Accurate Identification Of Microorganisms Research Articles

Multiplexing the Identification of Microorganisms via Tandem Mass Tag Labeling Augmented by Interference Removal through a Novel Modification of the Expectation Maximization Algorithm.

Having fast, accurate, and broad spectrum methods for the identification of microorganisms is of paramount importance to public health, research, and safety. Bottom-up mass spectrometer-based proteomics has emerged as an effective tool for the accurate identification of microorganisms from microbial isolates. However, one major hurdle that limits the deployment of this tool for routine clinical diagnosis, and other areas of research such as culturomics, is the instrument time required for the mass spectrometer to analyze a single sample, which can take ∼1 h per sample, when using mass spectrometers that are presently used in most institutes. To address this issue, in this study, we employed, for the first time, tandem mass tags (TMTs) in multiplex identifications of microorganisms from multiple TMT-labeled samples in one MS/MS experiment. A difficulty encountered when using TMT labeling is the presence of interference in the measured intensities of TMT reporter ions. To correct for interference, we employed in the proposed method a modified version of the expectation maximization (EM) algorithm that redistributes the signal from ion interference back to the correct TMT-labeled samples. We have evaluated the sensitivity and specificity of the proposed method using 94 MS/MS experiments (covering a broad range of protein concentration ratios across TMT-labeled channels and experimental parameters), containing a total of 1931 true positive TMT-labeled channels and 317 true negative TMT-labeled channels. The results of the evaluation show that the proposed method has an identification sensitivity of 93-97% and a specificity of 100% at the species level. Furthermore, as a proof of concept, using an in-house-generated data set composed of some of the most common urinary tract pathogens, we demonstrated that by using the proposed method the mass spectrometer time required per sample, using a 1 h LC-MS/MS run, can be reduced to 10 and 6 min when samples are labeled with TMT-6 and TMT-10, respectively. The proposed method can also be used along with Orbitrap mass spectrometers that have faster MS/MS acquisition rates, like the recently released Orbitrap Astral mass spectrometer, to further reduce the mass spectrometer time required per sample.

Microbiological diagnostics: From traditional to molecular genetic methods: A literature review

The development of new and optimisation of known cultural and molecular genetic methods for accurate species identification of microorganisms is an urgent and practically necessary task that is receiving great attention from researchers. The purpose of this study was to analyse and systematise theoretical scientific data on methods of microbial identification and assess their main advantages and disadvantages. For this purpose, a systematic review of 53 randomised research papers published between 2018 and 2023 was conducted. The search for publications using the keywords “microbiome”, “microbiological diagnostics”, “identification of microorganisms”, “sequencing”, and “omics technologies” in the title or text of the research paper was carried out in Web of Science, Scopus, PubMed, and Google Scholar. The study provides generalised information on traditional and modern methods of microbial identification. It is established that the advantages of traditional diagnostic methods include the possibility of preserving the obtained microorganisms for further research, in particular, for determining their antibiotic sensitivity. Modern molecular genetic methods open up new possibilities for the accurate identification of microorganisms, including those that are difficult to incubate using traditional cultural methods. The use of these methods allows obtaining detailed data on the genetic structure and diversity of microorganisms, which is important in many fields, including microbiology, medicine, and ecology. However, molecular methods are more sensitive to contamination or errors in the sample collection and processing. Moreover, omics technologies (genomics, transcriptomics, proteomics, and metabolomics) open up new opportunities for studying cells at more complex levels of life organisation. In everyday clinical practice, the microbiological method of isolating microbial cultures remains the main one, as it is the only one that allows determining not only the cause of the infection but also the antibiotic sensitivity. However, cultural methods for studying fastidious microorganisms are quite limited. Thus, the results obtained contribute to the development of fast and accurate methods for identifying, classifying, and systematising microorganisms, which facilitates the processes of diagnosis and development of strategies for the control and treatment of infectious diseases in laboratories and clinical institutions

Multi-point scanning confocal Raman spectroscopy for accurate identification of microorganisms at the single-cell level

Raman spectroscopy has been widely used for microbial analysis due to its exceptional qualities as a rapid, simple, non-invasive, reproducible, and real-time monitoring tool. The Raman spectrum of a cell is a superposition of the spectral information of all biochemical components in the laser focus. In the case where the microbial size is larger than the laser spot size, the Raman spectrum measured from a single-point within a cell cannot capture all biochemical information due to the spatial heterogeneity of microorganisms. In this work, we have proposed a method for the accurate identification of microorganisms using multi-point scanning confocal Raman spectroscopy. Through an image recognition algorithm and the control of a high-precision motorized stage, Raman spectra can be integrated at one time to measure the multi-point biochemical information of microorganisms. This solves the problem that the measured single microbial cells are of different sizes, and the laser spot of the confocal Raman system is not easy to change. Here, the single-cell Raman spectra of three Escherichia coli and seven Lactobacillus species were measured separately. The commonly used supervised classification method, support vector machine (SVM), was applied to compare the data based on the single-point spectra and multi-point scanning spectra. Multi-point spectra showed superior performance in terms of their accuracy and recall rates compared with single-point spectra. The results show that multi-point scanning confocal Raman spectra can be used for more accurate species classification at different taxonomic levels, which is of great importance in species identification.

SERS-PLSR Analysis of Vaginal Microflora: Towards the Spectral Library of Microorganisms.

The accurate identification of microorganisms belonging to vaginal microflora is crucial for establishing which microorganisms are responsible for microbial shifting from beneficial symbiotic to pathogenic bacteria and understanding pathogenesis leading to vaginosis and vaginal infections. In this study, we involved the surface-enhanced Raman spectroscopy (SERS) technique to compile the spectral signatures of the most significant microorganisms being part of the natural vaginal microbiota and some vaginal pathogens. Obtained data will supply our still developing spectral SERS database of microorganisms. The SERS results were assisted by Partial Least Squares Regression (PLSR), which visually discloses some dependencies between spectral images and hence their biochemical compositions of the outer structure. In our work, we focused on the most common and typical of the reproductive system microorganisms (Lactobacillus spp. and Bifidobacterium spp.) and vaginal pathogens: bacteria (e.g., Gardnerella vaginalis, Prevotella bivia, Atopobium vaginae), fungi (e.g., Candida albicans, Candida glabrata), and protozoa (Trichomonas vaginalis). The obtained results proved that each microorganism has its unique spectral fingerprint that differentiates it from the rest. Moreover, the discrimination was obtained at a high level of explained information by subsequent factors, e.g., in the inter-species distinction of Candida spp. the first three factors explain 98% of the variance in block Y with 95% of data within the X matrix, while in differentiation between Lactobacillus spp. and Bifidobacterium spp. (natural flora) and pathogen (e.g., Candida glabrata) the information is explained at the level of 45% of the Y matrix with 94% of original data. PLSR gave us insight into discriminating variables based on which the marker bands representing specific compounds in the outer structure of microorganisms were found: for Lactobacillus spp. 1400 cm−1, for fungi 905 and 1209 cm−1, and for protozoa 805, 890, 1062, 1185, 1300, 1555, and 1610 cm−1. Then, they can be used as significant marker bands in the analysis of clinical subjects, e.g., vaginal swabs.

“Omic” Approaches to Bacteria and Antibiotic Resistance Identification

The quick and accurate identification of microorganisms and the study of resistance to antibiotics is crucial in the economic and industrial fields along with medicine. One of the fastest-growing identification methods is the spectrometric approach consisting in the matrix-assisted laser ionization/desorption using a time-of-flight analyzer (MALDI-TOF MS), which has many advantages over conventional methods for the determination of microorganisms presented. Thanks to the use of a multiomic approach in the MALDI-TOF MS analysis, it is possible to obtain a broad spectrum of data allowing the identification of microorganisms, understanding their interactions and the analysis of antibiotic resistance mechanisms. In addition, the literature data indicate the possibility of a significant reduction in the time of the sample preparation and analysis time, which will enable a faster initiation of the treatment of patients. However, it is still necessary to improve the process of identifying and supplementing the existing databases along with creating new ones. This review summarizes the use of “-omics” approaches in the MALDI TOF MS analysis, including in bacterial identification and antibiotic resistance mechanisms analysis.

The Prevalence of Nosocomial Infections and Related Microbial Agents Based on the NNIS System in Sabzevar During 2011-2015

Background: Nosocomial infection is an infection that hospitalized patients get while receiving health care. This study aimed to determine the prevalence and factors involved in the incidence of nosocomial infections, related microbial agents, and antibiotic resistance profiles. Methods: This cross-sectional study was conducted on 390 patients with nosocomial infection admitted to Shahid Beheshti Hospital in Sabzevar from 2011 to 2015. The acquired data were assessed by the standard checklist of the National Nosocomial Infections Surveillance (NNIS) system of the Ministry of Health. The collected data were analyzed using the Stata 12 software. Results: Of the 41979 admitted patients during the mentioned period, 390 patients with an average age of 48.08 years suffered from a hospital-acquired infection. The prevalence of nosocomial infections was 1% with the highest rate related to the respiratory tract in men and surgical sites in women. Intravenous catheters, surgical wounds, urinary catheters, suction, ventilator, tracheotomy, and tracheostomy were the most commonly encountered factors (invasive measures) of nosocomial infection, respectively. The most prevalent causes of nosocomial infections were Klebsiella, Staphylococcus aureus, and Acinetobacter. Conclusions: Based on our findings, several factors play a pivotal role in preventing hospital-associated infections, including proper follow-up and timely reporting of nosocomial infection cases. The other influential factors were accurate identification of microorganisms involved, allocation of sufficient funds to provide appropriate facilities for infection prevention, the appropriate and timely medical interventions, and the rational use of antibiotics.

Traditional Fermented Foods from Ecuador: A Review with a Focus on Microbial Diversity.

The development of early civilizations was greatly associated with populations’ ability to exploit natural resources. The development of methods for food preservation was one of the pillars for the economy of early societies. In Ecuador, food fermentation significantly contributed to social advances and fermented foods were considered exclusive to the elite or for religious ceremonies. With the advancement of the scientific research on bioprocesses, together with the implementation of novel sequencing tools for the accurate identification of microorganisms, potential health benefits and the formation of flavor and aroma compounds in fermented foods are progressively being described. This review focuses on describing traditional fermented foods from Ecuador, including cacao and coffee as well as less popular fermented foods. It is important to provide new knowledge associated with nutritional and health benefits of the traditional fermented foods.

THz-ATR Spectroscopy Integrated with Species Recognition Based on Multi-Classifier Voting for Automated Clinical Microbial Identification.

The demand for rapid and accurate identification of microorganisms is growing due to considerable importance in all areas related to public health and safety. Here, we demonstrate a rapid and label-free strategy for the identification of microorganisms by integrating terahertz-attenuated total reflection (THz-ATR) spectroscopy with an automated recognition method based on multi-classifier voting. Our results show that 13 standard microbial strains can be classified into three different groups of microorganisms (Gram-positive bacteria, Gram-negative bacteria, and fungi) by THz-ATR spectroscopy. To detect clinical microbial strains with better differentiation that accounts for their greater sample heterogeneity, an automated recognition algorithm is proposed based on multi-classifier voting. It uses three types of machine learning classifiers to identify five different groups of clinical microbial strains. The results demonstrate that common microorganisms, once time-consuming to distinguish by traditional microbial identification methods, can be rapidly and accurately recognized using THz-ATR spectra in minutes. The proposed automatic recognition method is optimized by a spectroscopic feature selection algorithm designed to identify the optimal diagnostic indicator, and the combination of different machine learning classifiers with a voting scheme. The total diagnostic accuracy reaches 80.77% (as high as 99.6% for Enterococcus faecalis) for 1123 isolates from clinical samples of sputum, blood, urine, and feces. This strategy demonstrates that THz spectroscopy integrated with an automatic recognition method based on multi-classifier voting significantly improves the accuracy of spectral analysis, thereby presenting a new method for true label-free identification of clinical microorganisms with high efficiency.

Species-level discrimination of microorganisms by high-resolution paper spray – Ion mobility – Mass spectrometry

There is a projection of 10 million deaths per year by 2050 due to antimicrobial resistance, highlighting the need for rapid detection and accurate identification of microorganisms. Herein, we used the paper spray technique coupled with ion mobility separation and tandem mass spectrometry (PS-IM-MS/MS) to rapidly discriminate and identify five Bacillus species in 2 min of analysis time after only 4 h of incubation time. Bacterial cells were harvested by filtering their liquid cultures and ionized directly by PS. Numerical multivariate statistics (principal component analysis, followed by linear discriminant analysis) allowed species-level discrimination with a prediction rate of 92.4% and 97.6% utilizing the negative and positive ion information of PS-MS/MS, respectively. However, upon including the biomarkers' corresponding drift times, i.e., PS-IM-MS/MS, prediction rates of ca. 99.7% and 100% were obtained utilizing the negative and positive ion information, respectively. We attributed the enhancement in the prediction rates to the capability of IM separations in resolving isomers. Surfactins and phospholipids were the major ion populations detected in our experiments. They were found to have various diagnostic isomers for various Bacillus species. Therefore, improved prediction rates could be obtained upon including high-resolution IM separations in the workflow. These proof-of-concept studies described here suggest that PS-IM-MS/MS workflow would enable rapid discrimination of closely related bacteria species and strains.

Multi-Point Scanning Confocal Raman Spectroscopy for Accurate Identification of Microorganisms at the Single-Cell Level

Multi-Point Scanning Confocal Raman Spectroscopy for Accurate Identification of Microorganisms at the Single-Cell Level

Monitoring Methicillin-Resistant Staphylococcus Strains in the Moscow Medical and Surgical Center using Molecular-Biological Methods

Relevance. Staphylococci are one of the most common pathogens in the etiological structure of nosocomial infections. Methicillinresistant staphylococci are resistant to the main groups of antibiotics and are one of bacteria that pose the greatest threat to human health according to the World Health Organization. The introduction of modern molecular biological methods in the monitoring of methicillin-resistant staphylococci is necessary for the rapid and accurate identification of microorganisms, monitoring the epidemiological situation and studying the need for anti-epidemic measures. Aims. Аnalysis of the results of monitoring methicillinresistant staphylococcus strains using molecular biological methods in a multidisciplinary hospital in Moscow for one year. Materials and methods. Single-center observational study with a one-year follow-up period (December 2016 to December 2017). The research included a molecular-biological analysis of biological material from 240 patients with signs of infection and washings samples (n=250) from the objects of the hospital environment. The whole genome sequencing was carried out for 24 samples, isolated from patients with different forms of staphylococcal infection and washings from a hospital environment. DNA detection of methicillin-resistant strains was performed using the «AmpliSens®MRSA-screen-titer-FL» reagent kit. Sequencing was performed on an Illumina HiSeq1500 instrument using the IlluminaHiSeq PE RapidClusterKit v2 and IlluminaHiSeqRapid SBS Kit v2. Results. DNA of methicillin-resistant staphylococci were detected in 6.3% of blood samples from patients with signs of infection and in 42.4% of washings from the objects of the hospital environment. The results of PCR of washing samples showed that DNA of methicillin-resistant coagulase-negative staphylococci were detected much more often than MRSA (p <0.001). DNA of methicillin-resistant staphylococci were detected more often in the intensive care and intensive care units compared with the hematology and surgical departments (p <0.001). The examine samples of Staphylococcus aureus belonged to 6 different sequence types (ST-5, ST-7, ST-8, ST-22, ST-30 and ST-5555) and 8 spatypes (t008, t021, t091, t1062, t12437, t1544, t223, t4573). As a result of monitoring, an isolate with a new allelic profile was found. Today it has been assigned the number ST5555. The predominant type of staphylococcal mec cassette was the type IV SCCmec cassette. Conclusion. Due to the widespread distribution of methicillin-resistant strains and the identification of epidemiologically significant genetic lines of staphylococci, it is necessary to conduct regular monitoring, take measures to limit the spread of such strains and introduce modern molecular biological methods for quick and accurate identification.

Microbiome-based environmental monitoring of a dairy processing facility highlights the challenges associated with low microbial-load samples

Efficient and accurate identification of microorganisms throughout the food chain can potentially allow the identification of sources of contamination and the timely implementation of control measures. High throughput DNA sequencing represents a potential means through which microbial monitoring can be enhanced. While Illumina sequencing platforms are most typically used, newer portable platforms, such as the Oxford Nanopore Technologies (ONT) MinION, offer the potential for rapid analysis of food chain microbiomes. Initial assessment of the ability of rapid MinION-based sequencing to identify microbes within a simple mock metagenomic mixture is performed. Subsequently, we compare the performance of both ONT and Illumina sequencing for environmental monitoring of an active food processing facility. Overall, ONT MinION sequencing provides accurate classification to species level, comparable to Illumina-derived outputs. However, while the MinION-based approach provides a means of easy library preparations and portability, the high concentrations of DNA needed is a limiting factor.

Bioinformatics in the identification of microorganisms

Rapid and accurate identification of microorganisms can be of great value for clinical management. For many fastidious and slow-growing microorganisms, the conventional method used for detection is time-consuming, costly and labour-intensive. Hence, the development of new and improved microbial identification methods are necessary to overcome this bottleneck. Current trend has shifted towards the use of new molecular technologies in genomics and proteomics for bacterial identification and characterization. This mini review will focus on summarizing different types of genotypic and proteomics identification methods, as well as bioinformatics tools used for rapid identification and characterization of microorganisms from various specimens.

High-throughput proteotyping of bacterial isolates by double barrel chromatography-tandem mass spectrometry based on microplate paramagnetic beads and phylopeptidomics

Tandem mass spectrometry-based proteotyping of microorganisms presents several advantages over whole-cell MALDI-TOF mass spectrometry: because a larger number of signals are recorded with better accuracy and precision, the approach allows for the identification of microorganisms at more resolved taxonomic levels, and can easily manage complex samples. Additionally, the use of SP3 paramagnetic beads for cell lysis and protein cleanup simplifies sample preparation for proteotyping. Based on these features, we have developed and tested a 96-well plate platform for high-throughput proteotyping of a large variety of bacteria. We evaluated the performance of the platform in terms of bacterial load and found no cross-contamination between wells. Likewise, phylopeptidomics analysis revealed no alteration in the relative quantifications of microorganisms. Finally, we applied this new format for rapid proteotyping of a large set of dental isolates using double-barrel chromatography coupled to tandem mass spectrometry, which maximizes the number of spectra per unit of time. The procedure allowed us to establish whether these isolates were pure strains or mixtures of strains and to identify the microorganisms at the most resolved taxonomic level. SignificanceThe rapid and accurate identification of microorganisms is a clinical priority in medical diagnostics; however, specimens containing mixtures of microorganisms are difficult to analyze and the procedure is time-consuming. Tandem mass spectrometry proteotyping allows the fast identification of complex mixtures of microorganisms, known or unknown, and can also establish the biomass ratio of each component. We describe here a new workflow for preparing microbial samples in a 96-well-plate format for tandem mass spectrometry proteotyping and document its advantages and limitations. We demonstrate that this new format coupled to a highly efficient double-barrel LC-MS/MS system allows proteotyping of 96 isolates in 55 h.

Robust Accurate Identification and Biomass Estimates of Microorganisms via Tandem Mass Spectrometry.

Rapid and accurate identification of microorganisms and estimation of their biomasses are of extreme importance to public health. Mass spectrometry has become an important technique for these purposes. Previously we published a workflow named Microorganism Classification and Identification (MiCId v.12.26.2017) that was shown to perform no worse than other workflows. This manuscript presents MiCId v.12.13.2018 that, in comparison with the earlier version v.12.26.2017, allows for biomass estimates, provides more accurate microorganism identifications (better controls the number of false positives), and is robust against database size increase. This significant advance is made possible by several new ingredients introduced: first, we apply a modified expectation-maximization method to compute for each taxon considered a prior probability, which can be used for biomass estimate; second, we introduce a new concept called ownership, through which the participation ratio is computed and use it as the number of taxa to be kept within a cluster of closely related taxa; third, based on confidently identified peptides, we calculate for each taxon its degree of independence from the rest of taxa considered to determine whether or not to split this taxon off the cluster. Using 270 data files, each containing a large number of MS/MS spectra, we show that, in comparison with v.12.26.2017, version v.12.13.2018 yields superior retrieval results. We also show that MiCId v.12.13.2018 can estimate species biomass reasonably well. The new MiCId v.12.13.2018, designed to run in Linux environment, is freely available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

Utilisation of Ambient Laser Desorption Ionisation Mass Spectrometry (ALDI-MS) Improves Lipid-Based Microbial Species Level Identification

The accurate and timely identification of the causative organism of infection is important in ensuring the optimum treatment regimen is prescribed for a patient. Rapid evaporative ionisation mass spectrometry (REIMS), using electrical diathermy for the thermal disruption of a sample, has been shown to provide fast and accurate identification of microorganisms directly from culture. However, this method requires contact to be made between the REIMS probe and microbial biomass; resulting in the necessity to clean or replace the probes between analyses. Here, optimisation and utilisation of ambient laser desorption ionisation (ALDI) for improved speciation accuracy and analytical throughput is shown. Optimisation was completed on 15 isolates of Escherichia coli, showing 5 W in pulsatile mode produced the highest signal-to-noise ratio. These parameters were used in the analysis of 150 clinical isolates from ten microbial species, resulting in a speciation accuracy of 99.4% - higher than all previously reported REIMS modalities. Comparison of spectral data showed high levels of similarity between previously published electrical diathermy REIMS data. ALDI does not require contact to be made with the sample during analysis, meaning analytical throughput can be substantially improved, and further, increases the range of sample types which can be analysed in potential direct-from-sample pathogen detection.

Evaluation of QuickFISH and maldi Sepsityper for identification of bacteria in bloodstream infection

Background: Early detection of bacteria and their antibiotic susceptibility patterns are critical to guide therapeutic decision-making for optimal care of septic patients. The current gold standard, blood culturing followed by subculture on agar plates for subsequent identification, is too slow leading to excessive use of broad-spectrum antibiotic with harmful consequences for the patient and, in the long run, the public health. The aim of the present study was to assess the performance of two commercial assays, QuickFISH® (OpGen) and Maldi Sepsityper™ (Bruker Daltonics) for early and accurate identification of microorganisms directly from positive blood cultures.Materials and methods: During two substudies of positive blood cultures, the two commercial assays were assessed against the routine method used at the clinical microbiology laboratory, Unilabs AB, at Skaraborg Hospital, Sweden.Results: The Maldi Sepsityper™ assay enabled earlier microorganism identification. Using the cut-off for definite species identification according to the reference method (>2.0), sufficiently accurate species identification was achieved, but only among Gram-negative bacteria. The QuickFISH® assay was time-saving and showed high concordance with the reference method, 94.8% (95% CI 88.4–98.3), when the causative agent was covered by the QuickFISH® assay.Conclusions: The use of the commercial assays may shorten the time to identification of causative agents in bloodstream infections and can be a good complement to the current clinical routine diagnostics. Nevertheless, the performance of the commercial assays is considerably affected by the characteristics of the causative agents.

Direct identification of clinical pathogens from liquid culture media by MALDI-TOF MS analysis

ObjectivesWe propose using MALDI-TOF MS as a tool for identifying microorganisms directly from liquid cultures after enrichment of the clinical sample in the media, to obtain a rapid microbiological diagnosis and an adequate administration of the antibiotic therapy in a clinical setting. MethodsTo evaluate this approach, a series of quality control isolates were grown in thioglycollate (TG) broth and brain heart infusion (BHI) broth and extracted under four different protocols before finally being identified by MALDI-TOF MS. After establishing the best extraction protocol, we validated the method in a total of 300 liquid cultures (150 in TG broth and 150 in BHI broth) of different types of clinical samples obtained from two tertiary Spanish hospitals. ResultsThe initial evaluation showed that the extraction protocol including a 5 minute sonication step yielded 100% valid identifications, with an average score value of 2.305. In the clinical validation of the procedure, 98% of the microorganisms identified from the TG broth were correctly identified relative to 97% of those identified from the BHI broth. In 24% of the samples analysed, growth by direct sowing was only successful in the liquid medium, and no growth was observed in the direct solid agar cultures. ConclusionsUse of MALDI-TOF MS plus the sonication-based extraction method enabled direct and accurate identification of microorganisms in liquid culture media in 15 minutes, in contrast to the 24 hours of subculture required for conventional identification, allowing the administration of a targeted antimicrobial therapy.

Performance of MALDI-TOF MS platforms for fungal identification.

Matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-TOF MS) is increasingly used by clinical microbiology laboratories to cope with the need for rapid, cost-effective and accurate identification of microorganisms. Several research teams have recently succeed in identifying moulds using MALDI-TOF MS, which was first adapted to bacteria, then to yeast identification. Since 2004, different commercial firms have released several ready-to-use MALDI-TOF MS platforms. This review describes the similarities and differences between the commercially available systems. In two parts, we first describe and compare the preprocessing and identification steps between the platforms and then compare the identification efficacy of yeast, moulds and dermatophytes species.

Performance of the FilmArray Blood culture identification panel in positive blood culture bottles and cerebrospinal fluid for the diagnosis of sepsis and meningitis.

Sepsis and meningitis are life threatening medical conditions. Culture-based methods are used for identification of the causative pathogens, but they can be improved by implementation of additional test systems. We evaluated the performance of the novel FilmArray blood culture identification (BCID; Biofire Diagnostics) panel for rapid and accurate identification of microorganisms in positive blood cultures and additionally, in this cerebrospinal fluid (CSF) pilot study for direct testing of CSF. A total of 107 positive blood cultures and 20 CSF samples (positive and negative) were investigated and compared to the routine procedures. Of the 107 positive blood cultures, 90.7% (97/107) showed monomicrobial growth and 9.3% (10/107) polymicrobial growth. The FilmArray BCID panel covered 89.3% (25/28) of the bacteria and 100% (2/2) of the yeasts found in this study and accurately identified all of them.From the 20 retrospective analyzed CSF, in 9 positive specimens 6 different bacterial species were identified. Discrepant identification results were found in 25% (5/20) and a low sensitivity of 50% (95% CI of 15.7% to 84.3%) was detected.Our study confirms the FilmArray BCID panel as a rapid, easy to handle PCR system with a good performance in positive blood cultures without Gram-staining result. However, our results additionally suggest that the system is not useful for direct CSF testing due to poor sensitivity.