Composition, Abundance, and Diversity of the Soil Microbiome Associated with the Halophytic Plants Tamarix aphylla and Halopeplis perfoliata on Jeddah Seacoast, Saudi Arabia.

The coast of the Red Sea in Jeddah City is home to a unique microbial community that has adapted to extreme environmental conditions. Therefore, it is essential to characterize the microbial community in this unique microbiome to predict how environmental changes will affect it. The aim of this study was to conduct metagenomic sequencing of 16S rRNA and ITS rRNA genes for the taxonomic classification of the microbial community in soil samples associated with the halophytic plants Tamarix aphylla and Halopeplis perfoliata. Fifteen soil samples were collected in triplicate to enhance robustness and minimize sampling bias. Firstly, to identify novel microbial candidates, the gDNAs were isolated from the saline soil samples surrounding each plant, and then bacterial 16S (V3-V4) and fungal ITS1 regions were sequenced utilizing a high-throughput approach (next-generation sequencing; NGS) on an Illumina MiSeq platform. Quality assessment of the constructed amplicon libraries was conducted using Agilent Bioanalyzer and fluorometric quantification methods. The raw data were processed and analyzed using the Pipeline (Nova Lifetech, Singapore) for bioinformatics analysis. Based on the total number of readings, it was determined that the phylum Actinobacteriota was the most prevalent in the soil samples examined, followed by the phylum Proteobacteria. Based on ITS rRNA gene analysis, the alpha and beta fungal diversity in the studied soil samples revealed that the fungal population is structured into various groups according to the crust (c) and/or rhizosphere (r) plant parts. Fungal communities in the soil samples indicated that Ascomycota and Basidiomycota were the two most abundant phyla based on the total amount of sequence reads. Secondly, heat-map analysis of the diversity indices showed that the bacterial alpha diversity, as measured by Shannon, Simpson, and InvSimpson, was associated with soil crust (Hc and Tc enclosing H. perfoliata and T. aphylla, respectively) and that the soil rhizosphere (Hr and Tr) was strongly correlated with bacterial beta diversity. Finally, fungal-associated Tc and Hc samples clustered together, according to observations made using the Fisher and Chao1 methods, and Hr and Tr samples clustered together according to Shannon, Simpson, and InvSimpson analyses. As a result of the soil investigation, potential agents that have been identified could lead to innovative agricultural, medical, and industrial applications.

Exploring the taxonomic and functional diversity of marine benthic micro-Eukaryotes along the Red Sea coast of Jeddah city.

Backgrounds: Diverse marine habitats along Jeddah's Red Sea coast support rich biodiversity. Few studies have been done on its diverse communities, especially its microbial counterparts. Metagenomic analysis of marine benthic micro-eukaryotic communities was performed for the first time on the Red Sea coast of Jeddah. This research looks into their community structure and metabolic potential. Methods: Next-generation sequencing was used to examine the micro-eukaryotic communities of seven sedimentary soil samples from four Jeddah coast locations. After isolating DNA from seven benthic sedimentary soil samples, the 18S rDNA V4 regions were amplified and sequenced on the Illumina MiSeq. It was also verified using an Agilent Technologies 2100 Bioanalyzer with a DNA 1000 chip (Agilent Technologies, Fisher Scientific). A standard curve of fluorescence readings generated by qPCR quantification using the Illumina library was achieved using the GS FLX library. Metagenomic data analysis was used to evaluate the microbial communities' biochemical and enzymatic allocations in studied samples. Results: Blast analysis showed that the top ten phyla were Annelida, Eukaryota, Diatomea, Porifera, Phragmoplastophyta, Arthropoda, Dinoflagellata, Xenacoelomorpha Nematoda, and uncultured. Annelida was also found in the highest percentage (93%), in the sample M followed by Porifera (64%), the most abundant in the control sample then Eukaryotes (61%), Phragmatoplastophyta (55%), Arthropoda, and Diatomea (the least common) (32%). community diversity analysis: using Shannon and inverse Simpson indices showed sediment composition to be effective. Also, PICRUST2 indicated that the most abundant pathways were pyruvate fermentation to isobutanol, pyrimidine deoxyribonucleotide phosphorylation, adenosine ribonucleotide de novo biosynthesis, guanosine ribonucleotide de novo biosynthesis, NAD salvage pathway I, the super pathway of glyoxylate bypass and aerobic respiration I (cytochrome c). Conclusion: Results showed that high throughput metagenomics could reveal species diversity and estimate gene profiles. Environmental factors appear to be more important than geographic variation in determining the structure of these microbial communities. This study provides the first report of marine benthic micro-eukaryotic communities found on the Red Sea coast of Jeddah and will serve as a good platform for future research.

In silico screening of some compounds derived from the desert medicinal plant Rhazya stricta for the potential treatment of COVID-19.

The latest coronavirus pandemic (SARS-CoV-2) poses an exceptional threat to human health and society worldwide. The coronavirus (SARS-CoV-2) spike (S) protein, which is required for viral-host cell penetration, might be considered a promising and suitable target for treatment. In this study, we utilized the nonalkaloid fraction of the medicinal plant Rhazya stricta to computationally investigate its antiviral activity against SARS-CoV-2. Molecular docking and molecular dynamics simulations were the main tools used to examine the binding interactions of the compounds isolated by HPLC analysis. Ceftazidime was utilized as a reference control, which showed high potency against the SARS-CoV-2 receptor binding domain (RBD) in an in vitro study. The five compounds (CID:1, CID:2, CID:3, CID:4, and CID:5) exhibited remarkable binding affinities (CID:1, - 8.9; CID:2, - 8.7; and CID:3, 4, and 5, - 8.5 kcal/mol) compared to the control compound (- 6.2 kcal/mol). MD simulations over a period of 200 ns further corroborated that certain interactions occurred with the five compounds and the nonalkaloidal compounds retained their positions within the RBD active site. CID:2, CID:4, and CID:5 demonstrated high stability and less variance, while CID:1 and CID:3 were less stable than ceftazidime. The average number of hydrogen bonds formed per timeframe by CID:1, CID:2, CID:3, and CID:5 (0.914, 0.451, 1.566, and 1.755, respectively) were greater than that formed by ceftazidime (0.317). The total binding free energy calculations revealed that the five compounds interacted more strongly within RBD residues (CID:1 = - 68.8, CID:2 = - 71.6, CID:3 = - 74.9, CID:4 = - 75.4, CID:5 = - 60.9 kJ/mol) than ceftazidime (- 34.5 kJ/mol). The drug-like properties of the selected compounds were relatively similar to those of ceftazidime, and the toxicity predictions categorized these compounds into less toxic classes. Structural similarity and functional group analyses suggested that the presence of more H-acceptor atoms, electronegative atoms, acidic oxygen groups, and nitrogen atoms in amide or aromatic groups were common among the compounds with the lowest binding affinities. In conclusion, this in silico work predicts for the first time the potential of using five R. stricta nonalkaloid compounds as a treatment strategy to control SARS-CoV-2 viral entry.