Biomedical subjects

Magnus Palmblad

Publications and source records attributed to Magnus Palmblad.

At least 19 recordsLinked to original sources

PubMed2026

Integrating multi-omics technologies to decipher microbiome functions.

Multi-omics approaches have revolutionized our understanding of microbial communities by enabling simultaneous interrogation of genomic, transcriptomic, proteomic, and metabolomic data. The systematic integration and analysis of these deep datasets help decipher the functional roles of microbiomes, providing critical insights into microbial activities, interactions, and dynamics across diverse environments. Biological complexity makes multi-omics analysis of a single, isolated organism demanding but highly informative, yet this complexity increases further when samples comprise hundreds to thousands of individual species. As microbiome research continues to expand into clinical, environmental, and engineered systems, standardized workflows, benchmarked datasets, and community-driven initiatives are essential to ensure reproducibility, standardization and interpretability. Establishing and disseminating best practices for experimental design, data processing, and integrative analyses will be critical for maximizing comparability and scientific rigor across studies. This perspective highlights recent advances in multi-omics microbiome research, outlines key obstacles in data integration and metadata harmonization, and proposes a collaborative roadmap for scalable, FAIR-compliant multi-omics investigations and potentially disruptive Artificial Intelligence (AI) advances comparable to those of AlphaFold in the field of microbiome science.

Multiomics↗

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↗

PubMed2026

Open and sustainable AI: challenges, opportunities and the road ahead in the life sciences.

Artificial intelligence (AI) has seen transformative breakthroughs in the life sciences, expanding possibilities to interpret biological information at an unprecedented capacity. To maximize return on growing investments and accelerate progress, it is urgent to address long-standing research challenges arising from the rapid adoption of AI methods. We review the erosion of trust in AI outputs driven by poor reusability and reproducibility, and highlight their impact on environmental sustainability. Furthermore, we discuss the fragmented components of the AI ecosystem and lack of guiding pathways to support open and sustainable AI model development. In response, this Perspective introduces practical open and sustainable AI recommendations mapped to over 300 ecosystem components and provides guiding implementation pathways. Our work connects researchers with relevant AI resources, facilitating the implementation of sustainable, reusable and reproducible AI. Built upon community consensus and aligned to existing efforts, these outputs will aid future policy development and structured pathways for guiding AI implementation.

Artificial Intelligence↗

PubMed2007

Liquid matrix deposition on conductive hydrophobic surfaces for tuning and quantitation in UV-MALDI mass spectrometry.

With its highly fluctuating ion production matrix-assisted laser desorption/ionization (MALDI) poses many practical challenges for its application in mass spectrometry. Instrument tuning and quantitative ion abundance measurements using ion signal alone depend on a stable ion beam. Liquid MALDI matrices have been shown to be a promising alternative to the commonly used solid matrices. Their application in areas where a stable ion current is essential has been discussed but only limited data have been provided to demonstrate their practical use and advantages in the formation of stable MALDI ion beams. In this article we present experimental data showing high MALDI ion beam stability over more than two orders of magnitude at high analytical sensitivity (low femtomole amount prepared) for quantitative peptide abundance measurements and instrument tuning in a MALDI Q-TOF mass spectrometer. Samples were deposited on an inexpensive conductive hydrophobic surface and shrunk to droplets <10 nL in size. By using a sample droplet <10 nL it was possible to acquire data from a single irradiated spot for roughly 10,000 shots with little variation in ion signal intensity at a laser repetition rate of 5-20 Hz.

Hydrophobic and Hydrophilic Interactions↗

PubMed2007

Retention time prediction and protein identification.

Proteins are commonly identified through enzymatic digestion and generation of short sequence tags or fingerprints of peptide masses by mass spectrometry. Separation methods, such as liquid chromatography and electrophoresis, are often used to fractionate complex protein or peptide mixtures and these separations also provide information on the different species, such as molecular weight and isoelectric point from electrophoresis and hydrophobicity in reversed-phase chromatography. These are also properties that can be predicted from amino acid sequences derived from genomic sequences and used in protein identification. This chapter reviews recently introduced methods based on retention time prediction to extract information from chromatographic separations and the applications to protein identification in organisms with small and large genomes. Novel data on retention time prediction of posttranslationally modified peptides is also presented.

Amino Acid Sequence↗

PubMed2006

Automatic internal calibration in liquid chromatography/Fourier transform ion cyclotron resonance mass spectrometry of protein digests.

Accurately measured peptide masses can be used for large-scale protein identification from bacterial whole-cell digests as an alternative to tandem mass spectrometry (MS/MS) provided mass measurement errors of a few parts-per-million (ppm) are obtained. Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) routinely achieves such mass accuracy either with internal calibration or by regulating the charge in the analyzer cell. We have developed a novel and automated method for internal calibration of liquid chromatography (LC)/FTICR data from whole-cell digests using peptides in the sample identified by concurrent MS/MS together with ambient polydimethylcyclosiloxanes as internal calibrants in the mass spectra. The method reduced mass measurement error from 4.3 +/- 3.7 ppm to 0.3 +/- 2.3 ppm in an E. coli LC/FTICR dataset of 1000 MS and MS/MS spectra and is applicable to all analyses of complex protein digests by FTICRMS.

Algorithms↗

PubMed2005

Mass by energy loss quantitation as a practical submicrogram balance.

A simple device integrating a thin film support and a standard microcentrifuge tube can be used for making solutions of accurately known concentration of any organic compound in a single step, avoiding serial dilution and the use of microgram balances. Nanogram to microgram quantities of organic material deposited on the thin film are quantified by ion energy loss and transferred to the microcentrifuge tube with high recovery.

Biotechnology↗

PubMed2005

Quantitation of binding, recovery and desalting efficiency of peptides and proteins in solid phase extraction micropipette tips.

Micropipette-tip solid phase extraction (SPE) systems are common in proteomic analyses for desalting and concentrating samples for mass spectrometry, removing interferences, and increasing sensitivity. These systems are inexpensive, disposable, and highly efficient. Here, we show micropipette-tip solid phase extraction is a direct sample preparation method for (14)C-accelerator mass spectrometry (AMS), removing salts or reagent from labeled macromolecules. We compared loading, recovery and desalting efficiency in commercially available SPE micro-tips using (14)C-labeled peptides and proteins, AMS, and alpha spectrometry ion energy loss quantitation. The polypropylene in the tips was nearly (14)C-free and simultaneously provided low-background carrier for AMS. The silica material did not interfere with the analysis. Alpha spectrometry provided an absolute measurement of desalting efficiency.

Equipment and Supplies↗

PubMed2005

Neuroscience and accelerator mass spectrometry.

Accelerator mass spectrometry (AMS) is a mass spectrometric method for quantifying rare isotopes. It has had a great impact in geochronology and archaeology and is now being applied in biomedicine. AMS measures radioisotopes such as 3H, 14C, 26Al, 36Cl and 41Ca, with zepto- or attomole sensitivity and high precision and throughput, allowing safe human pharmacokinetic studies involving microgram doses, agents having low bioavailability or toxicology studies where administered doses must be kept low (<1 microg kg(-1)). It is used to study long-term pharmacokinetics, to identify biomolecular interactions, to determine chronic and low-dose effects or molecular targets of neurotoxic substances, to quantify transport across the blood-brain barrier and to resolve molecular turnover rates in the human brain on the time-scale of decades. We review here how AMS is applied in neurotoxicology and neuroscience.

Age Factors↗

PubMed2004

Protein identification by liquid chromatography-mass spectrometry using retention time prediction.

Liquid chromatography has been coupled with mass spectrometry to improve the dynamic range and to reduce the complexity of sample introduced to the mass spectrometer at any given time. The chromatographic separation also provides information on the analytes, such as peptides in enzymatic digests of proteins; information that can be used when identifying the proteins by peptide mass fingerprinting. This paper discusses a recently introduced method based on retention time prediction to extract information from chromatographic separations and the applications of this method to protein identification in organisms with small and large genomes.

Chromatography, Liquid↗

PubMed2003

Alpha-particle energy loss measurement of microgram depositions of biomolecules.

A commercially available alpha-particle spectrometer and 210Po alpha-particle source were used to determine the mass of microgram quantities of biomolecules. Samples were deposited in microliter volumes on thin silicon nitride windows and dried. The energy loss of the alpha-particles after traversing the sample was converted to a mass using tabulated alpha-particle stopping powers. The measurement was absolute, independent of biomolecule species, and no standards were needed for quantitation. The method has a dynamic range of 0.1-100 microg for deposits of diameter 1-2 mm. The precision varies from approximately 20% at 100 ng to a few percent at 5-100 microg. The silicon nitride windows allow multimodal analysis of the same quantified sample, including PIXE probing of elemental abundances, molecular identification by mass spectrometry, and isotopic quantitation of interactions. The method was used with accelerator mass spectrometry to quantify specific activities of microgram quantities of 14C-labeled proteins.

Alpha Particles↗

PubMed2003

Electron donor-acceptor dyads based on ruthenium(II) bipyridine and terpyridine complexes bound to naphthalenediimide.

Two series of photosensitizer-electron acceptor complexes have been synthesized and fully characterized: ruthenium(II) tris(bipyridine) ([Ru(II)(bpy)(2)(bpy-X-NDI)], where X = -CH(2)-, tolylene, or phenylene, bpy is 2,2'-bipyridine, and NDI is naphthalenediimide) and ruthenium(II) bis(terpyridine) ([Ru(II)(Y-tpy)(tpy-X-NDI)], where Y = H or tolyl and X = tolylene or phenylene, and tpy = 2,2':6',2' '-terpyridine). The complexes have been studied by cyclic and differential pulse voltammetry and by steady state and time-resolved absorption and emission techniques. Rates for forward and backward electron transfer have been investigated, following photoexcitation of the ruthenium(II) polypyridine moiety. The terpyridine complexes were only marginally affected by the linked diimide unit, and no electron transfer was observed. In the bipyridine complexes we achieved efficient charge separation. For the complexes containing a phenyl link between the ruthenium(II) and diimide moieties, our results suggest a biphasic forward electron-transfer reaction, in which 20% of the charge-separated state was formed via population of the naphthalenediimide triplet state.

Journal Article↗

PubMed2003

Protein identification in cerebrospinal fluid using packed capillary liquid chromatography Fourier transform ion cyclotron resonance mass spectrometry.

The identification and characterization of proteins in complex biological samples such as body fluids, require powerful and reliable tools. Mass spectrometry is today one of the most important methods in such research. This paper reports on the results from the first experiment where a tryptic digest of cerebrospinal fluid was analyzed applying reversed phase liquid chromatography coupled on-line to a 9.4 T Fourier transform ion cyclotron resonance mass spectrometer. In total, 70 204 peaks were detected, which originated from 16 296 isotopic clusters corresponding to 6551 unique peptide masses. From these masses, 39 proteins were identified in the sample. The amount of sample required for one experiment corresponds to 32 microL of cerebrospinal fluid.

Biophysics↗

PubMed2002

Prediction of chromatographic retention and protein identification in liquid chromatography/mass spectrometry.

Liquid chromatography coupled on- or off-line with mass spectrometry is rapidly advancing as a tool in proteomics capable of dealing with the inherent complexity in biology and complementing conventional approaches based on two-dimensional gel electrophoresis. Proteins can be identified by proteolytic digestion and peptide mass fingerprinting or by searching databases using short-sequence tags generated by tandem mass spectrometry. This paper shows that information on the chromatographic behavior of peptides can assist protein identification by peptide mass fingerprinting in liquid chromatography/mass spectrometry. This additional information is significant and already available at no extra experimental cost.

Amino Acids↗

PubMed2002

Oxidation of methionine 35 attenuates formation of amyloid beta -peptide 1-40 oligomers.

Amyloid plaques formed by aggregation of the amyloid beta-peptide (Abeta) are an intrinsic component of Alzheimer disease pathogenesis. It has been suggested that oxidation of methionine 35 in Abeta has implications for Alzheimer disease, and it has been shown that oxidation of Met-35 significantly inhibits aggregation in vitro. In this study, the aggregational properties of Abeta-(1-40) before and after Met-35 oxidation were investigated using electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry. The results show that Abeta-(1-40)Met-35(O) trimer and tetramer formation is significantly attenuated as compared with Abeta-(1-40). This suggests that oxidation of Met-35 inhibits a conformational switch in Abeta-(1-40) necessary for trimer but not dimer formation. Random incorporation of Abeta-(1-40) and Abeta-(1-40)Met-35(O) in homo- and heterooligomers could also be observed. This is the first report of an early rate-limiting step in Abeta-(1-40) aggregation. Slowing of the fibrillization process at this early step is likely to support prolonged solubility and clearance of Abeta from brain and may reduce disease progression.

Amyloid beta-Peptides↗

PubMed2002

Liquid chromatography and electron-capture dissociation in Fourier transform ion cyclotron resonance mass spectrometry.

Liquid separation methods in combination with electrospray mass spectrometry as well as the recently introduced fragmentation method electron capture dissociation (ECD) have become powerful tools in proteomics research. This paper presents the results of the first successful attempts to combine liquid chromatography (LC) and Fourier transform ion cyclotron resonance mass spectrometry (FTICRMS) with ECD in the analysis of a mixture of standard peptides and of a bovine serum albumin tryptic digest. A novel electron injection system provided conditions for ECD sufficient to yield extensive sequence information for the most abundant peptides in the mixtures on the time-scale of the chromatographic separation. The results suggest that LC/ECD-FTICRMS can be employed in the characterization of peptides in enzymatic digests of proteins or protein mixtures and identify and localize posttranslational modifications.

Chromatography, Liquid↗

PubMedDate not supplied

Peptide mapping of proteins in human body fluids using electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry.

Human body fluids have been rediscovered in the post-genomic era as great sources of biological markers and perhaps particularly as sources of potential protein biomarkers of disease. Analytical tools that allow rapid screening, low sample consumption, and accurate protein identification are of great importance in studies of complex biological samples and clinical diagnosis. Mass spectrometry is today one of the most important analytical tools with applications in a wide variety of fields. One of the fastest growing applications is in proteomics, or the study of protein expression in an organism. Mass spectrometry has been used to find post-translational modifications and to identify key functions of proteins in the human body. In this study, we review the use of human body fluids as sources for clinical markers and present new data that show the ability of Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) to identify and characterize proteins in four human body fluids: plasma, cerebrospinal fluid (CSF), saliva, and urine. The body fluids were tryptically digested without any prior separation, purification, or selection, and the digest was introduced into a 9.4 T FTICR mass spectrometer by direct-infusion electrospray ionization (ESI). Even though these samples represent complex biological mixtures, the described method provides information that is comparable with traditional 2D-PAGE data. The sample consumption is extremely low, a few microliters, and the analysis time is only a few minutes. It is, however, evident that the separation of proteins and/or peptides must be included in the methodology, in order to detect low-abundance proteins and other proteins of biological relevance.

Biomarkers↗

PubMedDate not supplied

Rapid analysis of tryptically digested cerebrospinal fluid using capillary electrophoresis-electrospray ionization-Fourier transform ion cyclotron resonance-mass spectrometry.

Mass spectrometry has in recent years been established as the method of choice for protein identification and characterization in proteomics. Capillary electrophoresis (CE) is a fast and efficient method for the separation of peptides and proteins. The on-line combination of CE with Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) has been shown to be a powerful tool in the analysis of complex mixtures of proteins. This paper presents the first results from a proteomic analysis of human cerebrospinal fluid proteins by tryptic digestion and CE-FTICR-MS, where 30 proteins could be identified on a 95% confidence level with mass measurement errors less than 5 ppm.

Cerebrospinal Fluid↗