Quantification of thyrotropin-releasing hormone by liquid chromatography–electrospray mass spectrometry

Thyrotropin-releasing hormone (TRH) is involved in a wide range of biological responses. It has a central role in the endocrine system and regulates several neurobiological activities. In the present study, a rapid, sensitive and selective liquid chromatography–mass spectrometry method for the identification and quantification of TRH has been developed. The methodology takes advantage of the specificity of the selected-ion monitoring acquisition mode with a limit of detection of 1 fmol. Furthermore, the MS/MS fragmentation pattern of TRH has been investigated to develop a selected reaction monitoring (SRM) method that allows the detection of a specific b2 product ion at m/z 249.1, corresponding to the N-terminus dipeptide pyroglutamic acid–histidine. The method has been tested on rat hypothalami to evaluate its suitability for the detection within very complex biological samples.     

Detection and structural investigation of metabolites of stanozolol in human urine by liquid chromatography tandem mass spectrometry

The applicability of LC–MS/MS in precursor ion scan mode for the detection of urinary stanozolol metabolites has been studied. The product ion at m/z 81 has been selected as specific for stanozolol metabolites without a modification in A- or N-rings and the product ions at m/z 97 and 145 for the metabolites hydroxylated in the N-ring and 4-hydroxy-stanozolol metabolites, respectively. Under these conditions, the parent drug and up to 15 metabolites were found in a positive doping test sample. The study of a sample from a chimeric uPA-SCID mouse collected after the administration of stanozolol revealed the presence of 4 additional metabolites. The information obtained from the product ion spectra was used to develop a SRM method for the detection of 19 compounds. This SRM method was applied to several doping positive samples. All the metabolites were detected in both the uPA-SCID mouse sample and positive human samples and were not detected in none of the blank samples tested; confirming the metabolic nature of all the detected compounds. In addition, the application of the SRM method to a single human excretion study revealed that one of the metabolites (4ξ,16ξ-dihydroxy-stanozolol) could be detected in negative ionization mode for a longer period than those commonly used in the screening for stanozolol misuse (3′-hydroxy-stanozolol, 16β-hydroxy-stanozolol and 4β-hydroxy-stanozolol) in doping analysis. The application of the developed approach to several positive doping samples confirmed the usefulness of this metabolite for the screening of stanozolol misuse. Finally, a tentative structure for each detected metabolite has been proposed based on the product ion spectra measured with accurate masses using UPLC–QTOF MS.     

Ultrasensitive determination of NE-100, a novel sigma ligand,in human plasma by liquid chromatography and electrospray ionization tandem mass spectrometry combined with a column-switching technique

For the highly sensitive and selective determination of NE-100, a novel sigma ligand, at levels of low picogram per milliliter of human plasma, a method with excellent reliability employing liquid chromatography (LC)–electrospray ionization (ESI) tandem mass spectrometry (MS–MS) combined with a column-switching technique has been developed. The method involves the use of a stable isotope labeled compound as the internal standard (I.S.), liquid–solid extraction of a plasma specimen with a C₈ cartridge, automated on-line clean-up on a short trapping column, subsequent separation on a micro-bore C₁₈ column and detection with ESI-MS–MS using m/z 356 ([M+H]⁺) as a precursor ion and m/z 105 as a product ion in a selected reaction monitoring mode. The detection and the quantification limits of NE-100 in plasma were 0.5 pg/ml with a signal-to-noise ratio (S/N) of 3 and 2.3 pg/ml, respectively, with an S/N of 21. The good linearity of the calibration graph was obtained in the range of 2.3∼907.0 pg/ml with excellent reliability. The developed method was applied to the determination of NE-100 in plasma obtained from the clinical trail.     

Chemotaxonomy and flavonoid profiling of Torilis species by HPLC/ESI/MS2

The flavonoid profiles of Turkish Torilis Gaertn. (Apiaceae) species were studied by TLC, HPLC-UV and HPLC/ESI/MS² (negative mode). O-glycosides of luteolin, apigenin and chrysoeriol were identified from crude extracts with the help of mass spectra in different MS/MS modes, such as full scan, precursor ion scan and product ion scan. Luteolin-7-O-glucoside and luteolin-7-O-rutinoside were common to all species. Flavonoid profiles usually differ from one species to another and can be put to use for a genus such as Torilis which has been little studied. By the help of different flavonoid profiles, it is concluded that, the plants, which are recognised as less rayed subspecies of Torilis arvensis (Huds.) Link. in various floras including Turkish one, must be classified in species category as Torilis chrysocarpa and Torilis purpurea. Flavonoid profiles seem to be in relation with evolutionary biogeography of the species. Because the most isolated species of the genus, endemic Torilis triradiata, has the most different flavonoid pattern. Moreover, geographically isolated species, T. triradiata and Torilis leptocarpa, do not share any flavonoid except for the two which are common to all species.     

Purification of rat liver asparagine synthetase by affinity chromatography on reactive blue 2-agarose

Studies on analysis of free animo acids using a support-coated, open-tube capillary column, and electron-capture detection or selective ion monitoring have been performed on samples from biological microenvironments. For most amino acids the detection limit was found to be less than 1 pg. The preparation of the support-coated open-tube capillary column is described as well as the gas-chromatographic conditions for direct injection and temperature-programmed separation of the N-heptafluorobutyryl iso butyl ester derivatives. Electron-capture detection and selected ion monitoring are compared with respect to linearity and sensitivity and the bases for the greater sensitivity of electron-capture detection compared with flame-ionization detection using halogenated derivatives is discussed. Applications of the gas-chromatographic method for analysis of free amino acids in environments deliberately chosen very small are demonstrated.     

The identification of trimethylsilylated dipeptides with chemical ionization mass spectrometry.

The chemical ionization (CI) and electron impact (EI) mass spectra were compared for over 40 trimethylsilylated (Me₃Si) dipeptides. The dipeptides chosen had all 20 common amino acids represented at amino and carboxyl positions. The CI mass spectra of Me₃Si dipeptides typically contain three ions of high abundance used for dipeptide identification: a sequence-determining ion and two molecular weight-determining ions. The intensity of the molecular weight-determining ions relative to that of the ion that characterizes the N-terminal residue (β-cleavage ion) is greater in the CI mode than in the EI mode. Because the available intensity of the β-cleavage ion is similar in both modes, use of the CI mode will extend the lower limit for Me₃Si dipeptide identification.     

Determination of a thermally labile metabolite of a novel growth hormone secretagogue in human and dog plasma by liquid chromatography with ion spray tandem mass spectrometric detection

A sensitive and selective assay for the determination of N-{1(R)-[(1,2-dihydro-1-methylsulfonylspiro[3H-indole-3,4′-piperidin]-1′-yl)carbonyl]-2-(phenylmethoxy)-ethyl}-2-hydroxyamino-2-methylpropanamide (I), a hydroxyl amine metabolite of a novel growth hormone secretagouge (II) has been developed utilizing high-performance liquid chromatography with ion spray tandem mass spectrometric detection (HPLC–MS–MS). The analyte and an internal standard (III) were isolated from the basified biological matrix using a liquid–liquid extraction with methyl tert.-butyl ether (MTBE). The organic extract was evaporated to dryness at room temperature. The residue was reconstituted in the mobile phase and injected into the HPLC–MS–MS system. Multiple reaction monitoring using the precursor→product ion combinations of m/z 545→267 and 543 →267 was used to quantify I and III, respectively, after chromatographic separation under isocratic conditions. The assay was validated in the concentration range of 0.5 to 500 ng/0.1 ml in both human and dog plasma. The precision of the assay, expressed as relative standard deviation, was less than 10% over the entire concentration range with the exception of the low concentration of 0.5 ng/0.1 ml which was 14.0% for human plasma. The HPLC–MS–MS method provided sufficient sensitivity to completely map the pharmacokinetic time course of I following a single 5 mg dose of II to human subjects and a 0.5 mg/kg dose to beagle dogs.     

Detection and structural investigation of metabolites of stanozolol in human urine by liquid chromatography tandem mass spectrometry

The applicability of LC–MS/MS in precursor ion scan mode for the detection of urinary stanozolol metabolites has been studied. The product ion at m/z 81 has been selected as specific for stanozolol metabolites without a modification in A- or N-rings and the product ions at m/z 97 and 145 for the metabolites hydroxylated in the N-ring and 4-hydroxy-stanozolol metabolites, respectively. Under these conditions, the parent drug and up to 15 metabolites were found in a positive doping test sample. The study of a sample from a chimeric uPA-SCID mouse collected after the administration of stanozolol revealed the presence of 4 additional metabolites. The information obtained from the product ion spectra was used to develop a SRM method for the detection of 19 compounds. This SRM method was applied to several doping positive samples. All the metabolites were detected in both the uPA-SCID mouse sample and positive human samples and were not detected in none of the blank samples tested; confirming the metabolic nature of all the detected compounds. In addition, the application of the SRM method to a single human excretion study revealed that one of the metabolites (4ξ,16ξ-dihydroxy-stanozolol) could be detected in negative ionization mode for a longer period than those commonly used in the screening for stanozolol misuse (3′-hydroxy-stanozolol, 16β-hydroxy-stanozolol and 4β-hydroxy-stanozolol) in doping analysis. The application of the developed approach to several positive doping samples confirmed the usefulness of this metabolite for the screening of stanozolol misuse. Finally, a tentative structure for each detected metabolite has been proposed based on the product ion spectra measured with accurate masses using UPLC–QTOF MS.     

Peptide-Centric Proteome Analysis: An Alternative Strategy for the Analysis of Tandem Mass Spectrometry Data

In mass spectrometry-based bottom-up proteomics, data-independent acquisition is an emerging technique because of its comprehensive and unbiased sampling of precursor ions. However, current data-independent acquisition methods use wide precursor isolation windows, resulting in cofragmentation and complex mixture spectra. Thus, conventional database searching tools that identify peptides by interpreting individual tandem MS spectra are inherently limited in analyzing data-independent acquisition data. Here we discuss an alternative approach, peptide-centric analysis, which tests directly for the presence and absence of query peptides. We discuss how peptide-centric analysis resolves some limitations of traditional spectrum-centric analysis, and we outline the unique characteristics of peptide-centric analysis in general.Tandem mass spectrometry has become the technology of choice for proteome characterization. In a typical bottom-up proteomic experiment, a mixture of proteins is proteolytically digested into peptides, separated by liquid chromatography, and analyzed using tandem mass spectrometry. The ultimate goal is to identify and quantify proteins by detecting and quantifying individual peptides, thereby shedding light on the underlying cellular mechanisms or phenotype. Several modes of data acquisition have been developed for bottom-up proteomics. The most commonly applied mode uses data-dependent acquisition (DDA)¹, in which tandem MS (MS/MS) spectra are acquired from the dissociation of precursor ions selected from an MS survey spectrum. Constrained by the speed of instrumentation, DDA can sample only a subset of precursor ions for MS/MS characterization, generally targeting the top-N most abundant ions detected in the most recent survey spectrum. In addition, DDA is typically coupled with a method referred to as “dynamic exclusion” (1) that attempts to prevent reselection of the same m/z for some specified period of time. These acquisition strategies greatly increase proteome coverage and extend the dynamic range of detection for shotgun proteomics. The resulting MS/MS spectra are typically analyzed using sequence database searching software such as SEQUEST, Mascot, X!Tandem, MaxQuant, Comet, MS-GF+, or OMSSA (2–8). Because these algorithms identify peptides by first associating each individual spectrum with a matching peptide sequence and then aggregating the thus matched spectra into a list of identified peptides, we refer to them as “spectrum-centric analyses.” In spectrum-centric analysis, spectra are most commonly interpreted using database searching, but can also be interpreted using de novo sequencing (9–11), or by searching against a spectrum library (12–14). For the past two decades, spectrum-centric analysis has been an essential driving force for the development of large-scale shotgun proteomics using DDA.DDA is a powerful and well-established technique for LC-MS/MS data acquisition. By targeting precursor ions observed in MS survey scans with highly selective MS/MS scans, DDA generates a large set of high quality MS/MS spectra, which can be automatically interpreted by database searching to identify thousands of proteins in a complex sample. When DDA was introduced, instrumentation was not fast enough to sample every observed precursor in the survey scan; thus, high-intensity precursors were preferentially targeted because they tend to generate higher quality MS/MS spectra that lead to peptide identification. Although this stochastic sampling approach results in a large amount of peptide identification in a single sample run, it comes at the cost of reproducibility of MS/MS acquisition between sample analyses and an inherent bias against low abundance analytes that are less likely to be sampled (15). On modern instrumentation, the speed of MS/MS acquisition has dramatically improved to the point where the majority of MS precursors that are not already in the dynamic exclusion list can be sampled for MS/MS analysis. However, even if every precursor observed in each survey MS scan is sampled, DDA is still biased against low abundance analytes that fall below the limit of detection in the MS analysis and will never be sampled. This bias is a practical limitation in the analysis of a complex mixture with high dynamic range in which many analytes will be below the limit of detection in MS analysis, but remain detectable by the more selective and more sensitive MS/MS analysis (16).DDA remains a powerful method for identifying a large number of proteins in a sample. However, because of the incomplete sampling, when a peptide is not identified in a conventional shotgun experiment using DDA, it is incorrect to conclude that the peptide is missing from the sample, or even below the limit of detection of MS/MS, because the peptide ions may have never been sampled for MS/MS analysis. To overcome such limitations, targeted acquisition approaches such as selected reaction monitoring (SRM, also commonly referred to as multiple reaction monitoring) are often the methods of choice. In targeted acquisition approaches, a set of predetermined precursor ions are systematically subjected to MS/MS characterization throughout the LC time domain. The collision energy for each targeted ion can be optimized for fragmentation efficiency. The resulting data are typically analyzed using “targeted analysis” (17–19), in which the software looks for the co-eluting patterns from a group of predetermined pairs of precursor–product ions (called transitions). With systematic MS/MS sampling and the combined specificity of chromatographic retention time, precursor ion mass, and the distribution of product ions, targeted acquisition allows highly sensitive and reproducible detection of the targeted analytes within a complex mixture.Modern targeted acquisition approaches are the gold standard for sensitively and reproducibly measuring hundreds of peptides in a single LC-MS/MS run (20–22). However, data acquired in this manner is only informative for the set of peptides targeted for analysis. Because of this narrow focus, iterative testing of different hypotheses (i.e. a different set of target peptides) also requires iterative acquisition of additional data. Moreover, assay development often requires retention time scheduling and/or refinement steps to find the optimal peptides and transitions for testing a particular hypothesis.With the existence of two complementary but distinct approaches—DDA for broad sample characterization and targeted acquisition for interrogation of a specific hypothesis—the natural question is if the benefits of both techniques may be combined in a single technique. A potential solution is an alternative mode of bottom-up proteomics referred to as data-independent acquisition (DIA) that has been described and realized with various implementations (16, 23–32). In DIA, the instrument acquires MS/MS spectra systematically and independently from the content of MS survey spectra. These DIA approaches differ from DDA methods, targeted acquisition methods, and from each other in MS/MS isolation window width, total range of precursor m/z covered, duration of completing one cycle of isolation scheme (called the cycle time), single or multiple isolation windows per MS/MS analysis, and instrument platform. Because of the benefits of systematic sampling of the precursor m/z range by MS/MS, data from a single DIA experiment can be useful for both peptide detection and quantification in a complex mixture. Similar to DDA approaches, DIA data is broadly informative because the MS/MS characterization is not specific to a predefined set of peptide targets. Similar to targeted approaches, MS/MS information of peptides across the entire LC time domain can be extracted from DIA data to test a particular hypothesis. As the acquisition speed of modern instrumentation continues to increase, DIA has become more popular because of its comprehensive and unbiased sampling.Although DIA resolves the problem of biased or incomplete MS/MS sampling, current DIA methods come with compromises (33), where the most common compromise is precursor selectivity. Constrained by the speed and accuracy of instrumentation, DIA methods typically use five- to 10-fold wider isolation windows compared with DDA to achieve the same breadth and depth of a single LC-MS/MS run. Because of this reduction in precursor selectivity, MS/MS spectra from DIA are noisier than DDA spectra. In particular, DIA by design generates mixture spectra, each containing product ions from multiple analytes with various abundance and different charge states. Fragmenting multiple analytes together also precludes DIA from tailoring collision energy for every analyte, a standard optimization in DDA and targeted acquisition.The low precursor selectivity and resulting complexity of DIA spectra severely challenges the performance of traditional spectrum-centric analysis, which generally assumes that the detected product ions were derived from a single, isolated precursor. The major challenges in interpreting mixture spectra lie in allowing for multiple contributing precursor ions, assessing the dynamic range of mixture peptides, distributing intensities of product ions shared by contributing peptides, and adjusting statistical confidence estimates. Because almost every spectrum is mixed in DIA data, it is poorly suited for analysis by classic spectrum-centric approaches initially designed for DDA data. Some sophisticated spectrum-centric approaches (34–39) address these challenges by deconvolving mixture spectra into pseudo spectra or by matching mixture spectra to combinations of product ions from multiple candidate peptides. However, identification of low abundance analytes by interpreting mixture spectra is inherently difficult because the MS/MS signals from low abundance analytes are naturally overwhelmed by the signals from high abundance ones.Recently, Gillet et al. demonstrated an alternative approach that analyzes DIA data in a targeted fashion (24), opening a new door for the investigation of tandem mass spectrometry data. Much like targeted analysis of transitions used in targeted acquisition methods, Gillet et al. use extracted ion chromatograms to detect and quantify query peptides. Similarly, Weisbrod et al. identify peptides by searching peptide fragmentation patterns against DIA data (25). Instead of interpreting individual spectra in a spectrum-centric fashion, these alternative approaches take each peptide of interest and ask: “Is this peptide detected in the data?” We refer to this approach as “peptide-centric analysis” in contrast with “spectrum-centric analysis.” In peptide-centric analysis, each peptide is detected by searching the MS and MS/MS data for signals selective for the query peptide. Peptide-centric analysis covers all methods that use peptides as an independent query unit, including but not limited to the targeted analysis. Peptide-centric analysis is intrinsically very different from spectrum-centric analysis (Fig. 1) and better suited for addressing many biological problems. This perspective discusses the analytical advantages of peptide-centric analysis and how they could translate to improvements in protein inference, and the analysis of DIA data.

Table I

Analytical comparison of spectrum-centric analysis versus peptide-centric analysis

Biological reactions at phosphorus: VII. The nature of metaphosphate ion,PO3−, as a reaction intermediate (1)

In order to improve our understanding of biological phosphorylations by “high-energy” compounds such as ATP, the hypothesis of metaphosphate ion as an intermediate in certain phosphorylation reactions has been critically examined. We have studied the rates and product composition for the solvolysis of the neutral form of N,N-dimethylphosphoroguanidinate (DMPG) at 30.5°C in various water-alcohol mixtures. The rates of solvolysis were found to decrease as the mole percent of the alcohol increased, but no systematic relationship with dielectric constant or Grunwald-Winstein y values was evident. A 1 : 1 correspondence between the percentage alkyl phosphate produced and the mole percent alcohol present was found with methanol, ethanol, and low concentrations of 2-propanol. At higher concentrations of 2-propanol, the product ratio favors water as nucleophile probably due to selective solvation of the metaphosphate precursor by water. These results indicate that metaphosphate mechanisms have a variable amount of nucleophilic participation. Although the reaction of phosphoroguanidines appears to involve metaphosphate ion as a free intermediate, analysis of results in the literature indicate that less reactive metaphosphate precursors react with nucleophilic participation. Extrapolation of these results to biological phosphorylations leads to the conclusion that nucleophilic participation may be an important feature of enzymic transition states due to the favorable orientation of nucleophile and incipient metaphosphate at enzymic active sites.     

Global combined precursor isotopic labeling and isobaric tagging (cPILOT) approach with selective MS3 acquisition

Recently, we reported a novel proteomics quantitation scheme termed “combined precursor isotopic labeling and isobaric tagging (cPILOT)” that allows for the identification and quantitation of nitrated peptides in as many as 12–16 samples in a single experiment. cPILOT offers enhanced multiplexing and posttranslational modification specificity, however excludes global quantitation for all peptides present in a mixture and underestimates reporter ion ratios similar to other isobaric tagging methods due to precursor co‐isolation. Here, we present a novel chemical workflow for cPILOT that can be used for global tagging of all peptides in a mixture. Specifically, through low pH precursor dimethylation of tryptic or LysC peptides followed by high pH tandem mass tags, the same reporter ion can be used twice in a single experiment. Also, to improve triple‐stage mass spectrometry (MS³) data acquisition, a selective MS³ method that focuses on product selection of the y₁ fragment of lysine‐terminated peptides is incorporated into the workflow. This novel cPILOT workflow has potential for global peptide quantitation that could lead to enhanced sample multiplexing and increase the number of quantifiable spectra obtained from MS³ acquisition methods.     

Novel approach in LC-MS/MS using MRM to generate a full profile of acyl-CoAs: discovery of acyl-dephospho-CoAs

A metabolomic approach to selectively profile all acyl-CoAs was developed using a programmed multiple reaction monitoring (MRM) method in LC-MS/MS and was employed in the analysis of various rat organs. The programmed MRM method possessed 300 mass ion transitions with the mass difference of 507 between precursor ion (Q1) and product ion (Q3), and the precursor ion started from m/z 768 and progressively increased one mass unit at each step. Acyl-dephospho-CoAs resulting from the dephosphorylation of acyl-CoAs were identified by accurate MS and fragmentation. Acyl-dephospho-CoAs were also quantitatively scanned by the MRM method with the mass difference of 427 between Q1 and Q3 mass ions. Acyl-CoAs and dephospho-CoAs were assayed with limits of detection ranging from 2 to 133 nM. The accuracy of the method was demonstrated by assaying a range of concentrations of spiked acyl-CoAs with the results of 80–114%. The distribution of acyl-CoAs reflects the metabolic status of each organ. The physiological role of dephosphorylation of acyl-CoAs remains to be further characterized. The methodology described herein provides a novel strategy in metabolomic studies to quantitatively and qualitatively profile all potential acyl-CoAs and acyl-dephospho-CoAs.     

L-arginine assay with the use of arginase I

A highly selective and sensitive method for the quantitative determination of L-arginine (Arg) with a fluorescent detection of the reaction product has been developed. The method is based on the use of human liver arginase I isolated from a recombinant producer strain, yeast Hansenula polymorpha, and 2,3-butanedione monoxime, which is used to detect carbamide—the product of enzymatic reactions. The linear concentration range for determining Arg in the final reaction mixture varies from 0.2 to 250 μM, and the detection limit is 0.16 μM. Tests of the new method using commercial Arg-containing pharmaceutical preparations showed a high correlation (R = 1.0) of the results with the manufacturer’s data and the results of other methods for Arg detection.     

Automated Validation of Results and Removal of Fragment Ion Interferences in Targeted Analysis of Data-independent Acquisition Mass Spectrometry (MS) using SWATHProphet

Proteomics by mass spectrometry technology is widely used for identifying and quantifying peptides and proteins. The breadth and sensitivity of peptide detection have been advanced by the advent of data-independent acquisition mass spectrometry. Analysis of such data, however, is challenging due to the complexity of fragment ion spectra that have contributions from multiple co-eluting precursor ions. We present SWATHProphet software that identifies and quantifies peptide fragment ion traces in data-independent acquisition data, provides accurate probabilities to ensure results are correct, and automatically detects and removes contributions to quantitation originating from interfering precursor ions. Integration in the widely used open source Trans-Proteomic Pipeline facilitates subsequent analyses such as combining results of multiple data sets together for improved discrimination using iProphet and inferring sample proteins using ProteinProphet. This novel development should greatly help make data-independent acquisition mass spectrometry accessible to large numbers of users.Mass spectrometry is widely used to identify and quantify protein samples. Proteins are typically cleaved into peptides (either enzymatically or chemically), separated by at least one-dimensional fractionation (e.g. liquid chromatography), and collisionally fragmented, and fragment ions are detected by their unique m/z values in a mass spectrometer (1). Data-dependent acquisition (shotgun) selects individual precursor ions for fragmentation and is limited in its ability to consistently detect large numbers of peptides, particularly those of lower intensity, in samples (2). In contrast, selective reaction monitoring (SRM)¹ is a targeted approach in which known precursor and a set of fragment ions are monitored over time upon selection by mass filters in a triple quadrupole instrument. The selected fragment ions in conjunction with the parent ion constitute a highly sensitive molecular assay specific for a precursor ion of interest. Although this strategy has been successfully applied for a large number of biological studies, it is limited by low throughput.An alternative approach, data-independent acquisition (DIA), aims to overcome the low throughput limitation of SRM while maintaining full quantitative analyses. It selects all ions within a sliding m/z precursor window for fragmentation (3–7) and effectively creates a digital record of the complete peptide contents of the sample. Its increased sensitivity, however, is limited by the challenge of interpreting fragment ion spectra generated from multiple precursors. This can be done by spectral deconvolution followed by database search (1, 8) or by query of the data with preselected fragment ions in a spectral library in a manner similar to targeted approaches such as SRM (3).Software packages currently available for targeted analysis of DIA MS data with precursor ion assays contained within a spectral library include PeakView^TM from (Sciex, Framingham, MA), for data generated on a TripleTOF mass spectrometer. The proprietary Spectronaut (Biognosys AG, Zurich, Switzerland) and open source OpenSWATH software (9) are adaptations of the mProphet software suite (10) originally designed for SRM data, and the widely used SRM software Skyline (11) now also incorporates mProphet software to handle DIA MS data. None of these available programs, however, provide validation of results with computed probabilities or detection and removal of fragment ion interferences that give rise to inaccurate quantitation and decreased sensitivity.Here we present SWATHProphet software that performs these functions in conjunction with a high quality spectral library. SWATHProphet validates results with accurate probabilities of being correct. These probabilities serve as input to downstream analyses in the highly developed Trans-Proteomic Pipeline (TPP) (12), such as combining together results of multiple runs for improved discrimination with iProphet (13) and inferring sample proteins with ProteinProphet (14). In addition, SWATHProphet uses these probabilities to help cope with complex spectra by automatically detecting fragment ion interferences and removing them in silico to yield accurate quantitation and adjusted probabilities.     

Chemical Imaging on Liver Steatosis Using Synchrotron Infrared and ToF-SIMS Microspectroscopies

Fatty liver or steatosis is a frequent histopathological change. It is a precursor for steatohepatitis that may progress to cirrhosis and in some cases to hepatocellular carcinoma. In this study we addressed the in situ composition and distribution of biochemical compounds on tissue sections of steatotic liver using both synchrotron FTIR (Fourier transform infrared) and ToF-SIMS (time of flight secondary ion mass spectrometry) microspectroscopies. FTIR is a vibrational spectroscopy that allows investigating the global biochemical composition and ToF-SIMS lead to identify molecular species in particular lipids. Synchrotron FTIR microspectroscopy demonstrated that bands linked to lipid contribution such as -CH₃ and -CH₂ as well as esters were highly intense in steatotic vesicles. Moreover, a careful analysis of the -CH₂ symmetric and anti-symmetric stretching modes revealed a slight downward shift in spectra recorded inside steatotic vesicles when compared to spectra recorded outside, suggesting a different lipid environment inside the steatotic vesicles. ToF-SIMS analysis of such steatotic vesicles disclosed a selective enrichment in cholesterol as well as in diacylglycerol (DAG) species carrying long alkyl chains. Indeed, DAG C36 species were selectively localized inside the steatotic vesicles whereas DAG C30 species were detected mostly outside. Furthermore, FTIR detected a signal corresponding to olefin (C = C, 3000-3060 cm⁻¹) and revealed a selective localization of unsaturated lipids inside the steatotic vesicles. ToF-SIMS analysis definitely demonstrated that DAG species C30, C32, C34 and C36 carrying at least one unsaturated alkyl chain were selectively concentrated into the steatotic vesicles. On the other hand, investigations performed on the non-steatotic part of the fatty livers have revealed important changes when compared to the normal liver. Although the non-steatotic regions of fatty livers exhibited normal histological aspect, IR spectra demonstrated an increase in the lipid content and ToF-SIMS detected small lipid droplets corresponding most likely to the first steps of lipid accretion.     

What is a species? Essences and generation

Arguments against essentialism in biology rely strongly on a claim that modern biology abandoned Aristotle’s notion of a species as a class of necessary and sufficient properties. However, neither his theory of essentialism, nor his logical definition of species and genus (eidos and genos) play much of a role in biological research and taxonomy, including his own. The objections to natural kinds thinking by early twentieth century biologists wrestling with the new genetics overlooked the fact that species have typical developmental cycles and most have a large shared genetic component. These are the “what-it-is-to-be” members of that species. An intrinsic biological essentialism does not commit us to Aristotelian notions, nor even modern notions, of essence. There is a long-standing definition of “species” and its precursor notions that goes back to the Greeks, and which Darwin and pretty well all biologists since him share, that I call the Generative Conception of Species. It relies on there being a shared generative power that makes progeny resemble parents. The “what-it-is-to-be” a member of that species is that developmental type, mistakes in development notwithstanding. Moreover, such “essences” have always been understood to include deviations from the type. Finally, I shall examine some implications of the collapse of the narrative about essences in biology.     

LC/ESI-MS/MS detection of FAs by charge reversal derivatization with more than four orders of magnitude improvement in sensitivity

Quantitative analysis of fatty acids (FAs) is an important area of analytical biochemistry. Ultra high sensitivity FA analysis usually is done with gas chromatography of pentafluorobenzyl esters coupled to an electron-capture detector. With the popularity of electrospray ionization (ESI) mass spectrometers coupled to liquid chromatography, it would be convenient to develop a method for ultra high sensitivity FA detection using this equipment. Although FAs can be analyzed by ESI in negative ion mode, this method is not very sensitive. In this study, we demonstrate a new method of FA analysis based on conversion of the carboxylic acid to an amide bearing a permanent positive charge, N-(4-aminomethylphenyl)pyridinium (AMPP) combined with analysis on a reverse-phase liquid chromatography column coupled to an ESI mass spectrometer operating in positive ion mode. This leads to an ∼60,000-fold increase in sensitivity compared with the same method carried out with underivatized FAs. The new method is about 10-fold more sensitive than the existing method of gas chromatography/electron-capture mass spectrometry of FA pentafluorobenzyl esters. Furthermore, significant fragmentation of the precursor ions in the nontag portion improves analytical specificity. We show that a large number of FA molecular species can be analyzed with this method in complex biological samples such as mouse serum.     

Highly sensitive determination of TS-962 (HL-004), a novel acyl-CoA:cholesterol acyltransferase inhibitor,in rat and rabbit plasma by liquid chromatography and atmospheric pressure chemical ionization-tandem mass spectrometry combined with a column-switching technique

A quantitative bioanalytical method with excellent specificity using liquid chromatography (LC) atmospheric pressure chemical ionization-tandem mass spectrometry (APCI-MS–MS) combined with a column-switching technique has been developed for the highly sensitive and reliable determination of TS-962 (HL-004), a novel acyl-CoA:cholesterol acyltransferase (ACAT) inhibitor, in rat and rabbit plasma. The method involves protein precipitation of a 25-μl aliquot of plasma sample with eight volumes of methanol containing a deuterium-labeled internal standard, the direct injection of a methanolic supernatant into the analytical instrumentation with no sample evaporation and reconstitution steps, automated on-line clean-up on a C₁₈ short trapping column (10 mm×4.0 mm I.D.) followed by separation on a C₁₈ analytical column (50 mm×4.6 mm I.D.), and detection with APCI-MS–MS using m/z 448 ([M+H]⁺) as a precursor ion and m/z 178 as a product ion in a selected reaction monitoring mode. The lower limit of quantification was 1 ng/ml, and good linearity of the calibration graph was obtained in the range of 1∼490 ng/ml with excellent reliability. The developed method enabled pharmacokinetic profiles to be determined for rats and rabbits with sequential plasma collection from an individual animal.     

Classification and identification of bacteria by mass spectrometry and computational analysis

Background

In general, the definite determination of bacterial species is a tedious process and requires extensive manual labour. Novel technologies for bacterial detection and analysis can therefore help microbiologists in minimising their efforts in developing a number of microbiological applications.

Methodology

We present a robust, standardized procedure for automated bacterial analysis that is based on the detection of patterns of protein masses by MALDI mass spectrometry. We particularly applied the approach for classifying and identifying strains in species of the genus Erwinia. Many species of this genus are associated with disastrous plant diseases such as fire blight. Using our experimental procedure, we created a general bacterial mass spectra database that currently contains 2800 entries of bacteria of different genera. This database will be steadily expanded. To support users with a feasible analytical method, we developed and tested comprehensive software tools that are demonstrated herein. Furthermore, to gain additional analytical accuracy and reliability in the analysis we used genotyping of single nucleotide polymorphisms by mass spectrometry to unambiguously determine closely related strains that are difficult to distinguish by only relying on protein mass pattern detection.

Conclusions

With the method for bacterial analysis, we could identify fire blight pathogens from a variety of biological sources. The method can be used for a number of additional bacterial genera. Moreover, the mass spectrometry approach presented allows the integration of data from different biological levels such as the genome and the proteome.