Bacterial Microbiota in Unfed Ticks (Dermacentor nuttalli) From Xinjiang Detected Through 16S rDNA Amplicon Sequencing and Culturomics

Background: Ticks are a major arthropod vector of zoonotic diseases affecting both humans and domestic animals worldwide. Thus, studying tick microbiota would aid in understanding of the potential threats posed by ticks. Methods: Approximately 8,000 unfed ticks, identified as Dermacentor nuttalli, were collected from the sylvosteppe in the western Tianshan mountains. To investigate their potential pathogens, we divided the ticks into 36 groups of 200–300 individuals each for examination with culturomics and 16S rDNA amplicon sequencing. Results: A total of 237 bacterial genera were identified with the two methods. Culturomics identified 46 bacterial species from 23 genera, predominantly Pseudomonas, Pantoea, and Bacillus, whereas 16S rDNA sequencing identified 461 OTUs from 233 genera, predominantly Pseudomonas (53.8%), Coxiella (17.2%), and Pantoea (6.4%). Coxiella, Rickettsia, and ten other genera were discovered only by sequencing, because optimal cultivating conditions were not used for their isolation, whereas Arthrobacter and three other genera were discovered only through culturomics. Conclusions: Several of the identified bacteria, such as line-related sepsis-causing Delftia acidovorans and the pneumonia agent Acinetobacter pittii, can cause human diseases. Thus, both sequencing and culturomics methods are crucial for comprehensive understanding of the microbiota of D. nuttalli.

Performance of RegCM4.5 in Simulating the Regional Climate of Western Tianshan Mountains in Xinjiang, China

The western Tianshan Mountains region in China has a complex topography where basins, mountains and glaciers co-exist. It is of great significance to study the sensitivity of meteorological factors in this region to different parameterization schemes of climate models. In this paper, the regional climate model RegCM4.5 is used to simulate the meteorological factor (mean temperature, maximum temperature, minimum temperature, precipitation and wind speed) occurring in the western Tianshan Mountains region from 2012 to 2016, so as to investigate the effects of different cumulus convective schemes (Grell, Tiedtke and Emanuel), including land cumulus convective schemes (LCCs) and ocean convective schemes (OCCs) on annual and seasonal simulations of meteorological factor by using the schemes of RUN1 (Grell for LCC and Tiedtke for OCC), RUN2 (Tiedtke for LCC and Emanuel for OCC), RUN3 (Grell for LCC and Emanuel for OCC) and ENS (the ensemble of RUN1, RUN2 and RUN3). The results show that the simulations of annual and seasonal meteorological factors are not significantly sensitive to the combination of LCCs and OCCs. In the annual simulations, RUN2 scheme has the best simulation performance for the maximum, average and minimum temperatures. However, other schemes of precipitation simulation outperform RUN2 scheme, and there is no difference among the four schemes for wind speed simulation. In the seasonal simulations, RUN2 scheme still performs well in the simulation of the average, maximum and minimum temperatures for four seasons, except for the simulation of the average temperature in spring and summer. For the simulation of the maximum temperature in summer, RUN2 scheme performs the same as ENS. For the simulation of other seasons, different meteorological factors have different performances in four seasons. Overall, the results show that different combinations of cumulus convection schemes can improve the simulation performance of meteorological factors in the western Tianshan Mountains of Xinjiang.