Biology subjects

Lin, J. T.

Publications and source records attributed to Lin, J. T..

5 recordsLinked to original sources

bioRxiv2025

Towards an evolutionary baseline model of Plasmodium falciparum for population-genomic inference

Malaria has caused over 15.7 million deaths in the 21st century and was responsible for [~]600 thousand deaths globally in 2023 alone. Although many effective antimalarial drugs have been developed and widely adopted to reduce the occurrence and severity of the disease, recurrent resistance to the frontline treatment has been of major concern. Multiple drug resistance alleles at intermediate and high allele frequency have been identified in specific Asian and African populations of P. falciparum, the deadliest malaria parasite. With the improvement in throughput of sequencing technologies and global efforts such as the MalariaGEN project to build genomic surveillance, we now have access to tens of thousands of genomes of P. falciparum from across the world. With this data, it is becoming increasingly possible to employ powerful population genetics approaches to understand the selective pressures and demographic history of the parasite. While several empirically motivated outlier-based approaches have been employed to identify targets of drug resistance, there is a lack of a framework that jointly accounts for the multiple concurrent processes occurring in natural populations of P. falciparum. We argue that a baseline evolutionary model that accounts for simultaneously acting evolutionary processes is needed to understand patterns of genomic variation in P. falciparum populations. Here, we identify key components essential for building such a baseline model for the malaria-causing pathogen. The development of an appropriate null model will be important to test evolutionary hypotheses using genomic datasets, will provide a path forward to improve the accuracy of inference of evolutionary parameters, and will help identify new gene candidates involved in drug resistance.

evolutionary biology↗

bioRxiv2024

Population genomics of Plasmodium ovale species in sub-Saharan Africa

Plasmodium ovale curtisi (Poc) and Plasmodium ovale wallikeri (Pow) are relapsing malaria parasites endemic to Africa and Asia that were previously thought to represent a single species. Amid increasing detection of ovale malaria in sub-Saharan Africa, we performed a population genomic study of both species across the continent. We conducted whole-genome sequencing of 25 isolates from Central and East Africa and analyzed them alongside 20 previously published African genomes. Isolates were predominantly monoclonal (43/45), with their genetic similarity aligning with geography. Pow showed lower average nucleotide diversity (1.8x10-4) across the genome compared to Poc (3.0x10-4) (p < 0.0001). Signatures of selective sweeps involving the dihydrofolate reductase gene were found in both species, as were signs of balancing selection at the merozoite surface protein 1 gene. Differences in the nucleotide diversity of Poc and Pow may reflect unique demographic history, even as similar selective forces facilitate their resilience to malaria control interventions.

genomics↗

bioRxiv2023

Multi-omic Profiling Reveals Early Immunological Indicators for Identifying COVID-19 Progressors

The pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to a rapid response by the scientific community to further understand and combat its associated pathologic etiology. A focal point has been on the immune responses mounted during the acute and post-acute phases of infection, but the immediate post-diagnosis phase remains relatively understudied. We sought to better understand the immediate post-diagnosis phase by collecting blood from study participants soon after a positive test and identifying molecular associations with longitudinal disease outcomes. Multi-omic analyses identified differences in immune cell composition, cytokine levels, and cell subset-specific transcriptomic and epigenomic signatures between individuals on a more serious disease trajectory (Progressors) as compared to those on a milder course (Non-progressors). Higher levels of multiple cytokines were observed in Progressors, with IL-6 showing the largest difference. Blood monocyte cell subsets were also skewed, showing a comparative decrease in non-classical CD14-CD16+ and intermediate CD14+CD16+ monocytes. Additionally, in the lymphocyte compartment, CD8+ T effector memory cells displayed a gene expression signature consistent with stronger T cell activation in Progressors. Importantly, the identification of these cellular and molecular immune changes occurred at the early stages of COVID-19 disease. These observations could serve as the basis for the development of prognostic biomarkers of disease risk and interventional strategies to improve the management of severe COVID-19. One Sentence SummaryImmunological changes associated with COVID-19 progression can be detected during the early stages of infection.

immunology↗

bioRxiv2023

Real-time PCR detection of mixed Plasmodium ovale curtisi and wallikeri species infections in human and mosquito hosts

Plasmodium ovale curtisi (Poc) and Plasmodium ovale wallikeri (Pow) represent distinct non-recombining malaria species that are increasing in prevalence in sub-Saharan Africa. Though they circulate sympatrically, co-infection within human and mosquito hosts has rarely been described. Separate 18S rRNA real-time PCR assays that detect Poc and Pow were modified to allow species determination in parallel under identical cycling conditions. The lower limit of detection was 0.6 plasmid copies/L (95% CI 0.4-1.6) for Poc and 4.5 plasmid copies/L (95% CI 2.7-18) for Pow, or 0.1 and 0.8 parasites/L, respectively, assuming 6 copies of 18s rRNA per genome. However, the assays showed cross-reactivity at concentrations greater than 103 plasmid copies/L (roughly 200 parasites/L). Mock mixtures were used to establish criteria for classifying mixed Poc/Pow infections that prevented false-positive detection while maintaining sensitive detection of the minority ovale species down to 100 copies/L (<1 parasite/L). When the modified real-time PCR assays were applied to field-collected blood samples from Tanzania and Cameroon, species identification by real-time PCR was concordant with nested PCR, but additionally detected two mixed Poc/Pow infections where nested PCR detected a single Po species. When real-time PCR was applied to 14 oocyst-positive Anopheles midguts saved from mosquitoes fed on P. ovale-infected persons, mixed Poc/Pow infections were detected in 11 (79%). Based on these results, 8/9 P. ovale carriers transmitted both P. ovale species to mosquitoes, though both Po species could only be detected in the blood of two carriers. The described real-time PCR approach can be used to identify the natural occurrence of mixed Poc/Pow infections in human and mosquito hosts and reveals that such co-infections and co-transmission are likely more common than appreciated. AUTHOR SUMMARYPlasmodium ovale, one of five species of malaria known to infect humans, in fact represents two distinct species, P. ovale curtisi (Poc) and wallikeri (Pow), that can only be distinguished using molecular diagnostics. Though Poc and Pow circulate in the same regions in Africa and Asia, mixed infections, where both are found in the same human host, have rarely been described. In this study, we modified existing real-time PCR assays targeting 18S rRNA and developed an algorithm to detect mixed Poc/Pow infections. We then applied these assays to field-collected samples from Tanzania and Cameroon, including blood samples from P. ovale-infected persons and P. ovale-positive mosquito midguts saved from mosquito feeding assays. We detected both Poc and Pow in roughly 10% of human P. ovale blood-stage infections, and surprisingly, in a majority of blood-fed mosquitoes. This suggests that Poc and Pow co-infect the same hosts more frequently than previously realized.

microbiology↗

bioRxiv2020

A novel CRISPR-based malaria diagnostic capable of Plasmodium detection, speciation, and drug-resistance genotyping

CRISPR-based diagnostics are a new class of highly sensitive and specific assays with multiple applications in infectious disease diagnosis. SHERLOCK, or Specific High-Sensitivity Enzymatic Reporter UnLOCKing, is one such CRISPR-based diagnostic that combines recombinase polymerase pre-amplification, CRISPR-RNA base-pairing, and LwCas13a activity for nucleic acid detection. We developed SHERLOCK assays for malaria capable of detecting all Plasmodium species known to cause malaria in humans and species-specific detection of P. vivax and P. falciparum, the species responsible for the majority of malaria cases worldwide. We validated these assays against parasite genomic DNA and achieved analytical sensitivities ranging from 2.5-18.8 parasites per reaction. We further tested these assays using a diverse panel of 123 clinical samples from the Democratic Republic of the Congo, Uganda, and Thailand and pools of Anopheles mosquitoes from Thailand. When compared to real-time PCR, the P. falciparum assay achieved 94% sensitivity and 94% specificity in clinical samples. In addition, we developed a SHERLOCK assay capable of detecting the dihydropteroate synthetase (dhps) single nucleotide variant A581G associated with P. falciparum sulfadoxine-pyrimethamine resistance. Compared to amplicon-based deep sequencing, the dhps SHERLOCK assay achieved 73% sensitivity and 100% specificity when applied to a panel of 43 clinical samples, with false-negative calls only at lower parasite densities. These novel SHERLOCK assays have potential to spawn a new generation of molecular diagnostics for malaria and demonstrate the versatility of CRISPR-based diagnostic approaches. One-sentence summaryNovel malaria SHERLOCK assays enabled robust detection, speciation, and genotyping of Plasmodium spp. in diverse samples collected in Africa and Asia.

molecular biology↗