Project description:Measuring the relative abundances of heavy stable isotopes of the elements C, H, N, and O in proteins is of interest in environmental science, archeology, zoology, medicine, and other fields. The isotopic abundance measurements of the fine structure of immonium ions with ultrahigh resolution mass spectrometry obtained in gas-phase fragmentation of polypeptides have previously uncovered anomalous deuterium enrichment in (hydroxy)proline of bone collagen in marine mammals. Here, we provide a detailed description and validation of this approach and demonstrate per mil-range precision of isotopic ratio measurements in aliphatic residues from proteins and cell lysates. The analysis consists of proteomics-type experiment demanding sub-microgram amounts of a protein sample and providing concomitantly protein sequence data allowing one to verify sample purity and establish its identity. A novel software tool protein amino acid-resolved isotopic ratio mass spectrometry (PAIR-MS) is presented for extracting isotopic ratio data from the raw data files acquired on an Orbitrap mass spectrometer.
Project description:The normalized cross-correlation (NCC), usually its 2D version, is routinely encountered in template matching algorithms, such as in facial recognition, motion-tracking, registration in medical imaging, etc. Its rapid computation becomes critical in time sensitive applications. Here I develop a scheme for the computation of NCC by fast Fourier transform that can favorably compare for speed efficiency with other existing techniques and may outperform some of them given an appropriate search scenario.
Project description:The fine structure of isotopic peak distributions of glutathione in mass spectra is measured using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) at 12 and 15 T magnetic field, with an infinity cell and a dynamically harmonized cell (DHC) respectively. The resolved peaks in the fine structure of glutathione consist of 2H, 13C, 15N, 17O, 18O, 33S, 34S, 36S, and combinations of them. The positions of the measured fine structure peaks agree with the simulated isotopic distributions with the mass error less than 250 ppb in broadband mode for the infinity cell and no more than 125 ppb with the DHC after internal calibration. The 15 T FT-ICR MS with DHC cell also resolved around 30 isotopic peaks in broadband with a resolving power (RP) of 2 M. In narrowband (m/z 307-313), our current highest RP of 13.9 M in magnitude mode was observed with a 36 s transient length by the 15 T FT-ICR MS with the DHC and 2ω detection on the 15 T offers slightly higher RP (14.8 M) in only 18 s. For the 12 T FT-ICR MS with the infinity cell, the highest RP achieved was 15.6 M in magnitude mode with a transient length of 45 s. Peak decay was observed for low abundance peaks, which could be due to the suppression effects from the most abundant peak, as result of ion cloud Coulombic interactions (space-charge).
Project description:The theory of the continuous two-dimensional (2D) Fourier Transform in polar coordinates has been recently developed but no discrete counterpart exists to date. In the first part of this two-paper series, we proposed and evaluated the theory of the 2D Discrete Fourier Transform (DFT) in polar coordinates. The theory of the actual manipulated quantities was shown, including the standard set of shift, modulation, multiplication, and convolution rules. In this second part of the series, we address the computational aspects of the 2D DFT in polar coordinates. Specifically, we demonstrate how the decomposition of the 2D DFT as a DFT, Discrete Hankel Transform and inverse DFT sequence can be exploited for coding. We also demonstrate how the proposed 2D DFT can be used to approximate the continuous forward and inverse Fourier transform in polar coordinates in the same manner that the 1D DFT can be used to approximate its continuous counterpart.
Project description:Metabolomics is an interdisciplinary field that aims to study all metabolites < 1500 Da that are ubiquitously found within all organisms. Metabolomics is experiencing exponential growth and commonly relies on high-resolution mass spectrometry (HRMS). Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is a form of HRMS that is particularly well suited for metabolomics research due to its exceptionally high resolution (105-106) and sensitivity with a mass accuracy in parts per billion (ppb). In this regard, FT-ICR-MS can provide valuable insights into the metabolomics analysis of complex biological systems due to unique capabilities such as the easy separation of isobaric and isomeric species, isotopic fine structure analysis, spatial resolution of metabolites in cells and tissues, and a high confidence (<1 ppm mass error) in metabolite identification. Alternatively, the large and complex data sets, long acquisition times, high cost, and limited access mainly through national mass spectrometry facilities may impede the routine adoption of FT-ICR-MS by metabolomics researchers. This review examines recent applications of FT-ICR-MS metabolomics in the search for clinical and non-human biomarkers; for the analysis of food, beverage, and environmental samples; and for the high-resolution imaging of tissues and other biological samples. We provide recent examples of metabolomics studies that highlight the advantages of FT-ICR-MS for the detailed and reliable characterization of the metabolome. Additionally, we offer some practical considerations for implementing FT-ICR-MS into a research program by providing a list of FT-ICR-MS facilities and by identifying different high-throughput interfaces, varieties of sample types, analysis methods (e.g., van Krevelen diagrams, Kendrick mass defect plot, etc.), and sample preparation and handling protocols used in FT-ICR-MS experiments. Overall, FT-ICR-MS holds great promise as a vital research tool for advancing metabolomics investigations.
Project description:A multiplexed tandem mass spectrometry (MS/MS) technique known as iterative accumulation multiplexing (IAM) has been implemented on a hybrid quadrupole Fourier transform ion cyclotron resonance mass spectrometer (Q-FTICR-MS). The IAM experiment resulted in obtaining MS/MS spectra for six analytes in two MS/MS experiments while characteristic resolving power and mass measurement accuracies were maintained. Parent-product ion correlations were graphically represented in a "ratiogram" where each product ion is encoded with a ratio unique to the parent ion from which it was formed. This is the first example of multiplexed MS on a FTICR instrument where the ions are encoded externally to the ICR cell. By performing the encoding external to the ICR cell, one set of ions can be encoded while the previous set of ions is being analyzed in the cell, maximizing the use of the continuous ion current emanating from the electrospray ionization source.
Project description:INTRODUCTION:Direct injection Fourier-transform mass spectrometry (FT-MS) allows for the high-throughput and high-resolution detection of thousands of metabolite-associated isotopologues. However, spectral artifacts can generate large numbers of spectral features (peaks) that do not correspond to known compounds. Misassignment of these artifactual features creates interpretive errors and limits our ability to discern the role of representative features within living systems. OBJECTIVES:Our goal is to develop rigorous methods that identify and handle spectral artifacts within the context of high-throughput FT-MS-based metabolomics studies. RESULTS:We observed three types of artifacts unique to FT-MS that we named high peak density (HPD) sites: fuzzy sites, ringing and partial ringing. While ringing artifacts are well-known, fuzzy sites and partial ringing have not been previously well-characterized in the literature. We developed new computational methods based on comparisons of peak density within a spectrum to identify regions of spectra with fuzzy sites. We used these methods to identify and eliminate fuzzy site artifacts in an example dataset of paired cancer and non-cancer lung tissue samples and evaluated the impact of these artifacts on classification accuracy and robustness. CONCLUSION:Our methods robustly identified consistent fuzzy site artifacts in our FT-MS metabolomics spectral data. Without artifact identification and removal, 91.4% classification accuracy was achieved on an example lung cancer dataset; however, these classifiers rely heavily on artifactual features present in fuzzy sites. Proper removal of fuzzy site artifacts produces a more robust classifier based on non-artifactual features, with slightly improved accuracy of 92.4% in our example analysis.
Project description:A new instrument configuration for native ion mobility-mass spectrometry (IM-MS) is described. Macromolecule ions are generated by using a static ESI source coupled to an RF ion funnel, and these ions are then mobility and mass analyzed using a periodic focusing drift tube IM analyzer and an Orbitrap mass spectrometer. The instrument design retains the capabilities for first-principles determination of rotationally averaged ion-neutral collision cross sections and high-resolution measurements in both mobility and mass analysis modes for intact protein complexes. Operation in the IM mode utilizes FT-IMS modes (originally described by Knorr ( Knorr , F. J. Anal. Chem . 1985 , 57 ( 2 ), 402 - 406 )), which provides a means to overcome the inherent duty cycle mismatch for drift tube (DT)-IM and Orbitrap mass analysis. The performance of the native ESI-FT-DT-IM-Orbitrap MS instrument was evaluated using the protein complexes Gln K (MW 44 kDa) and streptavidin (MW 53 kDa) bound to small molecules (ADP and biotin, respectively) and transthyretin (MW 56 kDa) bound to thyroxine and zinc.
Project description:We present a subspace method that accelerates data acquisition using Fourier transform-ion cyclotron resonance (FT-ICR) mass spectrometry imaging (MSI). For MSI of biological tissue samples, there is a finite number of heterogeneous tissue types with distinct chemical profiles that introduce redundancy in the high-dimensional measurements. Our subspace model exploits the redundancy in data measured from whole-slice tissue samples by decomposing the transient signals into linear combinations of a set of basis transients with the desired spectral resolution. This decomposition allowed us to design a strategy that acquires a subset of long transients for basis determination and short transients for the remaining pixels, drastically reducing the acquisition time. The computational reconstruction strategy can maintain high-mass-resolution and spatial-resolution MSI while providing a 10-fold improvement in throughput. We validated the capability of the subspace model using a rat sagittal brain slice imaging data set. Comprehensive evaluation of the quality of the mass spectral and ion images demonstrated that the reconstructed data produced by the reported method required only 15% of the typical acquisition time and exhibited both qualitative and quantitative consistency when compared to the original data. Our method enables either higher sample throughput or higher-resolution images at similar acquisition lengths, providing greater flexibility in obtaining FT-ICR MSI measurements.