Clinical Diagnostic Microbiology Research Articles

Evaluating Use of Generative Artificial Intelligence in Clinical Pathology Practice: Opportunities and the Way Forward.

Generative artificial intelligence (GAI) technologies are likely to dramatically impact health care workflows in clinical pathology (CP). Applications in CP include education, data mining, decision support, result summaries, and patient trend assessments. To review use cases of GAI in CP, with a particular focus on large language models. Specific examples are provided for the applications of GAI in the subspecialties of clinical chemistry, microbiology, hematopathology, and molecular diagnostics. Additionally, the review addresses potential pitfalls of GAI paradigms. Current literature on GAI in health care was reviewed broadly. The use case scenarios for each CP subspecialty review common data sources generated in each subspecialty. The potential for utilization of CP data in the GAI context was subsequently assessed, focusing on issues such as future reporting paradigms, impact on quality metrics, and potential for translational research activities. GAI is a powerful tool with the potential to revolutionize health care for patients and practitioners alike. However, GAI must be implemented with much caution considering various shortcomings of the technology such as biases, hallucinations, practical challenges of implementing GAI in existing CP workflows, and end-user acceptance. Human-in-the-loop models of GAI implementation have the potential to revolutionize CP by delivering deeper, meaningful insights into patient outcomes both at an individual and population level.

A rare case report of tissue infection caused by Pantoea piersonii (basionym Kalamiella piersonii).

In 2019, Pantoea piersonii was initially isolated from the interior surfaces of the International Space Station. This microorganism is a species within the genus Pantoea in the family Erwiniaceae, belonging to the order Enterobacterales. Recent literature has documented four cases of its isolation. Despite initial predictions suggesting the non-pathogenicity of P. piersonii strains, evidence from observed cases indicates potential pathogenicity. According to documented evidence in the literature, this microorganism is capable of causing severe and life-threatening conditions, including sepsis. Traditional tests, as well as automated systems, may fail to provide complete differentiation due to these similarities. While MALDI-TOF MS is a valuable tool for identification in clinical diagnostic microbiology, sequencing may be necessary for precise identification. To determine the antibiotic susceptibility profile, various methods can be utilized, including minimum inhibitory concentration determination, disk diffusion testing (Kirby-Bauer test), genotypic resistance assays (PCR and sequencing), and automated systems. The literature reports a limited number of cases associating P. piersonii with human infection. This study contributes to this body of knowledge by reporting a novel case in which P. piersonii was isolated from a tissue sample for the first time. In this case report, the patient achieved recovery following the administration of appropriate antibiotic treatment based on the diagnosis. It underscores the need for precise identification and understanding of its pathogenicity.

B-225 Bridging the Gap Between Clinical Microbiology and Molecular Diagnostics: Correlation of PCR Cycle Threshold Values for Establishing Semi-Quantitative CFU/mL Ranges of Bacterial Targets

Abstract Background Molecular diagnostics (MolDx) has surpassed culture in the clinical microbiology laboratory. Wong (2023) states PCR is more sensitive than urine culture in detecting polymicrobial infections (para. 8), marking an advantage in MolDX for urinary tract infections. This advancement poses a challenge for clinicians in treatment decision-making. To address requests for numerical MolDx result ranges, a validation accessed semi-quantitative Colony Forming Units per milliliter (CFU/mL) through the assessment of PCR cycle threshold (CT) values. Methods Bacterial targets of UTI and STI PCR panels were inoculated in nutrient broth (Hardy diagnostics cat#K43) and incubated overnight in a shaking incubator at 35±2°C. The density of the cultures was measured using the OD600 function of a NanoDrop One/One after 18-24 hour incubation. The density of stock cultures was adjusted to 106 CFU/mL. Serial dilutions of stock were made in 1:10 steps covering the range of 106 to 100 CFU/mL. The stock and dilutions were extracted, and PCR was performed in a minimum of 2 replicates of each sample for the UTI and STI PCR panels. Mean CT values, standard deviations and coefficients of variation were calculated for each sample. The linearity of CT values within each organism’s stock and dilution samples were assessed by evaluating the CT differences between each dilution step. Corresponding CFU/mL concentrations were tabulated against each mean CT value. Results The average CT values for reportable CFU/mL ranges were established for each stock and dilution. Mean CT values for each CFU/mL breakdown across all organisms were also calculated, along with standard deviations, to investigate universal CT-CFU/mL correlations. A final interpretation table (Table 1) was constructed according to the universal range calculations. Conclusions The study confirmed correlation between CT values and CFU/mL ranges. Further data analysis and comparison with other laboratories’ results will enhance accuracy and precision of reportable CFU/mL ranges.

Validation of a qualitative real-time PCR assay for the detection of Candida auris in hospital inpatient screening.

This study overviews the validation and implementation of a molecular screening tool for the detection of Candida auris in a College of American Pathologist-accredited clinical laboratory. This molecular laboratory-developed test is both highly sensitive and specific and has significant health-system cost-savings associated with significantly reduced turn-around-time compared to traditional standard-of-care culture-based work up. This method and workflow is of interest to support clinical microbiology diagnostics and to help aid in hospital inpatient, and infection prevention control screening.

Sampling for the diagnosis of orthopaedic surgical infections

Orthopaedic surgical infections, in Denmark, are managed heterogeneously, both within the orthopaedic surgical and the clinical microbiological specialty. More uniform guidelines for sampling and clinical microbiological diagnostics for suspected orthopedic surgical infections would be appropriate. The purpose of this review is therefore to initiate a process aiming for consensus on sampling methods of tissue materials and fluids and clinical microbiological sample handling.

Development and validation of a quick, automated, and reproducible ATR FT-IR spectroscopy machine-learning model for Klebsiella pneumoniae typing.

The reliability of Fourier-transform infrared (FT-IR) spectroscopy for Klebsiella pneumoniae typing and outbreak control has been previously assessed, but issues remain in standardization and reproducibility. We developed and validated a reproducible FT-IR with attenuated total reflectance (ATR) workflow for the identification of K. pneumoniae lineages. We used 293 isolates representing multidrug-resistant K. pneumoniae lineages causing outbreaks worldwide (2002-2021) to train a random forest classification (RF) model based on capsular (KL)-type discrimination. This model was validated with 280 contemporaneous isolates (2021-2022), using wzi sequencing and whole-genome sequencing as references. Repeatability and reproducibility were tested in different culture media and instruments throughout time. Our RF model allowed the classification of 33 capsular (KL)-types and up to 36 clinically relevant K. pneumoniae lineages based on the discrimination of specific KL- and O-type combinations. We obtained high rates of accuracy (89%), sensitivity (88%), and specificity (92%), including from cultures obtained directly from the clinical sample, allowing to obtain typing information the same day bacteria are identified. The workflow was reproducible in different instruments throughout time (>98% correct predictions). Direct colony application, spectral acquisition, and automated KL prediction through Clover MS Data analysis software allow a short time-to-result (5 min/isolate). We demonstrated that FT-IR ATR spectroscopy provides meaningful, reproducible, and accurate information at a very early stage (as soon as bacterial identification) to support infection control and public health surveillance. The high robustness together with automated and flexible workflows for data analysis provide opportunities to consolidate real-time applications at a global level. IMPORTANCE We created and validated an automated and simple workflow for the identification of clinically relevant Klebsiella pneumoniae lineages by FT-IR spectroscopy and machine-learning, a method that can be extremely useful to provide quick and reliable typing information to support real-time decisions of outbreak management and infection control. This method and workflow is of interest to support clinical microbiology diagnostics and to aid public health surveillance.

ChatGPT Performance in Diagnostic Clinical Microbiology Laboratory-Oriented Case Scenarios.

Artificial intelligence (AI)-based tools can reshape healthcare practice. This includes ChatGPT which is considered among the most popular AI-based conversational models. Nevertheless, the performance of different versions of ChatGPT needs further evaluation in different settings to assess its reliability and credibility in various healthcare-related tasks. Therefore, the current study aimed to assess the performance of the freely available ChatGPT-3.5 and the paid version ChatGPT-4 in 10 different diagnostic clinical microbiology case scenarios. The current study followed the METRICS (Model, Evaluation, Timing/Transparency, Range/Randomization, Individual factors, Count, Specificity of the prompts/language) checklist for standardization of the design and reporting of AI-based studies in healthcare. The models tested on December 3, 2023 included ChatGPT-3.5 and ChatGPT-4 and the evaluation of the ChatGPT-generated content was based on the CLEAR tool (Completeness, Lack of false information, Evidence support, Appropriateness, and Relevance) assessed on a 5-point Likert scale with a range of the CLEAR scores of 1-5. ChatGPT output was evaluated by two raters independently and the inter-rater agreement was based on the Cohen's κ statistic. Ten diagnostic clinical microbiology laboratory case scenarios were created in the English language by three microbiologists at diverse levels of expertise following an internal discussion of common cases observed in Jordan. The range of topics included bacteriology, mycology, parasitology, and virology cases. Specific prompts were tailored based on the CLEAR tool and a new session was selected following prompting each case scenario. The Cohen's κ values for the five CLEAR items were 0.351-0.737 for ChatGPT-3.5 and 0.294-0.701 for ChatGPT-4 indicating fair to good agreement and suitability for analysis. Based on the average CLEAR scores, ChatGPT-4 outperformed ChatGPT-3.5 (mean: 2.64±1.06 vs. 3.21±1.05,P=.012, t-test). The performance of each model varied based on the CLEAR items, with the lowest performance for the "Relevance" item (2.15±0.71 for ChatGPT-3.5 and 2.65±1.16 for ChatGPT-4). A statistically significant difference upon assessing the performance per each CLEAR item was only seen in ChatGPT-4 with the best performance in "Completeness", "Lack of false information", and "Evidence support" (P=0.043). The lowest level of performance for both models was observed with antimicrobial susceptibility testing (AST) queries while the highest level of performance was seen in bacterial and mycologic identification. Assessment of ChatGPT performance across different diagnostic clinical microbiology case scenarios showed that ChatGPT-4 outperformed ChatGPT-3.5. The performance of ChatGPT demonstrated noticeable variability depending on the specific topic evaluated. A primary shortcoming of both ChatGPT models was the tendency to generate irrelevant content lacking the needed focus. Although the overall ChatGPT performance in these diagnostic microbiology case scenarios might be described as "above average" at best, there remains a significant potential for improvement, considering the identified limitations and unsatisfactory results in a few cases.

Rapid identification of pathogens in blood serum via Raman tweezers in combination with advanced processing methods.

Pathogenic microbes contribute to several major global diseases that kill millions of people every year. Bloodstream infections caused by these microbes are associated with high morbidity and mortality rates, which are among the most common causes of hospitalizations. The search for the "Holy Grail" in clinical diagnostic microbiology, a reliable, accurate, low cost, real-time, and easy-to-use diagnostic method, is one of the essential issues in clinical practice. These very critical conditions can be met by Raman tweezers in combination with advanced analysis methods. Here, we present a proof-of-concept study based on Raman tweezers combined with spectral mixture analysis that allows for the identification of microbial strains directly from human blood serum without user intervention, thus eliminating the influence of a data analyst.

Environmental surveillance for Salmonella Typhi as a tool to estimate the incidence of typhoid fever in low-income populations.

Background: The World Health Organisation recommends prioritised use of recently prequalified typhoid conjugate vaccines in countries with the highest incidence of typhoid fever. However, representative typhoid surveillance data are lacking in many low-income countries because of the costs and challenges of diagnostic clinical microbiology. Environmental surveillance (ES) of Salmonella Typhi in sewage and wastewater using molecular methods may offer a low-cost alternative, but its performance in comparison with clinical surveillance has not been assessed. Methods: We developed a harmonised protocol for typhoid ES and its implementation in communities in India and Malawi where it will be compared with findings from hospital-based surveillance for typhoid fever. The protocol includes methods for ES site selection based on geospatial analysis, grab and trap sample collection at sewage and wastewater sites, and laboratory methods for sample processing, concentration and quantitative polymerase chain reaction (PCR) to detect Salmonella Typhi. The optimal locations for ES sites based on digital elevation models and mapping of sewage and river networks are described for each community and their suitability confirmed through field investigation. We will compare the prevalence and abundance of Salmonella Typhi in ES samples collected each month over a 12-month period to the incidence of blood culture confirmed typhoid cases recorded at referral hospitals serving the study areas. Conclusions: If environmental detection of Salmonella Typhi correlates with the incidence of typhoid fever estimated through clinical surveillance, typhoid ES may be a powerful and low-cost tool to estimate the local burden of typhoid fever and support the introduction of typhoid conjugate vaccines. Typhoid ES could also allow the impact of vaccination to be assessed and rapidly identify circulation of drug resistant strains.

Navigation of medical microbiology to diagnostic microbiology

Diagnostic microbiology is a branch of medical science concerned with the prevention, diagnosis and treatment of infectious diseases. The kinds of microorganisms that cause infectious disease i.e. bacteria, fungi, parasites and viruses, and other type of infectious protein called proon. This study, studies the characteristics of pathogens, their modes of growth and transmission of infections. In this respect the entire field, as an applied science, can be conceptually subdivided into academic and clinical sub-specialties, although in reality there is a fluid continuum between public health microbiology and clinical microbiology or Diagnostic microbiology, just as the state of the art in clinical laboratories depends on continual improvements in academic medicine and research laboratories.

Point of care testing for infectious disease: ownership and quality.

Traditionally, diagnosis of acute infections has been organism-growth based, which makes timely and actionable infection diagnosis a major challenge. In addition, traditional microbial detection methods, including direct microscopy, are not suited for outsourcing to clinical, non-laboratory-educated personnel. Optimal management of patients with known or suspected clinical infections, such as targeted (or no) antimicrobial treatment and correct use of single room contact isolation facilities, requires rapid identification of the causative infectious microorganism. We are now facing a new disruptive paradigm shift in diagnostic microbiology. The availability of small-footprint robust instruments with easy-to-use assay kits allows non-laboratory-trained nurses and physicians to perform high-quality molecular diagnostics in a near-patient setting with results available in <30 minutes. This technology is currently breaking the centralized laboratory monopoly on the delivery of gold-standard clinical microbiology diagnostics. There is clear potential for huge positive impacts on clinical patient management and antibiotic stewardship, especially in settings where access to timely laboratory test results is not possible, but there are also potentially huge risks. Moving diagnostic testing away from the controlled diagnostic laboratory environment will lead to risks such as increased risk of inappropriate use of the diagnostic tests, insufficient training of staff performing the tests, incorrect interpretation of the test results, lack of quality control procedures, failure to capture test results in electronic patient records and compromised local as well as national surveillance. To reap the upside and avoid the downside of point-of-care infectious disease testing, the diagnostic laboratory needs to maintain oversight, and each institution must have a clear strategy for implementation and execution. If we fail, the risks could outweigh the benefits.

Post-operative kinetics of C-reactive protein to distinguish between bacterial infection and systemic inflammation in infants after cardiopulmonary bypass surgery: the early and the late period.

Differentiation between post-operative inflammation and bacterial infection remains an important issue in infants following congenital heart surgery. We primarily assessed kinetics and predictive value of C-reactive protein for bacterial infection in the early (days 0-4) and late (days 5-28) period after cardiopulmonary bypass surgery. Secondary objectives were frequency, type, and timing of post-operative infection related to the risk adjustment for congenital heart surgery score. This 3-year single-centre retrospective cohort study in a paediatric cardiac ICU analysed 191 infants accounting for 235 episodes of CPBP surgery. Primary outcome was kinetics of CRP in the first 28 days after CPBP surgery in infected and non-infected patients. We observed 22 infectious episodes in the early and 34 in the late post-operative period. CRP kinetics in the early post-operative period did not accurately differentiate between infected and non-infected patients. In the late post-operative period, infected infants displayed significantly higher CRP values with a median of 7.91 (1.64-22.02) and 6.92 mg/dl (1.92-19.65) on days 2 and 3 compared to 4.02 (1.99-15.9) and 3.72 mg/dl (1.08-9.72) in the non-infection group. Combining CRP on days 2 and 3 after suspicion of infection revealed a cut-off of 9.47 mg/L with an acceptable predictive accuracy of 76%. In neonates and infants, CRP kinetics is not useful to predict infection in the first 72 hours after CPBP surgery due to the inflammatory response. However, in the late post-operative period, CRP is a valuable adjunctive diagnostic test in conjunction with clinical presentation and microbiological diagnostics.

An Improved Method for Rapid Detection of Mycobacterium abscessus Complex Based on Species-Specific Lipid Fingerprint by Routine MALDI-TOF.

Rapid diagnostics of bacterial infection is the key to successful recovery and eradication of the disease. Currently, identification of bacteria is based on the detection of highly abundant proteins, mainly ribosomal proteins, by routine MALDI-TOF mass spectrometry. However, relying solely on proteins is limited in subspecies typing for some pathogens. This is the case for, for example, the mycobacteria belonging to the Mycobacterium abscessus (MABS) complex, which is classified into three subspecies, namely, M. abscessus subsp. abscessus, M. abscessus subsp. bolletii, and M. abscessus subsp. massiliense. Being able to detect bacteria accurately and rapidly at the subspecies level could not only reliably identify the pathogen causing the disease but also enable better antibiotic stewardship. For instance, M. abscessus subsp. abscessus and M. abscessus subsp. bolletii possess a functional erm41 (erythromycin ribosomal methylation gene 41) gene, whilst M. abscessus subsp. massiliense does not, resulting in differences in macrolide antibiotic (e.g., clarithromycin and azithromycin) susceptibilities. This presents a challenge for physicians when designing an appropriate treatment regimen. To address this challenge, in addition to proteins, species-specific lipids have now been considered as a game changer in clinical microbiology diagnostics. However, their extraction can be time-consuming, and analysis requires the use of apolar toxic organic solvents (e.g., chloroform). Here, we present a new method to accurately detect species and subspecies, allowing the discrimination of the mycobacteria within the MABS complex and relying on the use of ethanol. We found that a combination of the matrix named super-DHB with 25% ethanol with a bacterial suspension at McFarland 20 gave robust and reproducible data, allowing the discrimination of the bacteria within the MABS complex strains tested in this study (n = 9). Further investigations have to be conducted to validate the method on a larger panel of strains for its use in diagnostic laboratories.

Quo vadis clinical diagnostic microbiology?

Hospital-acquired infections caused by antibiotic-resistant opportunistic pathogens are on the rise worldwide and represent one of the greatest challenges to modern medicine. Infections due to antibiotic-resistant pathogens cause suffering, incapacity and death, and impose an enormous financial burden both on healthcare systems and on society in general. In 2019, the WHO estimated that each year 700 000 deaths are a direct consequence of multidrug-resistant infections [1].

Performance of a loop-mediated isothermal amplification assay (Isoplex CRE-ART) to detect common carbapenemase-encoding genes in Gram-negative bacteria.

Carbapenem-resistant Gram-negative bacteria (CR-GNB) are a major source of nosocomial infections worldwide. In this study, the ability of a loop-mediated isothermal amplification (LAMP)-based method (Isoplex CRE-ART) to rapidly detect carbapenemase-encoding genes bla OXA-48-like, bla OXA-23-like, bla OXA-24-like, bla KPC, bla VIM, bla NDM and bla IMP in 231 carbapenem-resistant Enterobacterales, Pseudomonas aeruginosa and Acinetobacter baumannii isolates was investigated. The accuracy of the LAMP test was compared to results of molecular isolate characterization using a Laboratory Developed Test multiplex carbapenemase PCR assay. The LAMP test correctly identified the presence of on-panel carbapenemases with a sensitivity of 99.16 % [95 % confidence interval (CI): 95.39-99.96 %] and a specificity of 98.21 % (95 % CI: 93.72-99.68 %) in 60 min. Our findings suggest that the Isoplex CRE-ART assay is able to rapidly identify carbapenemase genes in CR-GNB and improves options for pathogen characterization in the context of clinical microbiological and infection control diagnostics.

Detection of Colistin Resistance in Carbapenem Resistant Enterobacteriaceae by Reference Broth Microdilution and Comparative Evaluation of Three Other Methods.

Objective Challenges in susceptibility testing of colistin along with increase in the prevalence of colistin-resistant carbapenemase-producing Enterobacteriaceae (CRE) pathogens needs addressal. Evaluation of user-friendly methods is necessary as an alternative to broth microdilution (BMD), the reference susceptibility testing method, for routine implementation in diagnostic clinical microbiology laboratories. Genotypic detection of the plasmid-mediated colistin resistance is also needed for infection control purposes. Materials and Methods Colistin susceptibility of 200 nonduplicate clinical CRE isolates from December 2017 to June 2019 was determined by BMD, agar dilution (AD), E test, and rapid polymyxin NP test and interpreted as per the European Committee on Antimicrobial Susceptibility Testing. The results of AD, E test, and NP test were compared with that of BMD, considering minimal inhibitory concentration (MIC) ≤ 2 µg/mL as susceptible and > 2 µg/mL as resistant. Presence of any plasmid-mediated colistin resistance (mcr-1 and 2) was evaluated in 27 colistin-resistant CRE isolates by polymerase chain reaction. Statistical Analysis Performance of different phenotypic methods was analyzed by comparing MIC results of AD and E test with that of reference BMD method. Agreement between BMD and the other two methods was expressed in terms of categorical agreement and essential agreement. Errors were expressed as very major error (VME: false-susceptible) and major error (ME: false-resistance) by AD/E test. VME and ME of 3% disagreement were considered unacceptable. Results Colistin resistance was found in 27 (13.5%) isolates by BMD method. The VME rates of both AD (11%) and E test (37%) could not meet the Clinical and Laboratory Standards Institute recommendation (< 3% VME rate is acceptable) as alternative tests to the reference BMD. Colistin NP test showed sensitivity and specificity of 85% and 98%, respectively. The percentage discordant result in NP test was highest in Enterobacter spp. (17%). None of the 27 colistin resistant isolates showed presence of mcr-1 and mcr-2 genes. Conclusion High VME rate in AD and E tests precludes their use as alternatives to BMD for colistin susceptibility testing. NP test with moderate sensitivity but excellent specificity can be a good alternative for testing colistin susceptibility in CRE isolates, except in Enterobacter spp. Absence of mcr-1 and mcr-2 gene necessitates the exploration of other mechanisms of colistin resistance.

Development of a multiplex real-time PCR assay for the simultaneous detection of four bacterial pathogens causing pneumonia.

Classification of clinical symptoms and diagnostic microbiology are essential to effectively employ antimicrobial therapy for lower respiratory tract infections (LRTIs) in a timely manner. Empirical antibiotic treatment without microbial identification hinders the selective use of narrow-spectrum antibiotics and effective patient treatment. Thus, the development of rapid and accurate diagnostic procedures that can be readily adopted by the clinic is necessary to minimize non-essential or excessive use of antibiotics and accelerate patient recovery from LRTI-induced damage. We developed and validated a multiplex real-time polymerase chain reaction (mRT-PCR) assay with good analytical performance and high specificity to simultaneously detect four bacterial pathogens causing pneumonia: Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus, and Moraxella catarrhalis. The analytical performance of mRT-PCR against target pathogens was evaluated by the limit of detection (LOD), specificity, and repeatability. Two hundred and ten clinical specimens from pneumonia patients were processed using an automatic nucleic acid extraction system for the "respiratory bacteria four" (RB4) mRT-PCR assay, and the results were directly compared to references from bacterial culture and/or Sanger sequencing. The RB4 mRT-PCR assay detected all target pathogens from sputum specimens with a coefficient of variation ranging from 0.29 to 1.71 and conservative LOD of DNA corresponding to 5 × 102 copies/reaction. The concordance of the assay with reference-positive specimens was 100%, and additional bacterial infections were detected from reference-negative specimens. Overall, the RB4 mRT-PCR assay showed a more rapid turnaround time and higher performance that those of reference assays. The RB4 mRT-PCR assay is a high-throughput and reliable tool that assists decision-making assessment and outperforms other standard methods. This tool supports patient management by considerably reducing the inappropriate use of antibiotics.

ProkEvo: an automated, reproducible, and scalable framework for high-throughput bacterial population genomics analyses.

Whole Genome Sequence (WGS) data from bacterial species is used for a variety of applications ranging from basic microbiological research, diagnostics, and epidemiological surveillance. The availability of WGS data from hundreds of thousands of individual isolates of individual microbial species poses a tremendous opportunity for discovery and hypothesis-generating research into ecology and evolution of these microorganisms. Flexibility, scalability, and user-friendliness of existing pipelines for population-scale inquiry, however, limit applications of systematic, population-scale approaches. Here, we present ProkEvo, an automated, scalable, reproducible, and open-source framework for bacterial population genomics analyses using WGS data. ProkEvo was specifically developed to achieve the following goals: (1) Automation and scaling of complex combinations of computational analyses for many thousands of bacterial genomes from inputs of raw Illumina paired-end sequence reads; (2) Use of workflow management systems (WMS) such as Pegasus WMS to ensure reproducibility, scalability, modularity, fault-tolerance, and robust file management throughout the process; (3) Use of high-performance and high-throughput computational platforms; (4) Generation of hierarchical-based population structure analysis based on combinations of multi-locus and Bayesian statistical approaches for classification for ecological and epidemiological inquiries; (5) Association of antimicrobial resistance (AMR) genes, putative virulence factors, and plasmids from curated databases with the hierarchically-related genotypic classifications; and (6) Production of pan-genome annotations and data compilation that can be utilized for downstream analysis such as identification of population-specific genomic signatures. The scalability of ProkEvo was measured with two datasets comprising significantly different numbers of input genomes (one with ~2,400 genomes, and the second with ~23,000 genomes). Depending on the dataset and the computational platform used, the running time of ProkEvo varied from ~3-26 days. ProkEvo can be used with virtually any bacterial species, and the Pegasus WMS uniquely facilitates addition or removal of programs from the workflow or modification of options within them. To demonstrate versatility of the ProkEvo platform, we performed a hierarchical-based population structure analyses from available genomes of three distinct pathogenic bacterial species as individual case studies. The specific case studies illustrate how hierarchical analyses of population structures, genotype frequencies, and distribution of specific gene functions can be integrated into an analysis. Collectively, our study shows that ProkEvo presents a practical viable option for scalable, automated analyses of bacterial populations with direct applications for basic microbiology research, clinical microbiological diagnostics, and epidemiological surveillance.

Detection of Species-Specific Lipids by Routine MALDI TOF Mass Spectrometry to Unlock the Challenges of Microbial Identification and Antimicrobial Susceptibility Testing.

MALDI-TOF mass spectrometry has revolutionized clinical microbiology diagnostics by delivering accurate, fast, and reliable identification of microorganisms. It is conventionally based on the detection of intracellular molecules, mainly ribosomal proteins, for identification at the species-level and/or genus-level. Nevertheless, for some microorganisms (e.g., for mycobacteria) extensive protocols are necessary in order to extract intracellular proteins, and in some cases a protein-based approach cannot provide sufficient evidence to accurately identify the microorganisms within the same genus (e.g., Shigella sp. vs E. coli and the species of the M. tuberculosis complex). Consequently lipids, along with proteins are also molecules of interest. Lipids are ubiquitous, but their structural diversity delivers complementary information to the conventional protein-based clinical microbiology matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) based approaches currently used. Lipid modifications, such as the ones found on lipid A related to polymyxin resistance in Gram-negative pathogens (e.g., phosphoethanolamine and aminoarabinose), not only play a role in the detection of microorganisms by routine MALDI-TOF mass spectrometry but can also be used as a read-out of drug susceptibility. In this review, we will demonstrate that in combination with proteins, lipids are a game-changer in both the rapid detection of pathogens and the determination of their drug susceptibility using routine MALDI-TOF mass spectrometry systems.

Oxford nanopore sequencing in clinical microbiology and infection diagnostics.

Extended turnaround times and large economic costs hinder the usage of currently applied screening methods for bacterial pathogen identification (ID) and antimicrobial susceptibility testing. This review provides an overview of current detection methods and their usage in a clinical setting. Issues of timeliness and cost could soon be circumvented, however, with the emergence of detection methods involving single molecule sequencing technology. In the context of bringing diagnostics closer to the point of care, we examine the current state of Oxford Nanopore Technologies (ONT) products and their interaction with third-party software/databases to assess their capabilities for ID and antimicrobial resistance (AMR) prediction. We outline and discuss a potential diagnostic workflow, enumerating (1) rapid sample prep kits, (2) ONT hardware/software and (3) third-party software and databases to improve the cost, accuracy and turnaround times for ID and AMR. Multiple studies across a range of infection types support that the speed and accuracy of ONT sequencing is now such that established ID and AMR prediction tools can be used on its outputs, and so it can be harnessed for near real time, close to the point-of-care diagnostics in common clinical circumstances.