Biology subjects

MacInnis, B. L.

Publications and source records attributed to MacInnis, B. L..

7 recordsLinked to original sources

bioRxiv2025

Phenotypic assessment and genetic validation of Plasmodium falciparum molecular markers associated with malaria chemoprevention in Senegal

Drug resistance in Plasmodium falciparum threatens to undermine malaria control and elimination efforts. Senegal is a malaria-endemic country that has implemented successive antimalarial and chemopreventive drug-based strategies for two decades. Sulfadoxine-pyrimethamine (SP) is used for chemoprevention in Senegal for intermittent preventive treatment in pregnancy (since 2004) and SP plus amodiaquine (AQ) is used for seasonal malaria chemoprevention (SMC, since 2013). Using whole genome sequence (WGS) data from malaria patient samples from health facilities across Senegal (2006 - 2022), we observed near fixation of Pfdhfr triple mutant and fluctuation in Pfdhps and Pfcrt mutation frequencies over time. It is unclear how these mutations influence drug resistance and fitness phenotypes in natural isolates; therefore, we evaluated natural parasite isolates with different Pfcrt, Pfmdr1, Pfdhps, and Pfdhfr haplotypes. Parasites were culture-adapted and phenotyped for antimalarial drug susceptibility and competitive growth (fitness). Pfcrt CVIET + A220S + Q271E + N326S + R371I and Pfcrt CVIET + A220S + Q271E + I356T + R371I mutants were significantly more resistant to monodesethyl-amodiaquine (md-AQ) compared to Pfcrt wild-type (WT) and Pfcrt CVIET + A220S + Q271E + R371I mutants. Pfdhfr triple mutants were significantly more pyrimethamine (PYR) resistant than Pfdhfr WT and revealed a range of phenotypes, but this was not explained by Pfgch1 copy-number. Pfdhps A437G parasites were significantly more sulfadoxine (SDX) resistant compared to Pfdhps wild-type and Pfdhps S436A mutants, suggesting that A437G is a key mutation for SDX resistance. Competitive growth assays between Pfdhfr-Pfdhps mutants revealed that Pfdhps mutations do not always result in fitness costs. Ongoing phenotypic assessment and genetic validation of these mutations in a Senegalese background is necessary to assess the impact of drug pressure, identify evolving genetic determinants of drug resistance, and provide molecular markers for ongoing surveillance to monitor and guide the use of drug-based interventions. AUTHOR SUMMARYDrug resistance is a major concern for both preventing and treating malaria, especially in Africa where most malaria cases and deaths occur. Since 2013, Senegal has been giving children under 10 years old a combination of sulfadoxine-pyrimethamine plus amodiaquine to prevent malaria during the transmission season, called Seasonal Malaria Chemoprevention (SMC), and plans to continue expanding its use. However, there is evidence from genetic surveillance that drug resistance mutations are present in Senegal which could render this antimalarial drug combination ineffective. Here we use natural P. falciparum isolates obtained from Senegalese patients that represent the extant parasite population to evaluate the consequences of evolving mutations on antimalarial drug resistance and fitness phenotypes. This study is one of the first to use natural parasites to assess the impact of naturally derived mutations on drug resistance and fitness phenotypes. Our results provide evidence that certain combinations of drug resistance mutations impact both parasite drug resistance and fitness, and therefore need to be closely monitored and can inform optimal antimalarial combinations for the prevention or treatment of malaria. This work informs the ongoing evolution of resistance and fitness phenotypes in malaria endemic settings that are introducing new multi first line therapies (MFTs) and SMC interventions that have been used for decades in Senegal. Our approach creates a framework for using genetic surveillance data to form a hypothesis, which can then be phenotypically tested by measuring the resistance and fitness levels of genetically diverse natural parasite isolates.

molecular biology↗

bioRxiv2025

Delphy: scalable, near-real-time Bayesian phylogenetics for outbreaks

Pathogen genomic analysis is central to tracking, understanding, and containing outbreaks, but complexity and high costs of state-of-the-art (SOTA) phylogenetic tools limit global access and impact. We introduce Delphy, an exact reformulation of Bayesian phylogenetics designed to transform its speed, scalability and accessibility while retaining SOTA accuracy. Delphys central data structure, an Explicit Mutation Annotated Tree, exploits the high sequence similarity in large-scale epidemic datasets for efficient tree exploration and convergence. By reproducing key analyses from recent major epidemics (Ebola, Zika, SARS-CoV-2, mpox, and H5N1), we demonstrate SOTA accuracy with up to 1,000x speedups. Assessing Delphys scalability, we show that a simulated dataset of 100,000 sequences can be analyzed in under a day-the largest such computation to date. We distribute Delphy as a client-side web application, enabling users worldwide to turn raw data into interactive results within minutes, without the data ever leaving the users machine. Delphy automatically identifies key viral lineages and mutations, as well as their emergence and prevalence through time, all with quantified uncertainties derived from a solid theoretical foundation. Delphy shows the power of Bayesian phylogenetics as a fast, accessible frontline tool for tackling future outbreaks.

genomics↗

bioRxiv2021

DNA spike-ins enable confident interpretation of SARS-CoV-2 genomic data from amplicon-based sequencing

The rapid global spread and continued evolution of SARS-CoV-2 has highlighted an unprecedented need for viral genomic surveillance and clinical viral sequencing. Amplicon-based sequencing methods provide a sensitive, low-cost and rapid approach but suffer a high potential for contamination, which can undermine lab processes and results. This challenge will only increase with expanding global production of sequences by diverse research groups for epidemiological and clinical interpretation. We present an approach which uses synthetic DNA spike-ins (SDSIs) to track samples and detect inter-sample contamination through a sequencing workflow. Applying this approach to the ARTIC Consortiums amplicon design, we define a series of best practices for Illumina-based sequencing and provide a detailed characterization of approaches to increase sensitivity for low-viral load samples incorporating the SDSIs. We demonstrate the utility and efficiency of the SDSI method amidst a real-time investigation of a suspected hospital cluster of SARS-CoV-2 cases.

molecular biology↗

bioRxiv2020

Integrated sample inactivation, amplification, and Cas13-based detection of SARS-CoV-2

The COVID-19 pandemic has highlighted that new diagnostic technologies are essential for controlling disease transmission. Here, we develop SHINE (SHERLOCK and HUDSON Integration to Navigate Epidemics), a sensitive and specific integrated diagnostic tool that can detect SARS-CoV-2 RNA from unextracted samples. We combine the steps of SHERLOCK into a single-step reaction and optimize HUDSON to accelerate viral inactivation in nasopharyngeal swabs and saliva. SHINEs results can be visualized with an in-tube fluorescent readout -- reducing contamination risk as amplification reaction tubes remain sealed -- and interpreted by a companion smartphone application. We validate SHINE on 50 nasopharyngeal patient samples, demonstrating 90% sensitivity and 100% specificity compared to RT-PCR with a sample-to-answer time of 50 minutes. SHINE has the potential to be used outside of hospitals and clinical laboratories, greatly enhancing diagnostic capabilities.

bioengineering↗

bioRxiv2019

Real-time Metagenomic Analysis of Undiagnosed Fever Cases Unveils a Yellow Fever Outbreak in Edo State, Nigeria

We report here the use of metagenomic sequencing to identify and characterize yellow fever virus (YFV) in a cluster of undiagnosed febrile patients from Edo State, Nigeria. Yellow fever, an acute mosquito-borne viral haemorrhagic fever, re-emerged in Nigeria in 2017 after decades of relative control.1 Once a major public health concern in the region,2 the prolonged absence of yellow fever has left a gap in knowledge about circulating virus and lowered clinical suspicion for a disease whose spectrum overlaps with endemic infections (e.g., malaria and Lassa fever). In this context, metagenomic sequencing can be a powerful tool for identifying and tracking pathogens causing infectious disease.3\n\nPlasma samples from thirteen epidemiologically-linked patients with unexplained, often fatal, fever were sent from Irrua Specialist Teaching Hospital to the African Center of Excellence for Genomics of ...

genomics↗

bioRxiv2018

Amplicon deep sequencing of low-density Plasmodium falciparum infections: an evaluation of analysis approaches

BackgroundDeep sequencing of targeted genomic regions is becoming a common tool for understanding the dynamics and complexity of Plasmodium infections, but its lower limit of detection is currently unknown. Here, a new amplicon analysis tool, the Parallel Amplicon Sequencing Error Correction (PASEC) pipeline, is used to evaluate the performance of amplicon sequencing on low-density Plasmodium DNA samples. Illumina-based sequencing of two P. falciparum genomic regions (CSP and SERA2) was performed on two types of samples: in vitro DNA mixtures mimicking low-density infections (1-200 genomes/l) and extracted blood spots from a combination of symptomatic and asymptomatic individuals (44-653,080 parasites/l). Three additional analysis tools--DADA2, HaplotypR, and SeekDeep--were applied to both datasets and the precision and sensitivity of each tool were evaluated. ResultsAmplicon sequencing can contend with low-density samples, showing reasonable detection accuracy down to a concentration of 5 Plasmodium genomes/l. Due to increased stochasticity and background noise, however, all four tools showed reduced sensitivity and precision on samples with very low parasitemia (<5 copies/l) or low read count (<100 reads per amplicon). PASEC could distinguish major from minor haplotypes with an accuracy of 90% in samples with at least 30 Plasmodium genomes/l, but only 61% at low Plasmodium concentrations (<5 genomes/l) and 46% at very low read counts (<25 reads per amplicon). The four tools were additionally used on a panel of extracted parasite-positive blood spots from natural malaria infections. While all four identified concordant patterns of complexity of infection (COI) across four sub-Saharan African countries, the COI values obtained for individual samples differed in some cases. ConclusionsAmplicon deep sequencing can be used to determine the complexity and diversity of low-density Plasmodium infections. Despite differences in their approach, four state-of-the-art tools resolved known haplotype mixtures with similar sensitivity and precision. Researchers can therefore choose from multiple robust approaches for analyzing amplicon data, however, error filtration approaches should not be uniformly applied across samples of varying parasitemia. Samples with very low parasitemia and very low read count have higher false positive rates and call for read count thresholds that are higher than current recommendations.

microbiology↗

bioRxiv2018

Co-circulating mumps lineages at multiple geographic scales

Despite widespread vaccination, eleven thousand mumps cases were reported in the United States (US) in 2016-17, including hundreds in Massachusetts, primarily in college settings. We generated 203 whole genome mumps virus (MuV) sequences from Massachusetts and 15 other states to understand the dynamics of mumps spread locally and nationally, as well as to search for variants potentially related to vaccination. We observed multiple MuV lineages circulating within Massachusetts during 2016-17, evidence for multiple introductions of the virus to the state, and extensive geographic movement of MuV within the US on short time scales. We found no evidence that variants arising during this outbreak contributed to vaccine escape. Combining epidemiological and genomic data, we observed multiple co-circulating clades within individual universities as well as spillover into the local community. Detailed data from one well-sampled university allowed us to estimate an effective reproductive number within that university significantly greater than one. We also used publicly available small hydrophobic (SH) gene sequences to estimate migration between world regions and to place this outbreak in a global context, but demonstrate that these short sequences, historically used for MuV genotyping, are inadequate for tracing detailed transmission. Our findings suggest continuous, often undetected, circulation of mumps both locally and nationally, and highlight the value of combining genomic and epidemiological data to track viral disease transmission at high resolution.

genomics↗