Agenda

Radical Protein Footprinting (RPF) is a powerful tool to probe protein higher order structure. It is mostly performed in vitro, but recent advances have enabled its use in live cells, nematodes, and 3D cultures. However, application in living mammalian tissues has not been accomplished. Here, we present the first successful use of radical protein footprinting in mammalian whole blood from wildtype (WT) and a Cg Dock7m +/+ Leprdb/J age-matched type 2 diabetes mouse model (n=4 for each group). The diabetic mouse model showed significant weight gain and glucose elevation over WT controls.

Using 200 mM persulfate photoactivated with the FOX Photolysis System immediately after mixing with EDTA-stabilized whole blood, we achieved effective protein labeling without significant disruption to blood cell morphology as observed by both bright field microscopy and hemolysis assay. An optimized quenching protocol eliminated background labeling. A significant increase in labeling of extracellular proteins was achieved at room temperature compared to 0V controls, with intracellular labeling being much lower. We observed improved labeling of intracellular proteins at higher temperatures, indicating that labeling specificity can be somewhat controlled by labeling temperature. Targeted analysis of proteins was used to allow for more detailed HRPF information of the top 11 proteins detected. Multiple proteins in the top 11 were found to have disease-associated conformational changes. Among them, complement c3 showed conformational changes consistent with complement activation while serotransferrin showed conformational changes consistent with a higher amount of iron binding. These conformational changes were confirmed by orthogonal assays, and are consistent with previously published reports from type 2 diabetes models and patients, while giving additional information regarding specific changes in protein topography that occurs in these disease states. Work is ongoing to further automate this method for application to clinical samples, as well as adaptation to CSF and other clinical biofluids.

Pulmonary fibrosis encompasses a heterogeneous group of interstitial lung diseases, of which idiopathic pulmonary fibrosis (IPF) is the most common and deadly. Despite advances in antifibrotic therapy, outcomes remain poor and treatment selection remains empiric. Traditional radiographic and physiologic measures incompletely capture the biologic diversity of these patients, limiting our ability to tailor therapy.

Proteomics provides an opportunity to move beyond descriptive disease labels by identifying molecular endophenotypes—biologically distinct subgroups that transcend conventional clinical classifications. By profiling the bronchoalveolar lavage fluid and lung tissue proteome across IPF and autoimmune-associated ILD, we aim to define shared and divergent molecular programs driving fibrogenesis, inflammation, and immune dysregulation.

In this presentation, I will highlight recent work applying unbiased, high-resolution mass spectrometry to large, well-characterized ILD cohorts. Using clustering and systems biology approaches, we demonstrate reproducible molecular signatures associated with disease progression, treatment response, and survival. Specific proteomic endophenotypes suggest the presence of “hypoinflammatory” versus “immune-activated” fibrotic states, offering a framework for precision medicine approaches.

Ultimately, proteomics-derived molecular endophenotypes can refine prognosis, guide rational treatment selection, and identify novel therapeutic targets. By integrating these signatures with quantitative imaging, genomics, and clinical data, we move toward a biologically anchored taxonomy of pulmonary fibrosis that has direct translational relevance.

Accurate cellular differentiation relies on precise regulation of RNA processing and decay that coordinates transcript maturation and turnover across developmental transitions. RNA surveillance machinery safeguards the transcriptome to ensure these transitions proceed correctly. Although many RNA surveillance systems are ubiquitously expressed, their dysregulation often causes tissue-specific neuropathology. At the center of this control is the RNA exosome, an essential 3’-5’ ribonuclease complex implicated in stem cell differentiation. Recessive mutations in EXOSC3, a structural subunit gene of the RNA exosome complex, cause Pontocerebellar Hypoplasia Type 1b (PCH1b), a severe neurodevelopmental disorder characterized by degeneration of the pons and cerebellum. The role of RNA surveillance in human cerebellum development, and the specific contribution of EXOSC3, has remained unclear. Here, we establish a human in vitro model of PCH1b by CRISPR-editing human induced pluripotent stem cells (hiPSCs) to introduce patient-derived EXOSC3 alleles spanning mild and severe disease, and differentiated into cerebellar organoids in 3D culture. Immunofluorescence and single-cell transcriptomics benchmarked to the human fetal cerebellar atlas show that our organoids recapitulate the expected cell-state landscape and developmental gradients, thus providing a platform to study RNA exosome-linked cerebellar phenotypes. Our findings reveal that pathogenic EXOSC3 variants do not broadly collapse lineages; instead, the principal effect is selective: the Purkinje trajectory is perturbed. Cells initiate the Purkinje trajectory but fail to consolidate late maturation features, accumulating at intermediate states. These results are consistent with a maturation checkpoint on the Purkinje branch, while other lineages progress comparatively well. The magnitude and direction of these alterations track with allelic severity, consistent with a graded requirement for RNA exosome function during high-flux developmental transitions. Together, these findings define the RNA  exosome as a gatekeeper of Purkinje maturation, clarify the cellular basis of PCH1b, and establish a platform to study how RNA quality control shapes brain development and disease.

Across a series of proteomics-driven studies, the Le Roch Lab, in collaboration with the Florens Lab, has employed an integrated suite of mass spectrometry and complementary omics technologies to uncover how the human malaria parasite Plasmodium falciparum regulates its genes through chromatin, RNA, and protein-complex interactions.

Early work applied quantitative proteomics to chromatin to map the parasite’s histone modifications during the red blood cell cycle. Using multidimensional protein identification technology (MudPIT), the team discovered more than 200 distinct post-translational histone marks, many unique to Plasmodium that change dynamically with developmental stage. These findings revealed a distinctive and highly combinatorial “histone code” linking epigenetic state to transcription, DNA replication, and virulence regulation. Building on this work, the labs used chromatin enrichment for proteomics (ChEP) to identify proteins controlling epigenetic features during parasite development and to define the chromatin-bound proteome, revealing both conserved and parasite-specific chromatin regulators. Together, these results highlighted that chromatin organization and associated protein complexes are central to transcriptional control in P. falciparum. Subsequent proteome-wide studies expanded the focus from DNA- to RNA-level regulation, including the use of the R-DeeP sucrose-gradient mass spectrometry method to catalog nearly 900 RNA-dependent proteins. This analysis revealed that non-coding RNAs scaffold many of the parasite’s regulatory complexes, influencing not only chromatin structure and epigenetic regulation but also RNA processing and translation. Targeted functional proteomics of DNA-binding and RNA-binding protein families, notably the MORC and RAP proteins, connected specific factors to chromatin structure and organellar RNA processing in the mitochondrion and apicoplast, demonstrating how parasite-specific mechanisms of gene regulation contribute to survival.

Together, these proteomic frameworks illustrate how the Le Roch and Florens Labs have, across multiple studies, defined the complex interface between chromatin and RNA–protein interactions, uncovering the networks that govern gene expression in the malaria parasite, and providing new mechanistic insights and potential therapeutic targets.

Liver diagnostic assays in the clinic have changed little since the deployment of the liver enzyme panel in the 1960s. This is striking due to the large proteomic interplay between blood and the liver, with as much as 70% of blood plasma proteins originating, in some way, from the liver. Single cell proteomics (SCP) is a flashy new tool that can be used to obtain unprecedented depth and granularity in the phenotypes of biological systems. In this talk I will detail our lab's ongoing work to characterize wasted material from both liver donors and transplant recipients following surgeries at the Pittsburgh Liver Research Center. Human hepatocytes have proven remarkably compatible with SCP methods due to their relatively large size and suspiciously limited proteomic complexity on a cell-by-cell basis. At the point of writing this abstract we are routinely quantifying more than 3,000 protein groups from single human hepatocytes derived from patient samples at a throughput approaching 100 cells per instrument per day with label free methods.