NMR-Based Metabolomic Analysis and Microbial Composition of Soil Supporting Burkea africana Growth

Soil metabolomics: Deciphering underground metabolic webs in terrestrial ecosystems

Soil metabolomics is an emerging approach for profiling diverse small molecule metabolites, i.e., metabolomes, in the soil. Soil metabolites, including fatty acids, amino acids, lipids, organic acids, sugars, and volatile organic compounds, often contain essential nutrients such as nitrogen, phosphorus, and sulfur and are directly linked to soil biogeochemical cycles driven by soil microorganisms. This paper presents an overview of methods for analyzing soil metabolites and the state-of-the-art of soil metabolomics in relation to soil nutrient cycling. We describe important applications of metabolomics in studying soil carbon cycling and sequestration, and the response of soil organic pools to changing environmental conditions. This includes using metabolomics to provide new insights into the close relationships between soil microbiome and metabolome, as well as responses of soil metabolome to plant and environmental stresses such as soil contamination. We also highlight the advantage of using soil metabolomics to study the biogeochemical cycles of elements and suggest that future research needs to better understand factors driving soil function and health.

Evaluating the Metabolomic Profile and Anti-Pathogenic Properties of Cannabis Species

The Cannabis species is one of the potent ancient medicinal plants acclaimed for its medicinal properties and recreational purposes. The plant parts are used and exploited all over the world for several agricultural and industrial applications. For many years Cannabis spp. has proven to present a highly diverse metabolomic profile with a pool of bioactive metabolites used for numerous pharmacological purposes ranging from anti-inflammatory to antimicrobial. Cannabis sativa has since been an extensive subject of investigation, monopolizing the research. Hence, there are fewer studies with a comprehensive understanding of the composition of bioactive metabolites grown in different environmental conditions, especially C. indica and a few other Cannabis strains. These pharmacological properties are mostly attributed to a few phytocannabinoids and some phytochemicals such as terpenoids or essential oils which have been tested for antimicrobial properties. Many other discovered compounds are yet to be tested for antimicrobial properties. These phytochemicals have a series of useful properties including anti-insecticidal, anti-acaricidal, anti-nematicidal, anti-bacterial, anti-fungal, and anti-viral properties. Research studies have reported excellent antibacterial activity against Gram-positive and Gram-negative multidrug-resistant bacteria as well as methicillin-resistant Staphylococcus aureus (MRSA). Although there has been an extensive investigation on the antimicrobial properties of Cannabis, the antimicrobial properties of Cannabis on phytopathogens and aquatic animal pathogens, mostly those affecting fish, remain under-researched. Therefore, the current review intends to investigate the existing body of research on metabolomic profile and anti-microbial properties whilst trying to expand the scope of the properties of the Cannabis plant to benefit the health of other animal species and plant crops, particularly in agriculture.

1H NMR-Based Metabolomics Profile of Green and Red Amaranthus Grown in Open Field versus Greenhouse Cultivation System

Traditionally, indigenous African leafy vegetables such as Amaranthus, blackjack, jute mallow, cleome monophyla, and spider plants have been conventionally and organically grown as weeds in open fields. However, the lack of land space due to the increase in population has resulted in unconventional, modern, and advanced agricultural farming. The introduction of a greenhouse has recently become the second most popular growing system alongside shade net and glasshouse to increase productivity and meet consumers' demand. Several studies on Amaranthus species have solely focused on physiological parameters and nutritional composition, leaving a huge gap on their metabolomic profile of the leaves which is crucial to comprehend when growing Amaranthus species in different cropping systems. Therefore, the study aimed to determine the influence of different cropping systems on the release of metabolites of two commonly consumed Amaranthus species in South Africa. H1 -Nuclear Magnetic Resonance (NMR) tool was used to profile the untargeted metabolites of green (Amaranthus graecizans L.) and red (Amaranthus cruentus L.) species. A total of 12 metabolites-trehalose, betaine, glutamine, choline, sucrose, caprate, adenosine, asparagine, carnitine, caffeine, aspartate, and alanine-were detected in green amaranth grown in open fields. Except for caffeine, aspartate, and caprate, which were found in the green amaranth grown in open fields, all the other metabolites were detected in the greenhouse grown once. Interestingly, allantoin, which serves as an allelochemical, was the sole distinct metabolite detected in greenhouse cultivated green amaranth. On the contrary, seven similar metabolites were quantified in red amaranth grown in both open fields and greenhouses, apart from caffeine, which was only detected in greenhouse-cultivated red amaranth.

A New Proposed Symbiotic Plant-Herbivore Relationship between Burkea africana Trees, Cirina forda Caterpillars and Their Associated Fungi Pleurostomophora richardsiae and Aspergillus nomius

Burkea africana is a tree found in savannah and woodland in southern Africa, as well as northwards into tropical African regions as far as Nigeria and Ethiopia. It is used as fuel wood, medicinally to treat various conditions, such as toothache, headache, migraine, pain, inflammation, and sexually transmitted diseases, such as gonorrhoea, but also an ornamental tree. The current study investigated the possible symbiotic relationship between B. africana trees and the C. forda caterpillars and the mutual role played in ensuring the survival of B. africana trees/seedlings in harsh natural conditions and low-nutrient soils. Deoxyribonucleic acid isolation and sequencing results revealed that the fungal species Pleurostomophora richardsiae was highly predominant in the leaves of B. africana trees and present in the caterpillars. The second most prominent fungal species in the caterpillars was Aspergillus nomius. The latter is known to be related to a Penicillium sp. which was found to be highly prevalent in the soil where B. africana trees grow and is suggested to play a role in enhancing the effective growth of B. africana trees in their natural habitat. To support this, a phylogenetic analysis was conducted, and a tree was constructed, which shows a high percentage similarity between Aspergillus and Penicillium sp. The findings of the study revealed that B. africana trees not only serve as a source of feed for the C. forda caterpillar but benefit from C. forda caterpillars which, after dropping onto the soil, is proposed to inoculate the soil surrounding the trees with the fungus A. nomius which suggests a symbiotic and/or synergistic relationship between B. africana trees and C. forda caterpillars.

The Use of Gonimbrasia belina (Westwood, 1849) and Cirina forda (Westwood, 1849) Caterpillars (Lepidoptera: Sarturniidae) as Food Sources and Income Generators in Africa

Gonimbrasia belina (mopane worm) and Cirina forda caterpillars (Lepidoptera: Saturniidae) are mostly found in shrubs and trees, from where they are collected as larvae and are widely consumed across southern Africa by rural and increasingly urban populations. These caterpillars are among the most prominent, traded, and economically beneficial edible insects found in Western African countries, but also in South Africa, Zimbabwe, Botswana, and the Democratic Republic of the Congo. Over the years, these caterpillars have evolved from being part of the diet in various communities to playing a vital role in income generation. In addition, consumption of G. belina and C. forda caterpillars as potential food sources has gained momentum due to their potential for contributing to livelihoods and mitigating food security challenges across Africa while providing significant benefits to developing countries on a socio-economic and ecological level. Edible caterpillars serve as a good source of rich nutrients such as proteins, fatty acids, and micronutrients and can be used in formulating nutrient-dense complementary foods. However, limited information is available, specifically on different trees that serve as hosts to these caterpillars, as they depend on the leaves as their only source of food. In addition, the review aims to critique and document knowledge on the nutritional benefits, acceptance of the use of these caterpillars as food security, commercial value, and level of acceptance towards the utilization of caterpillars as food sources.

Tapping into Plant-Microbiome Interactions through the Lens of Multi-Omics Techniques

This review highlights the pivotal role of root exudates in the rhizosphere, especially the interactions between plants and microbes and between plants and plants. Root exudates determine soil nutrient mobilization, plant nutritional status, and the communication of plant roots with microbes. Root exudates contain diverse specialized signaling metabolites (primary and secondary). The spatial behavior of these metabolites around the root zone strongly influences rhizosphere microorganisms through an intimate compatible interaction, thereby regulating complex biological and ecological mechanisms. In this context, we reviewed the current understanding of the biological phenomenon of allelopathy, which is mediated by phytotoxic compounds (called allelochemicals) released by plants into the soil that affect the growth, survival, development, ecological infestation, and intensification of other plant species and microbes in natural communities or agricultural systems. Advances in next-generation sequencing (NGS), such as metagenomics and metatranscriptomics, have opened the possibility of better understanding the effects of secreted metabolites on the composition and activity of root-associated microbial communities. Nevertheless, understanding the role of secretory metabolites in microbiome manipulation can assist in designing next-generation microbial inoculants for targeted disease mitigation and improved plant growth using the synthetic microbial communities (SynComs) tool. Besides a discussion on different approaches, we highlighted the advantages of conjugation of metabolomic approaches with genetic design (metabolite-based genome-wide association studies) in dissecting metabolome diversity and understanding the genetic components of metabolite accumulation. Recent advances in the field of metabolomics have expedited comprehensive and rapid profiling and discovery of novel bioactive compounds in root exudates. In this context, we discussed the expanding array of metabolomics platforms for metabolome profiling and their integration with multivariate data analysis, which is crucial to explore the biosynthesis pathway, as well as the regulation of associated pathways at the gene, transcript, and protein levels, and finally their role in determining and shaping the rhizomicrobiome.

Metabolomics and modelling approaches for systems metabolic engineering

Metabolic engineering involves the manipulation of microbes to produce desirable compounds through genetic engineering or synthetic biology approaches. Metabolomics involves the quantitation of intracellular and extracellular metabolites, where mass spectrometry and nuclear magnetic resonance based analytical instrumentation are often used. Here, the experimental designs, sample preparations, metabolite quenching and extraction are essential to the quantitative metabolomics workflow. The resultant metabolomics data can then be used with computational modelling approaches, such as kinetic and constraint-based modelling, to better understand underlying mechanisms and bottlenecks in the synthesis of desired compounds, thereby accelerating research through systems metabolic engineering. Constraint-based models, such as genome scale models, have been used successfully to enhance the yield of desired compounds from engineered microbes, however, unlike kinetic or dynamic models, constraint-based models do not incorporate regulatory effects. Nevertheless, the lack of time-series metabolomic data generation has hindered the usefulness of dynamic models till today. In this review, we show that improvements in automation, dynamic real-time analysis and high throughput workflows can drive the generation of more quality data for dynamic models through time-series metabolomics data generation. Spatial metabolomics also has the potential to be used as a complementary approach to conventional metabolomics, as it provides information on the localization of metabolites. However, more effort must be undertaken to identify metabolites from spatial metabolomics data derived through imaging mass spectrometry, where machine learning approaches could prove useful. On the other hand, single-cell metabolomics has also seen rapid growth, where understanding cell-cell heterogeneity can provide more insights into efficient metabolic engineering of microbes. Moving forward, with potential improvements in automation, dynamic real-time analysis, high throughput workflows, and spatial metabolomics, more data can be produced and studied using machine learning algorithms, in conjunction with dynamic models, to generate qualitative and quantitative predictions to advance metabolic engineering efforts.

Isolation, Characterization, and Metabolic Profiling of Ceratorhiza hydrophila from the Aquatic Plant Myriophyllum spicatum

The goal of the present study was to investigate the antibacterial properties, enzyme production, and metabolic profiling of a new Ceratorhiza hydrophila strain isolated from the submerged aquatic plant Myriophyllum spicatum. Furthermore, the fungus' morphological characterization and DNA sequencing have been described. The fungus has been identified and submitted to the GenBank as Ceratorhiza hydrophila isolate EG19 and the fungus ID is MK387081. The enzyme analyses showed its ability to produce protease and cellulase enzymes. According to the CSLI standard, the ethyl acetate extract of C. hydrophila showed intermediate antibacterial activity against Streptococcus pneumonia, Micrococcus luteus, and Staphylococcus aureus. Metabolic profiling has been carried out using 700 MHz NMR spectroscopy. Based on the ¹H and ¹H-¹³C heteronuclear single quantum coherence (HSQC) NMR data and NMR databases, 23 compounds have been identified. The identified metabolites include 31% amino acids, 9% sugars, 9% amines, 4% sugar alcohols, and 4% alkaloids. This is the first report for the metabolic characterization of C. hydrophila, which gave preliminary information about the fungus. It is expected that our findings not only will pave the way to other perspectives in enormous applications using C. hydrophila as a new promising source of antimicrobial agents and essential metabolites, but also it will be valuable in the classification and chemotaxonomy of the species.