fragment ions
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Lewis blood group antigens are a prominent example of isomeric oligosaccharides with biological activity. Understanding the fragmentation mechanism in the gas phase is essential for their identification and assignment by mass spectrometric methods such as ESI-MS. In this work, the [M + H]+ species of Lewis A trisaccharide and Lewis A trisaccharide methyl glycoside were studied by ESI-MS with FT-ICR as mass analyzer with respect to their fragmentation mechanism. The comparison between the underivatized and the methylated species has shown that the reducing end plays a key role in this mechanism. The results of this study question the existence of Z-type fragment ions after activation of the protonated species. The main product of the fragmentation are Y-type fragment ions and a combination of Y-type fragmentation and the loss of water at the reducing end instead of Z-type fragmentation. C-type fragment ions could not be detected. MS3 measurements also reveal that each fragment ion only occurs with the participation of a mobile proton and the possibility of glycosidic bond cleavage after fragmentation has already occurred at the reducing end as B2 fragment ion.

Fourteen proteins produced by three pathogenic Escherichia coli strains were identified using antibiotic induction, MALDI-TOF-TOF tandem mass spectrometry (MS/MS) and top-down proteomic analysis using software developed in-house. Host proteins as well as plasmid proteins were identified. Mature, intact protein ions were fragmented by post-source decay (PSD), and prominent fragment ions resulted from the aspartic acid effect fragmentation mechanism wherein polypeptide backbone cleavage (PBC) occurs on the C-terminal side of aspartic acid (D), glutamic acid (E) and asparagine (N) residues. These highly specific MS/MS-PSD fragment ions were compared to b- and y-type fragment ions on the C-terminal side of D-, E- and N-residues of in silico protein sequences derived from whole genome sequencing. Nine proteins were found to be post-translationally modified with either removal of an N-terminal methionine or a signal peptide. The protein sequence truncation algorithm of our software correctly identified all full and truncated protein sequences. Truncated sequences were compared to those predicted by SignalP. Nearly complete concurrence was obtained except for one protein where SignalP mis-identified the cleavage site by one residue. Two proteins had intramolecular disulfide bonds that were inferred by the absence of PBC on the C-terminal side of a D-residue located within the disulfide loop. These results demonstrate the utility of MALDI-TOF-TOF for identification of full and truncated bacterial proteins.

Deciphering the glycosylation of the viral envelope (Env) glycoprotein is critical for evaluating viral escape from the host’s immune response and developing vaccines and antiviral drugs. However, it is still challenging to precisely decode the site-specific glycosylation characteristics of the highly glycosylated Env proteins, although glycoproteomics have made significant advances in mass spectrometry techniques and data analysis tools. Here, we present a hybrid dissociation technique, EThcD-sceHCD, by combining electron transfer/higher-energy collisional dissociation (EThcD) and stepped collision energy/higher-energy collisional dissociation (sceHCD) into a sequential glycoproteomic workflow. Following this scheme, we characterized site-specific N/O-glycosylation of the human immunodeficiency virus type 1 (HIV-1) Env protein gp120. The EThcD-sceHCD method increased the number of identified glycopeptides when compared with EThcD, while producing more comprehensive fragment ions than sceHCD for site-specific glycosylation analysis, especially for accurate O-glycosite assignment. Finally, eighteen N-glycosites and five O-glycosites with attached glycans were assigned unambiguously from heavily glycosylated gp120. These results indicate that our workflow can achieve improved performance for analysis of the N/O-glycosylation of a highly glycosylated protein containing numerous potential glycosites in one process. Knowledge of the glycosylation landscape of the Env glycoprotein will be useful for understanding of HIV-1 infection and development of vaccines and drugs.

AbstractWe developed DreamDIAXMBD (denoted as DreamDIA), a software suite based on a deep representation model for data-independent acquisition (DIA) data analysis. DreamDIA adopts a data-driven strategy to capture comprehensive information from elution patterns of peptides in DIA data and achieves considerable improvements on both identification and quantification performance compared with other state-of-the-art methods such as OpenSWATH, Skyline and DIA-NN. Specifically, in contrast to existing methods which use only 6 to 10 selected fragment ions from spectral libraries, DreamDIA extracts additional features from hundreds of theoretical elution profiles originated from different ions of each precursor using a deep representation network. To achieve higher coverage of target peptides without sacrificing specificity, the extracted features are further processed by nonlinear discriminative models under the framework of positive-unlabeled learning with decoy peptides as affirmative negative controls. DreamDIA is publicly available at https://github.com/xmuyulab/DreamDIA-XMBD for high coverage and accuracy DIA data analysis.

Abstract A validated UHPLC-PDA with an ESI-MS/MS method has been developed for simultaneous estimation of six bioactive alkaloids (magnoflorine, berbamine, columbamine, jatrorrhizine, palmatine and berberine) in the different extracts of the roots of Berberis aristata DC (Family:Berberdiaceae). It is an important medicinal herb native to Northern Himalaya and commonly known as ‘daruharidra’, ‘daruhaldi’, ‘Indian barberry’ or ‘tree turmeric’. An insight into the research literature uncovered reports on isoquinoline alkaloids like magnoflorine, berbamine, columbamine, jatrorrhizine, palmatine, and berberine as major bioactives in B. aristata roots, possessing different pharmacological and therapeutic effects. In the present study, these aforementioned alkaloids were separated on Phenomenex Luna®, 5 µm-C8 analytical column. The HPLC-MS analysis was performed at a flow rate of 0.90 mL min−1. Each alkaloid that is resolved was characterized by precursor ions and fragment ions with electrospray ionization (ESI) source in both positive and negative ionization using scan mode. The limit of detections (LODs) were 0.087, 0.727, 0.035, 0.124, 0.782 and 0.794 μg mL−1 for magnoflorine, berbamine, columbamine, jatrorrhizine, palmatine and berberine, respectively. The proposed UHPLC-PDA method was fully validated according to international (ICH) guidelines and was found to be selective, sensitive and highly accurate for the concomitant estimation of the aforementioned symbolic bio-markers of B. aristata roots.

Saikosaponins comprise a large group of chemical components present in the Bupleurum species that have attracted attention in the field of medicine because of their significant biological activities. Due to the high polarity, structural similarity, and the presence of several isomers of this class of components, their structural identification is extremely challenging. In this study, the mass spectrometric fragmentation pathways, UV spectral features, and chromatographic behavior of different types of saikosaponins were investigated using 24 standard substances. Saikosaponins containing carbonyl groups (C=O) in the aglycone produced fragment ions by loss of 30 Da, and in addition, type IV saikosaponins could produce [aglycone−CH2OH−OH−H]− and [aglycone−H2O−H]− fragment ions through neutral losses at positions C16 and C17. The above characteristic ions can be used to identify saikosaponins. More notably, the identification process of saikosaponins was systematically summarized, and using this method, 109 saikosaponins were identified or tentatively characterized from the saikosaponins extract of Bupleurum marginatum var. stenophyllum (BMS) using UPLC-PDA-Q/TOF-MS with both data-dependent acquisition (DDA) and data-independent acquisition (DIA) modes, of which 25 were new compounds and 60 were first discovered from BMS. Further studies revealed that the saikosaponins profiles of BMS, Bupleurum chinense DC (BC), and Bupleurum marginatum Wall. ex DC (BMW) were very similar. This work is of great significance for the basic research of the Bupleurum species and provides strong technical support to solve the resource problems associated with Radix Bupleuri.

Collision-induced dissociation (CID) is a common fragmentation strategy in mass spectrometry (MS) analysis. A conventional understanding is that fragment ions generated in low-energy CID should follow the even-electron rule. As such, (de)protonated precursor ions should predominately generate (de)protonated fragment ions with very few radical fragment ions (RFIs). However, the extent to which RFIs present in MS2 spectra has not been comprehensively investigated. This work uses the latest NIST 20 tandem mass spectral library to investigate of the occurrence of RFIs in CID MS2 experiments. In particular, RFIs were recognized using their integer double bond equivalent (DBE) values calculated from their annotated molecular formulas. Our study shows unexpected results as 65.4% and 68.8% of MS2 spectra contain at least 10% RFIs by ion-count (total number of ions) in positive and negative electrospray ionization (ESI) modes, respectively. Furthermore, we classified chemicals based on their compound classes and chemical substructures, and calculated the percentages of RFIs in each class. Results show that “Organic 1,3-dipolar compounds” and “Lignans, neolignans and related compounds” are the top 2 compound superclasses which tend to produce RFIs in their CID MS2 spectra. Moreover, aromatic, arylbromide, heteroaromatic, alkylarylether, phenol, and conjugated double bond-containing chemicals are more likely to produce RFIs. We also found four possible patterns of change in RFI percentages as a function of CID collision energy. Finally, we demonstrate that the inadequate consideration of RFIs in most conventional bioinformatic tools might cause problems during in silico fragmentation and de novo annotation of MS2 spectra. This work provides a further understanding of CID MS2 mechanism, and the unexpectedly large percentage of RFIs suggests a need for consideration in the development of bioinformatic software for MS2 interpretation.

Bent metallocene dichlorides (Cp2MCl2, M = Ti, Mo, Nb, …) have found interest as anti-cancer drugs in order to overcome the drawbacks associated with platinum-based therapeutics. However, they suffer from poor hydrolytic stability at physiological pH. A promising approach to improve their hydrolytic stability is the formation of host-guest complexes with macrocyclic structures, such as cyclodextrins. In this work, we utilized nanoelectrospray ionization tandem mass spectrometry to probe the interaction of titanocene dichloride with β-cyclodextrin. Unlike the non-covalent binding of phenylalanine and oxaliplatin to β-cyclodextrin, the mixture of titanocene and β-cyclodextrin led to signals assigned as [βCD + Cp2Ti–H]+, indicating a covalent character of the interaction. This finding is supported by titanated cyclodextrin fragment ions occurring from collisional activation. Employing di- and trimethylated β-cyclodextrins as hosts enabled the elucidation of the influence of the cyclodextrin hydroxy groups on the interaction with guest structures. Masking of the hydroxy groups was found to impair the covalent interaction and enabling the encapsulation of the guest structure within the hydrophobic cavity of the cyclodextrin. Findings are further supported by breakdown curves obtained by gas-phase dissociation of the various complexes.