the ClinProTools software. We evaluated the diagnostic performance of this model using 408 H. influenzae and H. haemolyticus isolates from clinical respiratory specimens from 363 hospitalized patients and compared the identification results with those obtained with the Bruker IVD MALDI Biotyper. The IVD MALDI Biotyper identified only 86.9% of H. influenzae (311/358) and 98.0% of H. haemolyticus (49/50) clinical isolates to the species level. In comparison, the ClinProTools mass spectrum model could identify 100% of H. influenzae (358/358) and H. haemolyticus (50/50) clinical strains to the species level and significantly improved the species identification rate (McNemar's test, P < 0.0001). In conclusion, the use of ClinProTools demonstrated an alternative way for users lacking special expertise in mass spectrometry to handle closely related bacterial species when the proprietary spectrum library failed. This approach should be useful for the differentiation of other closely related bacterial species.

Accurate Differentiation of Streptococcus pneumoniae from other Species within the Streptococcus mitis Group by Peak Analysis Using MALDI-TOF MS

Despite the benefits of MALDI-TOF MS technology (Matrix-Assisted Laser Desorption-Ionization Time-Of-Flight Mass Spectrometry) reported worldwide and the continuous improving of the available databases, discrimination between Streptococcus pneumoniae and closely related species within the Streptococcus mitis group (SMG) using this methodology has been suboptimal. However, the accurate identification at the species level of this group of microorganisms is important for the appropriate management of infected patients. In this study, 216 SMG isolates -101 S. pneumoniae and 115 corresponding to 7 non-pneumococcal species within this group- were analyzed. All the isolates had been previously identified by conventional methods (optochin and bile solubility tests) and non-pneumococcal isolates were confirmed by sequence analysis (sodA and plys genes) when required. The isolates were also identified with the MALDI Biotyper 3.1 (Bruker Daltonics, Bremen, Germany) using an updated library containing 6,903 Main Spectra Profiles (MSPs). All the analyzed S. pneumoniae were correctly identified with MALDI-TOF MS at species level using the most updated database and all the non-pneumococcal SMG isolates were also identified at the group level. Several peaks (4,964.32, 6,888.90, and 9,516.46 m/z) have been found to be specific of S. pneumoniae, whilst a different set of peaks have proved to be present only in S. mitis (6,839.07 m/z) and S. oralis (5,297.61, 5822.53, and 6,839.07 m/z). Peak analysis allowed correct species assignment of 101/101 S. pneumoniae isolates (100%) and 102/105 S. mitis/oralis isolates (97.1%). Thus, the implementation of MALDI-TOF MS plus peak analysis for the identification of this group of microorganisms may provide precise species-level information that will allow the early implementation of directed antibiotic therapy.

Fast methods of fungal and bacterial identification. MALDI-TOF mass spectrometry, chromogenic media

MALDI-TOF mass spectrometry is now a routine resource in Clinical Microbiology, because of its speed and reliability in the identification of microorganisms. Its performance in the identification of bacteria and yeasts is perfectly contrasted. The identification of mycobacteria and moulds is more complex, due to the heterogeneity of spectra within each species. The methodology is somewhat more complex, and expanding the size of species libraries, and the number of spectra of each species, will be crucial to achieve greater efficiency. Direct identification from blood cultures has been implemented, since its contribution to the management of severe patients is evident, but its application to other samples is more complex. Chromogenic media have also contributed to the rapid diagnosis in both bacteria and yeast, since they accelerate the diagnosis, facilitate the detection of mixed cultures and allow rapid diagnosis of resistant species.

Matrix assisted laser desorption time of flight mass spectrometry (MALDI-TOF MS) in clinical microbiology

The microbiological management of patients with suspected bacterial infection includes the identification of the pathogen and the determination of the antibiotic susceptibility. These traditional approaches, based on the pure culture of the microorganism, require at least 36-48h. A new method, Matrix Assisted Laser Desorption Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS), has been recently developed to profile bacterial proteins from whole cell extracts and obtain a bacterial fingerprint able to discriminate microorganisms from different genera and species. By whole cell-mass spectrometry, microbial identification can be achieved within minutes from cultured isolate, rather than traditional phenotypic or genotypic characterizations. From the year 2009 an explosion of applications of this technology has been observed with promising results. Several studies have been performed and showed that MALDI-TOF represents a reliable alternative method for rapid bacteria and fungi identification in clinical setting. A future area of expansion is represented by the application of MALDI-TOF technology to the antibiotic susceptibility test. In conclusion, the revision of the literature available up to date demonstrated that MALDI-TOF MS represents an innovative technology for the rapid and accurate identification of bacterial and fungal isolates in clinical settings. By an earlier microbiological diagnosis, MALDI-TOF MS contributes to a reduced mortality and hospitalization time of the patients and consequently has a significant impact on cost savings and public health.

Streptococcus anginosus (milleri) Group Strains Isolated in Poland (1996-2012) and their Antibiotic Resistance Patterns

Streptococcus anginosus, Streptococcus intermedius and Streptococcus constellatus form a group of related streptococcal species, namely the Streptococcus Anginosus Group (SAG). The group, previously called "milleri" had been rarely described until 1980/1990 as source of infections. Nowadays SAG bacteria are often described as pathogens causing predominantly purulent infections. The number of infections is highly underestimated, as SAG strains are often classified in the microbiology laboratory as less virulent "viridans streptococci" Epidemiological situation regarding SAG infections in Poland has been unrecognized, therefore we performed a retrospective analysis of strains isolated between 1996 and 2012. Strains suspected of belonging to SAG were re-identified using an automated biochemical approach (Vitek2) and MALDI-TOF MS. We performed first analysis of antibiotic resistance among SAG strains isolated in Poland using automated methods (Vitek2), disk diffusion tests and E-Tests. We also performed PCR detection of resistance determinants in antibiotic resistant strains. Clonal structure of analyzed strains was evaluated with PFGE and MLVF methods. All three species are difficult to distinguish using automated diagnostic methods and the same is true for automated MIC evaluation. Our analysis revealed SAG strains are rarely isolated in Poland, predominantly from purulent infections. All isolates are very diverse on the genomic level as estimated by PFGE and MLVF analyses. All analyzed strains are sensitive to penicillin, a substantial group of strains is resistant to macrolides and the majority of strains are resistant to tetracycline.

Challenges in biomarker discovery with MALDI-TOF MS

MALDI-TOF MS technique is commonly used in system biology and clinical studies to search for new potential markers associated with pathological conditions. Despite numerous concerns regarding a sample preparation or processing of complex data, this strategy is still recognized as a popular tool and its awareness has risen in the proteomic community over the last decade. In this review, we present comprehensive application of MALDI mass spectrometry with special focus on profiling research. We also discuss major advantages and disadvantages of universal sample preparation methods such as micro-SPE columns, immunodepletion or magnetic beads, and we show the potential of nanostructured materials in capturing low molecular weight subproteomes. Furthermore, as the general protocol considerably affects spectra quality and interpretation, an alternative solution for improved ion detection, including hydrophobic constituents, data processing and statistical analysis is being considered in up-to-date profiling pattern. In conclusion, many reports involving MALDI-TOF MS indicated highly abundant proteins as valuable indicators, and at the same time showed the inaccuracy of available methods in the detection of low abundant proteome that is the most interesting from the clinical perspective. Therefore, the analytical aspects of sample preparation methods should be standardized to provide a reproducible, low sample handling and credible procedure.

Clinical features and outcome of bone and joint infections with streptococcal involvement: 5-year experience of interregional reference centres in the south of France

Streptococcal bone and joint infections are less common than staphylococcal cases. Few studies have reported the cases with well-identified Streptococcus species. Their clinical features and prognosis are not clearly known to date. Moreover, no treatment regimen has yet been clarified. We reviewed the streptococcal bone and joint infection cases managed in our centres from January 2009 to December 2013. We described the epidemiology, clinical and microbiologic characteristics, treatment approach and outcome. Among the 93 cases, 83% of patients were men with a median age of 60 years, and 90% of patients had comorbidities or risk factors. Bacteraemia occurred in 14% of cases. Serious complications occurred in six patients, including severe sepsis (two cases) and infective endocarditis (two cases). Orthopaedic device infections were observed in 35% of cases, including 17 patients with internal osteosynthesis device infection, 14 with prosthetic joint infection and three with vertebral osteosynthesis device infection. The median time between orthopaedic device implantation and onset of infection was 447 days. Fourteen species of Streptococcus were identified, including 97 isolates using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and three isolates using molecular identification. The five most represented species included S. agalactiae (37%), S. dysgalactiae (12%), S. anginosus (11%), S. constellatus (10%) and S. pneumoniae (9%). Streptococci isolates were susceptible to amoxicillin, with the exception of one S. mitis isolate. Remission 1 year after the end of treatment was recorded in 83%. One patient died of infection; eight patients had infections that failed to respond to treatment; and seven patients experienced relapse. Twenty patients (22%) had an unfavourable functional outcome, including 19 amputations and one arthrodesis. Five significant prognostic factors associated with an unfavourable clinical outcome were identified, including peripheral neuropathy (p 0.009), peripheral arterial disease (p 0.019), diabetes mellitus (p 0.031), location in the femur (p 0.0036), location in the foot (p 0.0475), osteitis without an orthopaedic device (p 0.041) and infection caused by S. dysgalactiae (p 0.020). The rate of poor outcomes remains high despite the low number of Streptococcus isolates resistant to antibiotics. Some prognostic factors, such as the presence of S. dysgalactiae, are associated with an unfavourable clinical outcome. Antibiotic regimens of streptococcal bone and joint infections are not standardized and need to be further investigated.

Antimicrobial effect of Pistacia atlantica leaf extract

The antimicrobial effect of the mastic tree (Pistacia atlantica) under in vitro conditions has been reported. Therefore, it is of interest to evaluate the effect of the plant leaf extract (aqueous) on bacterial load in mouth and saliva. The leaf of the Pistacia atlantica plant was collected and cleaned, dried at 40⁰c and then powdered. The extraction was carried out using the maceration method in vacuum with the rotary evaporator device. Bacterial inhibition (Streptococcus species) by the leaf extract was studied using the disc diffusion and embedding sink diffusion methods. The values of MIC and MBC were determined. The collected data was further analyzed using t-test and repeated measure statistical tests. The disc diffusion technique showed a significant inhibitory effect for Pistacia atlantica leaf extract on S. mutans (ATCC 35668) and S. mitis (ATCC 49456) with inhibition zones of 19 and 25 millimeters, respectively. This is for the highest leaf extract concentration used in this study (p<0.01). The values of MIC and MBC for S.mutans was 60, 90 μg/ml and for S. mitis was 75, 110 μg/ml (p<0.01 significance). The leaf extract has no significant effect on S. salivarius (ATCC 13419). Thus, the antimicrobial properties of the aqueous leaf extract from Pistacia atlantica is demonstrated in this study.

MLVF analysis of anginosus (milleri) group streptococci

We developed a new method of typing for anginosus group streptococci (SAG). It is the first SAG-dedicated, PCR-based method, which allows to determine the relationship between strains. The method is based on the detection of tandem repeats among 9 genomic loci and is classified as multilocus variable number tandem repeats fingerprint (MLVF) type of analysis. Using the described method, it is possible to detect over half million MLVF patterns, which correlate with pulsed-field gel electrophoresis profiles. The other advantage of the method is relatively short time from "cell to data", low costs, and easy application for epidemiological and evolutionary studies.