Ruqaia Al Shami

Emerging from millions of years of evolutionary optimization, Natural products (NPs) remain unique, unparalleled sources of bioactive scaffolds. Unlike synthetic molecules engineered around single therapeutic targets, NPs often exhibit multi-target, system-level bioactivity, aligned with the principles of network pharmacology, which modulates pathways in a coordinated, non-disruptive manner. This approach reduces resistance, buffers compensatory feedback loops, and enhances therapeutic resilience. Fungal endophytes represent one of the most chemically diverse and biologically sophisticated NP reservoirs known, producing polyketides, alkaloids, terpenoids, and peptides with intricate three-dimensional architectures and emergent bioactivity patterns that remain exceptionally difficult to design de novo. Advances in artificial intelligence (AI), machine learning, deep learning, and multi-omics integration have redefined the discovery landscape, transforming previously intractable fungal metabolomes and cryptic biosynthetic gene clusters (BGCs) into tractable, predictable, and engineerable systems. AI accelerates genome mining, metabolomic annotation, BGC-metabolite linking, structure prediction, and activation of silent pathways. Generative AI and diffusion models now enable de novo design of NP-inspired scaffolds while preserving biosynthetic feasibility, opening new opportunities for direct evolution, pathway refactoring, and precision biomanufacturing. This review synthesizes the chemical and biosynthetic diversity of major NP classes from fungal endophytes and maps them onto the rapidly expanding ecosystem of AI-driven tools. We outline how AI transforms NP discovery from empirical screening into a predictive, hypothesis-driven discipline with direct industrial implications for drug discovery and synthetic biology. By coupling evolutionarily refined chemistry with modern computational intelligence, the field is poised for a new era in which natural-product leads are not only rediscovered but systematically expanded, engineered, and industrialized to address urgent biomedical and sustainability challenges.

Background Climate change is expanding arid regions globally, intensifying drought, salinity, and heat stress that threaten ecosystem stability and food security. Desert plants of the Arabian Peninsula have evolved physiological and microbial adaptations that enable survival under such extremes. This study investigates the endophytic microbial communities of four representative xerophytic species; Zygophyllum mandavillei, Tribulus zeyheri, Limeum arabicum, and Cyperus conglomeratus, to identify functional traits that promote their climatic resilience. These perennial species were selected because they inhabit similar arid environments and share xerophytic traits such as reduced leaf area, fibrous root systems, and high drought tolerance, making them ideal models for examining interactions between plants and their associated microbes in desert ecosystems. Methods High-throughput environmental DNA (eDNA) sequencing was performed on 27 plant samples, generating 3,660,664 high-quality reads. Taxonomic clustering resolved the sequences into 30 phyla, 15 classes, 20 orders, 27 families, and 21 genera. Diversity analyses were conducted to evaluate microbial richness and community structure, and functional inference was performed using PICRUSt2. Results Dominant microbial taxa included Alphaproteobacteria, Actinomycetia, Cyanophyceae, and Gammaproteobacteria, groups known for nitrogen fixation, carbon cycling, and resistance to desiccation and heat. Alpha-diversity analyses revealed significant variation in species richness among the host plants, while beta-diversity metrics showed distinct clustering patterns, indicating host-specific microbial assembly shaped by plant genotype and microhabitat. Functional prediction suggested enrichment of pathways related to amino acid, carbohydrate, and lipid metabolism, oxidative phosphorylation, DNA repair, and secondary-metabolite biosynthesis, supporting metabolic versatility and stress adaptation. Conclusions These findings provide a comprehensive genomic overview of endophytic bacterial communities associated with key desert plants of the Arabian Peninsula and establish a foundation for future functional validation and sustainable applications of desert microbiomes under climate change.

The human body harbors distinct microbial communities at each body site. One microbial niche of particular interest within the human body is the tumor microenvironment. These intratumor microbes are linked to tumor initiation, progression, and metastasis through diverse mechanisms, including activation of oncogenic pathways and modulation of antitumor immunity. Recent studies have emphasized the role of intratumor microbes in influencing the response and outcome of cancer immunotherapeutics and vaccines. Further data suggest a crucial role of microbial metabolites in the metabolic rewiring of CD8+ T cells controlling antitumor immunity. This knowledge is vital to promote our understanding of the role of microbes in the tumor microenvironment and advance translational applications. In this review, we discuss factors that shape the structure of the intratumor microbiome, such as the translocation of gut microbes and the development of local microbial communities. This study highlights the remote control of gut microbes in the tumor microenvironment, disease progression, and therapy outcome. We detail interactions of intratumor microbes and their crosstalk with tumor and immune cells, such as tissue-resident and tumor-infiltrating T cells. We discuss open research questions in this field, including defining oncomicrobiotics, the subset of microbiota with biotherapeutic potential in inducing antitumor immunity. We highlight challenges and opportunities, emphasizing the future direction of developing next-generation engineered probiotics that can advance delivery, maximize the efficacy of cancer therapy, or even serve as a non-invasive technique to sense and detect tumor cells.