Recent Advances and Ongoing Challenges in the Diagnosis of Microbial Infections by MALDI-TOF Mass Spectrometry

Discriminatory power of MALDI-TOF MS protein profiling analysis of pork meat and meat products

Forty different sample preparation methods were tested to obtain the most informative MALDI-TOF MS protein profiles of pork meat. Extraction by 25% formic acid with the assistance of zirconia-silica beads followed by defatting by methanol:chloroform mixture (1:1, v/v) and deposition by using the layer-by-layer method was determined as the optimum sample preparation protocol. The discriminatory power of the method was then examined on samples of pork meat and meat products. The method was able to discriminate between selected salami based on the production method and brand and was able to monitor the ripening process in salami. However, it was not able to differentiate between different brands of pork ham or closely located parts of pork meat. In the latter case, a more comprehensive analysis using LC-MS/MS was used to assess the differences in protein abundance and their relation to the outputs of MALDI - TOF MS profiling.

Pathogens in FRI - Do bugs matter? - An analysis of FRI studies to assess your enemy

Fracture-related infection (FRI) is a devasting complication for both patients and their treating Orthopaedic surgeon that can lead to loss of limb function or even amputation. The unique and unpredictable features of FRI make its diagnosis and treatment a significant challenge. It has substantial morbidity and financial implications for patients, their families and healthcare providers. In this article, we perform an in-depth and comprehensive review of FRI through recent and seminal literature to highlight evolving definitions, diagnostic and treatment approaches, focusing on common pathogens such as Staphylococcus aureus, polymicrobial infections and multi-drug-resistant organisms (MDRO). Furthermore, multiple resistance mechanisms and adaptations for microbial survival are discussed, as well as modern evidence-based medical and surgical advancements in treatment strategies in combating FRI.

Applying Machine Learning for Antibiotic Development and Prediction of Microbial Resistance

Antimicrobial resistance (AMR) poses a serious threat to human health worldwide. It is now more challenging than ever to introduce a potent antibiotic to the market considering rapid emergence of antimicrobial resistance, surpassing the rate of antibiotic drug discovery. Hence, new approaches need to be developed to accelerate the rate of drug discovery process and meet the demands for new antibiotics, while reducing the cost of their development. Machine learning holds immense promise of becoming a useful tool, especially since in the last two decades, exponential growth has occurred in computational power and biological big data analytics. Recent advancements in machine learning algorithms for drug discovery have provided significant clues for potential antibiotic classes. Apart from discovery of new scaffolds, the machine learning protocols will significantly impact prediction of AMR patterns and drug metabolism. In this review, we outline power of machine learning in antibiotic drug discovery, metabolic fate, and AMR prediction to support researchers engaged and interested in this field.

Identification of environmental Actinobacteria in buildings by means of chemotaxonomy, 16S rRNA sequencing, and MALDI-TOF MS

Actinobacteria are abundant in soil and other environmental ecosystems and are also an important part of the human microbiota. Hence, they can also be detected in indoor environments and on building materials, where actinobacterial proliferation on damp materials can indicate moisture damage. The aim of this study was to evaluate the matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) for the identification of 28 environmental strains of Actinobacteria isolated from building materials and indoor and outdoor air samples, mainly collected in the context of moisture damage investigations in buildings in Finland. The 16S rRNA gene sequencing and chemotaxonomic analyses were performed, and results were compared with the MALDI-TOF MS Biotyper identification. Using 16S rRNA gene sequencing, all isolates were identified on the species or genus level and were representatives of Streptomyces, Nocardia, and Pseudonocardia genera. Based on MALDI-TOF MS analysis, initially, 11 isolates were identified as Streptomyces spp. and 1 as Nocardia carnea with a high identification score. After an upgrade in the MALDI-TOF MS in-house database and re-evaluation of mass spectra, 13 additional isolates were identified as Nocardia, Pseudonocardia, and Streptomyces. MALDI-TOF MS has the potential in environmental strain identification; however, the standard database needs to be considerably enriched by environmental Actinobacteria representatives.

IMPORTANCE

The manuscript addresses the challenges in identifying environmental bacteria using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) Biotyper-based protein profiling. The matter of the studies-actinobacterial strains-has been isolated mostly from building materials that originated from a confirmed moisture-damaged situation. Polyphasic taxonomy, 16S RNA gene sequencing, and MALDI-TOF mass spectrometry were applied for identification purposes. In this experimental paper, a few important facts are highlighted. First, Actinobacteria are abundant in the natural as well as built environment, and their identification on the species and genus levels is difficult and time-consuming. Second, MALDI-TOF MS is an effective tool for identifying bacterial environmental strains, and in parallel, continuous enrichment of the proteomics mass spectral databases is necessary for proper identification. Third, the chemical approach aids in the taxonomical inquiry of Actinobacteria environmental strains.

The influence of growth time on the identification of Bartonella henselae strains by MALDI-TOF mass spectrometry

Bartonella spp. are bacteria responsible for neglected diseases worldwide. Bartonella henselae is the species most associated with human infections. It is associated with a large spectrum of clinical manifestations and is potentially fatal. The identification of Bartonella spp. is considered a challenge in clinical routine. These bacteria are fastidious, and the time required to isolate them varies from one to six weeks. MALDI-TOF mass spectrometry has emerged as an application for research on Bartonella spp. , and has still been little explored. We investigated whether three different B. henselae strains with different growth times-14 and 28 days-could be correctly identified by MALDI-TOF mass spectra fingerprint comparison and matching. We found that the spectra from strains with different growth times do not match each other, leading to misidentification. We suggest creating database entries with multiple spectra from strains with different growth times to increase the chances of accurate identification of Bartonella spp. by MALD-TOF MS.

Clinical Impact of Rapid Bacterial Microbiological Identification with the MALDI-TOF MS

Rapid microbiological reports to clinicians are related to improved clinical outcomes. We conducted a 3-year quasi-experimental design, specifically a pretest-posttest single group design in a university medical center, to evaluate the clinical impact of rapid microbiological identification information using MALDI-TOF MS on optimizing antibiotic prescription. A total of 363 consecutive hospitalized patients with bacterial infections were evaluated comparing a historical control group (CG) (n = 183), in which the microbiological information (bacterial identification and antibiotic susceptibility) was reported jointly to the clinician between 18:00 h and 22:00 h of the same day and a prospective intervention group (IG) (n = 180); the bacterial identification information was informed to the clinician as soon as it was available between 12:00 h and 14:00 h and the antibiotic susceptibility between 18:00 h and 22:00 h). We observed, in favor of IG, a statistically significant decrease in the information time (11.44 h CG vs. 4.48 h IG (p < 0.01)) from the detection of bacterial growth in the culture medium to the communication of identification. Consequently, the therapeutic optimization was improved by introducing new antibiotics in the 10-24 h time window (p = 0.05) and conversion to oral route (p = 0.01). Additionally, we observed a non-statistically significant decrease in inpatient mortality (global, p = 0.15; infection-related, p = 0.21) without impact on hospital length of stay. In conclusion, the rapid communication of microbiological identification to clinicians reduced reporting time and was associated with early optimization of antibiotic prescribing without worsening clinical outcomes.

A risk assessment framework for multidrug-resistant Staphylococcus aureus using machine learning and mass spectrometry technology

The emergence of multidrug-resistant bacteria is a critical global crisis that poses a serious threat to public health, particularly with the rise of multidrug-resistant Staphylococcus aureus. Accurate assessment of drug resistance is essential for appropriate treatment and prevention of transmission of these deadly pathogens. Early detection of drug resistance in patients is critical for providing timely treatment and reducing the spread of multidrug-resistant bacteria. This study aims to develop a novel risk assessment framework for S. aureus that can accurately determine the resistance to multiple antibiotics. The comprehensive 7-year study involved ˃20 000 isolates with susceptibility testing profiles of six antibiotics. By incorporating mass spectrometry and machine learning, the study was able to predict the susceptibility to four different antibiotics with high accuracy. To validate the accuracy of our models, we externally tested on an independent cohort and achieved impressive results with an area under the receiver operating characteristic curve of 0. 94, 0.90, 0.86 and 0.91, and an area under the precision-recall curve of 0.93, 0.87, 0.87 and 0.81, respectively, for oxacillin, clindamycin, erythromycin and trimethoprim-sulfamethoxazole. In addition, the framework evaluated the level of multidrug resistance of the isolates by using the predicted drug resistance probabilities, interpreting them in the context of a multidrug resistance risk score and analyzing the performance contribution of different sample groups. The results of this study provide an efficient method for early antibiotic decision-making and a better understanding of the multidrug resistance risk of S. aureus.

Nano-Biotechnology for Bacteria Identification and Potent Anti-bacterial Properties: A Review of Current State of the Art

Sepsis is a critical disease caused by the abrupt increase of bacteria in human blood, which subsequently causes a cytokine storm. Early identification of bacteria is critical to treating a patient with proper antibiotics to avoid sepsis. However, conventional culture-based identification takes a long time. Polymerase chain reaction (PCR) is not so successful because of the complexity and similarity in the genome sequence of some bacterial species, making it difficult to design primers and thus less suitable for rapid bacterial identification. To address these issues, several new technologies have been developed. Recent advances in nanotechnology have shown great potential for fast and accurate bacterial identification. The most promising strategy in nanotechnology involves the use of nanoparticles, which has led to the advancement of highly specific and sensitive biosensors capable of detecting and identifying bacteria even at low concentrations in very little time. The primary drawback of conventional antibiotics is the potential for antimicrobial resistance, which can lead to the development of superbacteria, making them difficult to treat. The incorporation of diverse nanomaterials and designs of nanomaterials has been utilized to kill bacteria efficiently. Nanomaterials with distinct physicochemical properties, such as optical and magnetic properties, including plasmonic and magnetic nanoparticles, have been extensively studied for their potential to efficiently kill bacteria. In this review, we are emphasizing the recent advances in nano-biotechnologies for bacterial identification and anti-bacterial properties. The basic principles of new technologies, as well as their future challenges, have been discussed.

Epidemiological cut-off values for Vibrio anguillarum MIC and disc diffusion data generated by standardised methods

This work aims to generate the data needed to set epidemiological cut-off values for minimum inhibitory concentration (MIC) and disc-diffusion zone measurements of Vibrio anguillarum. A total of 261 unique isolates were tested, applying standard methods specifying incubation at 28°C for 24-28 h. Aggregated MIC distributions for a total of 247 isolates were determined in 9 laboratories for 11 agents. Data aggregations of the disc zone for the 10 agents analysed contained between 157 and 218 observations made by 4 to 7 laboratories. Acceptable ranges for quality control (QC) reference strains were available for 7 agents and the related multi-laboratory aggregated data were censored, excluding the data of a laboratory that failed to meet QC requirements. Statistical methods were applied to calculate epidemiological cut-off values. Cut-off values for MIC data were calculated for florfenicol (≤1 µg ml-1), gentamicin (≤4 µg ml-1), oxytetracycline (≤0.25 µg ml-1) and trimethoprim/sulfamethoxazole (≤0.125/2.38 µg ml-1). The cut-off values for disc zone data were calculated for enrofloxacin (≥29 mm), florfenicol (≥27 mm), gentamicin (≥19 mm), oxolinic acid (≥24 mm), oxytetracycline (≥24 mm) and trimethoprim/sulfamethoxazole (≥26 mm). MIC and disc-diffusion zone data for the other agents where not supported by QC, thus yielding only provisional cut-off values (meropenem, ceftazidime). Regardless of whether QC is available, some of the aggregated MIC distributions (enrofloxacin, oxolinic acid), disc zone (sulfamethoxazole), and MIC and disc-diffusion distributions (ampicillin, chloramphenicol) did not meet the statistical requirements. The data produced will be submitted to the Clinical Laboratory Standards Institute for their consideration in setting international consensus epidemiological cut-off values.

MALDI-TOF MS Indirect Beta-Lactamase Detection in Ampicillin-Resistant Haemophilus influenzae

Rapid identification of beta-lactamase-producing strains of Haemophilus influenzae plays key role in diagnostics in clinical microbiology. Therefore, the aim of this study was the rapid determination of beta-lactamase's presence in H. influenzae isolates via indirect detection of degradation ampicillin products using MALDI-TOF MS. H. influenzae isolates were subjected to antibiotic resistance testing using disk diffusion and MIC methodologies. Beta-lactamase activity was tested using MALDI-TOF MS, and results were compared to spectral analysis of alkaline hydrolysis. Resistant and susceptible strains of H. influenzae were distinguished, and strains with a high MIC level were identified as beta-lactamase-producing. Results indicate that MALDI-TOF mass spectrometry is also suitable for the rapid identification of beta-lactamase-producing H. influenzae. This observation and confirmation can accelerate identification of beta-lactamase strains of H. influenzae in clinical microbiology, which can have an impact on health in general.

Development of diagnostic tests for pathogen identification and detection of antimicrobial resistance on WHO global priority pathogens using modular real-time nucleic acid amplification test

BACKGROUND

Concerns regarding antimicrobial resistance (AMR) have resulted in the World Health Organization (WHO) designating so-called global priority pathogens (GPPs). However, little discussion has focused on the diagnosis of GPPs. To enable the simultaneous identification of pathogens and AMR, we developed a modular real-time nucleic acid amplification test (MRT-NAAT).

METHODS

Sequence-specific primers for each modular unit for MRT-NAAT pathogen identification and AMR sets were designed. The composition of the reaction mixture and the real-time PCR program were unified irrespective of primer type so to give MRT-NAAT modularity. Standard strains and clinical isolates were used to evaluate the performance of MRT-NAAT by real-time PCR and melting curve analysis. Probit analysis for the MRT-NAAT pathogen identification set was used to assess the limit of detection (LoD).

RESULTS

The MRT-NAAT pathogen identification set was made up of 15 modular units 109-199 bp in product size and with a T_ms of 75.5-87.5 °C. The LoD was < 15.548 fg/μL, and nine modular units successfully detected the target pathogens. The MRT-NAAT AMR set included 24 modular units 65-785 bp in product size with a T_ms of 75.5-87.5 °C; it showed high performance for detecting GPP target genes and variants.

CONCLUSIONS

MRT-NAAT enables pathogen identification and AMR gene detection and is time-effective. By unifying the reaction settings of each modular unit, the modularity where combinations of primers can be used according to need could be achieved. This would greatly help in reflecting the researcher's need and the AMR status of a certain region while successfully detecting pathogens and AMR genes.

Human Milk Sodium and Potassium as Markers of Mastitis in Mothers of Preterm Infants

Introduction: This prospective longitudinal study examined changes in milk sodium concentration (Na) and sodium:potassium ratio (Na:K), microbiological culture, milk production, and breast health in relation to mastitis after preterm birth. Methods: We studied women who gave birth at 29-34 weeks of gestation in a tertiary obstetric hospital in Perth, Western Australia. Milk samples, 24-hour milk production, and breast health data were collected every second day to day 10 postpartum, then every third day until infant discharge from the neonatal unit. Milk Na and K were measured at point of care (POC) using handheld ion selective meters, and Na:K calculated. Cultures were performed on postnatal days 8, 13, and every 6 days thereafter. For episodes of mastitis, milk was cultured at onset, and Na and Na:K measured daily until resolution. Women were followed up at 4 and 8 weeks postpartum. Results: In a sample of 44 women, 4 mastitis cases were detected in 3 women during their infants' neonatal stay; all had elevated milk Na and Na:K that resolved within 48 hours; 2/4 experienced reduced milk production and 1/4 had heavy growth of Staphylococcus epidermidis. A further 2 mastitis cases were reported in 39 women followed up to 8 weeks postpartum. Four women had elevated milk Na and Na:K without clinical signs of mastitis; three also had reduced milk production. Conclusions: POC testing of milk Na and/or Na:K may offer a useful indicator of breast health. Mastitis may cause an acute reduction in milk production regardless of the presence of culture-positive infection.

Wound swabs versus biopsies to detect methicillin resistant Staphylococcus aureus in experimental equine wounds

OBJECTIVE

To compare: (1) the load and diversity of cultivatable bacterial species isolated from tissue biopsies with cultures from surface swabs, and (2) the ability of each technique to detect methicillin-resistant Staphylococcus aureus (MRSA) in a model of MRSA-infected equine wounds.

STUDY DESIGN

Experimental in vivo study.

ANIMALS

Three light-breed adult horses.

METHODS

Four 2.5 × 2.5 cm full-thickness skin wounds were created on the dorsolateral aspect of each forelimb. Five days later, each wound was inoculated with a pure culture of MRSA (ATCC 43300). One hundred microlitres of 0, 5 × 108 , 5 × 109 or 5 × 1010 colony forming units (CFU)/ml was used to inoculate each wound. Surface swabs (Levine technique) and tissue biopsy samples (3 mm punch biopsy) were obtained at 2, 7, 14, and 21 days after inoculation. Quantitative aerobic culture was performed using routine clinical techniques.

RESULTS

A similar bacterial profile was identified from the culture of each wound-sampling technique and there was moderate correlation (R = 0.49, P < .001) between the bacterial bioburdens. Agreement was fair (κ = 0.31; 95% CI, 0.129-0.505) between the sampling techniques in identification of MRSA. Methicillin-resistant Staphylococcus aureus was isolated more frequently (P = .016) from cultures of tissue biopsies (79%; 76/96) than from surface swabs (62%; 60/96).

CONCLUSION

Bacterial load and diversity did not differ between sampling techniques but MRSA was detected more often from the cultures of tissue biopsies.

CLINICAL SIGNIFICANCE

Tissue biopsy should be preferred to culture swab in wounds where MRSA is suspected.

Accurate and fast identification of minimally prepared bacteria phenotypes using Raman spectroscopy assisted by machine learning

The worldwide increase of antimicrobial resistance (AMR) is a serious threat to human health. To avert the spread of AMR, fast reliable diagnostics tools that facilitate optimal antibiotic stewardship are an unmet need. In this regard, Raman spectroscopy promises rapid label- and culture-free identification and antimicrobial susceptibility testing (AST) in a single step. However, even though many Raman-based bacteria-identification and AST studies have demonstrated impressive results, some shortcomings must be addressed. To bridge the gap between proof-of-concept studies and clinical application, we have developed machine learning techniques in combination with a novel data-augmentation algorithm, for fast identification of minimally prepared bacteria phenotypes and the distinctions of methicillin-resistant (MR) from methicillin-susceptible (MS) bacteria. For this we have implemented a spectral transformer model for hyper-spectral Raman images of bacteria. We show that our model outperforms the standard convolutional neural network models on a multitude of classification problems, both in terms of accuracy and in terms of training time. We attain more than 96% classification accuracy on a dataset consisting of 15 different classes and 95.6% classification accuracy for six MR-MS bacteria species. More importantly, our results are obtained using only fast and easy-to-produce training and test data.

High-Throughput 16 S rRNA Gene Sequencing Reveals Bacterial Diversity of Infant Formula Production Line Samples in Spring and Summer

The trend of low breastfeeding rates increases the demand for infant milk formula (IMF) worldwide, but the use of IMF may be one of the causes of bacterial infections in infants. Complete sterility in the whole production line of IMF cannot be guaranteed; therefore, it is necessary to closely monitor the microbial content in the process. In the present study, an IMF powder production line based on the wet mixing process was sampled at 27 suspicious points in spring and summer to analyze the bacterial diversity by high-throughput sequencing. We found that 70 and 69 different bacterial phyla were present in spring and summer samples, respectively, with Proteobacteria and Firmicutes being the dominant phyla (>80% relative abundance). Moreover, 13 dominant genera each were present in spring (e. g., Pseudomonas and Lactococcus) and summer (e. g., Pseudomonas, Bacillus, and Streptococcus). Samples associated with workers showed higher bacterial species diversity (Shannon index) and richness (Chao1 index) in summer than in spring. The bacterial community composition showed high similarity between liquid milk after pasteurization and concentrated milk after evaporation. The potential bacterial pathogens were identified as Pseudomonas aeruginosa in spring and Acinetobacter baumannii in summer. Through retrospective analysis of the two opportunistic pathogens identified, it was found that the workshop environment was the potential contamination point in spring, whereas the auxiliary ingredients were the potential source of contamination in summer. The results highlight the effect of season on bacterial diversity associated with the production process of IMF and are useful in controlling the microbial quality and safety of infant dairy products.

Skeletal infections: microbial pathogenesis, immunity and clinical management

Osteomyelitis remains one of the greatest risks in orthopaedic surgery. Although many organisms are linked to skeletal infections, Staphylococcus aureus remains the most prevalent and devastating causative pathogen. Important discoveries have uncovered novel mechanisms of S. aureus pathogenesis and persistence within bone tissue, including implant-associated biofilms, abscesses and invasion of the osteocyte lacuno-canalicular network. However, little clinical progress has been made in the prevention and eradication of skeletal infection as treatment algorithms and outcomes have only incrementally changed over the past half century. In this Review, we discuss the mechanisms of persistence and immune evasion in S. aureus infection of the skeletal system as well as features of other osteomyelitis-causing pathogens in implant-associated and native bone infections. We also describe how the host fails to eradicate bacterial bone infections, and how this new information may lead to the development of novel interventions. Finally, we discuss the clinical management of skeletal infection, including osteomyelitis classification and strategies to treat skeletal infections with emerging technologies that could translate to the clinic in the future.

MALDI-TOF Mass Spectrometry Analysis and Human Post-Mortem Microbial Community: A Pilot Study

Introduction: The human post-mortem microbiome (HPM) plays a major role in the decomposition process. Successional changes in post-mortem bacterial communities have been recently demonstrated using high throughput metagenomic sequencing techniques, showing great potential as a post-mortem interval (PMI) predictor. The aim of this study is to verify the application of the mass spectrometry technique, better known as MALDI-TOF MS (matrix-assisted laser desorption/ionization time-of-flight mass spectrometry), as a cheap and quick method for microbe taxonomic identification and for studying the PM microbiome. Methods: The study was carried out on 18 human bodies, ranging from 4 months to 82 years old and with a PMI range from 24 h up to 15 days. The storage time interval in the coolers was included in the final PMI estimates. Using the PMI, the sample study was divided into three main groups: seven cases with a PMI < 72 h; six cases with a PMI of 72−168 h and five cases with a PMI > 168 h. For each body, microbiological swabs were sampled from five external anatomical sites (eyes, ears, nose, mouth, and rectum) and four internal organs (brain, spleen, liver, and heart). Results: The HPM became increasingly different from the starting communities over time in the internal organs as well as at skin sites; the HPM microbiome was mostly dominated by Firmicutes and Proteobacteria phyla; and a PM microbial turnover existed during decomposition, evolving with the PMI. Conclusions: MALDI-TOF is a promising method for PMI estimation, given its sample handling, good reproducibility, and high speed and throughput. Although several intrinsic and extrinsic factors can affect the structure of the HPM, MALDI-TOF can detect the overall microbial community turnover of most prevalent phyla during decomposition. Limitations are mainly related to its sensitivity due to the culture-dependent method and bias in the identification of new isolates.

Large-Scale Samples Based Rapid Detection of Ciprofloxacin Resistance in Klebsiella pneumoniae Using Machine Learning Methods

Klebsiella pneumoniae is one of the most common causes of hospital- and community-acquired pneumoniae. Resistance to the extensively used quinolone antibiotic, such as ciprofloxacin, has increased in Klebsiella pneumoniae, which leads to the increase in the risk of initial antibiotic selection for Klebsiella pneumoniae treatment. Rapid and precise identification of ciprofloxacin-resistant Klebsiella pneumoniae (CIRKP) is essential for clinical therapy. Nowadays, matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is another approach to discover antibiotic-resistant bacteria due to its shorter inspection time and lower cost than other current methods. Machine learning methods are introduced to assist in discovering significant biomarkers from MALDI-TOF MS data and construct prediction models for rapid antibiotic resistance identification. This study examined 16,997 samples taken from June 2013 to February 2018 as part of a longitudinal investigation done by Change Gung Memorial Hospitals (CGMH) at the Linkou branch. We applied traditional statistical approaches to identify significant biomarkers, and then a comparison was made between high-importance features in machine learning models and statistically selected features. Large-scale data guaranteed the statistical power of selected biomarkers. Besides, clustering analysis analyzed suspicious sub-strains to provide potential information about their influences on antibiotic resistance identification performance. For modeling, to simulate the real antibiotic resistance predicting challenges, we included basic information about patients and the types of specimen carriers into the model construction process and separated the training and testing sets by time. Final performance reached an area under the receiver operating characteristic curve (AUC) of 0.89 for support vector machine (SVM) and extreme gradient boosting (XGB) models. Also, logistic regression and random forest models both achieved AUC around 0.85. In conclusion, models provide sensitive forecasts of CIRKP, which may aid in early antibiotic selection against Klebsiella pneumoniae. The suspicious sub-strains could affect the model performance. Further works could keep on searching for methods to improve both the model accuracy and stability.

Application of Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry for the Rapid Identification of Yeast Species From Polar Regions

Protein profiling based on matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) has proved to be a powerful tool for yeast identification. However, it is rarely used in the identification of yeast isolates from polar regions, which may be due to the limited data available for the differentiation of polar yeast species. The present study constructed a supplementary database of MALDI-TOF MS, including 33 yeast species from the Arctic and Antarctica. These yeast species were used to assess the accuracy and practicality of MALDI-TOF MS-based identification compared to the ribosomal DNA [internal transcribed spacer (ITS) and large subunit (LSU) gene regions] sequencing identification. Their dendrogram based on main spectra profiles (MSPs) in the supplementary database was somewhat consistent with their phylogenetic tree. The accuracy of MALDI-TOF MS identification was also compared by the ethanol-formic acid extraction method and the on-plate extraction method. In addition, peptide markers of some yeast species (e.g., Glaciozyma, Phenoliferia, Mrakia, and Vishniacozyma) were identified. It is concluded that the MALDI-TOF MS method can differentiate some closely related yeast species from polar regions, thus is suitable for the identification of polar yeasts.

Multiplexed detection of bacterial nucleic acids using Cas13 in droplet microarrays

Rapid and accurate diagnosis of infections is fundamental to individual patient care and public health management. Nucleic acid detection methods are critical to this effort, but are limited either in the breadth of pathogens targeted or by the expertise and infrastructure required. We present here a high-throughput system that enables rapid identification of bacterial pathogens, bCARMEN, which utilizes: (1) modular CRISPR-Cas13-based nucleic acid detection with enhanced sensitivity and specificity; and (2) a droplet microfluidic system that enables thousands of simultaneous, spatially multiplexed detection reactions at nanoliter volumes; and (3) a novel preamplification strategy that further enhances sensitivity and specificity. We demonstrate bCARMEN is capable of detecting and discriminating 52 clinically relevant bacterial species and several key antibiotic resistance genes. We further develop a simple proof of principle workflow using stabilized reagents and cell phone camera optical readout, opening up the possibility of a rapid point-of-care multiplexed bacterial pathogen identification and antibiotic susceptibility testing.

Genomic Characterization of Imipenem- and Imipenem-Relebactam-Resistant Clinical Isolates of Pseudomonas aeruginosa

Pseudomonas aeruginosa is an opportunistic human pathogen and a major cause of nosocomial infections. The global spread of carbapenem-resistant strains is growing rapidly and has become a major public health challenge. Imipenem-relebactam (I/R) is a novel carbapenem-beta-lactamase inhibitor combination that can overcome carbapenem resistance. In this study, we aimed to understand the mechanism underlying resistance to imipenem and imipenem-relebactam. For this purpose, we performed a genomic comparison of 40 new clinical P. aeruginosa strains with different antibiotic sensitivity patterns as well as the presence/absence of carbapenemases. Results indicated the presence of a reduced flexible genome (15% total) mostly represented by phages and defense mechanisms against them, showing an important role in evolution and pathogenicity. We found a high diversity of antibiotic resistance genes grouped in small clusters mobilized via integrative and conjugative elements and facilitated by the high homologous recombination detected. Ortholog genes were found in several pathogenic strains from distantly related taxa in different mobile elements with a global distribution. The microdiversity found in those strains without carbapenemases did not reveal a clear pattern that could be associated with carbapenem resistance, suggesting multiple mechanisms of resistance in the core genome. Our results provide new insight into the dynamics and high genomic plasticity by which clinical strains of P. aeruginosa acquire resistance. This knowledge can be applied to other multidrug-resistant microbes to create predictive frameworks for assessing common molecular mechanisms of antibiotic resistance and integrated into new strategies for their prevention.

IMPORTANCE The growing emergence and spread of carbapenem-resistant pathogens worldwide exacerbate the clinical challenge of treating these infections. Given the importance of carbapenems for the treatment of infections caused by Pseudomonas aeruginosa, this study aimed to investigate the underlying genomic properties of the clinical isolates that exhibited resistance to imipenem and imipenem-relebactam. This information will enhance our ability to forecast traits of resistant strains and design reliable treatments against this important threat. Our results provide new insight into the dynamics and high genomic plasticity by which clinical strains of P. aeruginosa acquire resistance as well as offers a methodology that can be applied to many other opportunistic pathogens with broad antibiotic resistance.

Bacterial keratitis: identifying the areas of clinical uncertainty

Bacterial keratitis is a common corneal infection that is treated with topical antimicrobials. By the time of presentation there may already be severe visual loss from corneal ulceration and opacity, which may persist despite treatment. There are significant differences in the associated risk factors and the bacterial isolates between high income and low- or middle-income countries, so that general management guidelines may not be appropriate. Although the diagnosis of bacterial keratitis may seem intuitive there are multiple uncertainties about the criteria that are used, which impacts the interpretation of investigations and recruitment to clinical studies. Importantly, the concept that bacterial keratitis can only be confirmed by culture ignores the approximately 50% of cases clinically consistent with bacterial keratitis in which investigations are negative. The aetiology of these culture-negative cases is unknown. Currently, the estimation of bacterial susceptibility to antimicrobials is based on data from systemic administration and achievable serum or tissue concentrations, rather than relevant corneal concentrations and biological activity in the cornea. The provision to the clinician of minimum inhibitory concentrations of the antimicrobials for the isolated bacteria would be an important step forward. An increase in the prevalence of antimicrobial resistance is a concern, but the effect this has on disease outcomes is yet unclear. Virulence factors are not routinely assessed although they may affect the pathogenicity of bacteria within species and affect outcomes. New technologies have been developed to detect and kill bacteria, and their application to bacterial keratitis is discussed. In this review we present the multiple areas of clinical uncertainty that hamper research and the clinical management of bacterial keratitis, and we address some of the assumptions and dogma that have become established in the literature.

Investigation of effects of orthokeratology and povidone iodine disinfecting solution on the conjunctival microbiome using MALDI-TOF mass spectrometry

Purpose

To determine organisms present in the conjunctiva of children before and after orthokeratology lens wear, using MALDI-TOF mass spectrometry.

Methods

Conjunctival samples were collected from children aged 8-12 years (inclusive) at baseline and on three occasions over the first six months of orthokeratology treatment. All lenses were disinfected using the povidone iodine-based solution every day after use. Specimens were cultured and all isolated colonies were identified using MALDI-TOF mass spectrometry. Numbers of organisms and diversity were compared over the study period and the presence of any ocular pathogens noted and participants informed, where appropriate, to enhance their compliance with lens care routine.

Results

Organisms isolated from 76 children were generally similar to other studies employing culture methods. However, MALDI-TOF results yielded a wider range of species of micrococci and corynebacteria, as well as a few less frequently reported organisms. Only one culture yielded fungi. Ocular pathogens were only isolated from 9 subjects (4 before lens wear and 5 after lens wear), each on one occasion only. Diversity and numbers of organisms fell slowly over the period of the study, but the changes were not significant.

Conclusions

Lens wear did not affect the overall content of the ocular microbiome, but the diversity was somewhat reduced. The incidence of ocular pathogens was low, suggesting that risk of ocular infection was not substantially increased by orthokeratology treatment using a povidone-iodine disinfecting solution.

Recent Advances in the Use of Mesoporous Silica Nanoparticles for the Diagnosis of Bacterial Infections

Public awareness of infectious diseases has increased in recent months, not only due to the current COVID-19 outbreak but also because of antimicrobial resistance (AMR) being declared a top-10 global health threat by the World Health Organization (WHO) in 2019. These global issues have spiked the realization that new and more efficient methods and approaches are urgently required to efficiently combat and overcome the failures in the diagnosis and therapy of infectious disease. This holds true not only for current diseases, but we should also have enough readiness to fight the unforeseen diseases so as to avoid future pandemics. A paradigm shift is needed, not only in infection treatment, but also diagnostic practices, to overcome the potential failures associated with early diagnosis stages, leading to unnecessary and inefficient treatments, while simultaneously promoting AMR. With the development of nanotechnology, nanomaterials fabricated as multifunctional nano-platforms for antibacterial therapeutics, diagnostics, or both (known as "theranostics") have attracted increasing attention. In the research field of nanomedicine, mesoporous silica nanoparticles (MSN) with a tailored structure, large surface area, high loading capacity, abundant chemical versatility, and acceptable biocompatibility, have shown great potential to integrate the desired functions for diagnosis of bacterial infections. The focus of this review is to present the advances in mesoporous materials in the form of nanoparticles (NPs) or composites that can easily and flexibly accommodate dual or multifunctional capabilities of separation, identification and tracking performed during the diagnosis of infectious diseases together with the inspiring NP designs in diagnosis of bacterial infections.

Current Scenario and Challenges in the Direct Identification of Microorganisms Using MALDI TOF MS

MALDI TOF MS-based microbial identification significantly lowers the operational costs because of minimal requirements of substrates and reagents for extraction. Therefore, it has been widely used in varied applications such as clinical, food, military, and ecological research. However, the MALDI TOF MS method is laced with many challenges including its limitation of the reference spectrum. This review briefly introduces the background of MALDI TOF MS technology, including sample preparation and workflow. We have primarily discussed the application of MALDI TOF MS in the identification of microorganisms. Furthermore, we have discussed the current trends for bioaerosol detection using MALDI TOF MS and the limitations and challenges involved, and finally the approaches to overcome these challenges.

Mass Spectrometry Proteotyping-Based Detection and Identification of Staphylococcus aureus, Escherichia coli, and Candida albicans in Blood

Bloodstream infections (BSIs), the presence of microorganisms in blood, are potentially serious conditions that can quickly develop into sepsis and life-threatening situations. When assessing proper treatment, rapid diagnosis is the key; besides clinical judgement performed by attending physicians, supporting microbiological tests typically are performed, often requiring microbial isolation and culturing steps, which increases the time required for confirming positive cases of BSI. The additional waiting time forces physicians to prescribe broad-spectrum antibiotics and empirically based treatments, before determining the precise cause of the disease. Thus, alternative and more rapid cultivation-independent methods are needed to improve clinical diagnostics, supporting prompt and accurate treatment and reducing the development of antibiotic resistance. In this study, a culture-independent workflow for pathogen detection and identification in blood samples was developed, using peptide biomarkers and applying bottom-up proteomics analyses, i.e., so-called "proteotyping". To demonstrate the feasibility of detection of blood infectious pathogens, using proteotyping, Escherichia coli and Staphylococcus aureus were included in the study, as the most prominent bacterial causes of bacteremia and sepsis, as well as Candida albicans, one of the most prominent causes of fungemia. Model systems including spiked negative blood samples, as well as positive blood cultures, without further culturing steps, were investigated. Furthermore, an experiment designed to determine the incubation time needed for correct identification of the infectious pathogens in blood cultures was performed. The results for the spiked negative blood samples showed that proteotyping was 100- to 1,000-fold more sensitive, in comparison with the MALDI-TOF MS-based approach. Furthermore, in the analyses of ten positive blood cultures each of E. coli and S. aureus, both the MALDI-TOF MS-based and proteotyping approaches were successful in the identification of E. coli, although only proteotyping could identify S. aureus correctly in all samples. Compared with the MALDI-TOF MS-based approaches, shotgun proteotyping demonstrated higher sensitivity and accuracy, and required significantly shorter incubation time before detection and identification of the correct pathogen could be accomplished.

Applications of Raman Spectroscopy in Bacterial Infections: Principles, Advantages, and Shortcomings

Infectious diseases caused by bacterial pathogens are important public issues. In addition, due to the overuse of antibiotics, many multidrug-resistant bacterial pathogens have been widely encountered in clinical settings. Thus, the fast identification of bacteria pathogens and profiling of antibiotic resistance could greatly facilitate the precise treatment strategy of infectious diseases. So far, many conventional and molecular methods, both manual or automatized, have been developed for in vitro diagnostics, which have been proven to be accurate, reliable, and time efficient. Although Raman spectroscopy (RS) is an established technique in various fields such as geochemistry and material science, it is still considered as an emerging tool in research and diagnosis of infectious diseases. Based on current studies, it is too early to claim that RS may provide practical guidelines for microbiologists and clinicians because there is still a gap between basic research and clinical implementation. However, due to the promising prospects of label-free detection and noninvasive identification of bacterial infections and antibiotic resistance in several single steps, it is necessary to have an overview of the technique in terms of its strong points and shortcomings. Thus, in this review, we went through recent studies of RS in the field of infectious diseases, highlighting the application potentials of the technique and also current challenges that prevent its real-world applications.

Utility of MALDI-TOF MS for differentiation of Neisseria gonorrhoeae isolates with dissimilar azithromycin susceptibility profiles

BACKGROUND

Antibiotic-resistant gonorrhoea has been a chronic public health burden since the mid-1930s. Recent emergence of isolates resistant to the current recommended antibiotics for gonorrhoea further magnifies the threat of untreatable gonorrhoea. The lack of new, effective antibiotics highlights the need for better understanding of the population structure of Neisseria gonorrhoeae in order to provide greater insight on how to curtail the spread of antimicrobial-resistant N. gonorrhoeae.

OBJECTIVES

To explore a potential application of MALDI-TOF MS to differentiate N. gonorrhoeae displaying different levels of susceptibility to the antibiotic azithromycin.

METHODS

We conducted MALDI-TOF MS using the Bruker Biotyper on 392 N. gonorrhoeae isolates collected through the Gonococcal Isolate Surveillance Project (GISP) and/or the Strengthening the United States Response to Resistant Gonorrhea (SURRG) project. The MALDI-TOF MS spectra were visually analysed to assess the presence of distinctive peak(s). Statistical analysis was performed to assess the relationship between gonococcal isolates with the distinct protein peak and antibiotic susceptibility.

RESULTS

In this study, we were able to differentiate N. gonorrhoeae isolates into two distinct subpopulations using MALDI-TOF MS. Isolates were distinguished by the presence or absence of a spectral peak at 11 300 Da. Notably, these two groups exhibited different levels of susceptibility to azithromycin.

CONCLUSIONS

We have shown that in addition to its ability to identify N. gonorrhoeae, MALDI-TOF MS could also be used to differentiate gonococcal isolates with different levels of susceptibility to azithromycin.

Advances in the Microbiology of Stenotrophomonas maltophilia

Stenotrophomonas maltophilia is an opportunistic pathogen of significant concern to susceptible patient populations. This pathogen can cause nosocomial and community-acquired respiratory and bloodstream infections and various other infections in humans. Sources include water, plant rhizospheres, animals, and foods. Studies of the genetic heterogeneity of S. maltophilia strains have identified several new genogroups and suggested adaptation of this pathogen to its habitats. The mechanisms used by S. maltophilia during pathogenesis continue to be uncovered and explored. S. maltophilia virulence factors include use of motility, biofilm formation, iron acquisition mechanisms, outer membrane components, protein secretion systems, extracellular enzymes, and antimicrobial resistance mechanisms. S. maltophilia is intrinsically drug resistant to an array of different antibiotics and uses a broad arsenal to protect itself against antimicrobials. Surveillance studies have recorded increases in drug resistance for S. maltophilia, prompting new strategies to be developed against this opportunist. The interactions of this environmental bacterium with other microorganisms are being elucidated. S. maltophilia and its products have applications in biotechnology, including agriculture, biocontrol, and bioremediation.

Fluorescent-conjugated antibodies as rapid ex vivo markers for bacterial presence on orthopedic surgical explants and synovium: A pilot study

Surgical infection is one of the most pressing problems in the field of orthopedic surgery; however, current detection methods are plagued by high costs and long wait times. This study seeks to demonstrate the ability of a novel assay using fluorescently conjugated antibodies and confocal laser scanning microscopy (CLSM) to accurately detect bacterial presence on orthopedic surgical explants, tissue, and synovial fluid in 30 min. Explanted hardware, tissue, and synovial fluid samples suspected to be infected were collected from human subjects with institutional review board consent. Samples were prepared using a 30-min protocol, consisting of rinsing, nonspecific blocking and staining steps, and imaged using CLSM. Images were analyzed using ImageJ (National Institute of Health) to determine the percent area of Gram positive and Gram negative bacteria. Results of the assay were compared to the hospital's microbiological laboratory and Gram staining results. Ninety three samples were collected and tested using the 30-min testing protocol; 75 samples were synovial fluid and 18 were tissue and explants. Seventy four of 75 (98.6%) synovial fluid samples correlated with the hospital laboratory's microbiological findings. Of the 18 explant and tissue samples, our assay found bacterial presence in 14 of 18 samples, while the hospital microbiology laboratory found bacterial presence in 13 of 18 samples. This assay reliably stained and rapidly identified the presence of Gram negative and Gram positive bacteria on surgical explants, tissue and synovial fluid in 30 min. This methodology may serve as a point of service tool for the determination of bacterial presence during surgical procedures.

Exploring the value of MALDI-TOF MS for the detection of clonal outbreaks of Burkholderia contaminans

BACKGROUND

Molecular genetics has risen in both output and affordability to become the gold standard in diagnosis, however it is not yet available for most routine clinical microbiology due to cost and the level of skill it requires. Matrix assisted laser desorption/ionisation - time of flight mass spectrometry (MALDI-TOF MS) approaches may be useful in bridging the gap between low-resolution phenotypic methods and bulky genotypic methods in the goal of epidemiological source-typing of microbes. Burkholderia has been shown to be identifiable at the subspecies level using MALDI-TOF MS. There have not yet been studies assessing the ability of MALDI-TOF MS to source-type Burkholderia contaminans isolates into epidemiologically relevant outbreak clusters.

METHODS

55 well-characterised B. contaminans isolates were used to create a panel for analysis of MALDI-TOF MS biomarker peaks and their relation to outbreak strains, location, source, patient, diagnosis and isolate genetics. Unsupervised clustering was performed and classification models were generated using biostatistical analysis software.

RESULTS

B. contaminans spectra derived from MALDI-TOF MS were of sufficiently high resolution to identify 100% of isolates. Unsupervised clustering methods showed poor evidence of spectra clustering by all characteristics measured. Classification algorithms were discriminatory, with Genetic Algorithm models showing 100% recognition capability for all outbreaks, the pulsed-field gel electrophoresis (PFGE) typeability model, and 96.63% recognition for the location model. A consistent peak at m/z of approximately 6943 was identified in all non-typeable strains but in none of the typeable strains.

CONCLUSIONS

MALDI-TOF MS successfully discriminates B. contaminans isolates into clonal, epidemiological clusters, and can recognise isolates non-typeable by PFGE. Further work should investigate this capability, and include peptide studies and genomic sequencing to identify individual proteins or genes responsible for this non-typeablity, particularly at the peak weight identified.

Establishing a mass spectrometry-based system for rapid detection of SARS-CoV-2 in large clinical sample cohorts

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is pressing public health systems around the world, and large population testing is a key step to control this pandemic disease. Here, we develop a high-throughput targeted proteomics assay to detect SARS-CoV-2 nucleoprotein peptides directly from nasopharyngeal and oropharyngeal swabs. A modified magnetic particle-based proteomics approach implemented on a robotic liquid handler enables fully automated preparation of 96 samples within 4 hours. A TFC-MS system allows multiplexed analysis of 4 samples within 10 min, enabling the processing of more than 500 samples per day. We validate this method qualitatively (Tier 3) and quantitatively (Tier 1) using 985 specimens previously analyzed by real-time RT-PCR, and detect up to 84% of the positive cases with up to 97% specificity. The presented strategy has high sample stability and should be considered as an option for SARS-CoV-2 testing in large populations.

Polymer Electrochromism Driven by Metabolic Activity Facilitates Rapid and Facile Bacterial Detection and Susceptibility Evaluation

The electrochromism of a water-soluble naturally oxidized electrochromic polymer, ox-PPE, is harnessed for rapid and facile bacterial detection, discrimination, and susceptibility testing. The ox-PPE solution shows distinct colorimetric and spectroscopic changes within 30 min when mixed with live bacteria. For the underlying mechanism, it is found that ox-PPE responds to the reducing species (e.g. cysteine and glutathione) released by metabolically active bacteria. This reduction reaction is ubiquitous among various bacterial strains, with a noticeable difference that enables discrimination of Gram-negative and Gram-positive bacterial strains. Combining ox-PPE with antibiotics, methicillin-susceptible and -resistant S. aureus can be differentiated within 2.5 h. Proof-of-concept demonstration of ox-PPE for antimicrobial susceptibility testing is carried out by incubating E. coli with various antibiotics. The obtained minimum inhibition concentrations are consistent with the conventional culture-based methods, but with the procedure time significantly shortened to 3 h.

Isolation of Harveyi clade Vibrio spp. collected in aquaculture farms: How can the identification issue be addressed?

Aquaculture is a fast growing industry with its development hampered by bacterial diseases. Vibriosis caused by Harveyi clade strains is known for causing heavy loss especially in shrimp aquaculture farms. For farm treatment and pathogen spread management, veterinarians and researchers need reliable bacterial identification tools. A range of identification methods have been presented for Vibrio spp. in recent literature but little feedback on their performance have been made available to this day. This study aims at comparing Vibrio spp. identification methods and providing guidance on their use. Fifty farms were sampled and bacterial colonies were isolated using specific culture media before microscopic analysis and genomic profiling using ERIC-PCR. A preliminary identification step was carried out using MALDI-ToF mass spectrometry. Four methods were compared for strain identification on 14 newly isolated Harveyi clade Vibrio spp. strains: whole genome sequencing (digital DNA DNA Hybridization (dDDH)), 5 MLSA schemes, ferric uptake regulation (fur) and lecithin-dependent haemolysin (ldh) single gene based identification methods. Apart from dDDH which is a reference method, no technique could identify all the isolates to the species level. The other tested techniques allowed a faster, cheaper but sub genus clade identification which can be interesting when absolute precision is not required. In this regard, MALDI-ToF and fur based identification seemed especially promising.

Large-scale mass spectrometry data combined with demographics analysis rapidly predicts methicillin resistance in Staphylococcus aureus

BACKGROUND

A mass spectrometry-based assessment of methicillin resistance in Staphylococcus aureus would have huge potential in addressing fast and effective prediction of antibiotic resistance. Since delays in the traditional antibiotic susceptibility testing, methicillin-resistant S. aureus remains a serious threat to human health.

RESULTS

Here, linking a 7 years of longitudinal study from two cohorts in the Taiwan area of over 20 000 individually resolved methicillin susceptibility testing results, we identify associations of methicillin resistance with the demographics and mass spectrometry data. When combined together, these connections allow for machine-learning-based predictions of methicillin resistance, with an area under the receiver operating characteristic curve of >0.85 in both the discovery [95% confidence interval (CI) 0.88-0.90] and replication (95% CI 0.84-0.86) populations.

CONCLUSIONS

Our predictive model facilitates early detection for methicillin resistance of patients with S. aureus infection. The large-scale antibiotic resistance study has unbiasedly highlighted putative candidates that could improve trials of treatment efficiency and inform on prescriptions.

Detection of Antibiotic-Resistance by MALDI-TOF Mass Spectrometry: An Expanding Area

Several MALDI-TOF MS-based methods have been proposed for rapid detection of antimicrobial resistance. The most widely studied methods include assessment of β-lactamase activity by visualizing the hydrolysis of the β-lactam ring, detection of biomarkers responsible for or correlated with drug-resistance/non-susceptibility, and the comparison of proteomic profiles of bacteria incubated with or without antimicrobial drugs. Antimicrobial-resistance to a number of antibiotics belonging to different classes has been successfully tested by MALDI-TOF MS in a variety of clinically relevant bacterial species including members of Enterobacteriaceae family, non-fermenting Gram-negative bacteria, Gram-positive cocci, anaerobic bacteria and mycobacteria, opening this field to further clinically important developments. Early detection of drug-resistance by MALDI-TOF MS can be particularly helpful for clinicians to streamline the antibiotic therapy for a better outcome of patients with systemic infection, in all cases where a prompt and effective antibiotic treatment is essential to preserve organ function and/or patient survival.

Proteomic fingerprinting of Neotropical hard tick species (Acari: Ixodidae) using a self-curated mass spectra reference library

Matrix-assisted laser desorption/ionization (MALDI) time-of-flight mass spectrometry is an analytical method that detects macromolecules that can be used for proteomic fingerprinting and taxonomic identification in arthropods. The conventional MALDI approach uses fresh laboratory-reared arthropod specimens to build a reference mass spectra library with high-quality standards required to achieve reliable identification. However, this may not be possible to accomplish in some arthropod groups that are difficult to rear under laboratory conditions, or for which only alcohol preserved samples are available. Here, we generated MALDI mass spectra of highly abundant proteins from the legs of 18 Neotropical species of adult field-collected hard ticks, several of which had not been analyzed by mass spectrometry before. We then used their mass spectra as fingerprints to identify each tick species by applying machine learning and pattern recognition algorithms that combined unsupervised and supervised clustering approaches. Both Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) classification algorithms were able to identify spectra from different tick species, with LDA achieving the best performance when applied to field-collected specimens that did have an existing entry in a reference library of arthropod protein spectra. These findings contribute to the growing literature that ascertains mass spectrometry as a rapid and effective method to complement other well-established techniques for taxonomic identification of disease vectors, which is the first step to predict and manage arthropod-borne pathogens.

Advances in rapid diagnostics for bloodstream infections

Septicemia from bloodstream infections (BSI) is the second largest cause of inpatient mortality and the single most expensive condition for US hospitals to manage. There has been an explosive development of commercial diagnostic systems to accelerate the identification and antimicrobial susceptibility testing (AST) of causative pathogens. Despite adoption of advanced technologies like matrix-assisted laser desorption imaging-time-of-flight mass spectrometry and multiplex polymerase chain reaction for rapid identification, clinical impact has been variable, in part due to the persistent need for conventional AST as well as prescriber understanding of these rapidly evolving platforms. Newer technologies are expanding on rapid detection of genotypic determinants of resistance, but only recently has rapid phenotypic AST been available. Yet, improved outcomes with rapid diagnostic platforms are still most evident in conjunction with active antimicrobial stewardship. This review will outline key advancements in rapid diagnostics for BSI and the role of antimicrobial stewardship in this new era.

Interlaboratory Study for Characterizing Monoclonal Antibodies by Top-Down and Middle-Down Mass Spectrometry

The Consortium for Top-Down Proteomics (www.topdownproteomics.org) launched the present study to assess the current state of top-down mass spectrometry (TD MS) and middle-down mass spectrometry (MD MS) for characterizing monoclonal antibody (mAb) primary structures, including their modifications. To meet the needs of the rapidly growing therapeutic antibody market, it is important to develop analytical strategies to characterize the heterogeneity of a therapeutic product's primary structure accurately and reproducibly. The major objective of the present study is to determine whether current TD/MD MS technologies and protocols can add value to the more commonly employed bottom-up (BU) approaches with regard to confirming protein integrity, sequencing variable domains, avoiding artifacts, and revealing modifications and their locations. We also aim to gather information on the common TD/MD MS methods and practices in the field. A panel of three mAbs was selected and centrally provided to 20 laboratories worldwide for the analysis: Sigma mAb standard (SiLuLite), NIST mAb standard, and the therapeutic mAb Herceptin (trastuzumab). Various MS instrument platforms and ion dissociation techniques were employed. The present study confirms that TD/MD MS tools are available in laboratories worldwide and provide complementary information to the BU approach that can be crucial for comprehensive mAb characterization. The current limitations, as well as possible solutions to overcome them, are also outlined. A primary limitation revealed by the results of the present study is that the expert knowledge in both experiment and data analysis is indispensable to practice TD/MD MS.

Insights Into Subspecies Discrimination Potentiality From Bacteria MALDI-TOF Mass Spectra by Using Data Mining and Diversity Studies

Bacterial identification at subspecies level is critical in clinical care and epidemiological investigations due to the different epidemic potentialities of a species. For this purpose, matrix-assisted laser desorption ionization – time-of-flight mass spectrometry (MALDI-TOF MS) has been proposed in place of molecular genotyping, but with some result discrepancies. The aim of this work is to methodically mine the expression diversities of MALDI-TOF bacterial species spectra and their possible latent organization in order to evaluate their subspecies specific expression. Peak expression diversities of MALDI-TOF spectra coming from routine identifications have been analyzed using Hill numbers, rarefaction curves, and peak clustering. Some size effect critical thresholds were estimated using change point analyses. We included 167,528 spectra corresponding to 405 species. Species spectra diversities have a broad size-dependent variability, which may be influenced by the kind of sampling. Peak organization is characterized by the presence of a main cluster made of the most frequently co-occurring peaks and around 20 secondary clusters grouping less frequently co-occurring peaks. The 35 most represented species in our sample are distributed in two groups depending on the focusing of their protein synthesis activity on the main cluster or not. Our results may advocate some analogy with genomics studies of bacteria, with a main species-related cluster of co-occurring peaks and several secondary clusters, which may host peaks able to discriminate bacterial subgroups. This systematic study of the expression diversities of MALDI-TOF spectra shows that latent organization of co-occurring peaks supports subspecies discrimination and may explain why studies on MALDI-TOF-based typing exhibit some result divergences.

Matrix-assisted laser desorption/ionization time-of-flight MS for the accurate identification of Burkholderia cepacia complex and Burkholderia gladioli in the clinical microbiology laboratory

Introduction. Burkholderia cepacia complex (Bcc) bacteria, currently consisting of 23 closely related species, and Burkholderia gladioli, can cause serious and difficult-to-treat infections in people with cystic fibrosis. Identifying Burkholderia bacteria to the species level is considered important for understanding epidemiology and infection control, and predicting clinical outcomes. Matrix-assisted laser desorption/ionization time-of-flight MS (MALDI-TOF) is a rapid method recently introduced in clinical laboratories for bacterial species-level identification. However, reports on the ability of MALDI-TOF to accurately identify Bcc to the species level are mixed.Aim. The aim of this project was to evaluate the accuracy of MALDI-TOF using the Biotyper and VITEK MS systems in identifying isolates from 22 different Bcc species and B. gladioli compared to recA gene sequencing, which is considered the current gold standard for Bcc.Methodology. To capture maximum intra-species variation, phylogenetic trees were constructed from concatenated multi-locus sequence typing alleles and clustered with a novel k-medoids approach. One hundred isolates representing 22 Bcc species, plus B. gladioli, were assessed for bacterial identifications using the two MALDI-TOF systems.Results. At the genus level, 100 and 97.0 % of isolates were confidently identified as Burkholderia by the Biotyper and VITEK MS systems, respectively; moreover, 26.0 and 67.0 % of the isolates were correctly identified to the species level, respectively. In many, but not all, cases of species misidentification or failed identification, a representative library for that species was lacking.Conclusion. Currently available MALDI-TOF systems frequently do not accurately identify Bcc bacteria to the species level.

Recent methods and biosensors for foodborne pathogen detection in fish: progress and future prospects to sustainable aquaculture systems

The aquaculture industry has advanced toward sustainable recirculating systems, in where parameters of food quality are strictly monitored. Despite that, as in the case of conventional aquaculture practices, the recirculating systems also suffer threats from Aeromonas spp., Vibrio spp., Streptococcus spp., among other foodborne pathogens infecting farmed fish. The aquaculture pathogens are routinely detected by conventional PCR methods or antibody-based tests, with the detection protocols confined to laboratory use. Emerging assay technologies and biosensors recently reported in the literature open new opportunities to the development of sensitive, specific, and portable analytical devices to use in the field. Techniques of DNA/RNA analysis, immunoassays and other nanomolecular technologies have been facing important advances in response time, sensitivity, and enhanced power of discrimination among and within species. Moreover, the recent developments of electrochemical and optical signal transduction have facilitated the incorporation of the innovative assays to practical miniaturized devices. In this work, it is provided a critical review over foodborne pathogen detection by existing and promising methods and biosensors applied to fish samples and extended to other food matrices. While isothermal DNA/RNA amplification methods can be highlighted among the assay methods for their promising analytical performance and suitability for point-of-care testing, the electrochemical transduction provides a way to achieve cost-effective biosensors amenable to use in the aquaculture field. The adoption of new methods and biosensors would constitute a step forward in securing sustainable aquaculture systems.

Discovery of Species-unique Peptide Biomarkers of Bacterial Pathogens by Tandem Mass Spectrometry-based Proteotyping

Mass spectrometry (MS) and proteomics offer comprehensive characterization and identification of microorganisms and discovery of protein biomarkers that are applicable for diagnostics of infectious diseases. The use of biomarkers for diagnostics is widely applied in the clinic and the use of peptide biomarkers is increasingly being investigated for applications in the clinical laboratory. Respiratory-tract infections are a predominant cause for medical treatment, although, clinical assessments and standard clinical laboratory protocols are time-consuming and often inadequate for reliable diagnoses. Novel methods, preferably applied directly to clinical samples, excluding cultivation steps, are needed to improve diagnostics of infectious diseases, provide adequate treatment and reduce the use of antibiotics and associated development of antibiotic resistance. This study applied nano-liquid chromatography (LC) coupled with tandem MS, with a bioinformatics pipeline and an in-house database of curated high-quality reference genome sequences to identify species-unique peptides as potential biomarkers for four bacterial pathogens commonly found in respiratory tract infections (RTIs): Staphylococcus aureus; Moraxella catarrhalis; Haemophilus influenzae and Streptococcus pneumoniae The species-unique peptides were initially identified in pure cultures of bacterial reference strains, reflecting the genomic variation in the four species and, furthermore, in clinical respiratory tract samples, without prior cultivation, elucidating proteins expressed in clinical conditions of infection. For each of the four bacterial pathogens, the peptide biomarker candidates most predominantly found in clinical samples, are presented. Data are available via ProteomeXchange with identifier PXD014522. As proof-of-principle, the most promising species-unique peptides were applied in targeted tandem MS-analyses of clinical samples and their relevance for identifications of the pathogens, i.e. proteotyping, was validated, thus demonstrating their potential as peptide biomarker candidates for diagnostics of infectious diseases.

Evaluation of filter paper as a means to transport inactivated bacteria for identification using the MALDI-TOF MS system

A novel approach to transport inactivated bacteria in filter paper for identification in the MALDI-TOF MS was evaluated. Seventy four bacterial isolates were evaluated and the approach presented sensitivity of 97.3% and specificity of 100%. Inactivated bacteria in filter paper are a safer alternative to transport bacteria for MALDI-TOF MS identification.

Madurella mycetomatis infection of the foot: a case report of a neglected tropical disease in a non-endemic region

Background

Mycetoma is an uncommon chronic granulomatous infection of cutaneous and subcutaneous tissues that can be caused by filamentous bacteria (actinomycetoma) or fungi (eumycetoma). It is the prerogative of young men between the third and fourth decade and is transmitted through any trauma causing an inoculating point. The classic clinical triad associates a painless hard and swelling subcutaneous mass, multiple fistulas, and the pathognomonic discharge of grains. Although endemic in many tropical and subtropical countries, mycetoma can also be found in non-endemic areas as in Morocco, and causes then diagnosis problems leading to long lasting complications. Therefore, we should raise awareness of this neglected disease for an earlier management. Under medical treatment however, mycetoma has a slow healing and surgery is often needed, and relapses are possible.

Case presentation

Herein we report a case of a 64 years old patient, with a history of eumycetoma occurring ten years ago treated with oral terbinafine coupled with surgery. A complete remission was seen after 2 years. He presented a relapse on the previous scar 6 months ago. There wasn’t any bone involvement in the magnetic resonance imaging (MRI). The patient was put under oral terbinafine with a slow but positive outcome.

Conclusion

Through this case report, we perform a literature review and highlight the importance of increase awareness of mycetoma in clinical practice especially in non-endemic regions.