Group A Streptococcal S Protein Utilizes Red Blood Cells as Immune Camouflage and Is a Critical Determinant for Immune Evasion.

Group A Streptococcus (GAS) is a human-specific pathogen that evades the host immune response through the elaboration of multiple virulence factors. Although many of these factors have been studied, numerous proteins encoded by the GAS genome are of unknown function. Herein, we characterize a biomimetic red blood cell (RBC)-captured protein of unknown function-annotated subsequently as S protein-in GAS pathophysiology. S protein maintains the hydrophobic properties of GAS, and its absence reduces survival in human blood. S protein facilitates GAS coating with lysed RBCs to promote molecular mimicry, which increases virulence in vitro and in vivo. Proteomic profiling reveals that the removal of S protein from GAS alters cellular and extracellular protein landscapes and is accompanied by a decrease in the abundance of several key GAS virulence determinants. In vivo, the absence of S protein results in a striking attenuation of virulence and promotes a robust immune response and immunological memory

Amplification of Inflammation by Lubricin Deficiency Implicated in Incident, Erosive Gout Independent of Hyperuricemia

Objective In gout, hyperuricemia promotes urate crystal deposition that stimulates the NLRP3 inflammasome and IL-1β-mediated arthritis. Incident gout without background hyperuricemia is rarely reported. To identify hyperuricemia-independent mechanisms driving gout incidence and progression, we characterized erosive urate crystalline inflammatory arthritis meeting ACR/EULAR gout classification criteria in a normouricemic young adult female. Methods Whole genome sequencing, quantitative proteomics, whole blood RNA-seq, and IL-1β-induced murine knee synovitis characterized proband candidate genes, biomarkers, and pathogenic mechanisms. Results Lubricin was attenuated in proband serum, associated with elevated acute phase reactants and inflammatory whole blood transcripts and transcriptional pathways. The proband had predicted damaging gene variants of NLRP3 and of Inter-Alpha-Trypsin Inhibitor Heavy Chain 3, an inhibitor of lubricin-degrading Cathepsin G. Proband serum protein interactome network changes supported enhanced lubricin degradation, with Cathepsin G activity increased relative to its inhibitors SERPINB6 and Thrombospondin1. TLR2 activation suppressed cultured human synovial fibroblast lubricin mRNA and release (p\u3c0.01). Lubricin blunted urate crystal precipitation, and IL-1β induction of xanthine oxidase and urate in cultured macrophages (p\u3c0.001). In lubricin-deficient mice, IL-1β knee injection increased xanthine oxidase positive synovial resident M1 macrophages (p\u3c0.05). Conclusion We linked normouricemic erosive gout to attenuated lubricin, with impaired control of Cathepsin G activity, compounded by deleterious NLRP3 variants. Lubricin suppressed monosodium urate crystallization, and blunted IL-1β-induced increases in macrophage xanthine oxidase and urate. Collective activities of articular lubricin that could limit incident and erosive gouty arthritis independently of hyperuricemia are subject to disruption by inflammation, activated Cathepsin G, and synovial fibroblast TLR2 signaling

Master Manipulators: Using Proteomics to Understand how Streptococcal Biochemistry Conspires Against Host Defenses

We live in a world dominated by the microbes that have made their homes in and around us since the beginnings of human life. A major advancement in our understanding of the role microbes play in our lives came about in the recognition that many diseases are caused by microorganisms that have found ways to occupy our bodies. A still larger advancement was the realization that bacteria produce molecules that modulate host defenses in broad and targeted ways. Advances in our understanding of the host-pathogen relationship at the molecular level have relied on methods that evaluate one or a few molecules at a time. However, recent developments in unbiased -omics technologies are highly suited to studying the vast arsenal of molecules that bacteria use to subvert host defenses. This work describes one such -omics strategy for the discovery of novel bacterial virulence factors, termed Biomimetic Virulomics (BV). In chapter 1, I describe the impact of technological improvements in delineating the function of previously undescribed virulence factors on human health. I describe the results of a BV experiment oriented at discovering novel red blood cell-targeted virulence factors in the important human pathogen, Streptococcus pyogenes, also known as Group A Streptococcus (GAS). In chapter 2, I present an initial characterization of one of the GAS virulence factors discovered through this method, S protein, a previously-overlooked GAS virulence factor. In chapter 3, I expand on the initial description of S protein into the realm of vaccine development, finding that recombinant S protein is robustly protective against localized GAS skin infections. In chapter 4, I describe an S protein homolog in another important human pathogen and cause of neonatal morbidity, Group B Streptococcus (GBS). I find that as in GAS, GBS S protein is critical for bacterial pathogenesis. In chapter 5, I use quantitative proteomics paired with tissue-type specific isolation methods to describe the effect of another important GBS virulence factor, iagA, on manipulating the blood-brain barrier during meningitis. Finally, in chapter 6, I present the future plan and broader implications for the work encompassed in this thesis as a grant application

Master Manipulators: Using Proteomics to Understand how Streptococcal Biochemistry Conspires Against Host Defenses

We live in a world dominated by the microbes that have made their homes in and around us since the beginnings of human life. A major advancement in our understanding of the role microbes play in our lives came about in the recognition that many diseases are caused by microorganisms that have found ways to occupy our bodies. A still larger advancement was the realization that bacteria produce molecules that modulate host defenses in broad and targeted ways. Advances in our understanding of the host-pathogen relationship at the molecular level have relied on methods that evaluate one or a few molecules at a time. However, recent developments in unbiased -omics technologies are highly suited to studying the vast arsenal of molecules that bacteria use to subvert host defenses. This work describes one such -omics strategy for the discovery of novel bacterial virulence factors, termed Biomimetic Virulomics (BV). In chapter 1, I describe the impact of technological improvements in delineating the function of previously undescribed virulence factors on human health. I describe the results of a BV experiment oriented at discovering novel red blood cell-targeted virulence factors in the important human pathogen, Streptococcus pyogenes, also known as Group A Streptococcus (GAS). In chapter 2, I present an initial characterization of one of the GAS virulence factors discovered through this method, S protein, a previously-overlooked GAS virulence factor. In chapter 3, I expand on the initial description of S protein into the realm of vaccine development, finding that recombinant S protein is robustly protective against localized GAS skin infections. In chapter 4, I describe an S protein homolog in another important human pathogen and cause of neonatal morbidity, Group B Streptococcus (GBS). I find that as in GAS, GBS S protein is critical for bacterial pathogenesis. In chapter 5, I use quantitative proteomics paired with tissue-type specific isolation methods to describe the effect of another important GBS virulence factor, iagA, on manipulating the blood-brain barrier during meningitis. Finally, in chapter 6, I present the future plan and broader implications for the work encompassed in this thesis as a grant application

Proteome allocation is linked to transcriptional regulation through a modularized transcriptome.

It has proved challenging to quantitatively relate the proteome to the transcriptome on a per-gene basis. Recent advances in data analytics have enabled a biologically meaningful modularization of the bacterial transcriptome. We thus investigate whether matched datasets of transcriptomes and proteomes from bacteria under diverse conditions can be modularized in the same way to reveal novel relationships between their compositions. We find that; (1) the modules of the proteome and the transcriptome are comprised of a similar list of gene products, (2) the modules in the proteome often represent combinations of modules from the transcriptome, (3) known transcriptional and post-translational regulation is reflected in differences between two sets of modules, allowing for knowledge-mapping when interpreting module functions, and (4) through statistical modeling, absolute proteome allocation can be inferred from the transcriptome alone. Quantitative and knowledge-based relationships can thus be found at the genome-scale between the proteome and transcriptome in bacteria

Organ-level protein networks as a reference for the host effects of the microbiome.

Connections between the microbiome and health are rapidly emerging in a wide range of diseases. However, a detailed mechanistic understanding of how different microbial communities are influencing their hosts is often lacking. One method researchers have used to understand these effects are germ-free (GF) mouse models. Differences found within the organ systems of these model organisms may highlight generalizable mechanisms that microbiome dysbioses have throughout the host. Here, we applied multiplexed, quantitative proteomics on the brains, spleens, hearts, small intestines, and colons of conventionally raised and GF mice, identifying associations to colonization state in over 7000 proteins. Highly ranked associations were constructed into protein-protein interaction networks and visualized onto an interactive 3D mouse model for user-guided exploration. These results act as a resource for microbiome researchers hoping to identify host effects of microbiome colonization on a given organ of interest. Our results include validation of previously reported effects in xenobiotic metabolism, the innate immune system, and glutamate-associated proteins while simultaneously providing organism-wide context. We highlight organism-wide differences in mitochondrial proteins including consistent increases in NNT, a mitochondrial protein with essential roles in influencing levels of NADH and NADPH, in all analyzed organs of conventional mice. Our networks also reveal new associations for further exploration, including protease responses in the spleen, high-density lipoproteins in the heart, and glutamatergic signaling in the brain. In total, our study provides a resource for microbiome researchers through detailed tables and visualization of the protein-level effects of microbial colonization on several organ systems

Kinetic profiling of metabolic specialists demonstrates stability and consistency of in vivo enzyme turnover numbers

Enzyme turnover numbers (k cats) are essential for a quantitative understanding of cells. Because k cats are traditionally measured in low-throughput assays, they can be inconsistent, labor-intensive to obtain, and can miss in vivo effects. We use a data-driven approach to estimate in vivo k cats using metabolic specialist Escherichia coli strains that resulted from gene knockouts in central metabolism followed by metabolic optimization via laboratory evolution. By combining absolute proteomics with fluxomics data, we find that in vivo k cats are robust against genetic perturbations, suggesting that metabolic adaptation to gene loss is mostly achieved through other mechanisms, like gene-regulatory changes. Combining machine learning and genome-scale metabolic models, we show that the obtained in vivo k cats predict unseen proteomics data with much higher precision than in vitro k cats. The results demonstrate that in vivo k cats can solve the problem of inconsistent and low-coverage parameterizations of genome-scale cellular models

PEAK1 Acts as a Molecular Switch to Regulate Context-Dependent TGFβ Responses in Breast Cancer

<div><p>Transforming Growth Factor β (TGFβ) has dual functions as both a tumor suppressor and a promoter of cancer progression within the tumor microenvironment, but the molecular mechanisms by which TGFβ signaling switches between these outcomes and the contexts in which this switch occurs remain to be fully elucidated. We previously identified PEAK1 as a new non-receptor tyrosine kinase that associates with the cytoskeleton, and facilitates signaling of HER2/Src complexes. We also showed PEAK1 functions downstream of KRas to promote tumor growth, metastasis and therapy resistance using preclinical <i>in vivo</i> models of human tumor progression. In the current study, we analyzed PEAK1 expression in human breast cancer samples and found PEAK1 levels correlate with mesenchymal gene expression, poor cellular differentiation and disease relapse. At the cellular level, we also observed that PEAK1 expression was highest in mesenchymal breast cancer cells, correlated with migration potential and increased in response to TGFβ-induced epithelial-mesenchymal transition (EMT). Thus, we sought to evaluate the role of PEAK1 in the switching of TGFβ from a tumor suppressing to tumor promoting factor. Notably, we discovered that high PEAK1 expression causes TGFβ to lose its anti-proliferative effects, and potentiates TGFβ-induced proliferation, EMT, cell migration and tumor metastasis in a fibronectin-dependent fashion. In the presence of fibronectin, PEAK1 caused a switching of TGFβ signaling from its canonical Smad2/3 pathway to non-canonical Src and MAPK signaling. This report is the first to provide evidence that PEAK1 mediates signaling cross talk between TGFβ receptors and integrin/Src/MAPK pathways and that PEAK1 is an important molecular regulator of TGFβ-induced tumor progression and metastasis in breast cancer. Finally, PEAK1 overexpression/upregulation cooperates with TGFβ to reduce breast cancer sensitivity to Src kinase inhibition. These findings provide a rational basis to develop therapeutic agents to target PEAK1 expression/function or upstream/downstream pathways to abrogate breast cancer progression.</p></div