Identification of Microbial Strains via 2D Cross-Correlation of LC-MS Data

Mass spectrometry is commonly used in the identification of species present in microbial samples, but the high similarity in the peptide composition between strains of a single species has made analysis at the subspecies level challenging. Prior research in this area has employed methods such as Principal Component Analysis (PCA), the k-Nearest Neighbors' (kNN) algorithm, and Pearson correlation. Previously, 1D cross-correlation of mass spectra has been shown to be useful in the classification of small molecule compounds as well as in the identification of peptide sequences via the SEQUEST algorithm and its variants. While direct application of cross-correlation to mass spectral data has been shown to aid in the identification of many other types of compounds, this type of analysis has not been demonstrated in the literature for the purpose of LC-MS based identification of microbial strains. A method of identifying microbial strains is presented here that applies the principle of 2D cross-correlation to LC-MS data. For a set of N = 30 yeast isolate samples representing 5 yeast strains (K-97, S-33, T-58, US-05, WB-06), high-resolution LC-MS-Orbitrap data were collected. Reference spectra were then generated for each strain from the combined data of each sample of that strain. Sample strains were then predicted by computing the 2D cross-correlation of each sample against the reference spectra, followed by application of correction factors measuring the asymmetry of the 2D correlation functions.

Advances in rapid detection of SARS-CoV-2 by mass spectrometry

COVID-19 has already been lasting for more than two years and it has been severely affecting the whole world. Still, detection of SARS-CoV-2 remains the frontline approach to combat the pandemic, and the reverse transcription polymerase chain reaction (RT-PCR)-based method is the well recognized detection method for the enormous analytical demands. However, the RT-PCR method typically takes a relatively long time, and can produce false positive and false negative results. Mass spectrometry (MS) is a very commonly used technique with extraordinary sensitivity, specificity and speed, and can produce qualitative and quantitative information of various analytes, which cannot be achieved by RT-PCR. Since the pandemic outbreak, various mass spectrometric approaches have been developed for rapid detection of SARS-CoV-2, including the LC-MS/MS approaches that could allow analysis of several hundred clinical samples per day with one MS system, MALDI-MS approaches that could directly analyze clinical samples for the detection, and efforts for the on-site detection with portable devices. In this review, these mass spectrometric approaches were summarized, and their pros and cons as well as further development were also discussed.

Hydrophilic magnetic covalent triazine frameworks for differential N-glycopeptides enrichment in breast cancer plasma membranes

Alterations in plasma membrane glycoproteins (PMGs) have been identified as a hallmark of cancer. The comparison and identification of differential PMGs is significant for finding new markers and understanding pathological processes. However, the research on PMGs is often constrained by the low abundance and the disturbance of abundant endogenous biomolecules during direct analysis. Here, we report a bottom-up strategy to enrich the PMGs of breast cancer cells using hydrophilic magnetic covalent triazine frameworks (CTFs). A total of 972 N-glycopeptides and 1006 N-glycosites belonging to 526 N-glycoproteins were enriched in MCF-10A plasma membrane tryptic digest by magnetic CTFs. And 680 N-glycopeptides and 806 N-glycosites belonging to 443 N-glycoproteins were enriched in SK-BR-3 plasma membrane tryptic digest. Furthermore, comparative analysis was performed based on gene ontology to verify breast cancer biomarkers (SUSD2 and ALCAM) and differential PMGs' function. This strategy which systematically integrates efficient enrichment of differential PMGs and in-depth comparative analysis has great potential for helping illuminate the atlas of breast cancer PMGs and the causes of tumor metastasis.

Antibiotic Resistance: One Health One World Outlook

Antibiotic resistance (ABR) is a growing public health concern worldwide, and it is now regarded as a critical One Health issue. One Health’s interconnected domains contribute to the emergence, evolution, and spread of antibiotic-resistant microorganisms on a local and global scale, which is a significant risk factor for global health. The persistence and spread of resistant microbial species, and the association of determinants at the human-animal-environment interface can alter microbial genomes, resulting in resistant superbugs in various niches. ABR is motivated by a well-established link between three domains: human, animal, and environmental health. As a result, addressing ABR through the One Health approach makes sense. Several countries have implemented national action plans based on the One Health approach to combat antibiotic-resistant microbes, following the Tripartite’s Commitment Food and Agriculture Organization (FAO)-World Organization for Animal Health (OIE)-World Health Organization (WHO) guidelines. The ABR has been identified as a global health concern, and efforts are being made to mitigate this global health threat. To summarize, global interdisciplinary and unified approaches based on One Health principles are required to limit the ABR dissemination cycle, raise awareness and education about antibiotic use, and promote policy, advocacy, and antimicrobial stewardship.

Assessing direct analysis in real-time mass spectrometry for the identification and serotyping of Legionella pneumophila

AIMS

The efficacy of ambient mass spectrometry to identify and serotype Legionella pneumophila was assessed. To this aim, isolated waterborne colonies were submitted to a rapid extraction method and analysed by direct analysis in real-time mass spectrometry (DART-HRMS).

METHODS AND RESULTS

The DART-HRMS profiles, coupled with partial least squares discriminant analysis (PLS-DA), were first evaluated for their ability to differentiate Legionella spp. from other bacteria. The resultant classification model achieved an accuracy of 98.1% on validation. Capitalising on these encouraging results, DART-HRMS profiling was explored as an alternative approach for the identification of L. pneumophila sg. 1, L. pneumophila sg. 2-15 and L. non-pneumophila; therefore, a different PLS-DA classifier was built. When tested on a validation set, this second classifier reached an overall accuracy of 95.93%. It identified the harmful L. pneumophila sg. 1 with an impressive specificity (100%) and slightly lower sensitivity (91.7%), and similar performances were reached in the classification of L. pneumophila sg. 2-15 and L. non-pneumophila.

CONCLUSIONS

The results of this study show the DART-HMRS method has good accuracy, and it is an effective method for Legionella serogroup profiling.

SIGNIFICANCE AND IMPACT OF THE STUDY

These preliminary findings could open a new avenue for the rapid identification and quick epidemiologic tracing of L. pneumophila, with a consequent improvement to risk assessment.

Rapid and sensitive detection of Staphylococcus aureus and Klebsiella pneumonia based on bacitracin-modified Fe3O4@PDA magnetic beads combined with matrix-assisted laser desorption ionization-time of flight mass spectrometry

The highly effective detection of pathogens in complex biological samples is an attractive and critical topic of study. Bacitracin is a novel broad-spectrum antimicrobial peptide to enrich bacteria via interactions with the membrane surface of the different bacterial cells. In this study, for the first time, bacitracin was immobilized on the surface of Fe3O4@PDA magnetic nanoparticles for the enrichment of Staphylococcus aureus (G+) and Klebsiella pneumoniae (G-). Combined with matrix-assisted laser desorption ionization time-of-flight mass spectrometry, a rapid and sensitive detection method for these two bacteria was developed. In this method, the detectable concentration of bacteria was decreased by 2-3 orders of magnitude in unenriched samples. The enrichment and identification can be completed in one hour. All these results demonstrated that the bacitracin-functionalized magnetic composite has potential for use in the large-scale enrichment and isolation of target pathogens from complex biological samples, opening a new avenue for the rapid and sensitive detection of pathogens.

Evaluation of prostate cancer based on MALDI-TOF MS fingerprinting of nanoparticle-treated serum proteins/peptides

The serum MALDI-TOF MS spectrum includes signals for serum proteins and peptides between 1000 and 12,000 Da in size, presenting a fingerprint-like pattern. However, whole serum MALDI-TOF MS signals are complex and prejudiced for data analysis. Pre-treatment with specific nanomaterials can simplify the mass spectrum while retaining the characteristics of the fingerprint pattern. In the present study, we used hydrophilic interaction chromatography nanoparticles (HICNPs) to enrich proteins and peptides in serum from a large number prostate cancer samples and controls. After pre-treatment with HICNPs, the serum MALDI-TOF MS signals for samples were simpler, with more analysable fingerprint-like patterns. Principal component analysis and partial least squares discriminant analysis of the samples demonstrated a significant difference in the MALDI-TOF signals between prostate cancer and controls, with an analytical accuracy of 77%, approaching that of methods based on prostate-specific antigen. Due to the low cost and high flux, MALDI-TOF MS fingerprinting can be used in large-scale evaluation of various cancers, including prostate cancer.

Determination and Identification of Antibiotic Drugs and Bacterial Strains in Biological Samples

Antibiotics were initially natural substances. However, nowadays, they also include synthetic drugs, which show their activity against bacteria, killing or inhibiting their growth and division. Thanks to these properties, many antibiotics have quickly found practical application in the fight against infectious diseases such as tuberculosis, syphilis, gastrointestinal infections, pneumonia, bronchitis, meningitis and septicemia. Antibiotic resistance is currently a detrimental problem; therefore, in addition to the improvement of antibiotic therapy, attention should also be paid to active metabolites in the body, which may play an important role in exacerbating the existing problem. Taking into account the clinical, cognitive and diagnostic purposes of drug monitoring, it is important to select an appropriate analytical method that meets all the requirements. The detection and identification of the microorganism responsible for the infection is also an essential factor in the implementation of appropriate antibiotic therapy. In recent years, clinical microbiology laboratories have experienced revolutionary changes in the way microorganisms are identified. The MALDI-TOF MS technique may be interesting, especially in some areas where a quick analysis is required, as is the case with clinical microbiology. This method is not targeted, which means that no prior knowledge of the infectious agent is required, since identification is based on a database match.

Liquid biopsy for infectious diseases: a focus on microbial cell-free DNA sequencing

Metagenomic next-generation sequencing (mNGS) of microbial cell-free DNA (mcfDNA sequencing) is becoming an attractive diagnostic modality for infectious diseases, allowing broad-range pathogen detection, noninvasive sampling, and rapid diagnosis. At this key juncture in the translation of metagenomics into clinical practice, an integrative perspective is needed to understand the significance of emerging mcfDNA sequencing technology. In this review, we summarized the actual performance of the mcfDNA sequencing tests recently used in health care settings for the diagnosis of a variety of infectious diseases and further focused on the practice considerations (challenges and solutions) for improving the accuracy and clinical relevance of the results produced by this evolving technique. Such knowledge will be helpful for physicians, microbiologists and researchers to understand what is going on in this quickly progressing field of non-invasive pathogen diagnosis by mcfDNA sequencing and promote the routine implementation of this technique in the diagnosis of infectious disease.

Tissue classification by rapid evaporative ionization mass spectrometry (REIMS): comparison between a diathermic knife and CO2 laser sampling on classification performance

The increasing need for rapid, in situ, and robust tissue profiling approaches in the context of intraoperative diagnostics has led to the development of a large number of ambient ionization-based surface sampling strategies. This paper compares the performances of a diathermic knife and a CO2 laser handpiece, both clinically approved, coupled to a rapid evaporative ionization mass spectrometry (REIMS) source for quasi-instantaneous tissue classification. Several fresh meat samples (muscle, liver, bone, bone marrow, cartilage, skin, fat) were obtained from different animals. Overall, the laser produced cleaner cuts and more reproducible and higher spectral quality signals when compared with the diathermic knife (CV laser = 9-12%, CV diathermic = 14-23%). The molecular profiles were subsequently entered into a database and PCA/LDA classification/prediction models were built to assess if the data generated with one sampling modality can be employed to classify the data generated with the other handpiece. We demonstrate that the correct classification rate of the models increases (+ 25%) with the introduction of a model based on peak lists that are tissue-specific and common to the two handpieces, compared with considering solely the whole molecular profile. This renders it possible to use a unique and universal database for quasi-instantaneous tissue recognition which would provide similar classification results independent of the handpiece used. Furthermore, the laser was able to generate aerosols rich in lipids from hard tissues such as bone, bone marrow, and cartilage. Combined, these results demonstrate that REIMS is a valuable and versatile tool for instantaneous identification/classification of hard tissue and coupling to different aerosol-generating handpieces expands its field of application. Graphical abstract.

Microfluidic smartphone quantitation of Escherichia coli in synthetic urine

In spite of the clinical need, there is a major gap in rapid diagnostics for identification and quantitation of E. coli and other pathogens, also regarded as the biggest bottleneck in the fight against the spread of antimicrobial resistant bacterial strains. This study reports for the first time an optical, smartphone-based microfluidic fluorescence sandwich immunoassay capable of quantifying E. coli in buffer and synthetic urine in less than 25 min without sample preparation nor concentration. A limit of detection (LoD) up to 240 CFU/mL, comensurate with cut-off for UTIs (10³-10⁵ CFUs/mL) was achieved. Replicas of full response curves performed with 10⁰-10⁷ CFUs/mL of E. coli K12 in synthetic urine yielded recovery values in the range 80-120%, assay reproducibility below 30% and precision below 20%, therefore similar to high-performance automated immunoassays. The unrivalled LoD was mainly linked to the 'open fluidics' nature of the 10-bore microfluidic strips used that enabled passing a large volume of sample through the microcapillaries coated with capture antibody. The new smartphone based test has the potential of being as a rapid, point-of-care test for rule-in of E. coli infections that are responsible for around 80% of UTIs, helping to stop the over-prescription of antibiotics and the monitoring of patients with other symptomatic communicable diseases caused by E. coli at global scale.