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Detection of Oil Palm Root Penetration by Agrobacterium-Mediated Transformed Ganoderma boninense, Expressing Green Fluorescent Protein

Govender N, Wong MY

Phytopathology, 2017 04;107(4):483-490.
PMID: 27918241 DOI: 10.1094/PHYTO-02-16-0062-R

A highly efficient and reproducible Agrobacterium-mediated transformation protocol for Ganoderma boninense was developed to facilitate observation of the early stage infection of basal stem rot (BSR). The method was proven amenable to different explants (basidiospore, protoplast, and mycelium) of G. boninense. The transformation efficiency was highest (62%) under a treatment combination of protoplast explant and Agrobacterium strain LBA4404, with successful expression of an hyg marker gene and gus-gfp fusion gene under the control of heterologous p416 glyceraldehyde 3-phosphate dehydrogenase promoter. Optimal transformation conditions included a 1:100 Agrobacterium/explant ratio, induction of Agrobacterium virulence genes in the presence of 250 μm acetosyringone, co-cultivation at 22°C for 2 days on nitrocellulose membrane overlaid on an induction medium, and regeneration of transformants on potato glucose agar prepared with 0.6 M sucrose and 20 mM phosphate buffer. Evaluated transformants were able to infect root tissues of oil palm plantlets with needle-like microhyphae during the penetration event. The availability of this model pathogen system for BSR may lead to a better understanding of the pathogenicity factors associated with G. boninense penetration into oil palm roots.
Fulltext Green synthesis and characterization of UKMRC-8 rice husk-derived mesoporous silica nanoparticle for agricultural application

Dorairaj D, Govender N, Zakaria S, Wickneswari R

Sci Rep, 2022 Nov 23;12(1):20162.
PMID: 36424408 DOI: 10.1038/s41598-022-24484-z

Agriculture plays a crucial role in safeguarding food security, more so as the world population increases gradually. A productive agricultural system is supported by seed, soil, fertiliser and good management practices. Food productivity directly correlates to the generation of solid wastes and utilization of agrochemicals, both of which negatively impact the environment. The rice and paddy industry significantly adds to the growing menace of waste management. In low and middle-income countries, rice husk (RH) is an underutilized agro-waste discarded in landfills or burned in-situ. RH holds enormous potential in the development of value-added nanomaterials for agricultural applications. In this study, a simple and inexpensive sol-gel method is described to extract mesoporous silica nanoparticles (MSNs) from UKMRC8 RH using the bottom-up approach. RHs treated with hydrochloric acid were calcinated to obtain rice husk ash (RHA) with high silica purity (> 98% wt), as determined by the X-ray fluorescence analysis (XRF). Calcination at 650 °C for four hours in a box furnace yielded RHA that was devoid of metal impurities and organic matter. The X-ray diffraction pattern showed a broad peak at 2θ≈20-22 °C and was free from any other sharp peaks, indicating the amorphous property of the RHA. Scanning electron micrographs (SEM) showed clusters of spherically shaped uniform aggregates of silica nanoparticles (NPs) while transmission electron microscopy analysis indicated an average particle size of
Fulltext Transcriptome analysis of reproductive tissue differentiation in Jatropha curcas Linn

Govender N, Senan S, Mohamed-Hussein ZA, Ratnam W

Genom Data, 2017 Sep;13:11-14.
PMID: 28626637 DOI: 10.1016/j.gdata.2017.05.008

Shoot and inflorescence are central physiological and developmental tissues of plants. Flowering is one of the most important agronomic traits for improvement of crop yield. To analyze the vegetative to reproductive tissue transition in Jatropha curcas, gene expression profiles were generated from shoot and inflorescence tissues. RNA isolated from both tissues was sequenced using the Ilumina HiSeq 2500 platform. Differential gene expression analysis identified key biological processes associated with vegetative to reproductive tissue transition. The present data for J. curcas may inform the design of breeding strategies particularly with respect to reproductive tissue transition. The raw data of this study has been deposited in the NCBI's Sequence Read Archive (SRA) database with the accession number SRP090662.
Fulltext Effects of silica soil amendment against Exserohilum rostratum, the fungal pathogen of rice brown spot disease in Peninsular Malaysia

Mahmad-Toher AS, Govender N, Dorairaj D, Wong MY

Sci Rep, 2022 Sep 20;12(1):15690.
PMID: 36127366 DOI: 10.1038/s41598-022-19308-z

Rice brown spot (BS) exerts devastating agronomic effects on grain quality and overall productivity. In Peninsular Malaysia, BS disease incidence is fairly prevalent and little is known about the diversity of BS pathogens in the local granaries. Fifteen isolates from BS symptomatic rice plants were identified at five different rice granaries across Peninsular Malaysia. Based on the morphological and molecular analyses, two isolates were confirmed as Bipolaris oryzae while the rest were identified as Exserohilum rostratum. Phylogenetic tree analysis revealed that BS incidence in rice granaries in Peninsular Malaysia is caused by a pair of closely related fungal pathogens, E. rostratum and B. oryzae, with the former being more predominant. Cultural characterization of E. rostratum isolate KT831962 showed the best growth and sporulation activity on corn meal agar plates incubated in complete darkness. The effects of calcium silicate (CaSiO3) and rice husk ash (RHA) soil amendment against MR219 and MR253 rice varieties were evaluated during rice-E. rostratum interaction. Results showed that soil amelioration using CaSiO3 and RHA singly and in combination with manganese (Mn) significantly reduced rice BS disease severity. The BS disease index was reduced significantly to less than 31.6% in the silicon-treated rice plants relative to the control plants at 41.2%. Likewise, the grain yield at the harvest stage showed significantly higher yield in the Si-treated rice plants in comparison to the control, non-Si treated rice plants. The findings highlight the potential of RHA agro-waste as Si fertilizer in a sustainable rice production system.
Fulltext A gene co-expression network model identifies yield-related vicinity networks in Jatropha curcas shoot system

Govender N, Senan S, Mohamed-Hussein ZA, Wickneswari R

Sci Rep, 2018 Jun 15;8(1):9211.
PMID: 29907786 DOI: 10.1038/s41598-018-27493-z

The plant shoot system consists of reproductive organs such as inflorescences, buds and fruits, and the vegetative leaves and stems. In this study, the reproductive part of the Jatropha curcas shoot system, which includes the aerial shoots, shoots bearing the inflorescence and inflorescence were investigated in regard to gene-to-gene interactions underpinning yield-related biological processes. An RNA-seq based sequencing of shoot tissues performed on an Illumina HiSeq. 2500 platform generated 18 transcriptomes. Using the reference genome-based mapping approach, a total of 64 361 genes was identified in all samples and the data was annotated against the non-redundant database by the BLAST2GO Pro. Suite. After removing the outlier genes and samples, a total of 12 734 genes across 17 samples were subjected to gene co-expression network construction using petal, an R library. A gene co-expression network model built with scale-free and small-world properties extracted four vicinity networks (VNs) with putative involvement in yield-related biological processes as follow; heat stress tolerance, floral and shoot meristem differentiation, biosynthesis of chlorophyll molecules and laticifers, cell wall metabolism and epigenetic regulations. Our VNs revealed putative key players that could be adapted in breeding strategies for J. curcas shoot system improvements.
Fulltext RNA-seq data of the Jatropha curcas L. shoot system

Govender N, Senan S, Mohamed-Hussein ZA, Isa MNM, Yaakob Z, Ratnam W

Data Brief, 2018 Dec;21:71-74.
PMID: 30338276 DOI: 10.1016/j.dib.2018.09.081

Jatropha curcas L. or the physic nut is a monoecious shrub belonging to the Euphorbiaceae family. The plant is an ideal feedstock for biodiesel production; oil-rich seed (37-42%), has a broad range of growth habitat such as arid, semi-arid and tropical and a relatively feasible process for conversion of crude oil into biodiesel. The major constraint affecting the success of large-scale J. curcas plantation is seed yield inconsistency. Numerous research projects conducted on J. curcas with integrated genetic, genomic and transcriptomic approaches have been applied on the leaf, apical meristem, flower, root and fruit tissues. However, to date, no genomics data of J. curcas shoot system are publicly available, despite its importance in understanding flowering, fruiting and seed set qualities targeted for yield improvement. Here, we present eighteen sets of shoot and inflorescence transcriptomes generated from J. curcas plants with contrasting yields. Raw reads of the RNA-seq data are found in NCBI׳s Sequence Read Archive (SRA) database with the accession number SRP090662 (https://www.ncbi.nlm.nih.gov/sra/?term=SRP090662). This transcriptomic data could be integrated with the present genomic resources for in depth understanding of J. curcas reproductive system.
Fulltext Chemoinformatics-driven classification of Angiosperms using sulfur-containing compounds and machine learning algorithm

Abdullah-Zawawi MR, Govender N, Karim MB, Altaf-Ul-Amin M, Kanaya S, Mohamed-Hussein ZA

Plant Methods, 2022 Nov 05;18(1):118.
PMID: 36335358 DOI: 10.1186/s13007-022-00951-6

BACKGROUND: Phytochemicals or secondary metabolites are low molecular weight organic compounds with little function in plant growth and development. Nevertheless, the metabolite diversity govern not only the phenetics of an organism but may also inform the evolutionary pattern and adaptation of green plants to the changing environment. Plant chemoinformatics analyzes the chemical system of natural products using computational tools and robust mathematical algorithms. It has been a powerful approach for species-level differentiation and is widely employed for species classifications and reinforcement of previous classifications.
RESULTS: This study attempts to classify Angiosperms using plant sulfur-containing compound (SCC) or sulphated compound information. The SCC dataset of 692 plant species were collected from the comprehensive species-metabolite relationship family (KNApSAck) database. The structural similarity score of metabolite pairs under all possible combinations (plant species-metabolite) were determined and metabolite pairs with a Tanimoto coefficient value > 0.85 were selected for clustering using machine learning algorithm. Metabolite clustering showed association between the similar structural metabolite clusters and metabolite content among the plant species. Phylogenetic tree construction of Angiosperms displayed three major clades, of which, clade 1 and clade 2 represented the eudicots only, and clade 3, a mixture of both eudicots and monocots. The SCC-based construction of Angiosperm phylogeny is a subset of the existing monocot-dicot classification. The majority of eudicots present in clade 1 and 2 were represented by glucosinolate compounds. These clades with SCC may have been a mixture of ancestral species whilst the combinatorial presence of monocot-dicot in clade 3 suggests sulphated-chemical structure diversification in the event of adaptation during evolutionary change.
CONCLUSIONS: Sulphated chemoinformatics informs classification of Angiosperms via machine learning technique.
Fulltext Comparative genome-wide analysis of WRKY, MADS-box and MYB transcription factor families in Arabidopsis and rice

Abdullah-Zawawi MR, Ahmad-Nizammuddin NF, Govender N, Harun S, Mohd-Assaad N, Mohamed-Hussein ZA

Sci Rep, 2021 10 04;11(1):19678.
PMID: 34608238 DOI: 10.1038/s41598-021-99206-y

Transcription factors (TFs) form the major class of regulatory genes and play key roles in multiple plant stress responses. In most eukaryotic plants, transcription factor (TF) families (WRKY, MADS-box and MYB) activate unique cellular-level abiotic and biotic stress-responsive strategies, which are considered as key determinants for defense and developmental processes. Arabidopsis and rice are two important representative model systems for dicot and monocot plants, respectively. A comprehensive comparative study on 101 OsWRKY, 34 OsMADS box and 122 OsMYB genes (rice genome) and, 71 AtWRKY, 66 AtMADS box and 144 AtMYB genes (Arabidopsis genome) showed various relationships among TFs across species. The phylogenetic analysis clustered WRKY, MADS-box and MYB TF family members into 10, 7 and 14 clades, respectively. All clades in WRKY and MYB TF families and almost half of the total number of clades in the MADS-box TF family are shared between both species. Chromosomal and gene structure analysis showed that the Arabidopsis-rice orthologous TF gene pairs were unevenly localized within their chromosomes whilst the distribution of exon-intron gene structure and motif conservation indicated plausible functional similarity in both species. The abiotic and biotic stress-responsive cis-regulatory element type and distribution patterns in the promoter regions of Arabidopsis and rice WRKY, MADS-box and MYB orthologous gene pairs provide better knowledge on their role as conserved regulators in both species. Co-expression network analysis showed the correlation between WRKY, MADs-box and MYB genes in each independent rice and Arabidopsis network indicating their role in stress responsiveness and developmental processes.
Fulltext Pea eggplant (Solanum torvum Swartz) is a source of plant food polyphenols with SARS-CoV inhibiting potential

Govender N, Zulkifli NS, Badrul Hisham NF, Ab Ghani NS, Mohamed-Hussein ZA

PeerJ, 2022;10:e14168.
PMID: 36518265 DOI: 10.7717/peerj.14168

BACKGROUND: Pea eggplant (Solanum torvum Swartz) commonly known as turkey berry or 'terung pipit' in Malay is a vegetable plant widely consumed by the local community in Malaysia. The shrub bears pea-like turkey berry fruits (TBFs), rich in phytochemicals of medicinal interest. The TBF phytochemicals hold a wide spectrum of pharmacological properties. In this study, the TBF phytochemicals' potential inhibitory properties were evaluated against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) of the Coronavirus disease 2019 (COVID-19). The TBF polyphenols were screened against SARS-CoV receptors via molecular docking and the best receptor-ligand complex was validated further by molecular dynamics (MD) simulation.
METHOD: The SARS-CoV receptor structure files (viral structural components) were retrieved from the Protein Data Bank (PDB) database: membrane protein (PDB ID: 3I6G), main protease (PDB ID: 5RE4), and spike glycoproteins (PDB ID: 6VXX and 6VYB). The receptor binding pocket regions were identified by Discovery Studio (BIOVIA) for targeted docking with TBF polyphenols (genistin, kaempferol, mellein, rhoifolin and scutellarein). The ligand and SARS-CoV family receptor structure files were pre-processed using the AutoDock tools. Molecular docking was performed with the Lamarckian genetic algorithm using AutoDock Vina 4.2 software. The best pose (ligand-receptor complex) from the molecular docking analysis was selected based on the minimum binding energy (MBE) and extent of structural interactions, as indicated by BIOVIA visualization tool. The selected complex was validated by a 100 ns MD simulation run using the GROMACS software. The dynamic behaviour and stability of the receptor-ligand complex were evaluated by the root mean square displacement (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent accessible surface area (SASA), solvent accessible surface volume (SASV) and number of hydrogen bonds.
RESULTS: At RMSD = 0, the TBF polyphenols showed fairly strong physical interactions with SARS-CoV receptors under all possible combinations. The MBE of TBF polyphenol-bound SARS CoV complexes ranged from -4.6 to -8.3 kcal/mol. Analysis of the structural interactions showed the presence of hydrogen bonds, electrostatic and hydrophobic interactions between the receptor residues (RR) and ligands atoms. Based on the MBE values, the 3I6G-rhoifolin (MBE = -8.3 kcal/mol) and 5RE4-genistin (MBE = -7.6 kcal/mol) complexes were ranked with the least value. However, the latter showed a greater extent of interactions between the RRs and the ligand atoms and thus was further validated by MD simulation. The MD simulation parameters of the 5RE4-genistin complex over a 100 ns run indicated good structural stability with minimal flexibility within genistin binding pocket region. The findings suggest that S. torvum polyphenols hold good therapeutics potential in COVID-19 management.
Fulltext An integration of phenotypic and transcriptomic data analysis reveals yield-related hub genes in Jatropha curcas inflorescence

Govender N, Senan S, Sage EE, Mohamed-Hussein ZA, Mackeen MM, Wickneswari R

PLoS One, 2018;13(9):e0203441.
PMID: 30240391 DOI: 10.1371/journal.pone.0203441

Jatropha curcas is an oil-rich seed crop with huge potentials for bioenergy production. The inflorescence carries a number of processes that are likely to affect the overall yield potentials; floral development, male-to-female flower ratio, floral abscission and fruit set. In this study, a weighted gene co-expression network analysis which integrates the transcriptome, physical and simple sugar data of J. curcas inflorescence was performed and nine modules were identified by means of hierarchical clustering. Among them, four modules (green4, antiquewhite2, brown2 and lightskyblue4) showed significant correlation to yield factors at p≤0.01. The four modules are categorized into two clusters; cluster 1 of green4 and antiquewhite2 modules correspond to number of flowers/inflorescence, total seed weight/plant, number of seeds/plant, and number of fruits/plant, whereas cluster 2 of brown2 and lightskyblue4 modules correspond to glucose and fructose. Descriptive characterizations of cluster 1 show putative involvement in gibberellin signaling and responses, whereas cluster 2 may have been involved in sugar signaling, signal transductions and regulation of flowerings. Our findings present a list of hub genes for J. curcas yield improvement and reproductive biology enhancement strategies.
Fulltext Phenazine from Pseudomonas aeruginosa UPMP3 induced the host resistance in oil palm (Elaeis guineensis Jacq.)-Ganoderma boninense pathosystem

Parvin W, Govender N, Othman R, Jaafar H, Rahman M, Wong MY

Sci Rep, 2020 Sep 24;10(1):15621.
PMID: 32973199 DOI: 10.1038/s41598-020-72156-7

Pseudomonas aeruginosa developed its biocontrol agent property through the production of antifungal derivatives, with the phenazine among them. In this study, the applications of crude phenazine synthesized by Pseudomonas aeruginosa UPMP3 and hexaconazole were comparatively evaluated for their effectiveness to suppress basal stem rot infection in artificially G. boninense-challenged oil palm seedlings. A glasshouse experiment under the randomized completely block design was set with the following treatments: non-inoculated seedlings, G. boninense inoculated seedlings, G. boninense inoculated seedlings with 1 mg/ml phenazine application, G. boninense inoculated seedlings with 2 mg/ml phenazine application and G. boninense inoculated seedlings with 0.048 mg/ml hexaconazole application. Seedlings were screened for disease parameters and plant vigour traits (plant height, plant fresh weight, root fresh, and dry weight, stem diameter, and total chlorophyll) at 1-to-4 month post-inoculation (mpi). The application of 2 mg/ml phenazine significantly reduced disease severity (DS) at 44% in comparison to fungicide application (DS = 67%). Plant vigour improved from 1 to 4 mpi and the rate of disease reduction in seedlings with phenazine application (2 mg/ml) was twofold greater than hexaconazole. At 4, 6 and 8 wpi, an up-regulation of chitinase and β-1,3 glucanase genes in seedlings treated with phenazine suggests the involvement of induced resistance in G. boninense-oil palm pathosystem.
Evidence for the Higgs Boson Decay to a Z Boson and a Photon at the LHC

Aad G, Abbott B, Abeling K, Abicht NJ, Abidi SH, Aboulhorma A, et al.

Phys Rev Lett, 2024 Jan 12;132(2):021803.
PMID: 38277607 DOI: 10.1103/PhysRevLett.132.021803

The first evidence for the Higgs boson decay to a Z boson and a photon is presented, with a statistical significance of 3.4 standard deviations. The result is derived from a combined analysis of the searches performed by the ATLAS and CMS Collaborations with proton-proton collision datasets collected at the CERN Large Hadron Collider (LHC) from 2015 to 2018. These correspond to integrated luminosities of around 140 fb^{-1} for each experiment, at a center-of-mass energy of 13 TeV. The measured signal yield is 2.2±0.7 times the standard model prediction, and agrees with the theoretical expectation within 1.9 standard deviations.

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