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Malmström, J.

Publications and source records attributed to Malmström, J..

16 recordsLinked to original sources
bioRxiv2026

Learning proteomic disease trajectories with flow matching

High-throughput proteomics has enabled detailed characterization of molecular states across health and disease. However, biological systems are inherently dynamic and methods for reconstructing continuous proteome changes remain limited. Here, we introduce proteome velocity, a framework for inferring continuous proteome trajectories from cross-sectional or sparsely sampled proteomics data using flow matching, in which a neural network learns velocity fields over proteome space. Proteome velocity estimates how rapidly and in which direction protein abundances change along a biological progression, such as disease. In mouse sepsis, covariate-conditioned velocity models resolved tissue- and pathogen-specific proteome trajectories and identified inflammatory proteins with distinct temporal activation patterns across infection routes and organ systems. In clinical COVID-19 plasma proteomes, inferred trajectories separated into distinct velocity programs associated with disease severity. These results show how generative trajectory models can transform cross-sectional proteomics data into interpretable, protein-resolved representations of molecular progression.

bioinformatics↗
bioRxiv2026

Structural profiling of the pneumolysin epitope landscape uncovers a cross-species neutralising site across cholesterol-dependent cytolysins

Streptococcus pneumoniae remains a major public health concern, largely due to the limited serotype coverage and other constraints of pneumococcal conjugate vaccines, as well as the increasing antimicrobial resistance among circulating strains. In the pursuit of protein-based pneumococcal vaccines, pneumolysin (PLY), a secreted multifunctional cholesterol-dependent cytolysin, represents a promising target. To date, the relationship between the B-cell epitope landscape and neutralising PLY-specific antibody responses has remained elusive, hindering the rational design of effective PLY-based vaccines. Using a panel of PLY-specific monoclonal antibodies, functional assays, multimodal protein mass spectrometry and data-driven computational modelling, we mapped the structural epitope landscape of native PLY and linked epitope-paratope interactions to neutralising potency. We further refined and structurally characterised a protective cross-species epitope conserved among homologous cholesterol-dependent cytolysins (CDC). This epitope provides a promising foundation for rational, epitope-focused vaccine design, offering a pathway toward species-independent vaccines targeting the CDC protein superfamily.

immunology↗
bioRxiv2025

A cell-based degrader assessment platform facilitates discovery of functional NUDT5 PROTACs

Targeted protein degradation (TPD) via PROTACs and molecular glues holds significant therapeutic promise but demands detailed mechanistic evaluation in live cells to fully understand compound behavior and optimize efficacy. Here, we present an integrated, cell-first platform that combines a modular degradation assay with E3 ligase target engagement readouts for comprehensive assessment of TPD molecules in cells and use it to evaluate PROTACs towards NUDT5. To mimic endogenous degradation conditions and TPD amenability, we established a fusion protein expression system consisting of a lysine-free FKBP12 F36V PROTAC handle (FKBPVK0) and used a HiBiT/akaLuc dual luciferase reporter to accurately measure degradation dynamics. This set-up identified a VHL-dependent NUDT5 PROTAC, DDD2, that induced robust NUDT5 degradation, despite impaired NUDT5 binding in vitro and in cellulo, but no CRBN-dependent degraders. NUDT5 lysine availability mapping with DDD2 and FKBP12 F36V-directed PROTACs suggested that the CRL4CRBN complex is more sensitive to target lysine accessibility than CRL2VHL, which may have implications for E3 ligase choice and therapeutic resistance. CeTEAM drug biosensors were also established towards CRBN and VHL to quantitatively monitor degrader engagement in living cells and confirmed that the tested CRBN-directed NUDT5 PROTACs poorly engaged the E3. All together, this platform provides a versatile and scalable framework for TPD molecule discovery in a cellular context.

biochemistry↗
bioRxiv2025

Design of a Streptolysin O Epitope-Centric Nanoparticle Vaccine Against Streptococcus pyogenes

Streptococcus pyogenes (Group A Streptococcus, GAS) is a significant human pathogen for which no licensed vaccine is currently available. Here, we report a de novo designed epitope-centric protein-based nanoparticle vaccine against GAS. By integrating structural mass spectrometry techniques and deep learning approaches, we re-engineered a protective epitope (D3m) present in domain 3 of streptolysin O, a prominent pore-forming toxin produced by GAS. D3m was displayed on the surface of a self-assembling icosahedral nanoparticle (D3m-NP) to enhance epitope presentation and immunogenicity. Mice immunised with D3m-NP mounted haemolysis-neutralising titres and displayed a more uniform, epitope-centric antibody response than those receiving the community-standard detoxified full-length streptolysin O. Our findings highlight a promising strategy for GAS vaccine development by combining multimodal protein mass spectrometry, protein design and a versatile protein-based nanoparticle vaccine platform.

immunology↗
bioRxiv2024

Streptolysin O Accelerates the Conversion of Plasminogen to Plasmin

Streptococcus pyogenes is a human-specific bacterial pathogen that produces several proteins that exploit the plasminogen (PLG)-plasmin (PLM) fibrinolysis system to dismantle blood clots and to facilitate spread and survival within the host. In this study, we explored the interactions between streptolysin O (SLO), a key cytolytic toxin produced by S. pyogenes, and human plasma proteins using affinity-enrichment mass spectrometry. SLO binds specifically to PLG, and this interaction accelerates the conversion of PLG to PLM by tissue-type plasminogen activator (tPA). To further investigate the molecular detail of the PLG-SLO interaction, we employed hydrogen/deuterium exchange mass spectrometry combined with targeted cross-linking mass spectrometry, uncovering that SLO binding induces local conformational shifts in PLG. These changes lead to the formation of a stabilized intermediate PLG-SLO complex that becomes significantly more sensitive to proteolytic processing by tPA. Our findings reveal a conserved moonlighting pathomechanistic role for SLO extending beyond the well characterized cytolytic activity. Additionally, the work underscores the diversity of functional proteomics in identifying and clarifying new host-pathogen interactions.

molecular biology↗
bioRxiv2023

Community-based peptidomic clustering reveals pathogen-specific proteolytic signatures in wounds

Recent advances in mass spectrometry-based peptidomics has catalyzed the identification and quantification of thousands endogenous peptides across diverse biological systems. However, the large theoretical peptidomic landscape and high proportion of missing values poses several challenges for downstream analyses and limits the comparability of clinical samples. Here, we present a generalizable computational workflow that clusters peptides with overlapping sequences to reduce the dimensionality of peptidomic data, improve the definition of protease cut-sites, enhance inter-sample comparability, and enable the implementation of reliable and large-scale data analysis methods akin to those employed in other omics fields. We showcase the algorithm by performing large-scale quantitative analysis of wound fluid peptidomes of highly defined porcine wounds and human clinical non-healing wounds. The analysis revealed signature phenotype-specific peptide regions reflecting pathogen-specific proteolytic activity at the earliest stages of colonization, resulting in novel class of potential peptide cluster-based biomarkers.

bioinformatics↗
bioRxiv2023

Multi-Modal Mass Spectrometry Identifies a Conserved Protective Epitope in S. pyogenes Streptolysin O

An important element of antibody-guided vaccine design is the use of neutralizing/opsonic monoclonal antibodies to define protective epitopes in their native three-dimensional conformation. Here, we demonstrate a multi-modal mass spectrometry-based strategy for in-depth characterization of antigen-antibody complexes to enable the identification of protective epitopes using the cytolytic exotoxin Streptolysin O (SLO) from Streptococcus pyogenes as a showcase. We first discovered a monoclonal antibody with an undisclosed sequence capable of neutralizing SLO-mediated cytolysis. The amino acid sequence of both the antibody light and the heavy chain was determined using mass spectrometry-based de novo sequencing, followed by chemical crosslinking mass spectrometry to generate distance constraints between the antibody fragment antigen-binding region and SLO. Subsequent integrative computational modeling revealed a discontinuous epitope located in Domain 3 of SLO that was experimentally validated by hydrogen-deuterium exchange mass spectrometry and reverse-engineering of the targeted epitope. The results show that the antibody inhibits SLO-mediated cytolysis by binding to a discontinuous epitope in Domain 3, likely preventing oligomerization and subsequent secondary structure changes critical for pore-formation. The epitope is highly conserved across >98% of the characterized S. pyogenes isolates, making it an attractive target for antibody-based therapy and vaccine design against severe streptococcal infections.

biochemistry↗
bioRxiv2023

The increased hinge flexibility of an IgG1-IgG3 hybrid monoclonal enhances Fc-mediated protection against group A streptococci

Antibodies are central to the immune response against microbes. We have previously generated a protective IgG1 monoclonal antibody targeting the M protein, a critical virulence factor of Streptococcus pyogenes. Here, we generated this antibody in all human IgG subclasses and evaluated their function. Despite significantly reduced binding, the IgG3 subclass antibody demonstrated remarkably enhanced opsonic function. We hypothesized that increased Fc flexibility could explain this improved efficacy. We engineered a hybrid IgG subclass antibody, IgGh, containing the backbone of IgG1 with the hinge of IgG3, leaving the Fabs unchanged. The IgGh maintained a similar binding ability as IgG1 while gaining the strong opsonic function seen with IgG3. Molecular dynamics simulations of the different antibodies showed altered IgG Fab-antigen interactions, reflecting the differences observed in affinity. More importantly, when the antibodies were bound to the antigen, the simulations showed that the Fc of both IgGh and IgG3 exhibited extensive movement in 3D space relative to the M protein. The increased flexibility of IgGh directly translated to enhanced opsonic function and significantly increased the protection against infection with Streptococcus pyogenes in mice. Our findings demonstrate how altering Fc flexibility can improve Fc-mediated opsonic function and how modifications in the constant domain can regulate Fab-antigen interactions. In addition, the enhanced in vivo function of a more flexible IgG provides new therapeutic opportunities for monoclonal antibodies. One sentence summaryAntibody Fc flexibility in 3D space correlates with efficient Fc-mediated phagocytosis of streptococci

immunology↗
bioRxiv2023

Interpreting biologically informed neural networks for enhanced biomarker discovery and pathway analysis

The advent of novel methods in mass spectrometry-based proteomics allows for the identification of biomarkers and biological pathways which are crucial for the understanding of complex diseases. However, contemporary analytical methods often omit essential information, such as protein abundance and protein co-regulation, and therefore miss crucial relationships in the data. Here, we introduce a generalized workflow that incorporates proteins, their abundances, and associated pathways into a deep learning-based methodology to improve biomarker identification and pathway analysis through the creation and interpretation of biologically informed neural networks (BINNs). We successfully employ BINNs to differentiate between two subphenotypes of septic acute kidney injury (AKI) and COVID-19 from the plasma proteome and utilize feature attribution-methods to introspect the networks to identify which proteins and pathways are important for distinguishing between subphenotypes. Compared to existing methods, BINNs achieved the highest predictive accuracy and revealed that metabolic processes were key to differentiating between septic AKI subphenotypes, while the immune system was more important to the classification of COVID-19 subphenotypes. The methodology behind creating, interpreting, and visualizing BINNs were implemented in a free and open source Python-package: https://github.com/InfectionMedicineProteomics/BINN.

bioinformatics↗
bioRxiv2022

Multienzyme deep learning models improve peptide de novo sequencing by mass spectrometry proteomics

Generating and analyzing overlapping peptides through multienzymatic digestion is an efficient procedure for de novo protein using from bottom-up mass spectrometry (MS). Despite improved instrumentation and software, de novo MS data analysis remains challenging. In recent years, deep learning models have represented a performance breakthrough. Incorporating that technology into de novo protein sequencing workflows require machine-learning models capable of handling highly diverse MS data. In this study, we analyzed the requirements for assembling such generalizable deep learning models by systematically varying the composition and size of the training set. We assessed the generated models performances using two test sets composed of peptides originating from the multienzyme digestion of samples from various species. The peptide recall values on the test sets showed that the deep learning models generated from a collection of highly N- and C-termini diverse peptides generalized 76% more over the termini-restricted ones. Moreover, expanding the training sets size by adding peptides from the multienzymatic digestion with five proteases of several species samples led to a 2-3 fold generalizability gain. Furthermore, we tested the applicability of these multienzyme deep learning (MEM) models by fully de novo sequencing the heavy and light monomeric chains of five commercial antibodies (mAbs). MEM models extracted over 10000 matching and overlapped peptides across six different proteases mAb samples, achieving a 100% sequence coverage for 8 of the ten polypeptide chains. We foretell that the MEM models proven improvements to de novo analysis will positively impact several applications, such as analyzing samples of high complexity, unknown nature, or the peptidomics field.

bioinformatics↗
bioRxiv2022

Invasive streptococcal infection can lead to the generation of cross-strain opsonic antibodies

IntroductionThe human pathogen Streptococcus pyogenes causes substantial morbidity and mortality. It is unclear if antibodies developed after infections with this pathogen are opsonic and if they are strain-specific or more broadly protective. Here, we quantified the opsonic antibody response following invasive S. pyogenes infection. Materials and MethodsFour patients with S. pyogenes bacteremia between 2018-2020 at Sk[a]ne University Hospital in Lund, Sweden, were prospectively enrolled. Acute and convalescent sera were obtained, and the S. pyogenes isolates were genome-sequenced (emm118, emm85, and two emm1). Quantitative antibody binding and phagocytosis assays were used to evaluate isolate-dependent opsonic antibody function in response to infection. ResultsAntibody binding increased modestly against the infecting isolate and across emm types in convalescent compared to acute sera for all patients. For two patients, phagocytosis increased in convalescent serum for both the infecting isolate and across types. The increase was only across types for one patient, and one had no improvement. No correlation to the clinical outcomes was observed. ConclusionInvasive S. pyogenes infections result in a modestly increased antibody binding with differential opsonic capacity, both non-functional binding and broadly opsonic binding across types. These findings question the dogma that an invasive infection should lead to a strong type-specific antibody increase rather than a more modest but broadly reactive response, as seen in these patients. Furthermore, our results indicate that an increase in antibody titers might not be indicative of an opsonic response and highlight the importance of evaluating antibody function in S. pyogenes infections.

immunology↗
bioRxiv2021

Vascular proteome responses precede organ dysfunction in sepsis

Vascular dysfunction and organ failure are two distinct, albeit highly interconnected clinical outcomes linked to morbidity and mortality in human sepsis. The mechanisms driving vascular and parenchymal damage are dynamic and display significant molecular crosstalk between organs and tissues. Therefore, assessing their individual contribution to disease progression is technically challenging. Here, we hypothesize that dysregulated vascular responses predispose the organism to organ failure. To address this hypothesis, we have evaluated four major organs in a murine model of S. aureus sepsis by combining in vivo labeling of the endothelial proteome, data-independent acquisition (DIA) mass spectrometry, and an integrative computational pipeline. The data reveal, with unprecedented depth and throughput, that a septic insult evokes organ-specific proteome responses that are highly compartmentalized, synchronously coordinated, and significantly correlated with the progression of the disease. Vascular proteome changes were found to precede bacterial invasion and leukocyte infiltration into the organs, as well as to precede changes in various well-established cellular and biochemical correlates of systemic coagulopathy and tissue dysfunction. Importantly, our data suggests a potential role for the vascular proteome as a determinant of the susceptibility of the organs to undergo failure during sepsis.

immunology↗
bioRxiv2021

Opsonization by non-neutralizing antibodies can confer protection to SARS-CoV-2 despite Spike-dependent modulation of phagocytosis

Spike-specific antibodies are central to effective COVID19 immunity. Research efforts have focused on antibodies that neutralize the ACE2-Spike interaction but not on non-neutralizing antibodies. Antibody-dependent phagocytosis is an immune mechanism enhanced by opsonization, where typically, more bound antibodies trigger a stronger phagocyte response. Here, we show that Spike-specific antibodies, dependent on concentration, can either enhance or reduce Spike-bead phagocytosis by monocytes independently of the antibody neutralization potential. Surprisingly, we find that both convalescent patient plasma and patient-derived monoclonal antibodies lead to maximum opsonization already at low levels of bound antibodies and is reduced as antibody binding to Spike protein increases. Moreover, we show that this Spike-dependent modulation of opsonization seems to affect the outcome in an experimental SARS-CoV-2 infection model. These results suggest that the levels of anti-Spike antibodies could influence monocyte-mediated immune functions and propose that non-neutralizing antibodies could confer protection to SARS-CoV-2 infection by mediating phago-cytosis.

immunology↗
bioRxiv2020

Extending the proteomic characterization of Candida albicans exposed to stress and apoptotic inducers through data-independent acquisition mass spectrometry

Candida albicans is a commensal fungus that causes systemic infections in immunosuppressed patients. In order to deal with the changing environment during commensalism or infection, C. albicans must reprogram its proteome. Characterizing the stress-induced changes in the proteome that C. albicans uses to survive should be very useful in the development of new antifungal drugs. We studied the C. albicans global proteome after exposure to hydrogen peroxide (H2O2) and acetic acid (AA), using a DIA-MS strategy. More than 2000 C. albicans proteins were quantified using an ion library previously constructed using DDA-MS. C. albicans responded to treatment with H2O2 with an increase in the abundance of many proteins involved in the oxidative stress response, protein folding and proteasome-dependent catabolism, which led to an increased proteasome activity. The data revealed a previously unknown key role for Prn1, a protein similar to pirins, in the oxidative stress response. Treatment with AA resulted in a general decrease in the abundance of proteins involved in amino acid biosynthesis, protein folding, and rRNA processing. Almost all proteasome proteins declined, as did proteasome activity. Apoptosis was observed after treatment with H2O2, but not AA. A targeted proteomic study of 32 proteins related to apoptosis in yeast supported the results found by DIA-MS and allowed the creation of an efficient method to quantify relevant proteins after treatment with stressors (H2O2, AA, and amphotericin B). This approach also uncovered a main role for Oye32, an oxidoreductase, suggesting this protein as a possible apoptotic marker common to many stressors. IMPORTANCEFungal infections are a worldwide health problem especially in immunocompromised patients and patients with chronic disorders. Invasive candidiasis, mainly caused by C. albicans, are among the most common fungal diseases. Despite the existence of treatments to combat candidiasis the spectra of drugs available are limited. For the discovery of new drug targets is essential to know the pathogen response to different stress conditions. Our study provides a global vision of proteomic remodeling in C. albicans after exposure to different agents such as hydrogen peroxide, acetic acid and amphotericin B that can cause apoptotic cell death. This results revealed the significance of many proteins related to oxidative stress response and proteasome activity among others. Of note, the discovery of Prn1 as a key protein in the defence against oxidative stress as well the increase in the abundance of Oye32 protein when apoptotic process occurred point out them as possible drug targets.

microbiology↗
bioRxiv2020

Structural determination of Streptococcus pyogenes M1 protein interactions with human immunoglobulin G using integrative structural biology

Streptococcus pyogenes (Group A streptococcus; GAS) is an important human pathogen responsible for mild to severe, life-threatening infections. GAS expresses a wide range of virulence factors, including the M family proteins. The M proteins allow the bacteria to evade parts of the human immune defenses by triggering the formation of a dense coat of plasma proteins surrounding the bacteria, including IgGs. However, the molecular level details of the M1-IgG interaction have remained unclear. Here, we characterized the structure and dynamics of this interaction interface in human plasma on the surface of live bacteria using integrative structural biology, combining cross-linking mass spectrometry and molecular dynamics (MD) simulations. We show that the primary interaction is formed between the S-domain of M1 and the conserved IgG Fc-domain. In addition, we show evidence for a so far uncharacterized interaction between the A-domain and the IgG Fc-domain. Both these interactions mimic the protein G-IgG interface of group C and G streptococcus. These findings underline a conserved scavenging mechanism used by GAS surface proteins that block the IgG-receptor (Fc{gamma}R) to inhibit phagocytic killing. We additionally show that we can capture Fab-bound IgGs in a complex background and identify the specific M1 epitopes targeted on live bacteria. Our results elucidate the M1-IgG interaction network involved in inhibition of phagocytosis and reveal important M1 peptides that can be further investigated as future vaccine targets.

molecular biology↗
bioRxiv2019

Sweet revenge - Streptococcus pyogenes showcases first example of immune evasion through specific IgG glycan hydrolysis

Streptococcus pyogenes (Group A streptococcus, GAS) is an important human pathogen responsible for a wide variety of diseases from uncomplicated tonsillitis to life-threatening invasive infections. GAS secretes EndoS, an endoglycosidase able to specifically cleave the conserved N-glycan on human IgG antibodies. In vitro, removal of this glycan impairs IgG effector functions but its relevance to GAS infection in vivo is unclear. Using targeted mass spectrometry, we were able to characterize the effects of EndoS on host IgG glycosylation during the course of natural infections in human patients. We found substantial IgG glycan hydrolysis locally at site of infection as well as systemically in the most severe cases. Using these findings we were able to set up appropriate model systems to demonstrate decreased resistance to phagocytic killing of GAS lacking EndoS in vitro, as well as decreased virulence in a mouse model of invasive infection. This study represents the first described example of specific bacterial IgG glycan hydrolysis during infection and highlights the importance of IgG glycan hydrolysis for streptococcal pathogenesis. We thereby offer new insights into the mechanism of immune evasion employed by this pathogen with clear implications for treatment of severe GAS infections and future efforts at vaccine development.

microbiology↗