Rapid Microbial Identification Research Articles

Troubleshooting high laboratory pasteurization counts in organic raw milk requires characterization of dominant thermoduric bacteria, which includes nonsporeformers as well as sporeformers

Laboratory Pasteurization Count (LPC) enumerates thermoduric bacteria and is one parameter used to assess raw milk quality. While there is currently no regulatory limit for LPC, LPC data are used by some dairy processors and cooperatives to designate raw milk quality premiums paid to farmers and may also be used for troubleshooting bacterial contamination issues. Despite occasionally being used as a proxy for levels of bacterial spores in raw milk, there is limited knowledge of the types of organisms that are enumerated by LPC in contemporary raw milk supplies. While historical studies have reported that thermoduric bacteria quantified by LPC may predominantly represent Gram-positive cocci, updated knowledge on microbial populations enumerated by LPC in contemporary organic raw milk supplies is needed. To address this gap, organic raw milk samples from across the United States (n = 94) were assessed using LPC, and bacterial isolates were characterized. LPC ranged from below detection (<0.70 log cfu/mL) to 4.07 log cfu/mL, with a geometric mean of 1.48 log cfu/mL. Among 380 isolates characterized by 16S rDNA sequencing, 52.6%, 44.5%, and 2.4% were identified as Gram-positive sporeformers, Gram-positive non-sporeformers, and Gram-negatives, respectively, and 0.5% that could not be categorized into those groups because they could only be assigned a higher level of taxonomy. Isolates identified as Gram-positive sporeformers were predominantly Bacillus (168/200) and Gram-positive non-sporeformers were predominately Brachybacterium (56/169) and Kocuria (47/169). To elucidate if the LPC level can be an indicator of the type of thermoduric (e.g., sporeforming bacteria) present in raw milk, we evaluated the proportion of sporeformers in raw milk samples with LPC of ≤100 cfu/mL, 100 to 200 cfu/mL, and ≥200 cfu/mL (51%, 67%, and 35%), showing a trend for sporeformers to represent a smaller proportion of the total thermoduric population when LPC increases, although overall linear regression showed no significant association between the proportion of sporeformers and the LPC concentration. Hence, LPC level alone provides no insight into the makeup of the thermoduric population in raw milk and further characterization is needed to elucidate the bacterial drivers of elevated LPC in raw milk. We therefore further characterized the isolates from this study using matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS), a rapid microbial identification tool that is more readily available to dairy producers than 16S rDNA PCR and sequencing. While our data indicated agreement between 16S and MALDI-TOF MS for 66.6% of isolates at the genus level, 24.2% and 9.2% could not be reliably identified or were mischaracterized using MALDI-TOF, respectively. This suggests that further optimization of this method is needed to allow for accurate characterization of thermoduric organisms commonly found in raw milk. Ultimately, our study provides a contemporary perspective on thermoduric bacteria selected by the LPC method and establishes that the LPC alone is not sufficient for identifying the bacterial drivers of LPC levels. Further development of rapid characterization methods that are accessible to producers, cooperatives, and processors will support milk quality troubleshooting efforts and ultimately improve outcomes for dairy industry community members.

Present and future perspectives on mass spectrometry for clinical microbiology

In the last decade, MALDI-TOF Mass Spectrometry (MALDI-TOF MS) has been introduced and broadly accepted by clinical laboratory laboratories throughout the world as a powerful and efficient tool for rapid microbial identification. During the MALDI-TOF MS process, microbes are identified using either intact cells or cell extracts. The process is rapid, sensitive, and economical in terms of both labor and costs involved. Whilst MALDI-TOF MS is currently the gold-standard, it suffers from several shortcomings such as lack of direct information on antibiotic resistance, poor depth of analysis and insufficient discriminatory power for the distinction of closely related bacterial species or for reliably sub-differentiating isolates to the level of clones or strains. Thus, new approaches targeting proteins and allowing a better characterization of bacterial strains are strongly needed, if possible, on a very short time scale after sample collection in the hospital. Bottom-up proteomics (BUP) is a nice alternative to MALDI-TOF MS, offering the possibility for in-depth proteome analysis. Top-down proteomics (TDP) provides the highest molecular precision in proteomics, allowing the characterization of proteins at the proteoform level. A number of studies have already demonstrated the potential of these techniques in clinical microbiology. In this review, we will discuss the current state-of-the-art of MALDI-TOF MS for the rapid microbial identification and detection of resistance to antibiotics and describe emerging approaches, including bottom-up and top-down proteomics as well as ambient MS technologies.

New Antibiotic Binding Resin Bottles Collected from Children Enhances Rapid Microbial Identification.

Bloodstream infections (BSI) represent a common cause of sepsis and mortality in children. Blood culture (BC) is the gold standard for diagnosis of BSI. The low sensitivity of BC in the pediatric population is usually due to the small volume of blood used for inoculation and to the antibiotics used before sampling. Here, we explore the ways to effectively reduce antibiotic activity to maximize the chances of pathogen recovery, and to enhance the growth of microorganisms in lower blood volume and bacterial counts. The recovery of common pathogens causing blood stream infections was analyzed after exposure to cefo-perazone/sulbactam, vancomycin, and caspofung by using resin-containing or not BacT/Alert PF Plus and BD FX400 peds plus pediatric bottles. The microbial growth in the resin-containing bottles was assessed using 0.5 colony-forming units (CFU) bacterial inoculum to mimic the bacteremia/fungemia condition. The usefulness of a diagnosis to confirm or exclude BSI was evaluated by lower than recommended blood culture sampling (102 CFU/mL, 0.3 mL). Staphylococcus aureus (S. aureus), and Candida glabrata (C. glabrata) were recovered from 100% of two types of resin-containing bottles in the presence of a sufficient antibiotic dose, while Escherichia coli (E. coli) was not restored to 100% in BD FX400 peds plus pediatric bottles. The shorter TTD for S. aureus, C. glabrata, and E. coli were observed in antibiotic-containing BacT/Alert PF Plus bottles. Both the PF Plus and BD resin test bottles showed consistently good TTD performances to Gram-negative, Gram-positive, and yeast species in low inoculum levels, with the exception of S. aureus. The lower volume of blood inoculated into culture bottles hardly affected the growth of most bacteria, but optimized PF Plus resin-bottles accelerated the detection of infectious agents, especially S. aureus, Streptococcus pneumoniae, and C. glabrata. It is possible to enhance recovery from antibiotic-containing pediatric bottles and shorten TTD for the identification of pathogens by using the BacT/Alert blood culture system combination with new resin-containing media.

The clinical value of metagenomic next-generation sequencing for rapid microbial identification of chronic granulation wound infections.

The clinical value of metagenomic next-generation sequencing for rapid microbial identification of chronic granulation wound infections.

Data-Driven Two-Stage Framework for Identification and Characterization of Different Antibiotic-Resistant Escherichia coli Isolates Based on Mass Spectrometry Data.

In clinical microbiology, matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) is frequently employed for rapid microbial identification. However, rapid identification of antimicrobial resistance (AMR) in Escherichia coli based on a large amount of MALDI-TOF MS data has not yet been reported. This may be because building a prediction model to cover all E. coli isolates would be challenging given the high diversity of the E. coli population. This study aimed to develop a MALDI-TOF MS-based, data-driven, two-stage framework for characterizing different AMRs in E. coli. Specifically, amoxicillin (AMC), ceftazidime (CAZ), ciprofloxacin (CIP), ceftriaxone (CRO), and cefuroxime (CXM) were used. In the first stage, we split the data into two groups based on informative peaks according to the importance of the random forest. In the second stage, prediction models were constructed using four different machine learning algorithms-logistic regression, support vector machine, random forest, and extreme gradient boosting (XGBoost). The findings demonstrate that XGBoost outperformed the other four machine learning models. The values of the area under the receiver operating characteristic curve were 0.62, 0.72, 0.87, 0.72, and 0.72 for AMC, CAZ, CIP, CRO, and CXM, respectively. This implies that a data-driven, two-stage framework could improve accuracy by approximately 2.8%. As a result, we developed AMR prediction models for E. coli using a data-driven two-stage framework, which is promising for assisting physicians in making decisions. Further, the analysis of informative peaks in future studies could potentially reveal new insights. IMPORTANCE Based on a large amount of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) clinical data, comprising 37,918 Escherichia coli isolates, a data-driven two-stage framework was established to evaluate the antimicrobial resistance of E. coli. Five antibiotics, including amoxicillin (AMC), ceftazidime (CAZ), ciprofloxacin (CIP), ceftriaxone (CRO), and cefuroxime (CXM), were considered for the two-stage model training, and the values of the area under the receiver operating characteristic curve (AUC) were 0.62 for AMC, 0.72 for CAZ, 0.87 for CIP, 0.72 for CRO, and 0.72 for CXM. Further investigations revealed that the informative peak m/z 9714 appeared with some important peaks at m/z 6809, m/z 7650, m/z 10534, and m/z 11783 for CIP and at m/z 6809, m/z 10475, and m/z 8447 for CAZ, CRO, and CXM. This framework has the potential to improve the accuracy by approximately 2.8%, indicating a promising potential for further research.

MALDI‐TOF mass spectrometry rapid pathogen identification and outcomes of patients with bloodstream infection: A systematic review and meta‐analysis

There was inconsistent evidence regarding the use of matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry (MALDI‐TOF MS) for microorganism identification with/without antibiotic stewardship team (AST) and the clinical outcome of patients with bloodstream infections (BSI). In a systematic review and meta‐analysis, we evaluated the effectiveness of rapid microbial identification by MALDI‐TOF MS with and without AST on clinical outcomes. We searched PubMed and EMBASE databases from inception to 1 February 2022 to identify pre–post and parallel comparative studies that evaluated the use of MALDI‐TOF MS for microorganism identification. Pooled effect estimates were derived using the random‐effects model. Twenty‐one studies with 14,515 patients were meta‐analysed. Compared with conventional phenotypic methods, MALDI‐TOF MS was associated with a 23% reduction in mortality (RR = 0.77; 95% CI: 0.66; 0.90; I 2 = 35.9%; 13 studies); 5.07‐h reduction in time to effective antibiotic therapy (95% CI: −5.83; −4.31; I 2 = 95.7%); 22.86‐h reduction in time to identify microorganisms (95% CI: −23.99; −21.74; I 2 = 91.6%); 0.73‐day reduction in hospital stay (95% CI: −1.30; −0.16; I 2 = 53.1%); and US$4140 saving in direct hospitalization cost (95% CI: $‐8166.75; $‐113.60; I 2 = 66.1%). No significant heterogeneity sources were found, and no statistical evidence for publication bias was found. Rapid pathogen identification by MALDI‐TOF MS with or without AST was associated with reduced mortality and improved outcomes of BSI, and may be cost‐effective among patients with BSI.

Bioactivity against Staphylococcus aureus of New Nanoparticles Derived from Iron Oxide and Beta vulgaris Extracts and Synthesis Characterization

In this study an opportunity was obtained that combines the VITEK system and the detection system of clinical microbiology laboratories to reach the rapid microbial identification and sensitivity test for Staph aureus bacteria, where the results of the susceptibility test were compared to 3925 combinations of antibiotics. The total rate was for the normal antimicrobials as well as the category approval for direct sensitivity test. 92% with less than 3% significant errors and the average time required to identify the identity with a sensitivity test is 7.5 hours (3.0 SD hours), compared to an average of 32.3 hours 9-14 hours for the normal method. The study focuses on the effectiveness of anti-bacterial iron nanoparticles from Beta vulgaris extract in various concentrations (1 mg/ml. 2 mg/ml. 3 mg/ml.4 mg/ml. against Stphylococcus aureus. Where in an inhibition zone was obtained for the highest concentration of iron nanoparticles for Beta vulgaris when compared to other samples.

Rapid species identification of pathogenic bacteria from a minute quantity exploiting three-dimensional quantitative phase imaging and artificial neural network

The healthcare industry is in dire need of rapid microbial identification techniques for treating microbial infections. Microbial infections are a major healthcare issue worldwide, as these widespread diseases often develop into deadly symptoms. While studies have shown that an early appropriate antibiotic treatment significantly reduces the mortality of an infection, this effective treatment is difficult to practice. The main obstacle to early appropriate antibiotic treatments is the long turnaround time of the routine microbial identification, which includes time-consuming sample growth. Here, we propose a microscopy-based framework that identifies the pathogen from single to few cells. Our framework obtains and exploits the morphology of the limited sample by incorporating three-dimensional quantitative phase imaging and an artificial neural network. We demonstrate the identification of 19 bacterial species that cause bloodstream infections, achieving an accuracy of 82.5% from an individual bacterial cell or cluster. This performance, comparable to that of the gold standard mass spectroscopy under a sufficient amount of sample, underpins the effectiveness of our framework in clinical applications. Furthermore, our accuracy increases with multiple measurements, reaching 99.9% with seven different measurements of cells or clusters. We believe that our framework can serve as a beneficial advisory tool for clinicians during the initial treatment of infections.

MALDI-Based Mass Spectrometry in Clinical Testing: Focus on Bacterial Identification

The term “proteome” refers to the total of all proteins expressed in an organism. The term “proteomics” refers to the field of research that includes not only information on the expression levels of individual proteins, but also their higher-order structures, intermolecular interactions, and post-translational modifications. The core technology, matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS), is available for protein analysis thanks to the work of Koichi Tanaka and John Fenn, who were awarded the Nobel Prize in Chemistry in 2002. The most successful proteome analysis in clinical practice is rapid microbial identification. This method determines the bacterial species by comparing the proteome profile of the bacteria obtained by matrix-assisted laser desorption ionization-time of flight MS (MALDI-TOF MS) with a database. MS is superior in simplicity, speed, and accuracy to classic speciation by staining and phenotyping. In clinical microbiology, MS has had a large impact on the diagnosis and treatment of infectious disease. Early diagnosis and treatment of infectious disease are important, and rapid identification by MALDI-TOF MS has made a major contribution to this field.

Cost-effectiveness of rapid laboratory-based mass-spectrometry diagnosis of bloodstream infection: evidence from the RAPIDO randomised controlled trial

Objectives and interventionBloodstream infection, the presence of viable micro-organisms in the blood, is a prevalent clinical event associated with substantial mortality. Patient outcomes may be improved when the causative micro-organism...

DiagnoTop: A Computational Pipeline for Discriminating Bacterial Pathogens without Database Search.

Pathogen identification is crucial to confirm bacterial infections and guide antimicrobial therapy. Although MALDI-TOF mass spectrometry (MS) serves as foundation for tools that enable rapid microbial identification, some bacteria remain challenging to identify. We recently showed that top-down proteomics (TDP) could be used to discriminate closely related enterobacterial pathogens (Escherichia coli, Shigella, and Salmonella) that are indistinguishable with tools rooted in the MALDI-TOF MS approach. Current TDP diagnostic relies on the identification of specific proteoforms for each species through a database search. However, microbial proteomes are often poorly annotated, which complicates the large-scale identification of proteoforms and leads to many unidentified high-quality mass spectra. Here, we describe a new computational pipeline called DiagnoTop that lists discriminative spectral clusters found in TDP data sets that can be used for microbial diagnostics without database search. Applied to our enterobacterial TDP data sets, DiagnoTop could easily shortlist high-quality discriminative spectral clusters, leading to increased diagnostic power. This pipeline opens new perspectives in clinical microbiology and biomarker discovery using TDP.

Rapid microbial identification and colistin resistance detection via MALDI-TOF MS using a novel on-target extraction of membrane lipids

Rapid infection diagnosis is critical to improving patient treatment and outcome. Recent studies have shown microbial lipids to be sensitive and selective biomarkers for identifying bacterial and fungal species and antimicrobial resistance. Practical procedures for microbial lipid biomarker analysis will therefore improve patient outcomes and antimicrobial stewardship. However, current lipid extraction methods require significant hands-on time and are thus not suited for direct adoption as a clinical assay for microbial identification. Here, we have developed a method for lipid extraction directly on the surface of stainless-steel matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) plates, termed fast lipid analysis technique or FLAT, which facilitates the identification of bacterial and fungal species using a sub-60-minute workflow. Additionally, our method detects lipid A modifications in Gram-negative bacteria that are associated with antimicrobial resistance, including to colistin.

Impact of rapid microbial identification on clinical outcomes in bloodstream infection: the RAPIDO randomized trial

ObjectivesBloodstream infection has a high mortality rate. It is not clear whether laboratory-based rapid identification of the organisms involved would improve outcome. MethodsThe RAPIDO trial was an open parallel-group multicentre randomized controlled trial. We tested all positive blood cultures from hospitalized adults by conventional methods of microbial identification and those from patients randomized (1:1) to rapid diagnosis in addition to matrix-assisted desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) performed directly on positive blood cultures. The only primary outcome was 28-day mortality. Clinical advice on patient management was provided to members of both groups by infection specialists. ResultsFirst positive blood culture samples from 8628 patients were randomized, 4312 into rapid diagnosis and 4136 into conventional diagnosis. After prespecified postrandomization exclusions, 2740 in the rapid diagnosis arm and 2810 in the conventional arm were included in the mortality analysis. There was no significant difference in 28-day survival (81.5% 2233/2740 rapid vs. 82.3% 2313/2810 conventional; hazard ratio 1.05, 95% confidence interval 0.93–1.19, p 0.42). Microbial identification was quicker in the rapid diagnosis group (median (interquartile range) 38.5 (26.7–50.3) hours after blood sampling vs. 50.3 (47.1–72.9) hours after blood sampling, p < 0.01), but times to effective antimicrobial therapy were no shorter (respectively median (interquartile range) 24 (2–78) hours vs. 13 (2–69) hours). There were no significant differences in 7-day mortality or total antibiotic consumption; times to resolution of fever, discharge from hospital or de-escalation of broad-spectrum therapy or 28-day Clostridioides difficile incidence. ConclusionsRapid identification of bloodstream pathogens by MALDI-TOF MS in this trial did not reduce patient mortality despite delivering laboratory data to clinicians sooner.

Power of Scanning Electron Microscopy and Energy Dispersive X-Ray Analysis in Rapid Microbial Detection and Identification at the Single Cell Level

The demand for rapid, consistent and easy-to-use techniques for detecting and identifying pathogens in various areas, such as clinical diagnosis, the pharmaceutical industry, environmental science and food inspection, is very important. In this study, the reference strains of six food-borne pathogens, namely, Escherichia coli 0157: H7 ATCC 43890, Cronobacter sakazakii ATCC 29004, Salmonella Typhimurium ATCC 43971, Staphylococcus aureus KCCM 40050, Bacillus subtilis ATCC 14579, and Listeria monocytogenes ATCC 19115, were chosen for scanning electron microscopy (SEM) and energy dispersive X-ray (EDX) analysis. In our study, the time-consuming sample preparation step for the microbial analysis under SEM was avoided, which makes this detection process notably rapid. Samples were loaded onto a 0.01-µm-thick silver (Ag) foil surface to avoid any charging effect. Two different excitation voltages, 10 kV and 5 kV, were used to determine the elemental information. Information obtained from SEM-EDX can distinguish individual single cells and detect viable and nonviable microorganisms. This work demonstrates that the combination of morphological and elemental information obtained from SEM-EDX analysis with the help of principal component analysis (PCA) enables the rapid identification of single microbial cells without following time-consuming microbiological cultivation methods.

Rapid microbial identification and phenotypic antimicrobial susceptibility testing directly from positive blood cultures: a new platform compared to routine laboratory methods

The Accelerate Pheno™ System (APS), a new platform that combines rapid identification (ID) of bacteria and yeasts and phenotypic antimicrobial susceptibility testing (AST) in a single assay, has been evaluated directly from positive blood cultures in comparison to routine laboratory methods. The APS ID results showed an overall sensitivity and specificity of 92.6% and 99.6%, respectively. With regard to AST results, 31 discrepancies (8 single errors and 23 combined errors) were observed, including 13 major errors (3.3%) and 18 minor errors (4.6%) mainly involving Pseudomonas aeruginosa. No very major error was observed. The APS ID results were obtained in 1.5 h and the AST results were available in 7 h, on average 34.1 h before routine laboratory methods. This reduction in AST time-to-result represents one of the main advantages of this technology, reducing the time to provide to the physician the microbiological report.

Synthesis Characterization of new Nanoparticles Derived From Iron Oxide and Beta vulgaris extracts and its Bioactivity against Pantoea spp

This study discovers the opportunity of combining the clinical microbiology laboratories detection system with the VITEK 2 system to achieve rapid microbial identification and susceptibility testing of Pantoea spp. Susceptibility test results were compared for 3, 925 organism antibiotic combinations. The overall rate of categorical agreement of direct and conventional antimicrobial susceptibility testing was 92% with less than 3% very major and major errors combined. The mean turnaround time for identification and susceptibility testing was 7.5 hours (SD 3.0 hours) compared to a mean of 32.3 hours (SD 14.7 hours) for the conventional method. The present study concentrate on the antibacterial activity of Iron nanoparticle synthesized using Beta vulgaris extracts using a different concentrations (1 mg/ml, 2 mg/ml, 3 mg/ml, 4 mg/ml, against P ntoea spp.) and it was found that the highest concentration of Beta vulgaris iron nanoparticle gave the highest inhibition zone compare with the other samples.

2125. Staphylococcus Species Identification by Fourier Transform Infrared (FTIR) Spectroscopic Techniques: A Cross-Lab Study

Background Staphylococcus aureus is well known to be associated with atopic dermatitis. Recent studies also report S. aureus presence in lesional skin of squamous cell carcinoma (SCC) and its precursor lesion, actinic keratosis (AK). Therefore, it is of potential clinical interest to monitor skin S. aureus colonization on AK lesions. Fourier transform infrared (FTIR) spectroscopy is a cost-effective, nondestructive, and reagent-free technique for rapid microbial identification. It is based on the use of spectral databases developed with well-characterized strains in conjunction with the application of multivariate statistical analysis to elaborate classification models. In the present cross-lab study, spectral databases containing FTIR spectra of over 1000 staphylococcal isolates obtained from reference and clinical microbiology laboratories across Canada were employed in the FTIR spectroscopic identification of Staphylococcus spp. isolated from AK, SCC and perilesional skin of patients at the Princess Alexandra Hospital Dermatology Clinic in Brisbane, Australia.MethodsFTIR spectra of 51 staphylococcal isolates from AK, SCC and perilesional skin were acquired by both attenuated total reflectance (ATR)-FTIR and transflection-FTIR spectroscopy. All isolates had been previously characterized by 16S rRNA sequencing. ATR- and transflection-FTIR spectra were recorded in triplicate from isolated colonies taken from the same agar plate. Identification of the bacteria was based on the similarities of their spectra with those in ATR- and transflection-FTIR spectral databases originating from the Canadian lab.ResultsAmong the 51 staphylococcal isolates included in this study, identification of S. aureus (n = 24) with 100% specificity and 100% sensitivity was achieved by both ATR- and transflection-FTIR spectroscopy. Overall, FTIR-based species identification was in 90.2% concordance with 16S rRNA sequencing.ConclusionThis cross-lab study demonstrates the applicability of Canadian isolate-based ATR- and transflection-FTIR spectral databases for the identification of clinical staphylococcal isolates obtained in Australia. The results support the potential utility of FTIR spectroscopic techniques to monitor skin S. aureus colonization on AK lesions.Disclosures All authors: No reported disclosures.

243. Transflection Fourier Transform Infrared Spectroscopy as a Real-Time Strain Typing Technique: A Vancomycin-Resistant Enterococcus faecium (VRE) Typing Prospective Study

BackgroundRapid bacterial strain typing for nosocomial outbreak surveillance is critical for timely outbreak detection and implementation of appropriate infection control protocols in hospitals. Pulsed-field gel electrophoresis (PFGE) remains the gold standard for strain typing, but it has the disadvantages of being time-consuming and costly. Transflection Fourier transform infrared (FTIR) spectroscopy is a nondestructive and reagent-free technique for rapid microbial identification and subspecies-level discrimination. The potential of employing transflection FTIR spectroscopy as a rapid, real-time typing technique was evaluated in the present study.MethodsTransflection FTIR spectra were acquired from vancomycin-resistant Enterococcus faecium (VRE) isolates obtained from rectal swabs (n = 36) of patients in 6 units at a Montreal hospital over a 3-month period and from environmental screening samples (n = 2). Upon confirmation as VRE using a transflection FTIR spectral database previously developed in our laboratory, isolates were further typed by unsupervised hierarchical cluster analysis and principal component analysis of the FTIR spectral data with the use of a feature selection algorithm.ResultsAnalysis of the FTIR data identified independent cases of VRE outbreak in 2 of 6 units; these outbreaks were confirmed retrospectively by PFGE. Based on the PFGE typing results for all 38 isolates included in this study, FTIR spectral analyses successfully identified 95% (n = 18) of isolates related to the outbreaks and 95% (n = 18) of non-outbreak-related isolates, resulting in a false-positive (n = 1), and a false-negative (n = 1), rate of 5%. Additionally, the two environmental isolates were identified as part of the outbreak from one of the outbreak-positive units.ConclusionThe results in this study indicate that transflection FTIR spectroscopy-based typing can be considered as an alternative typing technique to PFGE, providing real-time results to track the spread of antibiotic-resistant pathogens within hospitals. Furthermore, when combined with the use of a transflection FTIR spectral database, both identification and typing of an isolate can be achieved from a single spectral measurement, thereby reducing the time and cost required for outbreak investigation.Disclosures All authors: No reported disclosures.

The implementation of rapid microbial identification via MALDI-ToF reduces mortality in gram-negative but not gram-positive bacteremia.

Our goals were to study the effect of rapid microbial identification (RMI) of positive blood culture on patient's outcome and to identify specific microbiological characteristics related to clinical benefit of RMI. This was a retrospective-cohort study of hospitalized, adult patients with bacteremia. The outcome of patients with bacteremia episodes was compared before vs. after the initiation of RMI. RMI was done by matrix-assisted laser desorption/ionization time-of-flight testing of microcolonies. The study included 1460 and 2710 cases in the pre- and post-intervention periods, respectively. There were similar rates of gram-negative, gram-positive, anaerobes, and polymicrobial infections, but higher rate of contaminants in the intervention period (39.9 vs. 43.7%, p = 0.019). The median time-to-identification decreased from 47.5 to 21.3h (p < 0.001). Post-intervention, the median LOS declined from 10.83 to 9.79days (p = 0.016), the rate of ICU transfer declined from 13.8 to 11.6% (p = 0.054), and the mortality rate declined from 20.9 to 18.3% (p = 0.047). The improvement in outcome variables remained statistically significant in multivariate analysis when performed for all episodes and non-contaminants but not for contaminants. The mortality declined in gram-negative bacteremia (20% vs. 15.5%, p = 0.005 in multivariate analysis) but not in gram-positive bacteremia (18.1% vs. 18.5%). RMI reduces mortality from gram-negative but not gram-positive bacteremia.

Ask a Pathologist: Again. Faster. The impact of MALDI-TOF technology on rapid microbial identification and changes in hospital practice

Ask a Pathologist: Again. Faster. The impact of MALDI-TOF technology on rapid microbial identification and changes in hospital practice