Efficient Interpretation of Tandem Mass Tags in Top-Down Proteomics

Mass spectrometry is the major analytical tool for the identification and quantification of proteins in biological samples. In so-called top-down proteomics, separation and mass spectrometric analysis is performed at the level of intact proteins, without preparatory digestion steps. It has been shown that the tandem mass tag (TMT) labeling technology, which is often used for quantification based on digested proteins (bottom-up studies), can be applied in top-down proteomics as well. This, however, leads to a complex interpretation problem, where we need to annotate measured peaks with their respective generating protein, the number of charges, and the a priori unknown number of TMT-groups attached to this protein. In this work, we give an algorithm for the efficient enumeration of all valid annotations that fulfill available experimental constraints. Applying the algorithm to real-world data, we show that the annotation problem can indeed be efficiently solved. However, our experiments also demonstrate that reliable annotation in complex mixtures requires at least partial sequence information and high mass accuracy and resolution to go beyond the proof-of-concept stage

Finding Disjoint Paths on Directed Acyclic Graphs

Given k+1 pairs of vertices (s_1,s_2),(u_1,v_1),...,(u_k,v_k) of a directed acyclic graph, we show that a modified version of a data structure of Suurballe and Tarjan can output, for each pair (u_l,v_l) with 1<=l<=k, a tuple (s_1,t_1,s_2,t_2) with {t_1,t_2}={u_l,v_l} in constant time such that there are two disjoint paths p_1, from s_1 to t_1, and p_2, from s_2 to t_2, if such a tuple exists. Disjoint can mean vertex- as well as edge-disjoint. As an application we show that the presented data structure can be used to improve the previous best known running time O(mn) for the so called 2-disjoint paths problem on directed acyclic graphs to O(m(log(n)/log(2+m/n))+n*log³(n)). In this problem, given four vertices s_1, s_2, t_1, and t_2, we want to construct two disjoint paths p_1, from s_1 to t_1, and p_2, from s_2 to t_2, if such paths exist

Sample preparation: a crucial factor for the analytical performance of rationally designed MALDI matrices

Evidence is presented that the performance of the rationally designed MALDI matrix 4-chloro-α-cyanocinnamic acid (ClCCA) in comparison to its well-established predecessor α-cyano-4-hydroxycinnamic acid (CHCA) is significantly dependent on the sample preparation, such as the choice of the target plate. In this context, it becomes clear that any rational designs of MALDI matrices and their successful employment have to consider a larger set of physicochemical parameters, including sample crystallization and morphology/topology, in addition to parameters of basic (solution and/or gas-phase) chemistry

Analysis of Cytotoxic Granules and Constitutively Produced Extracellular Vesicles from Large Granular Lymphocytic Leukemia Cell Lines

Background Large granular lymphocyte leukemias (LGLLs) are rare lymphoproliferative malignancies caused by clonal expansion of granular lymphocytes. T-cell LGLL and natural killer (NK) cell LGLL are defined based on their cellular origin. Their clinical manifestation and pathophysiology vary depending on the subtype and include, e.g., neutropenia, anemia, recurrent infections, and autoimmunity. A limited number of available patient-derived cell lines are considered valuable tools to study the biology of these malignancies. They differ in the expression of lineage-specific surface markers, but generally contain cytotoxic effector molecules in characteristic granules. Methods We investigated the presence and release of lysosome-associated effector proteins in patient-derived LGLL cell lines by flow and imaging cytometry, by Western blotting and by bottom-up proteomics profiling. Results The tested cell lines did not express FasL (CD178), but did express CD26/DPP4+. Intracellularly, we detected major differences in the abundance and subcellular distribution of granzymes, perforin, and granulysin. Similar differences were seen in enriched lysosome-related effector vesicles (LREVs). The proteomics profiling of enriched EVs from an NK-LGLL line (NKL) and a T-LGLL line (MOTN-1), confirmed individual profiles of effector molecules. Conclusion Our analyses underscore the individual distribution of effector proteins but also open new routes to define the role of intra- and extracellular granules in the disease manifestation or pathology of LGLLs

The intracellular proteome of the gut bacterium Bacteroides thetaiotaomicron is widely unaffected by a switch from glucose to sucrose as main carbohydrate source

Bacteroides thetaiotaomicron is a gram negative bacterium within the human gut microbiome that metabolizes a wide range of dietary and mucosal polysaccharides. Here, we analyze the proteome response of B. thetaiotaomicron cultivated on two different carbon sources, glucose and sucrose. Two quantitative LC-MS based proteomics approaches, encompassing label free quantification and isobaric labeling by tandem mass tags were applied. The results obtained by both workflows were compared with respect to the number of identified and quantified proteins, peptides supporting identification and quantification, sequence coverage, and reproducibility. A total of 1719 and 1696 proteins, respectively, were quantified, covering 35 % of the predicted B. thetaiotaomicron proteome. The data show that B. thetaiotaomicron widely maintains its intracellular proteome upon change of the carbohydrates and that major changes are observed solely in the machinery necessary to make use of the carbon sources provided. With respect to the central role of carbohydrates on gut health these data contribute to the understanding of how different carbohydrates contribute to shape bacterial community in the gut microbiome. All proteomics raw data have been uploaded to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD033704

Cysteine-Directed Isobaric Labeling Combined with GeLC-FAIMS-MS for Quantitative Top-Down Proteomics

The quantification of proteoforms, i.e., all molecular forms in which proteins can be present, by top-down proteomics provides essential insights into biological processes at the molecular level. Isobaric labeling-based quantification strategies are suitable for multidimensional separation strategies and allow for multiplexing of the samples. Here, we investigated cysteine-directed isobaric labeling by iodoTMT in combination with a gel- and gas-phase fractionation (GeLC-FAIMS-MS) for in-depth quantitative proteoform analysis. We optimized the acquisition workflow (i.e., the FAIMS compensation voltages, isolation windows, acquisition strategy, and fragmentation method) using a two-proteome mix to increase the number of quantified proteoforms and reduce ratio compression. Additionally, we implemented a mass feature-based quantification strategy in the widely used deconvolution algorithm FLASHDeconv, which improves and facilitates data analysis. The optimized iodoTMT GeLC-FAIMS-MS workflow was applied to quantitatively analyze the proteome of Escherichia coli grown under glucose or acetate as the sole carbon source, resulting in the identification of 726 differentially abundant proteoforms

Hepatitis C Virus Detection and Management After Implementation of Universal Screening in Pregnancy

BACKGROUND: Accurately identifying cases of hepatitis C virus has important medical and public health consequences. In the setting of rising hepatitis C virus prevalence and highly effective treatment with direct-acting antivirals, the Society for Maternal-Fetal Medicine guidelines recently changed to recommend universal screening for hepatitis C virus during pregnancy. However, there is little data on the influence of this policy change on case identification and management. OBJECTIVE: We aimed to examine the influence of universal hepatitis C virus screening on our patient population. Our primary objective was to determine if there was a difference in the detected hepatitis C virus prevalence after the policy change. Our secondary objectives were to determine which factors were associated with a positive test for hepatitis C virus and to examine postpartum management of pregnant patients living with hepatitis C virus, including the (1) gastroenterology referral rate, (2) treatment rate, (3) infantile hepatitis C virus screening rate, and (4) factors associated with being referred for treatment. STUDY DESIGN: We conducted a single-center, retrospective cohort study of deliveries that occurred before (July 2018–June 2020) and after (July 2020–December 2021) the implementation of universal hepatitis C virus screening. Information on hepatitis C virus and HIV status, if patients were screened for hepatitis C virus, history of intravenous drug use, and basic demographic information were abstracted from the electronic medical records. A subset of patients was administered a questionnaire regarding hepatitis C virus risk factors. For all patients who tested positive for hepatitis C virus, information on if they were referred for treatment in the postpartum period and if their infant was screened for hepatitis C virus were abstracted from the electronic medical records. RESULTS: A total of 8973 deliveries occurred during this study period. A total of 71 (0.79%) patients had a detectable viral load. With implementation of universal screening, hepatitis C virus screening rates increased from 5.78% to 77.25% of deliveries (P\u3c.01). The hepatitis C virus prevalence rates before and after universal screening was implemented were 0.78% and 0.81%, respectively (P=.88). There were significant demographic shifts in our pregnant population over this time period, including a reduction in intravenous drug use. A subset of 958 patients completed a hepatitis C virus risk factor questionnaire, in addition to undergoing universal hepatitis C virus screening. Ten patients screened positive with universal screening; only 8 of these individuals would have been identified with risk-based screening. Among the patients with a detectable viral load, 67.61% were referred for treatment and 18.75% were treated. A multivariate logistic regression model indicated that intravenous drug use was associated with significantly decreased odds of being referred for treatment (odds ratio, 0.14; 95% confidence interval, 0.04–0.59; P=.01). At the time of our evaluation, 52 infants were at least 18 months old and thus eligible for hepatitis C virus screening. Among these infants, 8 (15.38%) were screened for hepatitis C virus, and all were negative. CONCLUSION: Following the practice shift, we saw a significant increase in hepatitis C virus screening during pregnancy. However, postpartum treatment and infant screening remained low. Intravenous drug use was associated with a decreased likelihood of being referred for treatment. Pregnancy represents a unique time for hepatitis C virus case identification, although better linkage to care is needed to increase postpartum treatment