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PubMed2026

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry↗
PubMed1979

Protein amino acid analysis by an isotope ratio gas chromatography mass spectrometry computer technique.

A method for quantitative analysis of protein amino acids by a gas chromatography mass spectrometry computer system is described. Amino acids were analysed as their N-trifluoroacetyl n-butyl ester derivatives. Isotope ratio determination was used as the quantitating technique via multiple internal standards. The exact composition of a deuterated amino acid mixture was determined against a standard amino acid calibration mixture and in turn the protein amino acid composition was determined against the deuterated amino acid mixture. The amount of protein taken for analysis was 100 micrograms and the procedure, excluding hydrolysis, could be performed with 2 1/2 hours. The introduction of the internal standards prior to protein hydrolysis provides a method with good precision (mean coefficient of variation less than 5%). The method, tested on insulin, gave results which agreed well with the known composition of the protein and with simultaneous analysis on ion exchangers.

Amino Acids↗
PubMed1978

Analysis of fatty acid methyl esters by a gas--liquid chromatography--chemical ionization mass spectrometry computer system.

The technique of gas-liquid chromatography-chemical ionization mass spectrometry can easily identify trace peaks and unresolved peaks on gas-liquid chromatography, utilizing MH(+) ions of chemical ionization mass spectra. In polyunsaturated fatty acid methyl esters such as C22:5 and C22:6, the determination of molecular weights that are difficult to determine by electron impact mass spectrometry could be easily identified by chemical ionization mass spectrometry. The identification could be performed even more easily from a mass chromatogram obtained by means of a gas-liquid chromatography-chemical ionization mass spectrometry-computer system. This technique was applied to analysis of fatty acid methyl esters of triglycerides, cholesteryl esters, nonesterified fatty acids, and phospholipids obtained from normal human serum. It was observed that odd-carbon-number fatty acids contained more isomers of different types than even-carbon-number fatty acids, whether the fatty acids were saturated or unsaturated. As for the types of isomers, we presume the existence of iso, anteiso, branched, cyclic fatty acids, and, in the case of unsaturated fatty acids, positional isomers. The qualitative determination of the group of fatty acid isomers containing 20 carbon atoms was also investigated as well as the application of procedures for quantitative determination. Sensitivities for saturated fatty acids differ from those for unsaturated fatty acids of the same carbon number, and sensitivities for unsaturated fatty acids of the same carbon number differ with the number of double bonds because the amounts of MH(+) - 32 and MH(+) - 32 - 18 fragment ions formed are different.

Chromatography, Gas↗
PubMed1978

Determination of double bond positions of unsaturated fatty acids by a chemical ionization mass spectrometry computer system.

After stereospecific oxidation, trimethylsilylated methyl esters of mono- and diunsaturated fatty acids were analyzed by combined gas-liquid chromatography-chemical ionization mass spectrometry. The positions of original double bonds were deduced from the fragment ions produced by the cleavage of the carbon-carbon bond between two trimethylsilyl ethers. These fragment ions were recorded at m/e 187 and 259 in the case of 16:1(n-7), at m/e 187 and 287 in the case of 18:1(n-7), at m/e 215 and 259 in the case of 18:1(n-9), and at m/e 172 and 259 in the case of 18:2(n-6), respectively. The diastereoisomers of monounsaturated fatty acids can be discriminated by comparing the intensities of the fragment ions at m/e 253 and 285 in the case of 16:1 and at m/e 281 and 313 in the case of 18:1. The diastereosiomers of diunsaturated fatty acids may also be distinguished from each other by comparing the intensities of the fragment ions formed by the loss of trimethylsilyl function from the characteristic ions. Mono- and diunsaturated fatty acids in liver may be dominantly in cis- 18:1(n-1) and cis-cis-18:2(n-6) as determined by a mass chromatographic technique.

Computers↗
PubMed2025

Seq2Saccharide: Discovering Oligosaccharides and Aminoglycosides Natural Products by Integrating Computational Mass Spectrometry and Genome Mining.

Natural oligosaccharides and aminoglycosides are important sources of new drug candidates, especially in the development of antibiotics. In the past, discovering novel saccharides has been time-consuming and costly. However, the rapid expansion of high-throughput data, including genomic and mass spectrometry data sets, has greatly increased opportunities for natural saccharide discovery. Yet, due to the complex biosynthesis pathways of saccharides, no existing method can predict their structures with high precision. To address this, we introduce Seq2Saccharide, a tool designed to automate saccharide natural product discovery by integrating both genomic and mass spectrometry data. To enhance accuracy, Seq2Saccharide predicts hundreds or thousands of putative structures for each gene cluster. The correct structure is then identified from these predictions using a mass spectral search. Benchmarks against saccharides in the MiBIG database show that Seq2Saccharide outperforms existing methods in predicting the structure of saccharides. Furthermore, mass spectrometry analysis indicates that the variable search module can correct mispredictions from genome mining. By searching genomic and mass spectrometry data of microbial strains, Seq2Saccharide correctly identified the biosynthetic gene cluster for the polysaccharide oligosaccharide trestatin B.

Aminoglycosides↗
PubMed2026

Computational mass spectrometry and genome mining guided discovery of metallophores produced by Microbulbifer.

Iron is an essential component of cellular biology. Thus, iron's low bioavailability is a key evolutionary pressure guiding microbial dynamics in the marine environment. Among marine bacteria, Microbulbifer is a chemically underexplored and functionally versatile bacterial genus, which is commonly associated with sponges, algae, corals, and sediments. Previously, genome analyses have revealed that Microbulbifer spp. can degrade polymers and synthesize natural products. Despite their recognized potential to produce secondary metabolites, siderophores are yet to be identified in Microbulbifer, and their iron acquisition strategies remain largely unknown. Here, we developed a comprehensive mass spectrometry-based query language code to determine siderophore production by Microbulbifer spp. in mono- and mixed cultures. Using this workflow, we discovered a new metallophore, which we named bulbichelin, as well as a suite of previously unreported petrobactins containing an unprecedented longer chain length acylation on the central spermidine moiety. We applied genome mining methods to describe the biosynthesis of these compounds. Using metal infusion mass spectrometry, we show that bulbichelins bind a variety of metals. Notably, neither of these compounds were produced in a co-culture of Microbulbifer with coral-derived pathogen Vibrio coralliilyticus Cn52-H1. Understanding how siderophores shape interspecies interactions between Microbulbifer spp. and other marine organisms will aid in unraveling the chemical and catalytic versatility of this genus and adaptation in nutrient deplete marine environment.

MassQL↗
PubMed1979

Gas chromatography-mass spectrometry in analysis of protein amino acid composition.

A method for quantitative analysis of protein amino acids using isotope ratio gas chromatography-mass spectrometry computer techniques is described. The amino acids are analysed as their N-trifluoroacetyl-n-butyl esters and the quantitation is accomplished by the inclusion of deuterated amino acid mixtures of known composition. The inclusion of internal standards prior to protein hydrolysis provides a method with high precision (coefficient of variation less than 5%). The method, which requires 100 microgram and can be performed in just over 2 h, when tested on insulin gave results which agreed well with the known composition of the protein and with simultaneous analysis on ion exchangers. Thus, the technique offers an alternative to automatic amino acid analysers (utilizing ion exchangers) for quantitative amino acid analysis.

Amino Acids↗
PubMed1979

Identification of urinary and biliary metabolites of alprenolol in the rat.

1. After oral administration of alprenolol to rat, 12 metabolites were isolated and characterized as trifluoroacetyl, trimethylsilyl and n-butylboronate derivatives, using a g.l.c.-mass spectrometry-computer system. Fragmentation pathways of derivatives in the mass-spectrometric analysis are discussed. 2. Metabolic reactions involved are oxidative degradation of the propanolisopropylamine side-chain, aromatic hydroxylation, oxidation of the allyl group, and conjugation. A method for direct analysis of epoxide functions in the allyl group is described. 3. In comparison with metabolism of alprenolol in vitro, more polar metabolites are formed in vivo but the same principal metabolic pathways are valid. Structural features for biliary excretion are discussed.

Alprenolol↗
PubMed1978

Polypeptide sequencing by liquid chromatography mass spectrometry.

Key steps in a proposed automated system for polypeptide sequencing utilizing a liquid chromatograph mass spectrometer computer system have been tested with mixtures containing up to six model oligopeptides. At the low nanomole level it was possible to obtain complete sequence information for all components in many, but not all, of the mixtures tried. Interpretation of the results is complicated by the presence of numerous side-products formed in the derivatization process. Minimization of such impurities will be necessary to reduce the ambiguity of the sequence information resulting from more complex mixtures, such as those expected from the degradation of larger polypeptides, and to reduce sample requirements to the subnanomole level. However, the present system appears to have unique advantages over other proposed automated methods.

Amino Acid Sequence↗
PubMed2025

Emerging protein sequencing technologies: proteomics without mass spectrometry?

INTRODUCTION: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has been a leading method for proteomics for 30 years. Advantages provided by LC-MS/MS are offset by significant disadvantages, including cost. Recently, several non-mass spectrometric methods have emerged, but little information is available about their capacity to analyze the complex mixtures routine for mass spectrometry. AREAS COVERED: We review recent non-mass-spectrometric methods for sequencing proteins and peptides, including those using nanopores, sequencing by degradation, reverse translation, and short-epitope mapping, with comments on bioinformatics challenges, fundamental limitations, and areas where new technologies will be more or less competitive with LC-MS/MS. In addition to conventional literature searches, instrument vendor websites, patents, webinars, and preprints were also consulted to give a more up-to-date picture. EXPERT OPINION: Many new technologies are promising. However, demonstrations that they outperform mass spectrometry in terms of peptides and proteins identified have not yet been published, and astute observers note important disadvantages, especially relating to the dynamic range of single-molecule measurements of complex mixtures. Still, even if the performance of emerging methods proves inferior to LC-MS/MS, their low cost could create a different kind of revolution: a dramatic increase in the number of biology laboratories engaging in new forms of proteomics research.

Proteomics↗
PubMed1978

Studies on drug metabolism by use of isotopes XX: Ion cluster technique for detection of urinary metabolites of 1-butyryl-4-cinnamylpiperazine by mass chromatography.

An ion cluster technique and mass chromatography were used for the structural elucidation of several unidentified urinary metabolites of 1-butyryl-4-cinnamylpiperazine (I) in mice and guinea pigs. The urinary metabolites in guinea pigs and mice receiving a single 100 mg/kg dose of an equimolar mixture of 1-butyryl-4-[aromatic-d(5)]-cinnamylpiperazine (I-d(5)) hydrochloride and I hydrochloride (I:I-d(5)) were purified and subjected to trimethylsilyl derivatization with bis(trimethylsilyl)acetamide, followed by GLC-mass spectrometry-computer analysis. Appropriate fragment and molecular ions of unidentified metabolites were selected based on the major mass fragment ions appearing in the mass spectra of the previously identified metabolites of I to provide the mass chromatograms. The presence of ion clusters as doublet peaks in the mass chromatograms indicated that the corresponding total ion peaks originated from the administered I:I-d(5). The mass spectra of selected scans from the total ion chromatogram were plotted, and the structures of unidentified metabolites were readily determined by the presence of ion clusters separated by 3-5 mass units and by the shift of the fragment ions. By using this technique, six previously unidentified metabolites were identified in the urine of guinea pigs and two were identified in the urine of mice.

Analgesics↗
PubMed2026

Clinical proteomics in inborn errors of metabolism: from biomarker discovery to implementation.

INTRODUCTION: Inborn errors of metabolism (IEMs) are rare, heterogeneous disorders traditionally diagnosed through genetic testing, enzyme assays, and metabolite measurements. However, these tools often do not fully explain phenotypic variability, organ involvement, disease progression, or treatment response. Clinical proteomics provides a complementary functional layer by capturing changes in protein abundance, proteoforms, post-translational modifications (PTM), and biological pathways, offering insights beyond genotype- and metabolite-based approaches. AREAS COVERED: This review examines the role of high-resolution mass spectrometry and computational proteomics in biomarker discovery and clinical decision-making for IEMs. It focuses on their contribution to diagnosis, variant interpretation, patient stratification, and treatment monitoring. Disease-specific applications are discussed, with the strongest evidence in lysosomal storage disorders, mitochondrial diseases, congenital disorders of glycosylation, and selected neurodegenerative or renal metabolic conditions. The literature search was performed in PubMed, Scopus, Web of Science, and Google Scholar, covering peer-reviewed articles available up to 2026, with emphasis on methodological advances and translational applications in clinical proteomics for IEMs. EXPERT OPINION: Proteomics will not replace established diagnostic tools, but it can help address clinically actionable questions in selected contexts. Translation into clinical practice will require standardized workflows, multicenter validation, clinically anchored endpoints, and integration with other omics approaches.

Humans↗