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Segeren, L.

Publications and source records attributed to Segeren, L..

2 recordsLinked to original sources

Spatiotemporal dynamics of cryptococcal infection reveal novel immune modulatory mechanisms and antifungal targets

The threat and incidence of fungal diseases are increasing, as is the severity and mortality rates associated with these infections. New strategies to combat fungal infections are urgently needed to overcome rising rates of resistance and the emergence of new pathogens. To promote invasion within a host, fungi use highly adapted and regulated virulence factors, and, in turn, the host adopts an active and dynamic immune response to suppress infection. Understanding the interplay between these processes is crucial to move fungal disease management and treatment forward and improve global health outcomes. Within the present study, we tackle these challenges using state-of-the-art mass spectrometry instrumentation to explore proteome remodeling during active infection of Cryptococcus neoformans at an unprecedented depth with spatiotemporal resolution. Our prioritization of three host organs (i.e., lungs, brain, spleen) critical to initiation, progression, and response of disease discovers tissue-specific remodeling across time. Within the lungs, we revealed early and sustained activation of the host immune response integrated with characterization of a promising new antifungal target, and we propose the discovery of a competitive inhibitor for functional target disruption. Within the brain, proteome remodeling aligns with disease progression, and we define a new mechanistic role for haptoglobin in fungal cell modulation, as well as showcasing an adaptive survival response of C. neoformans within an hypoxic environment. Within the spleen, we reveal new dynamics of immune system activation upon cryptococcal infection. Overall, we provide the deepest integrated view of cryptococcal disease dynamics across temporal and spatial scales, revealing unrecognized mechanisms of host immunity and fungal pathogenesis that offer new avenues for targeted therapeutic intervention and disease management.

microbiology↗

Whole blood proteome dynamics defines predictive diagnostic and prognostic signatures of cryptococcal infection

Across the globe, fungi are impacting the lives of millions of people through the development of infections ranging from superficial to systemic with limited treatment options. To effectively combat fungal disease, rapid and reliable diagnostic methods are required, including current methodologies using antigen detection, culturing, microscopy, and molecular tools. However, the flexibility of these platforms to diagnose infection using non-invasive methods and predict the outcome of disease are limited. In this study, we apply state-of-the-art mass spectrometry-based proteomics to perform dual perspective (i.e., host and pathogen) profiling of cryptococcal infection. Whole blood collected over a temporal scale following murine model challenged with the human fungal pathogen, Cryptococcus neoformans, detected >3,000 host proteins and 160 fungal proteins. From the host perspective, temporal regulation of known immune-associated proteins, including eosinophil peroxidase and lipocalin-2, along with suppression of lipoproteins, demonstrated infection- and time-dependent host remodeling. Conversely, from the pathogen perspective, known and putative virulence-associated proteins were detected, including proteins associated with fungal extracellular vesicles and host immune modulation. We also observed and validated a new mechanism of immune system response to C. neoformans through modulation of haptoglobin. Further, we assessed the predictive power of dual perspective proteome profiling toward prognostics of cryptococcal infection and report a previously undisclosed integration among virulence factor production, immune system modulation, and individual model survival. Together, our findings pose novel biomarkers of cryptococcal infection from whole blood and highlight the potential of personal proteome profiles to determine the prognosis of cryptococcal infection, a new parameter in fungal disease management.

microbiology↗