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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.

Neglected tropical diseases (NTDs) continue to affect the livelihood of individuals in countries in the Southeast Asia and Western Pacific region. These diseases have been long existing and have caused devastating health problems and economic decline to people in low- and middle-income (developing) countries. An estimated 1.7 billion of the world’s population suffer one or more NTDs annually, this puts approximately one in five individuals at risk for NTDs. In addition to health and social impact, NTDs inflict significant financial burden to patients, close relatives, and are responsible for billions of dollars lost in revenue from reduced labor productivity in developing countries alone. There is an urgent need to better improve the control and eradication or elimination efforts towards NTDs. This can be achieved by utilizing machine learning tools to better the surveillance, prediction and detection program, and combat NTDs through the discovery of new therapeutics against these pathogens. This review surveys the current application of machine learning tools for NTDs and the challenges to elevate the state-of-the-art of NTDs surveillance, management, and treatment.

Background: Members of the genus Klebsiella are among the leading microbial pathogens associated with nosocomial infection. The increased incidence of antimicrobial resistance in these species has propelled the need for alternate/combination therapeutic regimens to aid clinical treatment, including bacteriophage therapy. Bacteriophages are considered very safe and effective in treating bacterial infections. In this study, we characterize eight lytic bacteriophages that were previously isolated by our team against carbapenem-resistant Klebsiella pneumoniae. Methods: The one-step-growth curves, stability and lytic ability of eight bacteriophages were characterized. Restriction fragment length polymorphism (RFLP), random amplification of polymorphic DNA (RAPD) typing analysis and protein profiling were used to characterize the microbes at the molecular level. Phylogenetic trees of four important proteins were constructed for the two selected bacteriophages. Results and conclusions: All eight bacteriophages showed high efficiency for reducing bacterial concentration with high stability under different physical and chemical conditions. We found four major protein bands out of at least ten 15–190 KDa bands that were clearly separated by SDS-PAGE, which were assumed to be the major head and tail proteins. The genomes were found to be dsDNA, with sizes of approximately 36–87 Kb. All bacteriophages reduced the optical density of the planktonic K. pneumoniae abruptly, indicating great potential to reduce K. pneumoniae infection. In this study, we have found that tail fiber protein can further distinguished closely related bacteriophages. The characterised bacteriophages showed promising potential as candidates against carbapenem-resistant Klebsiella pneumoniae via bacteriophage therapy.

Neglected tropical diseases (NTDs) continue to affect the livelihood of individuals in countries in the Southeast Asia and Western Pacific region. These diseases have been long existing and have caused devastating health problems and economic decline to people in low- and middle-income (developing) countries. An estimated 1.7 billion of the world’s population suffer one or more NTDs annually, this puts approximately one in five individuals at risk for NTDs. In addition to health and social impact, NTDs inflict significant financial burden to patients, close relatives, and are responsible for billions of dollars lost in revenue from reduced labor productivity in developing countries alone. There is an urgent need to better improve the control and eradication or elimination efforts towards NTDs. This can be achieved by utilizing machine learning tools to better the surveillance, prediction and detection program, and combat NTDs through the discovery of new therapeutics against these pathogens. This review surveys the current application of machine learning tools for NTDs and the challenges to elevate the state-of-the-art of NTDs surveillance, management, and treatment.

Sulfur is an essential element required for plant growth and development, physiological processes and stress responses. Sulfur-encoding biosynthetic genes are involved in the primary sulfur assimilation pathway, regulating various mechanisms at the gene, cellular and system levels, and in the biosynthesis of sulfur-containing compounds (SCCs). In this study, the SCC-encoding biosynthetic genes in rice were identified using a sulfur-dependent model plant, the Arabidopsis . A total of 139 At SCC from Arabidopsis were used as reference sequences in search of putative rice SCCs. At similarity index > 30%, the similarity search against Arabidopsis SCC query sequences identified 665 putative Os SCC genes in rice. The gene synteny analysis showed a total of 477 syntenic gene pairs comprised of 89 At SCC and 265 Os SCC biosynthetic genes in Arabidopsis and rice, respectively. Phylogenetic tree of the collated ( At SCCs and Os SCCs) SCC-encoding biosynthetic genes were divided into 11 different clades of various sizes comprised of branches of subclades. In clade 1, nearing equal representation of Os SCC and At SCC biosynthetic genes imply the most ancestral lineage. A total of 25 candidate Arabidopsis SCC homologs were identified in rice. The gene ontology enrichment analysis showed that the rice- Arabidopsis SCC homologs were significantly enriched in the following terms at false discovery rate (FDR) < 0.05: (i) biological process; sulfur compound metabolic process and organic acid metabolic processes, (ii) molecular function; oxidoreductase activity, acting on paired donors with incorporation or reduction of molecular oxygen and (iii) KEGG pathway; metabolic pathways and biosynthesis of secondary metabolites. At less than five duplicated blocks of separation, no tandem duplications were observed among the SCC biosynthetic genes distributed in rice chromosomes. The comprehensive rice SCC gene description entailing syntenic events with Arabidopsis, motif distribution and chromosomal mapping of the present findings offer a foundation for rice SCC gene functional studies and advanced strategic rice breeding.

Epidemics caused by fungal plant pathogens pose a major threat to agro-ecosystems and impact global food security. High-throughput sequencing enabled major advances in understanding how pathogens cause disease on crops. Hundreds of fungal genomes are now available and analyzing these genomes highlighted the key role of effector genes in disease. Effectors are small secreted proteins that enhance infection by manipulating host metabolism. Fungal genomes carry 100s of putative effector genes, but the lack of homology among effector genes, even for closely related species, challenges evolutionary and functional analyses. Furthermore, effector genes are often found in rapidly evolving chromosome compartments which are difficult to assemble. We review how population and comparative genomics toolsets can be combined to address these challenges. We highlight studies that associated genome-scale polymorphisms with pathogen lifestyles and adaptation to different environments. We show how genome-wide association studies can be used to identify effectors and other pathogenicity-related genes underlying rapid adaptation. We also discuss how the compartmentalization of fungal genomes into core and accessory regions shapes the evolution of effector genes. We argue that an understanding of genome evolution provides important insight into the trajectory of host-pathogen co-evolution.

Compromised nutritional conditions associated with dietary transitions and feeding cessation in the wild and during fish aquaculture operations are common and can impact growth and survival. These effects are especially prevalent during early ontogenetic stages. We quantified phenotypic and GI tract microbial community responses with an emphasis on protease-producing bacteria of lake sturgeon (Acipenser fulvescens) larvae, a species of aquacultural and conservational importance. To quantify responses associated with experimental food transition and feeding cessation, we performed a 36-day feeding experiment using two treatments: control and diet transition. However, larvae in the diet transition treatment failed to undergo transition and ceased feeding. Larvae in the diet transition treatment exhibited lower growth (total length and body weight) and survival than control larvae. Treatment had a greater effect than ontogenetic changes on taxonomic composition and diversity of the GI tract microbial community. Proteobacteria dominated the GI tract microbial community of the diet transition larvae whereas Firmicutes dominated the GI tracts of control larvae. Most of the 98 identified protease-producing isolates in both treatments were from genera Pseudomonas and Aeromonas: taxonomic groups that include known fish pathogens. Overall, failing to transition diets affected responses in growth and GI tract microbiome composition and diversity, with the later dysbiosis being an indicator of morbidity and mortality in larval lake sturgeon. Thus, microbiological interrogations can characterize responses to dietary regimes. The results can inform fish culturalists and microbiologists of the importance of dietary practices consistent with the establishment and maintenance of healthy GI tract microbiota and optimal growth during early ontogeny.

Glucosinolates (GSLs) and cyanogenic glycosides (CGs) fulfil functions in plant defence and have been reported to be anticancer agents. Generally, GSL-containing plants do not produce CG, and vice versa, CG-containing plants do not synthesise GSLs. However, the production of both GSL and CG compounds was observed in Carica papaya. Additionally, several studies found both GSL glucotropaeolin and CG prunasin in papaya leaves. The advancement of genome technologies can be explored to elucidate the gene functions and other molecular discoveries in plants that might relate to GSLs and CGs. This review aims to discuss the complex interplay of the rare events whereby these two compounds (GSL and CG) co-occur in a bifurcation pathway in papaya. To our knowledge, this is the first review that highlights novel GSL and CG genes in papaya. Furthermore, species-specific pathways in papaya are also discussed and comprehensively described. The transcription factors involved in regulating GSL and CG biosynthesis pathways are also discussed, accompanied by relevant bioinformatic approaches that can help discover potential regulatory genes that control the production of prunasin and glucotropaeolin in papaya.

The oil palm-pollinating weevil (Elaeidobius kamerunicus Faust) was introduced from Cameroon, West Africa, to Malaysia in 1981, and subsequently, to other oil palm-growing countries as well. This study aims to develop a set of robust E. kamerunicus-specific nuclear DNA markers to directly assess the genetic diversity of the weevil populations. A total of 19,148 SNP and 223,200 SSR were discovered from 48 weevils representing three origins (Peninsular Malaysia, Sabah, and Riau) using RAD tag sequencing. Subsequent filtering steps further reduced these to 1000 SNP and 120 SSR. The selected 220 SNP exhibited a polymorphism information content (PIC) of 0.2387 (±0.1280), and 8 SSR had the PIC of 0.5084 (±0.1928). These markers were found to show sufficient polymorphism, making it possible to assign 180 weevils into three major clusters from Ghana, Cameroon, and Southeast Asia (mainly in Malaysia and Indonesia). These DNA markers successfully confirmed the Cameroon origin of the Southeast Asian cluster. However, the presence of null alleles in the SSR markers, due to limited flexibility of the probe design on the short RAD tags, led to an underestimation of heterozygosity within the populations. Hence, the developed SNP markers turned out to be more efficient than the SSR markers in the genetic diversity assessment of the E. kamerunicus populations. The genetic information provides useful insight into developing guidelines for the genetic monitoring and conservation planning of E. kamerunicus.

The red palm weevil (RPW), scientifically known as Rhynchophorus ferrugineus , poses a significant threat to various palm species, leading to substantial economic losses in affected countries. The success of R. ferrugineus infestations can be attributed to numerous factors, such as its discreet behaviour, highly chitinized mouthpart, and prolific reproduction. Efforts to control R. ferrugineus , including insecticides, have encountered challenges such as resistance development and environmental harm. Consequently, there is a vital requirement for environmentally friendly chemicals that specifically target R. ferrugineus , with the chemosensory system being a potential focal point. The chemosensory system of the insect, which is crucial to its interaction with its plant host, could provide an effective strategy for preventing infestations. However, current knowledge about R. ferrugineus chemosensory system, including its anatomy, physiology, and relevant receptors or proteins, remains limited. This review aims to compile existing information on the chemosensory system to guide future research initiatives. It highlights the lack of omics-derived data on the chemosensory system of R. ferrugineus . It emphasises the need for a deeper understanding of the structural and functional aspects of related proteins. The review underscores the necessity for comprehensive, multidisciplinary approaches, such as systems biology and computational methods, to unravel the complexities of R. ferrugineus chemosensory system. The review discusses recent findings and seeks to inform and inspire future research endeavours to prevent R. ferrugineus infestations through targeted strategies. In conclusion, omics data available on the chemosensory system of R. ferrugineus is plentiful. This information is a valuable resource that enables analyses to identify potential targets for enhanced pest management strategies.