Evaluation of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry for Molecular Typing of Acinetobacter baumannii in Comparison with Orthogonal Methods.

Colonization and subsequent health care-associated infection (HCAI) with Acinetobacter baumannii are a concern for vulnerable patient groups within the hospital setting. Outbreaks involving multidrug-resistant strains are associated with increased patient morbidity and mortality and poorer overall outcomes. Reliable molecular typing methods can help to trace transmission routes and manage outbreaks. In addition to methods deployed by reference laboratories, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) may assist by making initial in-house judgments on strain relatedness. However, limited studies on method reproducibility exist for this application. We applied MALDI-TOF MS typing to A. baumannii isolates associated with a nosocomial outbreak and evaluated different methods for data analysis. In addition, we compared MALDI-TOF MS with whole-genome sequencing (WGS) and Fourier transform infrared spectroscopy (FTIR) as orthogonal methods to further explore their resolution for bacterial strain typing. A related subgroup of isolates consistently clustered separately from the main outbreak group by all investigated methods. This finding, combined with epidemiological data from the outbreak, indicates that these methods identified a separate transmission event unrelated to the main outbreak. However, the MALDI-TOF MS upstream approach introduced measurement variability impacting method reproducibility and limiting its reliability as a standalone typing method. Availability of in-house typing methods with well-characterized sources of measurement uncertainty could assist with rapid and dependable confirmation (or denial) of suspected transmission events. This work highlights some of the steps to be improved before such tools can be fully integrated into routine diagnostic service workflows for strain typing. IMPORTANCE Managing the transmission of antimicrobial resistance necessitates reliable methods for tracking outbreaks. We compared the performance of MALDI-TOF MS with orthogonal approaches for strain typing, including WGS and FTIR, for Acinetobacter baumannii isolates correlated with a health care-associated infection (HCAI) event. Combined with epidemiological data, all methods investigated identified a group of isolates that were temporally and spatially linked to the outbreak, yet potentially attributed to a separate transmission event. This may have implications for guiding infection control strategies during an outbreak. However, the technical reproducibility of MALDI-TOF MS needs to be improved for it to be employed as a standalone typing method, as different stages of the experimental workflow introduced bias influencing interpretation of biomarker peak data. Availability of in-house methods for strain typing of bacteria could improve infection control practices following increased reports of outbreaks of antimicrobial-resistant organisms during the COVID-19 pandemic, related to sessional usage of personal protective equipment (PPE).

Changes in the Protein Profile in Staphylococcal Strains from Patients Infected with the SARS-CoV-2 Virus.

Staphylococcus aureus strains are particularly often isolated from patients with SARS-CoV-2 infection. The aim of the current research was to determine whether the SARS-CoV-2 virus infection affects the protein profile of S. aureus. Bacteria were isolated from the forty swabs collected from the patients in the hospitals of the Pomeranian region. MALDI-TOF MS spectra were obtained using a Microflex LT instrument. Twenty-nine peaks were identified. The peak (2,430) is described here for the first time and was unique for the isolates from patients infected with the SARS-CoV-2 virus. These results support the hypothesis of bacterial adaptation to the conditions caused by viral infection.

Inhibitory activity of a sulfated oligo-porphyran from Pyropia yezoensis against SARS-CoV-2.

COVID-19 caused by SARS-CoV-2 has spread around the world at an unprecedented rate. A more homogeneous oligo-porphyran with mean molecular weight of 2.1 kD, named OP145, was separated from Pyropia yezoensis. NMR analysis showed OP145 was mainly composed of →3)-ß-d-Gal-(1 â†’ 4)-α-l-Gal (6S) repeating units with few replacement of 3,6-anhydride, and the molar ratio was 1:0.85:0.11. MALDI-TOF MS revealed OP145 contained mainly tetrasulfate-oligogalactan with Dp range from 4 to 10 and with no more than two 3,6-anhydro-α-l-Gal replacement. The inhibitory activity of OP145 against SARS-CoV-2 was investigated in vitro and in silico. OP145 could bind to Spike glycoprotein (S-protein) through SPR result, and pseudovirus tests confirmed that OP145 could inhibite the infection with an EC50 of 37.52 µg/mL. Molecular docking simulated the interaction between the main component of OP145 and S-protein. All the results indicated that OP145 had the potency to treat and prevent COVID-19.

Resolving omicron sub-variants of SARS CoV-2 coronavirus with MALDI mass spectrometry.

Mass mapping using high resolution mass spectrometry has been applied to identify and rapidly distinguish the omicron sub-variants across the BA.1-BA.5 lineages. Lineage-specific protein mutations in the surface spike protein give rise to peptide biomarkers of unique mass that can be confidently and sensitively detected with high resolution mass spectrometry. Those that are most efficiently ionised and detected within the S1 subunit in recombinant forms facilitate their detection in clinical specimens containing other SARS-CoV2 viral proteins and contaminants. A study of five dozen omicron-positive specimens, using a selected ion monitoring approach, detected peptide biomarkers for strains of BA.1, BA.2.75 and BA.4 sub-variants in 23%, 42% and 28% of samples respectively, consistent with their reported levels in the local population. The virus was confidently assigned in over 93% of omicron positive specimens. The ease of detection of the BA.2.75 variant, in particular, is of vital importance given its rapid global spread in late 2022 due to several immune evasive mutations within the receptor-binding domain.

Simultaneous detection of omicron and other SARS-CoV-2 variants by multiplex PCR MassARRAY technology.

The rapid emergence of SARS-CoV-2 variants with high severity and transmutability adds further urgency for rapid and multiplex molecular testing to identify the variants. A nucleotide matrix-assisted laser-desorption-ionization time-of-flight mass spectrophotometry (MALDI-TOF MS)-based assay was developed (called point mutation array, PMA) to identify four major SARS-CoV-2 variants of concern (VOCs) including Alpha, Beta, Delta, and Omicron (namely PMA-ABDO) and differentiate Omicron subvariant (namely PMA-Omicron). PMA-ABDO and PMA-Omicron consist of 24 and 28 mutation sites of the spike gene. Both PMA panels specifically identified VOCs with as low as 10 viral copies/µl. The panel has shown a 100% concordant with the Next Generation Sequencing (NGS) results testing on 256 clinical specimens with real-time PCR cycle threshold (Ct) values less than 26. It showed a higher sensitivity over NGS; 25/28 samples were positive by PMA but not NGS in the clinical samples with PCR Ct higher than 26. Due to the mass of nucleotide used to differentiate between wild-type and mutation strains, the co-infection or recombination of multiple variants can be determined by the PMA method. This method is flexible in adding a new primer set to identify a new emerging mutation site among the current circulating VOCs and the turnaround time is less than 8 h. However, the spike gene sequencing or NGS retains the advantage of detecting newly emerged variants.

CEST MRI and MALDI imaging reveal metabolic alterations in the cervical lymph nodes of EAE mice.

BACKGROUND: Multiple sclerosis (MS) is a neurodegenerative disease, wherein aberrant immune cells target myelin-ensheathed nerves. Conventional magnetic resonance imaging (MRI) can be performed to monitor damage to the central nervous system that results from previous inflammation; however, these imaging biomarkers are not necessarily indicative of active, progressive stages of the disease. The immune cells responsible for MS are first activated and sensitized to myelin in lymph nodes (LNs). Here, we present a new strategy for monitoring active disease activity in MS, chemical exchange saturation transfer (CEST) MRI of LNs. METHODS AND RESULTS: We studied the potential utility of conventional (T2-weighted) and CEST MRI to monitor changes in these LNs during disease progression in an experimental autoimmune encephalomyelitis (EAE) model. We found CEST signal changes corresponded temporally with disease activity. CEST signals at the 3.2 ppm frequency during the active stage of EAE correlated significantly with the cellular (flow cytometry) and metabolic (mass spectrometry imaging) composition of the LNs, as well as immune cell infiltration into brain and spinal cord tissue. Correlating primary metabolites as identified by matrix-assisted laser desorption/ionization (MALDI) imaging included alanine, lactate, leucine, malate, and phenylalanine. CONCLUSIONS: Taken together, we demonstrate the utility of CEST MRI signal changes in superficial cervical LNs as a complementary imaging biomarker for monitoring disease activity in MS. CEST MRI biomarkers corresponded to disease activity, correlated with immune activation (surface markers, antigen-stimulated proliferation), and correlated with LN metabolite levels.

An outbreak of Ralstonia insidiosa bloodstream infections caused by contaminated heparinized syringes.

INTRODUCTION: Ralstonia insidiosa, a gram-negative waterborne bacteria able to survive and grow in any type of water source, can cause nosocomial infections, and are considered emerging pathogens of infectious diseases in hospital settings. In this study, we report an outbreak of R. insidiosa at our center related to contaminated heparinized syringes. MATERIAL AND METHODS: The present study was conducted in a tertiary care university hospital in Turkey. An outbreak analysis was performed between September 2021 and December 2021. Microbiological samples were obtained from environmental sources and from patient blood cultures. Species identification was performed using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). To investigate the clonality of strains, all confirmed isolates were sent to the National Reference Laboratory and pulsed-field gel electrophoresis (PFGE) was used to perform molecular typing. RESULTS: Seventeen R. insidiosa isolates were identified from the blood cultures of 13 patients from various wards and intensive care units. Isolates from seven patient blood cultures and two heparinized blood gas syringes were characterized by PFGE. All isolates were found to belong to the same clone of R. insidiosa. CONCLUSION: R. insidiosa was identified as the cause of a nosocomial infection outbreak in our hospital, which was then rapidly controlled by the infection-control team. When rare waterborne microorganisms grow in blood or other body fluid cultures, clinicians and the infection-control team should be made aware of a possible outbreak.

Serum N-glycomic profiling may provide potential signatures for surveillance of COVID-19.

Disease development and progression are often associated with aberrant glycosylation, indicating that changes in biological fluid glycome may potentially serve as disease signatures. The corona virus disease-2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represents a significant threat to global human health. However, the effect of SARS-CoV-2 infection on the overall serum N-glycomic profile has been largely unexplored. Here, we extended our 96-well-plate-based high-throughput, high-sensitivity N-glycan profiling platform further with the aim of elucidating potential COVID-19-associated serum N-glycomic alterations. Use of this platform revealed both similarities and differences between the serum N-glycomic fingerprints of COVID-19 positive and control cohorts. Although there were no specific glycan peaks exclusively present or absent in COVID-19 positive cohort, this cohort showed significantly higher levels of glycans and variability. On the contrary, the overall N-glycomic profiles for healthy controls were well-contained within a narrow range. From the serum glycomic analysis, we were able to deduce changes in different glycan subclasses sharing certain structural features. Of significance was the hyperbranched and hypersialylated glycans and their derived glycan subclass traits. T-distributed stochastic neighbor embedding and hierarchical heatmap clustering analysis were performed to identify 13 serum glycomic variables that potentially distinguished the COVID-19 positive from healthy controls. Such serum N-glycomic changes described herein may indicate or correlate to the changes in serum glycoproteins upon COVID-19 infection. Furthermore, mapping the serum N-glycome following SARS-CoV-2 infection may help us better understand the disease and enable "Long-COVID" surveillance to capture the full spectrum of persistent symptoms.

Comparative performance of two automated machine learning platforms for COVID-19 detection by MALDI-TOF-MS.

The 2019 novel coronavirus infectious disease (COVID-19) pandemic has resulted in an unsustainable need for diagnostic tests. Currently, molecular tests are the accepted standard for the detection of SARS-CoV-2. Mass spectrometry (MS) enhanced by machine learning (ML) has recently been postulated to serve as a rapid, high-throughput, and low-cost alternative to molecular methods. Automated ML is a novel approach that could move mass spectrometry techniques beyond the confines of traditional laboratory settings. However, it remains unknown how different automated ML platforms perform for COVID-19 MS analysis. To this end, the goal of our study is to compare algorithms produced by two commercial automated ML platforms (Platforms A and B). Our study consisted of MS data derived from 361 subjects with molecular confirmation of COVID-19 status including SARS-CoV-2 variants. The top optimized ML model with respect to positive percent agreement (PPA) within Platforms A and B exhibited an accuracy of 94.9%, PPA of 100%, negative percent agreement (NPA) of 93%, and an accuracy of 91.8%, PPA of 100%, and NPA of 89%, respectively. These results illustrate the MS method's robustness against SARS-CoV-2 variants and highlight similarities and differences in automated ML platforms in producing optimal predictive algorithms for a given dataset.

MALDI(+) FT-ICR Mass Spectrometry (MS) Combined with Machine Learning toward Saliva-Based Diagnostic Screening for COVID-19.

Rapid identification of existing respiratory viruses in biological samples is of utmost importance in strategies to combat pandemics. Inputting MALDI FT-ICR MS (matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometry) data output into machine learning algorithms could hold promise in classifying positive samples for SARS-CoV-2. This study aimed to develop a fast and effective methodology to perform saliva-based screening of patients with suspected COVID-19, using the MALDI FT-ICR MS technique with a support vector machine (SVM). In the method optimization, the best sample preparation was obtained with the digestion of saliva in 10 µL of trypsin for 2 h and the MALDI analysis, which presented a satisfactory resolution for the analysis with 1 M. SVM models were created with data from the analysis of 97 samples that were designated as SARS-CoV-2 positives versus 52 negatives, confirmed by RT-PCR tests. SVM1 and SVM2 models showed the best results. The calibration group obtained 100% accuracy, and the test group 95.6% (SVM1) and 86.7% (SVM2). SVM1 selected 780 variables and has a false negative rate (FNR) of 0%, while SVM2 selected only two variables with a FNR of 3%. The proposed methodology suggests a promising tool to aid screening for COVID-19.

Machine Learning Approaches to Analyze MALDI-TOF Mass Spectrometry Protein Profiles.

Machine learning is being employed for the development of diagnostic methods for several diseases, but prognostic techniques are still poorly explored. The development of such approaches is essential to assist healthcare workers to ensure the most appropriate treatment for patients. In this chapter, we demonstrate a detailed protocol for the application of machine learning to MALDI-TOF MS spectra of COVID-19-infected plasma samples for risk classification and biomarker identification.

Identification of Circulating Biomarkers of COVID-19 Using MALDI-TOF Mass Spectrometry.

Matrix-assisted laser desorption/ionization source coupled with time-of-flight mass analyzer mass spectrometry (MALDI-TOF MS) is being widely used to obtain proteomic profiles for clinical purposes, as a fast, low-cost, robust, and efficient technique. Here we describe a method for biofluid analysis using MALDI-TOF MS for rapid acquisition of proteomic signatures of COVID-19 infected patients. By using solid-phase extraction, the method allows the analysis of biofluids in less than 15 min.

MALDI-TOF Mass Spectrometric Detection of SARS-CoV-2 Using Cellulose Sulfate Ester Enrichment and Hot Acid Treatment.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes the ongoing coronavirus disease 2019 (COVID-19) pandemic. Here we report a novel strategy for the rapid detection of SARS-CoV-2 based on an enrichment approach exploiting the affinity between the virus and cellulose sulfate ester functional groups, hot acid hydrolysis, and matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS). Virus samples were enriched using cellulose sulfate ester microcolumns. Virus peptides were prepared using the hot acid aspartate-selective hydrolysis and characterized by MALDI-TOF MS. Collected spectra were processed with a peptide fingerprint algorithm, and searching parameters were optimized for the detection of SARS-CoV-2. These peptides provide high sequence coverage for nucleocapsid (N protein) and allow confident identification of SARS-CoV-2. Peptide markers contributing to the detection were rigorously identified using bottom-up proteomics. The approach demonstrated in this study holds the potential for developing a rapid assay for COVID-19 diagnosis and detecting virus variants from a variety of sources, such as sewage and nasal swabs.

Use of MALDI-TOF mass spectrometry for virus identification: a review.

The coronavirus pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) directly or indirectly affects every individual worldwide. The fight against SARS-CoV-2 is based on the rapid and accurate diagnosis and subsequent isolation of infected individuals. Therefore, the demands for the scientific development of diagnostic methods for the confirmation of SARS-CoV-2 are enormous. Currently, reverse-transcription quantitative polymerase chain reaction (RT-qPCR) is the main method used for detecting viruses, including SARS-CoV-2, and is considered the gold standard for coronavirus disease 2019 (COVID-19) identification. However, various alternatives have been investigated due to the time and cost demands of this method or to shortages of reagents. In this review, we focus on matrix-assisted laser desorption and ionisation with time-of-flight analyser mass spectrometry (MALDI-TOF MS) techniques as potential tools for the diagnosis of viruses with an emphasis on SARS-CoV-2. MALDI-TOF is commonly used in clinical laboratories for bacterial characterization and identification, but in the field of clinical virology, MALDI-TOF remains only a promising technology for routine diagnosis. This review provides an overview of the development of clinical virology from the point of view of using MALDI-TOF for virus identification and as a possible diagnostic tool for SARS-CoV-2 detection. In addition, this review summarizes the current state of standard methods for virus diagnostics including the preparation of clinical samples.

Case report of Curtobacterium isolated from a catheter tip sample misidentified as Cronobacter.

The Curtobacterium genus is a member of the family Microbacteriaceae, and Curtobacterium species are recognized as plant pathogens. The aim of this study was to investigate a dubious result of species identification for an infection located on a catheter tip of a patient with Covid-19. A strain isolated from a catheter tip sample, identified by VITEK® 2 as Cronobacter spp., was submitted to polyphasic analysis: Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) using VITEK® MS, real-time polymerase chain reaction targeting dnaG gene, and 16S rRNA full gene Sanger sequencing analysis for confirmation. The strain presented negative result using qPCR and could not identified by MALDI-TOF MS. 16S rRNA full gene Sanger sequencing analysis identified the strain as Curtobacterium spp. The Gram-variable characteristic (Gram-negative instead of Gram-positive) of the isolated strain was the responsible for the misidentification by VITEK® 2 and VITEK® MS did not identify the strain. 16S rRNA full gene sequencing analysis identified the strain as Curtobacterium genus, but other complementary techniques are necessary to identify at species level.

RT-PCR/MALDI-TOF Diagnostic Target Performance Reflects Circulating SARS-CoV-2 Variant Diversity in New York City.

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to circulate, multiple variants of concern have emerged. New variants pose challenges for diagnostic platforms because sequence diversity can alter primer/probe-binding sites (PBSs), causing false-negative results. The MassARRAY SARS-CoV-2 Panel (Agena Bioscience) uses RT-PCR and mass spectrometry to detect five multiplex targets across N and ORF1ab genes. Herein, we use a data set of 256 SARS-CoV-2-positive specimens collected between April 11, 2021, and August 28, 2021, to evaluate target performance with paired sequencing data. During this time frame, two targets in the N gene (N2 and N3) were subject to the greatest sequence diversity. In specimens with N3 dropout, 69% harbored the Alpha-specific A28095U polymorphism that introduces a 3'-mismatch to the N3 forward PBS and increases risk of target dropout relative to specimens with 28095A (relative risk, 20.02; 95% CI, 11.36 to 35.72; P < 0.0001). Furthermore, among specimens with N2 dropout, 90% harbored the Delta-specific G28916U polymorphism that creates a 3'-mismatch to the N2 probe PBS and increases target dropout risk (relative risk, 11.92; 95% CI, 8.17 to 14.06; P < 0.0001). These findings highlight the robust capability of MassARRAY SARS-CoV-2 Panel target results to reveal circulating virus diversity, and they underscore the power of multitarget design to capture variants of concern.

Staphylococcus massiliensis isolated from human blood cultures, Germany, 2017-2020.

Clinical and laboratory data on newly described staphylococcal species is rare, which hampers decision-making when such pathogens are detected in clinical specimens. Here, we describe Staphylococcus massiliensis detected in three patients at a university hospital in southwest Germany. We report the discrepancy of microbiological findings between matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, 16S-rRNA polymerase chain reaction, and whole-genome sequencing for all three isolates. Our findings highlight the diagnostic pitfalls pertinent to novel and non-model organisms in daily microbiological practice, in whom the correct identification is dependent on database accuracy.

Matrix-Assisted Laser Desorption and Ionization Time-of-Flight Mass Spectrometry Analysis for the Direct Detection of SARS-CoV-2 in Nasopharyngeal Swabs.

The most common diagnostic method used for coronavirus disease-2019 (COVID-19) is real-time reverse transcription polymerase chain reaction (PCR). However, it requires complex and labor-intensive procedures and involves excessive positive results derived from viral debris. We developed a method for the direct detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in nasopharyngeal swabs, which uses matrix-assisted laser desorption and ionization time-of-flight mass spectrometry (MALDI-ToF MS) to identify specific peptides from the SARS-CoV-2 nucleocapsid phosphoprotein (NP). SARS-CoV-2 viral particles were separated from biological molecules in nasopharyngeal swabs by an ultrafiltration cartridge. Further purification was performed by an anion exchange resin, and purified NP was digested into peptides using trypsin. The peptides from SARS-CoV-2 that were inoculated into nasopharyngeal swabs were detected by MALDI-ToF MS, and the limit of detection was 106.7 viral copies. This value equates to 107.9 viral copies per swab and is approximately equivalent to the viral load of contagious patients. Seven NP-derived peptides were selected as the target molecules for the detection of SARS-CoV-2 in clinical specimens. The method detected between two and seven NP-derived peptides in 19 nasopharyngeal swab specimens from contagious COVID-19 patients. These peptides were not detected in four specimens in which SARS-CoV-2 RNA was not detected by PCR. Mutated NP-derived peptides were found in some specimens, and their patterns of amino acid replacement were estimated by accurate mass. Our results provide evidence that the developed MALDI-ToF MS-based method in a combination of straightforward purification steps and a rapid detection step directly detect SARS-CoV-2-specific peptides in nasopharyngeal swabs and can be a reliable high-throughput diagnostic method for COVID-19.

Robust clinical detection of SARS-CoV-2 variants by RT-PCR/MALDI-TOF multitarget approach.

The coronavirus disease 2019 (COVID-19) pandemic has sparked the rapid development of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnostics. However, emerging variants pose the risk for target dropout and false-negative results secondary to primer/probe binding site (PBS) mismatches. The Agena MassARRAY® SARS-CoV-2 Panel combines reverse-transcription polymerase chain reaction and matrix-assisted laser desorption/ionization time-of-flight mass-spectrometry to probe for five targets across N and ORF1ab genes, which provides a robust platform to accommodate PBS mismatches in divergent viruses. Herein, we utilize a deidentified data set of 1262 SARS-CoV-2-positive specimens from Mount Sinai Health System (New York City) from December 2020 to April 2021 to evaluate target results and corresponding sequencing data. Overall, the level of PBS mismatches was greater in specimens with target dropout. Of specimens with N3 target dropout, 57% harbored an A28095T substitution that is highly specific for the Alpha (B.1.1.7) variant of concern. These data highlight the benefit of redundancy in target design and the potential for target performance to illuminate the dynamics of circulating SARS-CoV-2 variants.