Browsing by Author "Mohareb, Fady"
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Item Open Access Application of spectroscopic and multispectral imaging technologies on the assessment of ready-to-eat pineapple quality: A performance evaluation study of machine learning models generated from two commercial data analytics tools(Elsevier, 2020-06-03) Manthou, Evanthia; Lago, Sergio-Llaneza; Dagres, Evaggelos; Lianou, Alexandra; Tsakanikas, Panagiοtis; Panagou, Efstathios Z.; Anastasiadi, Maria; Mohareb, Fady; Nychas, George-John E.Recently, rapid, non-invasive analytical methods relying on vibrational spectroscopy and hyper/multispectral imaging, are increasingly gaining popularity in food science. Although such instruments offer a promising alternative to the conventional methods, the analysis of generated data demands complex multidisciplinary approaches based on data analytics tools utilization. Therefore, the objective of this work was to (i) assess the predictive power of different analytical platforms (sensors) coupled with machine learning algorithms in evaluating quality of ready-to-eat (RTE) pineapple (Ananas comosus) and (ii) explore the potentials of The Unscrambler software and the online machine-learning ranking platform, SorfML, in developing the predictive models required by such instruments to assess quality indices. Pineapple samples were stored at 4, 8, 12 °C and dynamic temperatures and were subjected to microbiological (total mesophilic microbial populations, TVC) and sensory analysis (colour, odour, texture) with parallel acquisition of spectral data. Fourier-transform infrared, fluorescence (FLUO) and visible sensors, as well as Videometer instrument were used. For TVC, almost all the combinations of sensors and Partial-least squares regression (PLSR) algorithm from both analytics tools reached values of root mean square error of prediction (RMSE) up to 0.63 log CFU/g, as well as the highest coefficient of determination values (R2). Moreover, Linear Support Vector Machine (SVM Linear) combined with each one of the sensors reached similar performance. For odour, FLUO sensor achieved the highest overall performance, when combined with Partial-least squares discriminant analysis (PLSDA) in both platforms with accuracy close to 85%, but also with values of sensitivity and specificity above 85%. The SVM Linear and MSI combination also achieved similar performance. On the other hand, all models developed for colour and texture showed poor prediction performance. Overall, the use of both analytics tools, resulted in similar trends concerning the feasibility of the different analytical platforms and algorithms on quality evaluation of RTE pineapple.Item Open Access Contribution of data acquired from spectroscopic, genomic and microbiological analyses to enhance mussels’ quality assessment(Elsevier, 2024-12-01) Lytou, Anastasia; Saxton, Léa; Fengou, Lemonia-Christina; Anagnostopoulos, Dimitrios A.; Parlapani, Foteini F.; Boziaris, Ioannis S.; Mohareb, Fady; Nychas, George-JohnIn this study, a large amount of heterogeneous data (i.e., microbiological, spectral and Next Generation Sequencing data) were obtained analyzing mussels of different species and origin, to acquire a comprehensive view about the quality and safety of these products. More specifically, spectral data were collected through Fourier transform Infrared (FTIR) spectroscopy, while the overall profile of microorganisms present in these samples, affecting quality and safety of mussels throughout storage, was determined through Next Generation Sequencing (NGS) using 16S rRNA metabarcoding analysis. In parallel, conventional microbiological analysis for the estimation of culturable spoilage microorganisms (total aerobes, Pseudomonas spp., B. thermosphacta, Shewanella spp. and Enterobacteriaceae) was applied. Different machine learning algorithms, namely Partial Least Square (PLS), Support Vector Machines (SVM), k-Nearest Neighbors (kNN), Random Forest (RF) Neural Networks (NN)) were applied accordingly, to assess the potential of FTIR and NGS data to provide useful information about mussels’ microbiological quality. Microbial counts ranged from 3.5 to 9.0 log CFU/g, while NGS revealed several bacterial genera such as Pseudoalteromonas, Psychrobacter, Acinetobacter, Pseudomonas, B. thermosphacta, Psychrobacter, Kistimonas, Psychrilyobacter to affect the quality of mussels, depending on the mussel species, batch and storage conditions. According to the performance metrics, the SVM algorithm in tandem with FTIR achieved the highest prediction accuracy for microbial counts in M. chilensis samples (Rsquared; 0.89, RMSE; 0,74), while in the case of predicting the abundance of microbial genera using spectroscopic data, the best performing algorithm varied by bacterial genus. Indicatively, in M. chilensis, RF, kNN and NN performed better in predicting Enterococcus, Enhydrobacterium and Pseudoalteromonas, respectively (Rsquared = 0.92, 0.93, 0.99). Associations between genomics data and specific spectral regions were further investigated, revealing certain spectral regions that are associated with mussels’ quality and safety. The application of “multi-omics” in seafood supply chain can provide insightful information about mussels’ quality and safety compared to the methodologies followed in current quality and safety management systems.Item Open Access Data underpinning "Biochemical Profile of Heritage and Modern Apple Cultivars and Application of Machine Learning Methods to Predict Usage, Age, and Harvest Season"(Cranfield University, 2017-06-05 09:32) Anastasiadi, Maria; Terry, Leon; Redfern, Sally; Mohareb, Fady; Berry, MarkThis dataset contains the quantitative data used for statistical analysis and predictive modelling in the paper entitled "Biochemical Profile of Heritage and Modern Apple Cultivars and Application of Machine Learning Methods to Predict Usage, Age, and Harvest Season". Specifically it contains concentration of phenolic compounds per Fresh weight in the whole apples as well as sugars and organic acids. In addition the phenolic content of individual tissues (peel, flesh, seeds) is uploaded.Item Open Access Dataset "BIFURCATE FLOWER TRUSS: a novel locus controlling inflorescence branching in tomato contains a defective MAP kinase gene"(Cranfield University, 2024-05-22 08:52) Thompson, Andrew; Kevei, Zoltan; Silva ferreira, Demetryus; Mohareb, Fady; Kurowski, TomaszData underlying manuscript entitled: "Identification and characterisation of bifuricate, a novel locus on chromosome 12 controlling truss branching and flower number in tomato"Item Open Access Detection of meat adulteration using spectroscopy-based sensors(MDPI, 2021-04-15) Fengou, Lemonia-Christina; Lianou, Alexandra; Tsakanikas, Panagiοtis; Mohareb, Fady; Nychas, George-John E.Minced meat is a vulnerable to adulteration food commodity because species- and/or tissue-specific morphological characteristics cannot be easily identified. Hence, the economically motivated adulteration of minced meat is rather likely to be practiced. The objective of this work was to assess the potential of spectroscopy-based sensors in detecting fraudulent minced meat substitution, specifically of (i) beef with bovine offal and (ii) pork with chicken (and vice versa) both in fresh and frozen-thawed samples. For each case, meat pieces were minced and mixed so that different levels of adulteration with a 25% increment were achieved while two categories of pure meat also were considered. From each level of adulteration, six different samples were prepared. In total, 120 samples were subjected to visible (Vis) and fluorescence (Fluo) spectra and multispectral image (MSI) acquisition. Support Vector Machine classification models were developed and evaluated. The MSI-based models outperformed the ones based on the other sensors with accuracy scores varying from 87% to 100%. The Vis-based models followed in terms of accuracy with attained scores varying from 57% to 97% while the lowest performance was demonstrated by the Fluo-based models. Overall, spectroscopic data hold a considerable potential for the detection and quantification of minced meat adulteration, which, however, appears to be sensor-specific.Item Open Access Fact-based nutrition for infants and lactating mothers – The NUTRISHIELD study(Frontiers, 2023-04-18) Ramos-Garcia, Victoria; Ten-Doménech, Isabel; Moreno-Giménez, Alba; Campos-Berga, Laura; Parra-Llorca, Anna; Ramón-Beltrán, Amparo; Vaya, María J.; Mohareb, Fady; Molitor, Corentin; et al., on behalf of the NUTRISHIELD teamBackground: Human milk (HM) is the ideal source of nutrients for infants. Its composition is highly variable according to the infant’s needs. When not enough own mother’s milk (OMM) is available, the administration of pasteurized donor human milk (DHM) is considered a suitable alternative for preterm infants. This study protocol describes the NUTRISHIELD clinical study. The aim of this study is to evaluate the influence of diet, lifestyle habits, psychological stress, and pasteurization on the milk composition, and how it modulates infant’s growth, health, and development. Methods and design: NUTRISHIELD is a prospective mother-infant birth cohort in the Spanish-Mediterranean area including three groups: preterm infants <32 weeks of gestation (i) exclusively receiving OMM, and (ii) exclusively receiving DHM, and (iii) term infants exclusively receiving OMM, as well as their mothers. Biological samples and nutritional, clinical, and anthropometric characteristics are collected at six time points covering the period from birth and until six months of infant’s age. The genotype, metabolome, and microbiota as well as the HM composition (i.e., macronutrients, fatty acids, vitamins, human milk oligosaccharides, and steroids) are characterized. Portable sensor prototypes for the analysis of HM and urine are benchmarked. Additionally, maternal psychosocial status is measured at the beginning of the study and at month six, including social support, family functioning, perceived stress, anxiety, and depression symptoms, and traumatic life events. Mother-infant postpartum bonding and parental stress are also examined. At six months, infant neurodevelopment scales are applied. Mother’s concerns and attitudes to breastfeeding are also registered through a specific questionnaire. Discussion: NUTRISHIELD provides an in-depth longitudinal study of the mother-infant-microbiota triad combining multiple biological matrices, newly developed analytical methods, and ad-hoc designed sensor prototypes with a wide range of clinical outcome measures. Data obtained from this study will be used to train a machine-learning algorithm for providing dietary advice to lactating mothers and will be implemented in a user-friendly platform based on a combination of user-provided information and biomarker analysis. A better understanding of the factors affecting milk’s composition, together with the health implications for infants plays an important role in developing improved strategies of nutraceutical management in infant care.Item Open Access Field phenotyping for African crops: overview and perspectives(Frontiers, 2023-10-04) Cudjoe, Daniel; Virlet, Nicolas; Castle, March; Riche, Andrew B.; Mhada, Manal; Waine, Toby W.; Mohareb, Fady; Hawkesford, MalcolmImprovements in crop productivity are required to meet the dietary demands of the rapidly-increasing African population. The development of key staple crop cultivars that are high-yielding and resilient to biotic and abiotic stresses is essential. To contribute to this objective, high-throughput plant phenotyping approaches are important enablers for the African plant science community to measure complex quantitative phenotypes and to establish the genetic basis of agriculturally relevant traits. These advances will facilitate the screening of germplasm for optimum performance and adaptation to low-input agriculture and resource-constrained environments. Increasing the capacity to investigate plant function and structure through non-invasive technologies is an effective strategy to aid plant breeding and additionally may contribute to precision agriculture. However, despite the significant global advances in basic knowledge and sensor technology for plant phenotyping, Africa still lags behind in the development and implementation of these systems due to several practical, financial, geographical and political barriers. Currently, field phenotyping is mostly carried out by manual methods that are prone to error, costly, labor-intensive and may come with adverse economic implications. Therefore, improvements in advanced field phenotyping capabilities and appropriate implementation are key factors for success in modern breeding and agricultural monitoring. In this review, we provide an overview of the current state of field phenotyping and the challenges limiting its implementation in some African countries. We suggest that the lack of appropriate field phenotyping infrastructures is impeding the development of improved crop cultivars and will have a detrimental impact on the agricultural sector and on food security. We highlight the prospects for integrating emerging and advanced low-cost phenotyping technologies into breeding protocols and characterizing crop responses to environmental challenges in field experimentation. Finally, we explore strategies for overcoming the barriers and maximizing the full potential of emerging field phenotyping technologies in African agriculture. This review paper will open new windows and provide new perspectives for breeders and the entire plant science community in Africa.Item Open Access Flavivirus integrations in Aedes aegypti are limited and highly conserved across samples from different geographic regions unlike integrations in Aedes albopictus(Springer, 2021-06-26) Spadar, Anton; Phelan, Jody; Benavente, Ernest Diez; Campos, Monica; Gomez, Lara Ferrero; Mohareb, Fady; Clark, Taane G.; Campino, SusanaMosquitoes of the genus Aedes are the main vectors of many viruses, e.g. dengue and Zika, which affect millions of people each year and for which there are limited treatment options. Understanding how Aedes mosquitoes tolerate high viral loads may lead to better disease control strategies. Elucidating endogenous viral elements (EVEs) within vector genomes may give exploitable biological insights. Previous studies have reported the presence of a large number of EVEs in Aedes genomes. Here we investigated if flavivirus EVEs are conserved across populations and different Aedes species by using ~ 500 whole genome sequence libraries from Aedes aegypti and Aedes albopictus, sourced from colonies and field mosquitoes across continents. We found that nearly all flavivirus EVEs in the Ae. aegypti reference genome originate from four separate putative viral integration events, and that they are highly conserved across geographically diverse samples. By contrast, flavivirus EVEs in the Ae. albopictus reference genome originate from up to nine distinct integration events and show low levels of conservation, even within samples from narrow geographical ranges. Our analysis suggests that flaviviruses integrated as long sequences and were subsequently fragmented and shuffled by transposable elements. Given that EVEs of Ae. aegypti and Ae. albopictus belong to different phylogenetic clades and have very differing levels of conservation, they may have different evolutionary origins and potentially different functional roles.Item Open Access Genes involved in auxin biosynthesis, transport and signalling underlie the extreme adventitious root phenotype of the tomato aer mutant(Springer, 2024-03-03) Kevei, Zoltan; Larriba, Eduardo; Romero‑Bosquet, María Dolores; Nicolás‑Albujer, Miriam; Kurowski, Tomasz J.; Mohareb, Fady; Rickett, Daniel; Pérez‑Pérez, José Manuel; Thompson, Andrew J.The use of tomato rootstocks has helped to alleviate the soaring abiotic stresses provoked by the adverse effects of climate change. Lateral and adventitious roots can improve topsoil exploration and nutrient uptake, shoot biomass and resulting overall yield. It is essential to understand the genetic basis of root structure development and how lateral and adventitious roots are produced. Existing mutant lines with specific root phenotypes are an excellent resource to analyse and comprehend the molecular basis of root developmental traits. The tomato aerial roots (aer) mutant exhibits an extreme adventitious rooting phenotype on the primary stem. It is known that this phenotype is associated with restricted polar auxin transport from the juvenile to the more mature stem, but prior to this study, the genetic loci responsible for the aer phenotype were unknown. We used genomic approaches to define the polygenic nature of the aer phenotype and provide evidence that increased expression of specific auxin biosynthesis, transport and signalling genes in different loci causes the initiation of adventitious root primordia in tomato stems. Our results allow the selection of different levels of adventitious rooting using molecular markers, potentially contributing to rootstock breeding strategies in grafted vegetable crops, especially in tomato. In crops vegetatively propagated as cuttings, such as fruit trees and cane fruits, orthologous genes may be useful for the selection of cultivars more amenable to propagation.Item Open Access Genetic and physiological responses to heat stress in Brassica napus(Frontiers, 2022-04-05) Kourani, Mariam; Mohareb, Fady; Rezwan, Faisal I.; Anastasiadi, Maria; Hammond, John P.Given the current rise in global temperatures, heat stress has become a major abiotic challenge affecting the growth and development of various crops and reducing their productivity. Brassica napus, the second largest source of vegetable oil worldwide, experiences a drastic reduction in seed yield and quality in response to heat. This review outlines the latest research that explores the genetic and physiological impact of heat stress on different developmental stages of B. napus with a special attention to the reproductive stages of floral progression, organogenesis, and post flowering. Several studies have shown that extreme temperature fluctuations during these crucial periods have detrimental effects on the plant and often leading to impaired growth and reduced seed production. The underlying mechanisms of heat stress adaptations and associated key regulatory genes are discussed. Furthermore, an overview and the implications of the polyploidy nature of B. napus and the regulatory role of alternative splicing in forming a priming-induced heat-stress memory are presented. New insights into the dynamics of epigenetic modifications during heat stress are discussed. Interestingly, while such studies are scarce in B. napus, opposite trends in expression of key genetic and epigenetic components have been identified in different species and in cultivars within the same species under various abiotic stresses, suggesting a complex role of these genes and their regulation in heat stress tolerance mechanisms. Additionally, omics-based studies are discussed with emphasis on the transcriptome, proteome and metabolome of B. napus, to gain a systems level understanding of how heat stress alters its yield and quality traits. The combination of omics approaches has revealed crucial interactions and regulatory networks taking part in the complex machinery of heat stress tolerance. We identify key knowledge gaps regarding the impact of heat stress on B. napus during its yield determining reproductive stages, where in-depth analysis of this subject is still needed. A deeper knowledge of heat stress response components and mechanisms in tissue specific models would serve as a stepping-stone to gaining insights into the regulation of thermotolerance that takes place in this important crop species and support future breeding of heat tolerant crops.Item Open Access The impact of plasma membrane lipid composition on flagella-mediated adhesion of enterohemorrhagic Escherichia coli(American Society for Microbiology, 2020-09-16) Cazzola, Hélène; Lemaire, Laurine; Acket, Sébastien; Prost, Elise; Duma, Luminita; Erhardt, Marc; Čechová, Petra; Trouillas, Patrick; Mohareb, Fady; Rossi, Claire; Rossez, YannickEnterohemorrhagic Escherichia coli (EHEC) O157:H7 is a major cause of foodborne gastrointestinal illness. The adhesion of EHEC to host tissues is the first step enabling bacterial colonization. Adhesins such as fimbriae and flagella mediate this process. Here, we studied the interaction of the bacterial flagellum with the host cell’s plasma membrane using giant unilamellar vesicles (GUVs) as a biologically relevant model. Cultured cell lines contain many different molecular components, including proteins and glycoproteins. In contrast, with GUVs, we can characterize the bacterial mode of interaction solely with a defined lipid part of the cell membrane. Bacterial adhesion on GUVs was dependent on the presence of the flagellar filament and its motility. By testing different phospholipid head groups, the nature of the fatty acid chains, or the liposome curvature, we found that lipid packing is a key parameter to enable bacterial adhesion. Using HT-29 cells grown in the presence of polyunsaturated fatty acid (α-linolenic acid) or saturated fatty acid (palmitic acid), we found that α-linolenic acid reduced adhesion of wild-type EHEC but not of a nonflagellated mutant. Finally, our results reveal that the presence of flagella is advantageous for the bacteria to bind to lipid rafts. We speculate that polyunsaturated fatty acids prevent flagellar adhesion on membrane bilayers and play a clear role for optimal host colonization. Flagellum-mediated adhesion to plasma membranes has broad implications for host-pathogen interactions.Item Open Access Improving the tea withering process using ethylene or UV-C(American Chemical Society, 2021-11-05) Collings, Emma R.; Alamar, M. Carmen; Bogaerts Márquez, Maria; Kourmpetli, Sofia; Kevei, Zoltan; Thompson, Andrew J.; Mohareb, Fady; Terry, Leon A.Using a combination of biochemical, transcriptomic, and physiological analyses, we elucidated the mechanisms of physical and chemical withering of tea shoots subjected to UV-C and ethylene treatments. UV-C irradiation (15 kJ m–2) initiated oxidation of catechins into theaflavins, increasing theaflavin-3-monogallate and theaflavin digallate by 5- and 13.2–4.4-fold, respectively, at the end of withering. Concomitantly, a rapid change to brown/red, an increase in electrolyte leakage, and the upregulation of peroxidases (viz. Px2, Px4, and Px6) and polyphenol oxidases (PPO-1) occurred. Exogenous ethylene significantly increased the metabolic rate (40%) and moisture loss (30%) compared to control during simulated withering (12 h at 25 °C) and upregulated transcripts associated with responses to dehydration and abiotic stress, such as those in the ethylene signaling pathway (viz. EIN4-like, EIN3-FBox1, and ERFs). Incorporating ethylene during withering could shorten the tea manufacturing process, while UV-C could enhance the accumulation of flavor-related compounds.Item Open Access Improving the tea withering process using ethylene or UV-C(Cranfield University, 2021-12-13 11:24) del carmen Alamar Gavidia, Maria; Terry, Leon; Collings, Emma; Thompson, Andrew; Mohareb, Fady; Kourmpetli, Sofia; Kevei, Zoltan; Bogaerts Marquez, MariaThe data set contains objective colour, respiration rate, water loss data, as well as individual catechin and theobromine concentrations of Camellia sinensis shoots subjected to UV-C radiation and ethylene supplementation during simulated withering.Item Open Access Leveraging large-scale Mycobacterium tuberculosis whole genome sequence data to characterise drug-resistant mutations using machine learning and statistical approaches(Springer, 2024-12-01) Pruthi, Siddharth Sanjay; Billows, Nina; Thorpe, Joseph; Campino, Susana; Phelan, Jody E.; Mohareb, Fady; Clark, Taane G.Tuberculosis disease (TB), caused by Mycobacterium tuberculosis (Mtb), is a major global public health problem, resulting in > 1 million deaths each year. Drug resistance (DR), including the multi-drug form (MDR-TB), is challenging control of the disease. Whilst many DR mutations in the Mtb genome are known, analysis of large datasets generated using whole genome sequencing (WGS) platforms can reveal new variants through the assessment of genotype-phenotype associations. Here, we apply tree-based ensemble methods to a dataset comprised of 35,777 Mtb WGS and phenotypic drug-susceptibility test data across first- and second-line drugs. We compare model performance across models trained using mutations in drug-specific regions and genome-wide variants, and find high predictive ability for both first-line (area under ROC curve (AUC); range 88.3–96.5) and second-line (AUC range 84.1–95.4) drugs. To aggregate information from low-frequency variants, we pool mutations by functional impact and observe large improvements in predictive accuracy (e.g., sensitivity: pyrazinamide + 25%; ethionamide + 10%). We further characterise loss-of-function mutations observed in resistant phenotypes, uncovering putative markers of resistance (e.g., ndh 293dupG, Rv3861 78delC). Finally, we profile the distribution of known DR-associated single nucleotide polymorphisms across discretised minimum inhibitory concentration (MIC) data generated from phenotypic testing (n = 12,066), and identify mutations associated with highly resistant phenotypes (e.g., inhA − 779G > T and 62T > C). Overall, our work demonstrates that applying machine learning to large-scale WGS data is useful for providing insights into predicting Mtb binary drug resistance and MIC phenotypes, thereby potentially assisting diagnosis and treatment decision-making for infection control.Item Open Access Missense mutation of a class B heat shock factor is responsible for the tomato bushy root-2 phenotype(Biomed Central, 2022-02-08) Kevei, Zoltan; Silva Ferreira, Demetryus; Perez Casenave, Cristina Maria; Kurowski, Tomasz J.; Mohareb, Fady; Rickett, Daniel; Stain, Chris; Thompson, Andrew J.The bushy root-2 (brt-2) tomato mutant has twisting roots, and slower plant development. Here we used whole genome resequencing and genetic mapping to show that brt-2 is caused by a serine to cysteine (S75C) substitution in the DNA binding domain (DBD) of a heat shock factor class B (HsfB) encoded by SolycHsfB4a. This gene is orthologous to the Arabidopsis SCHIZORIZA gene, also known as AtHsfB4. The brt-2 phenotype is very similar to Arabidopsis lines in which the function of AtHsfB4 is altered: a proliferation of lateral root cap and root meristematic tissues, and a tendency for lateral root cap cells to easily separate. The brt-2 S75C mutation is unusual because all other reported amino acid substitutions in the highly conserved DBD of eukaryotic heat shock factors are dominant negative mutations, but brt-2 is recessive. We further show through reciprocal grafting that brt-2 exerts its effects predominantly through the root genotype even through BRT-2 is expressed at similar levels in both root and shoot meristems. Since AtHsfB4 is induced by root knot nematodes (RKN), and loss-of-function mutants of this gene are resistant to RKNs, BRT-2 could be a target gene for RKN resistance, an important trait in tomato rootstock breeding.Item Open Access Modeling the spatial-spectral characteristics of plants for nutrient status identification using hyperspectral data and deep learning methods(Frontiers, 2023-10-16) Okyere, Frank Gyan; Cudjoe, Daniel; Sadeghi-Tehran, Pouria; Virlet, Nicolas; Riche, Andrew B.; Castle, March; Greche, Latifa; Simms, Daniel M.; Mhada, Manal; Mohareb, Fady; Hawkesford, Malcolm JohnSustainable fertilizer management in precision agriculture is essential for both economic and environmental reasons. To effectively manage fertilizer input, various methods are employed to monitor and track plant nutrient status. One such method is hyperspectral imaging, which has been on the rise in recent times. It is a remote sensing tool used to monitor plant physiological changes in response to environmental conditions and nutrient availability. However, conventional hyperspectral processing mainly focuses on either the spectral or spatial information of plants. This study aims to develop a hybrid convolution neural network (CNN) capable of simultaneously extracting spatial and spectral information from quinoa and cowpea plants to identify their nutrient status at different growth stages. To achieve this, a nutrient experiment with four treatments (high and low levels of nitrogen and phosphorus) was conducted in a glasshouse. A hybrid CNN model comprising a 3D CNN (extracts joint spectral-spatial information) and a 2D CNN (for abstract spatial information extraction) was proposed. Three pre-processing techniques, including second-order derivative, standard normal variate, and linear discriminant analysis, were applied to selected regions of interest within the plant spectral hypercube. Together with the raw data, these datasets were used as inputs to train the proposed model. This was done to assess the impact of different pre-processing techniques on hyperspectral-based nutrient phenotyping. The performance of the proposed model was compared with a 3D CNN, a 2D CNN, and a Hybrid Spectral Network (HybridSN) model. Effective wavebands were selected from the best-performing dataset using a greedy stepwise-based correlation feature selection (CFS) technique. The selected wavebands were then used to retrain the models to identify the nutrient status at five selected plant growth stages. From the results, the proposed hybrid model achieved a classification accuracy of over 94% on the test dataset, demonstrating its potential for identifying nitrogen and phosphorus status in cowpea and quinoa at different growth stages.Item Open Access Mutagenesis of Puccinia graminis f. sp. tritici and selection of gain-of-virulence mutants(Frontiers, 2020-09-16) Kangara, Ngonidzashe; Kurowski, Tomasz J.; Radhakrishnan, Guru V.; Ghosh, Sreya; Cook, Nicola M.; Yu, Guotai; Arora, Sanu; Steffenson, Brian J.; Figueroa, Melania; Mohareb, Fady; Saunders, Diane G. O.; Wulff, Brande B. H.Wheat stem rust caused by the fungus Puccinia graminis f. sp. tritici (Pgt), is regaining prominence due to the recent emergence of virulent isolates and epidemics in Africa, Europe and Central Asia. The development and deployment of wheat cultivars with multiple stem rust resistance (Sr) genes stacked together will provide durable resistance. However, certain disease resistance genes can suppress each other or fail in particular genetic backgrounds. Therefore, the function of each Sr gene must be confirmed after incorporation into an Sr-gene stack. This is difficult when using pathogen disease assays due to epistasis from recognition of multiple avirulence (Avr) effectors. Heterologous delivery of single Avr effectors can circumvent this limitation, but this strategy is currently limited by the paucity of cloned Pgt Avrs. To accelerate Avr gene cloning, we outline a procedure to develop a mutant population of Pgt spores and select for gain-of-virulence mutants. We used ethyl methanesulphonate (EMS) to mutagenize urediniospores and create a library of > 10,000 independent mutant isolates that were combined into 16 bulks of ~658 pustules each. We sequenced random mutants and determined the average mutation density to be 1 single nucleotide variant (SNV) per 258 kb. From this, we calculated that a minimum of three independently derived gain-of-virulence mutants is required to identify a given Avr gene. We inoculated the mutant library onto plants containing Sr43, Sr44, or Sr45 and obtained 9, 4, and 14 mutants with virulence toward Sr43, Sr44, or Sr45, respectively. However, only mutants identified on Sr43 and Sr45 maintained their virulence when reinolculated onto the lines from which they were identified. We further characterized 8 mutants with virulence toward Sr43. These also maintained their virulence profile on the stem rust international differential set containing 20 Sr genes, indicating that they were most likely not accidental contaminants. In conclusion, our method allows selecting for virulent mutants toward targeted resistance (R) genes. The development of a mutant library from as little as 320 mg spores creates a resource that enables screening against several R genes without the need for multiple rounds of spore multiplication and mutagenesis.Item Open Access A near-chromosome level genome assembly of the European hoverfly, Sphaerophoria rueppellii (Diptera: Syrphidae), provides comparative insights into insecticide resistance-related gene family evolution(BioMed Central, 2022-03-12) Bailey, Emma; Field, Linda; Rawlings, Christopher; King, Rob; Mohareb, Fady; Pak, Keywan‑Hassani; Hughes, David; Williamson, Martin; Ganko, Eric; Buer, Benjamin; Nauen, RalfBackground Sphaerophoria rueppellii, a European species of hoverfly, is a highly effective beneficial predator of hemipteran crop pests including aphids, thrips and coleopteran/lepidopteran larvae in integrated pest management (IPM) programmes. It is also a key pollinator of a wide variety of important agricultural crops. No genomic information is currently available for S. rueppellii. Without genomic information for such beneficial predator species, we are unable to perform comparative analyses of insecticide target-sites and genes encoding metabolic enzymes potentially responsible for insecticide resistance, between crop pests and their predators. These metabolic mechanisms include several gene families - cytochrome P450 monooxygenases (P450s), ATP binding cassette transporters (ABCs), glutathione-S-transferases (GSTs), UDP-glycosyltransferases (UGTs) and carboxyl/choline esterases (CCEs). Methods and findings In this study, a high-quality near-chromosome level de novo genome assembly (as well as a mitochondrial genome assembly) for S. rueppellii has been generated using a hybrid approach with PacBio long-read and Illumina short-read data, followed by super scaffolding using Hi-C data. The final assembly achieved a scaffold N50 of 87Mb, a total genome size of 537.6Mb and a level of completeness of 96% using a set of 1,658 core insect genes present as full-length genes. The assembly was annotated with 14,249 protein-coding genes. Comparative analysis revealed gene expansions of CYP6Zx P450s, epsilon-class GSTs, dietary CCEs and multiple UGT families (UGT37/302/308/430/431). Conversely, ABCs, delta-class GSTs and non-CYP6Zx P450s showed limited expansion. Differences were seen in the distributions of resistance-associated gene families across subfamilies between S. rueppellii and some hemipteran crop pests. Additionally, S. rueppellii had larger numbers of detoxification genes than other pollinator species. Conclusion and significance This assembly is the first published genome for a predatory member of the Syrphidae family and will serve as a useful resource for further research into selectivity and potential tolerance of insecticides by beneficial predators. Furthermore, the expansion of some gene families often linked to insecticide resistance and selectivity may be an indicator of the capacity of this predator to detoxify IPM selective insecticides. These findings could be exploited by targeted insecticide screens and functional studies to increase effectiveness of IPM strategies, which aim to increase crop yields by sustainably and effectively controlling pests without impacting beneficial predator populations.Item Open Access De novo genome assembly and functional annotation for Fusarium langsethiae(Springer, 2022-02-22) Zuo, Ya; Verheecke-Vaessen, Carol; Molitor, Corentin; Medina, Angel; Magan, Naresh; Mohareb, FadyBackground Fusarium langsethiae is a T-2 and HT-2 mycotoxins producing species firstly characterised in 2004. It is commonly isolated from oats in Northern Europe. T-2 and HT-2 mycotoxins exhibit immunological and haemotological effects in animal health mainly through inhibition of protein, RNA and DNA synthesis. The development of a high-quality and comprehensively annotated assembly for this species is therefore essential in providing the molecular understanding and the mechanism of T-2 and HT-2 biosynthesis in F. langsethiae to help develop effective control strategies. Results The F. langsethiae assembly was produced using PacBio long reads, which were then assembled independently using Canu, SMARTdenovo and Flye. A total of 19,336 coding genes were identified using RNA-Seq informed ab-initio gene prediction. Finally, predicting genes were annotated using the basic local alignment search tool (BLAST) against the NCBI non-redundant (NR) genome database and protein hits were annotated using InterProScan. Genes with blast hits were functionally annotated with Gene Ontology. Conclusions We developed a high-quality genome assembly of a total length of 59 Mb and N50 of 3.51 Mb. Raw sequence reads and assembled genome is publicly available and can be downloaded from: GenBank under the accession JAFFKB000000000.Item Open Access The ORGAN SIZE (ORG) locus modulates both vegetative and reproductive gigantism in domesticated tomato(Oxford University Press, 2023-10-11) Vicente, Mateus Henrique; MacLeod, Kyle; Zhu, Feng; Rafael, Diego D.; Figueira, Antonio; Fernie, Alisdair R.; Mohareb, Fady; Kevei, Zoltan; Thompson, Andrew J.; Zsögön, Agustin; Pereira Peres, Lázaro EustáquioBackground and Aims Gigantism is a key component of the domestication syndrome, a suite of traits that differentiates crops from their wild relatives. Allometric gigantism is strongly marked in horticultural crops, causing disproportionate increases in the size of edible parts such as stems, leaves or fruits. Tomato (Solanum lycopersicum) has attracted attention as a model for fruit gigantism, and many genes have been described controlling this trait. However, the genetic basis of a corresponding increase in size of vegetative organs contributing to isometric gigantism has remained relatively unexplored. Methods Here, we identified a 0.4-Mb region on chromosome 7 in introgression lines (ILs) from the wild species Solanum pennellii in two different tomato genetic backgrounds (cv. ‘M82’ and cv. ‘Micro-Tom’) that controls vegetative and reproductive organ size in tomato. The locus, named ORGAN SIZE (ORG), was fine-mapped using genotype-by-sequencing. A survey of the literature revealed that ORG overlaps with previously mapped quantitative trait loci controlling tomato fruit weight during domestication. Key Results Alleles from the wild species led to lower cell number in different organs, which was partially compensated by greater cell expansion in leaves, but not in fruits. The result was a proportional reduction in leaf, flower and fruit size in the ILs harbouring the alleles from the wild species. Conclusions Our findings suggest that selection for large fruit during domestication also tends to select for increases in leaf size by influencing cell division. Since leaf size is relevant for both source–sink balance and crop adaptation to different environments, the discovery of ORG could allow fine-tuning of these parameters.