quantification-insoluble-protein-aggregation-caenorhabditis-elegans

Quantification of Insoluble Protein Aggregation in <em>Caenorhabditis elegans</em> during Aging with a Novel Data-Independent Acquisition Workflow

We and others have shown that the aging process results in a proteome-wide accumulation of insoluble proteins. Knocking down genes encoding the insoluble ...

Buck Institute for Research on Aging

Loss of germline precursor cells in C. elegans has previously been shown to improve protein homeostasis and extend lifespan, possibly due to reallocation of resources to somatic cells. In contrast, mutants that are sterile simply due to loss of sperm or oocyte production have a normal lifespan, often leading to the conclusion that loss of reproduction per se may have minor effects on C. elegans. We have found that inhibiting reproduction in C. elegans via the DNA synthesis inhibitor 5-fluoro-2-deoxyuridine (FUdR) improves protein homeostasis, stress resistance, and healthspan in wild-type animals. We find that FUdR is dependent on oogenesis and oocytic maturation. The effects of FUdR are dependent on FEM pathways, which regulate initiation of spermatogenesis. Loss of FEM expression leads to feminized animals that maintain arrested oocytes and are refractory to the effects of FUdR. FUdR-dependence is restored by spermatogenic signals, which trigger oocytic maturation and ovulation. Further, loss of FEM-3, a novel protein required for spermatogenesis, is sufficient to improve aspects of proteostasis. These effects are independent of previously described germline signals, including the DAF-16/FOXO, DAF-12/VDR, and HSF-1 pathways. These findings suggest that genetic or chemical inhibition of oocyte production can improve protein homeostasis in C. elegans. 

A DNA synthesis inhibitor is protective against proteotoxic stressors via modulation of fertility pathways in Caenorhabditis elegans.

One major hurdle to the development of effective treatments to many diseases is the lack of suitable human model systems. The ability to reprogram human somatic cells to induced pluripotent stem cells (iPSC) offers an excellent opportunity to generate human disease models with primary cells. Currently, several methods to generate iPSC lines exist, and iPSC can be generated from various tissue sources including skin fibroblasts, blood, hair follicles, dental tissue, and urine. In this chapter we describe the generation and characterization of iPSC from blood or fibroblast on a routine base and focus on the integration-free methodologies. 

Generation and Characterization of Patient-Specific Induced Pluripotent Stem Cell for Disease Modeling.

We report generation of induced pluripotent stem cell (iPSC) lines from ten Parkinson's disease (PD) patients carrying SNCA, PARK2, LRRK2, and GBA mutations, and one age-matched control. After validation of pluripotency, long-term genome stability, and integration-free reprogramming, eight of these lines (one of each SNCA, LRRK2 and GBA, four PARK2 lines, and the control) were differentiated into neural stem cells (NSC) and subsequently to dopaminergic cultures. We did not observe significant differences in the timeline of neural induction and NSC derivation between the patient and control line, nor amongst the patient lines, although we report considerable variability in the efficiency of dopaminergic differentiation among patient lines. We performed whole genome expression analyses of the lines at each stage of differentiation (fibroblast, iPSC, NSC, and dopaminergic culture) in an attempt to identify alterations by large-scale evaluation. While gene expression profiling clearly distinguished cells at different stages of differentiation, no mutation-specific clustering or difference was observed, though consistent changes in patient lines were detected in genes associated mitochondrial biology. We further examined gene expression in a stress model (MPTP-induced dopaminergic neuronal death) using two clones from the SNCA triplication line, and detected changes in genes associated with mitophagy. Our data suggested that even a well-characterized line of a monogenic disease may not be sufficient to determine the cause or mechanism of the disease, and highlights the need to use more focused strategies for large-scale data analysis.

Derivation, Characterization, and Neural Differentiation of Integration-Free Induced Pluripotent Stem Cell Lines from Parkinson's Disease Patients Carrying SNCA, LRRK2, PARK2, and GBA Mutations.

Renuka Sivapatham

Buck Institute for Research on Aging

Quantification of Insoluble Protein Aggregation in Caenorhabditis elegans during Aging with a Novel Data-Independent Acquisition Workflow