Rapid clinical bacteriology and its future impact

Clinical considerations on antimicrobial resistance potential of complex microbiological samples

Antimicrobial resistance (AMR) is one of our greatest public health challenges. Targeted use of antibiotics (ABs) can reduce the occurrence and spread of AMR and boost the effectiveness of treatment. This requires knowledge of the AB susceptibility of the pathogens involved in the disease. Therapeutic recommendations based on classical AB susceptibility testing (AST) are based on the analysis of only a fraction of the bacteria present in the disease process. Next and third generation sequencing technologies allow the identification of antimicrobial resistance genes (ARGs) present in a bacterial community. Using this metagenomic approach, we can map the antimicrobial resistance potential (AMRP) of a complex, multi-bacterial microbial sample. To understand the interpretiveness of AMRP, the concordance between phenotypic AMR properties and ARGs was investigated by analyzing data from 574 Escherichia coli strains of five different studies. The overall results show that for 44% of the studied ABs, phenotypically resistant strains are genotypically associated with a 90% probability of resistance, while for 92% of the ABs, the phenotypically susceptible strains are genotypically susceptible with a 90% probability. ARG detection showed a phenotypic prediction with at least 90% confidence in 67% of ABs. The probability of detecting a phenotypically susceptible strain as resistant based on genotype is below 5% for 92% of ABs. While the probability of detecting a phenotypically resistant strain as susceptible based on genotype is below 5% for 44% of ABs. We can assume that these strain-by-strain concordance results are also true for bacteria in complex microbial samples, and conclude that AMRP obtained from metagenomic ARG analysis can help choose efficient ABs. This is illustrated using AMRP by a canine external otitis sample.

Efficient Absorbance-Based Assay for Rapid Antibiotic Susceptibility Testing of Enterobacterales

It is increasingly important to rapidly receive information on the antimicrobial susceptibility of bacteria due to the rise in antimicrobial resistance worldwide. However, traditional phenotypic methods are time-consuming. Thus, the objective of this study was to develop a rapid assay that can detect antibiotic-resistant bacterial isolates phenotypically in less than 2 h. The microplate assay used in this study is based on absorbance measurements of pure bacterial isolates grown in liquid media with and without antibiotics. Absorbance was measured at the beginning of the assay and after 90 min of incubation at 37 °C. Susceptibility was calculated for bacterial isolates that, in the absence of antibiotics, exhibited more than a 50% growth increase by comparing the absorbance value of the culture in the presence of an antibiotic at 90 min with its initial value. Here, we show that it is possible to phenotypically screen the antibiotic susceptibility of Enterobacterales and Acinetobacter spp. isolates to three different antibiotics in 90 min. The test demonstrated an accuracy of 98.8%, sensitivity of 97.6%, and specificity of 99.6%. The false susceptibility rates were 0.2% and false resistance rates were 1.0%. This rapid and simple absorbance test has proven suitable for the screening of antibiotic susceptibility for a large number of strains with high accuracy and sensitivity. This method can be performed without specialized and costly materials and/or equipment, which makes it highly suitable for laboratories with limited resources.

Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology

Full Laboratory Automation is revolutionizing work habits in an increasing number of clinical microbiology facilities worldwide, generating huge streams of digital images for interpretation. Contextually, deep learning architectures are leading to paradigm shifts in the way computers can assist with difficult visual interpretation tasks in several domains. At the crossroads of these epochal trends, we present a system able to tackle a core task in clinical microbiology, namely the global interpretation of diagnostic bacterial culture plates, including presumptive pathogen identification. This is achieved by decomposing the problem into a hierarchy of complex subtasks and addressing them with a multi-network architecture we call DeepColony. Working on a large stream of clinical data and a complete set of 32 pathogens, the proposed system is capable of effectively assist plate interpretation with a surprising degree of accuracy in the widespread and demanding framework of Urinary Tract Infections. Moreover, thanks to the rich species-related generated information, DeepColony can be used for developing trustworthy clinical decision support services in laboratory automation ecosystems from local to global scale.

Harnessing Variabilities in Digital Melt Curves for Accurate Identification of Bacteria

Digital PCR combined with high resolution melt (HRM) is an emerging method for identifying pathogenic bacteria with single cell resolution via species-specific digital melt curves. Currently, the development of such digital PCR-HRM assays entails first identifying PCR primers to target hypervariable gene regions within the target bacteria panel, next performing bulk-based PCR-HRM to examine whether the resulting species-specific melt curves possess sufficient interspecies variability (i.e., variability between bacterial species), and then digitizing the bulk-based PCR-HRM assays with melt curves that have high interspecies variability via microfluidics. In this work, we first report our discovery that the current development workflow can be inadequate because a bulk-based PCR-HRM assay that produces melt curves with high interspecies variability can, in fact, lead to a digital PCR-HRM assay that produces digital melt curves with unwanted intraspecies variability (i.e., variability within the same bacterial species), consequently hampering bacteria identification accuracy. Our subsequent investigation reveals that such intraspecies variability in digital melt curves can arise from PCR primers that target nonidentical gene copies or amplify nonspecifically. We then show that computational in silico HRM opens a window to inspect both interspecies and intraspecies variabilities and thus provides the missing link between bulk-based PCR-HRM and digital PCR-HRM. Through this new development workflow, we report a new digital PCR-HRM assay with improved bacteria identification accuracy. More broadly, this work can serve as the foundation for enhancing the development of future digital PCR-HRM assays toward identifying causative pathogens and combating infectious diseases.

Current and Future Technologies for the Detection of Antibiotic-Resistant Bacteria

Antibiotic resistance is a global public health concern, posing a significant threat to the effectiveness of antibiotics in treating bacterial infections. The accurate and timely detection of antibiotic-resistant bacteria is crucial for implementing appropriate treatment strategies and preventing the spread of resistant strains. This manuscript provides an overview of the current and emerging technologies used for the detection of antibiotic-resistant bacteria. We discuss traditional culture-based methods, molecular techniques, and innovative approaches, highlighting their advantages, limitations, and potential future applications. By understanding the strengths and limitations of these technologies, researchers and healthcare professionals can make informed decisions in combating antibiotic resistance and improving patient outcomes.

Clinical Diagnostics of Bacterial Infections and Their Resistance to Antibiotics-Current State and Whole Genome Sequencing Implementation Perspectives

Antimicrobial resistance (AMR), defined as the ability of microorganisms to withstand antimicrobial treatment, is responsible for millions of deaths annually. The rapid spread of AMR across continents warrants systematic changes in healthcare routines and protocols. One of the fundamental issues with AMR spread is the lack of rapid diagnostic tools for pathogen identification and AMR detection. Resistance profile identification often depends on pathogen culturing and thus may last up to several days. This contributes to the misuse of antibiotics for viral infection, the use of inappropriate antibiotics, the overuse of broad-spectrum antibiotics, or delayed infection treatment. Current DNA sequencing technologies offer the potential to develop rapid infection and AMR diagnostic tools that can provide information in a few hours rather than days. However, these techniques commonly require advanced bioinformatics knowledge and, at present, are not suited for routine lab use. In this review, we give an overview of the AMR burden on healthcare, describe current pathogen identification and AMR screening methods, and provide perspectives on how DNA sequencing may be used for rapid diagnostics. Additionally, we discuss the common steps used for DNA data analysis, currently available pipelines, and tools for analysis. Direct, culture-independent sequencing has the potential to complement current culture-based methods in routine clinical settings. However, there is a need for a minimum set of standards in terms of evaluating the results generated. Additionally, we discuss the use of machine learning algorithms regarding pathogen phenotype detection (resistance/susceptibility to an antibiotic).

The Impact of mNGS Technology in the Etiological Diagnosis of Severe Pneumonia in Children During the Epidemic of COVID-19

Purpose

Metagenomic next-generation sequencing (mNGS) is an emerging technique for pathogen detection. However, most literature on the clinical application of pediatrics generally comprises case reports or small-scale cohort studies.

Patients and Methods

A total of 101 children with community-acquired severe pneumonia admitted to Tianjin Children's Hospital from November 2021 to February 2022 were included. Pathogens in bronchoalveolar lavage fluid (BALF) specimens were detected using mNGS. The performances of mNGS and conventional tests on pulmonary infection diagnosis and pathogen identification were compared.

Results

According to our data, mNGS had a broader spectrum for pathogen detection. The mNGS results of BALF showed that the number of children with severe pneumonia hospitalized for mycoplasma pneumoniae infection was more than that for other bacterial infections during the COVID-19 epidemic. In addition, 43 cases (42.6%) had been identified with mixed infection, including 36 cases (35.6%) of Mycoplasma pneumoniae mixed with other pathogenic bacteria. Analytically, the mNGS exhibited significantly enhanced detection in the BALF as compared with the conventional laboratory pathogenic detection approaches (P < 0.05). The Pearson correlation analysis revealed positive correlation between the time of fever during hospitalization and the number of mycoplasma sequences (P < 0.05).

Conclusion

Compared with traditional methods, mNGS has a higher etiological detection rate and can comprehensively detect various pathogens of severe pneumonia. Therefore, mNGS of bronchoalveolar lavage fluid should be performed in children with severe pneumonia, which is of great significance for guiding treatment.

Novel application of metagenomics for the strain-level detection of bacterial contaminants within non-sterile industrial products - a retrospective, real-time analysis

The home and personal care (HPC) industry generally relies on initial cultivation and subsequent biochemical testing for the identification of microorganisms in contaminated products. This process is slow (several days for growth), labour intensive, and misses organisms which fail to revive from the harsh environment of preserved consumer products. Since manufacturing within the HPC industry is high-throughput, the process of identification of microbial contamination could benefit from the multiple cultivation-independent methodologies that have developed for the detection and analysis of microbes. We describe a novel workflow starting with automated DNA extraction directly from a HPC product, and subsequently applying metagenomic methodologies for species and strain-level identification of bacteria. The workflow was validated by application to a historic microbial contamination of a general-purpose cleaner (GPC). A single strain of Pseudomonas oleovorans was detected metagenomically within the product. The metagenome mirrored that of a contaminant isolated in parallel by a traditional cultivation-based approach. Using a dilution series of the incident sample, we also provide evidence to show that the workflow enables detection of contaminant organisms down to 100 CFU/ml of product. To our knowledge, this is the first validated example of metagenomics analysis providing confirmatory evidence of a traditionally isolated contaminant organism, in a HPC product.

On-Chip Optical Nano-Tweezers for Culture-Less Fast Bacterial Viability Assessment

Because of antibiotics misuse, the dramatic growth of antibioresistance threatens public health. Tests are indeed culture-based, and require therefore one to two days. This long time-to-result implies the use of large-spectrum antibiotherapies as a first step, in absence of pathogen characterization. Here, a breakthrough approach for a culture-less fast assessment of bacterial response to stress is proposed. It is based on non-destructive on-chip optical tweezing. A laser loads an optical nanobeam cavity whose evanescent part of the resonant field acts as a nano-tweezer for bacteria surrounding the cavity. Once optically trapped, the bacterium-nanobeam cavity interaction induces a shift of the resonance driven by the bacterial cell wall optical index. The analysis of the wavelength shift yields an assessment of viability upon stress at the single-cell scale. As a proof of concept, bacteria are stressed by incursion, before optical trapping, at different temperatures (45, 51, and 70 °C). Optical index changes correlate with the degree of thermal stress allowing to sort viable and dead bacteria. With this disruptive diagnosis method, bacterial viability upon stress is probed much faster (typically less than 4 h) than with conventional culture-based enumeration methods (24 h).

Copan Walk Away Specimen Processor (WASP) Automated System for Pathogen Detection in Female Reproductive Tract Specimens

Objective

Automation is increasingly being applied in clinical laboratories; however, preanalytical processing for microbiology tests and screening is still largely performed using manual methods owing to the complex procedures involved. To promote automation of clinical microbiology laboratories, it is important to assess the performance of automated systems for different specimen types separately. Therefore, the aim of this study was to explore the potential clinical application of the Copan Walk Away Specimen Processor (WASP) automated preanalytical microbiology processing system in the detection of pathogens in female reproductive tract specimens and its feasibility in optimizing diagnostic procedures.

Methods

Female reproductive tract specimens collected from pregnant women at their first obstetric check-up were inoculated into culture media using the Copan WASP automated specimen processing system and were also cultured using a conventional manual inoculation method. After 48 h of culture, the growth of colonies was observed, and the types of bacteria, number of colonies, and efficiency in isolating single colonies were compared between the automated and manual groups. The specimens collected from the WASP system using the Copan-ESwab sample collection tubes were further analyzed for the presence of Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), and Ureaplasmaurealyticum (UU) via fluorescence quantitative polymerase chain reaction (qPCR) and an immunochromatographic assay to investigate the feasibility of this method in optimizing detection of these common pathogens of the female reproductive tract.

Results

Compared with the manual culture method, the Copan WASP microbiology automation system detected fewer bacterial types (P<0.001) and bacterial colonies (P<0.001) but had a higher detection rate of single colonies (P<0.001). There was no significant difference in the detection rates of common pathogens encountered in clinical obstetrics and gynecology, including group B Streptococcus (GBS) (P=0.575) and Candida (P=0.917), between the two methods. Specimens collected in the Copan-ESwab tubes could be used for screening of GBS and CT via fluorescence-based qPCR but not with immunochromatography. However, UU and NG were not detected in any sample with either method; thus, further validation is required to determine the feasibility of the Copan system for screening these pathogens.

Conclusion

The Copan WASP microbiology automation system could facilitate the optimization of diagnostic procedures for detecting common pathogens of the female reproductive system, thereby reducing associated costs.

Rapid in vitro differentiation of bacteria by ion mobility spectrometry

Rapid screening of infected people plays a crucial role in interrupting infection chains. However, the current methods for identification of bacteria are very tedious and labor intense. Fast on-site screening for pathogens based on volatile organic compounds (VOCs) by ion mobility spectrometry (IMS) could help to differentiate between healthy and potentially infected subjects. As a first step towards this, the feasibility of differentiating between seven different bacteria including resistant strains was assessed using IMS coupled to multicapillary columns (MCC-IMS). The headspace above bacterial cultures was directly drawn and analyzed by MCC-IMS after 90 min of incubation. A cluster analysis software and statistical methods were applied to select discriminative VOC clusters. As a result, 63 VOC clusters were identified, enabling the differentiation between all investigated bacterial strains using canonical discriminant analysis. These 63 clusters were reduced to 7 discriminative VOC clusters by constructing a hierarchical classification tree. Using this tree, all bacteria including resistant strains could be classified with an AUC of 1.0 by receiver-operating characteristic analysis. In conclusion, MCC-IMS is able to differentiate the tested bacterial species, even the non-resistant and their corresponding resistant strains, based on VOC patterns after 90 min of cultivation. Although this result is very promising, in vivo studies need to be performed to investigate if this technology is able to also classify clinical samples. With a short analysis time of 5 min, MCC-IMS is quite attractive for a rapid screening for possible infections in various locations from hospitals to airports.

Key Points

• Differentiation of bacteria by MCC-IMS is shown after 90-min cultivation.

• Non-resistant and resistant strains can be distinguished.

• Classification of bacteria is possible based on metabolic features.

Laboratory Automation in the Microbiology Laboratory: an Ongoing Journey, Not a Tale?

Clinical chemistry laboratories implemented fully automated devices decades before microbiologists started their subtle approaches to follow. Meanwhile several papers have been published about reduced time to reports, faster workflows, and increased sensitivity as results of lab automation. While the journey of automating microbiology workflows step by step was fascinating and beneficial, monetary aspects were uncommon in most publications. In this issue of the Journal of Clinical Microbiology, K. Culbreath, H. Piwonka, J. Korver, and M. Noorbakhsh (J Clin Microbiol 59:e01969-20, https://doi.org/10.1128/JCM.01969-20) calculate the benefits of total lab automation in terms of cost savings and lab efficiency in a "tale of four laboratories." The authors here provide facts and solid calculations about the benefits achieved in four different-sized labs after implementation of full laboratory automation.

Genotypic Characteristics and Correlation of Epidemiology of Staphylococcus aureus in Healthy Pigs, Diseased Pigs, and Environment

China is one of the largest producers of pigs and pork in the world. However, large-scale studies on pig-associated Staphylococcus aureus in relation to healthy pigs, diseased pigs and environment are scarce. The objective of the present study was to characterize and compare S. aureus isolates from healthy pigs, diseased pigs and environment through antimicrobial susceptibility testing, multiple locus sequence typing, spa typing, and antimicrobial resistance gene screening. Results showed all isolates were susceptible to linezolid and vancomycin. However, 66.7% (104/156) isolates were multidrug-resistant by displaying resistance to three or more antibiotics and high rates of resistance to penicillin, tetracycline, clindamycin, and clarithromycin were observed. Of the 20 multilocus sequence types (STs) identified among the isolates, ST9, ST188, and ST7 were most commonly isolated from healthy pigs and environment, while ST1 was most commonly isolated from diseased pigs. In total, 17 spa types were represented among the isolates, while t4792 was most commonly isolated from diseased pigs and t899, t189 were most commonly isolated from healthy pigs and environment. In conclusion, the genotypic and epidemiology characteristics observed among the isolates suggest pigs and pork could be important players in S. aureus dissemination.

Prevalence and Antibiotic Susceptibility of Bacterial Isolates From Dogs With Ulcerative Keratitis in Midwestern United States

The objective of this study was to describe bacterial culture and antibiotic susceptibility results in 476 dogs presenting with suspected bacterial keratitis in Iowa and surrounding Midwestern states, further detailing trends in patient characteristics, seasonality, and antimicrobial resistance. Corneal swabs yielded 465 bacterial isolates and 220 cultures (46.2%) with no apparent growth (0–5 isolates per culture). The most frequent bacterial genera were Staphylococcus (32.3%), Streptococcus (19.1%), and Pseudomonas (12.5%), while the most common bacterial species were Staphylococcus pseudintermedius (26.7%), Streptococcus canis (12%), and Pseudomonas aeruginosa (7.5%). Compared to mixed-breed dogs, canine breeds most likely to be examined for ulcerative keratitis included Boston terrier, Cavalier King Charles spaniel, miniature pinscher, pug, rat terrier, Saint Bernard, shih tzu, and silky terriers. In summer, the likelihood to yield a negative culture was reduced while the likelihood to culture Pseudomonas species was increased. Bacteria considered multidrug resistant (MDR, resistant to ≥ 3 antibiotic classes) represented 20% of all canine isolates and were most prevalent for Staphylococcus species (33%). An alarming, escalating trend of MDR prevalence was noted between 2016 (5%) and 2020 (34%). Individual ophthalmic preparations (i.e., single antibiotics or commercially available antibiotic combinations) with highest efficacy against all bacterial isolates included chloramphenicol (83%), ceftiofur (79%), amikacin (77%), neomycin-polymyxin B-bacitracin (77%), and gentamicin (74%). Efficacy of systemic antibiotics and combinations of ophthalmic preparations was also evaluated. Based on the present findings, triple antibiotic (Neo-Poly-Bac) is recommended as empirical monotherapy for prophylactic antibiotic therapy in dogs with simple corneal ulcers, while a chloramphenicol-ciprofloxacin combination is empirically recommended for therapeutic management of infected corneal ulcers. Pending culture and susceptibility results, appropriate selection of empiric antibiotic therapy is important to enhance therapeutic outcome and reduce antibacterial resistance in dogs with corneal ulceration.

Optotracing for selective fluorescence-based detection, visualization and quantification of live S. aureus in real-time

Methods for bacterial detection are needed to advance the infection research and diagnostics. Based on conformation-sensitive fluorescent tracer molecules, optotracing was recently established for dynamic detection and visualization of structural amyloids and polysaccharides in the biofilm matrix of gram-negative bacteria. Here, we extend the use of optotracing for detection of gram-positive bacteria, focussing on the clinically relevant opportunistic human pathogen Staphylococcus aureus. We identify a donor-acceptor-donor-type optotracer, whose binding-induced fluorescence enables real-time detection, quantification, and visualization of S. aureus in monoculture and when mixed with gram-negative Salmonella Enteritidis. An algorithm-based automated high-throughput screen of 1920 S. aureus transposon mutants recognized the cell envelope as the binding target, which was corroborated by super-resolution microscopy of bacterial cells and spectroscopic analysis of purified cell wall components. The binding event was essentially governed by hydrophobic interactions, which permitted custom-designed tuning of the binding selectivity towards S. aureus versus Enterococcus faecalis by appropriate selection of buffer conditions. Collectively this work demonstrates optotracing as an enabling technology relevant for any field of basic and applied research, where visualization and detection of S. aureus is needed.

Nanofluidic Immobilization and Growth Detection of Escherichia coli in a Chip for Antibiotic Susceptibility Testing

Infections with antimicrobial resistant bacteria are a rising threat for global healthcare as more and more antibiotics lose their effectiveness against bacterial pathogens. To guarantee the long-term effectiveness of broad-spectrum antibiotics, they may only be prescribed when inevitably required. In order to make a reliable assessment of which antibiotics are effective, rapid point-of-care tests are needed. This can be achieved with fast phenotypic microfluidic tests, which can cope with low bacterial concentrations and work label-free. Here, we present a novel optofluidic chip with a cross-flow immobilization principle using a regular array of nanogaps to concentrate bacteria and detect their growth label-free under the influence of antibiotics. The interferometric measuring principle enabled the detection of the growth of Escherichia coli in under 4 h with a sample volume of 187.2 µL and a doubling time of 79 min. In proof-of-concept experiments, we could show that the method can distinguish between bacterial growth and its inhibition by antibiotics. The results indicate that the nanofluidic chip approach provides a very promising concept for future rapid and label-free antimicrobial susceptibility tests.

A Rapid Flow Cytometric Antimicrobial Susceptibility Assay (FASTvet) for Veterinary Use - Preliminary Data

A rapid flow cytometric antimicrobial susceptibility test for bacteria isolated from companion animals – the FASTvet assay, developed by FASTinov^®, was evaluated. Bacterial strains isolated from different biological samples of companion animals with infectious diseases in progress were obtained from several veterinary clinical laboratories across the country. A total of 115 strains, comprising 65 Gram-negative and 50 Gram positive isolates, were incubated with 13 antimicrobial drugs (ampicillin, amoxicillin-clavulanic acid, piperacillin-tazobactam, cefpodoxime, imipenem, enrofloxacin, gentamicin, amikacin for Gram-negative; penicillin, cefoxitin, enrofloxacin, vancomycin and ampicillin for Gram-positive) at breakpoint concentrations following CLSI protocol (CLSI Vet 01, 2018) for 1 h and analyzed by flow cytometry. The overall categorical agreement was 95.6% in case of Gram-negative and of 96.7% in Gram-positive isolates when compared to microdilution. FASTvet kits contribute to reduce the turnaround time (2 vs. 24 h) with early determination of the antimicrobial susceptibility profile. The correct and rapid choice of the target antibiotic therapy, will have a positive impact on animal care, contributing for preventing antimicrobial resistance. In conclusion, FASTinov^® vet kits showed an excellent performance, both for Gram-negative and Gram-positive isolates encouraging us to enlarge the sample size and planning multicentric studies.

Microfluidic systems for rapid antibiotic susceptibility tests (ASTs) at the single-cell level

Infectious diseases caused by multidrug resistant (MDR) bacterial pathogens are impending threats to global health. Since delays in identifying drug resistance would significantly increase mortality, fast and accurate antibiotic susceptibility tests (ASTs) are critical for addressing the antibiotic resistance issue. However, the conventional methods for ASTs are always labor-intensive, imprecise, complex and slow (taking 2-3 days). To address these issues, some advanced microfluidic systems have been designed for rapid phenotypic and genotypic analysis of antibiotic resistance. This review highlights the recent development of microfluidics-based ASTs at the single-cell or single-molecule level for guiding antibiotic treatment decisions and predicting therapeutic outcomes.

Understanding the challenges of non-food industrial product contamination

Preventing microbial contamination of non-food products is a major area of industrial microbiology where preservatives are used to stop microbial growth. However, microorganisms occasionally overcome product preservation, causing recalls and the implementation of multiple procedures to prevent further contamination. Correct reporting of microbial contamination in non-food industrial products is vital, especially if spoilage organisms are antimicrobial resistant and pose a health threat. Gram-negative bacteria such as Pseudomonas, Burkholderia and Enterobacteriaceae are frequently reported as non-food product contaminants, including species that overlap current antimicrobial resistance priorities. Historical analysis of recall databases highlighted that for greater than 15% of contamination incidents, the causative microbial agents are reported as unidentified. Here we review the current antimicrobial resistant bacterial species associated with non-food product contamination and evaluate recall reporting in Europe from 2005 to 2018. Our review shows that 49% of microbial contaminants are reported as unidentified despite frequent detection of antimicrobial resistant pathogens; in contrast, 98% of food-related microbial contaminants are classified. Recommendations to fill this microbial identification gap in non-food product recalls are made. Overall, reporting standards for microbial contamination in non-food products must be improved to enable surveillance and for understanding the risks associated with antimicrobial resistant microorganisms.

Microbiome and diversity indices during blood stem cells transplantation - new perspectives?

OBJECTIVE

The human body is colonized by bacteria, fungi and viruses. Resident commensal bacteria are a fundamental line of resistance to colonization by exogenous microbes. They actively regulate the production of nutrients by the host through a negative feedback mechanism, in order to prevent the availability of nutrients for potential pathogens. While only a small fraction of these microorganism may be pathogenic, the relationship between host and commensal microbiome is now studied as a whole, impacting several aspects of the host biology. Some studies have made clear the progresses in examining the role of microbiome on transplants and graft versus host disease (GVHD) severity and its pathogenesis: the risk of complications from allogenic hematopoietic stem cells transplantation (HSCT) is greater with the highest mortality if a patient has a lower bacterial diversity in the gut prior to the transplantation process beginning. Microbiota-associated molecular patterns are directly recognized by pathogen recognition receptors. The development of molecular methods has greatly expanded our knowledge of the composition and function of the microbiome in health and disease, shortening the response times vs. microbiological culture tests. The gut flora can make the difference when it comes to allo-HSCT. The aim of the study was to monitor microbiome of 10 children during allo-HSCT.

METHODS

Oral specimens and gut faecal microbiome (100 grams) samples were collected at 2, 16, 24 days. The samples were analysed by polymerase chain reaction and primary sequencing was done. To calculate the biodiversity of microbiome the Shannon index and the Observed species index were chosen.

RESULTS

Our study suggests some differences in the diversity indices (DIs) in 5 children affected by GVHD vs. not affected. The DIs in oral and faecal specimens show in all patients a diminution in the post-transplant phase with an improvement in species diversity after 16 days from the transplant. The Observed species index in faeces specimens after 16 days was higher in patients which had not GVHD; moreover, patients with GVHD showed a deterioration at 24 days. Oral specimens after 24 days showed a parallel trend in the two groups. The Shannon index shows a downward trend in faeces specimens of the children with GVHD at 24 days; the children without GVHD recover a good trend of entropy. Oral specimens at 24 days show low entropy in the two groups. Very aggressive bacterial species as Cronobacter and Routella in the faeces specimens of a child had not serious consequences for disease status: Cronobacter were not present 24 days after transplantation.

CONCLUSIONS

The data show the microbial metabolome could have an impact on patients with GVHD vs. no GVHD. A better understanding of the role of the oral and gut microbiome in GVHD can give directions to move towards the development of innovative approaches for preventing GVHD following allo-HCT, reducing also antibiotic therapy.

A Selective, Dual Emission β-Alanine Aminopeptidase Activated Fluorescent Probe for the Detection of Pseudomonas aeruginosa, Burkholderia cepacia, and Serratia marcescens

Selective detection of β-alanyl aminopeptidase (BAP)-producing Pseudomonas aeruginosa, Serratia marcescens, and Burkholderia cepacia was achieved by employing the blue-to-yellow fluorescent transition of a BAP-specific enzyme substrate, 3-hydroxy-2-(p-dimethylaminophenyl)flavone derivative, incorporating a self-immolative linker to β-alanine. Upon cellular uptake and accumulation of the substrate by viable bacterial colonies, blue fluorescence was generated, while hydrolysis of the N-terminal peptide bond by BAP resulted in the elimination of the self-immolative linker and the restoration of the original fluorescence of the flavone derivative.

Clinical Utility of Advanced Microbiology Testing Tools

Advanced microbiology technologies are rapidly changing our ability to diagnose infections, improve patient care, and enhance clinical workflow. These tools are increasing the breadth, depth, and speed of diagnostic data generated per patient, and testing is being moved closer to the patient through rapid diagnostic technologies, including point-of-care (POC) technologies.

Advanced microbiology technologies are rapidly changing our ability to diagnose infections, improve patient care, and enhance clinical workflow. These tools are increasing the breadth, depth, and speed of diagnostic data generated per patient, and testing is being moved closer to the patient through rapid diagnostic technologies, including point-of-care (POC) technologies. While select stakeholders have an appreciation of the value/importance of improvements in the microbial diagnostic field, there remains a disconnect between clinicians and some payers and hospital administrators in terms of understanding the potential clinical utility of these novel technologies. Therefore, a key challenge for the clinical microbiology community is to clearly articulate the value proposition of these technologies to encourage payers to cover and hospitals to adopt advanced microbiology tests. Specific guidance on how to define and demonstrate clinical utility would be valuable. Addressing this challenge will require alignment on this topic, not just by microbiologists but also by primary care and emergency room (ER) physicians, infectious disease specialists, pharmacists, hospital administrators, and government entities with an interest in public health. In this article, we discuss how to best conduct clinical studies to demonstrate and communicate clinical utility to payers and to set reasonable expectations for what diagnostic manufacturers should be required to demonstrate to support reimbursement from commercial payers and utilization by hospital systems.

Model-Based Spectral Library Approach for Bacterial Identification via Membrane Glycolipids

By circumventing the need for a pure colony, MALDI-TOF mass spectrometry of bacterial membrane glycolipids (lipid A) has the potential to identify microbes more rapidly than protein-based methods. However, currently available bioinformatics algorithms (e.g., dot products) do not work well with glycolipid mass spectra such as those produced by lipid A, the membrane anchor of lipopolysaccharide. To address this issue, we propose a spectral library approach coupled with a machine learning technique to more accurately identify microbes. Here, we demonstrate the performance of the model-based spectral library approach for microbial identification using approximately a thousand mass spectra collected from multi-drug-resistant bacteria. At false discovery rates < 1%, our approach identified many more bacterial species than the existing approaches such as the Bruker Biotyper and characterized over 97% of their phenotypes accurately. As the diversity in our glycolipid mass spectral library increases, we anticipate that it will provide valuable information to more rapidly treat infected patients.

Isolation of intact bacteria from blood by selective cell lysis in a microfluidic porous silica monolith

Rapid and efficient isolation of bacteria from complex biological matrices is necessary for effective pathogen identification in emerging single-cell diagnostics. Here, we demonstrate the isolation of intact and viable bacteria from whole blood through the selective lysis of blood cells during flow through a porous silica monolith. Efficient mechanical hemolysis is achieved while providing passage of intact and viable bacteria through the monoliths, allowing size-based isolation of bacteria to be performed following selective lysis. A process for synthesizing large quantities of discrete capillary-bound monolith elements and millimeter-scale monolith bricks is described, together with the seamless integration of individual monoliths into microfluidic chips. The impact of monolith morphology, geometry, and flow conditions on cell lysis is explored, and flow regimes are identified wherein robust selective blood cell lysis and intact bacteria passage are achieved for multiple gram-negative and gram-positive bacteria. The technique is shown to enable rapid sample preparation and bacteria analysis by single-cell Raman spectrometry. The selective lysis technique presents a unique sample preparation step supporting rapid and culture-free analysis of bacteria for the point of care.

Direct matrix-assisted laser desorption ionization time-of-flight mass spectrometry and real-time PCR in a combined protocol for diagnosis of bloodstream infections: a turnaround time approach

Bloodstream infections (BSIs) are serious infections associated with high rates of morbidity and mortality. Every hour delay in initiation of an effective antibiotic increases mortality due to sepsis by 7%. Turnaround time (TAT) for conventional blood cultures takes 48 h, forcing physicians to streamline therapy by exposing patients to broad-spectrum antimicrobials. Our objective was (1) to evaluate the accuracy and TAT of an optimized workflow combining direct matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) and in-house real-time polymerase chain reaction (PCR) for bacterial identification and antimicrobial resistance profiling directly from positive blood bottles for diagnosing bloodstream infections and (2) to verify the effect of reporting results to medical staff. A total of 103 BSI episodes from 91 patients admitted to three hospitals in São Paulo, Brazil were included. TAT from molecular versus conventional methods was measured and compared. Our protocol showed an overall agreement of 93.5% for genus and 78.5% for species identification; 74.2% for methicillin resistance detection, 89.2% for extended-spectrum β-lactamase profiling, 77.8% for metallo-β-lactamase profiling, and 100% for carbapenemase profile and vancomycin-resistance detection when compared with conventional testing. TAT of molecular sample processing according to our protocol was 38 h shorter than conventional methods. Antimicrobial interventions were possible in 27 BSI episodes. Antimicrobial discontinuation was achieved in 12 BSI episodes while escalation of therapy occurred in 15 episodes. Antimicrobial therapy was inadequate in three (12%) BSI episodes diagnosed using results of molecular testing. Our in-house rapid protocol for identifying both bacteria and antimicrobial resistance provided rapid and accurate results, having good agreement with conventional testing results. These results could contribute to faster antimicrobial therapy interventions in BSI episodes.

Molecular identification of Salmonella Typhimurium from village chickens based on invA and spvC genes

AIM

This study aimed to identify Salmonella enterica serovars by polymerase chain reaction (PCR) based on virulence genes invasion A (invA) and Salmonella plasmid virulence C (spvC).

MATERIALS AND METHODS

DNA extraction of eight bacteria isolates was done using the PowerSoil® DNA Isolation Kit. The amplification of invA and spvC genes was done using conventional PCR. The positive PCR products were purified using the GeneJET Purification Kit and then sequenced using ABI 3730 XL automated genetic analyzer. The sequences obtained were compared for similarities with other Salmonella serovars deposited on the NCBI GenBank using BLASTN.

RESULTS

Four out of eight samples were amplified by primers FS139/RS141 that target invA gene with products of about 284 bp, and three out of four of the same invA positive samples were also amplified by primers FSPV-1/RSPV-2 targeting spvC with a product of about 571 bp. One sample was not amplified by primers FSPV-1/RSPV-2 as it lacked virulence plasmid. Analysis of sequences indicated 100% homology with closely related serovars of S. enterica subspecies enterica serovar Typhimurium.

CONCLUSION

Salmonella Typhimurium that contained invA and spvC genes are pathogenic and virulent strains.

Rapid Microbial Identification and Antibiotic Resistance Detection by Mass Spectrometric Analysis of Membrane Lipids

Infectious diseases have a substantial global health impact. Clinicians need rapid and accurate diagnoses of infections to direct patient treatment and improve antibiotic stewardship. Current technologies employed in routine diagnostics are based on bacterial culture followed by morphological trait differentiation and biochemical testing, which can be time-consuming and labor-intensive. With advances in mass spectrometry (MS) for clinical diagnostics, the U.S. Food and Drug Administration has approved two microbial identification platforms based on matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS analysis of microbial proteins. We recently reported a novel and complementary approach by comparing MALDI-TOF mass spectra of microbial membrane lipid fingerprints to identify ESKAPE pathogens. However, this lipid-based approach used a sample preparation method that required more than a working day from sample collection to identification. Here, we report a new method that extracts lipids efficiently and rapidly from microbial membranes using an aqueous sodium acetate (SA) buffer that can be used to identify clinically relevant Gram-positive and -negative pathogens and fungal species in less than an hour. The SA method also has the ability to differentiate antibiotic-susceptible and antibiotic-resistant strains, directly identify microbes from biological specimens, and detect multiple pathogens in a mixed sample. These results should have positive implications for the manner in which bacteria and fungi are identified in general hospital settings and intensive care units.

Microbial Proteomics and Their Importance in Medical Microbiology

Microbial infection is a leading cause of death around the world. Most of the infectious diseases are caused by drug-resistant microbes; this may lead to a delay in the administration of microbiologically effective therapy (Chen et al., 2017; Del Chierico et al., 2014). Therefore, exhaustive understanding of microbial physiologies, infection and defense systems, and survival strategies is of great interest in order to actively defeat microbial infection. Microbial proteomics provides complete information of microbial physiology and expression and function of the proteins that are involved in infection and also gives a clue in clinical diagnosis and antimicrobial therapy (Pérez-Llarena and Bou, 2016; Vranakis et al., 2014). Microbial proteomics helps to identify the proteins associated with microbial activity, microbial host-pathogen interactions, and antimicrobial resistant mechanism. Microbial activity of pathogens can be confirmed by using the 2-D gel-based and gel-free method with the combination of MALDI-TOF-LC-MS/MS. Proteomic analysis of microbial host-pathogen interaction reveals valuable information about the virulence of the pathogen and its resistance; it helps in better understanding of the infection and for developing strategies against microbial infections (Cheng et al., 2016). Fig. 3.1 schematically illustrates the proteomic analysis of the bacterial samples.

Phenotypic antibiotic susceptibility testing of pathogenic bacteria using photonic readout methods: recent achievements and impact

The development of antibiotic resistances in common pathogens is an increasing challenge for therapy of infections and especially severe complications like sepsis. To prevent administration of broad-spectrum and potentially non-effective antibiotics, the susceptibility spectrum of the pathogens underlying the infection has to be determined. Current phenotypic standard methods for antibiotic susceptibility testing (AST) require the isolation of pathogens from the patient and the subsequent culturing in the presence of antibiotics leading to results only after 24-72 h. Since the early initialization of an effective antibiotic therapy is crucial for positive treatment result in severe infections, faster methods of AST are urgently needed. A large number of different assay systems are currently tested for their practicability for fast detection of antibiotic resistance profiles. They can be divided into genotypic ones which detect the presence of certain genes or gene products associated with resistances and phenotypic assays which determine the effect of antibiotics on the pathogens. In this mini-review, we summarize current developments in fast phenotypic tests that use photonic approaches and critically discuss their status. We further outline steps that are required to bring these assays into clinical practice.

Pathogen Identification Direct From Polymicrobial Specimens Using Membrane Glycolipids

With the increased prevalence of multidrug-resistant Gram-negative bacteria, the use of colistin and other last-line antimicrobials is being revisited clinically. As a result, there has been an emergence of colistin-resistant bacterial species, including Acinetobacter baumannii and Klebsiella pneumoniae. The rapid identification of such pathogens is vitally important for the effective treatment of patients. We previously demonstrated that mass spectrometry of bacterial glycolipids has the capacity to identify and detect colistin resistance in a variety of bacterial species. In this study, we present a machine learning paradigm that is capable of identifying A. baumannii, K. pneumoniae and their colistin-resistant forms using a manually curated dataset of lipid mass spectra from 48 additional Gram-positive and -negative organisms. We demonstrate that these classifiers detect A. baumannii and K. pneumoniae in isolate and polymicrobial specimens, establishing a framework to translate glycolipid mass spectra into pathogen identifications.

Culture-free Antibiotic-susceptibility Determination From Single-bacterium Raman Spectra

Raman spectrometry appears to be an opportunity to perform rapid tests in microbiological diagnostics as it provides phenotype-related information from single bacterial cells thus holding the promise of direct analysis of clinical specimens without any time-consuming growth phase. Here, we demonstrate the feasibility of a rapid antibiotic-susceptibility determination based on the use of Raman spectra acquired on single bacterial cells. After a two-hour preculture step, one susceptible and two resistant E. coli strains were incubated, for only two hours, in the presence of different bactericidal antibiotics (gentamicin, ciprofloxacin, amoxicillin) in a range of concentrations that included the clinical breakpoints used as references in microbial diagnostic. Spectra were acquired and processed to isolate spectral modifications associated with the antibiotic effect. We evidenced an “antibiotic effect signature” which is expressed with specific Raman peaks and the coexistence of three spectral populations in the presence of antibiotic. We devised an algorithm and a test procedure that overcome single-cell heterogeneities to estimate the MIC and determinate the susceptibility phenotype of the tested bacteria using only a few single-cell spectra in four hours only if including the preculture step.

Control of Infectious Diseases in the Era of European Clinical Microbiology Laboratory Consolidation: New Challenges and Opportunities for the Patient and for Public Health Surveillance

Many new innovative diagnostic approaches have been made available during the last 10 years with major impact on patient care and public health surveillance. In parallel, to enhance the cost-effectiveness of the clinical microbiology laboratories (CMLs), European laboratory professionals have streamlined their organization leading to amalgamation of activities and restructuring of their professional relationships with clinicians and public health specialists. Through this consolidation process, an operational model has emerged that combines large centralized clinical laboratories performing most tests on one high-throughput analytical platform connected to several distal laboratories dealing locally with urgent analyses at near point of care. The centralization of diagnostic services over a large geographical region has given rise to the concept of regional-scale "microbiology laboratories network." Although the volume-driven cost savings associated with such laboratory networks seem self-evident, the consequence(s) for the quality of patient care and infectious disease surveillance and control remain less obvious. In this article, we describe the range of opportunities that the changing landscape of CMLs in Europe can contribute toward improving the quality of patient care but also the early detection and enhanced surveillance of public health threats caused by infectious diseases. The success of this transformation of health services is reliant on the appropriate preparation in terms of staff, skills, and processes that would be inclusive of stakeholders. In addition, rigorous metrics are needed to set out more concrete laboratory service performance objectives and assess the expected benefits to society in terms of saving lives and preventing diseases.

Growth of Escherichia coli on the GaAs (001) surface

Detection of pathogenic bacteria and monitoring their susceptibility to antibiotics are of great importance in the fields of medicine, pharmaceutical research, as well as water and food industries. In order to develop a photonic biosensor for detection of bacteria by taking advantage of photoluminescence (PL) of GaAs-based devices, we have investigated the capture and growth of Escherichia coli K12 on bare and biofunctionalized surfaces of GaAs (001) - a material of interest for capping different semiconductor microstructures. The results were compared with the capture and growth of Escherichia coli K12 on Au surfaces that have commonly been applied for studying a variety of biological and biochemical reactions. We found that neither GaAs nor Au-coated glass wafers placed in Petri dishes inoculated with bacteria inhibited bacterial growth in nutrient agar, regardless of the wafers being bare or biofunctionalized. However, the capture and growth of bacteria on biofunctionalized surfaces of GaAs and Au wafers kept in a flow cell and exposed to different concentrations of bacteria and growth medium revealed that the initial surface coverage and the subsequent bacterial growth were dependent on the biofunctionalization architecture, with antibody-coated surfaces clearly being most efficient in capturing bacteria and offering better conditions for growth of bacteria. We have observed that, as long as the GaAs wafers were exposed to bacterial suspensions at concentrations of at least 10⁵ CFU/mL, bacteria could grow on the surface of wafers, regardless of the type of biofunctionalization architecture used to capture the bacteria. These results provide important insight towards the successful development of GaAs-based devices designed for photonic monitoring of bacterial reactions to different biochemical environments.

Antimicrobial resistance and antibiotic stewardship programs in the ICU: insistence and persistence in the fight against resistance. A position statement from ESICM/ESCMID/WAAAR round table on multi-drug resistance

Antimicrobial resistance (AMR) is a clear and present danger to patients in any intensive care unit (ICU) around the world. Whereas AMR may affect any patient in the hospital, patients in the ICU are particularly at risk of acquiring AMR infections due to the intensity of the treatment, use of invasive devices, increased risk of transmission and exposure to antibiotics. AMR is present in every ICU, although prevalence is geographically different and AMR pathogens encountered are variable. Intensive care and infectious disease specialists from the European Society of Intensive Care Medicine, European Society of Microbiology and Infectious Diseases and World Alliance Against Antimicrobial Resistance, united in the ANTARCTICA (Antimicrobial Resistance in Critical Care) coalition, call for increased awareness and action among health care professionals to reduce AMR development in critically ill patients, to improve treatment of AMR infections and to coordinate scientific research in this high-risk patient population. Close collaboration with other specialties, and combining these and other interventions in antibiotic stewardship programmes should be a priority in every ICU. Considerate antibiotic use and adopting strict infection control practices to halt AMR remains a responsibility shared by all healthcare workers, from physicians to maintenance personnel, from nurses to physiotherapists, from consultants to medical students. Together, we can reduce AMR in our ICUs and continue to treat our patients effectively.

The Changing Role of the Clinical Microbiology Laboratory in Defining Resistance in Gram-negatives

The evolution of resistance in Gram-negatives has challenged the clinical microbiology laboratory to implement new methods for their detection. Multidrug-resistant strains present major challenges to conventional and new detection methods. More rapid pathogen identification and antimicrobial susceptibility testing have been developed for use directly on specimens, including fluorescence in situ hybridization tests, automated polymerase chain reaction systems, microarrays, mass spectroscopy, next-generation sequencing, and microfluidics. Review of these methods shows the advances that have been made in rapid detection of resistance in cultures, but limited progress in direct detection from specimens.

Antibiotic susceptibility testing in less than 30 min using direct single-cell imaging

The emergence and spread of antibiotic-resistant bacteria are aggravated by incorrect prescription and use of antibiotics. A core problem is that there is no sufficiently fast diagnostic test to guide correct antibiotic prescription at the point of care. Here, we investigate if it is possible to develop a point-of-care susceptibility test for urinary tract infection, a disease that 100 million women suffer from annually and that exhibits widespread antibiotic resistance. We capture bacterial cells directly from samples with low bacterial counts (10⁴ cfu/mL) using a custom-designed microfluidic chip and monitor their individual growth rates using microscopy. By averaging the growth rate response to an antibiotic over many individual cells, we can push the detection time to the biological response time of the bacteria. We find that it is possible to detect changes in growth rate in response to each of nine antibiotics that are used to treat urinary tract infections in minutes. In a test of 49 clinical uropathogenic Escherichia coli (UPEC) isolates, all were correctly classified as susceptible or resistant to ciprofloxacin in less than 10 min. The total time for antibiotic susceptibility testing, from loading of sample to diagnostic readout, is less than 30 min, which allows the development of a point-of-care test that can guide correct treatment of urinary tract infection.

Rapid Phenotypic Detection of Microbial Resistance in Gram-Positive Bacteria by a Real-Time Laser Scattering Method

We developed a methodology for antimicrobial susceptibility testing (AST) based on the BacterioScan^TM216R laser scattering technology, using methicillin resistance in Staphylococcus aureus and vancomycin resistance in enterococci as exemplar for important resistance phenotypes. Fifty methicillin-resistant (MRSA) and 50 methicillin-susceptible (MSSA) S. aureus, as well as 50 vancomycin-resistant enterococci (VRE) and 50 vancomycin-susceptible enterococci (VSE) isolates were used for the study. Optimal test conditions were derived by investigating the effects of inoculum size, medium, incubation temperature and broth filtration. We proposed four different statistical approaches for rapid discrimination between resistant and susceptible bacteria. The statistical approach based on raw measurements of bacterial concentrations delivered sensitivity of 100% and specificity of 94% for discrimination between MRSA and MSSA already after 3 hours of incubation. Categorical agreement of ≥90% was achieved after 140 min with this approach. Differentiation between VRE and VSE was possible with 98% sensitivity and 92% specificity after 3 hours, using a sophisticated statistical approach based on concentration slopes derived from the raw concentration measurements. This approach provided categorical agreement of ≥90% after 165 min. The sensitivity and specificity estimates were confirmed by leave-one-out cross validation. In conclusion, the phenotypic AST methods developed in this study are promising for rapid detection of MRSA and VRE. The development and application of this technology would allow early detection of the resistant pathogens, thus facilitating swift change to the targeted antimicrobial treatment as well as timely initiation of appropriate infection control measures. Further studies are warranted to validate this approach for the detection of other resistance phenotypes, including direct testing from clinical specimens.

Mass spectrometry applied to the identification of Mycobacterium tuberculosis and biomarker discovery

An adequate and effective tuberculosis (TB) diagnosis system has been identified by the World Health Organization as a priority in the fight against this disease. Over the years, several methods have been developed to identify the bacillus, but bacterial culture remains one of the most affordable methods for most countries. For rapid and accurate identification, however, it is more feasible to implement molecular techniques, taking advantage of the availability of public databases containing protein sequences. Mass spectrometry (MS) has become an interesting technique for the identification of TB. Here, we review some of the most widely employed methods for identifying Mycobacterium tuberculosis and present an update on MS applied for the identification of mycobacterial species.

Novel portable platform for molecular detection of toxigenic Clostridium difficile in faeces: a diagnostic accuracy study

BACKGROUND

A novel portable platform for nucleic acid amplification enables rapid detection of diarrhoea causing toxigenic Clostridium difficile directly from faeces, even in resource-limited settings. We evaluated the accuracy and precision of the new commercial molecular test system.

METHODS

One thousand one hundred and sixty faecal samples from patients suspected of having Clostridium difficile infection (CDI) were analysed using the Orion GenRead C. difficile test system (Orion Diagnostica Oy, Espoo, Finland) and comparative methods in three teaching hospital laboratories in Finland and France. The precision of the Orion GenRead C. difficile test system was evaluated in a reproducibility study with a set of blind-coded samples. The test system is based on a new isothermal amplification technology (Strand Invasion Based Amplification, SIBA®) and detection of the tcdB gene of C. difficile. We calculated the sensitivity, specificity, and the overall agreement according to Clinical and Laboratory Standards Institute recommendations.

FINDINGS

The overall agreement of the Orion GenRead C. difficile test when compared to the comparative methods in routine use in the participating laboratories was between 96.7% and 98.8%. In the reproducibility study; the total percent agreement between three laboratories was 99.8%.

INTERPRETATION

The identification of toxigenic C. difficile from faeces with the light-weight portable Orion GenRead test system was highly sensitive and specific, and the results were reproducible in the participating laboratories. This platform could enable fast and accurate molecular pathogen detection even in resource-limited or point-of-care settings.

Antimicrobial susceptibility testing of Gram-positive and -negative bacterial isolates directly from spiked blood culture media with Raman spectroscopy

Patients suffering from bacterial bloodstream infections have an increased risk of developing systematic inflammatory response syndrome (SIRS), which can result in rapid deterioration of the patients' health. Diagnostic methods for bacterial identification and antimicrobial susceptibility tests are time-consuming. The aim of this study was to investigate whether Raman spectroscopy would be able to rapidly provide an antimicrobial susceptibility profile from bacteria isolated directly from positive blood cultures. First, bacterial strains (n = 133) were inoculated in tryptic soy broth and incubated in the presence or absence of antibiotics for 5 h. Antimicrobial susceptibility profiles were analyzed by Raman spectroscopy. Subsequently, a selection of strains was isolated from blood cultures and analyzed similarly. VITEK®2 technology and broth dilution were used as the reference methods. Raman spectra from 67 antibiotic-susceptible strains showed discriminatory spectra in the absence or at low concentrations of antibiotics as compared to high antibiotic concentrations. For 66 antibiotic-resistant strains, no antimicrobial effect was observed on the bacterial Raman spectra. Full concordance with VITEK®2 data and broth dilution was obtained for the antibiotic-susceptible strains, 68 % and 98 %, respectively, for the resistant strains. Discriminative antimicrobial susceptibility testing (AST) profiles were obtained for all bacterial strains isolated from blood cultures, resulting in full concordance with the VITEK®2 data. It can be concluded that Raman spectroscopy is able to detect the antimicrobial susceptibility of bacterial species isolated from a positive blood culture bottle within 5 h. Although Raman spectroscopy is cheap and rapid, further optimization is required, to fulfill a great promise for future AST profiling technology development.

Mass spectrometry methods for predicting antibiotic resistance

Developing elaborate techniques for clinical applications can be a complicated process. Whole-cell MALDI-TOF MS revolutionized reliable microorganism identification in clinical microbiology laboratories and is now replacing phenotypic microbial identification. This technique is a generic, accurate, rapid, and cost-effective growth-based method. Antibiotic resistance keeps emerging in environmental and clinical microorganisms, leading to clinical therapeutic challenges, especially for Gram-negative bacteria. Antimicrobial susceptibility testing is used to reliably predict antimicrobial success in treating infection, but it is inherently limited by the need to isolate and grow cultures, delaying the application of appropriate therapies. Antibiotic resistance prediction by growth-independent methods is expected to reduce the turnaround time. Recently, the potential of next-generation sequencing and microarrays in predicting microbial resistance has been demonstrated, and this review evaluates the potential of MS in this field. First, technological advances are described, and the possibility of predicting antibiotic resistance by MS is then illustrated for three prototypical human pathogens: Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa. Clearly, MS methods can identify antimicrobial resistance mediated by horizontal gene transfers or by mutations that affect the quantity of a gene product, whereas antimicrobial resistance mediated by target mutations remains difficult to detect.