Immune-associated biomarkers for early diagnosis of Parkinson’s disease based on hematological lncRNA–mRNA co-expression

Early stage diagnosis of Parkinson’s disease (PD) is challenging without significant motor symptoms. The identification of effective molecular biomarkers as a hematological indication of PD may help improve the diagnostic timelines and accuracy. In the present paper, we analyzed and compared the blood samples of PD and control (CTR) patients to identify the disease-related changes and determine the putative biomarkers for PD diagnosis. Based on the RNA sequencing analysis, differentially expressed genes (DEGs) were identified, and the co-expression network of DEGs was constructed using the weighted gene correlation network analysis (WGCNA). The analysis leads to the identification of 87 genes that were exclusively regulated in the PD group, whereas 66 genes were significantly increased and 21 genes were significantly decreased in contrast with the control group. The results indicate that the core lncRNA–mRNA co-expression network greatly changes the immune response in PD patients. Specifically, the results showed that Prader Willi Angelman Region RNA6 (PWAR6), LINC00861, AC83843.1, IRF family, IFIT family and calcium/calmodulin-dependent protein kinase IV (CaMK4) may play important roles in the immune system of PD. Based on the findings from the present study, future research aims at identifying novel therapeutic strategies for PD.     

Identifying potential entry inhibitors for emerging Nipah virus by molecular docking and chemical-protein interaction network

Abstract

Nipah Virus (NiV) is a newly emergent paramyxovirus that has caused various outbreaks in Asian countries. Despite its acute pathogenicity and lack of approved therapeutics for human use, there is an urgent need to determine inhibitors against NiV. Hence, this work includes prospection of potential entry inhibitors by implementing an integrative structure- and network-based drug discovery approach. FDA-approved drugs were screened against attachment glycoprotein (NiV-G, PDB: 2VSM), one of the prime targets to inhibit viral entry, using a molecular docking approach that was benchmarked both on CCDC/ASTEX and known NIV-G inhibitor set. The predicted small molecules were prioritized on the basis of topological analysis of the chemical-protein interaction network, which was inferred by integrating the drug-target network, NiV-human interaction network, and human protein-protein interaction network. A total of 17 drugs were predicted to be NiV-G inhibitors using molecular docking studies that were further prioritized to 3 novel leads???Nilotinib, Deslanoside and Acetyldigitoxin???on the basis of topological analysis of inferred chemical-protein interaction network. While Deslanoside and Acetyldigitoxin belong to an already known class of anti-NiV inhibitors, Nilotinib belongs to Benzenoids chemical class that has not been reported hitherto for developing anti-NiV inhibitors. These identified drugs are expected to be successful in further experimental evaluation and therefore could be used for anti-Nipah drug discovery. Apart, we also obtained various insights into the underlying chemical-protein interaction network, based on which several important network nodes were predicted. The applicability of our proposed approach was also demonstrated by prospecting for anti-NiV phytochemicals on an independent dataset.

Communicated by Ramaswamy H. Sarma     

Complete mitochondrial genomes offer insights into the evolutionary relationships and comparative genetic diversity of New Zealand’s iconic kiwi (Apteryx spp.)

ABSTRACT

Kiwis (Apterygidae) are an enigmatic family of flightless birds endemic to New Zealand. Apterygidae is made up of a single genus, Apteryx with five species, four of which are characterised as at risk of greater by the New Zealand Department of Conservation. These five species are further separated into two morphologically and genetically distinguishable clades, containing A.haastii, and A.owenii in one and A.rowi, A.mantelli, and A.australis in the other. We reconstructed 17 kiwi mitochondrial genomes from previously published genomic data, nine from A.rowi and eight from A.owenii. Mitochondrial diversity analyses uncovered low levels of genetic diversity consistent with their reduced ranges and conservation concern. We further used one of the assembled A.rowi mitochondrial genomes together with mitochondrial genomes from A.haastii, A.owenii, A.mantelli, and several other individuals from Palaeognathae to estimate the within and between clade divergence times of kiwis. Our study exemplifies how available published data can be used in novel ways to provide new and complementary evolutionary insights to previous studies.     

ProDCoNN: Protein design using a convolutional neural network

Designing protein sequences that fold to a given three-dimensional (3D) structure has long been a challenging problem in computational structural biology with significant theoretical and practical implications. In this study, we first formulated this problem as predicting the residue type given the 3D structural environment around the C _α atom of a residue, which is repeated for each residue of a protein. We designed a nine-layer 3D deep convolutional neural network (CNN) that takes as input a gridded box with the atomic coordinates and types around a residue. Several CNN layers were designed to capture structure information at different scales, such as bond lengths, bond angles, torsion angles, and secondary structures. Trained on a very large number of protein structures, the method, called ProDCoNN (protein design with CNN), achieved state-of-the-art performance when tested on large numbers of test proteins and benchmark datasets.     

Roles of CytR,an anti-activator of cyclic-AMP receptor protein (CRP) on flagellar expression and virulence in uropathogenic Escherichia coli

Uropathogenic Escherichia coli (UPEC) is a major pathogen that causes urinary tract infection (UTI), a common bacterial infectious disease. This bacterium invades the urinary tract cells, where it aggregates, and subsequently forms multicellular colonies termed intracellular bacterial communities (IBCs). The motility of the bacteria plays a key role in the mechanism of virulence in the host bladder. Here, we show that CytR is a modulator of bacterial internalization and aggregation within the bladder epithelial cells sustained by CRP in UPEC. Mutational analyses and gel-shift assays indicated that CytR represses the expression of flhD, thereby encoding a master regulator for flagellar expression that is responsible for bacterial motility when CRP is present, whereas CRP is an activator of flhD expression. Thus, elevated flagellar expression was involved in promoted virulence in the cytR mutant. These combined observations suggest another regulatory layer of flagellar expression and the role of CytR in UPEC virulence.     

Evolution under pH stress and high population densities leads to increased density-dependent fitness in the protist Tetrahymena thermophila

Abiotic stress is a major force of selection that organisms are constantly facing. While the evolutionary effects of various stressors have been broadly studied, it is only more recently that the relevance of interactions between evolution and underlying ecological conditions, that is, eco-evolutionary feedbacks, have been highlighted. Here, we experimentally investigated how populations adapt to pH-stress under high population densities. Using the protist species Tetrahymena thermophila, we studied how four different genotypes evolved in response to stressfully low pH conditions and high population densities. We found that genotypes underwent evolutionary changes, some shifting up and others shifting down their intrinsic rates of increase (r₀). Overall, evolution at low pH led to the convergence of r₀ and intraspecific competitive ability (α) across the four genotypes. Given the strong correlation between r₀ and α, we argue that this convergence was a consequence of selection for increased density-dependent fitness at low pH under the experienced high density conditions. Increased density-dependent fitness was either attained through increase in r₀, or decrease of α, depending on the genetic background. In conclusion, we show that demography can influence the direction of evolution under abiotic stress.