Exploring Cereal Metagenomics: Unravelling Microbial Communities for Improved Food Security.

Food security is an urgent global challenge, with cereals playing a crucial role in meeting the nutritional requirements of populations worldwide. In recent years, the field of metagenomics has emerged as a powerful tool for studying the microbial communities associated with cereal crops and their impact on plant health and growth. This chapter aims to provide a comprehensive overview of cereal metagenomics and its role in enhancing food security through the exploration of beneficial and pathogenic microbial interactions. Furthermore, we will examine how the integration of metagenomics with other tools can effectively address the adverse effects on food security. For this purpose, we discuss the integration of metagenomic data and machine learning in providing novel insights into the dynamic interactions shaping plant-microbe relationships. We also shed light on the potential applications of leveraging microbial diversity and epigenetic modifications in improving crop resilience and yield sustainability. Ultimately, cereal metagenomics has revolutionized the field of food security by harnessing the potential of beneficial interactions between cereals and their microbiota, paving the way for sustainable agricultural practices.

Analysis of the bacterial and fungal populations in South African sorghum beer (umqombothi) using full-length 16S rRNA amplicon sequencing.

There is a need to profile microorganisms which exist pre-and-post-production of umqombothi, to understand its microbial diversity and the interactions which subsequently influence the final product. Thus, this study sought to determine the relative microbial abundance in umqombothi and predict the functional pathways of bacterial and fungal microbiota present. Full-length bacterial 16S rRNA and internal transcribed spacer (ITS) gene sequencing using PacBio single-molecule, real-time (SMRT) technology was used to assess the microbial compositions. PICRUSt2 was adopted to infer microbial functional differences. A mixture of harmful and beneficial microorganisms was observed in all samples. The microbial diversity differed significantly between the mixed raw ingredients (MRI), customary beer brew (CB), and optimised beer brew (OPB). The highest bacterial species diversity was observed in the MRI, while the highest fungal species diversity was observed in the OPB. The dominant bacterial species in the MRI, CB, and OPB were Kosakonia cowanii, Apilactobacillus pseudoficulneus, and Vibrio alginolyticus, respectively, while the dominant fungal species was Apiotrichum laibachii. The predicted functional annotations revealed significant (p < 0.05) differences in the microbial pathways of the fermented and unfermented samples. The most abundant pathways in the MRI were the branched-chain amino acid biosynthesis super pathway and the pentose phosphate pathway. The CB sample was characterised by folate (vitamin B9) transformations III, and mixed acid fermentation. Biotin (vitamin B7) biosynthesis I and L-valine biosynthesis characterised the OPB sample. These findings can assist in identifying potential starter cultures for the commercial production of umqombothi. Specifically, A. pseudoficulneus can be used for controlled fermentation during the production of umqombothi. Likewise, the use of A. laibachii can allow for better control over the fermentation kinetics such as carbohydrate conversion and end-product characteristics, especially esters and aroma compounds.

Physicochemical Properties and Bacterial Community Profiling of Optimal Mahewu (A Fermented Food Product) Prepared Using White and Yellow Maize with Different Inocula.

Mahewu is a fermented food product from maize, commonly consumed in Southern Africa. This study investigated the effect of optimizing fermentation (time and temperature) and boiling time of white maize (WM) and yellow maize (YM) mahewu, with the use of the Box-Behnken-response surface methodology (RSM). Fermentation time and temperature as well as boiling time were optimized and pH, total titratable acidity (TTA) and total soluble solids (TSS) determined. Results obtained showed that the processing conditions significantly (p ≤ 0.05) influenced the physicochemical properties. pH values of the mahewu samples ranged between 3.48-5.28 and 3.50-4.20 for YM mahewu and WM mahewu samples, respectively. Reduction in pH values after fermentation coincided with an increase in TTA as well as changes in the TSS values. Using the numerical multi-response optimisation of three investigated responses the optimal fermentation conditions were observed to be 25 °C for 54 h and a boiling time of 19 min for white maize mahewu and 29 °C for 72 h and a boiling time of 13 min for yellow maize mahewu. Thereafter white and yellow maize mahewu were prepared with the optimized conditions using different inocula (sorghum malt flour, wheat flour, millet malt flour or maize malt flour) and the pH, TTA and TSS of the derived mahewu samples determined. Additionally, amplicon sequencing of the 16S rRNA gene was used to characterise the relative abundance of bacterial genera in optimized mahewu samples, malted grains as well as flour samples. Major bacterial genera observed in the mahewu samples included Paenibacillus, Stenotrophomonas, Weissella, Pseudomonas, Lactococcus, Enterococcus, Lactobacillus, Bacillus, Massilia, Clostridium sensu stricto 1, Streptococcus, Staphylococcus, Sanguibacter, Roseococcus, Leuconostoc, Cutibacterium, Brevibacterium, Blastococcus, Sphingomonas and Pediococcus, with variations noted for YM mahewu and WM mahewu. As a result, the variations in physicochemical properties are due to differences in maize type and modification in processing conditions. This study also discovered the existence of variety of bacterial that can be isolated for controlled fermentation of mahewu.