Diagnosis of Malaria Parasites Plasmodium spp. in Endemic Areas: Current Strategies for an Ancient Disease

Machine learning for predicting Plasmodium liver stage development in vitro using microscopy imaging

Malaria, a significant global health challenge, is caused by Plasmodium parasites. The Plasmodium liver stage plays a pivotal role in the establishment of the infection. This study focuses on the liver stage development of the model organism Plasmodium berghei, employing fluorescent microscopy imaging and convolutional neural networks (CNNs) for analysis. Convolutional neural networks have been recently proposed as a viable option for tasks such as malaria detection, prediction of host-pathogen interactions, or drug discovery. Our research aimed to predict the transition of Plasmodium-infected liver cells to the merozoite stage, a key development phase, 15 hours in advance. We collected and analyzed hourly imaging data over a span of at least 38 hours from 400 sequences, encompassing 502 parasites. Our method was compared to human annotations to validate its efficacy. Performance metrics, including the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity, were evaluated on an independent test dataset. The outcomes revealed an AUC of 0.873, a sensitivity of 84.6%, and a specificity of 83.3%, underscoring the potential of our CNN-based framework to predict liver stage development of P. berghei. These findings not only demonstrate the feasibility of our methodology but also could potentially contribute to the broader understanding of parasite biology.

Identification of Malaria-Selective Proteasome β5 Inhibitors Through Pharmacophore Modeling, Molecular Docking, and Molecular Dynamics Simulation

Malaria remains a global health challenge, with increasing resistance to frontline antimalarial treatments such as artemisinin (ART) threatening the efficacy of current therapies. In this study, we investigated the potential of FDA-approved drugs to selectively inhibit the malarial proteasome, a novel target for antimalarial drug development. By leveraging pharmacophore modeling, molecular docking, molecular dynamics (MD) simulations, and binding free-energy calculations, we screened a library of compounds to identify inhibitors selective for the Plasmodium proteasome over the human proteasome. Our results highlighted Argatroban, LM-3632, Atazanavir Sulfate, and Pemetrexed Hydrate as promising candidates, with Argatroban and Pemetrexed Hydrate showing the highest binding affinity and selectivity toward the malarial proteasome. MD simulation and gmx_MMPBSA analysis confirmed the compounds' ability to remain within the active site of the malarial proteasome, while some exited or exhibited reduced stability within the human proteasome. This study underscores the potential of proteasome-targeting drugs for overcoming malarial drug resistance and paves the way for the further optimization of these compounds.

A transfer learning approach to identify Plasmodium in microscopic images

Plasmodium parasites cause Malaria disease, which remains a significant threat to global health, affecting 200 million people and causing 400,000 deaths yearly. Plasmodium falciparum and Plasmodium vivax remain the two main malaria species affecting humans. Identifying the malaria disease in blood smears requires years of expertise, even for highly trained specialists. Literature studies have been coping with the automatic identification and classification of malaria. However, several points must be addressed and investigated so these automatic methods can be used clinically in a Computer-aided Diagnosis (CAD) scenario. In this work, we assess the transfer learning approach by using well-known pre-trained deep learning architectures. We considered a database with 6222 Region of Interest (ROI), of which 6002 are from the Broad Bioimage Benchmark Collection (BBBC), and 220 were acquired locally by us at Fundação Oswaldo Cruz (FIOCRUZ) in Porto Velho Velho, Rondônia-Brazil, which is part of the legal Amazon. We exhaustively cross-validated the dataset using 100 distinct partitions with 80% train and 20% test for each considering circular ROIs (rough segmentation). Our experimental results show that DenseNet201 has a potential to identify Plasmodium parasites in ROIs (infected or uninfected) of microscopic images, achieving 99.41% AUC with a fast processing time. We further validated our results, showing that DenseNet201 was significantly better (99% confidence interval) than the other networks considered in the experiment. Our results support claiming that transfer learning with texture features potentially differentiates subjects with malaria, spotting those with Plasmodium even in Leukocytes images, which is a challenge. In Future work, we intend scale our approach by adding more data and developing a friendly user interface for CAD use. We aim at aiding the worldwide population and our local natives living nearby the legal Amazon's rivers.

Cloning, Expression, Purification, and Characterization of Lactate Dehydrogenase from Plasmodium knowlesi: A Zoonotic Malaria Parasite

Plasmodium knowlesi is the only Plasmodium that causes zoonotic disease among the Plasmodium that cause infection in humans. It is fatal due to its short asexual growth cycle within 24 h. Lactate dehydrogenase (LDH), an enzyme that catalyzes the final step of glycolysis, is a biomarker for diagnosing infection by Plasmodium spp. parasite. Therefore, this study aimed to efficiently produce the soluble form of P. knowlesi LDH (PkLDH) using a bacterial expression system for studying malaria caused by P. knowlesi. Recombinant pET-21a(+)-PkLDH plasmid was constructed by inserting the PkLDH gene into a pET-21a(+) expression vector. Subsequently, the recombinant plasmid was inserted into the protein-expressing Escherichia coli Rosetta(DE3) strain, and the optimal conditions for overexpression of the PkLDH protein were established using this strain. We obtained a yield of 52.0 mg/L PkLDH from the Rosetta(DE3) strain and confirmed an activity of 483.9 U/mg through experiments. This methodology for high-efficiency PkLDH production can be utilized for the development of diagnostic methods and drug candidates for distinguishing malaria caused by P. knowlesi.

Hesitancy towards R21/Matrix-M malaria vaccine among Ghanaian parents and attitudes towards immunizing non-eligible children: a cross-sectional survey

BACKGROUND

The newly developed malaria vaccine called "R21/Matrix-M malaria vaccine" showed a high safety and efficacy level, and Ghana is the first country to approve this new vaccine. The present study aimed to evaluate the rate of vaccine hesitancy (VH) towards the newly developed malaria vaccine among parents who currently have children who are not eligible for the vaccine but may be eligible in the near future. Additionally, the study aimed to identify the factors that could potentially influence VH.

METHODS

A cross-sectional survey using both online-based questionnaires and face-to-face interviews was conducted in Ghana from June to August 2023. The survey specifically targeted parents of ineligible children for vaccination, including those aged less than 5 months or between 3 and 12 years. The Parent Attitudes about Childhood Vaccination (PACV) scale was used to assess parental VH.

RESULTS

A total of 765 people participated in this study. Their median age was 36.0 years with an interquartile range of 31.0-41.0 years, 67.7% were females, 41.8% completed their tertiary education, 63.3% were married, 81.6% worked in non-healthcare sectors, and 59.7% reported that their monthly income was insufficient. About one-third (34.5%) of the parents were hesitant to give their children the R21/Matrix-M malaria vaccine. The following predictors were associated with VH: working in the healthcare sector (adjusted odds ratio (AOR) = 0.50; 95% confidence interval (CI) 0.30-0.80; p = 0.005), having the other parent working in the healthcare sector (AOR = 0.54; 95% CI 0.30-0.94; p = 0.034), and not taking scheduled routine vaccinations (AOR = 1.90; 95% CI 1.27-2.84; p = 0.002).

CONCLUSIONS

Addressing VH is crucial for optimizing R21/Matrix-M vaccine coverage in Ghana's malaria control strategy. By tackling VH issues, Ghana can effectively safeguard children's health in malaria-prone areas.

The Laboratory Diagnosis of Malaria: A Focus on the Diagnostic Assays in Non-Endemic Areas

Even if malaria is rare in Europe, it is a medical emergency and programs for its control should ensure both an early diagnosis and a prompt treatment within 24-48 h from the onset of the symptoms. The increasing number of imported malaria cases as well as the risk of the reintroduction of autochthonous cases encouraged laboratories in non-endemic countries to adopt diagnostic methods/algorithms. Microscopy remains the gold standard, but with limitations. Rapid diagnostic tests have greatly expanded the ability to diagnose malaria for rapid results due to simplicity and low cost, but they lack sensitivity and specificity. PCR-based assays provide more relevant information but need well-trained technicians. As reported in the World Health Organization Global Technical Strategy for Malaria 2016-2030, the development of point-of-care testing is important for the improvement of diagnosis with beneficial consequences for prompt/accurate treatment and for preventing the spread of the disease. Despite their limitations, diagnostic methods contribute to the decline of malaria mortality. Recently, evidence suggested that artificial intelligence could be utilized for assisting pathologists in malaria diagnosis.

Novel secretory organelles of parasite origin - at the center of host-parasite interaction

Reorganization of cell organelle-deprived host red blood cells by the apicomplexan malaria parasite Plasmodium falciparum enables their cytoadherence to endothelial cells that line the microvasculature. This increases the time red blood cells infected with mature developmental stages remain within selected organs such as the brain to avoid the spleen passage, which can lead to severe complications and cumulate in patient death. The Maurer's clefts are a novel secretory organelle of parasite origin established by the parasite in the cytoplasm of the host red blood cell in order to facilitate the establishment of cytoadherence by conducting the trafficking of immunovariant adhesins to the host cell surface. Another important function of the organelle is the sorting of other proteins the parasite traffics into its host cell. Although the organelle is of high importance for the pathology of malaria, additional putative functions, structure, and genesis remain shrouded in mystery more than a century after its discovery. In this review, we highlight our current knowledge about the Maurer's clefts and other novel secretory organelles established within the host cell cytoplasm by human-pathogenic malaria parasites and other parasites that reside within human red blood cells.

Expression, Purification, and Characterization of Plasmodium vivax Lactate Dehydrogenase from Bacteria without Codon Optimization

Plasmodium vivax is the most widespread cause of malaria, especially in subtropical and temperate regions such as Asia-Pacific and America. P. vivax lactate dehydrogenase (PvLDH), an essential enzyme in the glycolytic pathway, is required for the development and reproduction of the parasite. Thus, LDH from these parasites has garnered attention as a diagnostic biomarker for malaria and as a potential molecular target for developing antimalarial drugs. In this study, we prepared a transformed Escherichia coli strain for the overexpression of PvLDH without codon optimization. We introduced this recombinant plasmid DNA prepared by insertion of the PvLDH gene in the pET-21a(+) expression vector, into the Rosetta(DE3), an E. coli strain suitable for eukaryotic protein expression. The time, temperature, and inducer concentration for PvLDH expression from this E. coli Rosetta(DE3), containing the original PvLDH gene, were optimized. We obtained PvLDH with a 31.0 mg/L yield and high purity (>95%) from this Rosetta(DE3) strain. The purified protein was characterized structurally and functionally. The PvLDH expressed and purified from transformed bacteria without codon optimization was successfully demonstrated to exhibit its potential tetramer structure and enzyme activity. These findings are expected to provide valuable insights for research on infectious diseases, metabolism, diagnostics, and therapeutics for malaria caused by P. vivax.

Malaria therapeutics: are we close enough?

Malaria is a vector-borne parasitic disease caused by the apicomplexan protozoan parasite Plasmodium. Malaria is a significant health problem and the leading cause of socioeconomic losses in developing countries. WHO approved several antimalarials in the last 2 decades, but the growing resistance against the available drugs has worsened the scenario. Drug resistance and diversity among Plasmodium strains hinder the path of eradicating malaria leading to the use of new technologies and strategies to develop effective vaccines and drugs. A timely and accurate diagnosis is crucial for any disease, including malaria. The available diagnostic methods for malaria include microscopy, RDT, PCR, and non-invasive diagnosis. Recently, there have been several developments in detecting malaria, with improvements leading to achieving an accurate, quick, cost-effective, and non-invasive diagnostic tool for malaria. Several vaccine candidates with new methods and antigens are under investigation and moving forward to be considered for clinical trials. This article concisely reviews basic malaria biology, the parasite's life cycle, approved drugs, vaccine candidates, and available diagnostic approaches. It emphasizes new avenues of therapeutics for malaria.

LC-MS Analysis, Computational Investigation, and Antimalarial Studies of Azadirachta indica Fruit

Malaria is a deadly disease that continues to pose a threat to children and maternal well-being. This study was designed to identify the chemical constituents in the ethanolic fruit extract of Azadirachta indica, elucidate the pharmacological potentials of identified phytochemicals through the density functional theory method and carry out the antimalarial activity of extract using chemosuppression and curative models. The liquid chromatography-mass spectrometry (LC-MS) analysis of the ethanolic extract was carried out, followed by the density functional theory studies of the identified phytochemicals using B3LYP and 6-31G (d, p) basis set. The antimalarial assays were performed using the chemosuppression (4 days) and curative models. The LC-MS fingerprint of the extract led to the identification of desacetylnimbinolide, nimbidiol, O-methylazadironolide, nimbidic acid, and desfurano-6α-hydroxyazadiradione. Also, the frontier molecular orbital properties, molecular electrostatic potential, and dipole moment studies revealed the identified phytochemicals as possible antimalarial agents. The ethanolic extract of A indica fruit gave 83% suppression at 800 mg/kg, while 84% parasitaemia clearance was obtained in the curative study. The study provided information about the phytochemicals and background pharmacological evidences of the antimalarial ethnomedicinal claim of A indica fruit. Thus, isolation and structure elucidation of the identified phytochemicals from the active ethanolic extract and extensive antimalarial studies towards the discovery of new therapeutic agents is recommended for further studies.

Performance Analysis of Deep Learning Algorithms in Diagnosis of Malaria Disease

Malaria is predominant in many subtropical nations with little health-monitoring infrastructure. To forecast malaria and condense the disease's impact on the population, time series prediction models are necessary. The conventional technique of detecting malaria disease is for certified technicians to examine blood smears visually for parasite-infected RBC (red blood cells) underneath a microscope. This procedure is ineffective, and the diagnosis depends on the individual performing the test and his/her experience. Automatic image identification systems based on machine learning have previously been used to diagnose malaria blood smears. However, so far, the practical performance has been insufficient. In this paper, we have made a performance analysis of deep learning algorithms in the diagnosis of malaria disease. We have used Neural Network models like CNN, MobileNetV2, and ResNet50 to perform this analysis. The dataset was extracted from the National Institutes of Health (NIH) website and consisted of 27,558 photos, including 13,780 parasitized cell images and 13,778 uninfected cell images. In conclusion, the MobileNetV2 model outperformed by achieving an accuracy rate of 97.06% for better disease detection. Also, other metrics like training and testing loss, precision, recall, fi-score, and ROC curve were calculated to validate the considered models.

Advances in Microfluidics for Single Red Blood Cell Analysis

The utilizations of microfluidic chips for single RBC (red blood cell) studies have attracted great interests in recent years to filter, trap, analyze, and release single erythrocytes for various applications. Researchers in this field have highlighted the vast potential in developing micro devices for industrial and academia usages, including lab-on-a-chip and organ-on-a-chip systems. This article critically reviews the current state-of-the-art and recent advances of microfluidics for single RBC analyses, including integrated sensors and microfluidic platforms for microscopic/tomographic/spectroscopic single RBC analyses, trapping arrays (including bifurcating channels), dielectrophoretic and agglutination/aggregation studies, as well as clinical implications covering cancer, sepsis, prenatal, and Sickle Cell diseases. Microfluidics based RBC microarrays, sorting/counting and trapping techniques (including acoustic, dielectrophoretic, hydrodynamic, magnetic, and optical techniques) are also reviewed. Lastly, organs on chips, multi-organ chips, and drug discovery involving single RBC are described. The limitations and drawbacks of each technology are addressed and future prospects are discussed.

Cerebral Malaria and Neuronal Implications of Plasmodium Falciparum Infection: From Mechanisms to Advanced Models

Reorganization of host red blood cells by the malaria parasite Plasmodium falciparum enables their sequestration via attachment to the microvasculature. This artificially increases the dwelling time of the infected red blood cells within inner organs such as the brain, which can lead to cerebral malaria. Cerebral malaria is the deadliest complication patients infected with P. falciparum can experience and still remains a major public health concern despite effective antimalarial therapies. Here, the current understanding of the effect of P. falciparum cytoadherence and their secreted proteins on structural features of the human blood-brain barrier and their involvement in the pathogenesis of cerebral malaria are highlighted. Advanced 2D and 3D in vitro models are further assessed to study this devastating interaction between parasite and host. A better understanding of the molecular mechanisms leading to neuronal and cognitive deficits in cerebral malaria will be pivotal in devising new strategies to treat and prevent blood-brain barrier dysfunction and subsequent neurological damage in patients with cerebral malaria.

Advances and challenges in automated malaria diagnosis using digital microscopy imaging with artificial intelligence tools: A review

Malaria is an infectious disease caused by parasites of the genus Plasmodium spp. It is transmitted to humans by the bite of an infected female Anopheles mosquito. It is the most common disease in resource-poor settings, with 241 million malaria cases reported in 2020 according to the World Health Organization. Optical microscopy examination of blood smears is the gold standard technique for malaria diagnosis; however, it is a time-consuming method and a well-trained microscopist is needed to perform the microbiological diagnosis. New techniques based on digital imaging analysis by deep learning and artificial intelligence methods are a challenging alternative tool for the diagnosis of infectious diseases. In particular, systems based on Convolutional Neural Networks for image detection of the malaria parasites emulate the microscopy visualization of an expert. Microscope automation provides a fast and low-cost diagnosis, requiring less supervision. Smartphones are a suitable option for microscopic diagnosis, allowing image capture and software identification of parasites. In addition, image analysis techniques could be a fast and optimal solution for the diagnosis of malaria, tuberculosis, or Neglected Tropical Diseases in endemic areas with low resources. The implementation of automated diagnosis by using smartphone applications and new digital imaging technologies in low-income areas is a challenge to achieve. Moreover, automating the movement of the microscope slide and image autofocusing of the samples by hardware implementation would systemize the procedure. These new diagnostic tools would join the global effort to fight against pandemic malaria and other infectious and poverty-related diseases.

Evaluation of antibody serology to determine current helminth and Plasmodium falciparum infections in a co-endemic area in Southern Mozambique

Background

Soil-transmitted helminths (STH), Schistosoma spp. and Plasmodium falciparum are parasites of major public health importance and co-endemic in many sub-Saharan African countries. Management of these infections requires detection and treatment of infected people and evaluation of large-scale measures implemented. Diagnostic tools are available but their low sensitivity, especially for low intensity helminth infections, leaves room for improvement. Antibody serology could be a useful approach thanks to its potential to detect both current infection and past exposure.

Methodology

We evaluated total IgE responses and specific-IgG levels to 9 antigens from STH, 2 from Schistosoma spp., and 16 from P. falciparum, as potential markers of current infection in a population of children and adults from Southern Mozambique (N = 715). Antibody responses were measured by quantitative suspension array Luminex technology and their performance was evaluated by ROC curve analysis using microscopic and molecular detection of infections as reference.

Principal findings

IgG against the combination of EXP1, AMA1 and MSP2 (P. falciparum) in children and NIE (Strongyloides stercoralis) in adults and children had the highest accuracies (AUC = 0.942 and AUC = 0.872, respectively) as markers of current infection. IgG against the combination of MEA and Sm25 (Schistosoma spp.) were also reliable markers of current infection (AUC = 0.779). In addition, IgG seropositivity against 20 out of the 27 antigens in the panel differentiated the seropositive endemic population from the non-endemic population, suggesting a possible role as markers of exposure although sensitivity could not be assessed.

Conclusions

We provided evidence for the utility of antibody serology to detect current infection with parasites causing tropical diseases in endemic populations. In addition, most of the markers have potential good specificity as markers of exposure. We also showed the feasibility of measuring antibody serology with a platform that allows the integration of control and elimination programs for different pathogens.

Parasitic worms and Plasmodium falciparum, the causal agent of malaria, are among the most relevant parasitic diseases of our time and efforts are under way for their control and, ultimately, elimination. An accurate diagnosis is relevant for case management, but also allows calculating the prevalence and evaluating the effectiveness of treatment and control measures. Unfortunately, current diagnostic methods for parasitic worms are not optimal and many infections remain undetected. As for P. falciparum, current diagnostic techniques are satisfactory but do not allow for ascertaining exposure, which is relevant for evaluating control measures. Here we investigated the utility of measuring antibodies to these parasites as a diagnostic method. Our results indicate that it is possible to detect current infection with parasitic worms and P. falciparum using antibody detection with a moderate to high accuracy. We also show that antibodies against the antigens in this study have potential as markers of exposure. Importantly, we used a platform that allows for the simultaneous detection of immunoglobulins to different parasites, which would be extremely useful as a tool to integrate control and elimination programs for several pathogens.

Blood Cell Analysis: From Traditional Methods to Super-Resolution Microscopy

Blood cell analysis is essential for the diagnosis and identification of hematological malignancies. The use of digital microscopy systems has been extended in clinical laboratories. Super-resolution microscopy (SRM) has attracted wide attention in the medical field due to its nanoscale spatial resolution and high sensitivity. It is considered to be a potential method of blood cell analysis that may have more advantages than traditional approaches such as conventional optical microscopy and hematology analyzers in certain examination projects. In this review, we firstly summarize several common blood cell analysis technologies in the clinic, and analyze the advantages and disadvantages of these technologies. Then, we focus on the basic principles and characteristics of three representative SRM techniques, as well as the latest advances in these techniques for blood cell analysis. Finally, we discuss the developmental trend and possible research directions of SRM, and provide some discussions on further development of technologies for blood cell analysis.

Review of the Current Landscape of the Potential of Nanotechnology for Future Malaria Diagnosis, Treatment, and Vaccination Strategies

Malaria eradication has for decades been on the global health agenda, but the causative agents of the disease, several species of the protist parasite Plasmodium, have evolved mechanisms to evade vaccine-induced immunity and to rapidly acquire resistance against all drugs entering clinical use. Because classical antimalarial approaches have consistently failed, new strategies must be explored. One of these is nanomedicine, the application of manipulation and fabrication technology in the range of molecular dimensions between 1 and 100 nm, to the development of new medical solutions. Here we review the current state of the art in malaria diagnosis, prevention, and therapy and how nanotechnology is already having an incipient impact in improving them. In the second half of this review, the next generation of antimalarial drugs currently in the clinical pipeline is presented, with a definition of these drugs' target product profiles and an assessment of the potential role of nanotechnology in their development. Opinions extracted from interviews with experts in the fields of nanomedicine, clinical malaria, and the economic landscape of the disease are included to offer a wider scope of the current requirements to win the fight against malaria and of how nanoscience can contribute to achieve them.

Development of a Fast Chemiluminescent Magneto-Immunoassay for Sensitive Plasmodium falciparum Detection in Whole Blood

The World Health Organization (WHO) estimates that over three billion people are at risk of acquiring malaria, a parasitic infection that produces more than 200 million new infections and nearly half a million deaths each year. Expanding the access to early diagnosis and treatment is one of the most effective ways to prevent disease complications, reduce patient mortality, and curb the community transmission. However, none of the diagnostic methods used currently for malaria detection, including light microscopy, polymerase chain reaction (PCR), and rapid diagnostic tests (RDTs), can provide simultaneously fast results, high sensitivity, and parasitaemia quantitation with minimal user intervention. Here, we present a magneto-immunoassay that, based on the unique combination of magnetic beads (MB), an enzymatic signal amplifier (Poly-HRP), and chemiluminescence detection, provides fast, sensitive, and quantitative malaria diagnosis with easy user manipulation. This assay quantifies Plasmodium falciparum lactate dehydrogenase (PfLDH) in lysed whole blood samples in <15 min, exhibiting a limit of detection (LOD) of 0.02 ng mL^-1 and providing patient stratification consistent with the reference methods. These figures of merit surpass the performance of the magneto-immunoassays reported previously for Plasmodium detection and demonstrate for the first time that the proposed combination of MB, Poly-HRP, and chemiluminescence detection produces extremely fast, simple, and efficient assays that approach the requirements of point-of-care (POC) malaria surveillance.

New insights into the spread of resistance to artemisinin and its analogues

Plasmodium falciparum, the causative agent of malaria, has been developing resistance to several drugs worldwide for more than five decades. Initially, resistance was against drugs such as chloroquine, pyrimethamine, sulfadoxine, mefloquine and quinine. Research studies are now reporting parasites with resistance to the most effective and novel drug used against malaria infection worldwide, namely artemisinin. For this reason, the first-line treatment strategy of artemisinin-based combination therapy is becoming unsuccessful in areas where drug resistance is highly prevalent. The increase in artemisinin-resistant P. falciparum strains has threatened international efforts to eliminate malarial infections and to reduce the disease burden. Detection of several phenotypes that display artemisinin resistance, specification of basic genetic factors, the discovery of molecular pathways, and evaluation of its clinical outcome are possible by the current series of research on genomics and transcriptomic levels in Asia and Africa. In artemisinin resistance, slow parasite clearance among malaria-infected patients and enhanced in vitro survival of parasites occurs at the early ring stage. This resistance is due to single nucleotide polymorphisms within the Kelch 13 gene of the parasite and is related to significantly upregulated resistance signalling pathways; thus, the pro-oxidant action of artemisinins can be antagonised. New strategies are required to halt the spread of artemisinin-resistant malarial parasites.

Chemical Biology Tools To Investigate Malaria Parasites

Parasitic diseases like malaria tropica have been shaping human evolution and history since the beginning of mankind. After infection, the response of the human host ranges from asymptomatic to severe and may culminate in death. Therefore, proper examination of the parasite's biology is pivotal to deciphering unique molecular, biochemical and cell biological processes, which in turn ensure the identification of treatment strategies, such as potent drug targets and vaccine candidates. However, implementing molecular biology methods for genetic manipulation proves to be difficult for many parasite model organisms. The development of fast and straightforward applicable alternatives, for instance small-molecule probes from the field of chemical biology, is essential. In this review, we will recapitulate the highlights of previous molecular and chemical biology approaches that have already created insight and understanding of the malaria parasite Plasmodium falciparum. We discuss current developments from the field of chemical biology and explore how their application could advance research into this parasite in the future. We anticipate that the described approaches will help to close knowledge gaps in the biology of P. falciparum and we hope that researchers will be inspired to use these methods to gain knowledge - with the aim of ending this devastating disease.

Microfluidic detection of human diseases: From liquid biopsy to COVID-19 diagnosis

Microfluidic devices can be thought of as comprising interconnected miniaturized compartments performing multiple experimental tasks individually or in parallel in an integrated fashion. Due to its small size, portability, and low cost, attempts have been made to incorporate detection assays into microfluidic platforms for diseases such as cancer and infection. Some of these technologies have served as point-of-care and sample-to-answer devices. The methods for detecting biomarkers in different diseases usually share similar principles and can conveniently be adapted to cope with arising health challenges. The COVID-19 pandemic is one such challenge that is testing the performance of both our conventional and newly-developed disease diagnostic technologies. In this mini-review, we will first look at the progress made in the past few years in applying microfluidics for liquid biopsy and infectious disease detection. Following that, we will use the current pandemic as an example to discuss how such technological advancements can help in the current health challenge and better prepare us for future ones.

Sensitive Immunoassay Detection of Plasmodium Lactate Dehydrogenase by Inductively Coupled Plasma Mass Spectrometry

Rapid, reliable, and sensitive detection of Plasmodium infection is central to malaria control and elimination. Many Malaria Rapid Diagnostic Tests (RDTs) developed for this purpose depend upon immunoassays that can be improved by advances in bound antibody sensor technology. In a previous study, immuno-polymerase chain reaction (PCR) was shown to provide highly sensitive detection of Plasmodium falciparum lactate dehydrogenase (PfLDH) in monoclonal antibody (mAb) sandwich assays. Here, we show comparably high immunoassay sensitivity by inductively coupled plasma mass spectrometry (ICP-MS) detection of gold nanoparticles (AuNPs). Following capture of PfLDH with the primary mAb and binding of the AuNP-labeled detection mAb, ICP-MS signals from the AuNPs provided quantitative measures of recombinant PfLDH test dilutions and P. falciparum-infected erythrocytes. A detection limit of 1.5 pg/mL was achieved with the PfLDH protein. Parasitemia in cultures of P. falciparum-infected erythrocytes could be detected to a lower limit of 1.6 parasite/μl (p/μl) for early ring-stage forms and 0.3 p/μl for mixed stages including mature trophozoites and schizont-stages. These results show that ICP-MS detection of AuNPs can support highly sensitive and accurate detection of Plasmodium infection.

The host mTOR pathway and parasitic diseases pathogenesis

The mechanistic (or mammalian) target of rapamycin (mTOR) is considered as a critical regulatory enzyme involved in essential signaling pathways affecting cell growth, cell proliferation, protein translation, regulation of cellular metabolism, and cytoskeletal structure. Also, mTOR signaling has crucial roles in cell homeostasis via processes such as autophagy. Autophagy prevents many pathogen infections and is involved on immunosurveillance and pathogenesis. Immune responses and autophagy are therefore key host responses and both are linked by complex mTOR regulatory mechanisms. In recent years, the mTOR pathway has been highlighted in different diseases such as diabetes, cancer, and infectious and parasitic diseases including leishmaniasis, toxoplasmosis, and malaria. The current review underlines the implications of mTOR signals and intricate networks on pathogen infections and the modulation of this master regulator by parasites. Parasitic infections are able to induce dynamic metabolic reprogramming leading to mTOR alterations in spite of many other ways impacting this regulatory network. Accordingly, the identification of parasite effects and interactions over such a complex modulation might reveal novel information regarding the biology of the abovementioned parasites and might allow the development of therapeutic strategies against parasitic diseases. In this sense, the effects of inhibiting the mTOR pathways are also considered in this context in the light of their potential for the prevention and treatment of parasitic diseases.

Palmitoylated Proteins in Plasmodium falciparum-Infected Erythrocytes: Investigation with Click Chemistry and Metabolic Labeling

The examination of the complex cell biology of the human malaria parasite Plasmodium falciparum usually relies on the time-consuming generation of transgenic parasites. Here, metabolic labeling and click chemistry are employed as a fast transfection-independent method for the microscopic examination of protein S-palmitoylation, an important post-translational modification during the asexual intraerythrocytic replication of P. falciparum. Applying various microscopy approaches such as confocal, single-molecule switching, and electron microscopy, differences in the extent of labeling within the different asexual developmental stages of P. falciparum and the host erythrocytes over time are observed.