Biology subjects

Malmstrom, L.

Publications and source records attributed to Malmstrom, L..

10 recordsLinked to original sources

bioRxiv2025

Streptococcus pyogenes nuclease A interferes with host complement functions

Bacterial pathogens deploy diverse virulence factors to subvert host immunity, yet the molecular details of these interactions often remain unresolved. Here, we investigate the structure and host interactome of the Streptococcus pyogenes nuclease A (SpnA). We characterized the structure and dynamics of SpnA using hydrogen-deuterium exchange mass spectrometry and single-particle electron cryo microscopy, yielding the first structural insights to this protein. This allowed us to identify an additional oligonucleotide-binding domain whose flexible structure may play an important function in the nucleolytic activity of SpnA. Affinity-pulldown mass spectrometry identified the complement system membrane attack complex C5b67 components as key interactors in human plasma. Cross-linking mass spectrometry combined with integrative modeling identified the direct binding interfaces between SpnA and C5b67. These interfaces are highly conserved among genetically diverse S. pyogenes strains. The interaction between SpnA and C5b67 is suggested to prevent the assembly of a functional membrane attack complex. Taken together, our findings uncover a novel function of SpnA in complement inhibition and identifies new potential targets to prevent and treat S. pyogenes infections.

microbiology↗

bioRxiv2025

Cumulating MS Signal enables polyclonal antibody analysis

Unraveling the complexities of protein systems via Mass Spectrometry (MS), particularly polyclonal antibodies, demands innovative analytical strategies. Here, we introduce the cumulative MS score (cMS), a novel mathematical framework that transcends traditional spectrum-matching, integrating MS evidence across multiple sample injections to achieve robust de novo peptide sequencing annotation. This approach, shifting from isolated spectrum analysis to a holistic MS signal-based methodology, was rigorously evaluated and validated across diverse sample types and experimental conditions. We applied this framework to characterize a complex polyclonal antibody mixture of Streptococcus pyogenes M1 protein binders derived from intravenous immunoglobulin (IVIG), revealing predominant variable heavy (VH) and light (VL) chain subgroups consistent with established genetic studies. Furthermore, we successfully identified conserved complementarity-determining region (CDR) features and predicted stable antibody-antigen interactions through molecular dynamics simulations, demonstrating the methods potential for dissecting intricate antibody responses. This work establishes a powerful alternative to conventional tandem mass spectrometry MS/MS data analysis, enabling deeper insights into protein systems and paving the way for targeted therapeutic development.

bioinformatics↗

bioRxiv2024

Inferring the composition of the blood plasma proteome by a human proteome distribution atlas

The plasma proteome is maintained by the influx and efflux of proteins from surrounding organs and cells. To quantify the extent different organs and cells contribute to the plasma proteome composition, we developed a mass spectrometry-based proteomics strategy to infer the origin of proteins detected in human plasma in health and disease. First, we constructed an extensive human proteome atlas from 18 vascularized organs and the most abundant cell types in blood. Second, the atlas was interfaced with previous RNA/protein atlases to objectively define proteome wide protein-organ associations to enable both the inference of origin and the reproducible quantification of organ-specific proteins in plasma. We demonstrate that the resource can determine disease-specific quantitative changes of organ-enriched protein panels in three separate patient cohorts with infection, pancreatitis, and myocardial injury. The strategy can be extended to other diseases to advance our understanding of the processes contributing to plasma proteome dynamics.

systems biology↗

bioRxiv2023

Dissecting the properties of circulating IgG against Group A Streptococcus through a combined systems antigenomics-serology workflow

Most individuals maintain circulating antibodies against various pathogenic bacteria as a consequence of previous exposures. However, it remains unclear to what extent these antibodies contribute to host protection. This knowledge gap is linked to the need for better methods to characterize antimicrobial polyclonal antibodies, including their antigen and epitope repertoires, subclass distribution, glycosylation status, and effector functions. Here, we showcase a generic mass spectrometry-based strategy that couples systems antigenomics and systems serology to characterize human antibodies directly in clinical samples. The method is based on automated affinity purification workflows coupled to an integrated suite of high-resolution MS-based quantitative, structural- and glyco-proteomics readouts. We focused on Streptococcus pyogenes (Group A Streptococcus; GAS), a major human pathogen still awaiting an approved vaccine. Our methodology reveals that both healthy and GAS infected individuals have circulating Immunoglobulin G (IgG) against a subset of genomically conserved streptococcal proteins, including numerous toxins and virulence factors. The antigen repertoire targeted by these antibodies was relatively constant across healthy individuals, but considerably changed in GAS bacteremia. Detailed analysis of the antigen-specific IgG indicates inter-individual variation regarding titers, subclass distributions, and Fc-signaling capacity, but not in epitope and Fc-glycosylation patterns. Importantly, we show that the IgG subclass has a major impact on the ability of GAS-antibodies to trigger immune signaling, in an antigen- and Fc receptor-specific fashion. Overall, these results uncover exceeding complexity in the properties of GAS-specific IgG, and showcase our methodology as high-throughput and flexible workflow to understand adaptive immune responses to bacterial pathogens. Significance statementMost people develop polyclonal antibodies against bacterial pathogens during infections but their structural and functional properties are poorly understood. Here, we showcase a combined systems antigenomics and systems serology strategy to quantify key antibody properties directly in clinical samples. We applied this method to characterize polyclonal antibody responses against Streptococcus pyogenes, a major human pathogen. We mapped the antigen and epitope landscape of anti-streptococcal antibodies circulating in healthy adult plasma, and their changes during blood infections. We further demonstrate the analytical power of our approach to resolve individual variations in the structure and effector functions of antigen-specific antibodies, including a dependency between immunoglobulin subclass and Fc-signaling capacity.

immunology↗

bioRxiv2022

Shigella ipaA mediates actin bundling through diffusible vinculin oligomers with activation imprint

Upon activation, vinculin reinforces cytoskeletal anchorage during cell adhesion. Activating ligands classically disrupt intramolecular interactions between the vinculin head and tail domain that binds to actin filaments. Here, we show that Shigella IpaA triggers major allosteric changes in the head domain leading to vinculin homo-oligomerization. Through the cooperative binding of its three vinculin-binding sites (VBSs), IpaA induces a striking reorientation of the D1 and D2 head subdomains associated with vinculin oligomerization. IpaA thus acts as a catalyst producing vinculin clusters that bundle actin at a distance from the activation site and trigger the formation of highly stable adhesions resisting the action of actin relaxing drugs. Unlike canonical activation, vinculin homo-oligomers induced by IpaA appear to keep a persistent imprint of the activated state in addition to their bundling activity, accounting for stable cell adhesion independent of force transduction and relevant to bacterial invasion.

microbiology↗

bioRxiv2022

Generalized peakgroup scoring boosts identification rates and accuracy in mass spectrometry based discovery proteomics

The statistical validation of peptide and protein identifications in mass spectrometry proteomics is a critical step in the analytical workflow. This is particularly important in discovery experiments to ensure only confident identifications are accumulated for downstream analysis and biomarker consideration. However, the inherent nature of discovery proteomics experiments leads to scenarios where the search space will inflate substantially due to the increased number of potential proteins that are being queried in each sample. In these cases, issues will begin to arise when the machine learning algorithms that are trained on an experiment specific basis cannot accurately distinguish between correct and incorrect identifications and will struggle to accurately control the false discovery rate. Here, we propose an alternative validation algorithm trained on a curated external data set of 2.8 million extracted peakgroups that leverages advanced machine learning techniques to create a generalizable peakgroup scoring (GPS) method for data independent acquisition (DIA) mass spectrometry. By breaking the reliance on the experimental data at hand and instead training on a curated external dataset, GPS can confidently control the false discovery rate while increasing the number of identifications and providing more accurate quantification in different search space scenarios. To first test the performance of GPS in a standard experimental environment and to provide a benchmark against other methods, a novel spike-in data set with known varying concentrations was analyzed. When compared to existing methods GPS increased the nunmber of identifications by 5-18% and was able to provide more accurate quantification by increasing the number of ratio validated identifications by 24-74%. To evaluate GPS in a larger search space, a novel data set of 141 blood plasma samples from patients developing acute kidney injury after sepsis was searched with a human tissue spectral library (10000+ proteins). Using GPS, we were able to provide a 207-377% increase in the number of candidate differentially abundant proteins compared to the existing methods while maintaining competitive numbers of global identifications. Finally, using an optimized human tissue library and workflow we were able to identify 1205 proteins from the 141 plasma samples and increase the number of candidate differentially abundant proteins by 70.87%. With the addition of machine learning aided differential expression, we were able to identify potential new biomarkers for stratifying subphenotypes of acute kidney injury in sepsis. These findings suggest that by using a generalized model such as GPS in tandem with a massive scale spectral library it is possible to expand the boundaries of discovery experiments in DIA proteomics. GPS is open source and freely available on github at (https://github.com/InfectionMedicineProteomics/gscore).

bioinformatics↗

bioRxiv2022

A pharmacoproteomic landscape of organotypic intervention responses in gram-negative sepsis

Sepsis is the major cause of mortality across intensive care units globally, yet details of accompanying pathological molecular events remains unclear. This knowledge gap has resulted in ineffective development of sepsis-specific biomarkers and therapies, and suboptimal treatment regimens to prevent or reverse organ damage. Here, we used pharmacoproteomics to score treatment effects in a murine Escherichia coli sepsis model based on changes in the organ, cell, and plasma proteome landscapes. A combination of pathophysiological read-outs and time-resolved proteome maps of organs and blood enabled us to define time-dependent and organotypic proteotypes of dysfunction and damage upon administration of several combinations of the broad-spectrum beta-lactam antibiotic meropenem (Mem) and/or the immunomodulatory glucocorticoid methylprednisolone (Gcc). Three distinct response patterns were identified, defined as intervention-specific reversions, non-reversions, and specific intervention-induced effects, which depended on the underlying proteotype and varied significantly across organs. In the later stages of the disease, Gcc enhanced some positive treatment effects of Mem with superior reduction of the inflammatory response in the kidneys and partial restoration of sepsis-induced metabolic dysfunction. Unexpectedly, Mem introduced sepsis-independent perturbations in the mitochondrial proteome that were to some degree counteracted by Gcc. In summary, this study provides a pharmacoproteomic resource describing the time-resolved septic organ failure landscape across organs and blood, coupled to a novel scoring strategy that captures unintended secondary drug effects as an important criterion to consider when assessing therapeutic efficacy. Such information is critical for quantitative, objective, and organotypic assessment of benefits and unintended effects of candidate treatments in relationship to dosing, timing, and potential synergistic combinations in murine sepsis models.

systems biology↗

bioRxiv2022

Evolution of ipsilateral breast cancer decoded by proteogenomics

Ipsilateral breast tumor recurrence (IBTR) is a clinically important event, where an isolated in-breast recurrence is a potentially curable event but also associated with an increased risk of distant metastases and breast cancer death. It currently remains unclear if IBTRs are associated with molecular changes that can be explored as a resource for precision medicine strategies targeting locally recurring breast cancer. Here, we employed a recently developed proteogenomics workflow to analyze a cohort of 27 primary breast cancers and their matched IBTRs by whole genome sequencing, RNA sequencing, and mass spectrometry-based proteomics to define proteogenomic features of tumor evolution. Analysis of mutational signatures, copy number changes, and cancer specific mutations revealed a relationship with estrogen and progesterone receptor statuses and increased levels of genetic change. This in turn altered the re-programming of the transcriptome and proteome towards a recurring molecular disease phenotype with high replicating capacity and a higher degree of genomic instability possibly enhanced by high expression of APOBEC3B. In conclusion, this study defines how primary breast tumors differentially evolve into different ipsilateral recurrent malignancies depending on their key biomarker status, suggesting that further enhancing the genomic instability in some tumors could serve as an alternative treatment option.

cancer biology↗

bioRxiv2021

Bacterial clearance caused by a single anti-M protein antibody simultaneously binding two separate epitopes

Group A streptococci have evolved multiple strategies to evade human antibodies, making it challenging to create effective vaccines or antibody treatments. Here, we have generated antibodies derived from the memory B cells of an individual who had successfully cleared a group A streptococcal infection. The antibodies bind with high affinity in the central region of the surface-bound M protein. Such antibodies are typically non-opsonic. However, one antibody could effectively promote vital immune functions, including phagocytosis and in vivo protection. Remarkably, this antibody primarily interacts through a bivalent dual-Fab cis mode, where the Fabs bind to two distinct epitopes in the M protein. The dual-Fab cis binding phenomenon is conserved across different groups of M types. In contrast, other antibodies binding with normal single-Fab mode to the same region can not bypass the M proteins virulent effects. A broadly binding, protective monoclonal antibody could be a candidate for anti-streptococcal therapy. Our findings highlight the concept of dual-Fab cis binding as a means to access conserved, and normally non-opsonic regions, for protective antibody targeting.

immunology↗

bioRxiv2019

Vinculin targeting by Shigella IpaA promotes stable cell adhesion independent of mechanotransduction

The Shigella effector IpaA co-opts the focal adhesion protein vinculin to promote bacterial invasion. Here, we show that IpaA triggers an unreported mode of vinculin activation through the cooperative binding of its three vinculin-binding sites (VBSs) leading to vinculin oligomerization via its D1 and D2 head subdomains and highly stable adhesions resisting actin relaxing drugs. Using cross-linking mass spectrometry, we found that while IpaA VBSs1-2 bound to D1, IpaA VBS3 interacted with D2, a subdomain masked to other known VBSs. Structural modeling indicated that as opposed to canonical activation linked to interaction with D1, these combined VBSs interactions triggered major allosteric changes leading to D1D2 oligomerization. A cysteine-clamp preventing these changes and D1D2 oligomerization impaired growth of vinculin microclusters and cell adhesion. We propose that D1D2-mediated vinculin oligomerization occurs during the maturation of adhesion structures to enable the scaffolding of high-order vinculin complexes, and is triggered by Shigella IpaA to promote bacterial invasion in the absence of mechanotransduction. SummaryThe Shigella IpaA effector binds to cryptic vinculin sites leading to oligomerization via its head domain. This vinculin oligomerization mode appears required for the maturation and strengthening of cell adhesion but is co-opted by invasive bacteria independent of actomyosin contractility.

microbiology↗