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Fulltext Pyrethroid Resistance in Malaysian Populations of Dengue Vector Aedes aegypti Is Mediated by CYP9 Family of Cytochrome P450 Genes

Ishak IH, Kamgang B, Ibrahim SS, Riveron JM, Irving H, Wondji CS

PLoS Negl Trop Dis, 2017 01;11(1):e0005302.
PMID: 28114328 DOI: 10.1371/journal.pntd.0005302

BACKGROUND: Dengue control and prevention rely heavily on insecticide-based interventions. However, insecticide resistance in the dengue vector Aedes aegypti, threatens the continued effectiveness of these tools. The molecular basis of the resistance remains uncharacterised in many endemic countries including Malaysia, preventing the design of evidence-based resistance management. Here, we investigated the underlying molecular basis of multiple insecticide resistance in Ae. aegypti populations across Malaysia detecting the major genes driving the metabolic resistance.
METHODOLOGY/PRINCIPAL FINDINGS: Genome-wide microarray-based transcription analysis was carried out to detect the genes associated with metabolic resistance in these populations. Comparisons of the susceptible New Orleans strain to three non-exposed multiple insecticide resistant field strains; Penang, Kuala Lumpur and Kota Bharu detected 2605, 1480 and 425 differentially expressed transcripts respectively (fold-change>2 and p-value ≤ 0.05). 204 genes were commonly over-expressed with monooxygenase P450 genes (CYP9J27, CYP6CB1, CYP9J26 and CYP9M4) consistently the most up-regulated detoxification genes in all populations, indicating that they possibly play an important role in the resistance. In addition, glutathione S-transferases, carboxylesterases and other gene families commonly associated with insecticide resistance were also over-expressed. Gene Ontology (GO) enrichment analysis indicated an over-representation of GO terms linked to resistance such as monooxygenases, carboxylesterases, glutathione S-transferases and heme-binding. Polymorphism analysis of CYP9J27 sequences revealed a high level of polymorphism (except in Joho Bharu), suggesting a limited directional selection on this gene. In silico analysis of CYP9J27 activity through modelling and docking simulations suggested that this gene is involved in the multiple resistance in Malaysian populations as it is predicted to metabolise pyrethroids, DDT and bendiocarb.
CONCLUSION/SIGNIFICANCE: The predominant over-expression of cytochrome P450s suggests that synergist-based (PBO) control tools could be utilised to improve control of this major dengue vector across Malaysia.
Fulltext The Cytochrome P450 gene CYP6P12 confers pyrethroid resistance in kdr-free Malaysian populations of the dengue vector Aedes albopictus

Ishak IH, Riveron JM, Ibrahim SS, Stott R, Longbottom J, Irving H, et al.

Sci Rep, 2016 Apr 20;6:24707.
PMID: 27094778 DOI: 10.1038/srep24707

Control of Aedes albopictus, major dengue and chikungunya vector, is threatened by growing cases of insecticide resistance. The mechanisms driving this resistance remain poorly characterised. This study investigated the molecular basis of insecticide resistance in Malaysian populations of Ae. albopictus. Microarray-based transcription profiling revealed that metabolic resistance (cytochrome P450 up-regulation) and possibly a reduced penetration mechanism (consistent over-expression of cuticular protein genes) were associated with pyrethroid resistance. CYP6P12 over-expression was strongly associated with pyrethroid resistance whereas CYP6N3 was rather consistently over-expressed across carbamate and DDT resistant populations. Other detoxification genes also up-regulated in permethrin resistant mosquitoes included a glucuronosyltransferase (AAEL014279-RA) and the glutathione-S transferases GSTS1 and GSTT3. Functional analyses further supported that CYP6P12 contributes to pyrethroid resistance in Ae. albopictus as transgenic expression of CYP6P12 in Drosophila was sufficient to confer pyrethroid resistance in these flies. Furthermore, molecular docking simulations predicted CYP6P12 possessing enzymatic activity towards pyrethroids. Patterns of polymorphism suggested early sign of selection acting on CYP6P12 but not on CYP6N3. The major role played by P450 in the absence of kdr mutations suggests that addition of the synergist PBO to pyrethroids could improve the efficacy of this insecticide class and overcome resistance in field populations of Ae. albopictus.
Fulltext Genome-Wide Transcription and Functional Analyses Reveal Heterogeneous Molecular Mechanisms Driving Pyrethroids Resistance in the Major Malaria Vector Anopheles funestus Across Africa

Riveron JM, Ibrahim SS, Mulamba C, Djouaka R, Irving H, Wondji MJ, et al.

G3 (Bethesda), 2017 06 07;7(6):1819-1832.
PMID: 28428243 DOI: 10.1534/g3.117.040147

Pyrethroid resistance in malaria vector, An. funestus is increasingly reported across Africa, threatening the sustainability of pyrethroid-based control interventions, including long lasting insecticidal nets (LLINs). Managing this problem requires understanding of the molecular basis of the resistance from different regions of the continent, to establish whether it is being driven by a single or independent selective events. Here, using a genome-wide transcription profiling of pyrethroid resistant populations from southern (Malawi), East (Uganda), and West Africa (Benin), we investigated the molecular basis of resistance, revealing strong differences between the different African regions. The duplicated cytochrome P450 genes (CYP6P9a and CYP6P9b) which were highly overexpressed in southern Africa are not the most upregulated in other regions, where other genes are more overexpressed, including GSTe2 in West (Benin) and CYP9K1 in East (Uganda). The lack of directional selection on both CYP6P9a and CYP6P9b in Uganda in contrast to southern Africa further supports the limited role of these genes outside southern Africa. However, other genes such as the P450 CYP9J11 are commonly overexpressed in all countries across Africa. Here, CYP9J11 is functionally characterized and shown to confer resistance to pyrethroids and moderate cross-resistance to carbamates (bendiocarb). The consistent overexpression of GSTe2 in Benin is coupled with a role of allelic variation at this gene as GAL4-UAS transgenic expression in Drosophila flies showed that the resistant 119F allele is highly efficient in conferring both DDT and permethrin resistance than the L119. The heterogeneity in the molecular basis of resistance and cross-resistance to insecticides in An. funestus populations throughout sub-Saharan African should be taken into account in designing resistance management strategies.
Fulltext Occupational Injury Risk Mitigation: Machine Learning Approach and Feature Optimization for Smart Workplace Surveillance

Khairuddin MZF, Lu Hui P, Hasikin K, Abd Razak NA, Lai KW, Mohd Saudi AS, et al.

Int J Environ Res Public Health, 2022 Oct 27;19(21).
PMID: 36360843 DOI: 10.3390/ijerph192113962

Forecasting the severity of occupational injuries shall be all industries' top priority. The use of machine learning is theoretically valuable to assist the predictive analysis, thus, this study attempts to propose a feature-optimized predictive model for anticipating occupational injury severity. A public database of 66,405 occupational injury records from OSHA is analyzed using five sets of machine learning models: Support Vector Machine, K-Nearest Neighbors, Naïve Bayes, Decision Tree, and Random Forest. For model comparison, Random Forest outperformed other models with higher accuracy and F1-score. Therefore, it highlighted the potential of ensemble learning as a more accurate prediction model in the field of occupational injury. In constructing the model, this study also proposed the feature optimization technique that revealed the three most important features; 'nature of injury', 'type of event', and 'affected body part' in developing model. The accuracy of the Random Forest model was improved by 0.5% or 0.895 and 0.954 for the prediction of hospitalization and amputation, respectively by redeveloping and optimizing the model with hyperparameter tuning. The feature optimization is essential in providing insight knowledge to the Safety and Health Practitioners for future injury corrective and preventive strategies. This study has shown promising potential for smart workplace surveillance.
Fulltext Systematic Review of Brain-Eating Amoeba: A Decade Update

Ahmad Zamzuri M'I, Abd Majid FN, Mihat M, Ibrahim SS, Ismail M, Abd Aziz S, et al.

Int J Environ Res Public Health, 2023 Feb 09;20(4).
PMID: 36833715 DOI: 10.3390/ijerph20043021

INTRODUCTION: Primary amoebic meningoencephalitis (PAM) is a rare but lethal infection of the brain caused by a eukaryote called Naegleria fowleri (N. fowleri). The aim of this review is to consolidate the recently published case reports of N. fowleri infection by describing its epidemiology and clinical features with the goal of ultimately disseminating this information to healthcare personnel.
METHODS: A comprehensive literature search was carried out using PubMed, Web of Science, Scopus, and OVID databases until 31 December 2022 by two independent reviewers. All studies from the year 2013 were extracted, and quality assessments were carried out meticulously prior to their inclusion in the final analysis.
RESULTS: A total of 21 studies were selected for qualitative analyses out of the 461 studies extracted. The cases were distributed globally, and 72.7% of the cases succumbed to mortality. The youngest case was an 11-day-old boy, while the eldest was a 75-year-old. Significant exposure to freshwater either from recreational activities or from a habit of irrigating the nostrils preceded onset. The symptoms at early presentation included fever, headache, and vomiting, while late sequalae showed neurological manifestation. An accurate diagnosis remains a challenge, as the symptoms mimic bacterial meningitis. Confirmatory tests include the direct visualisation of the amoeba or the use of the polymerase chain reaction method.
CONCLUSIONS: N. fowleri infection is rare but leads to PAM. Its occurrence is worldwide with a significant risk of fatality. The suggested probable case definition based on the findings is the acute onset of fever, headache, and vomiting with meningeal symptoms following exposure to freshwater within the previous 14 days. Continuous health promotion and health education activities for the public can help to improve knowledge and awareness prior to engagement in freshwater activities.
Fulltext Permeation Flux Prediction of Vacuum Membrane Distillation Using Hybrid Machine Learning Techniques

Ismael BH, Khaleel F, Ibrahim SS, Khaleel SR, AlOmar MK, Masood A, et al.

Membranes (Basel), 2023 Dec 05;13(12).
PMID: 38132904 DOI: 10.3390/membranes13120900

Vacuum membrane distillation (VMD) has attracted increasing interest for various applications besides seawater desalination. Experimental testing of membrane technologies such as VMD on a pilot or large scale can be laborious and costly. Machine learning techniques can be a valuable tool for predicting membrane performance on such scales. In this work, a novel hybrid model was developed based on incorporating a spotted hyena optimizer (SHO) with support vector machine (SVR) to predict the flux pressure in VMD. The SVR-SHO hybrid model was validated with experimental data and benchmarked against other machine learning tools such as artificial neural networks (ANNs), classical SVR, and multiple linear regression (MLR). The results show that the SVR-SHO predicted flux pressure with high accuracy with a correlation coefficient (R) of 0.94. However, other models showed a lower prediction accuracy than SVR-SHO with R-values ranging from 0.801 to 0.902. Global sensitivity analysis was applied to interpret the obtained result, revealing that feed temperature was the most influential operating parameter on flux, with a relative importance score of 52.71 compared to 17.69, 17.16, and 14.44 for feed flowrate, vacuum pressure intensity, and feed concentration, respectively.
Understanding The Mimicker: Epidemiological Pattern and Determinant of Melioidosis Mortality in Negeri Sembilan, Malaysia

Md Hanif SA, Hassan MR, Rafi'i MR, Abdul Halim AFN, Ahmad Zamzuri M'I, Ismail M, et al.

PLoS Negl Trop Dis, 2024 May 06;18(5):e0012147.
PMID: 38709822 DOI: 10.1371/journal.pntd.0012147

BACKGROUND: Melioidosis, a tropical infectious disease caused by Burkholderia pseudomallei, is epidemic in most region in Southeast Asia with high case fatality. However, there is scanty information regarding the disease's epidemiological pattern, demographics, and underlying risk factors.
METHOD: This 5-year retrospective study of 185 confirmed cases which were taken from the Negeri Sembilan Melioidosis Registry between 2018 and 2022. We aim to describe the incidence, mortality rate, case fatality, relationship with meteorology, and factors that influence mortality in this central region of Peninsular Malaysia.
RESULTS: Incidence rate (IR) of melioidosis in Negeri Sembilan is varied at 1.9 to 5.1 with mean of 3.1 in 100,000 population per year. IR varied between districts in the state from zero to 22.01 in 100,000 population per year. Mortality rate were ranged from 0.17 to 0.74 cases with mean of 0.44 cases in 100,000 population per year. The case fatality rate of this state scattered from 8.70% to 16.67%. There were no significant linear associations between cases and deaths with monthly rainfall and humidity. The mean age of patients was 52.8 years, predominated with age around 41-60 years old. Males (77.8%) predominated, and the majority of cases were Malays (88.9%) and had exposed to soil related activities (74.6%). Mortality from melioidosis was more likely in Bumiputera and non-Malaysians (p<0.05). Patients who had at least one comorbidity were at a higher risk of death from melioidosis (p<0.05). Diabetes mellitus was found in 41.1% of all identified cases, making it a major underlying risk factor for both developing and dying from melioidosis (aOR:19.32, 95%CI:1.91-195.59, p<0.05). Hypertension and mortality status in melioidosis are also significantly correlated (aOR: 7.75, 95% CI: 2.26-26.61, p<0.05).
CONCLUSION: The epidemiological patterns of cases reported from Negeri Sembilan are consistent for the most part from previous studies in other states in Malaysia and global with regard to its incidence, case fatality, demographic and predisposing chronic diseases. Diabetes mellitus and hypertension were significantly linked to increased mortality among all determinants.