Using the Plasmodium mitochondrial genome for classifying mixed-species infections and inferring the geographical origin of P. falciparum parasites imported to the U.S

A new long-read mitochondrial-genome protocol (PacBio HiFi) for haemosporidian parasites: a tool for population and biodiversity studies

BACKGROUND

Studies on haemosporidian diversity, including origin of human malaria parasites, malaria's zoonotic dynamic, and regional biodiversity patterns, have used target gene approaches. However, current methods have a trade-off between scalability and data quality. Here, a long-read Next-Generation Sequencing protocol using PacBio HiFi is presented. The data processing is supported by a pipeline that uses machine-learning for analysing the reads.

METHODS

A set of primers was designed to target approximately 6 kb, almost the entire length of the haemosporidian mitochondrial genome. Amplicons from different samples were multiplexed in an SMRTbell® library preparation. A pipeline (HmtG-PacBio Pipeline) to process the reads is also provided; it integrates multiple sequence alignments, a machine-learning algorithm that uses modified variational autoencoders, and a clustering method to identify the mitochondrial haplotypes/species in a sample. Although 192 specimens could be studied simultaneously, a pilot experiment with 15 specimens is presented, including in silico experiments where multiple data combinations were tested.

RESULTS

The primers amplified various haemosporidian parasite genomes and yielded high-quality mt genome sequences. This new protocol allowed the detection and characterization of mixed infections and co-infections in the samples. The machine-learning approach converged into reproducible haplotypes with a low error rate, averaging 0.2% per read (minimum of 0.03% and maximum of 0.46%). The minimum recommended coverage per haplotype is 30X based on the detected error rates. The pipeline facilitates inspecting the data, including a local blast against a file of provided mitochondrial sequences that the researcher can customize.

CONCLUSIONS

This is not a diagnostic approach but a high-throughput method to study haemosporidian sequence assemblages and perform genotyping by targeting the mitochondrial genome. Accordingly, the methodology allowed for examining specimens with multiple infections and co-infections of different haemosporidian parasites. The pipeline enables data quality assessment and comparison of the haplotypes obtained to those from previous studies. Although a single locus approach, whole mitochondrial data provide high-quality information to characterize species pools of haemosporidian parasites.

Malaria Molecular Surveillance in the Peruvian Amazon with a Novel Highly Multiplexed Plasmodium falciparum AmpliSeq Assay

Molecular surveillance for malaria has great potential to support national malaria control programs (NMCPs). To bridge the gap between research and implementation, several applications (use cases) have been identified to align research, technology development, and public health efforts. For implementation at NMCPs, there is an urgent need for feasible and cost-effective tools. We designed a new highly multiplexed deep sequencing assay (Pf AmpliSeq), which is compatible with benchtop sequencers, that allows high-accuracy sequencing with higher coverage and lower cost than whole-genome sequencing (WGS), targeting genomic regions of interest. The novelty of the assay is its high number of targets multiplexed into one easy workflow, combining population genetic markers with 13 nearly full-length resistance genes, which is applicable for many different use cases. We provide the first proof of principle for hrp2 and hrp3 deletion detection using amplicon sequencing. Initial sequence data processing can be performed automatically, and subsequent variant analysis requires minimal bioinformatic skills using any tabulated data analysis program. The assay was validated using a retrospective sample collection (n = 254) from the Peruvian Amazon between 2003 and 2018. By combining phenotypic markers and a within-country 28-single-nucleotide-polymorphism (SNP) barcode, we were able to distinguish different lineages with multiple resistance haplotypes (in dhfr, dhps, crt and mdr1) and hrp2 and hrp3 deletions, which have been increasing in recent years. We found no evidence to suggest the emergence of artemisinin (ART) resistance in Peru. These findings indicate a parasite population that is under drug pressure but is susceptible to current antimalarials and demonstrate the added value of a highly multiplexed molecular tool to inform malaria strategies and surveillance systems. IMPORTANCE While the power of next-generation sequencing technologies to inform and guide malaria control programs has become broadly recognized, the integration of genomic data for operational incorporation into malaria surveillance remains a challenge in most countries where malaria is endemic. The main obstacles include limited infrastructure, limited access to high-throughput sequencing facilities, and the need for local capacity to run an in-country analysis of genomes at a large-enough scale to be informative for surveillance. In addition, there is a lack of standardized laboratory protocols and automated analysis pipelines to generate reproducible and timely results useful for relevant stakeholders. With our standardized laboratory and bioinformatic workflow, malaria genetic surveillance data can be readily generated by surveillance researchers and malaria control programs in countries of endemicity, increasing ownership and ensuring timely results for informed decision- and policy-making.

Application of machine and deep learning algorithms in optical microscopic detection of Plasmodium: A malaria diagnostic tool for the future

Machine and deep learning techniques are prevalent in the medical discipline due to their high level of accuracy in disease diagnosis. One such disease is malaria caused by Plasmodium falciparum and transmitted by the female anopheles mosquito. According to the World Health Organisation (WHO), millions of people are infected annually, leading to inevitable deaths in the infected population. Statistical records show that early detection of malaria parasites could prevent deaths and machine learning (ML) has proved helpful in the early detection of malarial parasites. Human error is identified to be a major cause of inaccurate diagnostics in the traditional microscopy malaria diagnosis method. Therefore, the method would be more reliable if human expert dependency is restricted or entirely removed, and thus, the motivation of this paper. This study presents a systematic review to understand the prevalent machine learning algorithms applied to a low-cost, portable optical microscope in the automation of blood film interpretation for malaria parasite detection. Peer-reviewed papers were downloaded from selected reputable databases eg. Elsevier, IEEExplore, Pubmed, Scopus, Web of Science, etc. The extant literature suggests that convolutional neural network (CNN) and its variants (deep learning) account for 41.9% of the microscopy malaria diagnosis using machine learning with a prediction accuracy of 99.23%. Thus, the findings suggest that early detection of the malaria parasite has improved through the application of CNN and other ML algorithms on microscopic malaria parasite detection.

The genetic and morphological diversity of Haemogregarina infecting turtles in Colombia: Are mitochondrial markers useful as barcodes for these parasites?

Adeleorinid parasites commonly infect turtles and tortoises in nature. Currently, our knowledge about such parasites is extremely poor. Their characterization is based on morphological and molecular approaches using the 18S rDNA molecular marker. However, there is a limitation with the 18S rDNA due to its slow rate of evolution. For that reason, the goals of this study were to 1) design primers for new molecular mitochondrial markers to improve the phylogenetic reconstructions of adeleorinid parasites and 2) to determine the morphological and genetic diversity of Haemogregarina infecting turtles and tortoises in Colombia. Turtles from 16 species representing six families were examined for the presence of haemoparasites. We analyzed 457 samples using PCR, and 203 of them were also analyzed by microscopy. Using a mitochondrial genome of Haemogregarina sequenced in this study, we designed primers to amplify fragments of the cytochrome oxidase I (coxI), cytochrome oxidase III (coxIII), and cytochrome b (cytb) mitochondrial markers in adeleorinid parasites. Lineages obtained from nuclear and mitochondrial molecular markers clustered according to the turtle lineages from which they were isolated. It is noteworthy that we found different evolutionary lineages within the same morphotype, which may indicate heteroplasmy and/or cryptic diversity in Haemogregarina. Due to this situation, we could not make a species delimitation, even when integrating the different lines of evidence we had in this study. However, the primers presented here are useful for diagnosis and, moreover, according to the available information, all three genes retain phylogenetic signals; thereby fragments amplified can be used in reconstructing evolutionary relationships. This effort contributes to the knowledge of the diversity of these parasites infecting continental turtles from Colombia.

A powerful qPCR-high resolution melting assay with taqman probe in plasmodium species differentiation

BACKGROUND

The use of highly sensitive molecular tools in malaria diagnosis is currently largely restricted to research and epidemiological settings, but will ultimately be essential during elimination and potentially eradication. Accurate diagnosis and differentiation down to species levels, including the two Plasmodium ovale species and zoonotic variants of the disease, will be important for the understanding of changing epidemiological patterns of the disease.

METHODS

A qPCR-high resolution melting (HRM) method was to detect and differentiate all human Plasmodium species with one forward and one reverse primer set. The HRM detection method was further refined using a hydrolysis probe to specifically discriminate Plasmodium falciparum.

RESULTS

Out of the 113 samples tested with the developed HRM-qPCR- P. falciparum probe assay, 96 (85.0 %) single infections, 12 (10.6 %) mixed infections, and 5 (4.4 %) were Plasmodium negative. The results were concordant with those of the nested PCR at 98.2 %. The assay limit of detection was varied from 21.47 to 46.43 copies /µl, equivalent to 1-2.11 parasites/µl. All P. falciparum infections were confirmed with the associated Taqman probe.

CONCLUSIONS

Although the dependence on qPCR currently limits its deployment in resource-limited environments, this assay is highly sensitive and specific, easy to perform and convenient for Plasmodium mono-infection and may provide a novel tool for rapid and accurate malaria diagnosis also in epidemiological studies.

Unique Mitochondrial Single Nucleotide Polymorphisms Demonstrate Resolution Potential to Discriminate Theileria parva Vaccine and Buffalo-Derived Strains

Distinct pathogenic and epidemiological features underlie different Theileria parva strains resulting in different clinical manifestations of East Coast Fever and Corridor Disease in susceptible cattle. Unclear delineation of these strains limits the control of these diseases in endemic areas. Hence, an accurate characterization of strains can improve the treatment and prevention approaches as well as investigate their origin. Here, we describe a set of single nucleotide polymorphisms (SNPs) based on 13 near-complete mitogenomes of T. parva strains originating from East and Southern Africa, including the live vaccine stock strains. We identified 11 SNPs that are non-preferentially distributed within the coding and non-coding regions, all of which are synonymous except for two within the cytochrome b gene of buffalo-derived strains. Our analysis ascertains haplotype-specific mutations that segregate the different vaccine and the buffalo-derived strains except T. parva-Muguga and Serengeti-transformed strains suggesting a shared lineage between the latter two vaccine strains. Phylogenetic analyses including the mitogenomes of other Theileria species: T. annulata, T. taurotragi, and T. lestoquardi, with the latter two sequenced in this study for the first time, were congruent with nuclear-encoded genes. Importantly, we describe seven T. parva haplotypes characterized by synonymous SNPs and parsimony-informative characters with the other three transforming species mitogenomes. We anticipate that tracking T. parva mitochondrial haplotypes from this study will provide insight into the parasite’s epidemiological dynamics and underpin current control efforts.