13 research outputs found
Dense-core granules: a specific hallmark of the neuronal/neurosecretory cell phenotype.
Expression of dense-core granules, a typical exocytic organelle, is widely believed to be controlled by coordinate gene expression mechanisms specific to neurones and neurosecretory cells. Recent studies in PC12 cells, however, have suggested the number of granules/cells depends on the levels of only one of their cargo proteins, chromogranin A, regulating the metabolism of the other proteins, and thus the composition of the organelles, by an on/off switch mechanism. In addition, transfection of chromogranin A was reported to induce appearance of dense-core granules in the non-neurosecretory fibroblasts of the CV-1 line. Here the role of chromogranin A has been reinvestigated using not the heterogeneous PC12 line but several clones isolated therefrom. In these clones, investigated as such or after transfection with chromogranin A antisense sequences, the ratio between chromogranin A and its secretory protein mate, chromogranin B, was not constant but highly and apparently randomly variable. Variability of the chromogranin A/chromogranin B ratio was seen by confocal immunofluorescence also among the cells of single clones and subclones and among the granules of single cells. Moreover, stable and transient transfections of chromogranin A in a PC12 clone characterised by a low number of dense-core granules (one fifth of the reference clone) failed to modify significantly the number of the organelles, despite the several-fold increase of the granin. Finally, in three types of non-neurosecretory cells (CV-1, adenocarcinoma TS/A and a clone of PC12 incompetent for secretion) the transfected chromogranin A accumulated mostly in the Golgi/transGolgi area and was released rapidly from resting cells (constitutive secretion) as revealed by both immunofluorescence during cycloheximide treatment and pulse-chase experiments. Only a minor fraction was sorted to discrete organelles that were not dense-core granules, but primarily lysosomes because they contained no chromogranin B, and were largely positive for the late endosomal-lysosomal markers, lamp1 and lamp3. Dense-core granules are therefore true hallmarks of neurones and neurosecretory cells. Their number/cell appears independent of chromogranin A and their composition does not appear to be constant; in particular, they exhibit considerable, and so far unexplained variability in the chromogranin A/chromogranin B ratio
Expression of the neurosecretory process in pc12 cells is governed by rest
The neurosecretory process is acquired during differentiation and can be lost en block by differentiated cells. To investigate the role of REST/NRSF, a transcription repressor, in the maintenance of the process we studied two PC12 clones, one wt and one defective, expressing low and high levels of endogenous RE-1 silencing transcription (factor) (REST), respectively. Stable transfection of constructs demonstrated that REST represses 10 genes coding for proteins of neurosecretory vesicles and their exocytosis, eight including and two lacking the REST-binding sequence, RE-1. Of these genes, those of chromogranins were strongly repressed by fewfold increases of REST, those of VAMP2 and syntaxin1a required much higher levels. Moreover, in wt cells transfected with an active construct the dense-core vesicles, still competent for regulated exocytosis, were much smaller, with lighter cores; in defective cells, the dominant-negative construct induced the rescue of many vesicle/exocytosis genes but not of those of chromogranins. Small dense-core vesicles, exocytized upon stimulation, were rescued when the construct-transfected defective cells were transfected also with chromograninA or treated with trichostatinA, a blocker of histone deacetylases. Our results identify REST, working by direct and indirect mechanisms, as the factor governing the maintenance of the neurosecretory process and the properties of dense-core vesicles in PC12 cells
Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA
Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis
Neurosecretion competence. A comprehensive gene expression program identified in PC12 cells
The phenotype of neurosecretory cells is characterized by clear vesicles and dense granules, both discharged by regulated exocytosis. However, these organelles are lacking completely in a few neurosecretion-incompetent clones of the pheochromocytoma PC12 line, in which other specific features are maintained (incompetent clones). In view of the heterogeneity of PC12 cells, a differential characterization of the incompetent phenotype based on the comparison of a single incompetent and a single wild-type clone would have been inconclusive. Therefore, we have compared two pairs of PC12 clones, studying in parallel the transcript levels of 4,200 genes and 19,000 express sequence tags (ESTs) by high density oligonucleotide arrays. After accurate data processing for quality control and filtration, a total of 755 transcripts, corresponding to 448 genes and 307 ESTs, was found consistently changed, with 46% up-regulated and 54% down-regulated in incompetent versus wild-type clones. Many but not all neurosecretion genes were profoundly down-regulated in incompetent cells. Expression of endocytosis genes was normal, whereas that of many nuclear and transcription factors, including some previously shown to play key roles in neurogenesis, was profoundly changed. Additional differences appeared in genes involved in signaling and metabolism. Taken together these results demonstrate for the first time that expression of neurosecretory vesicles and granules is part of a complex gene expression program that includes many other features that so far have not been recognized
Expression of the neurosecretory process in pc12 cells is governed by rest
The neurosecretory process is acquired during differentiation and can be lost en block by differentiated cells. To investigate the role of REST/NRSF, a transcription repressor, in the maintenance of the process we studied two PC12 clones, one wt and one defective, expressing low and high levels of endogenous RE-1 silencing transcription (factor) (REST), respectively. Stable transfection of constructs demonstrated that REST represses 10 genes coding for proteins of neurosecretory vesicles and their exocytosis, eight including and two lacking the REST-binding sequence, RE-1. Of these genes, those of chromogranins were strongly repressed by fewfold increases of REST, those of VAMP2 and syntaxin1a required much higher levels. Moreover, in wt cells transfected with an active construct the dense-core vesicles, still competent for regulated exocytosis, were much smaller, with lighter cores; in defective cells, the dominant-negative construct induced the rescue of many vesicle/exocytosis genes but not of those of chromogranins. Small dense-core vesicles, exocytized upon stimulation, were rescued when the construct-transfected defective cells were transfected also with chromograninA or treated with trichostatinA, a blocker of histone deacetylases. Our results identify REST, working by direct and indirect mechanisms, as the factor governing the maintenance of the neurosecretory process and the properties of dense-core vesicles in PC12 cells
Epigenomics of Neural Cells: REST-Induced Down- and Upregulation of Gene Expression in a Two-Clone PC12 Cell Model
Cell epigenomics depends on the marks released by transcription factors operating via the assembly of complexes that induce focal changes of DNA and histone structure. Among these factors is REST, a repressor that, via its strong decrease, governs both neuronal and neural cell differentiation and specificity. REST operation on thousands of possible genes can occur directly or via indirect mechanisms including repression of other factors. In previous studies of gene down- and upregulation, processes had been only partially investigated in neural cells. PC12 are well-known neural cells sharing properties with neurons. In the widely used PC12 populations, low-REST cells coexist with few, spontaneous high-REST PC12 cells. High- and low-REST PC12 clones were employed to investigate the role and the mechanisms of the repressor action. Among 15,500 expressed genes we identified 1,770 target and nontarget, REST-dependent genes. Functionally, these genes were found to operate in many pathways, from synaptic function to extracellular matrix. Mechanistically, downregulated genes were predominantly repressed directly by REST; upregulated genes were mostly governed indirectly. Among other factors, Polycomb complexes cooperated with REST for downregulation, and Smad3 and Myod1 participated in upregulation. In conclusion, we have highlighted that PC12 clones are a useful model to investigate REST, opening opportunities to development of epigenomic investigation
Monoclonal antibody 76F distinguishes IA-2 from IA-2β and overlaps an autoantibody epitope
IA-2 and IA-2β are highly related proteins that are autoantigens in type 1 diabetes, and provide a model for developing reagents and assays that distinguish similar proteins with unique autoantibody epitopes.
Monoclonal antibodies (mAb) to IA-2 and IA-2β were prepared and tested for their ability to bind to the related proteins and their ability to compete for specific autoantibody epitope binding by sera from patients with type 1 diabetes.
Monoclonal antibodies that specifically bound IA-2 (76F) or bound both IA-2 and IA-2β (A9) were isolated and characterized. 76F mAb recognized IA-2 of human, rat and mouse origin in native and denatured forms and had an epitope specificity for residues 626–630 (FEYQD) which are found in the juxtamembrane (JM) region of human and mouse IA-2, but not IA-2β. This region overlaps with the autoantibody epitope JM2. Binding to the 76F monoclonal antibody was specifically inhibited by sera with antibodies to the JM2 epitope but not with antibodies to the adjacent JM1 epitope, indicating that unique epitopes can be distinguished by this approach.
76F mAb has the unique property to distinguish between the two closely related autoantigens IA-2 and IA-2β by targeting an IA-2 specific epitope of the juxtamembrane region. The findings define an approach to develop assays for specific antibody epitope measurements which may be relevant for disease prognosis and monitoring intervention therapies
A multicenter prospective study validated a nomogram to predict individual risk of dependence in ambulation after rehabilitation
To develop the FRIDA (Functional Risk Index for Dependence in Ambulation) score, a nomogram to predict individual risk of dependence in ambulation at discharge (DAD) from post-acute rehabilitation and validate its performance temporally and spatially