Defective Human SRP Induces Protein Quality Control and Triggers Stress Response

Loss of Preproinsulin Interaction with Signal Recognition Particle Activates Protein Quality Control, Decreasing mRNA Stability

Many insulin gene variants alter the protein sequence and result in monogenic diabetes due to insulin insufficiency. However, the molecular mechanisms of various disease-causing mutations are unknown. Insulin is synthesized as preproinsulin containing a signal peptide (SP). SPs of secreted proteins are recognized by the signal recognition particle (SRP) or by another factor in a SRP-independent pathway. If preproinsulin uses SRP-dependent or independent pathways is still debatable. We demonstrate by the use of site-specific photocrosslinking that the SRP subunit, SRP54, interacts with the preproinsulin SP. Moreover, SRP54 depletion leads to the decrease of insulin mRNA and protein expression, supporting the involvement of the RAPP protein quality control in insulin biogenesis. RAPP regulates the quality of secretory proteins through degradation of their mRNA. We tested five disease-causing mutations in the preproinsulin SP on recognition by SRP and on their effects on mRNA and protein levels. We demonstrate that the effects of mutations are associated with their position in the SP and their severity. The data support diverse molecular mechanisms involved in the pathogenesis of these mutations. We show for the first time the involvement of the RAPP protein quality control pathway in insulin biogenesis that is implicated in the development of neonatal diabetes caused by the Leu13Arg mutation.

Pathogenic signal peptide variants in the human genome

Secreted and membrane proteins represent a third of all cellular proteins and contain N-terminal signal peptides that are required for protein targeting to endoplasmic reticulum (ER). Mutations in signal peptides affect protein targeting, translocation, processing, and stability, and are associated with human diseases. However, only a few of them have been identified or characterized. In this report, we identified pathogenic signal peptide variants across the human genome using bioinformatic analyses and predicted the molecular mechanisms of their pathology. We recovered more than 65 thousand signal peptide mutations, over 11 thousand we classified as pathogenic, and proposed framework for distinction of their molecular mechanisms. The pathogenic mutations affect over 3.3 thousand genes coding for secreted and membrane proteins. Most pathogenic mutations alter the signal peptide hydrophobic core, a critical recognition region for the signal recognition particle, potentially activating the Regulation of Aberrant Protein Production (RAPP) quality control and specific mRNA degradation. The remaining pathogenic variants (about 25%) alter either the N-terminal region or signal peptidase processing site that can result in translocation deficiencies at the ER membrane or inhibit protein processing. This work provides a conceptual framework for the identification of mutations across the genome and their connection with human disease.

Amyloid Precursor Protein and Alzheimer's Disease

Alzheimer's disease (AD) is one of the most common neurodegenerative disorders associated with age or inherited mutations. It is characterized by severe dementia in the late stages that affect memory, cognitive functions, and daily life overall. AD progression is linked to the accumulation of cytotoxic amyloid beta (Aβ) and hyperphosphorylated tau protein combined with other pathological features such as synaptic loss, defective energy metabolism, imbalances in protein, and metal homeostasis. Several treatment options for AD are under investigation, including antibody-based therapy and stem cell transplantation. Amyloid precursor protein (APP) is a membrane protein considered to play a main role in AD pathology. It is known that APP in physiological conditions follows a non-amyloidogenic pathway; however, it can proceed to an amyloidogenic scenario, which leads to the generation of extracellular deleterious Aβ plaques. Not all steps of APP biogenesis are clear so far, and these questions should be addressed in future studies. AD is a complex chronic disease with many factors that contribute to disease progression.

Specialized Ribosomes in Health and Disease

Ribosomal heterogeneity exists within cells and between different cell types, at specific developmental stages, and occurs in response to environmental stimuli. Mounting evidence supports the existence of specialized ribosomes, or specific changes to the ribosome that regulate the translation of a specific group of transcripts. These alterations have been shown to affect the affinity of ribosomes for certain mRNAs or change the cotranslational folding of nascent polypeptides at the exit tunnel. The identification of specialized ribosomes requires evidence of the incorporation of different ribosomal proteins or of modifications to rRNA and/or protein that lead(s) to physiologically relevant changes in translation. In this review, we summarize ribosomal heterogeneity and specialization in mammals and discuss their relevance to several human diseases.

Dynamical modeling reveals RNA decay mediates the effect of matrix stiffness on aged muscle stem cell fate

Loss of muscle stem cell (MuSC) self-renewal with aging reflects a combination of influences from the intracellular (e.g., post-transcriptional modifications) and extracellular (e.g., matrix stiffness) environment. Whereas conventional single cell analyses have revealed valuable insights into factors contributing to impaired self-renewal with age, most are limited by static measurements that fail to capture nonlinear dynamics. Using bioengineered matrices mimicking the stiffness of young and old muscle, we showed that while young MuSCs were unaffected by aged matrices, old MuSCs were phenotypically rejuvenated by young matrices. Dynamical modeling of RNA velocity vector fields in silico revealed that soft matrices promoted a self-renewing state in old MuSCs by attenuating RNA decay. Vector field perturbations demonstrated that the effects of matrix stiffness on MuSC self-renewal could be circumvented by fine-tuning the expression of the RNA decay machinery. These results demonstrate that post-transcriptional dynamics dictate the negative effect of aged matrices on MuSC self-renewal.