Inference of the oxidative stress network in Anopheles stephensi upon Plasmodium infection

CSDE1 promotes miR-451 biogenesis

MicroRNAs are sequentially processed by RNase III enzymes Drosha and Dicer. miR-451 is a highly conserved miRNA in vertebrates which bypasses Dicer processing and instead relies on AGO2 for its maturation. miR-451 is highly expressed in erythrocytes and regulates the differentiation of erythroblasts into mature red blood cells. However, the mechanistic details underlying miR-451 biogenesis in erythrocytes remains obscure. Here, we report that the RNA binding protein CSDE1 which is required for the development of erythroblasts into erythrocytes, controls the expression of miR-451 in erythroleukemia cells. CSDE1 binds miR-451 and regulates AGO2 processing of pre-miR-451 through its N-terminal domains. CSDE1 further interacts with PARN and promotes the trimming of intermediate miR-451 to the mature length. Together, our results demonstrate that CSDE1 promotes biogenesis of miR-451 in erythroid progenitors.

Machine learning approaches classify clinical malaria outcomes based on haematological parameters

BACKGROUND

Malaria is still a major global health burden, with more than 3.2 billion people in 91 countries remaining at risk of the disease. Accurately distinguishing malaria from other diseases, especially uncomplicated malaria (UM) from non-malarial infections (nMI), remains a challenge. Furthermore, the success of rapid diagnostic tests (RDTs) is threatened by Pfhrp2/3 deletions and decreased sensitivity at low parasitaemia. Analysis of haematological indices can be used to support the identification of possible malaria cases for further diagnosis, especially in travellers returning from endemic areas. As a new application for precision medicine, we aimed to evaluate machine learning (ML) approaches that can accurately classify nMI, UM, and severe malaria (SM) using haematological parameters.

METHODS

We obtained haematological data from 2,207 participants collected in Ghana: nMI (n = 978), SM (n = 526), and UM (n = 703). Six different ML approaches were tested, to select the best approach. An artificial neural network (ANN) with three hidden layers was used for multi-classification of UM, SM, and uMI. Binary classifiers were developed to further identify the parameters that can distinguish UM or SM from nMI. Local interpretable model-agnostic explanations (LIME) were used to explain the binary classifiers.

RESULTS

The multi-classification model had greater than 85% training and testing accuracy to distinguish clinical malaria from nMI. To distinguish UM from nMI, our approach identified platelet counts, red blood cell (RBC) counts, lymphocyte counts, and percentages as the top classifiers of UM with 0.801 test accuracy (AUC = 0.866 and F1 score = 0.747). To distinguish SM from nMI, the classifier had a test accuracy of 0.96 (AUC = 0.983 and F1 score = 0.944) with mean platelet volume and mean cell volume being the unique classifiers of SM. Random forest was used to confirm the classifications, and it showed that platelet and RBC counts were the major classifiers of UM, regardless of possible confounders such as patient age and sampling location.

CONCLUSION

The study provides proof of concept methods that classify UM and SM from nMI, showing that the ML approach is a feasible tool for clinical decision support. In the future, ML approaches could be incorporated into clinical decision-support algorithms for the diagnosis of acute febrile illness and monitoring response to acute SM treatment particularly in endemic settings.

Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets

Recent technological advances for the acquisition of multi-omics data have allowed an unprecedented understanding of the complex intricacies of biological systems. In parallel, a myriad of computational analysis techniques and bioinformatics tools have been developed, with many efforts directed towards the creation and interpretation of networks from this data. In this review, we begin by examining key network concepts and terminology. Then, computational tools that allow for their construction and analysis from high-throughput omics datasets are presented. We focus on the study of functional relationships such as co-expression, protein-protein interactions, and regulatory interactions that are particularly amenable to modeling using the framework of networks. We envisage that many potential users of these analytical strategies may not be completely literate in programming languages and code adaptation, and for this reason, emphasis is given to tools' user-friendliness, including plugins for the widely adopted Cytoscape software, an open-source, cross-platform tool for network analysis, visualization, and data integration.

Characterization of the complete mitogenome of Anopheles aquasalis, and phylogenetic divergences among Anopheles from diverse geographic zones

Whole mitogenome sequences (mtDNA) have been exploited for insect ecology studies, using them as molecular markers to reconstruct phylogenies, or to infer phylogeographic relationships and gene flow. Recent Anopheles phylogenomic studies have provided information regarding the time of deep lineage divergences within the genus. Here we report the complete 15,393 bp mtDNA sequences of Anopheles aquasalis, a Neotropical human malaria vector. When comparing its structure and base composition with other relevant and available anopheline mitogenomes, high similarity and conserved genomic features were observed. Furthermore, 22 mtDNA sequences comprising anopheline and Dipteran sibling species were analyzed to reconstruct phylogenies and estimate dates of divergence between taxa. Phylogenetic analysis using complete mtDNA sequences suggests that A. aquasalis diverged from the Anopheles albitarsis complex ~28 million years ago (MYA), and ~38 MYA from Anopheles darlingi. Bayesian analysis suggests that the most recent ancestor of Nyssorhynchus and Anopheles + Cellia was extant ~83 MYA, corroborating current estimates of ~79–100 MYA. Additional sampling and publication of African, Asian, and North American anopheline mitogenomes would improve the resolution of the Anopheles phylogeny and clarify early continental dispersal routes.

Lutzomyia longipalpis TGF-β Has a Role in Leishmania infantum chagasi Survival in the Vector

Despite the increasing number of studies concerning insect immunity, Lutzomyia longipalpis immune responses in the presence of Leishmania infantum chagasi infection has not been widely investigated. The few available studies analyzed the role of the Toll and IMD pathways involved in response against Leishmania and microbial infections. Nevertheless, effector molecules responsible for controlling sand fly infections have not been identified. In the present study we investigated the role a signal transduction pathway, the Transforming Growth Factor-beta (TGF-β) pathway, on the interrelation between L. longipalpis and L. i. chagasi. We identified an L. longipalpis homolog belonging to the multifunctional cytokine TGF-β gene family (LlTGF-β), which is closely related to the activin/inhibin subfamily and potentially involved in responses to infections. We investigated this gene expression through the insect development and in adult flies infected with L. i. chagasi. Our results showed that LlTGF-β was expressed in all L. longipalpis developmental stages and was upregulated at the third day post L. i. chagasi infection, when protein levels were also higher as compared to uninfected insects. At this point blood digestion is finished and parasites are in close contact with the insect gut. In addition, we investigated the role of LlTGF-β on L. longipalpis infection by L. i. chagasi using either gene silencing by RNAi or pathway inactivation by addition of the TGF-β receptor inhibitor SB431542. The blockage of the LlTGF-β pathway increased significantly antimicrobial peptides expression and nitric oxide levels in the insect gut, as expected. Both methods led to a decreased L. i. chagasi infection. Our results show that inactivation of the L. longipalpis TGF-β signal transduction pathway reduce L. i. chagasi survival, therefore suggesting that under natural conditions the parasite benefits from the insect LlTGF-β pathway, as already seen in Plamodium infection of mosquitoes.

Redox state affects fecundity and insecticide susceptibility in Anopheles gambiae

Redox reactions play a central role in the metabolism of an organism. It is vital to maintain redox homeostasis in response to the fluctuation of redox shift in various biological contexts. NADPH-dependent reducing capacity is one of the key factors contributing to the redox homeostasis. To understand the redox capacity and its impact on mosquito fecundity and susceptibility to insecticides in Anopheles gambiae, we examined the dynamics of elevated oxidative state via induction by paraquat (PQ) and the inhibition of NADPH regeneration by 6-aminonicotinamide (6AN). In naïve conditions, inherent oxidative capacity varies between individuals, as measured by GSSG/GSH ratio. The high GSSG/GSH ratio was negatively correlated with fecundity. Both PQ and 6AN feeding increased GSSG/GSH ratio and elevated protein carbonylation, a marker of oxidative damage. Both pro-oxidants lowered egg production. Co-feeding the pro-oxidants with antioxidant lycopene attenuated the adverse effects on fecundity, implying that oxidative stress was the cause of this phenotype. Pre-feeding with 6AN increased insecticide susceptibility in DDT resistant mosquitoes. These results indicate that oxidative state is delicate in mosquitoes, manipulation of NADPH pool may adversely affect fecundity and insecticide detoxification capacity. This knowledge can be exploited to develop novel vector control strategies targeting fecundity and insecticide resistance.

Systems Biology-Based Investigation of Host-Plasmodium Interactions

Malaria is a serious, complex disease caused by parasites of the genus Plasmodium. Plasmodium parasites affect multiple tissues as they evade immune responses, replicate, sexually reproduce, and transmit between vertebrate and invertebrate hosts. The explosion of omics technologies has enabled large-scale collection of Plasmodium infection data, revealing systems-scale patterns, mechanisms of pathogenesis, and the ways that host and pathogen affect each other. Here, we provide an overview of recent efforts using systems biology approaches to study host-Plasmodium interactions and the biological themes that have emerged from these efforts. We discuss some of the challenges in using systems biology for this goal, key research efforts needed to address those issues, and promising future malaria applications of systems biology.

miRNA⁻mRNA Conflux Regulating Immunity and Oxidative Stress Pathways in the Midgut of Blood-Fed Anopheles stephensi

Blood feeding in Anopheles stephensi initiates a cascade of events that modulate several physiological functions in the mosquito. The midgut epithelium activates several of its molecules, most important among these being microRNAs, which regulate some of the physiological changes by targeting diverse mRNAs. The present study was conducted to identify and evaluate interactions between targets of eight miRNAs that are regulated on blood feeding. Identified from our previous study, we show these eight miRNAs exhibited distinct tissue specific expression. Targets of these miRNAs were predicted using computational approaches involving bioinformatics, co-expression analysis of the transcriptome and miRNome of blood-fed An. stephensi midgut. Using degradome sequencing, we identified some cleaved mRNAs of these microRNAs and, by using antagomiR knockdown technology to repress the miRNAs, the targets were validated in an An. stephensi cell line and in An. stephensi mosquitoes. In-depth analysis of predicted and identified targets revealed that the regulated miRNAs modulate well-characterized molecules that are involved in combating oxidative stress and immunity pathways through a dynamic miRNA:mRNA network. Our study is the first to identify miRNA:mRNA interactomes that play important role in maintaining redox homeostasis during blood feeding in the midgut of An. stephensi.

The cell biology of malaria infection of mosquito: advances and opportunities

Recent reviews (Feachem et al.; Alonso et al.) have concluded that in order to have a sustainable impact on the global burden of malaria, it is essential that we knowingly reduce the global incidence of infected persons. To achieve this we must reduce the basic reproductive rate of the parasites to < 1 in diverse epidemiological settings. This can be achieved by impacting combinations of the following parameters: the number of mosquitoes relative to the number of persons, the mosquito/human biting rate, the proportion of mosquitoes carrying infectious sporozoites, the daily survival rate of the infectious mosquito and the ability of malaria-infected persons to infect mosquito vectors.

This paper focuses on our understanding of parasite biology underpinning the last of these terms: infection of the mosquito. The article attempts to highlight central issues that require further study to assist in the discovery of useful transmission-blocking measures.