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.

Streamlined Development of Targeted Mass Spectrometry-Based Method Combining Scout-MRM and a Web-Based Tool Indexed with Scout Peptides.

MS-based targeted proteomics is a relevant technology for sensitive and robust relative or absolute quantification of proteins biomarker candidates in complex human biofluids or tissue extracts. Performing a multiplex assay imposes time scheduling of peptide monitoring only around their expected retention time that needs to be defined with synthetic peptide. Time-scheduled monitoring is clearly a constraint that precludes from straightforward assay transfer between biological matrices or distinct experimental setup. Any unexpected retention time (RT) shift challenges assay robustness and its implementation for large-scale analysis. Recently, Scout-multiple reaction monitoring that fully releases multiplexed targeted acquisition from RT scheduling by successively monitoring complex transition groups triggered with sentinel molecules called Scout has been introduced. It is herein documented how Peptide Selector database and tool streamlines the building of a multiplexed method thanks to RT indexation relative to Scout peptides. This case study deals with surrogate peptides of biomarker candidates related to drug-induced liver and vascular injury, running such on-line built method (eight Scouts triggering the monitoring of a total of 692 transitions) enables 100% recovery of a panel of 93 spiked-in heavy labeled standards, despite significant RT shifts between serum, plasma, or urine. This result illustrates the simplicity of automatically building and deploying robust proteomics targeted assay.

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.

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.

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.