Multimodal 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 or opsonic monoclonal antibodies to define protective epitopes in their native three-dimensional conformation. Here, we demonstrate a multimodal 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 cross-linking 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 transitions 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.

The hinge-engineered IgG1-IgG3 hybrid subclass IgGh47 potently enhances Fc-mediated function of anti-streptococcal and SARS-CoV-2 antibodies.

Streptococcus pyogenes can cause invasive disease with high mortality despite adequate antibiotic treatments. To address this unmet need, we have previously generated an opsonic IgG1 monoclonal antibody, Ab25, targeting the bacterial M protein. Here, we engineer the IgG2-4 subclasses of Ab25. Despite having reduced binding, the IgG3 version promotes stronger phagocytosis of bacteria. Using atomic simulations, we show that IgG3's Fc tail has extensive movement in 3D space due to its extended hinge region, possibly facilitating interactions with immune cells. We replaced the hinge of IgG1 with four different IgG3-hinge segment subclasses, IgGhxx. Hinge-engineering does not diminish binding as with IgG3 but enhances opsonic function, where a 47 amino acid hinge is comparable to IgG3 in function. IgGh47 shows improved protection against S. pyogenes in a systemic infection mouse model, suggesting that IgGh47 has promise as a preclinical therapeutic candidate. Importantly, the enhanced opsonic function of IgGh47 is generalizable to diverse S. pyogenes strains from clinical isolates. We generated IgGh47 versions of anti-SARS-CoV-2 mAbs to broaden the biological applicability, and these also exhibit strongly enhanced opsonic function compared to the IgG1 subclass. The improved function of the IgGh47 subclass in two distant biological systems provides new insights into antibody function.

Proteomic profiling reveals that ESR1 mutations enhance cyclin-dependent kinase signaling.

Three quarters of all breast cancers express the estrogen receptor (ER, ESR1 gene), which promotes tumor growth and constitutes a direct target for endocrine therapies. ESR1 mutations have been implicated in therapy resistance in metastatic breast cancer, in particular to aromatase inhibitors. ESR1 mutations promote constitutive ER activity and affect other signaling pathways, allowing cancer cells to proliferate by employing mechanisms within and without direct regulation by the ER. Although subjected to extensive genetic and transcriptomic analyses, understanding of protein alterations remains poorly investigated. Towards this, we employed an integrated mass spectrometry based proteomic approach to profile the protein and phosphoprotein differences in breast cancer cell lines expressing the frequent Y537N and Y537S ER mutations. Global proteome analysis revealed enrichment of mitotic and immune signaling pathways in ER mutant cells, while phosphoprotein analysis evidenced enriched activity of proliferation associated kinases, in particular CDKs and mTOR. Integration of protein expression and phosphorylation data revealed pathway-dependent discrepancies (motility vs proliferation) that were observed at varying degrees across mutant and wt ER cells. Additionally, protein expression and phosphorylation patterns, while under different regulation, still recapitulated the estrogen-independent phenotype of ER mutant cells. Our study is the first proteome-centric characterization of ESR1 mutant models, out of which we confirm estrogen independence of ER mutants and reveal the enrichment of immune signaling pathways at the proteomic level.

Quantification of Adaptive Immune Responses Against Protein-Binding Interfaces in the Streptococcal M1 Protein.

Bacterial or viral antigens can contain subdominant protein regions that elicit weak antibody responses upon vaccination or infection although there is accumulating evidence that antibody responses against subdominant regions can enhance the protective immune response. One proposed mechanism for subdominant protein regions is the binding of host proteins that prevent antibody production against epitopes hidden within the protein binding interfaces. Here, we used affinity purification combined with quantitative mass spectrometry (AP-MS) to examine the level of competition between antigen-specific antibodies and host-pathogen protein interaction networks using the M1 protein from Streptococcus pyogenes as a model system. As most humans have circulating antibodies against the M1 protein, we first used AP-MS to show that the M1 protein interspecies protein network formed with human plasma proteins is largely conserved in naïve mice. Immunizing mice with the M1 protein generated a time-dependent increase of anti-M1 antibodies. AP-MS analysis comparing the composition of the M1-plasma protein network from naïve and immunized mice showed significant enrichment of 292 IgG peptides associated with 56 IgG chains in the immune mice. Despite the significant increase of bound IgGs, the levels of interacting plasma proteins were not significantly reduced in the immune mice. The results indicate that the antigen-specific polyclonal IgG against the M1 protein primarily targets epitopes outside the other plasma protein binding interfaces. In conclusion, this study demonstrates that AP-MS is a promising strategy to determine the relationship between antigen-specific antibodies and host-pathogen interaction networks that could be used to define subdominant protein regions of relevance for vaccine development.

Decoding of the surfaceome and endocytome in primary glioblastoma cells identifies potential target antigens in the hypoxic tumor niche.

Immunotherapies with antibody-drug-conjugates (ADC) and CAR-T cells, targeted at tumor surface antigens (surfaceome), currently revolutionize clinical oncology. However, target identification warrants a better understanding of the surfaceome and how it is modulated by the tumor microenvironment. Here, we decode the surfaceome and endocytome and its remodeling by hypoxic stress in glioblastoma (GBM), the most common and aggressive brain tumor in adults. We employed a comprehensive approach for global and dynamic profiling of the surfaceome and endocytosed (endocytome) proteins and their regulation by hypoxia in patient-derived GBM cultures. We found a heterogeneous surface-endocytome profile and a divergent response to hypoxia across GBM cultures. We provide a quantitative ranking of more than 600 surface resident and endocytosed proteins, and their regulation by hypoxia, serving as a resource to the cancer research community. As proof-of-concept, the established target antigen CD44 was identified as a commonly and abundantly expressed surface protein with high endocytic activity. Among hypoxia induced proteins, we reveal CXADR, CD47, CD81, BSG, and FXYD6 as potential targets of the stressed GBM niche. We could validate these findings by immunofluorescence analyses in patient tumors and by increased expression in the hypoxic core of GBM spheroids. Selected candidates were finally confronted by treatment studies, showing their high capacity for internalization and ADC delivery. Importantly, we highlight the limited correlation between transcriptomics and proteomics, emphasizing the critical role of membrane protein enrichment strategies and quantitative mass spectrometry. Our findings provide a comprehensive understanding of the surface-endocytome and its remodeling by hypoxia in GBM as a resource for exploration of targets for immunotherapeutic approaches in GBM.

Pathogen-driven degradation of endogenous and therapeutic antibodies during streptococcal infections.

Group A streptococcus (GAS) is a major bacterial pathogen responsible for both local and systemic infections in humans. The molecular mechanisms that contribute to disease heterogeneity remain poorly understood. Here we show that the transition from a local to a systemic GAS infection is paralleled by pathogen-driven alterations in IgG homeostasis. Using animal models and a combination of sensitive proteomics and glycoproteomics readouts, we documented the progressive accumulation of IgG cleavage products in plasma, due to extensive enzymatic degradation triggered by GAS infection in vivo. The level of IgG degradation was modulated by the route of pathogen inoculation, and mechanistically linked to the combined activities of the bacterial protease IdeS and the endoglycosidase EndoS, upregulated during infection. Importantly, we show that these virulence factors can alter the structure and function of exogenous therapeutic IgG in vivo. These results shed light on the role of bacterial virulence factors in shaping GAS pathogenesis, and potentially blunting the efficacy of antimicrobial therapies.

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

The incorporation of machine learning methods into proteomics workflows improves the identification of disease-relevant biomarkers and biological pathways. However, machine learning models, such as deep neural networks, typically suffer from lack of interpretability. Here, we present a deep learning approach to combine biological pathway analysis and biomarker identification to increase the interpretability of proteomics experiments. Our approach integrates a priori knowledge of the relationships between proteins and biological pathways and biological processes into sparse neural networks to create biologically informed neural networks. We employ these networks to differentiate between clinical subphenotypes of septic acute kidney injury and COVID-19, as well as acute respiratory distress syndrome of different aetiologies. To gain biological insight into the complex syndromes, we utilize feature attribution-methods to introspect the networks for the identification of proteins and pathways important for distinguishing between subtypes. The algorithms are implemented in a freely available open source Python-package ( https://github.com/InfectionMedicineProteomics/BINN ).

Quantification of heat shock proteins in the posterior interosseous nerve among subjects with type 1 and type 2 diabetes compared to healthy controls.

Introduction: Diabetic peripheral neuropathy (DPN) is a common complication of both type 1 (T1D) and type 2 diabetes (T2D). No cure for DPN is available, but several potential targets have been proposed for treatment. Heat shock proteins (HSPs) are known to respond to both hyper- and hypoglycemia. DPN can be diagnosed using electrophysiology and studied using peripheral nerve biopsies. Aim: This study aimed to analyze the presence and patterns of HSPs in peripheral nerve biopsies from subjects with T1D, T2D, and healthy controls. Methods: Posterior interosseous nerves (PIN) from a total of 56 subjects with T1D (n = 9), with T2D (n = 24), and without diabetes (i.e., healthy controls, n = 23) were harvested under local anesthesia and prepared for quantitative mass spectrometry analysis. Protein intensities were associated with electrophysiology data of the ulnar nerve and morphometry of the same PIN, and differences in protein intensities between groups were analyzed. Results: In total, 32 different HSPs were identified and quantified in the nerve specimens. No statistically significant differences were observed regarding protein intensities between groups. Furthermore, protein intensities did not correlate with amplitude or conduction velocity in the ulnar nerve or with the myelinated nerve fiber density of PIN. Conclusion: Quantitative proteomics can be used to study HSPs in nerve biopsies, but no clear differences in protein quantities were observed between groups in this cohort.

Serum proteome profiles in patients treated with targeted temperature management after out-of-hospital cardiac arrest.

BACKGROUND: Definition of temporal serum proteome profiles after out-of-hospital cardiac arrest may identify biological processes associated with severe hypoxia-ischaemia and reperfusion. It may further explore intervention effects for new mechanistic insights, identify candidate prognostic protein biomarkers and potential therapeutic targets. This pilot study aimed to investigate serum proteome profiles from unconscious patients admitted to hospital after out-of-hospital cardiac arrest according to temperature treatment and neurological outcome. METHODS: Serum samples at 24, 48, and 72 h after cardiac arrest at three centres included in the Target Temperature Management after out-of-hospital cardiac arrest trial underwent data-independent acquisition mass spectrometry analysis (DIA-MS) to find changes in serum protein concentrations associated with neurological outcome at 6-month follow-up and targeted temperature management (TTM) at 33 °C as compared to 36 °C. Neurological outcome was defined according to Cerebral Performance Category (CPC) scale as "good" (CPC 1-2, good cerebral performance or moderate disability) or "poor" (CPC 3-5, severe disability, unresponsive wakefulness syndrome, or death). RESULTS: Of 78 included patients [mean age 66 ± 12 years, 62 (80.0%) male], 37 (47.4%) were randomised to TTM at 36 °C. Six-month outcome was poor in 47 (60.3%) patients. The DIA-MS analysis identified and quantified 403 unique human proteins. Differential protein abundance testing comparing poor to good outcome showed 19 elevated proteins in patients with poor outcome (log2-fold change (FC) range 0.28-1.17) and 16 reduced proteins (log2(FC) between - 0.22 and - 0.68), involved in inflammatory/immune responses and apoptotic signalling pathways for poor outcome and proteolysis for good outcome. Analysis according to level of TTM showed a significant protein abundance difference for six proteins [five elevated proteins in TTM 36 °C (log2(FC) between 0.33 and 0.88), one reduced protein (log2(FC) - 0.6)] mainly involved in inflammatory/immune responses only at 48 h after cardiac arrest. CONCLUSIONS: Serum proteome profiling revealed an increase in inflammatory/immune responses and apoptosis in patients with poor outcome. In patients with good outcome, an increase in proteolysis was observed, whereas TTM-level only had a modest effect on the proteome profiles. Further validation of the differentially abundant proteins in response to neurological outcome is necessary to validate novel biomarker candidates that may predict prognosis after cardiac arrest.

Generalized precursor prediction boosts identification rates and accuracy in mass spectrometry based proteomics.

Data independent acquisition mass spectrometry (DIA-MS) has recently emerged as an important method for the identification of blood-based biomarkers. However, the large search space required to identify novel biomarkers from the plasma proteome can introduce a high rate of false positives that compromise the accuracy of false discovery rates (FDR) using existing validation methods. We developed a generalized precursor scoring (GPS) method trained on 2.75 million precursors that can confidently control FDR while increasing the number of identified proteins in DIA-MS independent of the search space. We demonstrate how GPS can generalize to new data, increase protein identification rates, and increase the overall quantitative accuracy. Finally, we apply GPS to the identification of blood-based biomarkers and identify a panel of proteins that are highly accurate in discriminating between subphenotypes of septic acute kidney injury from undepleted plasma to showcase the utility of GPS in discovery DIA-MS proteomics.

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 remain unclear. This knowledge gap has resulted in ineffective biomarker development and suboptimal treatment regimens to prevent and manage organ dysfunction/damage. Here, we used pharmacoproteomics to score time-dependent treatment impact in a murine Escherichia coli sepsis model after administering beta-lactam antibiotic meropenem (Mem) and/or the immunomodulatory glucocorticoid methylprednisolone (Gcc). Three distinct proteome response patterns were identified, which depended on the underlying proteotype for each organ. Gcc enhanced some positive proteome responses of Mem, including superior reduction of the inflammatory response in kidneys and partial restoration of sepsis-induced metabolic dysfunction. Mem introduced sepsis-independent perturbations in the mitochondrial proteome that Gcc counteracted. We provide a strategy for the quantitative and organotypic assessment of treatment effects of candidate therapies in relationship to dosing, timing, and potential synergistic intervention combinations during sepsis.

Alveolar epithelial cells are competent producers of interstitial extracellular matrix with disease relevant plasticity in a human in vitro 3D model.

Alveolar epithelial cells (AEC) have been implicated in pathological remodelling. We examined the capacity of AEC to produce extracellular matrix (ECM) and thereby directly contribute towards remodelling in chronic lung diseases. Cryopreserved type 2 AEC (AEC2) from healthy lungs and chronic obstructive pulmonary disease (COPD) afflicted lungs were cultured in decellularized healthy human lung slices for 13 days. Healthy-derived AEC2 were treated with transforming growth factor ß1 (TGF-ß1) to evaluate the plasticity of their ECM production. Evaluation of phenotypic markers and expression of matrisome genes and proteins were evaluated by RNA-sequencing, mass spectrometry and immunohistochemistry. The AEC2 displayed an AEC marker profile similar to freshly isolated AEC2 throughout the 13-day culture period. COPD-derived AECs proliferated as healthy AECs with few differences in gene and protein expression while retaining increased expression of disease marker HLA-A. The AEC2 expressed basement membrane components and a complex set of interstitial ECM proteins. TGF-ß1 stimuli induced a significant change in interstitial ECM production from AEC2 without loss of specific AEC marker expression. This study reveals a previously unexplored potential of AEC to directly contribute to ECM turnover by producing interstitial ECM proteins, motivating a re-evaluation of the role of AEC2 in pathological lung remodelling.

Phenotypic Characterization of Acoustically Enriched Extracellular Vesicles from Pathogen-Activated Platelets.

Extracellular vesicles (EVs) are derived from the membrane of platelets and released into the circulation upon activation or injury. Analogous to the parent cell, platelet-derived EVs play an important role in hemostasis and immune responses by transfer of bioactive cargo from the parent cells. Platelet activation and release of EVs increase in several pathological inflammatory diseases, such as sepsis. We have previously reported that the M1 protein released from the bacterial pathogen Streptococcus pyogenes directly mediates platelet activation. In this study, EVs were isolated from these pathogen-activated platelets using acoustic trapping, and their inflammation phenotype was characterized using quantitative mass spectrometry-based proteomics and cell-based models of inflammation. We determined that M1 protein mediated release of platelet-derived EVs that contained the M1 protein. The isolated EVs derived from pathogen-activated platelets contained a similar protein cargo to those from physiologically activated platelets (thrombin) and included platelet membrane proteins, granule proteins, cytoskeletal proteins, coagulation factors, and immune mediators. Immunomodulatory cargo, complement proteins, and IgG3 were significantly enriched in EVs isolated from M1 protein-stimulated platelets. Acoustically enriched EVs were functionally intact and exhibited pro-inflammatory effects on addition to blood, including platelet-neutrophil complex formation, neutrophil activation, and cytokine release. Collectively, our findings reveal novel aspects of pathogen-mediated platelet activation during invasive streptococcal infection.

In Vivo Profiling of the Vascular Cell Surface Proteome in Murine Models of Bacteremia.

Vascular dysfunction is a hallmark of systemic inflammatory responses such as bacterial sepsis. The luminal surface of the blood vessels is coated with a dense layer of glycans and proteoglycans, collectively known as the glycocalyx. Surface associated glycoproteins of endothelial origin, or derived from pericytes, intravascular leukocytes, and plasma, are other important components of the glycocalyx, constituting a vascular cell surface proteome that is dynamic, tissue-specific, and sensitive to changes in vascular homeostasis, blood infection, and inflammation. Here, we describe an experimental protocol to chemically tag and quantify the vascular cell surface proteome in murine models of bacteremia, in a time-resolved and organ-specific manner. This method facilitates the identification of markers of vascular activation and provides a molecular framework to understand the contribution of vascular dysfunction to the organ pathology of systemic inflammation.

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 systemcally 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 set's 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). MEMs 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 MEMs' proven improvements to de novo analysis will positively impact several applications, such as analyzing samples of high complexity, unknown nature, or the peptidomics field.

A human monoclonal antibody bivalently binding two different epitopes in streptococcal M protein mediates immune function.

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 cannot bypass the M protein's 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, regions for protective antibody targeting.

Invasive Streptococcal Infection Can Lead to the Generation of Cross-Strain Opsonic Antibodies.

The 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. Four patients with S. pyogenes bacteremia between 2018 and 2020 at Skåne University Hospital in Lund, Sweden, were prospectively enrolled. Acute- and convalescent-phase sera were obtained, and the S. pyogenes isolates were genome sequenced (emm118, emm85, and two emm1 isolates). Quantitative antibody binding and phagocytosis assays were used to evaluate isolate-dependent opsonic antibody function in response to infection. Antibody binding increased modestly against the infecting isolate and across emm types in convalescent- compared to acute-phase sera for all patients. For two patients, phagocytosis increased in convalescent-phase serum both for 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. Invasive S. pyogenes infections result in a modestly increased antibody binding with differential opsonic capacity, both nonfunctional 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. IMPORTANCE The bacterium Streptococcus pyogenes is a common cause of both mild and severe human diseases resulting in substantial morbidity and mortality each year. No vaccines are available, and our understanding of the antibody response to this human pathogen is still incomplete. Here, we carefully analyzed the opsonic antibody response following invasive infection in four patients. Unexpectedly, the patients did not always generate opsonic antibodies against the specific infecting strain. Instead, we found that some patients could generate cross-opsonic antibodies, leading to phagocytosis of bacteria across strains. The emergence of cross-opsonic antibodies is likely important for long-term immunity against S. pyogenes. Our findings question the dogma that mostly strain-specific immunity is developed after infection and add to our overall understanding of how immunity to S. pyogenes can evolve.

Vascular Proteome Responses Precede Organ Dysfunction in a Murine Model of Staphylococcus aureus Bacteremia.

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 cross talk 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 Staphylococcus aureus sepsis by combining in vivo labeling of the endothelial cell surface 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. These responses include abundant vascular shedding, dysregulation of the intrinsic pathway of coagulation, compartmentalization of the acute phase response, and abundant upregulation of glycocalyx components. Vascular cell surface proteome changes were also 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 suggest a potential role for the vascular proteome as a determinant of the susceptibility of the organs to undergo failure during sepsis. IMPORTANCE Sepsis is a life-threatening response to infection that results in immune dysregulation, vascular dysfunction, and organ failure. New methods are needed for the identification of diagnostic and therapeutic targets. Here, we took a systems-wide approach using data-independent acquisition (DIA) mass spectrometry to track the progression of bacterial sepsis in the vasculature leading to organ failure. Using a murine model of S. aureus sepsis, we were able to quantify thousands of proteins across the plasma and parenchymal and vascular compartments of multiple organs in a time-resolved fashion. We showcase the profound proteome remodeling triggered by sepsis over time and across these compartments. Importantly, many vascular proteome alterations precede changes in traditional correlates of organ dysfunction, opening a molecular window for the discovery of early markers of sepsis progression.

Interaction of Bartonella henselae with Fibronectin Represents the Molecular Basis for Adhesion to Host Cells.

Bacterial adhesion to the host is the most decisive step in infections. Trimeric autotransporter adhesins (TAA) are important pathogenicity factors of Gram-negative bacteria. The prototypic TAA Bartonella adhesin A (BadA) from human-pathogenic Bartonella henselae mediates bacterial adherence to endothelial cells (ECs) and extracellular matrix proteins. Here, we determined the interaction between BadA and fibronectin (Fn) to be essential for bacterial host cell adhesion. BadA interactions occur within the heparin-binding domains of Fn. The exact binding sites were revealed by mass spectrometry analysis of chemically cross-linked whole-cell bacteria and Fn. Specific BadA interactions with defined Fn regions represent the molecular basis for bacterial adhesion to ECs and these data were confirmed by BadA-deficient bacteria and CRISPR-Cas knockout Fn host cells. Interactions between TAAs and the extracellular matrix might represent the key step for adherence of human-pathogenic Gram-negative bacteria to the host. IMPORTANCE Deciphering the mechanisms of bacterial host cell adhesion is a clue for preventing infections. We describe the underestimated role that the extracellular matrix protein fibronectin plays in the adhesion of human-pathogenic Bartonella henselae to host cells. Fibronectin-binding is mediated by a trimeric autotransporter adhesin (TAA) also present in many other human-pathogenic Gram-negative bacteria. We demonstrate that both TAA and host-fibronectin contribute significantly to bacterial adhesion, and we present the exact sequence of interacting amino acids from both proteins. Our work shows the domain-specific pattern of interaction between the TAA and fibronectin to adhere to host cells and opens the perspective to fight bacterial infections by inhibiting bacterial adhesion which represents generally the first step in infections.

Long-Read Sequencing Reveals Genetic Adaptation of Bartonella Adhesin A Among Different Bartonella henselae Isolates.

Bartonella henselae is the causative agent of cat scratch disease and other clinical entities such as endocarditis and bacillary angiomatosis. The life cycle of this pathogen, with alternating host conditions, drives evolutionary and host-specific adaptations. Human, feline, and laboratory adapted B. henselae isolates often display genomic and phenotypic differences that are related to the expression of outer membrane proteins, for example the Bartonella adhesin A (BadA). This modularly-structured trimeric autotransporter adhesin is a major virulence factor of B. henselae and is crucial for the initial binding to the host via the extracellular matrix proteins fibronectin and collagen. By using next-generation long-read sequencing we demonstrate a conserved genome among eight B. henselae isolates and identify a variable genomic badA island with a diversified and highly repetitive badA gene flanked by badA pseudogenes. Two of the eight tested B. henselae strains lack BadA expression because of frameshift mutations. We suggest that active recombination mechanisms, possibly via phase variation (i.e., slipped-strand mispairing and site-specific recombination) within the repetitive badA island facilitate reshuffling of homologous domain arrays. The resulting variations among the different BadA proteins might contribute to host immune evasion and enhance long-term and efficient colonisation in the differing host environments. Considering the role of BadA as a key virulence factor, it remains important to check consistently and regularly for BadA surface expression during experimental infection procedures.