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        <title>Frontiers in Analytical Science | Omics section | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/analytical-science/sections/omics</link>
        <description>RSS Feed for Omics section in the Frontiers in Analytical Science journal | New and Recent Articles</description>
        <language>en-us</language>
        <generator>Frontiers Feed Generator,version:1</generator>
        <pubDate>2026-05-10T13:34:15.03+00:00</pubDate>
        <ttl>60</ttl>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2025.1596778</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2025.1596778</link>
        <title><![CDATA[Editorial: Thought leaders in analytical science research]]></title>
        <pubdate>2025-04-04T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Binesh Unnikrishnan</author><author>Chih-Ching Huang</author><author>Huan-Tsung Chang</author><author>Elefteria Psillakis</author><author>Federico Marini</author><author>John T. Grant</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2024.1512573</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2024.1512573</link>
        <title><![CDATA[Protein carbamylation and proteomics: from artifacts to elucidation of biological functions]]></title>
        <pubdate>2025-01-03T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Youngki You</author><author>Gina Many</author><author>Ernesto S. Nakayasu</author>
        <description><![CDATA[Lysine carbamylation is a non-enzymatic protein post-translational modification (PTM) that plays important roles in regulating enzymatic activity and the pathogenesis of diseases such as atherosclerosis, rheumatoid arthritis, and uremia. The progress of understanding the roles of carbamylation in biological systems has been delayed due to lack of systematic assays to study its functions. To aggravate this scenario, carbamylation is a major artifact in proteomics analysis given that urea, which is used during sample preparation, induces carbamylation. In addition, anti-acetyllysine antibodies co-purify carbamylated and acetylated peptides. In a recent paper, we leveraged co-purification with anti-acetyllysine antibodies to develop a method for analyzing carbamylated proteomes. In this perspective article, we discuss how this method may be applied to characterize the physiological functions of carbamylation in humans and other biological models, as well as the utility of establishing novel disease biomarkers.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2024.1397810</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2024.1397810</link>
        <title><![CDATA[Parallel reaction monitoring targeted mass spectrometry as a fast and sensitive alternative to antibody-based protein detection]]></title>
        <pubdate>2024-09-10T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Karel Bezstarosti</author><author>Lennart Van der Wal</author><author>Wouter A. S. Doff</author><author>Jeroen A. A. Demmers</author>
        <description><![CDATA[The reliable, accurate and quantitative targeted detection of proteins is a key technology in molecular and cell biology and molecular diagnostics. The current golden standard for targeted protein detection in complex mixtures such as complete cell lysates or body fluids is immunoblotting, a technology that was developed in the late 1970s and has not undergone major changes since. Although widespread, this methodology suffers from several disadvantages, such as the inability to detect low-abundant proteins or specific posttranslational modifications, the requirement for highly specific antibodies, the lack of quantitative power and the often-tedious practical procedures. Mass spectrometry (MS) based targeted protein detection is an alternative technology that could circumvent these caveats. Here, we compare immunoblotting with targeted protein mass spectrometry using a parallel reaction monitoring (PRM) regime on the Orbitrap mass spectrometer. We show that PRM based MS has superior sensitivity and quantitative accuracy over immunoblotting. The limit of detection for proteolytic peptides of a purified target protein was found to be in the mid- to low-attomole range and approximately one order of magnitude higher when embedded in a complex biological matrix. The incorporation of synthetic heavy isotope labeled (AQUA) peptides as internal calibrants into the PRM workflow allows for even higher accuracy for both the relative and absolute quantitation of tryptic target peptides. In conclusion, PRM is a versatile and sensitive technology, which can overcome the shortcomings of immunoblotting. We argue that PRM based MS could become the method of choice for the targeted detection of proteins in complex cellular matrices or body fluids and may eventually replace standard methods such as Western blotting and ELISA in biomedical research and in the clinic.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2024.1425190</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2024.1425190</link>
        <title><![CDATA[mini-Complexome Profiling (mCP), an FDR-controlled workflow for global targeted detection of protein complexes]]></title>
        <pubdate>2024-08-01T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Hugo Amedei</author><author>Niels Benjamin Paul</author><author>Brian Foo</author><author>Lisa Neuenroth</author><author>Stephan E. Lehnart</author><author>Henning Urlaub</author><author>Christof Lenz</author>
        <description><![CDATA[IntroductionCo-fractionation mass spectrometry couples native-like separations of protein-protein complexes with mass spectrometric proteome analysis for global characterization of protein networks. The technique allows for both de novo detection of complexes and for the detection of subtle changes in their protein composition. The typical requirement for fine-grained fractionation of >80 fractions, however, translates into significant demands on sample quantity and mass spectrometric instrument time, and represents a significant barrier to experimental replication and the use of scarce sample material (ex. patient biopsies).MethodsWe developed mini-Complexome Profiling (mCP), a streamlined workflow with reduced requirements for fractionation and, thus, biological material and laboratory and instrument time. Soluble and membrane-associated protein complexes are extracted from biological material under mild conditions, and fractionated by Blue Native electrophoresis using commercial equipment. Each fraction is analysed by data-independent acquisition mass spectrometry, and known protein complexes are detected based on the coelution of known components using a novel R package with a controlled false discovery rate approach. The tool is available to the community on a GitHub repository.ResultsmCP was benchmarked using HEK293 cell lysate and exhibited performance similar to established workflows, but from a significantly reduced number of fractions. We then challenged mCP by performing comparative complexome analysis of cardiomyocytes isolated from different chambers from a single mouse heart, where we identified subtle chamber-specific changes in mitochondrial OxPhos complexes.DiscussionThe reduced sample and instrument time requirements open up new applications of co-fractionation mass spectrometry, specifically for the analysis of sparse samples such as human patient biopsies. The ability to identify subtle changes between similar tissue types (left/right ventricular and atrial cardiomyocytes) serves as a proof of principle for comparative analysis of mild/asymptomatic disease states.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2023.1278170</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2023.1278170</link>
        <title><![CDATA[Editorial: Plant-microbe omics]]></title>
        <pubdate>2023-11-07T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Kim K. Hixson</author><author>Amit Dhingra</author><author>Francisco Dini-Andreote</author><author>Mitchel J. Doktycz</author><author>Timothy J. Tschaplinski</author><author>Ljiljana Paša-Tolić</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2023.1306435</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2023.1306435</link>
        <title><![CDATA[Editorial: Perspectives in omics 2022]]></title>
        <pubdate>2023-10-13T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Sophie Ayciriex</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2023.1258558</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2023.1258558</link>
        <title><![CDATA[Maximizing analytical precision: exploring the advantages of ratiometric strategy in fluorescence, Raman, electrochemical, and mass spectrometry detection]]></title>
        <pubdate>2023-09-25T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Manivannan Madhu</author><author>S. Santhoshkumar</author><author>Wei-Bin Tseng</author><author>Wei-Lung Tseng</author>
        <description><![CDATA[Ratiometric strategy are an invaluable method that helps to detect and quantify analytes. This approach relies on measuring changes in the ratio of two or more signals to improve the accuracy and sensitivity of the results. Ratiometric strategies are widely used in a variety of fields including biomedical, environmental monitoring and food safety. It is particularly popular when traditional single-signal based detection methods are not feasible, especially when interfering substances severely affect the detection. In addition, ratiometric methods have the potential to improve the accuracy and reliability of analyte detection, leading to better results in a variety of complex environments. The article provides a comprehensive review of ratiometric strategy, focusing on ratiometric fluorescent nanoprobes for the visual detection of analytes. This paper also discusses the design of ratiometric two-photon fluorescent probes for biomedical imaging, the synthesis of ratiometric surface-enhanced Raman scattering nanoprobes for the imaging of intracellular analytes, the development of ratiometric molecularly imprinted electrochemical sensors for detection of electroactive species, and the use of isotopically-labeled internal standards in matrix-assisted laser desorption/ionization for ratiometric analysis. The article not only discusses each technique in detail, including its principles, advantages, potential applications, and limitations, but also highlights recent advances in each method and possible future directions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2023.1205583</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2023.1205583</link>
        <title><![CDATA[Metatranscriptomic analysis of tomato rhizospheres reveals insight into plant-microbiome molecular response to biochar-amended organic soil]]></title>
        <pubdate>2023-08-29T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Seanna Hewitt</author><author>Rishikesh Ghogare</author><author>William Troxel</author><author>Elvir Tenic</author><author>Daylen Isaac</author><author>Amit Dhingra</author>
        <description><![CDATA[We characterized the effects of crop residue derived biochar on tomato growth, soil microbial diversity, and rhizosphere-level gene expression responses in an organic production system. Shoot fresh biomass and fruit yield were assessed at the end of the growing cycle. The corresponding transcriptomic response of the roots, the soil microbial community profiles, and the active transcripts within the communities were quantified using a metatranscriptomic approach at four different developmental stages of the plant. Biochar treatment did not impact shoot biomass or fruit production; however, metatranscriptome analysis revealed that the gene expression activity of the tomato rhizosphere changes over time in response to the biochar treatment, with a number of bacteria with known benefits to soil health and plant growth displaying increased gene expression (e.g., Rhizobiaceae, Pseudomonadaceae, Micromonosporaceae, Sphingomonadaceae). Streptomycetaceae were expressed at the highest levels in the rhizosphere. Biochar seemed to attenuate the expression of this bacteria by the end of the time course, possibly due to the rise in competition for resources driven by the increased activity of other beneficial microbes. Notably, pathogenic fungi in the soil displayed generally reduced expression in the biochar-amended rhizosphere in comparison with the control. In addition to the assessment of the rhizosphere microbiome, transcriptome analysis and gene ontology analysis of tomato roots revealed functional enrichment of genes associated with nitrogen metabolic processes, regulation of metabolic processes, and production of organic compounds in the biochar treated rhizosphere. Together, these results suggest that biochar amendment enhances gene expression of beneficial soil microbes, and also impacts gene expression in the plant roots, which may in turn lead to improvements in soil and plant health. The results of this study provide foundations and a methodology for using metatranscriptomic approaches to investigate the impacts of biochar or other soil amendments in different crops, varying soil types, and with greater experimental complexity. The findings of such investigations will inform the development of biochar-based soil amendment strategies to enhance soil fertility and crop health in a wide range of production systems.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2023.1259466</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2023.1259466</link>
        <title><![CDATA[Editorial: Emerging structural proteomics methodologies]]></title>
        <pubdate>2023-08-17T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Mowei Zhou</author><author>Nicholas B. Borotto</author><author>Huilin Li</author><author>Tara L. Pukala</author><author>Ian K. Webb</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2023.1124741</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2023.1124741</link>
        <title><![CDATA[Sequencing intact membrane proteins using MALDI mass spectrometry]]></title>
        <pubdate>2023-07-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Edison Zhamungui Sánchez</author><author>Hassan Hijazi</author><author>Jana Haidar</author><author>Enrica Mecarelli</author><author>Elda Bauda</author><author>Isabelle Petit-Härtlein</author><author>Jean-Marie Teulon</author><author>Jean-Luc Pellequer</author><author>Elisabetta Boeri Erba</author>
        <description><![CDATA[Membrane proteins are key players in many cellular events and represent crucial drug targets. Matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) is a valuable approach to investigate them. To our knowledge, there are only a few reports of sequencing small membrane proteins using MALDI in-source decay (ISD). We report the successful fragmentation and sequencing of membrane proteins up to 46 kDa by MALDI-ISD. We have 1) investigated key MALDI parameters that influence the sequencing of a soluble protein; 2) used atomic force microscopy to observe our samples and correlate their topological features with MALDI data, which allowed us to optimize fragmentation conditions; 3) sequenced N- and C-termini of three membrane proteins (SpoIIIAF, TIM23, and NOX), solubilized in three different ways. Our results indicate that detergent and buffer type are of key importance for successful MALDI-ISD sequencing. Our findings are significant because sequencing membrane proteins enables the unique characterization of challenging biomolecules. The resulting fragmentation patterns provide key insights into the identity of proteins, their sequences, modifications, and other crucial information, such as the position of unexpected truncation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2023.1186623</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2023.1186623</link>
        <title><![CDATA[Toward the analysis of functional proteoforms using mass spectrometry-based stability proteomics]]></title>
        <pubdate>2023-06-22T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Ji Kang</author><author>Meena Seshadri</author><author>Kellye A. Cupp-Sutton</author><author>Si Wu</author>
        <description><![CDATA[Functional proteomics aims to elucidate biological functions, mechanisms, and pathways of proteins and proteoforms at the molecular level to examine complex cellular systems and disease states. A series of stability proteomics methods have been developed to examine protein functionality by measuring the resistance of a protein to chemical or thermal denaturation or proteolysis. These methods can be applied to measure the thermal stability of thousands of proteins in complex biological samples such as cell lysate, intact cells, tissues, and other biological fluids to measure proteome stability. Stability proteomics methods have been popularly applied to observe stability shifts upon ligand binding for drug target identification. More recently, these methods have been applied to characterize the effect of structural changes in proteins such as those caused by post-translational modifications (PTMs) and mutations, which can affect protein structures or interactions and diversify protein functions. Here, we discussed the current application of a suite of stability proteomics methods, including thermal proteome profiling (TPP), stability of proteomics from rates of oxidation (SPROX), and limited proteolysis (LiP) methods, to observe PTM-induced structural changes on protein stability. We also discuss future perspectives highlighting the integration of top-down mass spectrometry and stability proteomics methods to characterize intact proteoform stability and understand the function of variable protein modifications.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2023.1073540</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2023.1073540</link>
        <title><![CDATA[What is a consistent glycan composition dataset?]]></title>
        <pubdate>2023-06-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Federico Saba</author><author>Julien Mariethoz</author><author>Frederique Lisacek</author>
        <description><![CDATA[Introduction: One of the main challenges in bioinformatics has been and still is, the comparison of entities through the development of algorithms for similarity scoring and data clustering according to biologically relevant aspects. Glycoinformatics also faces this challenge, in particular regarding the automated comparison of protein and/or tissue glycomes, that remains a relatively uncharted territory.Methods: Low and high throughput experimental glycomic and glycoproteomic results were collected, revealing a bias toward N-linked glycomes. Then, N-glycomes were considered and represented as networks of related glycan compositions as opposed to lists of glycans. They were processed and compared through a java application generating graphs and another producing a similarity matrix based on graph content. Several scoring schemes (e.g., Jaccard index or cosine) were tested and evaluated using the Matthews Correlation Coefficient, in order to capture a meaningful protein and tissue N-glycome similarity.Results: Assuming that a glycome corresponds to a well-connected graph of glycan compositions, graph comparison has revealed gaps that can be interpreted as inconsistencies. The outcome of systematic graph comparison is both formal and practical. In principle, it is shown that the idiosyncrasy of current glycome data limits the definition of appropriate estimates for systematically comparing N-glycomes. Yet, several potentially interesting criteria could be identified in a series of use cases detailed in the study.Discussion: Differentially expressed glycomes are usually compared manually, but the resulting work tends to remain in publications due to the lack of dedicated tools. Even manually, cross-comparison is challenging mostly because different sets of features are used from one study to the other. The work presented here enables laying down guidelines for developing a software tool comparing glycomes based on appropriate definitions of similarity and suitable methods for its evaluation and implementation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2023.1118749</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2023.1118749</link>
        <title><![CDATA[Hydrogen deuterium exchange and other mass spectrometry- based approaches for epitope mapping]]></title>
        <pubdate>2023-05-18T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Prashant N. Jethva</author><author>Michael L. Gross</author>
        <description><![CDATA[Antigen-antibody interactions are a fundamental subset of protein-protein interactions responsible for the “survival of the fittest.” Determining the interacting interface of the antigen, called an epitope, and that on the antibody, called a paratope, is crucial to antibody development. Because each antigen presents multiple epitopes (unique footprints), sophisticated approaches are required to determine the target region for a given antibody. Although X-ray crystallography, Cryo-EM, and nuclear magnetic resonance can provide atomic details of an epitope, they are often laborious, poor in throughput, and insensitive. Mass spectrometry-based approaches offer rapid turnaround, intermediate structural resolution, and virtually no size limit for the antigen, making them a vital approach for epitope mapping. In this review, we describe in detail the principles of hydrogen deuterium exchange mass spectrometry in application to epitope mapping. We also show that a combination of MS-based approaches can assist or complement epitope mapping and push the limit of structural resolution to the residue level. We describe in detail the MS methods used in epitope mapping, provide our perspective about the approaches, and focus on elucidating the role that HDX-MS is playing now and in the future by organizing a discussion centered around several improvements in prototype instrument/applications used for epitope mapping. At the end, we provide a tabular summary of the current literature on HDX-MS-based epitope mapping.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2023.1119438</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2023.1119438</link>
        <title><![CDATA[Mass spectrometry and machine learning in the identification of COVID-19 biomarkers]]></title>
        <pubdate>2023-03-31T00:00:00Z</pubdate>
        <category>Mini Review</category>
        <author>Lucas C. Lazari</author><author>Gilberto Santos de Oliveira</author><author>Janaina Macedo-Da-Silva</author><author>Livia Rosa-Fernandes</author><author>Giuseppe Palmisano</author>
        <description><![CDATA[Identifying specific diagnostic and prognostic biological markers of COVID-19 can improve disease surveillance and therapeutic opportunities. Mass spectrometry combined with machine and deep learning techniques has been used to identify pathways that could be targeted therapeutically. Moreover, circulating biomarkers have been identified to detect individuals infected with SARS-CoV-2 and at high risk of hospitalization. In this review, we have surveyed studies that have combined mass spectrometry-based omics techniques (proteomics, lipdomics, and metabolomics) and machine learning/deep learning to understand COVID-19 pathogenesis. After a literature search, we show 42 studies that applied reproducible, accurate, and sensitive mass spectrometry-based analytical techniques and machine/deep learning methods for COVID-19 biomarker discovery and validation. We also demonstrate that multiomics data results in classification models with higher performance. Furthermore, we focus on the combination of MALDI-TOF Mass Spectrometry and machine learning as a diagnostic and prognostic tool already present in the clinics. Finally, we reiterate that despite advances in this field, more optimization in the analytical and computational parts, such as sample preparation, data acquisition, and data analysis, will improve biomarkers that can be used to obtain more accurate diagnostic and prognostic tools.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2023.1157582</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2023.1157582</link>
        <title><![CDATA[What information is contained in experimentally determined lipid profiles?]]></title>
        <pubdate>2023-03-23T00:00:00Z</pubdate>
        <category>Mini Review</category>
        <author>Dominik Schwudke</author>
        <description><![CDATA[Hundreds of molecular species make up the cellular lipidome. In this minireview, considerations for interpreting membrane and storage lipid profile changes that are often the focal point of lipidomic studies are discussed. In addition, insights how the most conserved molecular patterns are formed in eukaryotic systems and the consequences for the perturbation of lipid homeostasis are addressed. The implications of lipid identification specificity and experimental variability on modeling membrane structure and systemic responses are also discussed. The profile changes of membrane and storage lipids are bound to the kinetics of the metabolic system, and experimental design and functional interpretation in lipidomic research should be adapted accordingly.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2023.1142606</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2023.1142606</link>
        <title><![CDATA[What clinical metabolomics will bring to the medicine of tomorrow]]></title>
        <pubdate>2023-02-24T00:00:00Z</pubdate>
        <category>Mini Review</category>
        <author>Audrey Le Gouellec</author><author>Caroline Plazy</author><author>Bertrand Toussaint</author>
        <description><![CDATA[The purpose of this review is to explore how clinical metabolomics could help physicians in the future. The recent advent of medical genomics brings new and interesting technological tools to measure genetic predispositions to a disease. But metabolomics will allow us to go even further by linking the patient’s pathological phenotype with gene expression defects and metabolic disorders. It is in this context that the clinical chemist must adapt and be a force of proposal to meet these health challenges. He must help the clinician by mastering these new innovative tools, in order to participate in the implementation of clinical studies for the discovery of biomarkers, but also to propose the assays of biomarkers called “signatures,” which can be composite biomarkers or fingerprints, which will ultimately guide the clinician. He will have to propose them as clinical chemistry tests. In the first part, we will look at some concrete examples of the use of clinical metabolomics in clinical research projects that have led to the identification of a new biomarker. We will use the example of trimethylamine N-oxide (or TMAO) and review the clinical studies that have proposed TMAO as a biomarker for cardiovascular diseases. In a second part, we will see through bibliographic studies, how the metabolomic fingerprint can be useful to build a supervised model for patient stratification. In conclusion, we will discuss the limitations currently under debate.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2023.1119489</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2023.1119489</link>
        <title><![CDATA[Determination of dissociation constants via quantitative mass spectrometry]]></title>
        <pubdate>2023-02-24T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Jonathan Schulte</author><author>Jan-Niklas Tants</author><author>Julian von Ehr</author><author>Andreas Schlundt</author><author>Nina Morgner</author>
        <description><![CDATA[The interplay of biomolecules governs all cellular processes. Qualitative analysis of such interactions between biomolecules as well as the quantitative assessment of their binding affinities are essential for the understanding of biochemical mechanisms. As scientific interest therefore moves beyond pure structural investigation, methods that allow for the investigation of such interactions become increasingly relevant. In this perspective we outline classical methods that are applicable for the determination of binding constants and highlight specifically mass spectrometry based methods. The use of mass spectrometry to gain quantitative information about binding affinities however is a still developing field. Here, we discuss different approaches, which emerged over the last years to determine dissociation constants (KD) with mass spectrometry based methods. Specifically, we highlight the recent development of quantitative Laser Induced Liquid Bead Ion Desorption (qLILBID) mass spectrometry for the example of double stranded deoxyribonucleic acids as well as for different RNA—RNA binding protein systems. We show that quantitative laser induced liquid bead ion desorption can successfully be used for the top down investigation of complexes and their dissociation constants values ranging from low nM to low µM affinities.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2023.1112390</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2023.1112390</link>
        <title><![CDATA[Why do we need to go beyond overall biological variability assessment in metabolomics?]]></title>
        <pubdate>2023-02-13T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Julien Boccard</author><author>Serge Rudaz</author>
        <description><![CDATA[Unlike other systems such as plants, microorganisms or fungi, human cells are not proficient in eliciting the production of defense compounds in response to external stresses and threats. Human metabolism is essentially based on a set of primary metabolites that participate in the various regulatory events of cells and tissues. The challenge is therefore to maintain homeostasis and allow the survival of the individual through the modulation of existing endogenous metabolic pathways with a relatively stable set of ubiquitous compounds. Since these complex regulatory phenomena are potentially subject to multiple influences, assessing their overall variability, as achieved by most conventional approaches, is not sufficiently informative. The experimental evaluation of several factors acting simultaneously on the metabolome is paramount. Because metabolomics involves the characterization of multivariate metabolic phenotypes, such a methodology requires specific data analysis tools to fully exploit the relevant information considering the different factors, as well as their respective impact on metabolite levels. The investigation of high-dimensional multifactorial data in metabolomics opens new challenges and requires the development of innovative experimental strategies involving structured designs of experiments to assess cause-effect associations and offer deeper insight into relevant biological information. In the future, key outputs should not only consider lists of metabolites, but also include their specific variation related to each effect that can be identified and/or quantified, thus allowing accurate biochemical and functional relationships to be highlighted.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2023.1118494</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2023.1118494</link>
        <title><![CDATA[Challenges and perspectives in MS-based omics approaches for ecotoxicology studies: An insight on Gammarids sentinel amphipods]]></title>
        <pubdate>2023-02-13T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Valentina Calabrese</author><author>Arnaud Salvador</author><author>Yohann Clément</author><author>Thomas Alexandre Brunet</author><author>Anabelle Espeyte</author><author>Arnaud Chaumot</author><author>Olivier Geffard</author><author>Davide Degli-Esposti</author><author>Sophie Ayciriex</author>
        <description><![CDATA[The aquatic environment is one of the most complex biosystems, as organism at all trophic levels may be exposed to a multitude of pollutants. As major goals, ecotoxicology typically investigates the impact of toxic pollutants on the ecosystems through the study of sentinel organisms. Over the past decades, Mass Spectrometry (MS)-based omics approaches have been extended to sentinel species both in laboratory and field exposure conditions. Single-omics approaches enable the discovery of biomarkers mirroring the health status of an organism. By covering a restricted set of the molecular cascade, they turn out to only partially satisfy the understanding of complex ecotoxicological effects. In contrast, a more complete understanding of the ecotoxicity pathways can be accessed through multi-omics approaches. In this perspective, we provide a state-of-the-art and a critical evaluation on further developments in MS-based single and multi-omics studies in aquatic ecotoxicology. As case example, literature regarding Gammarids freshwater amphipods, non-model sentinel organisms sensitive to pollutants and environmental changes and crucial species for downstream ecosystems, will be reviewed.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frans.2023.1118742</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frans.2023.1118742</link>
        <title><![CDATA[Recent methodological developments in data-dependent analysis and data-independent analysis workflows for exhaustive lipidome coverage]]></title>
        <pubdate>2023-02-10T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Marie Valmori</author><author>Vincent Marie</author><author>François Fenaille</author><author>Benoit Colsch</author><author>David Touboul</author>
        <description><![CDATA[Untargeted lipidomics applied to biological samples typically involves the coupling of separation methods to high-resolution mass spectrometry (HRMS). Getting an exhaustive coverage of the lipidome with a high confidence in structure identification is still highly challenging due to the wide concentration range of lipids in complex matrices and the presence of numerous isobaric and isomeric species. The development of innovative separation methods and HRMS(/MS) acquisition workflows helped improving the situation but issues still remain regarding confident structure characterization. To overcome these issues, thoroughly optimized MS/MS acquisition methods are needed. For this purpose, different methodologies have been developed to enable MS and MS/MS acquisition in parallel. Those methodologies, derived from the proteomics, are referred to Data Dependent Acquisition (DDA) and Data Independent Acquisition (DIA). In this context, this perspective paper presents the latest developments of DDA- and DIA-based lipidomic workflows and lists available bioinformatic tools for the analysis of resulting spectral data.]]></description>
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