mass spectrometry data
Recently Published Documents


TOTAL DOCUMENTS

1299
(FIVE YEARS 427)

H-INDEX

66
(FIVE YEARS 11)

2022 ◽  
Vol 116 (1) ◽  
pp. 11-19
Author(s):  
Jiří Novák ◽  
Vladimír Havlíček

We describe the molecular dereplication principles and de novo characterization of small molecules obtained from liquid-chromatography mass spectrometry and imaging mass spectrometry data sets. Our methodology aims at supporting chemists and computer programmers to understand the hidden computing algorithms used for metabolomics mass spectrometry data processing. The approaches have been made available in the open-source tool CycloBranch. The presented tutorial extends the interpretation of mass spectra portfolia described in a series of papers published in Chemicke Listy, issues 2/2020 and 3/2020.


2022 ◽  
Author(s):  
Andy Lin ◽  
Brooke L. Deatherage Kaiser ◽  
Janine R. Hutchison ◽  
Jeffrey A. Bilmes ◽  
William Stafford Noble

Interpretation of newly acquired mass spectrometry data can be improved by identifying, from an online repos- itory, previous mass spectrometry runs that resemble the new data. However, this retrieval task requires comput- ing the similarity between an arbitrary pair of mass spectrometry runs. This is particularly challenging for runs acquired using different experimental protocols. We propose a method, MS1Connect, that calculates the simi- larity between a pair of runs by examining only the intact peptide (MS1) scans, and we show evidence that the MS1Connect score is accurate. Specifically, we show that MS1Connect outperforms several baseline methods on the task of predicting the species from which a given proteomics sample originated. In addition, we show that MS1Connect scores are highly correlated with similarities computed from fragment (MS2) scans, even though this data is not used by MS1Connect.


2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Miaoshan Lu ◽  
Shaowei An ◽  
Ruimin Wang ◽  
Jinyin Wang ◽  
Changbin Yu

Abstract Background With the precision of the mass spectrometry (MS) going higher, the MS file size increases rapidly. Beyond the widely-used open format mzML, near-lossless or lossless compression algorithms and formats emerged in scenarios with different precision requirements. The data precision is often related to the instrument and subsequent processing algorithms. Unlike storage-oriented formats, which focus more on lossless compression rate, computation-oriented formats concentrate as much on decoding speed as the compression rate. Results Here we introduce “Aird”, an opensource and computation-oriented format with controllable precision, flexible indexing strategies, and high compression rate. Aird provides a novel compressor called Zlib-Diff-PforDelta (ZDPD) for m/z data. Compared with Zlib only, m/z data size is about 55% lower in Aird average. With the high-speed decoding and encoding performance of the single instruction multiple data technology used in the ZDPD, Aird merely takes 33% decoding time compared with Zlib. We have downloaded seven datasets from ProteomeXchange and Metabolights. They are from different SCIEX, Thermo, and Agilent instruments. Then we convert the raw data into mzML, mgf, and mz5 file formats by MSConvert and compare them with Aird format. Aird uses JavaScript Object Notation for metadata storage. Aird-SDK is written in Java, and AirdPro is a GUI client for vendor file converting written in C#. They are freely available at https://github.com/CSi-Studio/Aird-SDK and https://github.com/CSi-Studio/AirdPro. Conclusions With the innovation of MS acquisition mode, MS data characteristics are also constantly changing. New data features can bring more effective compression methods and new index modes to achieve high search performance. The MS data storage mode will also become professional and customized. ZDPD uses multiple MS digital features, and researchers also can use it in other formats like mzML. Aird is designed to become a computing-oriented data format with high scalability, compression rate, and fast decoding speed.


2022 ◽  
Vol 12 ◽  
Author(s):  
Simona Reina ◽  
Vanessa Checchetto

Voltage-dependent anion-selective channels (VDAC) are pore-forming proteins located in the outer mitochondrial membrane. Three isoforms are encoded by separate genes in mammals (VDAC1-3). These proteins play a crucial role in the cell, forming the primary interface between mitochondrial and cellular metabolisms. Research on the role of VDACs in the cell is a rapidly growing field, but the function of VDAC3 remains elusive. The high-sequence similarity between isoforms suggests a similar pore-forming structure. Electrophysiological analyzes revealed that VDAC3 works as a channel; however, its gating and regulation remain debated. A comparison between VDAC3 and VDAC1-2 underlines the presence of a higher number of cysteines in both isoforms 2 and 3. Recent mass spectrometry data demonstrated that the redox state of VDAC3 cysteines is evolutionarily conserved. Accordingly, these residues were always detected as totally reduced or partially oxidized, thus susceptible to disulfide exchange. The deletion of selected cysteines significantly influences the function of the channel. Some cysteine mutants of VDAC3 exhibited distinct kinetic behavior, conductance values and voltage dependence, suggesting that channel activity can be modulated by cysteine reduction/oxidation. These properties point to VDAC3 as a possible marker of redox signaling in the mitochondrial intermembrane space. Here, we summarize our current knowledge about VDAC3 predicted structure, physiological role and regulation, and possible future directions in this research field.


Author(s):  
Hirotaka Iijima ◽  
Gabrielle Gilmer ◽  
Kai Wang ◽  
Sruthi Sivakumar ◽  
Christopher Evans ◽  
...  

Abstract Increased mechanistic insight into the pathogenesis of knee osteoarthritis (KOA) is needed to develop efficacious disease-modifying treatments. Though age-related pathogenic mechanisms are most relevant to the majority of clinically-presenting KOA, the bulk of our mechanistic understanding of KOA has been derived using surgically induced post-traumatic OA (PTOA) models. Here, we took an integrated approach of meta-analysis and multi-omics data analysis to elucidate pathogenic mechanisms of age-related KOA in mice. Protein-level data were integrated with transcriptomic profiling to reveal inflammation, autophagy, and cellular senescence as primary hallmarks of age-related KOA. Importantly, the molecular profiles of cartilage aging were unique from those observed following PTOA, with less than 3% overlap between the two models. At the nexus of the three aging hallmarks, Advanced Glycation End-Product (AGE)/Receptor for AGE emerged as the most statistically robust pathway associated with age-related KOA. This pathway was further supported by analysis of mass spectrometry data. Notably, the change in AGE-RAGE signaling over time was exclusively observed in male mice, suggesting sexual dimorphism in the pathogenesis of age-induced KOA in murine models. Collectively, these findings implicate dysregulation of AGE-RAGE signaling as a sex-dependent driver of age-related KOA.


2021 ◽  
Vol 23 (1) ◽  
pp. 319
Author(s):  
Nicolai Bjødstrup Palstrøm ◽  
Aleksandra M. Rojek ◽  
Hanne E. H. Møller ◽  
Charlotte Toftmann Hansen ◽  
Rune Matthiesen ◽  
...  

Amyloidosis is a rare disease caused by the misfolding and extracellular aggregation of proteins as insoluble fibrillary deposits localized either in specific organs or systemically throughout the body. The organ targeted and the disease progression and outcome is highly dependent on the specific fibril-forming protein, and its accurate identification is essential to the choice of treatment. Mass spectrometry-based proteomics has become the method of choice for the identification of the amyloidogenic protein. Regrettably, this identification relies on manual and subjective interpretation of mass spectrometry data by an expert, which is undesirable and may bias diagnosis. To circumvent this, we developed a statistical model-assisted method for the unbiased identification of amyloid-containing biopsies and amyloidosis subtyping. Based on data from mass spectrometric analysis of amyloid-containing biopsies and corresponding controls. A Boruta method applied on a random forest classifier was applied to proteomics data obtained from the mass spectrometric analysis of 75 laser dissected Congo Red positive amyloid-containing biopsies and 78 Congo Red negative biopsies to identify novel “amyloid signature” proteins that included clusterin, fibulin-1, vitronectin complement component C9 and also three collagen proteins, as well as the well-known amyloid signature proteins apolipoprotein E, apolipoprotein A4, and serum amyloid P. A SVM learning algorithm were trained on the mass spectrometry data from the analysis of the 75 amyloid-containing biopsies and 78 amyloid-negative control biopsies. The trained algorithm performed superior in the discrimination of amyloid-containing biopsies from controls, with an accuracy of 1.0 when applied to a blinded mass spectrometry validation data set of 103 prospectively collected amyloid-containing biopsies. Moreover, our method successfully classified amyloidosis patients according to the subtype in 102 out of 103 blinded cases. Collectively, our model-assisted approach identified novel amyloid-associated proteins and demonstrated the use of mass spectrometry-based data in clinical diagnostics of disease by the unbiased and reliable model-assisted classification of amyloid deposits and of the specific amyloid subtype.


Author(s):  
Rigaud Sébastien ◽  
Ana Cristina Martinez Maciel ◽  
Tristan Lombard ◽  
Sylvie Grugeon ◽  
Pierre Tran-Van ◽  
...  

Abstract With the aim of establishing a data simultaneous comparison, the Principal Component Analysis (PCA) statistical tool was applied to LiNi0.6Mn0.2Co0.2O2/graphite Li-ion cells electrolyte’s decomposition products detected by UHPLC-ESI-HRMS. Herein, we illustrate how the chemometric tool associated with mass spectrometry data can be relevant to provide information about the presence of unusual molecules. Indeed, pristine Triton X-100 surfactant molecules used in electrode elaboration process were detected after impregnation stage. However, as they chemically react and oxidize at a potential lower than 4.5V vs. Li/Li+, only surfactant derivatives and classical ageing molecules were observed, respectively, after storage and cycling stages at 55°C, leading to a triangle-type correlation circle. On the other hand, global schemes of LiPF6-based electrolyte degradation pathways were elaborated from a comparative study with literature to help interpret results in future electrolyte ageing studies.


Sign in / Sign up

Export Citation Format

Share Document