The metagenomic whole genome shotgun sequencing (mWGS) approach was used to detect signatures of the rhizosphere microbiomes of Dipterygium glaucum and surrounding bulk soil microbiomes, and to detect differential microbial responses due to watering. Preliminary results reflect the reliability of the experiment and the rationality of grouping microbiomes. Based on the abundance of non-redundant genes, bacterial genomes showed the highest level, followed by Archaeal and Eukaryotic genomes, then, the least abundant viruses. Overall results indicate that most members of bacteria have a higher abundance/relative abundance (AB/RA) pattern in the rhizosphere towards plant growth promotion, while members of eukaryota have a higher pattern in bulk soil, most likely acting as pathogens. The results also indicate the contribution of mycorrhiza (genus Rhizophagus) in mediating complex mutualistic associations between soil microbes (either beneficial or harmful) and plant roots. Some of these symbiotic relationships involve microbes of different domains responding differentially to plant root exudates. Among these are included the bacterial genus Burkholderia and eukaryotic genus Trichoderma, which have antagonistic activities against the eukaryotic genus Fusarium. Another example involves Ochrobactrum phage POA1180, its bacterial host and plant roots. One of the major challenges in plant nutrition involves other microbes that manipulate nitrogen levels in the soil. Among these are the microbes that perform contraversal actions of nitrogen fixation (the methanogen Euryarchaeota) and ammonia oxidation (Crenarchaeota). The net nitrogen level in the soil is originally based on the AB/RA of these microbes and partially on the environmental condition. Watering seems to influence the AB/RA of a large number of soil microbes, where drought-sensitive microbes (members of phyla Acidobacteria and Gemmatimonadetes) showed an increased AB/RA pattern after watering, while others (Burkholderia and Trichoderma) seem to be among microbes assisting plants to withstand abiotic stresses. This study sheds light on the efficient use of mWGS in the taxonomic assignment of soil microbes and in their response to watering. It also provides new avenues for improving biotic and abiotic resistance in domestic plant germplasm via the manipulation of soil microbes.

The large family of enzymes, known as polyphenols oxidases, includes laccase. Due to the inclusion of a copper atom in their catalytic core, laccases are frequently referred to as multi-copper oxidases. Laccases are versatile enzymes that can catalyze the oxidation of a wide range of phenolic and non-phenolic substances. In the current study, a local strain of Aspergillus niger was used for solid-state fermentation to produce fungal laccase, as well as purify and optimize laccase. The enzyme profile, which was acquired using guaiacol to measure enzyme activity, showed that after five days of incubation, wheat straw provided the highest level of laccase activity, or 2.551 U/mL. A technique called response surface methodology (RSM) was used to examine the effects of various conditions on the production of enzymes. The RSM results demonstrated that after five days of incubation, the enzyme activity was at its highest at 45 °C, pH 5.5, and 30% moisture level, inoculated with 2 mL mycelium. Through ammonium sulphate precipitation and dialysis, the enzyme was purified. Additionally, column chromatography was used to further purify laccase. The next step was enzyme characterization to evaluate how temperature and pH affected enzyme activity. At 45 °C and pH 5.5, the isolated enzyme produced its highest level of activity. The findings of the current study showed that A. niger is capable of producing laccase in an economical and environmentally friendly way. Due to its unique oxidative and catalytic features, this enzyme has received a lot of attention recently.

A wide range of histological as well as clinical properties are exhibited by B-cell non-Hodgkin’s lymphomas. These properties could make the diagnostics process complicated. The diagnosis of lymphomas at an initial stage is essential because early remedial actions taken against destructive subtypes are commonly deliberated as successful and restorative. Therefore, better protective action is needed to improve the condition of those patients who are extensively affected by cancer when diagnosed for the first time. The development of new and efficient methods for early detection of cancer has become crucial nowadays. Biomarkers are urgently needed for diagnosing B-cell non-Hodgkin’s lymphoma and assessing the severity of the disease and its prognosis. New possibilities are now open for diagnosing cancer with the help of metabolomics. The study of all the metabolites synthesised in the human body is called “metabolomics.” A patient’s phenotype is directly linked with metabolomics, which can help in providing some clinically beneficial biomarkers and is applied in the diagnostics of B-cell non-Hodgkin’s lymphoma. In cancer research, it can analyse the cancerous metabolome to identify the metabolic biomarkers. This review provides an understanding of B-cell non-Hodgkin’s lymphoma metabolism and its applications in medical diagnostics. A description of the workflow based on metabolomics is also provided, along with the benefits and drawbacks of various techniques. The use of predictive metabolic biomarkers for the diagnosis and prognosis of B-cell non-Hodgkin’s lymphoma is also explored. Thus, we can say that abnormalities related to metabolic processes can occur in a vast range of B-cell non-Hodgkin’s lymphomas. The metabolic biomarkers could only be discovered and identified as innovative therapeutic objects if we explored and researched them. In the near future, the innovations involving metabolomics could prove fruitful for predicting outcomes and bringing out novel remedial approaches.

The functional processes and mutual benefits of the wild plant Moringa oleifera and its rhizosphere microbiome were studied via metagenomic whole-genome shotgun sequencing (mWGS) in comparison with a bulk soil microbiome. The results indicated high gene abundance of the four KEGG categories, “Cellular Processes”, “Environmental Information Processing”, “Genetic Information Processing”, and “Metabolism”, in the rhizosphere microbiome. Most of the enriched enzymes in rhizobacteria are assigned to the pathway “Amino acids metabolism”, where soil-dwelling microbes use amino acids as a defense mechanism against phytopathogens, while promoting growth, colonizing the cohabiting commensal microbes and conferring tolerance against abiotic stresses. In the present study, it was proven that these beneficial microbes include Bacillus subtilis, Pseudomonas fluorescens, and Escherichia coli. Mineral solubilization in these rhizobacteria can make nutrients available for plant utilization. These rhizobacteria extensively synthesize and metabolize amino acids at a high rate, which makes nitrogen available in different forms for plants and microbes. Amino acids in the rhizosphere might stand mainly as an intermediate switcher for the direction of the soil nitrogen cycle. Indole acetic acid (IAA) was proven to be synthesized by these beneficial rhizobacteria via route indole-3-pyruvate (IPyA) of the pathway “Tryptophan metabolism”. This hormone might stand as a shuttle signaling molecule between M. oleifera and its rhizobacteria. Tryptophan is also metabolized to promote other processes with important industrial applications. Rhizobacteria were also proven to breakdown starch and sucrose into glucose, which is the primary metabolic fuel of living organisms. In conclusion, we assume that the metabolic processes in the rhizosphere microbiome of this wild plant can be eventually utilized in boosting the sustainability of agriculture applications and the plant’s ability to benefit from soil nutrients when they are not in the form available for plant root absorption.

Quorum sensing inhibitor (QSI) has been attracting attention as anti-virulence agent which disarms pathogens of their virulence rather than killing them. QSI marking cyclic peptide-mediated QS in Gram-positive bacteria is an effective tool to overcome the crisis of antibiotic-dependent chemotherapy due to the emergence of drug resistance strain, e.g., methicillin resistant Staphylococcus aureus (MRSA) and Vancomycin resistant Enterococci (VRE). From a semi-large-scale screening thus far carried out, two Epoxide compounds, Ambuic acid and Synerazol, have been found to efficiently block agr and fsr QS systems, suggesting that the Epoxide group is involved in the mode of action of these QSIs. To address this notion, known natural Epoxide compounds, Cerulenin and Fosfomycin were examined for QSI activity for the agr and fsr systems in addition to in silico and SAR studies. As a result, most of investigated Epoxide containing antibiotics correlatively interfere with QSI activity for the agr and fsr systems under sublethal concentrations.

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.