Inhibition of Pro-Inflammatory Cytokines by Metabolites of Streptomycetes-A Potential Alternative to Current Anti-Inflammatory Drugs?

Pakpahan N, Sitohang AI, Sukarno MA, Yuandani, Harahap Y, Setyowati EP, Park MN, Yusoff SD, Zainalabidin S, Prananda AT, Mahadi MK, Kim B, Harahap U, Syahputra RA. In-depth analysis of lupeol: delving into the diverse pharmacological profile

Lupeol, a naturally occurring lupane-type pentacyclic triterpenoid, is widely distributed in various edible vegetables, fruits, and medicinal plants. Notably, it is found in high concentrations in plants like Tamarindus indica, Allanblackia monticola, and Emblica officinalis, among others. Quantitative studies have highlighted its presence in Elm bark, Olive fruit, Aloe leaf, Ginseng oil, Mango pulp, and Japanese Pear bark. This compound is synthesized from squalene through the mevalonate pathway and can also be synthetically produced in the lab, addressing challenges in natural product synthesis. Over the past four decades, extensive research has demonstrated lupeol's multifaceted pharmacological properties, including anti-inflammatory, antioxidant, anticancer, and antibacterial effects. Despite its significant therapeutic potential, clinical applications of lupeol have been limited by its poor water solubility and bioavailability. Recent advancements have focused on nano-based delivery systems to enhance its bioavailability, and the development of various lupeol derivatives has further amplified its bioactivity. This review provides a comprehensive overview of the latest advancements in understanding the pharmacological benefits of lupeol. It also discusses innovative strategies to improve its bioavailability, thereby enhancing its clinical efficacy. The aim is to consolidate current knowledge and stimulate further research into the therapeutic potential of lupeol and its derivatives.

Characterization and Bioactive Metabolite Profiling of Streptomyces sp. Y009: A Mangrove-Derived Actinomycetia with Anticancer and Antioxidant Potential

Microorganisms from poorly explored environments are promising sources for the development of novel drugs. In our continuous efforts to screen for mangrove actinomycetes that produce metabolites with potential pharmaceutical applications, Streptomyces sp. Y009 was isolated from mangrove sediments in Guangxi, China. The phenotypic, physiological, biochemical, and phylogenetic characteristics of this strain were investigated. Analysis of phylogenetic and 16S rRNA gene sequences showed that it had the highest sequence similarity to Streptomyces thermolilacinus NBRC 14274 (98.95%). Further, the Y009 extract exhibited antioxidant activity, as indicated by DPPH and superoxide dismutase assays. The extract showed broad-spectrum and potent anticancer potential against six human cancer cell lines, with IC50 values ranging from 5.61 to 72.15 μg/mL. Furthermore, the selectivity index (SI) demonstrated that the Y009 extract exhibited less toxicity toward normal cell lines in comparison to the lung cancer cell line (A549) and hepatoma cell line (HepG2). GC-MS analysis revealed that the extract contained some biologically important secondary metabolites, mainly cyclic dipeptides and esters, which might be responsible for the antioxidant and anticancer properties. 3-Isobutylhexahydropyrrolo[1,2-a]pyrazine-1,4-dione (28.32%) was the major chemical compound available in the extract. The effect on cancer cells was then confirmed using nuclear staining and in silico docking. This study suggests that further exploration of the bioactive compounds of the newly isolated strain may be a promising approach for the development of novel chemopreventive drugs.

Microbial natural compounds and secondary metabolites as Immunomodulators: A review

Immunomodulatory therapies are beneficial strategies for the improvement of immune system function. Today, due to the increasing prevalence of immune disorders, cancer, and new viral diseases, there is a greater need to introduce immunomodulatory compounds with more efficiency and fewer side effects. Microbial derivatives are fertile and attractive grounds for discovering lots of novel compounds with various medical properties. The discovery of many natural compounds derived from bacterial sources, such as secondary metabolites with promising immunomodulating activities, represents the importance of this topic in drug discovery and emphasizes the necessity for a coherent source of study in this area. Considering this need, in this review, we aim to focus on the current information about the immunomodulatory effects of bacterial secondary metabolites and natural immunomodulators derived from microorganisms.

Elucidation of the Late Steps during Hexacosalactone A Biosynthesis in Streptomyces samsunensis OUCT16-12

Hexacosalactone A (1) is a polyene macrolide compound featuring a 2-amino-3-hydroxycyclopent-2-enone (C5N)-fumaryl moiety. While compound 1 has been proposed to be assembled via a type I modular polyketide synthase (PKS) system, most of the putative biosynthetic steps lack experimental evidence. In this study, we elucidated the post-PKS tailoring steps of compound 1 through in vivo gene inactivation and in vitro biochemical assays. We demonstrated that the amide synthetase HexB and O-methyltransferase HexF are responsible for the installations of the C5N moiety and the methyl group at 15-OH of compound 1, respectively; two new hexacosalactone analogs, named hexacosalactones B (4) and C (5), were purified and structurally characterized, followed by anti-multidrug resistance (anti-MDR) bacterial assays, revealing that the C5N ring and the methyl group are necessary for the antibacterial bioactivities. Through database mining of C5N-forming proteins HexABC, six uncharacterized biosynthetic gene clusters (BGCs), putatively encoding compounds with different types of backbones, were identified, providing potentials to discover novel bioactive compounds with C5N moiety. IMPORTANCE In this study, we elucidate the post-PKS tailoring steps during the biosynthesis of compound 1 and demonstrate that both C5N and 15-OMe groups are critical for the antibacterial activities of compound 1, paving the way for generation of hexacosalactone derivatives via synthetic biology strategy. In addition, mining of HexABC homologs from the GenBank database revealed their wide distribution across the bacterial world, facilitating the discovery of other bioactive natural products with C5N moiety.

Streptomyces: The biofactory of secondary metabolites

Natural products derived from microorganisms serve as a vital resource of valuable pharmaceuticals and therapeutic agents. Streptomyces is the most ubiquitous bacterial genus in the environments with prolific capability to produce diverse and valuable natural products with significant biological activities in medicine, environments, food industries, and agronomy sectors. However, many natural products remain unexplored among Streptomyces. It is exigent to develop novel antibiotics, agrochemicals, anticancer medicines, etc., due to the fast growth in resistance to antibiotics, cancer chemotherapeutics, and pesticides. This review article focused the natural products secreted by Streptomyces and their function and importance in curing diseases and agriculture. Moreover, it discussed genomic-driven drug discovery strategies and also gave a future perspective for drug development from the Streptomyces.

Activation of a Cryptic Manumycin-Type Biosynthetic Gene Cluster of Saccharothrix espanaensis DSM44229 by Series of Genetic Manipulations

(1) Background: Manumycins are small actinomycete polyketides with prominent cancerostatic and immunosuppressive activities via inhibition of various eukaryotic enzymes. Their overall activity towards human cells depends on the structural variability of both their polyketide chains, mainly the upper one. In our genetic screening project to find novel producers of anti-inflammatory manumycins, the strain Saccharothrix espanaensis DSM44229 was identified as containing a novel manumycin-type biosynthetic gene cluster (BGC). (2) Methods: The biosynthetic genes appeared to be silent under all assayed laboratory conditions. Several techniques were used to activate the BGC, including: (i) heterologous expression in various hosts, (ii) overexpression of putative pathway-specific regulatory genes, and (iii) overexpression of a bottleneck cyclizing aminolevulinate synthase gene in both natural and heterologous producers. (3) Results: Multiple novel manumycin-type compounds were produced at various levels by genetically-modified strains, sharing a tetraene lower chain structure with a colabomycin subgroup of manumycins, but possessing much shorter and saturated upper chains. (4) Conclusions: A cryptic manumycin-type BGC was successfully activated by genetic means to gain production of novel manumycin-type compounds for future comparative activity assays. Heterologously produced compounds were identical to those found after final activation of the BGC in the original strain, proving the intactness of the cloned BGC.

The application potential of machine learning and genomics for understanding natural product diversity, chemistry, and therapeutic translatability

Covering: up to the end of 2020. The machine learning field can be defined as the study and application of algorithms that perform classification and prediction tasks through pattern recognition instead of explicitly defined rules. Among other areas, machine learning has excelled in natural language processing. As such methods have excelled at understanding written languages (e.g. English), they are also being applied to biological problems to better understand the "genomic language". In this review we focus on recent advances in applying machine learning to natural products and genomics, and how those advances are improving our understanding of natural product biology, chemistry, and drug discovery. We discuss machine learning applications in genome mining (identifying biosynthetic signatures in genomic data), predictions of what structures will be created from those genomic signatures, and the types of activity we might expect from those molecules. We further explore the application of these approaches to data derived from complex microbiomes, with a focus on the human microbiome. We also review challenges in leveraging machine learning approaches in the field, and how the availability of other "omics" data layers provides value. Finally, we provide insights into the challenges associated with interpreting machine learning models and the underlying biology and promises of applying machine learning to natural product drug discovery. We believe that the application of machine learning methods to natural product research is poised to accelerate the identification of new molecular entities that may be used to treat a variety of disease indications.