Photosynthetic light-harvesting antennae are pigment-binding proteins that perform one of the most fundamental tasks on Earth, capturing light and transferring energy that enables life in our biosphere. Adaptation to different light environments led to the evolution of an astonishing diversity of light-harvesting systems. At the same time, several strategies have been developed to optimize the light energy input into photosynthetic membranes in response to fluctuating conditions. The basic feature of these prompt responses is the dynamic nature of antenna complexes, whose function readily adapts to the light available. High-resolution microscopy and spectroscopic studies on membrane dynamics demonstrate the crosstalk between antennae and other thylakoid membrane components. With the increased understanding of light-harvesting mechanisms and their regulation, efforts are focusing on the development of sustainable processes for effective conversion of sunlight into functional bio-products. The major challenge in this approach lies in the application of fundamental discoveries in light-harvesting systems for the improvement of plant or algal photosynthesis. Here, we underline some of the latest fundamental discoveries on the molecular mechanisms and regulation of light harvesting that can potentially be exploited for the optimization of photosynthesis.

Cryptophycin-1 is a cyanotoxin produced by filamentous cyanobacteria. It has been evaluated as an anticancer agent with great potential. However, its synthesis provides insufficient yield for industrial use. An alternative solution for metabolite efficient production is to stress cyanobacteria by modifying the environmental conditions of the culture (Nostoc sp. ATCC 53789). Here, we examined the effects of light photoperiod, wavelength, and intensity. In light photoperiod, photoperiods 24:0 and 16:8 (light:dark) were tested while in wavelength, orange-red light was compared with blue. Medium, high, and very high light intensity experiments were performed to test the effect of light stress. For a 10-day period, growth was measured, metabolite concentration was calculated through HPLC, and the related curves were drawn. The differentiation of light wavelength had a major effect on the culture, as orange-red filter contributed to noticeable increase in both growth and doubled the cyanotoxin concentration in comparison to blue light. Remarkably, constant light provides higher cryptophycin yield, but slightly lower growth rate. Lastly, the microorganism prefers medium light intensities for both growth and metabolite expression. The combination of these optimal conditions would contribute to the further exploitation of cryptophycin.

Feature-Based Molecular Networking (FBMN) is a popular analysis approach for LC-MS/MS-based non-targeted metabolomics data. While processing LC-MS/MS data through FBMN is fairly streamlined, downstream data handling and statistical interrogation is often a key bottleneck. Especially, users new to statistical analysis struggle to effectively handle and analyze complex data matrices. In this protocol, we provide a comprehensive guide for the statistical analysis of FBMN results. We explain the data structure and principles of data clean-up and normalization, as well as uni- and multivariate statistical analysis of FBMN results. We provide explanations and code in two scripting languages (R and Python) as well as the QIIME2 framework for all protocol steps, from data clean-up to statistical analysis. Additionally, the protocol is accompanied by a web application with a graphical user interface (https://fbmn-statsguide.gnps2.org/), to lower the barrier of entry for new users. Together, the protocol, code, and web app provide a complete guide and toolbox for FBMN data integration, clean-up, and advanced statistical analysis, enabling new users to uncover molecular insights from their non-targeted metabolomics data. Our protocol is tailored for the seamless analysis of FBMN results from Global Natural Products Social Molecular Networking (GNPS and GNPS2) and can be adapted to other MS feature detection, annotation, and networking tools.

Dacryodes Vahl. species, belonging to the Burseraceae family, are widely used in traditional medicine in tropical regions to treat a range of ailments including malaria, wounds, tonsillitis, and ringworms. This review discusses the distribution, ethnobotanical uses, phytochemistry, and bioactivities of Dacryodes species. The intent is to spur future research into isolating and identifying key active principles, secondary metabolites, and crude extracts, and evaluating their pharmacological and toxicological effects, as well as the mechanism of actions to understand their medicinal benefits. A systematic review of scientific electronic databases from 1963 to 2022 including Scifinder, Scopus, Pubmed, Springer Link, ResearchGate, Ethnobotany Research and Applications, Google Scholar, and ScienceDirect was conducted with a focus on Dacryodes edulis (G.Don) H.J. Lam and Dacryodes rostrata (Blume) H.J. Lam. Pharmacological data revealed that D. edulis isolates contain secondary metabolites and other phytochemical groups belonging to the terpenoids class with anti-microbial, anticancer, antidiabetic, antiinflammatory and hepatoprotective activities, highlighting its pharmacological potential in the therapy or management of diverse cancers, cardiovascular, and neurological diseases. Thus, phytochemicals and standardized extracts from D. edulis could offer safer and cost-effective chemopreventive and chemotherapeutic health benefits/regimen, or as alternative therapeutic remedy for several human diseases. Nevertheless, the therapeutic potential of most of the plants in the genus have not been exhaustively explored with regard to phytochemistry and pharmacology, but mostly complementary approaches lacking rigorous, scientific research-based knowledge. Therefore, the therapeutic potentials of the Dacryodes genus remain largely untapped, and comprehensive research is necessary to fully harness their medicinal properties.

While anthropogenic pollution is a major threat to aquatic ecosystem health, our knowledge of the presence of xenobiotics in coastal Dissolved Organic Matter (DOM) is still relatively poor. This is especially true for water bodies in the Global South with limited information gained mostly from targeted studies that rely on comparison with authentic standards. In recent years, non-targeted tandem mass spectrometry has emerged as a powerful tool to collectively detect and identify pollutants and biogenic DOM components in the environment, but this approach has yet to be widely utilized for monitoring ecologically important aquatic systems. In this study we compared the DOM composition of Algoa Bay, Eastern Cape, South Africa, and its two estuaries. The Swartkops Estuary is highly urbanized and severely impacted by anthropogenic pollution, while the Sundays Estuary is impacted by commercial agriculture in its catchment. We employed solid-phase extraction followed by liquid chromatography tandem mass spectrometry to annotate more than 200 pharmaceuticals, pesticides, urban xenobiotics, and natural products based on spectral matching. The identification with authentic standards confirmed the presence of methamphetamine, carbamazepine, sulfamethoxazole, N-acetylsulfamethoxazole, imazapyr, caffeine and hexa(methoxymethyl)melamine, and allowed semi-quantitative estimations for annotated xenobiotics. The Swartkops Estuary DOM composition was strongly impacted by features annotated as urban pollutants including pharmaceuticals such as melamines and antiretrovirals. By contrast, the Sundays Estuary exhibited significant enrichment of molecules annotated as agrochemicals widely used in the citrus farming industry, with predicted concentrations for some of them exceeding predicted no-effect concentrations. This study provides new insight into anthropogenic impact on the Algoa Bay system and demonstrates the utility of non-targeted tandem mass spectrometry as a sensitive tool for assessing the health of ecologically important coastal ecosystems and will serve as a valuable foundation for strategizing long-term monitoring efforts.