Morphological and molecular characterization of fungal pathogen, Magnaphorthe oryzae

Rice is arguably the most crucial food crops supplying quarter of calories intake. Fungal pathogen, Magnaphorthe oryzae promotes blast disease unconditionally to gramineous host including rice species. This disease spurred an outbreaks and constant threat to cereal production. Global rice yield declining almost 10-30% including Malaysia. As Magnaphorthe oryzae and its host is model in disease plant study, the rice blast pathosystem has been the subject of intense interest to overcome the importance of the disease to world agriculture. Therefore, in this study, our prime objective was to isolate samples of Magnaphorthe oryzae from diseased leaf obtained from MARDI Seberang Perai, Penang, Malaysia. Molecular identification was performed by sequences analysis from internal transcribed spacer (ITS) region of nuclear ribosomal RNA genes. Phylogenetic affiliation of the isolated samples were analyzed by comparing the ITS sequences with those deposited in the GenBank database. The sequence of the isolate demonstrated at least 99% nucleotide identity with the corresponding sequence in GenBank for Magnaphorthe oryzae. Morphological observed under microscope demonstrated that the structure of conidia followed similar characteristic as M. oryzae. Finding in this study provide useful information for breeding programs, epidemiology studies and improved disease management

Assessment of Variability and Genetic Diversity Study in an Advanced Segregating Population in Rice with Blast Resistance Genes Introgression

Blast disease caused by a pathogenic fungus, Magnaphorthe oryzae, is the most destructive disease and has resulted in more than 50% of crop losses worldwide, including in Malaysia. The present study was conducted to investigate genetic variability among 36 advanced lines of MR264 × PS2 rice with blast resistance genes introduced at the Faculty of Applied Sciences, Universiti Teknologi MARA, Malaysia. Traits such as days of maturity, plant height, grain width, and seed setting rate exhibited negative skewness in this study, indicating a doubling of gene effects. Seed setting rate and 1000 grain weight showed positive kurtosis, indicating gene interactions. The phenotypic coefficient of variation (PCV) was slightly higher than the genotypic coefficient of variation (GCV) for all traits, indicating that environmental influences affect the expression of these traits. High heritability associated with high genetic advance as a percentage of the mean was observed for filled grains per panicle. In addition, the second-highest value for high heritability and the high genetic advance was observed for the number of tillers. Cluster and principal component analysis revealed that 36 advanced lines were grouped into four clusters based on ten agromorphological traits. Clusters A and C had higher mean values for most of the traits studied than clusters B and D. Desirable recombinants for higher yields with a broad genetic base can be generated by using cross lines from different clusters

Genetic analysis and identification of SSR markers associated with rice blast disease in a BC2F1 backcross population

Rice (Oryza sativa L.) blast disease is one of the most destructive rice diseases in the world. The fungal pathogen, Magnaporthe oryzae, is the causal agent of rice blast disease. Development of resistant cultivars is the most preferred method to achieve sustainable rice production. However, the effectiveness of resistant cultivars is hindered by the genetic plasticity of the pathogen genome. Therefore, information on genetic resistance and virulence stability are vital to increase our understanding of the molecular basis of blast disease resistance. The present study set out to elucidate the resistance pattern and identify potential simple sequence repeat markers linked with rice blast disease. A backcross population (BC2F1), derived from crossing MR264 and Pongsu Seribu 2 (PS2), was developed using marker-assisted backcross breeding. Twelve microsatellite markers carrying the blast resistance gene clearly demonstrated a polymorphic pattern between both parental lines. Among these, two markers, RM206 and RM5961, located on chromosome 11 exhibited the expected 1:1 testcross ratio in the BC2F1population. The 195 BC2F1 plants inoculated against M. oryzae pathotype P7.2 showed a significantly different distribution in the backcrossed generation and followed Mendelian segregation based on a single-gene model. This indicates that blast resistance in PS2 is governed by a single dominant gene, which is linked to RM206 and RM5961 on chromosome 11. The findings presented in this study could be useful for future blast resistance studies in rice breeding programs

Targeting NDM-producing Klebsiella pneumoniae: Optimising novel combinations with polymyxins

New Delhi metallo-β-lactamase (NDM) producing Klebsiella pneumoniae are multidrug-resistant (MDR) and classified as an Urgent Threat by the US Centers for Disease Control and Prevention. Polymyxins remain effective as a last-line therapy for infections caused by MDR Gram-negative bacteria. However, resistance to polymyxins can emerge with monotherapy. As polymyxin-induced nephrotoxicity is the major dose-limiting adverse effect, combination therapy with other antibiotics is warranted to preserve the efficacy of polymyxins whilst minimising the emergence of resistance. This thesis focuses on identifying novel synergistic polymyxin combinations against NDM-producing K. pneumoniae and elucidating mechanisms of synergy at the systems level

Genetic analysis of yield and yield contributing traits in rice (Oryza sativa L.) BC2F3 population derived from MR264 × PS2

AbstractHigh yield potential in rice is indirectly determined by yield-related traits. These traits are complex and regulated by several genes whose expression is affected by environmental conditions. It is of great importance to disclose the genetic relationships between yield and its yield components for multi-trait improvement in rice. Therefore, the present study aimed to investigate the genetic variability and inheritance patterns of yield and yield attributed traits in BC2F3 rice lines to identify the ideal lines from the selection. A total of 36 improved versions of blast resistant plants in the BC2F3 population used in this study were developed from a single cross between a high yielding mutant rice variety but susceptible to blast, MR264, and Malaysian local variety donor for Pi-7(t) and Pikh blast resistant genes. Analysis of variance showed that all traits were significantly different for lines except grain length and grain width. High heritability and genetic advance were recorded for plant height, number of tillers, filled grain, 1000-grain weight and seed setting rate. A significant and positive correlation was recorded with most evaluated traits, except for grain length and grain width. Thirty-six BC2F3 lines were clustered into four major groups and the first three principal components (PC3) contributed 71.13% of the total variation, with 1000-seed weight, yield/hill and filled grain being the main discriminatory characters. There was an adequate genetic variability in the lines, and 1000-grain weight, yield/hill and filled grain traits could be considered for indirect selection in breeding programs in next generations

Exogenous metabolite feeding on altering antibiotic susceptibility in Gram-negative bacteria through metabolic modulation: a review

Background The rise of antimicrobial resistance at an alarming rate is outpacing the development of new antibiotics. The worrisome trends of multidrug-resistant Gram-negative bacteria have enormously diminished existing antibiotic activity. Antibiotic treatments may inhibit bacterial growth or lead to induce bacterial cell death through disruption of bacterial metabolism directly or indirectly. In light of this, it is imperative to have a thorough understanding of the relationship of bacterial metabolism with antimicrobial activity and leverage the underlying principle towards development of novel and effective antimicrobial therapies. Objective Herein, we explore studies on metabolic analyses of Gram-negative pathogens upon antibiotic treatment. Metabolomic studies revealed that antibiotic therapy caused changes of metabolites abundance and perturbed the bacterial metabolism. Following this line of thought, addition of exogenous metabolite has been employed in in vitro, in vivo and in silico studies to activate the bacterial metabolism and thus potentiate the antibiotic activity. Key scientific concepts of review Exogenous metabolites were discovered to cause metabolic modulation through activation of central carbon metabolism and cellular respiration, stimulation of proton motive force, increase of membrane potential, improvement of host immune protection, alteration of gut microbiome, and eventually facilitating antibiotic killing. The use of metabolites as antimicrobial adjuvants may be a promising approach in the fight against multidrug-resistant pathogens

In silico genome-scale metabolic modeling and in vitro static time-kill studies of exogenous metabolites alone and with polymyxin B against Klebsiella pneumoniae

Multidrug-resistant (MDR) Klebsiella pneumoniae is a top-prioritized Gram-negative pathogen with a high incidence in hospital-acquired infections. Polymyxins have resurged as a last-line therapy to combat Gram-negative “superbugs”, including MDR K. pneumoniae. However, the emergence of polymyxin resistance has increasingly been reported over the past decades when used as monotherapy, and thus combination therapy with non-antibiotics (e.g., metabolites) becomes a promising approach owing to the lower risk of resistance development. Genome-scale metabolic models (GSMMs) were constructed to delineate the altered metabolism of New Delhi metallo-β-lactamase- or extended spectrum β-lactamase-producing K. pneumoniae strains upon addition of exogenous metabolites in media. The metabolites that caused significant metabolic perturbations were then selected to examine their adjuvant effects using in vitro static time–kill studies. Metabolic network simulation shows that feeding of 3-phosphoglycerate and ribose 5-phosphate would lead to enhanced central carbon metabolism, ATP demand, and energy consumption, which is converged with metabolic disruptions by polymyxin treatment. Further static time–kill studies demonstrated enhanced antimicrobial killing of 10 mM 3-phosphoglycerate (1.26 and 1.82 log10 CFU/ml) and 10 mM ribose 5-phosphate (0.53 and 0.91 log10 CFU/ml) combination with 2 mg/L polymyxin B against K. pneumoniae strains. Overall, exogenous metabolite feeding could possibly improve polymyxin B activity via metabolic modulation and hence offers an attractive approach to enhance polymyxin B efficacy. With the application of GSMM in bridging the metabolic analysis and time–kill assay, biological insights into metabolite feeding can be inferred from comparative analyses of both results. Taken together, a systematic framework has been developed to facilitate the clinical translation of antibiotic-resistant infection management

Deciphering the action of polymyxins on pentose phosphate pathway metabolism in Acinetobacter Baumannii: a metabolite-based target towards safe antibiotic treatment

Emergence of Acinetobacter baumannii as multidrug-resistant (MDR) bacteria are a major global threat to the healthcare system, forcing the classic polymyxins to be revisited as the last-line therapy against MDR Gram-negative bacteria including A. baumannii. It exhibits rapid bactericidal activity through ‘self-uptake’ pathway to induce local membrane disturbance, osmotic imbalance which lead to cell death. Nevertheless, polymyxins are limited due to the previously reported nephrotoxicity and ineffective suboptimal concentrations among patients. Bacterial metabolic reaction toward antibiotics has not been well studied with cutting-edge metabolomics. Understanding the metabolome of bacterial cells can potentially open an opportunity for novel effective antibacterial therapy. Previous study indicated that there were significant global metabolic disturbance of A. baumannii induced by polymyxin treatments including D-ribose-5-phosphate, D-erythrose-4-phosphate and D- sedoheptulose-7-phosphate of pentose phosphate pathway (PPP) metabolites, highlighting the potential polymyxin target. Therefore, this study aims to investigate the mechanism of polymyxins action on the PPP metabolism in A. baumannii, employing a targeted metabolomics approach through in vitro static time-kill method and metabolic pathway analysis across different time points at 1 hour and 4 hours. Polymyxin B (2mg/L) induced significant bactericidal effect in A. baumannii as rapid killing was observed after 1 hour treatment. However, the bactericidal activity decreased after the first hour as the bacterial growth significantly increased at 4 hours. The significant bactericidal effect of polymyxin at 1 hour reflects its potential in treating A. baumannii infection and further analyzed through metabolomics study. Through targeted metabolomics, detailed analysis on polymyxins’ activity against A. baumannii at cellular level, specifically for PPP metabolism able to provide a novel insight for alternative strategy in combating MDR bacterial infection

Novel antimicrobial development using genome-scale metabolic model of Gram-negative pathogens: a review

Antimicrobial resistance (AMR) threatens the effective prevention and treatment of a wide range of infections. Governments around the world are beginning to devote effort for innovative treatment development to treat these resistant bacteria. Systems biology methods have been applied extensively to provide valuable insights into metabolic processes at system level. Genome-scale metabolic models serve as platforms for constraint-based computational techniques which aid in novel drug discovery. Tools for automated reconstruction of metabolic models have been developed to support system level metabolic analysis. We discuss features of such software platforms for potential users to best fit their purpose of research. In this work, we focus to review the development of genome-scale metabolic models of Gram-negative pathogens and also metabolic network approach for identification of antimicrobial drugs targets

Isotopic tracer for absolute quantification of metabolites of the pentose phosphate pathway in bacteria

The pentose phosphate pathway (PPP) plays a key role in many metabolic functions, including the generation of NADPH, biosynthesis of nucleotides, and carbon homeostasis. In particular, the intermediates of PPP have been found to be significantly perturbed in bacterial metabolomic studies. Nonetheless, detailed analysis to gain mechanistic information of PPP metabolism remains limited as most studies are unable to report on the absolute levels of the metabolites. Absolute quantification of metabolites is a prerequisite to study the details of fluxes and its regulations. Isotope tracer or labeling studies are conducted in vivo and in vitro and have significantly improved the analysis and understanding of PPP. Due to the laborious procedure and limitations in the in vivo method, an in vitro approach known as Group Specific Internal Standard Technology (GSIST) has been successfully developed to measure the absolute levels of central carbon metabolism, including PPP. The technique adopts derivatization of an experimental sample and a corresponding internal standard with isotope-coded reagents to provide better precision for accurate identification and absolute quantification. In this review, we highlight bacterial studies that employed isotopic tracers as the tagging agents used for the absolute quantification analysis of PPP metabolites