Evaluating reproducibility and similarity of mass and intensity data in complex spectra--applications to tubulin

Taurine Is Covalently Incorporated into Alpha-Tubulin

Taurine is the most abundant free amino acid in the human body. It is found in relatively high concentrations (1-10 mM) in many animal tissues but not in plants. It has been studied since the early 1800s but has not been found to be covalently incorporated into proteins in any animal tissue. Taurine has been found in only one macromolecular complex as a post-transcriptional modification to mitochondrial tRNA. Tubulin is the subunit of microtubules found in all eukaryotic species and almost all eukaryotic cells and subject to numerous post-translational modifications (PTMs). An important PTM on α-tubulin is the removal and re-ligation of the final carboxyl residue, tyrosine. We here demonstrate that taurine can be covalently incorporated at the C-terminal end of alpha-tubulin in avian erythrocytes in a reaction that requires the de-tyrosination PTM and prevents the re-tyrosination PTM. Further, this is, to our knowledge, the first instance of taurine incorporation into a large protein.

Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Typings of Edible Oils through Spectral Networking of Triacylglycerol Fingerprints

Adulteration of edible oils by the manufacturers has been found frequently in modern societies. Due to the complexity of the chemical contents in edible oils, it is challenging to quantitatively determine the extent of adulteration and prove the authenticity of edible oils. In this study, a robust and simple MALDI-TOF-MS platform for rapid fingerprinting of triacylglycerols (TAGs) in edible oils was developed, where spectral similarity analysis was performed to quantitatively reveal correlations among edible oils in the chemical level. Specifically, we proposed oil networking, a spectral similarity-based illustration, which enabled reliable classifications of tens of commercial edible oils from vegetable and animal origins. The strategy was superior to traditional multivariate statistics due to its high sensitivity in probing subtle changes in TAG profiles, as further demonstrated by the success in determination of the adulterated lard in a food fraud in Taiwan. Finally, we showed that the platform allowed quantitative assessment of the binary mixture of olive oil and canola oil, which is a common type of olive oil adulteration in the market. Overall, these results suggested a novel strategy for chemical fingerprint-based quality control and authentication of oils in the food industry.

A microtubule crosslinking protocol for integrative structural modeling activities

Microtubules (MTs) are key components in the cytoskeleton of the eukaryotic cell, and play roles in processes such as intracellular transport and cell division. An improved understanding MT regulation requires structural analysis of the extensive interactions between the MT lattice and its regulatory proteins, but MT interactions are challenging for even the most advanced structural methods to characterize. Integrative methods involving crosslinking mass spectrometry (XL-MS) can extend structural analysis to many interaction classes, but the representation of MTs in crosslinking data-sets has been surprisingly low. Here, we explore the basis for the underrepresentation of the MT lattice and present an enhanced method for mapping MT structural features using an optimized set of reagents, together with fluorescence detection to ensure MT structural integrity. Through the application of stringent identification criteria, 91 unique crosslinks were identified, 78 of which were uniquely matched to 7 distinct structural features of the MT lattice. Of note, 4 crosslinks were detected for the lattice-A protofilament organization. The lattice-A structure defines a "seam" or discontinuity in MTs and is an emerging site of interest for MT regulation. Our methodology should be broadly applicable to integrative structural studies involving any MT-protein interaction.

The quest for improved reproducibility in MALDI mass spectrometry

Reproducibility has been one of the biggest hurdles faced when attempting to develop quantitative protocols for MALDI mass spectrometry. The heterogeneous nature of sample recrystallization has made automated sample acquisition somewhat "hit and miss" with manual intervention needed to ensure that all sample spots have been analyzed. In this review, we explore the last 30 years of literature and anecdotal evidence that has attempted to address and improve reproducibility in MALDI MS. Though many methods have been attempted, we have discovered a significant publication history surrounding the use of nitrocellulose as a substrate to improve homogeneity of crystal formation and therefore reproducibility. We therefore propose that this is the most promising avenue of research for developing a comprehensive and universal preparation protocol for quantitative MALDI MS analysis. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 37:217-228, 2018.

Statistical comparison of mass spectra for identification of amphetamine-type stimulants

A method for the statistical comparison of mass spectral data is demonstrated for applications in controlled substance analysis. The method uses an unequal variance t-test at each mass-to-charge ratio in the scan range to determine if two spectra are statistically associated or discriminated. If the two spectra are associated, a random-match probability is calculated to estimate the likelihood that the mass spectral fragmentation pattern in question occurs by random chance alone. If the two spectra are discriminated, the fragment ions responsible for the discrimination are determined. In this work, mass spectral data from case samples containing amphetamine, methamphetamine, 3,4-methylenedioxyamphetamine (MDA), 3,4-methylenedioxymethamphetamine (MDMA), phentermine, and psilocin were investigated. All spectra were collected in an accredited forensic laboratory using routine methods for controlled substance analysis. Using the statistical method, spectra of case samples were statistically associated to the corresponding reference standard at the 99.9% confidence level. In these instances, random-match probabilities ranged from 10^-39 to 10^-29, indicating the probability that the characteristic fragmentation pattern occurred by random chance is extremely small. Further, spectra of case samples were discriminated from other reference standards at the 99.9% or 99.0% confidence level, with 1-26 ions responsible for discrimination in each comparison.

BRAF pyrosequencing analysis aided by a lookup table

OBJECTIVES

BRAF mutations have substantial therapeutic, diagnostic, and prognostic significance, so detecting and specifying them is an important part of the workload of molecular pathology laboratories. Pyrosequencing assays are well suited for this analysis but can produce complex results. Therefore, we introduce a pyrosequencing lookup table based on Pyromaker that assists the user in generating hypotheses for solving complex pyrosequencing results.

METHODS

The lookup table contains all known mutations in the sequenced region and the positions in the dispensation sequence at which changes would occur with those mutations. We demonstrate the lookup table using a homebrew dispensation sequence for BRAF codons 596 to 605 as well as a commercially available kit-based dispensation sequence for codons 599 to 600.

RESULTS

These results demonstrate that the homebrew dispensation sequence unambiguously identifies all known BRAF mutations in this region, whereas the kit-based dispensation sequence has one unresolvable degeneracy that could be solved with the addition of two injections.

CONCLUSIONS

Using the lookup table and confirmatory virtual pyrogram, we unambiguously solved clinical pyrograms of the complex mutations V600K (c.1798_1799delGTinsAA), V600R (c.1798_1799delGTinsAG), V600D (c.1799_1800delTGinsAT), V600E (c.1799_1800delTGinsAA), and V600_K601delinsE (c.1799_1801delTGA). In addition, we used the approach to hypothesize and confirm a new mutation in human melanoma, V600_K601delinsEI (c.1799_1802delTGAAinsAAAT).

Quantitative proteomic analysis of ovarian cancer cells identified mitochondrial proteins associated with Paclitaxel resistance

Paclitaxel has been widely used as an anti-mitotic agent in chemotherapy for a variety of cancers and adds substantial efficacy as the first-line chemotherapeutic regimen for ovarian cancers. However, the frequent occurrence of paclitaxel resistance limits its function in long-term management. Despite abundant clinical and cellular demonstration of paclitaxel resistant tumors, the molecular mechanisms leading to paclitaxel resistance are poorly understood. Using genomic approaches, we have previously identified an association between a BTB/POZ gene, Nac1, and paclitaxel resistance in ovarian cancer. The experiments presented here have applied multiple quantitative proteomic methods to identify protein changes associated with paclitaxel resistance and Nac1 function. The SKOV-3 ovarian serous carcinoma cell line, which has inducible expression of dominant negative Nac1, was used to determine the paclitaxel treatment associated changes in the presence and absence of functional Nac1. Quantitative proteomic analyses were performed using iTRAQ labeling and mass spectrometry. Two label-free quantitative proteomic methods: LC-MS and spectral count were used to increase confidence of proteomic quantification. A total of 1371 proteins were quantified by at least one of the quantitative proteomic methods. Candidate proteins related to paclitaxel and NAC1 function were identified in this study. Go analysis of the protein changes identified upon paclitaxel resistance revealed that cell component enrichment related to mitochondria. Moreover, tubulin and mitochondrial proteins were the major cellular components with changes associated with paclitaxel treatment. This suggests that mitochondria may play a role in paclitaxel resistance.

Production of reliable MALDI spectra with quality threshold clustering of replicates

We present the first application of the quality threshold (QT) clustering algorithm to mass spectrometry (MS) data. The unique abilities of QT clustering to yield precision nodes that are commensurate with the mass measurement precision of the instrument are exploited to generate a consensus spectrum out of multiple replicate spectra. The spectral dot product and confidence intervals are used as a tool for evaluating the similarity and reproducibility between the consensus and replicates. The method is equally applicable to high and low resolution measurements. This paper demonstrates applications to linear spectra from a matrix assisted laser desorption ionization (MALDI) time of flight (TOF) instrument as well as peptide fragmentation data obtained from a TOF/TOF after unimolecular decomposition. The advantages of clustering to mitigate the inherent precision the shortcomings of MALDI data are discussed.

Quality control based on isotopic distributions for high-throughput MALDI-TOF and MALDI-FTICR serum peptide profiling

In this study, we have implemented a new quality control (QC) parameter for peptide profiling based on isotopic distributions. This QC parameter is an objective measure and facilitates automatic sorting of large numbers of peptide spectra. Peptides in human serum samples were enriched using reversed-phase C(18)-functionalized magnetic beads using a high-throughput robotic platform. High-resolution MALDI-TOF and ultrahigh resolution MALDI-FTICR mass spectra were obtained and a workflow was developed for automated analysis and evaluation of these profiles. To this end, the isotopic distributions of multiple peptides were quantified from both MALDI-TOF and MALDI-FTICR spectra. Odd peptide isotope distributions in TOF spectra could be rationalized from ultrahigh resolution FTICR spectra that showed overlap of different peptides. The comparison of isotope patterns with estimated polyaveragine distributions was used to calculate a QC value for each single mass spectrum. Sorting these QC values enabled the best MALDI spectrum to be selected from replicate spots. Moreover, using this approach spectra containing high intensities of polymers or other contaminants and lacking peptides of interest can be efficiently removed from a clinical dataset. In general, this method simplifies the exclusion of low quality spectra from further statistical analysis.

A method for monitoring and controlling reproducibility of intensity data in complex electrospray mass spectra: a thermometer ion-based strategy

Reproducibility in mass spectral data is important in both biomarker discovery and spectral database searching. We report a strategy, employing a series of substituted benzylpyridinium thermometer ions that can be used to monitor changes in performance of multiple aspects of an electrospray ionization source that impact the intensity axis of a spectrum. Performance attributes, which could confound even isotope-based quantification strategies, are readily assessed using a mixture of thermometer ions. Based on the observed behavior of the ions, a procedure is proposed for monitoring instrument performance and compensating for factors that affect reproducibility across both time and instruments.

A spectral clustering approach to MS/MS identification of post-translational modifications

Unidentified tandem mass spectra typically represent 50-90% of the spectra acquired in proteomics studies. This manuscript describes a novel algorithm, "Bonanza", for clustering spectra without knowledge of peptide or protein identifications. Further analysis leverages existing peptide identifications to infer related, likely valid identifications. Significantly more spectra can be identified with this approach, including spectra with unexpected potential modifications or amino-acid substitutions.