Discovery of DNA Viruses in Wild-Caught Mosquitoes Using Small RNA High throughput Sequencing

BACKGROUND: Mosquito-borne infectious diseases pose a severe threat to public health in many areas of the world. Current methods for pathogen detection and surveillance are usually dependent on prior knowledge of the etiologic agents involved. Hence, efficient approaches are required for screening wild mosquito populations to detect known and unknown pathogens. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we explored the use of Next Generation Sequencing to identify viral agents in wild-caught mosquitoes. We extracted total RNA from different mosquito species from South China. Small 18-30 bp length RNA molecules were purified, reverse-transcribed into cDNA and sequenced using Illumina GAIIx instrumentation. Bioinformatic analyses to identify putative viral agents were conducted and the results confirmed by PCR. We identified a non-enveloped single-stranded DNA densovirus in the wild-caught Culex pipiens molestus mosquitoes. The majority of the viral transcripts (.>80% of the region) were covered by the small viral RNAs, with a few peaks of very high coverage obtained. The +/- strand sequence ratio of the small RNAs was approximately 7∶1, indicating that the molecules were mainly derived from the viral RNA transcripts. The small viral RNAs overlapped, enabling contig assembly of the viral genome sequence. We identified some small RNAs in the reverse repeat regions of the viral 5'- and 3' -untranslated regions where no transcripts were expected. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate for the first time that high throughput sequencing of small RNA is feasible for identifying viral agents in wild-caught mosquitoes. Our results show that it is possible to detect DNA viruses by sequencing the small RNAs obtained from insects, although the underlying mechanism of small viral RNA biogenesis is unclear. Our data and those of other researchers show that high throughput small RNA sequencing can be used for pathogen surveillance in wild mosquito vectors

Electron Impact Excitation and Dielectronic Recombination of Highly Charged Tungsten Ions

Electron impact excitation (EIE) and dielectronic recombination (DR) of tungsten ions are basic atomic processes in nuclear fusion plasmas of the International Thermonuclear Experimental Reactor (ITER) tokamak. Detailed investigation of such processes is essential for modeling and diagnosing future fusion experiments performed on the ITER. In the present work, we studied total and partial electron-impact excitation (EIE) and DR cross-sections of highly charged tungsten ions by using the multiconfiguration Dirac–Fock method. The degrees of linear polarization of the subsequent X-ray emissions from unequally-populated magnetic sub-levels of these ions were estimated. It is found that the degrees of linear polarization of the same transition lines, but populated respectively by the EIE and DR processes, are very different, which makes diagnosis of the formation mechanism of X-ray emissions possible. In addition, with the help of the flexible atomic code on the basis of the relativistic configuration interaction method, DR rate coefficients of highly charged W37+ to W46+ ions are also studied, because of the importance in the ionization equilibrium of tungsten plasmas under running conditions of the ITER

A pan-coronavirus RT-PCR assay for rapid viral screening of animal, human, and environmental specimens

We examined a collection of 386 animal, 451 human, and 109 archived bioaerosol samples with a new pan-species coronavirus molecular assay. Thirty-eight (4.02%) of 946 specimens yielded evidence of human or animal coronaviruses. Our findings demonstrate the utility of employing the pan-CoV RT-PCR assay in detecting varied coronavirus among human, animal, and environmental specimens. This RT-PCR assay might be employed as a screening diagnostic for early detection of coronaviruses incursions or prepandemic coronavirus emergence in animal or human populations

An Efficient Strategy of Screening for Pathogens in Wild-Caught Ticks and Mosquitoes by Reusing Small RNA Deep Sequencing Data

<div><p>This paper explored our hypothesis that sRNA (18∼30 bp) deep sequencing technique can be used as an efficient strategy to identify microorganisms other than viruses, such as prokaryotic and eukaryotic pathogens. In the study, the clean reads derived from the sRNA deep sequencing data of wild-caught ticks and mosquitoes were compared against the NCBI nucleotide collection (non-redundant nt database) using Blastn. The blast results were then analyzed with in-house Python scripts. An empirical formula was proposed to identify the putative pathogens. Results showed that not only viruses but also prokaryotic and eukaryotic species of interest can be screened out and were subsequently confirmed with experiments. Specially, a novel <i>Rickettsia</i> spp. was indicated to exist in <i>Haemaphysalis longicornis</i> ticks collected in Beijing. Our study demonstrated the reuse of sRNA deep sequencing data would have the potential to trace the origin of pathogens or discover novel agents of emerging/re-emerging infectious diseases.</p></div

Areas from which ticks and mosquitoes in the study were collected.

<p>Areas from which ticks and mosquitoes in the study were collected.</p

Phylogenetic analysis of confirmed pathogens of interests.

<p>Sequences were aligned using the MEGA5 (Version5.1) software package. NJ (Neighbor-joining method) phylogenetic tree construction and bootstrap analysis(1000 replicates) were carried out. Bars indicate the percentage of sequence divergence. All positions containing alignment gaps and missing data were deleted (Complete-deletion). <b>A.</b> Phylogenetic tree of bacteria belonging to <i>Rickettsia</i>, inferred from comparison of the partial 16s rDNA gene sequences. <b>B.</b> Phylogenetic tree of bacteria belonging to <i>Coxiella</i>, inferred from comparison of the partial 16s rDNA gene sequences. <b>C.</b> Phylogenetic tree of bacteria belonging to <i>Aspergillus</i>, inferred from comparison of the partial 18s rDNA gene sequences. <b>D.</b> Phylogenetic tree of bacteria belonging to <i>Nidovirales</i>, inferred from comparison of the partial RdRp gene sequences.</p

Experimental confirmation of predicted pathogens of interest predicted by bioinformatics.

<p>A), The second run of nested PCR amplification of the sample XCP (<i>Heamaphysalis longicornis</i> ticks collected from Beijing) to confirm the predicted <i>Coxiella</i> spp.. B), The second run of nested PCR amplification of the sample XCP (<i>Heamaphysalis longicornis</i> ticks collected from Beijing) to confirm the predicted <i>Rickettsia</i> spp.. C), The second run of nested PCR amplification of the sample CYP (<i>Heamaphysalis longicornis</i> ticks collected from Shanghai) to confirm the predicted <i>Coxiella</i> spp.. D), The PCR amplification of the sample XCP (<i>Heamaphysalis longicornis</i> ticks collected from Beijing) to confirm the predicted <i>Aspergillus</i> spp. E), The PCR amplification of the sample CYP (<i>Heamaphysalis longicornis</i> ticks collected from Shanghai) to confirm the predicted <i>Aspergillus</i> spp.. F), The PCR amplification of the sample <i>A. sinensis</i> collected from Yunnan to confirm the predicted ESV. G), The PCR amplification of the sample <i>A. sinensis</i> collected from Yunnan to confirm the predicted NDV. M, DNA marker; S, Sample; N,negtive control.</p

Coverage of respective microbe genomes by mapped sRNA reads.

<p>Coverage of respective microbe genomes by mapped sRNA reads.</p

BLAST Results of confirmation experiment.

<p>BLAST Results of confirmation experiment.</p