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Fulltext Analysis of viral diversity for vaccine target discovery

Khan AM, Hu Y, Miotto O, Thevasagayam NM, Sukumaran R, Abd Raman HS, et al.

BMC Med Genomics, 2017 12 21;10(Suppl 4):78.
PMID: 29322922 DOI: 10.1186/s12920-017-0301-2

BACKGROUND: Viral vaccine target discovery requires understanding the diversity of both the virus and the human immune system. The readily available and rapidly growing pool of viral sequence data in the public domain enable the identification and characterization of immune targets relevant to adaptive immunity. A systematic bioinformatics approach is necessary to facilitate the analysis of such large datasets for selection of potential candidate vaccine targets.
RESULTS: This work describes a computational methodology to achieve this analysis, with data of dengue, West Nile, hepatitis A, HIV-1, and influenza A viruses as examples. Our methodology has been implemented as an analytical pipeline that brings significant advancement to the field of reverse vaccinology, enabling systematic screening of known sequence data in nature for identification of vaccine targets. This includes key steps (i) comprehensive and extensive collection of sequence data of viral proteomes (the virome), (ii) data cleaning, (iii) large-scale sequence alignments, (iv) peptide entropy analysis, (v) intra- and inter-species variation analysis of conserved sequences, including human homology analysis, and (vi) functional and immunological relevance analysis.
CONCLUSION: These steps are combined into the pipeline ensuring that a more refined process, as compared to a simple evolutionary conservation analysis, will facilitate a better selection of vaccine targets and their prioritization for subsequent experimental validation.
DiMA: sequence diversity dynamics analyser for viruses

Tharanga S, Ünlü ES, Hu Y, Sjaugi MF, Çelik MA, Hekimoğlu H, et al.

Brief Bioinform, 2024 Nov 22;26(1).
PMID: 39592151 DOI: 10.1093/bib/bbae607

Sequence diversity is one of the major challenges in the design of diagnostic, prophylactic, and therapeutic interventions against viruses. DiMA is a novel tool that is big data-ready and designed to facilitate the dissection of sequence diversity dynamics for viruses. DiMA stands out from other diversity analysis tools by offering various unique features. DiMA provides a quantitative overview of sequence (DNA/RNA/protein) diversity by use of Shannon's entropy corrected for size bias, applied via a user-defined k-mer sliding window to an input alignment file, and each k-mer position is dissected to various diversity motifs. The motifs are defined based on the probability of distinct sequences at a given k-mer alignment position, whereby an index is the predominant sequence, while all the others are (total) variants to the index. The total variants are sub-classified into the major (most common) variant, minor variants (occurring more than once and of incidence lower than the major), and the unique (singleton) variants. DiMA allows user-defined, sequence metadata enrichment for analyses of the motifs. The application of DiMA was demonstrated for the alignment data of the relatively conserved Spike protein (2,106,985 sequences) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the relatively highly diverse pol gene (2637) of the human immunodeficiency virus-1 (HIV-1). The tool is publicly available as a web server (https://dima.bezmialem.edu.tr), as a Python library (via PyPi) and as a command line client (via GitHub).
Fulltext Genomic analysis of a pre-elimination Malaysian Plasmodium vivax population reveals selective pressures and changing transmission dynamics

Auburn S, Benavente ED, Miotto O, Pearson RD, Amato R, Grigg MJ, et al.

Nat Commun, 2018 Jul 03;9(1):2585.
PMID: 29968722 DOI: 10.1038/s41467-018-04965-4

The incidence of Plasmodium vivax infection has declined markedly in Malaysia over the past decade despite evidence of high-grade chloroquine resistance. Here we investigate the genetic changes in a P. vivax population approaching elimination in 51 isolates from Sabah, Malaysia and compare these with data from 104 isolates from Thailand and 104 isolates from Indonesia. Sabah displays extensive population structure, mirroring that previously seen with the emergence of artemisinin-resistant P. falciparum founder populations in Cambodia. Fifty-four percent of the Sabah isolates have identical genomes, consistent with a rapid clonal expansion. Across Sabah, there is a high prevalence of loci known to be associated with antimalarial drug resistance. Measures of differentiation between the three countries reveal several gene regions under putative selection in Sabah. Our findings highlight important factors pertinent to parasite resurgence and molecular cues that can be used to monitor low-endemic populations at the end stages of P. vivax elimination.
Fulltext Genomic Analysis of Plasmodium vivax in Southern Ethiopia Reveals Selective Pressures in Multiple Parasite Mechanisms

Auburn S, Getachew S, Pearson RD, Amato R, Miotto O, Trimarsanto H, et al.

J Infect Dis, 2019 Oct 22;220(11):1738-1749.
PMID: 30668735 DOI: 10.1093/infdis/jiz016

The Horn of Africa harbors the largest reservoir of Plasmodium vivax in the continent. Most of sub-Saharan Africa has remained relatively vivax-free due to a high prevalence of the human Duffy-negative trait, but the emergence of strains able to invade Duffy-negative reticulocytes poses a major public health threat. We undertook the first population genomic investigation of P. vivax from the region, comparing the genomes of 24 Ethiopian isolates against data from Southeast Asia to identify important local adaptions. The prevalence of the Duffy binding protein amplification in Ethiopia was 79%, potentially reflecting adaptation to Duffy negativity. There was also evidence of selection in a region upstream of the chloroquine resistance transporter, a putative chloroquine-resistance determinant. Strong signals of selection were observed in genes involved in immune evasion and regulation of gene expression, highlighting the need for a multifaceted intervention approach to combat P. vivax in the region.
Fulltext Genomic analysis of local variation and recent evolution in Plasmodium vivax

Pearson RD, Amato R, Auburn S, Miotto O, Almagro-Garcia J, Amaratunga C, et al.

Nat Genet, 2016 Aug;48(8):959-964.
PMID: 27348299 DOI: 10.1038/ng.3599

The widespread distribution and relapsing nature of Plasmodium vivax infection present major challenges for the elimination of malaria. To characterize the genetic diversity of this parasite in individual infections and across the population, we performed deep genome sequencing of >200 clinical samples collected across the Asia-Pacific region and analyzed data on >300,000 SNPs and nine regions of the genome with large copy number variations. Individual infections showed complex patterns of genetic structure, with variation not only in the number of dominant clones but also in their level of relatedness and inbreeding. At the population level, we observed strong signals of recent evolutionary selection both in known drug resistance genes and at new loci, and these varied markedly between geographical locations. These findings demonstrate a dynamic landscape of local evolutionary adaptation in the parasite population and provide a foundation for genomic surveillance to guide effective strategies for control and elimination of P. vivax.
Fulltext Challenges for achieving safe and effective radical cure of Plasmodium vivax: a round table discussion of the APMEN Vivax Working Group

Thriemer K, Ley B, Bobogare A, Dysoley L, Alam MS, Pasaribu AP, et al.

Malar J, 2017 04 05;16(1):141.
PMID: 28381261 DOI: 10.1186/s12936-017-1784-1

The delivery of safe and effective radical cure for Plasmodium vivax is one of the greatest challenges for achieving malaria elimination from the Asia-Pacific by 2030. During the annual meeting of the Asia Pacific Malaria Elimination Network Vivax Working Group in October 2016, a round table discussion was held to discuss the programmatic issues hindering the widespread use of primaquine (PQ) radical cure. Participants included 73 representatives from 16 partner countries and 33 institutional partners and other research institutes. In this meeting report, the key discussion points are presented and grouped into five themes: (i) current barriers for glucose-6-phosphate deficiency (G6PD) testing prior to PQ radical cure, (ii) necessary properties of G6PD tests for wide scale deployment, (iii) the promotion of G6PD testing, (iv) improving adherence to PQ regimens and (v) the challenges for future tafenoquine (TQ) roll out. Robust point of care (PoC) G6PD tests are needed, which are suitable and cost-effective for clinical settings with limited infrastructure. An affordable and competitive test price is needed, accompanied by sustainable funding for the product with appropriate training of healthcare staff, and robust quality control and assurance processes. In the absence of quantitative PoC G6PD tests, G6PD status can be gauged with qualitative diagnostics, however none of the available tests is currently sensitive enough to guide TQ treatment. TQ introduction will require overcoming additional challenges including the management of severely and intermediately G6PD deficient individuals. Robust strategies are needed to ensure that effective treatment practices can be deployed widely, and these should ensure that the caveats are outweighed by the benefits of radical cure for both the patients and the community. Widespread access to quality controlled G6PD testing will be critical.
Fulltext An open dataset of Plasmodium vivax genome variation in 1,895 worldwide samples

MalariaGEN, Adam I, Alam MS, Alemu S, Amaratunga C, Amato R, et al.

Wellcome Open Res, 2022;7:136.
PMID: 35651694 DOI: 10.12688/wellcomeopenres.17795.1

This report describes the MalariaGEN Pv4 dataset, a new release of curated genome variation data on 1,895 samples of Plasmodium vivax collected at 88 worldwide locations between 2001 and 2017. It includes 1,370 new samples contributed by MalariaGEN and VivaxGEN partner studies in addition to previously published samples from these and other sources. We provide genotype calls at over 4.5 million variable positions including over 3 million single nucleotide polymorphisms (SNPs), as well as short indels and tandem duplications. This enlarged dataset highlights major compartments of parasite population structure, with clear differentiation between Africa, Latin America, Oceania, Western Asia and different parts of Southeast Asia. Each sample has been classified for drug resistance to sulfadoxine, pyrimethamine and mefloquine based on known markers at the dhfr, dhps and mdr1 loci. The prevalence of all of these resistance markers was much higher in Southeast Asia and Oceania than elsewhere. This open resource of analysis-ready genome variation data from the MalariaGEN and VivaxGEN networks is driven by our collective goal to advance research into the complex biology of P. vivax and to accelerate genomic surveillance for malaria control and elimination.
A molecular barcode and web-based data analysis tool to identify imported Plasmodium vivax malaria

Trimarsanto H, Amato R, Pearson RD, Sutanto E, Noviyanti R, Trianty L, et al.

Commun Biol, 2022 Dec 23;5(1):1411.
PMID: 36564617 DOI: 10.1038/s42003-022-04352-2

Traditionally, patient travel history has been used to distinguish imported from autochthonous malaria cases, but the dormant liver stages of Plasmodium vivax confound this approach. Molecular tools offer an alternative method to identify, and map imported cases. Using machine learning approaches incorporating hierarchical fixation index and decision tree analyses applied to 799 P. vivax genomes from 21 countries, we identified 33-SNP, 50-SNP and 55-SNP barcodes (GEO33, GEO50 and GEO55), with high capacity to predict the infection's country of origin. The Matthews correlation coefficient (MCC) for an existing, commonly applied 38-SNP barcode (BR38) exceeded 0.80 in 62% countries. The GEO panels outperformed BR38, with median MCCs > 0.80 in 90% countries at GEO33, and 95% at GEO50 and GEO55. An online, open-access, likelihood-based classifier framework was established to support data analysis (vivaxGEN-geo). The SNP selection and classifier methods can be readily amended for other use cases to support malaria control programs.