Flexible and cost-effective genomic surveillance of P. falciparum malaria with targeted nanopore sequencing.

Genomic surveillance of Plasmodium falciparum malaria can provide policy-relevant information about antimalarial drug resistance, diagnostic test failure, and the evolution of vaccine targets. Yet the large and low complexity genome of P. falciparum complicates the development of genomic methods, while resource constraints in malaria endemic regions can limit their deployment. Here, we demonstrate an approach for targeted nanopore sequencing of P. falciparum from dried blood spots (DBS) that enables cost-effective genomic surveillance of malaria in low-resource settings. We release software that facilitates flexible design of amplicon sequencing panels and use this software to design two target panels for P. falciparum. The panels generate 3-4 kbp reads for eight and sixteen targets respectively, covering key drug-resistance associated genes, diagnostic test antigens, polymorphic markers and the vaccine target csp. We validate our approach on mock and field samples, demonstrating robust sequencing coverage, accurate variant calls within coding sequences, the ability to explore P. falciparum within-sample diversity and to detect deletions underlying rapid diagnostic test failure.

Elucidating relationships between P.falciparum prevalence and measures of genetic diversity with a combined genetic-epidemiological model of malaria.

There is an abundance of malaria genetic data being collected from the field, yet using these data to understand the drivers of regional epidemiology remains a challenge. A key issue is the lack of models that relate parasite genetic diversity to epidemiological parameters. Classical models in population genetics characterize changes in genetic diversity in relation to demographic parameters, but fail to account for the unique features of the malaria life cycle. In contrast, epidemiological models, such as the Ross-Macdonald model, capture malaria transmission dynamics but do not consider genetics. Here, we have developed an integrated model encompassing both parasite evolution and regional epidemiology. We achieve this by combining the Ross-Macdonald model with an intra-host continuous-time Moran model, thus explicitly representing the evolution of individual parasite genomes in a traditional epidemiological framework. Implemented as a stochastic simulation, we use the model to explore relationships between measures of parasite genetic diversity and parasite prevalence, a widely-used metric of transmission intensity. First, we explore how varying parasite prevalence influences genetic diversity at equilibrium. We find that multiple genetic diversity statistics are correlated with prevalence, but the strength of the relationships depends on whether variation in prevalence is driven by host- or vector-related factors. Next, we assess the responsiveness of a variety of statistics to malaria control interventions, finding that those related to mixed infections respond quickly (∼months) whereas other statistics, such as nucleotide diversity, may take decades to respond. These findings provide insights into the opportunities and challenges associated with using genetic data to monitor malaria epidemiology.

The origins and relatedness structure of mixed infections vary with local prevalence of P. falciparum malaria.

Individual malaria infections can carry multiple strains of Plasmodium falciparum with varying levels of relatedness. Yet, how local epidemiology affects the properties of such mixed infections remains unclear. Here, we develop an enhanced method for strain deconvolution from genome sequencing data, which estimates the number of strains, their proportions, identity-by-descent (IBD) profiles and individual haplotypes. Applying it to the Pf3k data set, we find that the rate of mixed infection varies from 29% to 63% across countries and that 51% of mixed infections involve more than two strains. Furthermore, we estimate that 47% of symptomatic dual infections contain sibling strains likely to have been co-transmitted from a single mosquito, and find evidence of mixed infections propagated over successive infection cycles. Finally, leveraging data from the Malaria Atlas Project, we find that prevalence correlates within Africa, but not Asia, with both the rate of mixed infection and the level of IBD.

Leveraging DNA damage response signaling to identify yeast genes controlling genome stability.

Oncogenesis frequently is accompanied by rampant genome instability, which fuels genetic heterogeneity and resistance to targeted cancer therapy. We have developed an approach that allows precise, quantitative measurement of genome instability in high-throughput format in the Saccharomyces cerevisiae model system. Our approach takes advantage of the strongly DNA damage-inducible gene RNR3, in conjunction with the reporter synthetic genetic array methodology, to infer mutants exhibiting genome instability by assaying for increased Rnr3 abundance. We screen for genome instability across a set of ~1000 essential and ~4200 nonessential mutant yeast alleles in untreated conditions and in the presence of the DNA-damaging agent methylmethane sulfonate. Our results provide broad insights into the cellular processes and pathways required for genome maintenance. Through comparison with existing genome instability screens, we isolated 130 genes that had not previously been linked to genome maintenance, 51% of which have human homologs. Several of these homologs are associated with a genome instability phenotype in human cells or are causally mutated in cancer. A comprehensive understanding of the processes required to prevent genome instability will facilitate a better understanding of its sources in oncogenesis.

MECP2e1 isoform mutation affects the form and function of neurons derived from Rett syndrome patient iPS cells.

MECP2 mutations cause the X-linked neurodevelopmental disorder Rett Syndrome (RTT) by consistently altering the protein encoded by the MECP2e1 alternative transcript. While mutations that simultaneously affect both MECP2e1 and MECP2e2 isoforms have been widely studied, the consequence of MECP2e1 deficiency on human neurons remains unknown. Here we report the first isoform-specific patient induced pluripotent stem cell (iPSC) model of RTT. RTTe1 patient iPS cell-derived neurons retain an inactive X-chromosome and express only the mutant allele. Single-cell mRNA analysis demonstrated they have a molecular signature of cortical neurons. Mutant neurons exhibited a decrease in soma size, reduced dendritic complexity and decreased cell capacitance, consistent with impaired neuronal maturation. The soma size phenotype was rescued cell-autonomously by MECP2e1 transduction in a level-dependent manner but not by MECP2e2 gene transfer. Importantly, MECP2e1 mutant neurons showed a dysfunction in action potential generation, voltage-gated Na(+) currents, and miniature excitatory synaptic current frequency and amplitude. We conclude that MECP2e1 mutation affects soma size, information encoding properties and synaptic connectivity in human neurons that are defective in RTT.

Dissecting DNA damage response pathways by analysing protein localization and abundance changes during DNA replication stress.

Relocalization of proteins is a hallmark of the DNA damage response. We use high-throughput microscopic screening of the yeast GFP fusion collection to develop a systems-level view of protein reorganization following drug-induced DNA replication stress. Changes in protein localization and abundance reveal drug-specific patterns of functional enrichments. Classification of proteins by subcellular destination enables the identification of pathways that respond to replication stress. We analysed pairwise combinations of GFP fusions and gene deletion mutants to define and order two previously unknown DNA damage responses. In the first, Cmr1 forms subnuclear foci that are regulated by the histone deacetylase Hos2 and are distinct from the typical Rad52 repair foci. In a second example, we find that the checkpoint kinases Mec1/Tel1 and the translation regulator Asc1 regulate P-body formation. This method identifies response pathways that were not detected in genetic and protein interaction screens, and can be readily applied to any form of chemical or genetic stress to reveal cellular response pathways.

Synthesis and characterization of single-phase silicon-substituted alpha-tricalcium phosphate.

Silicon-substituted calcium phosphate (CaP) powders with a Ca/(P+Si) ratio of 1.50 have been prepared by a wet chemical method, with silicon contents up to 2.16 weight percent (wt%). Sintering for 2 h at 1250 degrees C yields single-phase silicon-substituted alpha tricalcium phosphate (Si-alpha-TCP) for compositions between 0.59 and 1.14 wt% silicon. The sintered powders have been characterized with X-ray fluorescence (XRF) spectrometry, X-ray diffraction (XRD), attenuated total reflection infrared spectroscopy (ATR-IR) and transmission electron microscopy (TEM). Compositions with less than 0.59 wt% silicon result in mixtures of Si-alpha-TCP, beta-TCP, and calcium hydroxyapatite (HA), while compositions with more than 1.14 wt% silicon result in mixtures of Si-alpha-TCP and HA. The lattice parameters of single-phase Si-alpha-TCP prepared with 0.87 wt% silicon are a=12.874(1)A, b = 27.372(2) A, c = 15.225(1) A, and beta = 126.38(1) degrees .