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A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Biology".

Deadline for manuscript submissions: 31 August 2024 | Viewed by 12799

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Special Issue Editors

Dr. Christof Lenz

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Guest Editor

Department of Clinical Chemistry, University Medical Center Göttingen, Göttingen, Germany
Interests: proteomics; mass spectrometry; cardiovascular research

Dr. Christine Carapito

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Guest Editor

Laboratoire de Spectrométrie de Masse BioOrganique (LSMBO), Université de Strasbourg, CNRS, IPHC UMR 7178, 67000 Strasbourg, France
Interests: mass spectrometry; proteomics; bioinformatics and computational biology

Special Issue Information

Dear Colleagues,

Mass spectrometry is the core technology at the heart of proteome research. While it is now widely employed by researchers in (among others) biological and biomedical research, significant advances in sample preparation, in mass spectrometric instrumentation, and in bioinformatics are still opening up completely new lines of research ranging from the classification of archaeological artifacts to single-cell analysis of engineered tissues. We cordially invite researchers from the fields of analytical chemistry, instrument development, biological and biomedical sciences, as well as bioinformatics to highlight this progress by contributing to this Special Issue, specifically with contributions in the following areas and technologies:

Low-input proteomics;
Ion-mobility-enhanced mass spectrometry techniques;
Data-independent acquisition mass spectrometry;
Next-generation data processing and statistical approaches.

In addition to conventional research articles and reviews, we also welcome commentaries, opinions, and perspectives on the progress and applications of mass spectrometric proteome analysis.

Dr. Christof Lenz
Dr. Christine Carapito
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

proteomics
mass spectrometry
clinical research
bioinformatics
structural biology
biomarkers
orbitrap
time-of-flight
ion mobility
chromatography
peptides
proteins

Published Papers (6 papers)

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Research

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19 pages, 808 KiB

Open AccessArticle

A Mass Spectrometry-Based Proteome Study of Twin Pairs Discordant for Incident Acute Myocardial Infarction within Three Years after Blood Sampling Suggests Novel Biomarkers

by Hans Christian Beck, Asmus Cosmos Skovgaard, Afsaneh Mohammadnejad, Nicolai Bjødstrup Palstrøm, Palle Fruekilde Nielsen, Jonas Mengel-From, Jacob Hjelmborg, Lars Melholt Rasmussen and Mette Soerensen

Int. J. Mol. Sci. 2024, 25(5), 2638; https://doi.org/10.3390/ijms25052638 - 24 Feb 2024

Viewed by 608

Abstract

Acute myocardial infarction (AMI) is a major cause of mortality and morbidity worldwide, yet biomarkers for AMI in the short- or medium-term are lacking. We apply the discordant twin pair design, reducing genetic and environmental confounding, by linking nationwide registry data on AMI diagnoses to a survey of 12,349 twins, thereby identifying 39 twin pairs (48–79 years) discordant for their first-ever AMI within three years after blood sampling. Mass spectrometry of blood plasma identified 715 proteins. Among 363 proteins with a call rate > 50%, imputation and stratified Cox regression analysis revealed seven significant proteins (FDR < 0.05): FGD6, MCAM, and PIK3CB reflected an increased level in AMI twins relative to their non-AMI co-twins (HR > 1), while LBP, IGHV3-15, C1RL, and APOC4 reflected a decreased level in AMI twins relative to their non-AMI co-twins (HR < 1). Additional 50 proteins were nominally significant (p < 0.05), and bioinformatics analyses of all 57 proteins revealed biology within hemostasis, coagulation cascades, the immune system, and the extracellular matrix. A protein–protein-interaction network revealed Fibronectin 1 as a central hub. Finally, technical validation confirmed MCAM, LBP, C1RL, and APOC3. We put forward novel biomarkers for incident AMI, a part of the proteome field where markers are surprisingly rare and where additional studies are highly needed. Full article

(This article belongs to the Special Issue Advances in Mass Spectrometry-Based Proteomics)

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18 pages, 3359 KiB

Open AccessArticle

MS Identification of Blood Plasma Proteins Concentrated on a Photocrosslinker-Modified Surface

by Arina I. Gordeeva, Anastasia A. Valueva, Elizaveta E. Rybakova, Maria O. Ershova, Ivan D. Shumov, Andrey F. Kozlov, Vadim S. Ziborov, Anna S. Kozlova, Victor G. Zgoda, Yuri D. Ivanov, Ekaterina V. Ilgisonis, Olga I. Kiseleva, Elena A. Ponomarenko, Andrey V. Lisitsa, Alexander I. Archakov and Tatyana O. Pleshakova

Int. J. Mol. Sci. 2024, 25(1), 409; https://doi.org/10.3390/ijms25010409 - 28 Dec 2023

Viewed by 657

Abstract

This work demonstrates the use of a modified mica to concentrate proteins, which is required for proteomic profiling of blood plasma by mass spectrometry (MS). The surface of mica substrates, which are routinely used in atomic force microscopy (AFM), was modified with a photocrosslinker to allow “irreversible” binding of proteins via covalent bond formation. This modified substrate was called the AFM chip. This study aimed to determine the role of the surface and crosslinker in the efficient concentration of various types of proteins in plasma over a wide concentration range. The substrate surface was modified with a 4-benzoylbenzoic acid N-succinimidyl ester (SuccBB) photocrosslinker, activated by UV irradiation. AFM chips were incubated with plasma samples from a healthy volunteer at various dilution ratios (10²X, 10⁴X, and 10⁶X). Control experiments were performed without UV irradiation to evaluate the contribution of physical protein adsorption to the concentration efficiency. AFM imaging confirmed the presence of protein layers on the chip surface after incubation with the samples. MS analysis of different samples indicated that the proteomic profile of the AFM-visualized layers contained common and unique proteins. In the working series of experiments, 228 proteins were identified on the chip surface for all samples, and 21 proteins were not identified in the control series. In the control series, a total of 220 proteins were identified on the chip surface, seven of which were not found in the working series. In plasma samples at various dilution ratios, a total of 146 proteins were identified without the concentration step, while 17 proteins were not detected in the series using AFM chips. The introduction of a concentration step using AFM chips allowed us to identify more proteins than in plasma samples without this step. We found that AFM chips with a modified surface facilitate the efficient concentration of proteins owing to the adsorption factor and the formation of covalent bonds between the proteins and the chip surface. The results of our study can be applied in the development of highly sensitive analytical systems for determining the complete composition of the plasma proteome. Full article

(This article belongs to the Special Issue Advances in Mass Spectrometry-Based Proteomics)

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17 pages, 4253 KiB

Open AccessArticle

GroEL-Proteotyping of Bacterial Communities Using Tandem Mass Spectrometry

by Simon Klaes, Shobhit Madan, Darja Deobald, Myriel Cooper and Lorenz Adrian

Int. J. Mol. Sci. 2023, 24(21), 15692; https://doi.org/10.3390/ijms242115692 - 28 Oct 2023

Cited by 1 | Viewed by 1148

Abstract

Profiling bacterial populations in mixed communities is a common task in microbiology. Sequencing of 16S small subunit ribosomal-RNA (16S rRNA) gene amplicons is a widely accepted and functional approach but relies on amplification primers and cannot quantify isotope incorporation. Tandem mass spectrometry proteotyping is an effective alternative for taxonomically profiling microorganisms. We suggest that targeted proteotyping approaches can complement traditional population analyses. Therefore, we describe an approach to assess bacterial community compositions at the family level using the taxonomic marker protein GroEL, which is ubiquitously found in bacteria, except a few obligate intracellular species. We refer to our method as GroEL-proteotyping. GroEL-proteotyping is based on high-resolution tandem mass spectrometry of GroEL peptides and identification of GroEL-derived taxa via a Galaxy workflow and a subsequent Python-based analysis script. Its advantage is that it can be performed with a curated and extendable sample-independent database and that GroEL can be pre-separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) to reduce sample complexity, improving GroEL identification while simultaneously decreasing the instrument time. GroEL-proteotyping was validated by employing it on a comprehensive raw dataset obtained through a metaproteome approach from synthetic microbial communities as well as real human gut samples. Our data show that GroEL-proteotyping enables fast and straightforward profiling of highly abundant taxa in bacterial communities at reasonable taxonomic resolution. Full article

(This article belongs to the Special Issue Advances in Mass Spectrometry-Based Proteomics)

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14 pages, 3327 KiB

Open AccessArticle

Differentiation between Weissella cibaria and Weissella confusa Using Machine-Learning-Combined MALDI-TOF MS

by Eiseul Kim, Seung-Min Yang, Dae-Hyun Jung and Hae-Yeong Kim

Int. J. Mol. Sci. 2023, 24(13), 11009; https://doi.org/10.3390/ijms241311009 - 02 Jul 2023

Cited by 2 | Viewed by 1273

Abstract

Although Weissella cibaria and W. confusa are essential food-fermenting bacteria, they are also opportunistic pathogens. Despite these species being commercially crucial, their taxonomy is still based on inaccurate identification methods. In this study, we present a novel approach for identifying two important Weissella species, W. cibaria and W. confusa, by combining matrix-assisted laser desorption/ionization and time-of-flight mass spectrometer (MALDI-TOF MS) data using machine-learning techniques. After on- and off-plate protein extraction, we observed that the BioTyper database misidentified or could not differentiate Weissella species. Although Weissella species exhibited very similar protein profiles, these species can be differentiated on the basis of the results of a statistical analysis. To classify W. cibaria, W. confusa, and non-target Weissella species, machine learning was used for 167 spectra, which led to the listing of potential species-specific mass-to-charge (m/z) loci. Machine-learning techniques including artificial neural networks, principal component analysis combined with the K-nearest neighbor, support vector machine (SVM), and random forest were used. The model that applied the Radial Basis Function kernel algorithm in SVM achieved classification accuracy of 1.0 for training and test sets. The combination of MALDI-TOF MS and machine learning can efficiently classify closely-related species, enabling accurate microbial identification. Full article

(This article belongs to the Special Issue Advances in Mass Spectrometry-Based Proteomics)

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19 pages, 8027 KiB

Open AccessArticle

A Comparative Proteomic Analysis to Explore the Influencing Factors on Endometritis Using LC-MS/MS

by Xingcan Jiang, Ziyuan Li, Xiyv Chang, Zhengjie Lian, Aihua Wang, Pengfei Lin, Huatao Chen, Dong Zhou, Keqiong Tang and Yaping Jin

Int. J. Mol. Sci. 2023, 24(12), 10018; https://doi.org/10.3390/ijms241210018 - 12 Jun 2023

Viewed by 1214

Abstract

The inflammatory system activated by uterine infection is associated with decreased fertility. Diseases can be detected in advance by identifying biomarkers of several uterine diseases. Escherichia coli is one of the most frequent bacteria that is involved in pathogenic processes in dairy goats. The purpose of this study was to investigate the effect of endotoxin on protein expression in goat endometrial epithelial cells. In this study, the LC–MS/MS approach was employed to investigate the proteome profile of goat endometrial epithelial cells. A total of 1180 proteins were identified in the goat Endometrial Epithelial Cells and LPS-treated goat Endometrial Epithelial Cell groups, of which, 313 differentially expressed proteins were accurately screened. The proteomic results were independently verified by WB, TEM and IF techniques, and the same conclusion was obtained. To conclude, this model is suitable for the further study of infertility caused by endometrial damage caused by endotoxin. These findings may provide useful information for the prevention and treatment of endometritis. Full article

(This article belongs to the Special Issue Advances in Mass Spectrometry-Based Proteomics)

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Review

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23 pages, 1206 KiB

Open AccessReview

Bottom-Up Proteomics: Advancements in Sample Preparation

by Van-An Duong and Hookeun Lee

Int. J. Mol. Sci. 2023, 24(6), 5350; https://doi.org/10.3390/ijms24065350 - 10 Mar 2023

Cited by 15 | Viewed by 7102

Abstract

Liquid chromatography–tandem mass spectrometry (LC–MS/MS)-based proteomics is a powerful technique for profiling proteomes of cells, tissues, and body fluids. Typical bottom-up proteomic workflows consist of the following three major steps: sample preparation, LC–MS/MS analysis, and data analysis. LC–MS/MS and data analysis techniques have been intensively developed, whereas sample preparation, a laborious process, remains a difficult task and the main challenge in different applications. Sample preparation is a crucial stage that affects the overall efficiency of a proteomic study; however, it is prone to errors and has low reproducibility and throughput. In-solution digestion and filter-aided sample preparation are the typical and widely used methods. In the past decade, novel methods to improve and facilitate the entire sample preparation process or integrate sample preparation and fractionation have been reported to reduce time, increase throughput, and improve reproducibility. In this review, we have outlined the current methods used for sample preparation in proteomics, including on-membrane digestion, bead-based digestion, immobilized enzymatic digestion, and suspension trapping. Additionally, we have summarized and discussed current devices and methods for integrating different steps of sample preparation and peptide fractionation. Full article

(This article belongs to the Special Issue Advances in Mass Spectrometry-Based Proteomics)

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