Regionally defined proteomic profiles of human cerebral tissue and organoids reveal conserved molecular modules of neurodevelopment.

Cerebral organoids have emerged as robust models for neurodevelopmental and pathological processes, as well as a powerful discovery platform for less-characterized neurobiological programs. Toward this prospect, we leverage mass-spectrometry-based proteomics to molecularly profile precursor and neuronal compartments of both human-derived organoids and mid-gestation fetal brain tissue to define overlapping programs. Our analysis includes recovery of precursor-enriched transcriptional regulatory proteins not found to be differentially expressed in previous transcriptomic datasets. To highlight the discovery potential of this resource, we show that RUVBL2 is preferentially expressed in the SOX2-positive compartment of organoids and that chemical inactivation leads to precursor cell displacement and apoptosis. To explore clinicopathological correlates of this cytoarchitectural disruption, we interrogate clinical datasets and identify rare de novo genetic variants involving RUVBL2 in patients with neurodevelopmental impairments. Together, our findings demonstrate how cell-type-specific profiling of organoids can help nominate previously unappreciated genes in neurodevelopment and disease.

The promise of organoids for unraveling the proteomic landscape of the developing human brain.

Cerebral organoids offer an opportunity to bioengineer experimental avatars of the developing human brain and have already begun garnering relevant insights into complex neurobiological processes and disease. Thus far, investigations into their heterogeneous cellular composition and developmental trajectories have been largely limited to transcriptional readouts. Recent advances in global proteomic technologies have enabled a new range of techniques to explore dynamic and non-overlapping spatiotemporal protein-level programs operational in these humanoid neural structures. Here we discuss these early protein-based studies and their potentially essential role for unraveling critical secreted paracrine signals, processes with poor proteogenomic correlations, or neurodevelopmental proteins requiring post-translational modification for biological activity. Integrating emerging proteomic tools with these faithful human-derived neurodevelopmental models could transform our understanding of complex neural cell phenotypes and neurobiological processes, not exclusively driven by transcriptional regulation. These insights, less accessible by exclusive RNA-based approaches, could reveal new knowledge into human brain development and guide improvements in neural regenerative medicine efforts.

Cerebral organoids: emerging ex vivo humanoid models of glioblastoma.

Glioblastoma is an aggressive form of brain cancer that has seen only marginal improvements in its bleak survival outlook of 12-15 months over the last forty years. There is therefore an urgent need for the development of advanced drug screening platforms and systems that can better recapitulate glioblastoma's infiltrative biology, a process largely responsible for its relentless propensity for recurrence and progression. Recent advances in stem cell biology have allowed the generation of artificial tridimensional brain-like tissue termed cerebral organoids. In addition to their potential to model brain development, these reagents are providing much needed synthetic humanoid scaffolds to model glioblastoma's infiltrative capacity in a faithful and scalable manner. Here, we highlight and review the early breakthroughs in this growing field and discuss its potential future role for glioblastoma research.

Urine protein profiling with surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry.

BACKGROUND: In the last few years there has been an increasing interest in exploring the human proteome. In particular, efforts have focused on developing strategies to generate reproducible protein maps of normal cells, tissues, and biologic fluids, from which studies can then compare protein expression between different groups (e.g., healthy individuals vs. those with a specific pathologic state). METHODS: Various extrinsic factors (instrument settings, matrix composition, urine storage post void, freeze-thaw cycles) and intrinsic factors (blood in urine, urine dilution, first-void vs. midstream urine) were analyzed with respect to their impact on urine protein profiling using surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). RESULTS: Extrinsic factors that critically influenced reproducibility and peak detection of urine protein profiling were matrix composition and instrument settings, while freeze-thaw cycles had minimal impact. Midstream urines samples did not undergo changes in their protein profile when stored for three days at 4 degrees C. Intrinsic factors that influenced normal urine protein profiling were blood in the urine and urine dilution. Female first-void urine had a significantly different ratio of proteins present compared to a midstream urine sample. Limitations of the SELDI-TOF-MS technique included ion suppression and quantification of individual proteins when protein composition was complex. CONCLUSION: SELDI-TOF-MS offers a unique platform for high throughput urine protein profiling; however, standardization of analysis conditions is critical, and both extrinsic and intrinsic factors must be taken into account for accurate data interpretation.

Proteomic-based detection of urine proteins associated with acute renal allograft rejection.

At present, the diagnosis of renal allograft rejection requires a renal biopsy. Clinical management of renal transplant patients would be improved by the development of non-invasive markers of rejection that can be measured frequently. This study sought to determine whether such candidate proteins can be detected in urine using mass spectrometry. Four patient groups were rigidly defined on the basis of allograft function, clinical course, and allograft biopsy result: acute clinical rejection group (n = 18), stable transplant group (n = 22), acute tubular necrosis group (n = 5), and recurrent (or de novo) glomerulopathy group (n = 5). Urines collected the day of the allograft biopsy were analyzed by mass spectrometry. As a normal control group, 28 urines from healthy individuals were analyzed the identical manner, as well as 5 urines from non-transplanted patients with lower urinary tract infection. Furthermore, sequential urine analysis was performed in patients in the acute clinical rejection and the stable transplant group. Three prominent peak clusters were found in 17 of 18 patients (94%) with acute rejection episodes, but only in 4 of 22 patients (18%) without clinical and histologic evidence for rejection and in 0 of 28 normal controls (P < 0.001). In addition, the presence or absence of these peak clusters correlated with the clinicopathologic course in most patients. Acute tubular necrosis, glomerulopathies, lower urinary tract infection, and cytomegalovirus viremia were not confounding variables. In conclusion, proteomic technology together with stringent definition of patient groups can detect urine proteins associated with acute renal allograft rejection. Identification of these proteins may prove useful as non-invasive diagnostic markers for rejection and the development of novel therapeutic agents.