Direct detection of OXA-48-like carbapenemase variants with and without co-expression of an extended-spectrum ß-lactamase from bacterial cell lysates using mass spectrometry.

INTRODUCTION: Antibiotic-resistant Gram-negative bacteria are of a growing concern globally, especially those producing enzymes conferring resistance. OXA-48-like carbapenemases hydrolyze most ß-lactam antibiotics, with typically low-level hydrolysis of carbapenems, but have limited effect on broad-spectrum cephalosporins. These are frequently co-expressed with extended spectrum ß-lactamases, especially CTX-M-15, which typically shows high level resistance to broad-spectrum cephalosporins, yet is carbapenem susceptible. The combined resistance profile makes the need for successful detection of these specific resistance determinants imperative for effective antibiotic therapy. OBJECTIVES: The objective of this study is to detect and identify OXA-48-like and CTX-M-15 enzymes using mass spectrometry, and to subsequently develop a method for detection of both enzyme types in combination with liquid chromatography. METHODS: Cells grown in either broth or on agar were harvested, lysed, and, in some cases buffer-exchanged. Lysates produced from bacterial cells were separated and analyzed via liquid chromatography with mass spectrometry (LC-MS) and tandem mass spectrometry (LC-MS/MS). RESULTS: The intact proteins of OXA-48, OXA-181, and OXA-232 (collectively OXA-48-like herein) and CTX-M-15 were characterized and detected. Acceptance criteria based on sequence-informative fragments from each protein group were established as confirmatory markers for the presence of the protein(s). A total of 25 isolates were successfully tested for OXA-48 like (2), CTX-M-15 (3), or expression of both (7) enzymes. Thirteen isolates served as negative controls. CONCLUSIONS: Here we present a method for the direct and independent detection of both OXA-48-like carbapenemases and CTX-M-15 ß-lactamases using LC-MS/MS. The added sensitivity of MS/MS allows for simultaneous detection of at least two co-eluting, co-isolated and co-fragmented proteins from a single mass spectrum.

Rapid MRSA detection via tandem mass spectrometry of the intact 80 kDa PBP2a resistance protein.

Treatment of antibiotic-resistant infections is dependent on the detection of specific bacterial genes or proteins in clinical assays. Identification of methicillin-resistant Staphylococcus aureus (MRSA) is often accomplished through the detection of penicillin-binding protein 2a (PBP2a). With greater dependence on mass spectrometry (MS)-based bacterial identification, complementary efforts to detect resistance have been hindered by the complexity of those proteins responsible. Initial characterization of PBP2a indicates the presence of glycan modifications. To simplify detection, we demonstrate a proof-of-concept tandem MS approach involving the generation of N-terminal PBP2a peptide-like fragments and detection of unique product ions during top-down proteomic sample analyses. This approach was implemented for two PBP2a variants, PBP2amecA and PBP2amecC, and was accurate across a representative panel of MRSA strains with different genetic backgrounds. Additionally, PBP2amecA was successfully detected from clinical isolates using a five-minute liquid chromatographic separation and implementation of this MS detection strategy. Our results highlight the capability of direct MS-based resistance marker detection and potential advantages for implementing these approaches in clinical diagnostics.

Direct detection of intact Klebsiella pneumoniae carbapenemase variants from cell lysates: Identification, characterization and clinical implications.

INTRODUCTION: Carbapenemase-producing organisms (CPOs) are a growing threat to human health. Among the enzymes conferring antibiotic resistance produced by these organisms, Klebsiella pneumoniae carbapenemase (KPC) is considered to be a growing global health threat. Reliable and specific detection of this antibiotic resistance-causing enzyme is critical both for effective therapy and to mitigate further spread. OBJECTIVES: The objective of this study is to develop an intact protein mass spectrometry-based method for detection and differentiation of clinically-relevant KPC variants directly from bacterial cell lysates. The method should be specific for any variant expressed in multiple bacterial species, limit false positive results and be rapid in nature to directly influence clinical outcomes. METHODS: Lysates obtained directly from bacterial colonies were used for intact protein detection using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Bottom-up and top-down proteomic methods were used to characterize the KPC protein targets of interest. Comparisons between KPC-producing and KPC-non-producing isolates from a wide variety of species were also performed. RESULTS: Characterization of the mature KPC protein revealed an unexpected signal peptide cleavage site preceding an AXA signal peptide motif, modifying the molecular weight (MW) of the mature protein. Taking the additional AXA residues into account allowed for direct detection of the intact protein using top-down proteomic methods. Further validation was performed by transforming a KPC-harboring plasmid into a negative control strain, followed by MS detection of the KPC variant from the transformed cell line. Application of this approach to clearly identify clinically-relevant variants among several species is presented for KPC-2, KPC-3, KPC-4 and KPC-5. CONCLUSION: Direct detection of these enzymes contributes to the understanding of occurrence and spread of these antibiotic-resistant organisms. The ability to detect intact KPC variants via a simple LC-MS/MS approach could have a direct and positive impact on clinical therapy, by providing both direction for epidemiological tracking and appropriate therapy.

High sensitivity combined with extended structural coverage of labile compounds via nanoelectrospray ionization at subambient pressures.

Subambient pressure ionization with nanoelectrospray (SPIN) has proven to be effective in producing ions with high efficiency and transmitting them to low pressures for increased sensitivity in mass spectrometry (MS) analysis. Here we present evidence that the SPIN source not only improves MS sensitivity but also facilitates the detection of more labile compounds. The gentleness of conventional heated capillary electrospray ionization (ESI) and the SPIN designs was compared in conjunction with the liquid chromatography mass spectrometry (LC-MS) analysis of colominic acid and N-glycans containing sialic acid. Prior experiments conducted with the SPIN interface demonstrated the ability to detect labile glycans such as heavily sialylated and polysialic acid N-glycans, which are difficult to detect with a conventional ESI-MS interface. Colominic acid is a mixture of sialic acid polymers of different lengths containing labile glycosidic linkages between monomer units necessitating a gentle ion source. These labile covalent bonds may display similar behavior to sialic acid chains in N-glycans during MS analysis. By coupling the SPIN source with high-resolution mass spectrometry and using advanced data processing tools, we demonstrate much extended coverage of sialic acid polymer chains as compared to conventional ESI-MS and the ability to detect sialic acid containing N-glycans without the need of sample derivatization. In addition, we show that SPIN-LC-MS is effective in elucidating polymer features with high efficiency and high sensitivity previously unattainable by the conventional ESI-LC-MS methods.

Polysialylated N-glycans identified in human serum through combined developments in sample preparation, separations, and electrospray ionization-mass spectrometry.

The N-glycan diversity of human serum glycoproteins, i.e., the human blood serum N-glycome, is both complex and constrained by the range of glycan structures potentially synthesizable by human glycosylation enzymes. The known glycome, however, has been further limited by methods of sample preparation, available analytical platforms, e.g., based upon electrospray ionization-mass spectrometry (ESI-MS), and software tools for data analysis. In this report several improvements have been implemented in sample preparation and analysis to extend ESI-MS glycan characterization and to include polysialylated N-glycans. Sample preparation improvements included acidified, microwave-accelerated, PNGase F N-glycan release to promote lactonization, and sodium borohydride reduction, that were both optimized to improve quantitative yields and conserve the number of glycoforms detected. Two-stage desalting (during solid phase extraction and on the analytical column) increased sensitivity by reducing analyte signal division between multiple reducing-end-forms or cation adducts. Online separations were improved by using extended length graphitized carbon columns and adding TFA as an acid modifier to a formic acid/reversed phase gradient, providing additional resolving power and significantly improved desorption of both large and heavily sialylated glycans. To improve MS sensitivity and provide gentler ionization conditions at the source-MS interface, subambient pressure ionization with nanoelectrospray (SPIN) was utilized. When these improved methods are combined together with the Glycomics Quintavariate Informed Quantification (GlyQ-IQ) recently described (Kronewitter et al. Anal. Chem. 2014, 86, 6268-6276), we are able to significantly extend glycan detection sensitivity and provide expanded glycan coverage. We demonstrated the application of these advances in the context of the human serum glycome, and for which our initial observations included the detection of a new class of heavily sialylated N-glycans, including polysialylated N-glycans.

GlyQ-IQ: glycomics quintavariate-informed quantification with high-performance computing and GlycoGrid 4D visualization.

Glycomics quintavariate-informed quantification (GlyQ-IQ) is a biologically guided glycomics analysis tool for identifying N-glycans in liquid chromatography-mass spectrometry (LC-MS) data. Glycomics LC-MS data sets have convoluted extracted ion chromatograms that are challenging to deconvolve with existing software tools. LC deconvolution into constituent pieces is critical in glycomics data sets because chromatographic peaks correspond to different intact glycan structural isomers. The biological targeted analysis approach offers several key advantages to traditional LC-MS data processing. A priori glycan information about the individual target's elemental composition allows for improved sensitivity by utilizing the exact isotope profile information to focus chromatogram generation and LC peak fitting on the isotopic species having the highest intensity. Glycan target annotation utilizes glycan family relationships and in source fragmentation in addition to high specificity feature LC-MS detection to improve the specificity of the analysis. The GlyQ-IQ software was developed in this work and evaluated in the context of profiling the N-glycan compositions from human serum LC-MS data sets. A case study is presented to demonstrate how GlyQ-IQ identifies and removes confounding chromatographic peaks from high mannose glycan isomers from human blood serum. In addition, GlyQ-IQ was used to generate a broad human serum N-glycan profile from a high resolution nanoelectrospray-liquid chromatography-tandem mass spectrometry (nESI-LC-MS/MS) data set. A total of 156 glycan compositions and 640 glycan isomers were detected from a single sample. Over 99% of the GlyQ-IQ glycan-feature assignments passed manual validation and are backed with high-resolution mass spectra.

A Multi-Omic View of Host-Pathogen-Commensal Interplay in Salmonella-Mediated Intestinal Infection.

The potential for commensal microorganisms indigenous to a host (the 'microbiome' or 'microbiota') to alter infection outcome by influencing host-pathogen interplay is largely unknown. We used a multi-omics "systems" approach, incorporating proteomics, metabolomics, glycomics, and metagenomics, to explore the molecular interplay between the murine host, the pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium), and commensal gut microorganisms during intestinal infection with S. Typhimurium. We find proteomic evidence that S. Typhimurium thrives within the infected 129/SvJ mouse gut without antibiotic pre-treatment, inducing inflammation and disrupting the intestinal microbiome (e.g., suppressing Bacteroidetes and Firmicutes while promoting growth of Salmonella and Enterococcus). Alteration of the host microbiome population structure was highly correlated with gut environmental changes, including the accumulation of metabolites normally consumed by commensal microbiota. Finally, the less characterized phase of S. Typhimurium's lifecycle was investigated, and both proteomic and glycomic evidence suggests S. Typhimurium may take advantage of increased fucose moieties to metabolize fucose while growing in the gut. The application of multiple omics measurements to Salmonella-induced intestinal inflammation provides insights into complex molecular strategies employed during pathogenesis between host, pathogen, and the microbiome.

Automated assignments of N- and O-site specific glycosylation with extensive glycan heterogeneity of glycoprotein mixtures.

Site-specific glycosylation (SSG) of glycoproteins remains a considerable challenge and limits further progress in the areas of proteomics and glycomics. Effective methods require new approaches in sample preparation, detection, and data analysis. While the field has advanced in sample preparation and detection, automated data analysis remains an important goal. A new bioinformatics approach implemented in software called GP Finder automatically distinguishes correct assignments from random matches and complements experimental techniques that are optimal for glycopeptides, including nonspecific proteolysis and high mass resolution liquid chromatography/tandem mass spectrometry (LC/MS/MS). SSG for multiple N- and O-glycosylation sites, including extensive glycan heterogeneity, was annotated for single proteins and protein mixtures with a 5% false-discovery rate, generating hundreds of nonrandom glycopeptide matches and demonstrating the proof-of-concept for a self-consistency scoring algorithm shown to be compliant with the target-decoy approach (TDA). The approach was further applied to a mixture of N-glycoproteins from unprocessed human milk and O-glycoproteins from very-low-density-lipoprotein (vLDL) particles.

Improving N-glycan coverage using HPLC-MS with electrospray ionization at subambient pressure.

Human serum glycan profiling with mass spectrometry (MS) has been employed to study several disease conditions and is demonstrating promise in, for example, clinical biomarker discovery. However, the low glycan ionization efficiency and the large dynamic range of glycan concentrations in human sera can hinder comprehensive profiling. In particular, large glycans are problematic because they are present at low concentrations and are prone to fragmentation. Here we show that, following liquid chromatographic separation on graphite columns, subambient pressure ionization with nanoelectrospray (SPIN)-MS can expand the serum glycome profile in comparison with the conventional atmospheric pressure electrospray ionization (ESI)-MS with a heated capillary inlet. Notably, the ions generated by the SPIN interface were observed at higher charge states for approximately half of the annotated glycans. Out of a total of 130 detected glycans, 34 were only detected with the SPIN-MS, resulting in improved coverage of glycan families as well as of glycans with larger numbers of labile monosaccharides.

The glycolyzer: automated glycan annotation software for high performance mass spectrometry and its application to ovarian cancer glycan biomarker discovery.

Human serum glycomics is a promising method for finding cancer biomarkers but often lacks the tools for streamlined data analysis. The Glycolyzer software incorporates a suite of analytic tools capable of identifying informative glycan peaks out of raw mass spectrometry data. As a demonstration of its utility, the program was used to identify putative biomarkers for epithelial ovarian cancer from a human serum sample set. A randomized, blocked, and blinded experimental design was used on a discovery set consisting of 46 cases and 48 controls. Retrosynthetic glycan libraries were used for data analysis and several significant candidate glycan biomarkers were discovered via hypothesis testing. The significant glycans were attributed to a glycan family based on glycan composition relationships and incorporated into a linear classifier motif test. The motif test was then applied to the discovery set to evaluate the disease state discrimination performance. The test provided strongly predictive results based on receiver operator characteristic curve analysis. The area under the receiver operator characteristic curve was 0.93. Using the Glycolyzer software, we were able to identify a set of glycan biomarkers that highly discriminate between cases and controls, and are ready to be formally validated in subsequent studies.

Analysis of serum total and free PSA using immunoaffinity depletion coupled to SRM: correlation with clinical immunoassay tests.

Recently, selected reaction monitoring mass spectrometry (SRM-MS) has been more frequently applied to measure low abundance biomarker candidates in tissues and biofluids, owing to its high sensitivity and specificity, simplicity of assay configuration, and exceptional multiplexing capability. In this study, we report for the first time the development of immunoaffinity depletion-based workflows and SRM-MS assays that enable sensitive and accurate quantification of total and free prostate-specific antigen (PSA) in serum without the requirement for specific PSA antibodies. Low ng/mL level detection of both total and free PSA was consistently achieved in both PSA-spiked female serum samples and actual patient serum samples. Moreover, comparison of the results obtained when SRM PSA assays and conventional immunoassays were applied to the same samples showed good correlation in several independent clinical serum sample sets. These results demonstrate that the workflows and SRM assays developed here provide an attractive alternative for reliably measuring candidate biomarkers in human blood, without the need to develop affinity reagents. Furthermore, the simultaneous measurement of multiple biomarkers, including the free and bound forms of PSA, can be performed in a single multiplexed analysis using high-resolution liquid chromatographic separation coupled with SRM-MS. This article is part of a Special Issue entitled: Translational Proteomics.

High-mannose glycans are elevated during breast cancer progression.

Alteration in glycosylation has been observed in cancer. However, monitoring glycosylation changes during breast cancer progression is difficult in humans. In this study, we used a well-characterized transplantable breast tumor mouse model, the mouse mammary tumor virus-polyoma middle T antigen, to observe early changes in glycosylation. We have previously used the said mouse model to look at O-linked glycosylation changes with breast cancer. In this glycan biomarker discovery study, we examined N-linked glycan variations during breast cancer progression of the mouse model but this time doubling the number of mice and blood draw points. N-glycans from total mouse serum glycoproteins were profiled using matrix-assisted laser desorption/ionization Fourier transform-ion cyclotron resonance mass spectrometry at the onset, progression, and removal of mammary tumors. We observed four N-linked glycans, m/z 1339.480 (Hex(3)HexNAc), 1485.530 (Hex(3)HexNAc(4)Fuc), 1809.639 (Hex(5)HexNAc(4)Fuc), and 1905.630 (Man(9)), change in intensity in the cancer group but not in the control group. In a separate study, N-glycans from total human serum glycoproteins of breast cancer patients and controls were also profiled. Analysis of human sera using an internal standard showed the alteration of the low-abundant high-mannose glycans, m/z 1419.475, 1581.528, 1743.581, 1905.634 (Man(6-9)), in breast cancer patients. A key observation was the elevation of a high-mannose type glycan containing nine mannoses, Man(9), m/z 1905.630 in both mouse and human sera in the presence of breast cancer, suggesting an incompletion of the glycosylation process that normally trims back Man(9) to produce complex and hybrid type oligosaccharides.

Human serum processing and analysis methods for rapid and reproducible N-glycan mass profiling.

Glycans constitute a new class of compounds for biomarker discovery. Glycosylation is a common post-translational modification and is often associated with transformation to malignancy. To analyze glycans, they are released from proteins, enriched, and measured with mass spectrometry. For biomarker discovery, repeatability at every step of the process is important. Locating and minimizing the process variability is key to establishing a robust platform stable enough for biomarker discovery. Understanding the variability of the measurement devices helps understand the variability associated with the chemical processing. This report explores the potential use of methods expediting the enzymatic release of glycans such as a microwave reactor and automation of the solid-phase extraction with a robotic liquid handler. The study employs matrix-assisted laser desorption/ionization-Fourier transform ion cyclotron resonance mass spectrometry but would be suitable with any mass spectrometry method. Methods for system-wide data analysis are examined because proper metrics for evaluating the performance of glycan sample preparation procedures are not well established.

Glycomics and disease markers.

Glycomics is the comprehensive study of all glycans expressed in biological systems. The biosynthesis of glycan relies on a number of highly competitive processes involving glycosyl transferases. Glycosylation is therefore highly sensitive to the biochemical environment and has been implicated in many diseases including cancer. Recently, interest in profiling the glycome has increased owing to the potential of glycans for disease markers. In this regard, mass spectrometry is emerging as a powerful technique for profiling the glycome. Global glycan profiling of human serum based on mass spectrometry has already led to several potentially promising markers for several types of cancer and diseases.

Analysis of MALDI FT-ICR mass spectrometry data: a time series approach.

Matrix-assisted laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry is a technique for high mass-resolution analysis of substances that is rapidly gaining popularity as an analytic tool. Extracting signal from the background noise, however, poses significant challenges. In this article, we model the noise part of a spectrum as an autoregressive, moving average (ARMA) time series with innovations given by a generalized gamma distribution with varying scale parameter but constant shape parameter and exponent. This enables us to classify peaks found in actual spectra as either noise or signal using a reasonable criterion that outperforms a standard threshold criterion.

The development of retrosynthetic glycan libraries to profile and classify the human serum N-linked glycome.

Annotation of the human serum N-linked glycome is a formidable challenge but is necessary for disease marker discovery. A new theoretical glycan library was constructed and proposed to provide all possible glycan compositions in serum. It was developed based on established glycobiology and retrosynthetic state-transition networks. We find that at least 331 compositions are possible in the serum N-linked glycome. By pairing the theoretical glycan mass library with a high mass accuracy and high-resolution MS, human serum glycans were effectively profiled. Correct isotopic envelope deconvolution to monoisotopic masses and the high mass accuracy instruments drastically reduced the amount of false composition assignments. The high throughput capacity enabled by this library permitted the rapid glycan profiling of large control populations. With the use of the library, a human serum glycan mass profile was developed from 46 healthy individuals. This paper presents a theoretical N-linked glycan mass library that was used for accurate high-throughput human serum glycan profiling. Rapid methods for evaluating a patient's glycome are instrumental for studying glycan-based markers.

Detecting glycan cancer biomarkers in serum samples using MALDI FT-ICR mass spectrometry data.

MOTIVATION: The development of better tests to detect cancer in its earliest stages is one of the most sought-after goals in medicine. Especially important are minimally invasive tests that require only blood or urine samples. By profiling oligosaccharides cleaved from glycosylated proteins shed by tumor cells into the blood stream, we hope to determine glycan profiles that will help identify cancer patients using a simple blood test. The data in this article were generated using matrix-assisted laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry (MALDI FT-ICR MS). We have developed novel methods for analyzing this type of mass spectrometry data and applied it to eight datasets from three different types of cancer (breast, ovarian and prostate). RESULTS: The techniques we have developed appear to be effective in the analysis of MALDI FT-ICR MS data. We found significant differences between control and cancer groups in all eight datasets, including two structurally related compounds that were found to be significantly different between control and cancer groups in all three types of cancer studied.

A versatile and scalable strategy for glycoprofiling bifidobacterial consumption of human milk oligosaccharides.

Human milk contains approximately 200 complex oligosaccharides believed to stimulate the growth and establishment of a protective microbiota in the infant gut. The lack of scalable analytical techniques has hindered the measurement of bacterial metabolism of these and other complex prebiotic oligosaccharides. An in vitro, multi-strain, assay capable of measuring kinetics of bacterial growth and detailed oligosaccharide consumption analysis by FTICR-MS was developed and tested simultaneously on 12 bifidobacterial strains. For quantitative consumption, deuterated and reduced human milk oligosaccharide (HMO) standards were used. A custom software suite developed in house called Glycolyzer was used to process the large amounts of oligosaccharide mass spectra automatically with (13)C corrections based on de-isotoping protocols. High growth on HMOs was characteristic of Bifidobacterium longum biovar infantis strains, which consumed nearly all available substrates, while other bifidobacterial strains tested, B. longum bv. longum, B. adolescentis, B. breve and B. bifidum, showed low or only moderate growth ability. Total oligosaccharide consumption ranged from a high of 87% for B. infantis JCM 7009 to only 12% for B. adolescentis ATCC 15703. A detailed analysis of consumption glycoprofiles indicated strain-specific capabilities towards differential metabolism of milk oligosaccharides. This method overcomes previous limitations in the quantitative, multi-strain analysis of bacterial metabolism of HMOs and represents a novel approach towards understanding bacterial consumption of complex prebiotic oligosaccharides.