Use of MALDI-TOF mass spectrometry in the battle against bacterial infectious diseases: recent achievements and future perspectives

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry in the diagnosis of microorganisms

Microbiology culture is the gold standard method for identifying microorganisms. This identification protocol takes several days to complete. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a technique that can identify different microorganisms quickly and accurately. The objective of this work was to evaluate the use of MALDI-TOF MS in the routine of clinical laboratories to identify microorganisms and to identify their resistance to antimicrobials. This study evaluated the relevance of the MALDI-TOF MS technique for microbiological diagnosis through a literature review. The authors found that MALDI-TOF MS can identify bacteria, fungi, viruses and parasites, even in blood cultures, and also serves to assess antimicrobial resistance. Thus, MALDI-TOF MS can become an indispensable tool in laboratory diagnosis.

MDRSA: A Web Based-Tool for Rapid Identification of Multidrug Resistant Staphylococcus aureus Based on Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry

As antibiotics resistance on superbugs has risen, more and more studies have focused on developing rapid antibiotics susceptibility tests (AST). Meanwhile, identification of multiple antibiotics resistance on Staphylococcus aureus provides instant information which can assist clinicians in administrating the appropriate prescriptions. In recent years, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has emerged as a powerful tool in clinical microbiology laboratories for the rapid identification of bacterial species. Yet, lack of study devoted on providing efficient methods to deal with the MS shifting problem, not to mention to providing tools incorporating the MALDI-TOF MS for the clinical use which deliver the instant administration of antibiotics to the clinicians. In this study, we developed a web tool, MDRSA, for the rapid identification of oxacillin-, clindamycin-, and erythromycin-resistant Staphylococcus aureus. Specifically, the kernel density estimation (KDE) was adopted to deal with the peak shifting problem, which is critical to analyze mass spectra data, and machine learning methods, including decision trees, random forests, and support vector machines, which were used to construct the classifiers to identify the antibiotic resistance. The areas under the receiver operating the characteristic curve attained 0.8 on the internal (10-fold cross validation) and external (independent testing) validation. The promising results can provide more confidence to apply these prediction models in the real world. Briefly, this study provides a web-based tool to provide rapid predictions for the resistance of antibiotics on Staphylococcus aureus based on the MALDI-TOF MS data. The web tool is available at: http://fdblab.csie.ncu.edu.tw/mdrsa/.

A review of surface-enhanced Raman spectroscopy in pathological processes

With the continuous growth of the human population and new challenges in the quality of life, it is more important than ever to diagnose diseases and pathologies with high accuracy, sensitivity and in different scenarios from medical implants to the operation room. Although conventional methods of diagnosis revolutionized healthcare, alternative analytical methods are making their way out of academic labs into clinics. In this regard, surface-enhanced Raman spectroscopy (SERS) developed immensely with its capability to achieve single-molecule sensitivity and high-specificity in the last two decades, and now it is well on its way to join the arsenal of physicians. This review discusses how SERS is becoming an essential tool for the clinical investigation of pathologies including inflammation, infections, necrosis/apoptosis, hypoxia, and tumors. We critically discuss the strategies reported so far in nanoparticle assembly, functionalization, non-metallic substrates, colloidal solutions and how these techniques improve SERS characteristics during pathology diagnoses like sensitivity, selectivity, and detection limit. Moreover, it is crucial to introduce the most recent developments and future perspectives of SERS as a biomedical analytical method. We finally discuss the challenges that remain as bottlenecks for a routine SERS implementation in the medical room from in vitro to in vivo applications. The review showcases the adaptability and versatility of SERS to resolve pathological processes by covering various experimental and analytical methods and the specific spectral features and analysis results achieved by these methods.

MALDI-TOF Mass Spectroscopy Applications in Clinical Microbiology

There is a range of proteomics methods to spot and analyze bacterial protein contents such as liquid chromatography-mass spectrometry (LC-MS), two-dimensional gel electrophoresis, and matrix-assisted laser desorption/ionization mass spectrometry (MALDI-TOF MS), which give comprehensive information about the microorganisms that may be helpful within the diagnosis and coverings of infections. Microorganism identification by mass spectrometry is predicted on identifying a characteristic spectrum of every species so matched with an outsized database within the instrument. MALDI-TOF MS is one of the diagnostic methods, which is a straightforward, quick, and precise technique, and is employed in microbial diagnostic laboratories these days and may replace other diagnostic methods. This method identifies various microorganisms such as bacteria, fungi, parasites, and viruses, which supply comprehensive information. One of the MALDI-TOF MS's crucial applications is bacteriology, which helps identify bacterial species, identify toxins, and study bacterial antibiotic resistance. By knowing these cases, we will act more effectively against bacterial infections.

Crucial roles of different RNA-binding hnRNP proteins in Stem Cells

The self-renewal, pluripotency and differentiation of stem cells are regulated by various genetic and epigenetic factors. As a kind of RNA binding protein (RBP), the heterogeneous nuclear ribonucleoproteins (hnRNPs) can act as "RNA scaffold" and recruit mRNA, lncRNA, microRNA and circRNA to affect mRNA splicing and processing, regulate gene transcription and post-transcriptional translation, change genome structure, and ultimately play crucial roles in the biological processes of cells. Recent researches have demonstrated that hnRNPs are irreplaceable for self-renewal and differentiation of stem cells. hnRNPs function in stem cells by multiple mechanisms, which include regulating mRNA stability, inducing alternative splicing of mRNA, epigenetically regulate gene expression, and maintaining telomerase activity and telomere length. The functions and the underlying mechanisms of hnRNPs in stem cells deserve further investigation.

A Sample-to-Report Solution for Taxonomic Identification of Cultured Bacteria in the Clinical Setting Based on Nanopore Sequencing

Amplicon sequencing of the 16S rRNA gene is commonly used for the identification of bacterial isolates in diagnostic laboratories and mostly relies on the Sanger sequencing method. The latter, however, suffers from a number of limitations, with the most significant being the inability to resolve mixed amplicons when closely related species are coamplified from a mixed culture. This often leads to either increased turnaround time or absence of usable sequence data. Short-read next-generation sequencing (NGS) technologies could solve the mixed amplicon issue but would lack both cost efficiency at low throughput and fast turnaround times. Nanopore sequencing developed by Oxford Nanopore Technologies (ONT) could solve those issues by enabling a flexible number of samples per run and an adjustable sequencing time. Here, we report on the development of a standardized laboratory workflow combined with a fully automated analysis pipeline LORCAN (long read consensus analysis), which together provide a sample-to-report solution for amplicon sequencing and taxonomic identification of the resulting consensus sequences. Validation of the approach was conducted on a panel of reference strains and on clinical samples consisting of single or mixed rRNA amplicons associated with various bacterial genera by direct comparison to the corresponding Sanger sequences. Additionally, simulated read and amplicon mixtures were used to assess LORCAN's behavior when dealing with samples with known cross-contamination levels. We demonstrate that by combining ONT amplicon sequencing results with LORCAN, the accuracy of Sanger sequencing can be closely matched (>99.6% sequence identity) and that mixed samples can be resolved at the single-base resolution level. The presented approach has the potential to significantly improve the flexibility, reliability, and availability of amplicon sequencing in diagnostic settings.