Keith Richardson

Simultaneous Qualitative and Quantitative Analysis of theEscherichia coli Proteome A Sweet Tale

We describe a novel LCMS approach to the relative quantitation and simultaneous identification of proteins within the complex milieu of unfractionated Escherichia coli. This label-free, LCMS acquisition method observes all detectable, eluting peptides and their corresponding fragment ions. Postacquisition data analysis methods extract both the chromatographic and the mass spectrometric information on the tryptic peptides to provide time-resolved, accurate mass measurements, which are subsequently used for quantitation and identification of constituent proteins. The response of E. coli to carbon source variation is well understood, and it is thus commonly used as a model biological system when validating an analytical method. Using this LCMS approach, we characterized proteins isolated from E. coli grown in glucose, lactose, and acetate. The change in relative abundance of the corresponding proteins was measured from peptides common to both conditions. Protein identities were also determined for those peptides that were unique to each condition, and these identities were found to be consistent with the underlying biochemical restrictions imposed by the growth conditions. The relative change in abundance of the characterized proteins ranged from 0.1- to 90-fold among the three binary comparisons. The overall coverage of the characterized proteins ranged from 10 to 80%, consisting of one to 34 peptides per protein. The quantitative results obtained from our study were comparable to other existing proteomic and transcriptional profiling approaches. This study illustrates the robustness of this novel LCMS approach for the simultaneous quantitative and comprehensive qualitative analysis of proteins in complex mixtures.

Simultaneous qualitative and quantitative analysis of the E. coli proteome: A sweet tale

We describe a novel LCMS approach to the relative quantitation and simultaneous identification of proteins within the complex milieu of unfractionated Escherichia coli. This label-free, LCMS acquisition method observes all detectable, eluting peptides and their corresponding fragment ions. Postacquisition data analysis methods extract both the chromatographic and the mass spectrometric information on the tryptic peptides to provide time-resolved, accurate mass measurements, which are subsequently used for quantitation and identification of constituent proteins. The response of E. coli to carbon source variation is well understood, and it is thus commonly used as a model biological system when validating an analytical method. Using this LCMS approach, we characterized proteins isolated from E. coli grown in glucose, lactose, and acetate. The change in relative abundance of the corresponding proteins was measured from peptides common to both conditions. Protein identities were also determined for those peptides that were unique to each condition, and these identities were found to be consistent with the underlying biochemical restrictions imposed by the growth conditions. The relative change in abundance of the characterized proteins ranged from 0.1- to 90-fold among the three binary comparisons. The overall coverage of the characterized proteins ranged from 10 to 80%, consisting of one to 34 peptides per protein. The quantitative results obtained from our study were comparable to other existing proteomic and transcriptional profiling approaches. This study illustrates the robustness of this novel LCMS approach for the simultaneous quantitative and comprehensive qualitative analysis of proteins in complex mixtures.

Structural characterization of drug-like compounds by ion mobility mass spectrometry: comparison of theoretical and experimentally derived nitrogen collision cross sections.

We present the use of drug-like molecules as a traveling wave (T-wave) ion mobility (IM) calibration sample set, covering the m/z range of 122.1-609.3, the nitrogen collision cross-section (Ω(N(2))) range of 124.5-254.3 Å(2) and the helium collision cross-section (Ω(He)) range of 63.0-178.8 Å(2). Absolute Ω(N(2)) and Ω(He) values for the drug-like calibrants and two diastereomers were measured using a drift-tube instrument with radio frequency (RF) ion confinement. T-wave drift-times for the protonated diastereomers betamethasone and dexamethasone are reproducibly different. Calibration of these drift-times yields T-wave Ω(N(2)) values of 189.4 and 190.4 Å(2), respectively. These results demonstrate the ability of T-wave IM spectrometry to differentiate diastereomers differing in Ω(N(2)) value by only 1 Å(2), even though the resolution of these IM experiments were ∼40 (Ω/ΔΩ). Demonstrated through density functional theory optimized geometries and ionic electrostatic surface potential analysis, the small but measurable mobility difference between the two diastereomers is mainly due to short-range van der Waals interactions with the neutral buffer gas and not long-range charge-induced dipole interactions. The experimental RF-confining drift-tube and T-wave Ω(N(2)) values were also evaluated using a nitrogen based trajectory method, optimized for T-wave operating temperature and pressures, incorporating additional scaling factors to the Lennard-Jones potentials. Experimental Ω(He) values were also compared to the original and optimized helium based trajectory methods.

Ion Mobility-Derived Collision Cross Section As an Additional Measure for Lipid Fingerprinting and Identification

Despite recent advances in analytical and computational chemistry, lipid identification remains a significant challenge in lipidomics. Ion-mobility spectrometry provides an accurate measure of the molecules’ rotationally averaged collision cross-section (CCS) in the gas phase and is thus related to ionic shape. Here, we investigate the use of CCS as a highly specific molecular descriptor for identifying lipids in biological samples. Using traveling wave ion mobility mass spectrometry (MS), we measured the CCS values of over 200 lipids within multiple chemical classes. CCS values derived from ion mobility were not affected by instrument settings or chromatographic conditions, and they were highly reproducible on instruments located in independent laboratories (interlaboratory RSD < 3% for 98% of molecules). CCS values were used as additional molecular descriptors to identify brain lipids using a variety of traditional lipidomic approaches. The addition of CCS improved the reproducibility of analysis in a liquid chromatography-MS workflow and maximized the separation of isobaric species and the signal-to-noise ratio in direct-MS analyses (e.g., “shotgun” lipidomics and MS imaging). These results indicate that adding CCS to databases and lipidomics workflows increases the specificity and selectivity of analysis, thus improving the confidence in lipid identification compared to traditional analytical approaches. The CCS/accurate-mass database described here is made publicly available.

Use of ion mobility mass spectrometry and a collision cross‐section algorithm to study an organometallic ruthenium anticancer complex and its adducts with a DNA oligonucleotide

We report the development of an enhanced algorithm for the calculation of collision cross-sections in combination with Travelling-Wave ion mobility mass spectrometry technology and its optimisation and evaluation through the analysis of an organoruthenium anticancer complex [(eta6-biphenyl)Ru(II)(en)Cl]+. Excellent agreement was obtained between the experimentally determined and theoretically determined collision cross-sections of the complex and its major product ion formed via collision-induced dissociation. Collision cross-sections were also experimentally determined for adducts of this ruthenium complex with the single-stranded oligonucleotide hexamer d(CACGTG). Ion mobility tandem mass spectrometry measurements have allowed the binding sites for ruthenium on the oligonucleotide to be determined.

Continuous sample deposition from reversed‐phase liquid chromatography to tracks on a matrix‐assisted laser desorption/ionization precoated target for the analysis of protein digests

Peptide mass fingerprinting by matrix‐assisted laser desorption/ionization (MALDI)‐mass spectrometry (MS) is one of the standard high‐throughput methods for protein identification today. Traditionally this method has been based on spotting peptide mixtures onto MALDI targets. While this method works well for more abundant proteins, low‐abundance proteins mixed with high‐abundance proteins tend to go undetected due to ion suppression effects, instrumental dynamic range limitations and chemical noise interference. We present an alternative approach where liquid chromatography (LC) effluent is continuously collected as linear tracks on a MALDI target. In this manner the chromatographic separation is spatially preserved on the target, which enables generation of off‐line LC‐MS and LC‐MS/MS data by MALDI. LC‐MALDI sample collection provides improved sensitivity and dynamic range, spatial resolution of peptides along the sample track, and permits peptide mass mapping of low‐abundance proteins in mixtures containing high‐abundance proteins. In this work, standard and ribosomal protein digests are resolved and captured using LC‐MALDI sample collection and analyzed by MALDI‐TOF‐MS.

Ion mobility tandem mass spectrometry enhances performance of bottom-up proteomics

One of the limiting factors in determining the sensitivity of tandem mass spectrometry using hybrid quadrupole orthogonal acceleration time-of-flight instruments is the duty cycle of the orthogonal ion injection system. As a consequence, only a fraction of the generated fragment ion beam is collected by the time-of-flight analyzer. Here we describe a method utilizing postfragmentation ion mobility spectrometry of peptide fragment ions in conjunction with mobility time synchronized orthogonal ion injection leading to a substantially improved duty cycle and a concomitant improvement in sensitivity of up to 10-fold for bottom-up proteomic experiments. This enabled the identification of 7500 human proteins within 1 day and 8600 phosphorylation sites within 5 h of LC-MS/MS time. The method also proved powerful for multiplexed quantification experiments using tandem mass tags exemplified by the chemoproteomic interaction analysis of histone deacetylases with Trichostatin A.

Assigning structures to gas-phase peptide cations and cation-radicals. An infrared multiphoton dissociation, ion mobility, electron transfer, and computational study of a histidine peptide ion.

Infrared multiphoton dissociation (IRMPD) spectroscopy, using a free-electron laser, and ion mobility measurements, using both drift-cell and traveling-wave instruments, were used to investigate the structure of gas-phase peptide (AAHAL + 2H)(2+) ions produced by electrospray ionization. The experimental data from the IRMPD spectra and collisional cross section (Ω) measurements were consistent with the respective infrared spectra and Ω calculated for the lowest-energy peptide ion conformer obtained by extensive molecular dynamics searches and combined density functional theory and ab initio geometry optimizations and energy calculations. Traveling-wave ion mobility measurements were employed to obtain the Ω of charge-reduced peptide cation-radicals, (AAHAL + 2H)(+●), and the c(3), c(4), z(3), and z(4) fragments from electron-transfer dissociation (ETD) of (AAHAL + 2H)(2+). The experimental Ω for the ETD charge-reduced and fragment ions were consistent with the values calculated for fully optimized ion structures and indicated that the ions retained specific hydrogen bonding motifs from the precursor ion. In particular, the Ω for the doubly protonated ions and charge-reduced cation-radicals were nearly identical, indicating negligible unfolding and small secondary structure changes upon electron transfer. The experimental Ω for the (AAHAL + 2H)(+●) cation-radicals were compatible with both zwitterionic and histidine radical structures formed by electron attachment to different sites in the precursor ion, but did not allow their distinction. The best agreement with the experimental Ω was found for ion structures fully optimized with M06-2X/6-31+G(d,p) and using both projection approximation and trajectory methods to calculate the theoretical Ω values.

Simulating and validating proteomics data and search results

The computational simulation of complete proteomic data sets and their utility to validate detection and interpretation algorithms, to aid in the design of experiments and to assess protein and peptide false discovery rates is presented. The simulation software has been developed for emulating data originating from data‐dependent and data‐independent LC‐MS workflows. Data from all types of commonly used hybrid mass spectrometers can be simulated. The algorithms are based on empirically derived physicochemical liquid and gas phase models for proteins and peptides. Sample composition in terms of complexity and dynamic range, as well as chromatographic, experimental and MS conditions, can be controlled and adjusted independently. The effect of on‐column amounts, gradient length, mass resolution and ion mobility on search specificity will be demonstrated using tryptic peptides from human and yeast cellular lysates simulated over five orders of magnitude in dynamic range. Initial justification of the simulated data sets is achieved by comparing and contrasting the in silico simulated data to experimentally derived results from a 48 protein mixture, spanning a similar magnitude of five orders of magnitude. Additionally, experimental data from replicate and dilutions series experiments will be utilized to determine error rates at the peptide and protein level with respect to mass, area, retention and drift time. The data presented reveal a high degree of similarity at the ion detection, peptide and protein level when analyzed under similar conditions.

ProbSeq—A Fragmentation Model for Interpretation of Electrospray Tandem Mass Spectrometry Data

We describe a probabilistic peptide fragmentation model for use in protein databank searching and de novo sequencing of electrospray tandem mass spectrometry data. A probabilistic framework for tuning of the model using a range of well-characterized samples are introduced. We present preliminary results of our tuning efforts.