Biomarker- and similarity coefficient-based approaches to bacterial mixture characterization using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS)

Rapid and accurate identification of yeast subspecies by MALDI-MS combined with a cell membrane disruption reagent

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) has been widely used for microbial analysis. However, due to the impenetrable shell of fungi the direct identification of fungi remains challenges. Targeting on this problem, the yeast Saccharomyces cerevisiae (S. cerevisiae) was selected as a model fungus, and a new fungal cell membrane disruption reagent C18-G1 was used before MALDI-MS detection. As a result, much more intensive peaks which distributed in wider m/z range of S. cerevisiae have been identified in comparison with the use of traditional fungal pretreatment methods. Furthermore, a differential peak at m/z 4993 between two subspecies of S. cerevisiae has been identified. The corresponding protein with exclusive sequence of the specific peak was obtained based on MS/MS fragments and database searching. In addition, the method was successfully applied for the discrimination of four commercial yeasts.

Fusion data from FT-IR and MALDI-TOF MS result in more accurate classification of specific microbiota

Microbes are usually present as a specific microbiota, and their classification remains a challenge. MALDI-TOF MS is particularly successful in library-based microbial identification at the species level as it analyzes the molecular weight of peptides and ribosomal proteins. FT-IR allows more accurate classification of bacteria at the subspecies level due to the high sensitivity, specificity and repeatability of FT-IR signals from bacteria, which is not achievable with MALDI-TOF MS. Previous studies have shown that more accurate identification results can be obtained by the fusion of FT-IR and MALDI-TOF MS spectral data. Here, we constructed 20 groups of model microbiota samples and used FT-IR, MALDI-TOF MS, and their fusion data to classify them. Hierarchical clustering analysis (HCA) showed that the classification accuracy of FT-IR, MALDI-TOF MS, and the fusion data was 85%, 90%, and 100%, respectively. These results indicate that both FT-IR and MALDI-TOF MS can effectively classify specific microbiota, and the fusion of their spectral data could improve the classification accuracy. The FT-IR and MALDI-TOF MS data fusion strategy may be a promising technology for specific microbiota classification.

MALDI-TOF MS Is an Effective Technique To Classify Specific Microbiota

MALDI-TOF MS is well-recognized for single microbial identification and widely used in research and clinical fields due to its specificity, speed of analysis, and low cost of consumables. Multiple commercial platforms have been developed and approved by the U.S. Food and Drug Administration. Matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) has been used for microbial identification. However, microbes can present as a specific microbiota, and detection and classification remain a challenge. Here, we constructed several specific microbiotas and tried to classify them using MALDI-TOF MS. Different concentrations of nine bacterial strains (belonging to eight genera) constituted 20 specific microbiotas. Using MALDI-TOF MS, the overlap spectrum of each microbiota (MS spectra of nine bacterial strains with component percentages) could be classified by hierarchical clustering analysis (HCA). However, the real MS spectrum of a specific microbiota was different than that of the overlap spectrum of component bacteria. The MS spectra of specific microbiota showed excellent repeatability and were easier to classify by HCA, with an accuracy close to 90%. These results indicate that the widely used MALDI-TOF MS identification method for individual bacteria can be expanded to classification of microbiota. IMPORTANCE MALDI-TOF MS can be used to classify specific model microbiota. The actual MS spectrum of the model microbiota was not a simple superposition of every single bacterium in a certain proportion but had a specific spectral fingerprint. The specificity of this fingerprint can enhance the accuracy of microbiota classification.

Sample preparation and culture condition effects on MALDI-TOF MS identification of bacteria: A review

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is an excellent tool for bacterial identification. It allows high throughput, sensitive and specific applications in clinical diagnostics and environmental research. Currently, there is no optimal standardized protocol for sample preparation and culture conditions to profile bacteria. The performance of MALDI-TOF MS is affected by several variables, such as sample preparation, culture media and culture conditions, incubation time/growth stage, incubation temperature, high salt content, blood in the culture media, and others. This review thus aims to clarify why a uniformed protocol is not plausible, to assess the effects these factors have on MALDI-TOF MS identification score, and discuss possible optimizations for its methodology, in relation to specific bacterial representatives and strain requirements.

Strain-level epidemiology of microbial communities and the human microbiome

The biological importance and varied metabolic capabilities of specific microbial strains have long been established in the scientific community. Strains have, in the past, been largely defined and characterized based on microbial isolates. However, the emergence of new technologies and techniques has enabled assessments of their ecology and phenotypes within microbial communities and the human microbiome. While it is now more obvious how pathogenic strain variants are detrimental to human health, the consequences of subtle genetic variation in the microbiome have only recently been exposed. Here, we review the operational definitions of strains (e.g., genetic and structural variants) as they can now be identified from microbial communities using different high-throughput, often culture-independent techniques. We summarize the distribution and diversity of strains across the human body and their emerging links to health maintenance, disease risk and progression, and biochemical responses to perturbations, such as diet or drugs. We list methods for identifying, quantifying, and tracking strains, utilizing high-throughput sequencing along with other molecular and “culturomics” technologies. Finally, we discuss implications of population studies in bridging experimental gaps and leading to a better understanding of the health effects of strains in the human microbiome.

Identification of mixed and successive blood meals of mosquitoes using MALDI-TOF MS protein profiling

BACKGROUND

The accurate and rapid identification of mosquito blood meals is critical to study the interactions between vectors and vertebrate hosts and, subsequently, to develop vector control strategies. Recently, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiling has been shown to be a reliable and effective tool for identifying single blood meals from mosquitoes.

METHODS

In this study, we developed MALDI-TOF MS profiling protocols to identify Anopheles gambiae Giles, Anopheles coluzzii and Aedes albopictus mosquitoes' mixed blood meals and the last of successive blood meals. The mosquitoes were either successively artificially fed with distinct host bloods or engorged with mixed bloods from distinct vertebrate hosts, such as humans, sheep and dogs.

RESULTS

Blind test analyses revealed a correct identification of mixed blood meals from mosquitoes using MALDI-TOF MS profiling. The 353 MS spectra from mixed blood meals were identified using log score values >1.8. All MS spectra (n = 244) obtained from mosquitoes' successive blood meals were reproducible and specific to the last blood meal, suggesting that the previous blood meals do not have an impact on the identification of the last one.

CONCLUSION

MALDI-TOF MS profiling approach appears to be an effective and robust technique to identify the last and mixed blood meals during medical entomological surveys.

Identification performance of MALDI-ToF-MS upon mono- and bi-microbial cultures is cell number and culture proportion dependent

Biotyping using matrix-assisted laser desorption ionization-time of flight (MALDI-ToF) mass spectroscopy (MS) has revolutionized microbiology by allowing clinicians and scientists to rapidly identify microbes at genus and species levels. The present study extensively assesses the suitability and reliability of MALDI-ToF biotyping of 14 different aerobic and anaerobic bacterial species as pure and mixed cultures. Reliable identification at species level was possible from biomaterial of older colonies and even frozen biomaterial, although this was species dependent. Using standard instrument settings and direct application of biomaterial onto the MALDI-ToF target plates, it was determined that the cell densities necessary for completely reliable identification of pure cultures varied between 2.40 × 10⁸ and 1.10 × 10¹⁰ viable cell counts (VCCs) per mL, depending on the species. Evaluation of the mixed culture algorithm of the Bruker Biotyper^® software showed that the performance of the algorithm depends greatly on the targeted species, on their phylogenetic distance, and on their ratio of VCC per mL in the mixed culture. Hence, the use of MALDI-ToF-MS with incorporation of the mixed culture algorithm of the software is a useful pre-screening tool for early identification of contaminants, but due to the great variability in performance between different species and the usually unknown percentage of the possible contaminant in the mixture, it is advisable to combine this method with other microbiology methods.

Rapid dereplication of microbial isolates using matrix-assisted laser desorption ionization time-of-flight mass spectrometry: A mini-review

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MALDI-TOF MS is applicable as high-resolution and high-throughput tool.

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The classification and characterization of cultivable microorganisms is targeted.

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Advantageous are its simple sample preparation and short measurement time.

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It accelerates the dereplication of isolates from large-scale screening campaigns.

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Applications for studying microbial diversity and future trends are discussed.

Matrix-Assisted Laser Desorption Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) has become one of the most popular methods for the rapid, cost-effective and accurate classification and characterization of cultivable microorganisms. Due to its simple sample preparation and short measurement time, MALDI-TOF MS is an excellent choice for the high-throughput study of microbial isolates from rhizospheres or plants grown under diverse environmental conditions. While clinical isolates have a higher identification rate than environmental isolates due to the focus of commercial mass spectral libraries on the former, no identification is necessary in the dereplication step of large environmental studies. The grouping of large sets of isolates according to their intact protein profiles can be performed without knowledge of their taxonomy. Thus, this method is easily applicable to environmental samples containing microorganisms from yet undescribed phylogenetic origins. The main strategies applied to achieve effective dereplication are, first, expanding existing mass spectral libraries and, second, using an additional statistical analysis step to group measured mass spectra and identify unique isolates. In this review, these aspects are addressed. It closes with a prospective view on how MALDI-TOF MS-based microbial characterisation can accelerate the exploitation of plant-associated microbiota.

Comparing genome versus proteome-based identification of clinical bacterial isolates

Whole-genome sequencing (WGS) is gaining importance in the analysis of bacterial cultures derived from patients with infectious diseases. Existing computational tools for WGS-based identification have, however, been evaluated on previously defined data relying thereby unwarily on the available taxonomic information.Here, we newly sequenced 846 clinical gram-negative bacterial isolates representing multiple distinct genera and compared the performance of five tools (CLARK, Kaiju, Kraken, DIAMOND/MEGAN and TUIT). To establish a faithful 'gold standard', the expert-driven taxonomy was compared with identifications based on matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) analysis. Additionally, the tools were also evaluated using a data set of 200 Staphylococcus aureus isolates.CLARK and Kraken (with k =31) performed best with 626 (100%) and 193 (99.5%) correct species classifications for the gram-negative and S. aureus isolates, respectively. Moreover, CLARK and Kraken demonstrated highest mean F-measure values (85.5/87.9% and 94.4/94.7% for the two data sets, respectively) in comparison with DIAMOND/MEGAN (71 and 85.3%), Kaiju (41.8 and 18.9%) and TUIT (34.5 and 86.5%). Finally, CLARK, Kaiju and Kraken outperformed the other tools by a factor of 30 to 170 fold in terms of runtime.We conclude that the application of nucleotide-based tools using k-mers-e.g. CLARK or Kraken-allows for accurate and fast taxonomic characterization of bacterial isolates from WGS data. Hence, our results suggest WGS-based genotyping to be a promising alternative to the MS-based biotyping in clinical settings. Moreover, we suggest that complementary information should be used for the evaluation of taxonomic classification tools, as public databases may suffer from suboptimal annotations.

Clinical Mass Spectrometry in the Bioinformatics Era: A Hitchhiker's Guide

Mass spectrometry (MS) is a sensitive, specific and versatile analytical technique in the clinical laboratory that has recently undergone rapid development. From initial use in metabolic profiling, it has matured into applications including clinical toxicology assays, target hormone and metabolite quantitation, and more recently, rapid microbial identification and antimicrobial resistance detection by matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). In this mini-review, we first succinctly outline the basics of clinical mass spectrometry. Examples of hard ionization (electron ionization) and soft ionization (electrospray ionization, MALDI) are presented to demonstrate their clinical applications. Next, a conceptual discourse on mass selection and determination is presented: quadrupole mass filter, time-of-flight mass spectrometer and the Orbitrap; and MS/MS (tandem-in-space, tandem-in-time and data acquisition), illustrated with clinical examples. Current applications in (1) bacterial and fungal identification, antimicrobial susceptibility testing and phylogenetic classification, (2) general unknown urine toxicology screening and expanded new-born metabolic screening and (3) clinical metabolic profiling by gas chromatography are outlined. Finally, major limitations of MS-based techniques, including the technical challenges of matrix effect and isobaric interference; and novel challenges in the post-genomic era, such as protein molecular variants, are critically discussed from the perspective of service laboratories. Computer technology and structural biology have played important roles in the maturation of this field. MS-based techniques have the potential to replace current analytical techniques, and existing expertise and instrument will undergo rapid evolution. Significant automation and adaptation to regulatory requirements are underway. Mass spectrometry is unleashing its potentials in clinical laboratories.

Direct MALDI-TOF MS Identification of Bacterial Mixtures

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is now widely used to characterize bacterial samples for clinical diagnosis, food safety control, environmental monitoring, and so on. However, existing standard approaches are only applied to analyze single colonies purified by plate culture, which limits the approaches to cultivable bacteria and makes the whole approaches time-consuming. In this work, we propose a new framework to analyze MALDI-TOF spectra of bacterial mixtures and to directly characterize each component without purification procedures. The framework is a combination of a synthetic mixture model based on a non-negative linear combination of candidate reference spectra and a statistical assessment by in silico generated spectra via a jackknife resampling. Ninety-seven model bacterial mixture samples and 8 cocultured blind-coded bacterial mixture samples, containing up to 6 strains in varied ratios in each sample, together with a reference database containing the mass spectra of 1081 strains, were used to validate the framework. High sensitivity (>80%, with error rate <5%) was achieved for balanced binary and ternary mixtures. The sensitivity was >60% for balanced quaternary and pentabasic mixtures, and 48%-71% for asymmetric situation, with error rate <5%. The work can facilitate rapid and reliable characterization of bacterial mixtures without purification procedures, which is of practical value in clinical diagnosis, food safety control, environmental monitoring, and so on. The framework can be further applied to many other spectroscopy-based analytics to interpret spectra from mixed samples.

Characterization of microbial mixtures by mass spectrometry

MS applications in microbiology have increased significantly in the past 10 years, due in part to the proliferation of regulator-approved commercial MALDI MS platforms for rapid identification of clinical infections. In parallel, with the expansion of MS technologies in the "omics" fields, novel MS-based research efforts to characterize organismal as well as environmental microbiomes have emerged. Successful characterization of microorganisms found in complex mixtures of other organisms remains a major challenge for researchers and clinicians alike. Here, we review recent MS advances toward addressing that challenge. These include sample preparation methods and protocols, and established, for example, MALDI, as well as newer, for example, atmospheric pressure ionization (API) techniques. MALDI mass spectra of intact cells contain predominantly information on the highly expressed house-keeping proteins used as biomarkers. The API methods are applicable for small biomolecule analysis, for example, phospholipids and lipopeptides, and facilitate species differentiation. MS hardware and techniques, for example, tandem MS, including diverse ion source/mass analyzer combinations are discussed. Relevant examples for microbial mixture characterization utilizing these combinations are provided. Chemometrics and bioinformatics methods and algorithms, including those applied to large scale MS data acquisition in microbial metaproteomics and MS imaging of biofilms, are highlighted. Select MS applications for polymicrobial culture analysis in environmental and clinical microbiology are reviewed as well.

Improving Phylogeny Reconstruction at the Strain Level Using Peptidome Datasets

Typical bacterial strain differentiation methods are often challenged by high genetic similarity between strains. To address this problem, we introduce a novel in silico peptide fingerprinting method based on conventional wet-lab protocols that enables the identification of potential strain-specific peptides. These can be further investigated using in vitro approaches, laying a foundation for the development of biomarker detection and application-specific methods. This novel method aims at reducing large amounts of comparative peptide data to binary matrices while maintaining a high phylogenetic resolution. The underlying case study concerns the Bacillus cereus group, namely the differentiation of Bacillus thuringiensis, Bacillus anthracis and Bacillus cereus strains. Results show that trees based on cytoplasmic and extracellular peptidomes are only marginally in conflict with those based on whole proteomes, as inferred by the established Genome-BLAST Distance Phylogeny (GBDP) method. Hence, these results indicate that the two approaches can most likely be used complementarily even in other organismal groups. The obtained results confirm previous reports about the misclassification of many strains within the B. cereus group. Moreover, our method was able to separate the B. anthracis strains with high resolution, similarly to the GBDP results as benchmarked via Bayesian inference and both Maximum Likelihood and Maximum Parsimony. In addition to the presented phylogenomic applications, whole-peptide fingerprinting might also become a valuable complementary technique to digital DNA-DNA hybridization, notably for bacterial classification at the species and subspecies level in the future.

Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass-Spectrometry (MALDI-TOF MS) Based Microbial Identifications: Challenges and Scopes for Microbial Ecologists

Matrix-assisted laser desorption/ionization time-of-flight mass-spectrometry (MALDI-TOF MS) based biotyping is an emerging technique for high-throughput and rapid microbial identification. Due to its relatively higher accuracy, comprehensive database of clinically important microorganisms and low-cost compared to other microbial identification methods, MALDI-TOF MS has started replacing existing practices prevalent in clinical diagnosis. However, applicability of MALDI-TOF MS in the area of microbial ecology research is still limited mainly due to the lack of data on non-clinical microorganisms. Intense research activities on cultivation of microbial diversity by conventional as well as by innovative and high-throughput methods has substantially increased the number of microbial species known today. This important area of research is in urgent need of rapid and reliable method(s) for characterization and de-replication of microorganisms from various ecosystems. MALDI-TOF MS based characterization, in our opinion, appears to be the most suitable technique for such studies. Reliability of MALDI-TOF MS based identification method depends mainly on accuracy and width of reference databases, which need continuous expansion and improvement. In this review, we propose a common strategy to generate MALDI-TOF MS spectral database and advocated its sharing, and also discuss the role of MALDI-TOF MS based high-throughput microbial identification in microbial ecology studies.