Early and specific targeted mass spectrometry-based identification of bacteria in endotracheal aspirates of patients suspected with ventilator-associated pneumonia.

Rapid and reliable pathogen identification is compulsory to confirm ventilator-associated pneumonia (VAP) in order to initiate appropriate antibiotic treatment. In the present proof of concept, the effectiveness of rapid microorganism identification with a targeted bottom-up proteomics approach was investigated in endotracheal aspirate (ETA) samples of VAP patients. To do so, a prototype selected-reaction monitoring (SRM)-based assay was developed on a triple quadrupole mass spectrometer tracking proteotypic peptide surrogates of bacterial proteomes. Through the concurrent monitoring of 97 species-specific peptides, this preliminary assay was dimensioned to characterize the occurrence of six most frequent bacterial species responsible for over more than 65% of VAP. Assay performance was subsequently evaluated by analyzing early and regular 37 ETA samples collected from 15 patients. Twenty-five samples were above the significant threshold of 105 CFU/mL and five samples showed mixed infections (both pathogens ≥ 105 CFU/mL). The targeted proteomics assay showed 100% specificity for Acinetobacter baumannii, Escherichia coli, Haemophilus influenzae, Pseudomonas aeruginosa, Staphylococcus aureus, and Streptococcus pneumoniae. No false bacterial identification was reported and no interference was detected arising from the commensal flora. The overall species identification sensitivity was 19/25 (76%) and was higher at the patient level (84.6%). This successful proof of concept provides a rational to broaden the panel of bacteria for further clinical evaluation.

An update on the routine application of MALDI-TOF MS in clinical microbiology.

Introduction: Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has entered clinical diagnostics and is today a generally accepted and integral part of the workflow for microbial identification. MALDI-TOF MS identification systems received approval from national and international institutions, such as the USA-FDA, and are continuously improved and adopted to other fields like veterinary and industrial microbiology. The question is whether MALDI-TOF MS also has the potential to replace other conventional and molecular techniques operated in routine diagnostic laboratories. Areas covered: We give an overview of new advancements of mass spectral analysis in the context of microbial diagnostics. In particular, the expansion of databases to increase the range of readily identifiable bacteria and fungi, the refined discrimination of species complexes, subspecies, and types, the testing for antibiotic resistance or susceptibility, progress in sample preparation including automation, and applications of other mass spectrometry techniques are discussed. Expert opinion: Although many new approaches of MALDI-TOF MS are still in the stage of proof of principle, it is expectable that MALDI-TOF MS will expand its role in the clinical microbiology laboratory of the future. New databases, instruments and analytical software modules will continue to be developed to further improve diagnostic efficacy.

Linear MALDI-ToF simultaneous spectrum deconvolution and baseline removal.

BACKGROUND: Thanks to a reasonable cost and simple sample preparation procedure, linear MALDI-ToF spectrometry is a growing technology for clinical microbiology. With appropriate spectrum databases, this technology can be used for early identification of pathogens in body fluids. However, due to the low resolution of linear MALDI-ToF instruments, robust and accurate peak picking remains a challenging task. In this context we propose a new peak extraction algorithm from raw spectrum. With this method the spectrum baseline and spectrum peaks are processed jointly. The approach relies on an additive model constituted by a smooth baseline part plus a sparse peak list convolved with a known peak shape. The model is then fitted under a Gaussian noise model. The proposed method is well suited to process low resolution spectra with important baseline and unresolved peaks. RESULTS: We developed a new peak deconvolution procedure. The paper describes the method derivation and discusses some of its interpretations. The algorithm is then described in a pseudo-code form where the required optimization procedure is detailed. For synthetic data the method is compared to a more conventional approach. The new method reduces artifacts caused by the usual two-steps procedure, baseline removal then peak extraction. Finally some results on real linear MALDI-ToF spectra are provided. CONCLUSIONS: We introduced a new method for peak picking, where peak deconvolution and baseline computation are performed jointly. On simulated data we showed that this global approach performs better than a classical one where baseline and peaks are processed sequentially. A dedicated experiment has been conducted on real spectra. In this study a collection of spectra of spiked proteins were acquired and then analyzed. Better performances of the proposed method, in term of accuracy and reproductibility, have been observed and validated by an extended statistical analysis.

Variance component analysis to assess protein quantification in biomarker validation: application to selected reaction monitoring-mass spectrometry.

BACKGROUND: In the field of biomarker validation with mass spectrometry, controlling the technical variability is a critical issue. In selected reaction monitoring (SRM) measurements, this issue provides the opportunity of using variance component analysis to distinguish various sources of variability. However, in case of unbalanced data (unequal number of observations in all factor combinations), the classical methods cannot correctly estimate the various sources of variability, particularly in presence of interaction. The present paper proposes an extension of the variance component analysis to estimate the various components of the variance, including an interaction component in case of unbalanced data. RESULTS: We applied an experimental design that uses a serial dilution to generate known relative protein concentrations and estimated these concentrations by two processing algorithms, a classical and a more recent one. The extended method allowed estimating the variances explained by the dilution and the technical process by each algorithm in an experiment with 9 proteins: L-FABP, 14.3.3 sigma, Calgi, Def.A6, Villin, Calmo, I-FABP, Peroxi-5, and S100A14. Whereas, the recent algorithm gave a higher dilution variance and a lower technical variance than the classical one in two proteins with three peptides (L-FABP and Villin), there were no significant difference between the two algorithms on all proteins. CONCLUSIONS: The extension of the variance component analysis was able to estimate correctly the variance components of protein concentration measurement in case of unbalanced design.

Deciphering Multifactorial Resistance Phenotypes in Acinetobacter baumannii by Genomics and Targeted Label-free Proteomics.

Resistance to ß-lactams in Acinetobacter baumannii involves various mechanisms. To decipher them, whole genome sequencing (WGS) and real-time quantitative polymerase chain reaction (RT-qPCR) were complemented by mass spectrometry (MS) in selected reaction monitoring mode (SRM) in 39 clinical isolates. The targeted label-free proteomic approach enabled, in one hour and using a single method, the quantitative detection of 16 proteins associated with antibiotic resistance: eight acquired ß-lactamases (i.e. GES, NDM-1, OXA-23, OXA-24, OXA-58, PER, TEM-1, and VEB), two resident ß-lactamases (i.e. ADC and OXA-51-like) and six components of the two major efflux systems (i.e. AdeABC and AdeIJK). Results were normalized using "bacterial quantotypic peptides," i.e. peptide markers of the bacterial quantity, to obtain precise protein quantitation (on average 8.93% coefficient of variation for three biological replicates). This allowed to correlate the levels of resistance to ß-lactam with those of the production of acquired as well as resident ß-lactamases or of efflux systems. SRM detected enhanced ADC or OXA-51-like production and absence or increased efflux pump production. Precise protein quantitation was particularly valuable to detect resistance mechanisms mediated by regulated genes or by overexpression of chromosomal genes. Combination of WGS and MS, two orthogonal and complementary techniques, allows thereby interpretation of the resistance phenotypes at the molecular level.

Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry in Clinical Microbiology: What Are the Current Issues?

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) has revolutionized the identification of microbial species in clinical microbiology laboratories. MALDI-TOF-MS has swiftly become the new gold-standard method owing to its key advantages of simplicity and robustness. However, as with all new methods, adoption of the MALDI-TOF MS approach is still not widespread. Optimal sample preparation has not yet been achieved for several applications, and there are continuing discussions on the need for improved database quality and the inclusion of additional microbial species. New applications such as in the field of antimicrobial susceptibility testing have been proposed but not yet translated to the level of ease and reproducibility that one should expect in routine diagnostic systems. Finally, during routine identification testing, unexpected results are regularly obtained, and the best methods for transmitting these results into clinical care are still evolving. We here discuss the success of MALDI-TOF MS in clinical microbiology and highlight fields of application that are still amenable to improvement.

Bayesian inference for biomarker discovery in proteomics: an analytic solution.

This paper addresses the question of biomarker discovery in proteomics. Given clinical data regarding a list of proteins for a set of individuals, the tackled problem is to extract a short subset of proteins the concentrations of which are an indicator of the biological status (healthy or pathological). In this paper, it is formulated as a specific instance of variable selection. The originality is that the proteins are not investigated one after the other but the best partition between discriminant and non-discriminant proteins is directly sought. In this way, correlations between the proteins are intrinsically taken into account in the decision. The developed strategy is derived in a Bayesian setting, and the decision is optimal in the sense that it minimizes a global mean error. It is finally based on the posterior probabilities of the partitions. The main difficulty is to calculate these probabilities since they are based on the so-called evidence that require marginalization of all the unknown model parameters. Two models are presented that relate the status to the protein concentrations, depending whether the latter are biomarkers or not. The first model accounts for biological variabilities by assuming that the concentrations are Gaussian distributed with a mean and a covariance matrix that depend on the status only for the biomarkers. The second one is an extension that also takes into account the technical variabilities that may significantly impact the observed concentrations. The main contributions of the paper are: (1) a new Bayesian formulation of the biomarker selection problem, (2) the closed-form expression of the posterior probabilities in the noiseless case, and (3) a suitable approximated solution in the noisy case. The methods are numerically assessed and compared to the state-of-the-art methods (t test, LASSO, Battacharyya distance, FOHSIC) on synthetic and real data from proteins quantified in human serum by mass spectrometry in selected reaction monitoring mode.

Impact of Serum and Plasma Matrices on the Titration of Human Inflammatory Biomarkers Using Analytically Validated SRM Assays.

Protein biomarker discovery has inherent challenges linked to the validation of the analytical method used or to the impact of biological matrices. Matrix influences must be mastered to guarantee the reliability of the identified biomarkers to monitor human diseases. In this study, multiplexed mass spectrometry assays in selected reaction monitoring (SRM) mode have been developed to measure 107 inflammatory putative proteins in matched serum and plasma from 36 ICU trauma patients. The assays' validation directly in clinical samples was shown to be valuable to manage intersample variability. Using the validation process developed here, assays were validated for 58 biomarkers in serum, 57 in plasma, and 55 in both matrices. Correlation analyses demonstrated that the quantitation using SRM of most of the validated biomarkers (45/55) was impacted by the biological matrix and that the matrix impact was biomarker-dependent. Among the 45 impacted biomarkers, 23 were nevertheless correlated between serum and plasma, whereas the quantitation was shown to be equivalent in both for the 10 last proteins. Matrix selection using SRM is therefore suggested to be suitable prior to clinical evaluation of biomarkers in a large cohort of patients.

RiboDB Database: A Comprehensive Resource for Prokaryotic Systematics.

Ribosomal proteins (r-proteins) are increasingly used as an alternative to ribosomal rRNA for prokaryotic systematics. However, their routine use is difficult because r-proteins are often not or wrongly annotated in complete genome sequences, and there is currently no dedicated exhaustive database of r-proteins. RiboDB aims at fulfilling this gap. This weekly updated comprehensive database allows the fast and easy retrieval of r-protein sequences from publicly available complete prokaryotic genome sequences. The current version of RiboDB contains 90 r-proteins from 3,750 prokaryotic complete genomes encompassing 38 phyla/major classes and 1,759 different species. RiboDB is accessible at http://ribodb.univ-lyon1.fr and through ACNUC interfaces.

Rapid Bacterial Identification, Resistance, Virulence and Type Profiling using Selected Reaction Monitoring Mass Spectrometry.

Mass spectrometry (MS) in Selected Reaction Monitoring (SRM) mode is proposed for in-depth characterisation of microorganisms in a multiplexed analysis. Within 60-80 minutes, the SRM method performs microbial identification (I), antibiotic-resistance detection (R), virulence assessment (V) and it provides epidemiological typing information (T). This SRM application is illustrated by the analysis of the human pathogen Staphylococcus aureus, demonstrating its promise for rapid characterisation of bacteria from positive blood cultures of sepsis patients.

Label-free SRM-based relative quantification of antibiotic resistance mechanisms in Pseudomonas aeruginosa clinical isolates.

Both acquired and intrinsic mechanisms play a crucial role in Pseudomonas aeruginosa antibiotic resistance. Many clinically relevant resistance mechanisms result from changes in gene expression, namely multidrug efflux pump overproduction, AmpC ß-lactamase induction or derepression, and inactivation or repression of the carbapenem-specific porin OprD. Changes in gene expression are usually assessed using reverse-transcription quantitative real-time PCR (RT-qPCR) assays. Here, we evaluated label-free Selected Reaction Monitoring (SRM)-based mass spectrometry to directly quantify proteins involved in antibiotic resistance. We evaluated the label-free SRM using a defined set of P. aeruginosa isolates with known resistance mechanisms and compared it with RT-qPCR. Referring to efflux systems, we found a more robust relative quantification of antibiotic resistance mechanisms by SRM than RT-qPCR. The SRM-based approach was applied to a set of clinical P. aeruginosa isolates to detect antibiotic resistance proteins. This multiplexed SRM-based approach is a rapid and reliable method for the simultaneous detection and quantification of resistance mechanisms and we demonstrate its relevance for antibiotic resistance prediction.

Alternative representation for the stability diagram of quadrupole ion traps upon additional quadrupolar excitation.

We present a combined theoretical and experimental study of the stability of ions in a linear ion trap under the application of one or two auxiliary radiofrequency (RF) fields, in order to perform simultaneous resonant excitation/ejection of several different ions. The influence of the amplitude and frequency of the auxiliary field is addressed through the construction of experimental and theoretical stability diagrams. Theoretical diagrams are constructed using the method developed by Konenkov et al. [J. Am. Soc. Mass Spectrom. 13, 597 (2002)]. We propose a new representation of stability diagrams more adapted to the study of auxiliary excitations than the canonical one. Stability regions are represented as a function of the fundamental RF amplitude and of the relative intensity of the excitation. This representation facilitates the monitoring of the evolution of the mass-selectivity of first- and higher-order resonant excitations in the trap, for which an empirical law is derived. We also show that the relative phase shift between the excitation field and the main driving field has a strong influence on the shape of the diagrams.

Detection of Staphylococcus aureus delta-toxin production by whole-cell MALDI-TOF mass spectrometry.

The aim of the present study was to detect the Staphylococcus aureus delta-toxin using Whole-Cell (WC) Matrix Assisted Laser Desorption Ionization-Time-of-Flight (MALDI-TOF) mass spectrometry (MS), correlate delta-toxin expression with accessory gene regulator (agr) status, and assess the prevalence of agr deficiency in clinical isolates with and without resistance to methicillin and glycopeptides. The position of the delta-toxin peak in the mass spectrum was identified using purified delta-toxin and isogenic wild type and mutant strains for agr-rnaIII, which encodes delta-toxin. Correlation between delta-toxin production and agr RNAIII expression was assessed by northern blotting. A series of 168 consecutive clinical isolates and 23 unrelated glycopeptide-intermediate S. aureus strains (GISA/heterogeneous GISA) were then tested by WC-MALDI-TOF MS. The delta-toxin peak was detected at 3005±5 Thomson, as expected for the naturally formylated delta toxin, or at 3035±5 Thomson for its G10S variant. Multivariate analysis showed that chronicity of S. aureus infection and glycopeptide resistance were significantly associated with delta-toxin deficiency (p = 0.048; CI 95%: 1.01-10.24; p = 0.023; CI 95%: 1.20-12.76, respectively). In conclusion, the S. aureus delta-toxin was identified in the WC-MALDI-TOF MS spectrum generated during routine identification procedures. Consequently, agr status can potentially predict infectious complications and rationalise application of novel virulence factor-based therapies.

The current status of clinical proteomics and the use of MRM and MRM(3) for biomarker validation.

The transfer of biomarkers from the discovery field to clinical use is still, despite progress, on a road filled with pitfalls. Since the emergence of proteomics, thousands of putative biomarkers have been published, often with overlapping diagnostic capacities. The strengthening of the robustness of discovery technologies, particularly in mass spectrometry, has been followed by intense discussions on establishing well-defined evaluation procedures for the identified targets to ultimately allow the clinical validation and then the clinical use of some of these biomarkers. Some of the obstacles to the evaluation process have been the lack of the availability of quick and easy-to-develop, easy-to-use, robust, specific and sensitive alternative quantitative methods when immunoaffinity-based tests are unavailable. Multiple reaction monitoring (MRM; also called selected reaction monitoring) is currently proving its capabilities as a complementary or alternative technique to ELISA for large biomarker panel evaluation. Here, we present how MRM(3) can overcome the lack of specificity and sensitivity often encountered by MRM when tracking minor proteins diluted by complex biological matrices.

Identification and verification of heat shock protein 60 as a potential serum marker for colorectal cancer.

Colorectal cancer (CRC) is a major public health issue worldwide, and novel tumor markers may contribute to its efficient management by helping in early detection, prognosis or surveillance of disease. The aim of our study was to identify new serum biomarkers for CRC, and we followed a phased biomarker discovery and validation process to obtain an accurate preliminary assessment of potential clinical utility. We compared colonic tumors and matched normal tissue from 15 CRC patients, using two-dimensional difference gel electrophoresis (2D-DIGE), and identified 17 proteins that had significant differential expression. These results were further confirmed by western blotting for heat shock protein (HSP) 60, glutathione-S-transferase Pi, α-enolase, T-complex protein 1 subunit ß, and leukocyte elastase inhibitor, and by immunohistochemistry for HSP60. Using mAbs raised against HSP60, we developed a reliable (precision of 5-15%) and sensitive (0.3 ng·mL(-1)) immunoassay for the detection of HSP60 in serum. Elevated levels of HSP60 were found in serum from CRC patients in two independent cohorts; the receiver-operating characteristic curve obtained in 112 patients with CRC and 90 healthy controls had an area under the curve (AUC) of 0.70, which was identical to the AUC of carcinoembryonic antigen. Combination of serum markers improved clinical performance: the AUC of a three-marker logistic regression model combining HSP60, carcinoembryonic antigen and carbohydrate antigen 19-9 reached 0.77. Serum HSP60 appeared to be more specific for late-stage CRC; therefore, future studies should evaluate its utility for determining prognosis or monitoring therapy rather than early detection.

Clinical quantitation of prostate-specific antigen biomarker in the low nanogram/milliliter range by conventional bore liquid chromatography-tandem mass spectrometry (multiple reaction monitoring) coupling and correlation with ELISA tests.

Proteomics discovery leads to a list of potential protein biomarkers that have to be subsequently verified and validated with a statistically viable number of patients. Although the most sensitive, the development of an ELISA test is time-consuming when antibodies are not available and need to be conceived. Mass spectrometry analysis driven in quantitative multiple reaction monitoring mode is now appearing as a promising alternative to quantify proteins in biological fluids. However, all the studies published to date describe limits of quantitation in the low microg/ml range when no immunoenrichment of the target protein is applied, whereas the concentration of known clinical biomarkers is usually in the ng/ml range. Using prostate-specific antigen as a model biomarker, we now provide proof of principle that mass spectrometry enables protein quantitation in a concentration range of clinical interest without immunoenrichment. We have developed and optimized a robust sample processing method combining albumin depletion, trypsin digestion, and solid phase extraction of the proteotypic peptides starting from only 100 microl of serum. For analysis, mass spectrometry was coupled to a conventional liquid chromatography system using a 2-mm-internal diameter reverse phase column. This mass spectrometry-based strategy was applied to the quantitation of prostate-specific antigen in sera of patients with either benign prostate hyperplasia or prostate cancer. The quantitation was performed against an external calibration curve by interpolation, and results showed good correlation with existing ELISA tests applied to the same samples. This strategy might now be implemented in any clinical laboratory or certified company for further evaluation of any putative biomarker in the low ng/ml range of serum or plasma.

Analysis of high molecular mass proteins larger than 150 kDa using cyanogen bromide cleavage and conventional 2-DE.

Proteomic approaches including high-resolution 2-DE are providing the tools needed to discover disease-associated biomarkers in complex biological samples. Although 2-DE is an extremely powerful approach to analyze the proteome, the separation of proteins with extreme molecular masses still remains an issue requiring improvement. Because high molecular mass (HMM) proteins larger than 150 kDa have already been observed to be differentially expressed in several pathologies such as cancer, we developed an original strategy to analyze this part of the proteome that is not easily separated by 2-DE in polyacrylamide gels. This strategy is based on the 2-DE separation of cyanogen bromide (CNBr) fragments of purified HMM protein fractions, and combines techniques including SEC fractionation, TCA precipitation, CNBr cleavage, 2-DE and MS analysis. The method was first tested on a model protein, the BSA. Preliminary results obtained using colonic tissues led to the identification of six HMM proteins with M(r) comprised between 163 and 533 kDa in their reduced state. These results demonstrated that our CNBr/2-DE approach should provide a powerful tool for identification of new biomarkers larger than 150 kDa.

Isoelectric point determination of cardiac troponin I forms present in plasma from patients with myocardial infarction.

BACKGROUND: Cardiac troponin I (cTnI) is a specific marker of myocardial injury. In blood of patients with cardiovascular diseases, cTnI is released as a mixture of free, complexed and post-translationally modified forms. METHODS: The cTnI forms present in the plasma from 8 patients with acute myocardial infarction (AMI) have been analysed by two-dimensional gel electrophoresis (2-DE) and Western Blot using anti-cTnI mAb 19C7 and anti-phosphorylated cTnI (Serines 22-23) mAb 5E6. RESULTS: After immunoextraction of cTnI in plasma samples by 19C7 and 2-DE separation, 4 different forms were detected by 19C7 in 7 out the 8 AMI plasma samples. Two 29 kDa spots corresponding to intact free cTnI forms were detected at pIs 5.2 and 5.4. However, spot with pI 5.4 was also recognized by mAb 5E6, and should be bis-phosphorylated cTnI. Two 55 kDa spots with pIs 6.6 and 6.7 could be IC complexes. CTnI forms with pIs lower than the theoretical pI were also found in free cTnI and phosphorylated cTnI purified materials. CONCLUSIONS: 2-DE analysis of AMI plasma showed the presence of acidic cTnI forms, one of them being phosphorylated. The clinical significance of these forms has to be further investigated.

Selective recognition of enzymatically active prostate-specific antigen (PSA) by anti-PSA monoclonal antibodies.

Prostate-specific antigen (PSA) is widely used as a serum marker for the diagnosis of prostate cancer. To evaluate two anti-free PSA monoclonal antibodies (mAbs) as potential tools in new generations of more relevant PSA assays, we report here their properties towards the recognition of specific forms of free PSA in seminal fluids, LNCaP supernatants, 'non-binding' PSA and sera from cancer patients. PSA from these different origins was immunopurified by the two anti-free PSA mAbs (5D3D11 and 6C8D8) as well as by an anti-total PSA mAb. The composition of the different immunopurified PSA fractions was analysed and their respective enzymatic activities were determined. In seminal fluid, enzymatically active PSA was equally purified with the three mAbs. In LNCaP supernatants and human sera, 5D3D11 immunopurified active PSA mainly, whereas 6C8D8 immunopurified PSA with residual activity. In sera of prostate cancer patients, we identified the presence of a mature inactive PSA form which can be activated into active PSA by use of high saline concentration or capture by an anti-total PSA mAb capable of enhancing PSA activity. According to PSA models built by comparative modelling with the crystal structure of horse prostate kallikrein described previously, we assume that active and activable PSA could correspond to mature intact PSA with open and closed conformations of the kallikrein loop. The specificity of 5D3D11 was restricted to both active and activable PSA, whereas 6C8D8 recognized all free PSA including intact PSA, proforms and internally cleaved PSA.