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Hot Springs Thermophilic Microbiomes
Published in Ajar Nath Yadav, Ali Asghar Rastegari, Neelam Yadav, Microbiomes of Extreme Environments, 2021
Juan-José Escuder-Rodríguez, María-Eugenia DeCastro, Esther Rodríguez-Belmonte, Manuel Becerra, María-Isabel González-Siso
Wohlgemuth et al. (2018) studied 15 hot spring metagenomes looking for novel hydrolases in a combined sequence and function-based screening. As result of this project, novel hydrolases were studied and characterized such as carboxylesterases, enol lactonases, quorum sensing lactonases, gluconolactonases, cellulases and two epoxide hydrolases found by sequence metagenomics in the metagenomes of a Russian and a Chinese hot spring (Ferrandi et al. 2018). Gupta et al. (2017b) analyzed the bacterial diversity of hot sulfur springs of Leh (Nubra valley, Ladakh, India) looking for laccases. Lee et al. (2018) explored the bacterial diversity of Malaysian Y-shaped Sungai Klah hot spring, located in a wooded area, bioprospecting for Glycoside Hydrolases (GHs) that could be potentially used as cellulases and hemicellulases. The study revealed the huge potential of this hot spring as a source of these kinds of thermozymes. Using a similar procedure, the 140 thermophilic bacteria isolated from Manikaran and Yumthang hot springs (India) were studied for phylogenetic profiling, growth properties at varying conditions and potential sources of extracellular thermostable hydrolytic enzymes such as protease, amylase, xylanase and cellulase (Sahay et al. 2017). Kaushal et al. (2018) focused on the carbohydrate-related thermozymes of four thermal water reservoirs (55 to 98°C) located in Tattapani geothermal field of Chhattisgarh, India, using a metagenomic approach. McKay et al. (2017) centered their studies on the archaeal diversity of the sediment of Washburn and Heart Lake methanogenic hot springs (YNP, USA) in order to examine the presence and expression of novel methyl-coenzyme M reductase gene (mcrA) variants. Chuzel et al. (2018) used functional metagenomics screening of Dixie Valley hot spring mats (Nevada, USA) to seek enzymes capable of hydrolysis of sialic acids, sialidases. Other examples of different types of thermozymes obtained using classical approaches published since 2017 are listed in Tables 5.2, 5.3 and 5.4.
COVID-19;-The origin, genetics,and management of the infection of mothers and babies
Published in Egyptian Journal of Basic and Applied Sciences, 2020
Hassan Ih El-Sayyad, Yousef Ka Abdalhafid
The seventh novel human infecting beta-coronavirus that causes pneumonia (SARS-CoV-2) originated in Wuhan, China. There is no correlation between COVID-19 and other respiratory diseases. A phylogenetic tree was constructed from the genome sequences depending on the presence and absence of homologs of ten SARS-CoV-2 proteins. The data suggests that SARS-CoV-2 is most closely related to Bat CoV RaTG13 and belongs to subgenus Sarbecovirus of Betacoronavirus, together with SARS-CoV and Bat-SARS-like CoV. The phylogenetic profiling cluster of homolog proteins of one annotated SARS-CoV-2 protein against other genome sequences revealed two clades of ten SARS-CoV-2 proteins. Clade 1 consisted of a group of conserved proteins in Orthocoronavirinae comprising Orf1ab polyprotein, nucleocapsid protein, spike glycoprotein, and membrane protein. Clade 2 comprised six proteins exclusive to Sarbecovirus and Hibecovirus. Two of six Clade 2 nonstructural proteins, NS7b and NS8, were exclusively conserved among SARS-CoV-2, BetaCoV_RaTG, and BatSARS-like Cov. NS7b and NS8 have previously been shown to affect immune response signaling in the SARS-CoV experimental model. Thus, we speculated that knowledge of the functional changes in the NS7b and NS8 proteins during evolution could provide important information to explore the human infective property of SARS-CoV-2 [97].
Design of artificial cells: artificial biochemical systems, their thermodynamics and kinetics properties
Published in Egyptian Journal of Basic and Applied Sciences, 2022
Adamu Yunusa Ugya, Lin Pohan, Qifeng Wang, Kamel Meguellati
Artificial cells are able to mimic protein–protein interactions because these cells can be engineered as exact copies of protein fragments. The sites of protein–protein interactions seem to be conserved, clustered, and large compared to the binding sites of smaller molecules. The evolutionary conserved residues within interfaces appear to be unrelated to binding but have important implications for identifying protein–protein binding sites as well as being extremely useful for docking studies [97]. The interaction is classified as obligate, oligomeric, tight (permanent), relatively weak (transient), and unstructured segments of mediated proteins [98]. Cancer cells modify the protein-protein interactions taking place in apoptosis and escape potential molecular targets for anti-cancer drug development, which were identified by applying nonlinear stochastic modeling [99]. In addition, the metabolic regulation and the broad annotated protein–protein interaction network of signal transduction in yeast are carried out by reconstruction [100]. Eventually, the chemical and spatial patterns among protein–protein interfaces are studied using PCalign [101]. The study of the predictive interactions among the specific biological pathways of the protein is done by protein–protein functional linkage prediction methods, namely gene neighborhood, expression similarity, phylogenetic profiling, a mirror tree variant, and orthologous gene co-presence in the same gene clusters [102]. Muley group revealed that the purified human L1 ORF1p trimer played an important role in retrotransposition both as a nucleic acid binding protein and also as a nucleic acid chaperone [103].