Identification of pathogens from native urine samples by MALDI-TOF/TOF tandem mass spectrometry

Characterization of the internal working-life exposome using minimally and non-invasive sampling methods - a narrative review

During recent years, we are moving away from the 'one exposure, one disease'-approach in occupational settings and towards a more comprehensive approach, taking into account the totality of exposures during a life course by using an exposome approach. Taking an exposome approach however is accompanied by many challenges, one of which, for example, relates to the collection of biological samples. Methods used for sample collection in occupational exposome studies should ideally be minimally invasive, while at the same time sensitive, and enable meaningful repeated sampling in a large population and over a longer time period. This might be hampered in specific situations e.g., people working in remote areas, during pandemics or with flexible work hours. In these situations, using self-sampling techniques might offer a solution. Therefore, our aim was to identify existing self-sampling techniques and to evaluate the applicability of these techniques in an occupational exposome context by conducting a literature review. We here present an overview of current self-sampling methodologies used to characterize the internal exposome. In addition, the use of different biological matrices was evaluated and subdivided based on their level of invasiveness and applicability in an occupational exposome context. In conclusion, this review and the overview of self-sampling techniques presented herein can serve as a guide in the design of future (occupational) exposome studies while circumventing sample collection challenges associated with exposome studies.

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.

Current Viewpoint on Female Urogenital Microbiome-The Cause or the Consequence?

An increasing amount of evidence implies that native microbiota is a constituent part of a healthy urinary tract (UT), making it an ecosystem on its own. What is still not clear is whether the origin of the urinary microbial community is the indirect consequence of the more abundant gut microbiota or a more distinct separation exists between these two systems. Another area of uncertainty is the existence of a link between the shifts in UT microbial composition and both the onset and persistence of cystitis symptoms. Cystitis is one of the most common reasons for antimicrobial drugs prescriptions in primary and secondary care and an important contributor to the problem of antimicrobial resistance. Despite this fact, we still have trouble distinguishing whether the primary cause of the majority of cystitis cases is a single pathogen overgrowth or a systemic disorder affecting the entire urinary microbiota. There is an increasing trend in studies monitoring changes and dynamics of UT microbiota, but this field of research is still in its infancy. Using NGS and bioinformatics, it is possible to obtain microbiota taxonomic profiles directly from urine samples, which can provide a window into microbial diversity (or the lack of) underlying each patient's cystitis symptoms. However, while microbiota refers to the living collection of microorganisms, an interchangeably used term microbiome referring to the genetic material of the microbiota is more often used in conjunction with sequencing data. It is this vast amount of sequences, which are truly "Big Data", that allow us to create models that describe interactions between different species contributing to an UT ecosystem, when coupled with machine-learning techniques. Although in a simplified predator-prey form these multi-species interaction models have the potential to further validate or disprove current beliefs; whether it is the presence or the absence of particular key players in a UT microbial ecosystem, the exact cause or consequence of the otherwise unknown etiology in the majority of cystitis cases. These insights might prove to be vital in our ongoing struggle against pathogen resistance and offer us new and promising clinical markers.

Rapid Pathogen Identification in Aqueous Humor Samples by Combining Fc-MBL@Fe3O4 Enrichment and Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry Profiling

Prompt clinical diagnosis and antimicrobial therapy are key to managing infective endophthalmitis. The small volume of aqueous humor, low bacterial counts, and empirical medication by physicians make existing diagnostic methods time-consuming and imprecise. Here, we investigated the feasibility of combining Fc-containing mannose-binding lectin-coated Fe₃O₄ (Fc-MBL@Fe₃O₄) enrichment with matrix-assisted laser desorption-ionization time of flight mass spectrometry (MALDI-TOF MS) profiling to identify pathogens in aqueous humor. Aqueous humor aspirated from freshly enucleated porcine eyes was treated with different inocula of Staphylococcus aureus, Staphylococcus epidermidis, and Klebsiella pneumoniae. We performed identification directly in aqueous humor samples and after short-term culture of micro-LB broth. Aqueous humor endophthalmitis samples were enriched with Fc-MBL@Fe₃O₄ and analyzed using MALDI-TOF MS. The identification time and minimum bacterial concentration required for identification were determined. The enrichment efficiency of Fc-MBL@Fe₃O₄ for different bacteria was greater than (87.5 ± 5.0)%. The objects of direct identification include live bacteria and bacteria treated with antibiotics, which can be completed within 1.5 h. The minimum number of bacteria needed for positive identification was 2.20 × 10⁶ CFU. For micro-LB broth culture, the identification of bacteria can be completed within 6.5 to 9.5 h for aqueous humor samples with an initial bacterial count of tens to hundreds. IMPORTANCE Fc-MBL@Fe₃O₄ capture not only live bacteria in aqueous humor but also bacteria inactivated by antibiotics. Fc-MBL@Fe₃O₄ combined with micro-LB broth culture significantly reduced the turnaround time (TAT) by more than half a day by shortening the time required for bacterial identification. Our findings demonstrate that combining Fc-MBL@Fe₃O₄ enrichment with MALDI-TOF MS identification is a fast, sensitive, and efficient analytical method with great potential for identifying pathogens in aqueous humor samples.

Proteomics approaches: A review regarding an importance of proteome analyses in understanding the pathogens and diseases

Proteomics is playing an increasingly important role in identifying pathogens, emerging and re-emerging infectious agents, understanding pathogenesis, and diagnosis of diseases. Recently, more advanced and sophisticated proteomics technologies have transformed disease diagnostics and vaccines development. The detection of pathogens is made possible by more accurate and time-constrained technologies, resulting in an early diagnosis. More detailed and comprehensive information regarding the proteome of any noxious agent is made possible by combining mass spectrometry with various gel-based or short-gun proteomics approaches recently. MALDI-ToF has been proved quite useful in identifying and distinguishing bacterial pathogens. Other quantitative approaches are doing their best to investigate bacterial virulent factors, diagnostic markers and vaccine candidates. Proteomics is also helping in the identification of secreted proteins and their virulence-related functions. This review aims to highlight the role of cutting-edge proteomics approaches in better understanding the functional genomics of pathogens. This also underlines the limitations of proteomics in bacterial secretome research.

Applications of MALDI-MS/MS-Based Proteomics in Biomedical Research

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) is one of the most widely used techniques in proteomics to achieve structural identification and characterization of proteins and peptides, including their variety of proteoforms due to post-translational modifications (PTMs) or protein–protein interactions (PPIs). MALDI-MS and MALDI tandem mass spectrometry (MS/MS) have been developed as analytical techniques to study small and large molecules, offering picomole to femtomole sensitivity and enabling the direct analysis of biological samples, such as biofluids, solid tissues, tissue/cell homogenates, and cell culture lysates, with a minimized procedure of sample preparation. In the last decades, structural identification of peptides and proteins achieved by MALDI-MS/MS helped researchers and clinicians to decipher molecular function, biological process, cellular component, and related pathways of the gene products as well as their involvement in pathogenesis of diseases. In this review, we highlight the applications of MALDI ionization source and tandem approaches for MS for analyzing biomedical relevant peptides and proteins. Furthermore, one of the most relevant applications of MALDI-MS/MS is to provide “molecular pictures”, which offer in situ information about molecular weight proteins without labeling of potential targets. Histology-directed MALDI-mass spectrometry imaging (MSI) uses MALDI-ToF/ToF or other MALDI tandem mass spectrometers for accurate sequence analysis of peptide biomarkers and biological active compounds directly in tissues, to assure complementary and essential spatial data compared with those obtained by LC-ESI-MS/MS technique.

Native top-down mass spectrometry for higher-order structural characterization of proteins and complexes

Progress in structural biology research has led to a high demand for powerful and yet complementary analytical tools for structural characterization of proteins and protein complexes. This demand has significantly increased interest in native mass spectrometry (nMS), particularly native top-down mass spectrometry (nTDMS) in the past decade. This review highlights recent advances in nTDMS for structural research of biological assemblies, with a particular focus on the extra multi-layers of information enabled by TDMS. We include a short introduction of sample preparation and ionization to nMS, tandem fragmentation techniques as well as mass analyzers and software/analysis pipelines used for nTDMS. We highlight unique structural information offered by nTDMS and examples of its broad range of applications in proteins, protein-ligand interactions (metal, cofactor/drug, DNA/RNA, and protein), therapeutic antibodies and antigen-antibody complexes, membrane proteins, macromolecular machineries (ribosome, nucleosome, proteosome, and viruses), to endogenous protein complexes. The challenges, potential, along with perspectives of nTDMS methods for the analysis of proteins and protein assemblies in recombinant and biological samples are discussed.

Pathobionts: mechanisms of survival, expansion, and interaction with host with a focus on Clostridioides difficile

Pathobionts are opportunistic microbes that emerge as a result of perturbations in the healthy microbiome due to complex interactions of various genetic, exposomal, microbial, and host factors that lead to their selection and expansion. Their proliferations can aggravate inflammatory manifestations, trigger autoimmune diseases, and lead to severe life-threatening conditions. Current surge in microbiome research is unwinding these complex interplays between disease development and protection against pathobionts. This review summarizes the current knowledge of pathobiont emergence with a focus on Clostridioides difficile and the recent findings on the roles of immune cells such as iTreg cells, Th17 cells, innate lymphoid cells, and cytokines in protection against pathobionts. The review calls for adoption of innovative tools and cutting-edge technologies in clinical diagnostics and therapeutics to provide insights in identification and quantification of pathobionts.

New Microbiological Techniques for the Diagnosis of Bacterial Infections and Sepsis in ICU Including Point of Care

Purpose of Review

The aim of this article is to review current and emerging microbiological techniques that support the rapid diagnosis of bacterial infections in critically ill patients, including their performance, strengths and pitfalls, as well as available data evaluating their clinical impact.

Recent Findings

Bacterial infections and sepsis are responsible for significant morbidity and mortality in patients admitted to the intensive care unit and their management is further complicated by the increase in the global burden of antimicrobial resistance. In this setting, new diagnostic methods able to overcome the limits of traditional microbiology in terms of turn-around time and accuracy are highly warranted. We discuss the following broad themes: optimisation of existing culture-based methodologies, rapid antigen detection, nucleic acid detection (including multiplex PCR assays and microarrays), sepsis biomarkers, novel methods of pathogen detection (e.g. T2 magnetic resonance) and susceptibility testing (e.g. morphokinetic cellular analysis) and the application of direct metagenomics on clinical samples. The assessment of the host response through new “omics” technologies might also aid in early diagnosis of infections, as well as define non-infectious inflammatory states.

Summary

Despite being a promising field, there is still scarce evidence about the real-life impact of these assays on patient management. A common finding of available studies is that the performance of rapid diagnostic strategies highly depends on whether they are integrated within active antimicrobial stewardship programs. Assessing the impact of these emerging diagnostic methods through patient-centred clinical outcomes is a complex challenge for which large and well-designed studies are awaited.

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.

CD5L as an Extracellular Vesicle-Derived Biomarker for Liquid Biopsy of Lung Cancer

Cancer screening and diagnosis can be achieved by analyzing specific molecules within serum-derived extracellular vesicles (EVs). This study sought to profile EV-derived proteins to identify potential lung cancer biomarkers. EVs were isolated from 80 serum samples from healthy individuals and cancer patients via polyethylene glycol (PEG)-based precipitation and immunoaffinity separation using antibodies against CD9, CD63, CD81, and EpCAM. Proteomic analysis was performed using 2-D gel electrophoresis and matrix-assisted laser desorption ionization–time-of-flight mass spectrometry (MALDI–TOF MS). The expression of proteins that were differentially upregulated in the EVs or tissue of lung cancer samples was validated by Western blotting. The area under the curve (AUC) was calculated to assess the predictability of each differentially expressed protein (DEP) for lung cancer. A total of 55 upregulated protein spots were selected, seven of which (CD5L, CLEC3B, ITIH4, SERFINF1, SAA4, SERFINC1, and C20ORF3) were found to be expressed at high levels in patient-derived EVs by Western blotting. Meanwhile, only the expression of EV CD5L correlated with that in cancer tissues. CD5L also demonstrated the highest AUC value (0.943) and was found to be the core regulator in a pathway related to cell dysfunction. Cumulatively, these results show that EV-derived CD5L may represent a potential biomarker—detected via a liquid biopsy—for the noninvasive diagnosis of lung cancer.

Modeling of Urinary Microbiota Associated With Cystitis

A decade ago, when the Human Microbiome Project was starting, urinary tract (UT) was not included because the bladder and urine were considered to be sterile. Today, we are presented with evidence that healthy UT possesses native microbiota and any major event disrupting its “equilibrium” can impact the host also. This dysbiosis often leads to cystitis symptoms, which is the most frequent lower UT complaint, especially among women. Cystitis is one of the most common causes of antimicrobial drugs prescriptions in primary and secondary care and an important contributor to the problem of antimicrobial resistance. Despite this fact, we still have trouble distinguishing whether the primary cause of majority of cystitis cases is a single pathogen overgrowth, or a systemic disorder affecting entire UT microbiota. There are relatively few studies monitoring changes and dynamics of UT microbiota in cystitis patients, making this field of research still an unknown. In this study variations to the UT microbiota of cystitis patients were identified and microbial dynamics has been modeled. The microbial genetic profile of urine samples from 28 patients was analyzed by 16S rDNA Illumina sequencing and bioinformatics analysis. One patient with bacterial cystitis symptoms was prescribed therapy based on national guideline recommendations on antibacterial treatment of urinary tract infections (UTI) and UT microbiota change was monitored by 16S rDNA sequencing on 24 h basis during the entire therapy duration. The results of sequencing implied that a particular class of bacteria is associated with majority of cystitis cases in this study. The contributing role of this class of bacteria – Gammaproteobacteria, was further predicted by generalized Lotka-Volterra modeling (gLVM). Longitudinal microbiota insight obtained from a single patient under prescribed antimicrobial therapy revealed rapid and extensive changes in microbial composition and emphasized the need for current guidelines revision in regards to therapy duration. Models based on gLVM indicated protective role of two taxonomic classes of bacteria, Actinobacteria and Bacteroidia class, which appear to actively suppress pathogen overgrowth.