The relationship of epigenetic processes and the intestinal microbiota may serve as an essential role in elevating the bisulfite sequencing potentials in discovering host-microbiota interactions in germfree (GF) and conventional mice. The previous studies have established that the microbiota regulates a large proportion of the intestinal epithelial transcriptome in the adult host. However, microbial effects on DNA methylation and gene expression during early postnatal development are still poorly understood. In recent years, the number of studies investigating the impact of the gut microbiome in colorectal cancer (CRC) has risen sharply. As a result, we now know that various microbes (and microbial communities) are found more frequently in the stool and mucosa of individuals with CRC than healthy controls, including in the primary tumors themselves and even in distant metastases. We took albino mice and reared them under laboratory conditions. After 16 weeks of rearing, mice were slaughtered, and DNA extraction was performed later on. Bisulfite sequencing was done under controlled environmental conditions to unveil the role of sequencing in determining the host-microbiota interactions. The study results showed a strong host-microbiota interaction in GF mice as it significantly affects lipid metabolism, inflammation, carcinogenic, and postnatal development.

In the United States, over 200,000 people live with RCC; the mortality of half these patients significantly increase due to the lack of adequate and rapid diagnosis (Campbell, 2014). MicroRNAs have been found to be strong biomarkers of tumors, easily detected in the bloodstream around the tumor (Moldovan et al., 2014). Many regulated microRNAs affect the outcome of cancers. There is limited previous research in microRNAs’ potential role in RCC. A total of 7223 isoform microRNA expressions of healthy and cancerous RCC samples were taken from the Gene Expression Omnibus. Of the microRNAs, the Best First Attribute Selector (BFAS) was used in the Weka interface to choose 53 microRNAs, which are most significant in predicting each patient’s outcome. The dataset was separated between training and testing data using a 4-fold cross-validation. Moreover, algorithms were run with the selected features to determine the highest classification accuracy, precision, and recall. The BFAS with the J48 decision tree algorithm and the BFAS with a Hoeffding Tree algorithm each had an accuracy of 91.89%. According to these models, bta-miR-200c_st and ACA39_st may be significant as biomarkers of RCC.

Alzheimer’s disease (AD) is also known as neurodegenerative disease, which normally causes 60–70% of dementia. There are many genetic and environmental risk factors associated with its development. The strongest genetic risk factor occurs by apolipoprotein E (apoE). Another type of risk factor may include high blood pressure, clinical depression, and head injury. In 2015, there were 29.8 million people affected worldwide by AD. Women get at risk more often than men. The present study was to inhibit the expression of apoE by dihydrohelenalin (DH) with the help molecular docking for the treatment of AD. The molecular docking method was performed after the screening of molecules and selecting the ligands which can inhibit and target the proteins. apoE (Protein Data Bank [PDB] ID 1GS9) protein was targeted through seven ligands compound and the best ligand was selected for further molecular docking and modeling tools. Thus, screening showed DH (with the binding affinity of −5.3 kcal/mol) as a ligand molecule that may inhibit apoE. DH has the highest binding properties. Thus, it may be used further used for the treatment of AD. The DH may be the beneficial drug for the treatments of AD in future studies after in vitro and in vivo studies.

From the beginning of the year 2020, the emergence of a new coronavirus outbreak leads to the worldwide pandemic causing severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). To date, there is no medicine or vaccine for this infectious disease, so the discovery of coherent vaccines has become the top priority. Many studies are being able to show various techniques to facilitate the combination of immunoinformatics and comparative genomic approach to determine the potential peptides for designing T-cell-based peptide vaccine by the use of 2019-nCoV envelope protein as a target. By screening bioimmunoinformatic SARS-CoV-2-derived T-cell and B-cell epitopes within the basic immunogenic of SARS-CoV-2 proteins, a set of inferred B-cell and T-cell epitopes from the spike(S) and nucleocapsid (N) proteins having high anti-antigenicity and without allergenic property or toxic effects was studied. The findings of this study provide a screened set of epitopes that can be introduced as potential targets for developing peptide vaccines against the SARS-CoV-2 virus.