Citation: Makhumbila, P.; Rauwane, M.; Muedi, H.; Figlan, S. Metabolome Profiling: A Breeding Prediction Tool for Legume Performance under Biotic Stress Conditions. Plants 2022, 11, 1756. https://doi.org/10.3390/ plants11131756 Academic Editor: Alessandro Vitale Received: 25 May 2022 Accepted: 22 June 2022 Published: 1 July 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). plants Review Metabolome Profiling: A Breeding Prediction Tool for Legume Performance under Biotic Stress Conditions Penny Makhumbila 1, * , Molemi Rauwane 1 , Hangwani Muedi 2 and Sandiswa Figlan 1 1 Department of Agriculture and Animal Health, School of Agriculture and Life Sciences, College of Agriculture and Environmental Sciences, University of South Africa, 28 Pioneer Ave, Florida Park, Roodeport 1709, South Africa; rauwaneme@gmail.com (M.R.); figlas@unisa.ac.za (S.F.) 2 Research Support Services, North West Provincial Department of Agriculture and Rural Development, 114 Chris Hani Street, Potchefstroom 2531, South Africa; hmuedi@nwpg.gov.za * Correspondence: 57994463@mylife.unisa.ac.za Abstract: Legume crops such as common bean, pea, alfalfa, cowpea, peanut, soybean and others contribute significantly to the diet of both humans and animals. They are also important in the improvement of cropping systems that employ rotation and fix atmospheric nitrogen. Biotic stresses hinder the production of leguminous crops, significantly limiting their yield potential. There is a need to understand the molecular and biochemical mechanisms involved in the response of these crops to biotic stressors. Simultaneous expressions of a number of genes responsible for specific traits of interest in legumes under biotic stress conditions have been reported, often with the functions of the identified genes unknown. Metabolomics can, therefore, be a complementary tool to understand the pathways involved in biotic stress response in legumes. Reports on legume metabolomic studies in response to biotic stress have paved the way in understanding stress-signalling pathways. This review provides a progress update on metabolomic studies of legumes in response to different biotic stresses. Metabolome annotation and data analysis platforms are discussed together with future prospects. The integration of metabolomics with other “omics” tools in breeding programmes can aid greatly in ensuring food security through the production of stress tolerant cultivars. Keywords: legumes; metabolomics; biotic stress; stress tolerance; metabolome annotation 1. Introduction Leguminous crops such as Arachis hypogaea (groundnut), Glycine max (soybean), Phaseolus vulgaris (common bean), Pisum sativum (common pea), Cicier arietinum (chickpea), Vigna anguiculata (cowpea), Vicia faba (faba bean), Lens culinaris (lentil), Cajanus cajan (pigeon pea), Lupinus spp. (lupin), and Vigna subterranean (bambara bean) contribute to the improve- ment of ecosystems [1–3], nutrition and food security [4–7]. Although legumes contribute greatly to food security, their production globally is hindered by biotic stresses that include nematodes, viruses, insect pests, and bacterial and fungal pathogens [8–10]. The occurrence of biotic stresses in legume production systems has impacted negatively on production and has resulted in significant yield losses globally [11–13]. In many breeding programmes, the key objective is to develop crop varieties that are adaptable to an array of stressors in order to meet global food demands [14–16], thus addressing sustainable development goals 1 and 2 of the United Nations [17]. Legume programmes have been improving gradually over the years and have advanced from traditional methods of breeding to using genomic tools [18]. Traditional breeding techniques rely mostly on manual selection and the crossing of genotypes with desirable traits, and although these methods have contributed greatly to legume breeding, the genetic gain was often not statistically significant [19]. Contemporary biotechnology tools including next generation sequencing (NGS) plat- forms have aided many breeding programmes with provision of genetic data that traditional breeding techniques cannot fully reveal [20]. Biotechnological “omics” approaches have Plants 2022, 11, 1756. https://doi.org/10.3390/plants11131756 https://www.mdpi.com/journal/plants