Australian mosquito assemblages vary between ground and sub-canopy habitats

The surveillance and control of mosquito-borne diseases is dependent upon understanding the bionomics and distribution of the vectors. Most studies of mosquito assemblages describe species abundance, richness and composition close to the ground defined often by only one sampling method. In this study, we assessed Australian mosquito species near the ground and in the sub-canopy using two traps baited with a variety of lures

The <i>Plasmodium falciparum</i> transcriptome in severe malaria reveals altered expression of genes involved in important processes including surface antigen–encoding <i>var</i> genes

<div><p>Within the human host, the malaria parasite <i>Plasmodium falciparum</i> is exposed to multiple selection pressures. The host environment changes dramatically in severe malaria, but the extent to which the parasite responds to—or is selected by—this environment remains unclear. From previous studies, the parasites that cause severe malaria appear to increase expression of a restricted but poorly defined subset of the PfEMP1 variant, surface antigens. PfEMP1s are major targets of protective immunity. Here, we used RNA sequencing (RNAseq) to analyse gene expression in 44 parasite isolates that caused severe and uncomplicated malaria in Papuan patients. The transcriptomes of 19 parasite isolates associated with severe malaria indicated that these parasites had decreased glycolysis without activation of compensatory pathways; altered chromatin structure and probably transcriptional regulation through decreased histone methylation; reduced surface expression of PfEMP1; and down-regulated expression of multiple chaperone proteins. Our RNAseq also identified novel associations between disease severity and PfEMP1 transcripts, domains, and smaller sequence segments and also confirmed all previously reported associations between expressed PfEMP1 sequences and severe disease. These findings will inform efforts to identify vaccine targets for severe malaria and also indicate how parasites adapt to—or are selected by—the host environment in severe malaria.</p></div

Analysis of RNAseq data via de novo assembly at the level of <i>var</i> gene segments.

<p>Expression levels of novel conserved segment clusters found to be up-regulated in severe disease. Samples and segment clusters have been grouped using complete linkage hierarchical clustering. The raw read counts that were transformed for this figure are available in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2004328#pbio.2004328.s026" target="_blank">S12 Data</a>.</p

Genome-wide analysis of RNAseq data using 3D7 annotation.

<p>(A) Estimated stage proportions for each sample. The mixture model was constrained to require that each sample be made up of a combination of ring, early trophozoite, late trophozoite, schizont, and gametocyte stages. Consequently, the columns in this barplot must add to 1 for each sample. A small bias towards the early trophozoite appears in the nonsevere malaria samples. Sample SFC21 also appears to be an outlier due to its higher proportion of late-stage and gametocyte parasites, a finding which was confirmed by microscopy. Plotted proportions are available in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2004328#pbio.2004328.s016" target="_blank">S2 Data</a>. (B) A PCA plot of read counts normalised for library size (read counts are available in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2004328#pbio.2004328.s016" target="_blank">S2 Data</a>). Samples are coloured by phenotype, red for severe and blue for nonsevere. Some separation by disease severity phenotype is evident; however, staging effects are apparent as is seen in the outlying position of sample SFC21, which has been identified as having more late-stage and gametocyte parasites. (C) A PCA plot of read counts normalised for library size, staging effects, and other unwanted batch effects using the novel mixture model along with 3 unwanted factors of variation estimated by RUV4 (normalised read counts are available in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2004328#pbio.2004328.s016" target="_blank">S2 Data</a>). Sample SFC21 has been appropriately dealt with and a better separation of the samples by disease phenotype can be observed. PC, principal component; PCA, principal component analysis; RUV, Remove Unwanted Variation.</p

Analysis of RNAseq data at the level of <i>var</i> gene transcripts: Separate assembly.

<p>(A) Expression levels of clusters identified by Corset found to be up-regulated in severe disease. Samples and clusters have been grouped using complete linkage hierarchical clustering. Raw read counts are available in S7 data. (B) Expression levels of clusters identified by Corset found to be up-regulated in severe disease. Values for all samples and the IQR and median are indicated and are available in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2004328#pbio.2004328.s021" target="_blank">S7 Data</a>. RPKM is reads per kb of transcript per million reads mapped to total <i>var</i> transcripts. IQR, interquartile range; RPKM, Reads Per Kilobase of transcript per Million mapped reads.</p

Summary of PfEMP1 transcripts, domains, and segments that were up-regulated in severe malaria.

<p>Sequences up-regulated in severe malaria are organised in columns for each analysis method separated by grey bars. Multiple domains found in the same single transcripts from the combined or separate assemblies are on a single row. Closely related sequences found in multiple analyses are colour coded for each of the major domain types and are grouped together across analyses by unbroken horizontal lines. Domains and/or segments that clustered together by expression profile in multiple individuals within a single analysis are also grouped by unbroken horizontal lines. Grey shaded sequences at the bottom of the diagram are unrelated to each other. For example, in the case of DC4, 2 transcripts from the combined assembly were amongst the closest BLAST hits to the DC4-like transcripts from the CORSET cluster of the separate assembly; 6 domains and 5 blocks identified by HMM in the separate assembly are found in DC4 domains; and clusters for 1 domain and 4 segments identified by hierarchical analysis contained DC4 domain sequences, including those from the DC4-like transcripts from the CORSET cluster of the separate assembly. ^aCombined assembly transcripts up-regulated in severe malaria were all adjusted <i>p <</i> 0.05 except for domains marked ^b (adjusted <i>p <</i> 0.153). Domains HMM and blocks HMM were identified using the HMM of [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2004328#pbio.2004328.ref014" target="_blank">14</a>]. Domains and segments %ID were identified using the novel hierarchical approach developed for this study. ^cNon–DC8-like DBLδ1 and non–DC4-like DBLβ3 that clustered by expression profile in the same patients with a highly conserved CIDRβ1. A dashed line separates DBLβ12 from DC8 because DC8 typically contain DBLβ12, but these DBLβ12 formed a phylogenetic cluster with non-DC8 DBLβ12. Dashed lines separate putative DC9 components because transcripts containing all components were not up-regulated in the combined assembly or the Corset analysis, but the clusters from which the up-regulated segments were identified contained multiple transcripts carrying the DC9 domains. ATS, acidic terminal sequence; CIDR, cysteine-rich interdomain region; DBL, Duffy binding-like; DC, domain cassette; HMM, Hidden Markov Model; PfEMP1, <i>Plasmodium falciparum</i> Erythrocyte Membrane Protein 1; TM, transmembrane.</p