Mechanisms of Hypercapnia-Induced Endoplasmic Reticulum Dysfunction

Protein transcription, translation, and folding occur continuously in every living cell and are essential for physiological functions. About one-third of all proteins of the cellular proteome interacts with the endoplasmic reticulum (ER). The ER is a large, dynamic cellular organelle that orchestrates synthesis, folding, and structural maturation of proteins, regulation of lipid metabolism and additionally functions as a calcium store. Recent evidence suggests that both acute and chronic hypercapnia (elevated levels of CO2) impair ER function by different mechanisms, leading to adaptive and maladaptive regulation of protein folding and maturation. In order to cope with ER stress, cells activate unfolded protein response (UPR) pathways. Initially, during the adaptive phase of ER stress, the UPR mainly functions to restore ER protein-folding homeostasis by decreasing protein synthesis and translation and by activation of ER-associated degradation (ERAD) and autophagy. However, if the initial UPR attempts for alleviating ER stress fail, a maladaptive response is triggered. In this review, we discuss the distinct mechanisms by which elevated CO2 levels affect these molecular pathways in the setting of acute and chronic pulmonary diseases associated with hypercapnia.

Adverse event following platelet rich plasma injection for the management of early Osteoarthritis of knee – A report of 4 cases

Osteoarthritis is the leading cause of chronic disability affecting more than 80% of people over the age of 55. Several treatment options are there for early Osteoarthritis (OA) knee, like- rest, ice, brace, NSAIDs, intra-articular corticosteroid, Intra-Articular Hyaluronic Acid (IAHA), and intra-articular platelet-rich plasma (PRP) injection. Growth factors in PRP (PDGF, IGF, VEGF) promote matrix synthesis, cell growth, and migration, thus facilitating protein transcription. Several studies regarding PRP injection in the management of OA knee support this line of management without any documented complications of PRP at the knee joint.We report 4 cases of acute inflammation related to PRP injection for the treatment of OA knee. Two patients developed mild inflammation which was treated with oral medication on an outpatient basis. Another two patients developed moderate to severe inflammation which warranted surgical intervention.Intraarticular PRP injection has been reported in the literature as a successful modality of treatment in OA knee without any significant adverse effect. We are reporting four cases of adverse events following intraarticular PRP injection. Two cases were mild inflammations while the other two were moderate to severe. All four patients recovered and the outcome was satisfactory compared to the pre-injection status. The exact cause for the reaction after PRP injection in the knee is not known. Further study is needed for the cause of the inflammatory reaction.

UbiSites-SRF: Ubiquitination Sites Prediction Using Statistical Moment with Random Forest Approach

Ubiquitination is the process that supports the growth and development of eukaryotic and prokaryotic organisms. It is helpful in regulating numerous functions such as the cell division cycle, caspase-mediated cell death, maintenance of protein transcription, signal transduction, and restoration of DNA damage. Because of these properties, its identification is essential to understand its molecular mechanism. Some traditional methods such as mass spectrometry and site-directed mutagenesis are used for this purpose, but they are tedious and time consuming. In order to overcome such limitations, interest in computational models of this type of identification is therefore being developed. In this study, an accurate and efficient classification model for identifying ubiquitination sites was constructed. The proposed model uses statistical moments for feature extraction along with random forest for classification. Three sets of ubiquitination are used to train and test the model. The model is assessed through 10-fold cross-validation and jackknife tests. We achieved a 10-fold accuracy of 100% for dataset-1, 99.88% for dataset-2 and 99.84% for the dataset-3, while with Jackknife test we got 100% for the dataset-1, 99.91% for dataset-2 and 99.99%. for the dataset-3. The results obtained are almost the maximum, which is far better as compared to the pre-existing models available in the literature.

Bayesian inversion of a diffusion model with application to biology

A common task in experimental sciences is to fit mathematical models to real-world measurements to improve understanding of natural phenomenon (reverse-engineering or inverse modelling). When complex dynamical systems are considered, such as partial differential equations, this task may become challenging or ill-posed. In this work, a linear parabolic equation is considered as a model for protein transcription from MRNA. The objective is to estimate jointly the differential operator coefficients, namely the rates of diffusion and self-regulation, as well as a functional source. The recent Bayesian methodology for infinite dimensional inverse problems is applied, providing a unique posterior distribution on the parameter space continuous in the data. This posterior is then summarized using a Maximum a Posteriori estimator. Finally, the theoretical solution is illustrated using a state-of-the-art MCMC algorithm adapted to this non-Gaussian setting.

A deep learning approach to predict inter-omics interactions in multi-layer networks

Despite enormous achievements in production of high throughput datasets, constructing comprehensive maps of interactions remains a major challenge. The lack of sufficient experimental evidence on interactions is more significant for heterogeneous molecular types. Hence, developing strategies to predict inter-omics connections is essential to construct holistic maps of disease. Here, Data Integration with Deep Learning (DIDL), a novel nonlinear deep learning method is proposed to predict inter-omics interactions. It consists of an encoder that automatically extracts features for biomolecules according to existing interactions, and a decoder that predicts novel interactions. The applicability of DIDL is assessed with different networks namely drug-target protein, transcription factor-DNA element, and miRNA-mRNA. Also, the validity of novel predictions is assessed by literature surveys. Furthermore, DIDL outperformed state-of-the-art methods. Area under the curve, and area under the precision-recall curve for all three networks were more than 0.85 and 0.83, respectively. DIDL has several advantages like automatic feature extraction from raw data, end-to-end training, and robustness to sparsity. In addition, tensor decomposition structure, predictions solely based on existing interactions and biochemical data independence makes DIDL applicable for a variety of biological networks. DIDL paves the way to understand the underlying mechanisms of complex disorders through constructing integrative networks.

Persistent repression of tau in the brain using engineered zinc finger protein transcription factors

Neuronal tau reduction confers resilience against β-amyloid and tau-related neurotoxicity in vitro and in vivo. Here, we introduce a novel translational approach to lower expression of the tau gene MAPT at the transcriptional level using gene-silencing zinc finger protein transcription factors (ZFP-TFs). Following a single administration of adeno-associated virus (AAV), either locally into the hippocampus or intravenously to enable whole-brain transduction, we selectively reduced tau messenger RNA and protein by 50 to 80% out to 11 months, the longest time point studied. Sustained tau lowering was achieved without detectable off-target effects, overt histopathological changes, or molecular alterations. Tau reduction with AAV ZFP-TFs was able to rescue neuronal damage around amyloid plaques in a mouse model of Alzheimer’s disease (APP/PS1 line). The highly specific, durable, and controlled knockdown of endogenous tau makes AAV-delivered ZFP-TFs a promising approach for the treatment of tau-related human brain diseases.

Comparative genomic analysis of two novel plasmids from Acidithiobacillus ferrivorans strain PQ33

Acidithiobacillus ferrivorans is a psychrotolerant acidophile capable of growing and oxidizing ferrous and sulphide substrates at low temperatures. To date, six genomes of this organism have been characterized; however, evidence of a plasmid in this species has been reported only once, whereby there is no conclusive role of the plasmids in the species. Herein, two novel plasmids of A. ferrivorans PQ33 were molecularly characterized and compared at a genomic scale. The genomes of two plasmids (12 kbp and 10 kbp) from A. ferrivorans PQ33 (NZ_LVZL01000000) were sequenced and annotated. The plasmids, named pAfPQ33-1 (NZ_CP021414.1) and pAfPQ33-2 (NZ_CP021415.1), presented 9 CDS and 13 CDS, respectively. In silico analysis showed proteins involved in conjugation (TraD, MobA, Eep and XerD), toxin-antitoxin systems (HicA and HicB), replication (RepA and DNA binding protein), transcription regulation (CopG), chaperone DnaJ, and a virulence gene (vapD). Furthermore, the plasmids contain sequences similar to phosphate-selective porins O and P and a diguanylate cyclase-phosphodiesterase protein. The presence of these genes suggests the possibility of horizontal transfer, a regulatory system of plasmid maintenance, and adhesion to substrates for A. ferrivorans species and PQ33. This is the first report of plasmids in this strain.

YAP activation in melanoma contributes to anoikis resistance and metastasis

Melanoma is inherently heterogeneous, providing resistance to apoptosis. Anoikis resistance is a hallmark feature of metastatic melanoma to escape apoptosis when cells lose contact with adjacent cells or extracellular matrix. The yes-associated protein transcription co-activator is the effector of Hippo pathway. Herein, we investigated the function of yes-associated protein in anoikis resistance of melanoma cells. When melanoma cells were grown under anchorage-independent condition, anoikis-resistant cells displayed higher levels of yes-associated protein activation than the cells that were attached to the basement membrane, as evidenced by downregulated phosphorylated yes-associated protein at Ser127 and higher expression of downstream genes BCL2 and MCL-1. Yes-associated protein overexpression directly enhanced the anoikis resistance and metastatic potential of melanoma cells. Conversely, yes-associated protein inhibitor CA3 exhibited Dose-dependent induction of anoikis in resistant melanoma cells and exerted great inhibition on cell migration. Knockdown of yes-associated protein expression by shRNA also rendered melanoma cells susceptible to anoikis and interrupted cell invasiveness. Yes-associated protein inhibition in anoikis-resistant cells also reduced the number of metastatic nodules in the lung sections of SCID mice. Clinically, higher yes-associated protein level in the lung metastasis tissues correlated with higher BCL2 and MCL1 expressions compared with the non-metastasis tissues. Overall, our finding suggests that the aberrant activation of yes-associated protein exerts important role on anoikis resistance and metastatic capability of melanoma cells.