Disruption of cellular proteostasis by H1N1 influenza A virus causes α-synuclein aggregation.

Neurodegenerative diseases feature specific misfolded or misassembled proteins associated with neurotoxicity. The precise mechanisms by which protein aggregates first arise in the majority of sporadic cases have remained unclear. Likely, a first critical mass of misfolded proteins starts a vicious cycle of a prion-like expansion. We hypothesize that viruses, having evolved to hijack the host cellular machinery for catalyzing their replication, lead to profound disturbances of cellular proteostasis, resulting in such a critical mass of protein aggregates. Here, we investigated the effect of influenza virus (H1N1) strains on proteostasis of proteins associated with neurodegenerative diseases in Lund human mesencephalic dopaminergic cells in vitro and infection of Rag knockout mice in vivo. We demonstrate that acute H1N1 infection leads to the formation of α-synuclein and Disrupted-in-Schizophrenia 1 (DISC1) aggregates, but not of tau or TDP-43 aggregates, indicating a selective effect on proteostasis. Oseltamivir phosphate, an antiinfluenza drug, prevented H1N1-induced α-synuclein aggregation. As a cell pathobiological mechanism, we identified H1N1-induced blocking of autophagosome formation and inhibition of autophagic flux. In addition, α-synuclein aggregates appeared in infected cell populations connected to the olfactory bulbs following intranasal instillation of H1N1 in Rag knockout mice. We propose that H1N1 virus replication in neuronal cells can induce seeds of aggregated α-synuclein or DISC1 that may be able to initiate further detrimental downstream events and should thus be considered a risk factor in the pathogenesis of synucleinopathies or a subset of mental disorders. More generally, aberrant proteostasis induced by viruses may be an underappreciated factor in initiating protein misfolding.

RNA-induced silencing attenuates G protein-mediated calcium signals.

Phospholipase Cß (PLCß) is activated by G protein subunits in response to environmental stimuli to increase intracellular calcium. In cells, a significant portion of PLCß is cytosolic, where it binds a protein complex required for efficient RNA-induced silencing called C3PO (component 3 promoter of RISC). Binding between C3PO and PLCß raises the possibility that RNA silencing activity can affect the ability of PLCß to mediate calcium signals. By use of human and rat neuronal cell lines (SK-N-SH and PC12), we show that overexpression of one of the main components of C3PO diminishes Ca(2+) release in response to Gαq/PLCß stimulation by 30 to 40%. In untransfected SK-N-SH or PC12 cells, the introduction of siRNA(GAPDH) [small interfering RNA(glyceraldehyde 3-phosphate dehydrogenase)] reduces PLCß-mediated calcium signals by ∼30%, but addition of siRNA(Hsp90) (heat shock protein 90) had little effect. Fluorescence imaging studies suggest an increase in PLCß-C3PO association in cells treated with siRNA(GAPDH) but not siRNA(Hsp90). Taken together, our studies raise the possibility that Ca(2+) responses to extracellular stimuli can be modulated by components of the RNA silencing machinery.-Philip, F., Sahu, S., Golebiewska, U., Scarlata, S. RNA-induced silencing attenuates G protein-mediated calcium signals.

Hydrolysis rates of different small interfering RNAs (siRNAs) by the RNA silencing promoter complex, C3PO, determines their regulation by phospholipase Cß.

C3PO plays a key role in promoting RNA-induced gene silencing. C3PO consists of two subunits of the endonuclease translin-associated factor X (TRAX) and six subunits of the nucleotide-binding protein translin. We have found that TRAX binds strongly to phospholipase Cß (PLCß), which transmits G protein signals from many hormones and sensory inputs. The association between PLCß and TRAX is thought to underlie the ability of PLCß to reverse gene silencing by small interfering RNAs. However, this reversal only occurs for some genes (e.g. GAPDH and LDH) but not others (e.g. Hsp90 and cyclophilin A). To understand this specificity, we carried out studies using fluorescence-based methods. In cells, we find that PLCß, TRAX, and their complexes are identically distributed through the cytosol suggesting that selectivity is not due to large scale sequestration of either the free or complexed proteins. Using purified proteins, we find that PLCß binds ∼5-fold more weakly to translin than to TRAX but ∼2-fold more strongly to C3PO. PLCß does not alter TRAX-translin assembly to C3PO, and brightness studies suggest one PLCß binds to one C3PO octamer without a change in the number of TRAX/translin molecules suggesting that PLCß binds to an external site. Functionally, we find that C3PO hydrolyzes siRNA(GAPDH) at a faster rate than siRNA(Hsp90). However, when PLCß is bound to C3PO, the hydrolysis rate of siRNA(GAPDH) becomes comparable with siRNA(Hsp90). Our results show that the selectivity of PLCß toward certain genes lies in the rate at which the RNA is hydrolyzed by C3PO.

Prediction and forecasting of worldwide corona virus (COVID-19) outbreak using time series and machine learning.

How will the newly discovered coronavirus (COVID-19) affect the world and what will be its global impact? For answering this question, we will require a prediction of overall recoveries and fatalities, as well as a reliable prognosis of coronavirus cases. Predicting, however, requires an ample total of past data related to it. On any particular day, the prediction is unclear since events in the future rarely repeat themselves the way that they did in the past. Furthermore, forecasts and predictions are determined by the absolute interests, accuracy of the data, and prophesied variables. In addition, psychological factors play an enormous role in how people perceive and react to the danger from the disease and therefore the fear that it is going to affect them personally. This research paper advances an unbiased method for predicting the increase of the COVID-19 employing a simple, but powerful method to do so. Assumed that the data are accurate and reliable which the longer term will still follow an equivalent disease pattern, our projections intimate with a large association. Within the COVID-19 cases were documented, in contingency, there is a steady increase. The hazards are far away from symmetric, as underestimating a pandemic's spread and failing to do enough to prevent it is far a lot worse than overspending and being too cautious when it will not be needed. This paper illustrates the timeline of a live forecasting study with huge implied implications for devising and decision-making and gives unbiased predictions on COVID-19 confirmed cases, recovered cases, deaths, and ongoing cases are shown on a continental map using data science and machine learning (ML) approaches. Utilizing these ML-based techniques, the proposed system predicts the accurate COVID-19 cases and gives better performance.

Regulation of the activity of the promoter of RNA-induced silencing, C3PO.

RNA-induced silencing is a process which allows cells to regulate the synthesis of specific proteins. RNA silencing is promoted by the protein C3PO (component 3 of RISC). We have previously found that phospholipase Cß, which increases intracellular calcium levels in response to specific G protein signals, inhibits C3PO activity towards certain genes. Understanding the parameters that control C3PO activity and which genes are impacted by G protein activation would help predict which genes are more vulnerable to downregulation. Here, using a library of 1018 oligonucleotides, we show that C3PO binds oligonucleotides with structural specificity but little sequence specificity. Alternately, C3PO hydrolyzes oligonucleotides with a rate that is sensitive to substrate stability. Importantly, we find that oligonucleotides with higher Tm values are inhibited by bound PLCß. This finding is supported by microarray analysis in cells over-expressing PLCß1. Taken together, this study allows predictions of the genes whose post-transcriptional regulation is responsive to the G protein/phospholipase Cß/calcium signaling pathway.

Phospholipase Cß connects G protein signaling with RNA interference.

Phosphoinositide-specific-phospholipase Cß (PLCß) is the main effector of Gαq stimulation which is coupled to receptors that bind acetylcholine, bradykinin, dopamine, angiotensin II as well as other hormones and neurotransmitters. Using a yeast two-hybrid and other approaches, we have recently found that the same region of PLCß that binds Gαq also interacts with Component 3 Promoter of RNA induced silencing complex (C3PO), which is required for efficient activity of the RNA-induced silencing complex. In purified form, C3PO competes with Gαq for PLCß binding and at high concentrations can quench PLCß activation. Additionally, we have found that the binding of PLCß to C3PO inhibits its nuclease activity leading to reversal of RNA-induced silencing of specific genes. In cells, we found that PLCß distributes between the plasma membrane where it localizes with Gαq, and in the cytosol where it localizes with C3PO. When cells are actively processing small interfering RNAs the interaction between PLCß and C3PO gets stronger and leads to changes in the cellular distribution of PLCß. The magnitude of attenuation is specific for different silencing RNAs. Our studies imply a direct link between calcium responses mediated through Gαq and post-transcriptional gene regulation through PLCß.

Role of phospholipase C-ß in RNA interference.

Phospholipase C-ß (PLCß) enzymes are activated by G proteins in response to agents such as hormones and neurotransmitters, and have been implicated in leukemias and neurological disorders. PLCß activity causes an increase in intracellular calcium which ultimately leads to profound changes in the cell. PLCß localizes to three cellular compartments: the plasma membrane, the cytosol and the nucleus. Under most cell conditions, the majority of PLCß localizes to the plasma membrane where it interacts with G proteins. In trying to determine the factors that localize PLCß to the cytosol and nucleus, we have recently identified the binding partner, TRAX. TRAX is a nuclease and part of the machinery involved in RNA interference. This review discusses the interaction between PLCß and TRAX, and its repercussions in G protein signaling and RNA silencing.