Molecular surveillance of Kelch-13 gene in Plasmodium falciparum field isolates from Mayurbhanj District, Odisha, India, and in silico artemisinin-Kelch-13 protein interaction study.

The global malaria control and elimination program faces major threats due to the emergence and transmission of the anti-malarial drug-resistant strain of Plasmodium falciparum. Monitoring of artemisinin (ART) resistance marker Kelch-13 in the malaria-endemic region is essential in mitigating the disease's morbidity and mortality. The current study aimed to generate baseline information for further surveillance in the future. The current research was designed and conducted from July 2019 to June 2021 to monitor Pfkelch13 mutation at the molecular level in the eastern region of India. We also conducted an in silico study to understand the drug-protein interactions between ART and the protein crystal of PfKelch13 (KELCH) with PDB id:4ZGC. The kelch-13 gene was amplified by nested polymerase chain reaction (PCR) and sequenced through the Sanger sequencing method. Reference 3D7 clone (PF3D7_1343700) was used to align and probe all the sequences. The sequence analysis showed the absence of validated or associated mutation in the Kelch-13 propeller domain. The absence of natural selection in drug resistance was confirmed by the Tajima test. Further, in silico interaction studies between the drug ART and the Kelch propeller domain of P. falciparum were evaluated by structure predictions, molecular docking, molecular dynamics (MD) simulations, and estimations of binding free energies for the KELCH-ART complex. The results were compared with the apoprotein (KELCH-APO). The study confirmed the favorable binding of ART with the Kelch-13 propeller domain.

Artificial intelligence (AI): a new window to revamp the vector-borne disease control.

Artificial intelligence (AI) facilitates scientists to devise intelligent machines that work and behave like humans to resolve difficulties and problems by utilizing minimal resources. The Healthcare sector has benefited due to this. Mosquito-transmitted diseases pose a significant health risk. Despite all advances, present strategies for curbing these diseases still depend largely on controlling the mosquito vectors. This strategy demands an army of entomology experts for thorough monitoring, determining, and finally eradicating the targeted mosquito population. Deep learning (DL) algorithms may substitute such unmanageable processes. The current review focuses on how AI, with particular emphasis on deep learning, demonstrates effectiveness in quick detection, identification, monitoring, and finally controlling the target mosquito populations with minimal resources. It accelerates the pace of operation and data exploration on ongoing evolutionary status, tendency to feed blood, and age grading of mosquitoes. The successful combination of computer and biological sciences will provide practical insight and generate a new research niche in this study area.

An analysis of Plasmodium falciparum-K13 mutations in India.

Malaria is one of the deadliest parasitic diseases in human. Currently, Artemisinin-based combination therapy is considered as the gold standard and most common treatment option. However, the origin and transmission of Plasmodium falciparum from the Greater Mekong Subregion, which has decreased artemisinin (ART) sensitivity, has sparked global concern. The reduced ART sensitivity has been associated with mutations in the Atpase6 and Kelch13 propeller domain of Plasmodium falciparum. A molecular marker is critically needed to monitor the spread of artemisinin resistance. In this article, we reviewed the k13 mutations and potential marker for ART resistance in India. There have been fourteen mutations identified, three of which have been validated by the World Health Organization (WHO) as artemisinin resistance mutations (F446I, R561H/C, and R539T). Among them, the role of F446I and R561H/C in ART resistance is conflicting. R539T and G625R mutation has been identified as an ART- resistance marker in India.

First record of Lobothorax typus from Odisha coast, India, with molecular characterization and observation of its biphasic moulting.

Two distinct morphologies of Cymothoidae isopod, Lobothorax typus were collected from the marine water of Bay of Bengal, Goapalpur-on-Sea as the first record of this parasite from coastal water of Odisha, India. All specimens were found attached to the buccal region of different individuals of the same host fish Trichiurus lepturus. With the aid of COI gene sequencing and morphological analysis, the individuals were found to be conspecific. The most prominent variation among the two morphologies includes the size of 5th pereonite and pleon length to total body length ratio. These variations are as a result of the biphasic moulting process. Maximum Likelihood tree analysis based on COI gene sequences concluded the monophyletic taxonomy of different buccal attaching genera under the family Cymothoidae which is in congruence with their morphological divergence.

Diagnosing the drug resistance signature in Plasmodium falciparum: a review from contemporary methods to novel approaches.

The genome sequence project of the human malaria parasite Plasmodium falciparum reveal variations in the parasite DNA sequence. Most of these variations are single nucleotide polymorphism (SNP). A high frequency of single nucleotide polymorphism (SNP) in the Plasmodium falciparum population is usually a benchmark for anti-malarial resistance which allows parasites to be elusive to the chemotherapeutic agents, vaccine and vector control strategies, resulting in the leading cause of morbidity and mortality globally. The high density of drug resistance signature markers such as pfcrt,pfmdr1, pfdhps, pfdhfr, pfkelch13, pfatpase6 and pfmrp1 in the genome opens up a scope for the study of the genetic basis of this elusive parasite. The precise and prompt diagnosis of resistance strains of parasite plays vital role in malaria elimination program.This review probably shed light on contemporary SNP diagnostic tools used in molecular surveillance of Plasmodium falciparum drug resistance in terms of mechanism, reaction modalities, and development with their virtues and shortcomings.