scholarly journals The transcriptome of the avian malaria parasite Plasmodium ashfordi displays host-specific gene expression

2016 ◽  
Author(s):  
Elin Videvall ◽  
Charlie K. Cornwallis ◽  
Dag Ahrén ◽  
Vaidas Palinauskas ◽  
Gediminas Valkiūnas ◽  
...  

AbstractMalaria parasites (Plasmodium spp.) include some of the world’s most widespread and virulent pathogens. Our knowledge of the molecular mechanisms these parasites use to invade and exploit hosts other than mice and primates is, however, extremely limited. It is therefore imperative to characterize transcriptome-wide gene expression from non-model malaria parasites and how this varies across host individuals. Here, we used high-throughput Illumina RNA-sequencing on blood from wild-caught Eurasian siskins experimentally infected with a clonal strain of the avian malaria parasite Plasmodium ashfordi (lineage GRW2). By using a multi-step approach to filter out host transcripts, we successfully assembled the blood-stage transcriptome of P. ashfordi. A total of 11 954 expressed transcripts were identified, and 7 860 were annotated with protein information. We quantified gene expression levels of all parasite transcripts across three hosts during two infection stages – peak and decreasing parasitemia. Interestingly, parasites from the same host displayed remarkably similar expression profiles during different infection stages, but showed large differences across hosts, indicating that P. ashfordi may adjust its gene expression to specific host individuals. We further show that the majority of transcripts are most similar to the human parasite Plasmodium falciparum, and a large number of red blood cell invasion genes were discovered, suggesting evolutionary conserved invasion strategies between mammalian and avian Plasmodium. The transcriptome of P. ashfordi and its host-specific gene expression advances our understanding of Plasmodium plasticity and is a valuable resource as it allows for further studies analysing gene evolution and comparisons of parasite gene expression.

2017 ◽  
Vol 26 (11) ◽  
pp. 2939-2958 ◽  
Author(s):  
Elin Videvall ◽  
Charlie K. Cornwallis ◽  
Dag Ahrén ◽  
Vaidas Palinauskas ◽  
Gediminas Valkiūnas ◽  
...  

2021 ◽  
Author(s):  
Giulia Zancolli ◽  
Maarten Reijnders ◽  
Robert Waterhouse ◽  
Marc Robinson-Rechavi

Animals have repeatedly evolved specialized organs and anatomical structures to produce and deliver a cocktail of potent bioactive molecules to subdue prey or predators: venom. This makes it one of the most widespread convergent functions in the animal kingdom. Whether animals have adopted the same genetic toolkit to evolved venom systems is a fascinating question that still eludes us. Here, we performed the first comparative analysis of venom gland transcriptomes from 20 venomous species spanning the main Metazoan lineages, to test whether different animals have independently adopted similar molecular mechanisms to perform the same function. We found a strong convergence in gene expression profiles, with venom glands being more similar to each other than to any other tissue from the same species, and their differences closely mirroring the species phylogeny. Although venom glands secrete some of the fastest evolving molecules (toxins), their gene expression does not evolve faster than evolutionarily older tissues. We found 15 venom gland specific gene modules enriched in endoplasmic reticulum stress and unfolded protein response pathways, indicating that animals have independently adopted stress response mechanisms to cope with mass production of toxins. This, in turns, activates regulatory networks for epithelial development, cell turnover and maintenance which seem composed of both convergent and lineage-specific factors, possibly reflecting the different developmental origins of venom glands. This study represents the first step towards an understanding of the molecular mechanisms underlying the repeated evolution of one of the most successful adaptive traits in the animal kingdom.


Heart Rhythm ◽  
2013 ◽  
Vol 10 (3) ◽  
pp. 383-391 ◽  
Author(s):  
Yung-Hsin Yeh ◽  
Chi-Tai Kuo ◽  
Yun-Shien Lee ◽  
Yuan-Min Lin ◽  
Stanley Nattel ◽  
...  

2017 ◽  
Vol 35 (4_suppl) ◽  
pp. 51-51
Author(s):  
Patrick James McLaren ◽  
Anthony P Barnes ◽  
Willy Z Terrell ◽  
Gina M. Vaccaro ◽  
Jack Wiedrick ◽  
...  

51 Background: Predicting prognosis in esophageal cancer remains an unrealized goal despite studies linking constellations of genes to therapeutic response. In this study, we analyzed specific predictor genes expressed in tumor specimens from our institutional repository. Our aim was to determine if specific gene expression profiles are associated with pathologic complete response (pCR) after neoadjuvant chemo-radiotherapy (CRT). Methods: We investigated eleven genes identified from prior studies (CCL28, SPARC, S100A2, SPRR3, SIRT2, NOV, PERP, PAPSS2, DCK, DKK3, ALDH1) that have significant association with esophageal cancer progression. Patients with esophageal adenocarcinoma treated with neoadjuvant CRT followed by esophagectomy at our institution between January 2011 and July 2015 were included. Quantitative real-time polymerase chain reaction was conducted on pre-treatment biopsy specimens to determine gene expression. Patients were classified into two groups: 1) pCR and, 2) no or poor response (NR) after CRT based on final pathology report. An omnibus test using Mahalanobis distance was applied to evaluate overall genetic expression differences between groups. Log-rank tests compared the differential expression of individual genes. Results: 29 patients (11 pCR and 18 NR) were analyzed. Overall, gene expression profiles were significantly different between pCR and NR patients (p < 0.01). In particular, CCL28 was over-expressed in pCR (Log-HR: 1.53, 95%CI: 0.46-2.59, p = 0.005), and DKK3-was under-expressed in pCR patients (Log-HR: -1.03 95%CI: -1.97, -0.10, p = 0.031). Conclusions: Esophageal adenocarcinoma patients with a pCR after neoadjuvant therapy have genetic profiles that are significantly different from typical NR profiles. In our population, the genes CCL28 and DKK3 are potential predictors of treatment response.


BMC Cancer ◽  
2009 ◽  
Vol 9 (1) ◽  
Author(s):  
Cinzia Lavarino ◽  
Nai-Kong V Cheung ◽  
Idoia Garcia ◽  
Gema Domenech ◽  
Carmen de Torres ◽  
...  

Author(s):  
Karlijn J. Doorn ◽  
John J. P. Brevé ◽  
Benjamin Drukarch ◽  
Hendrikus W. Boddeke ◽  
Inge Huitinga ◽  
...  

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