Genetic diversity and evolutionary dynamics of Ebola virus in Sierra Leone.

A novel Ebola virus (EBOV) first identified in March 2014 has infected more than 25,000 people in West Africa, resulting in more than 10,000 deaths. Preliminary analyses of genome sequences of 81 EBOV collected from March to June 2014 from Guinea and Sierra Leone suggest that the 2014 EBOV originated from an independent transmission event from its natural reservoir followed by sustained human-to-human infections. It has been reported that the EBOV genome variation might have an effect on the efficacy of sequence-based virus detection and candidate therapeutics. However, only limited viral information has been available since July 2014, when the outbreak entered a rapid growth phase. Here we describe 175 full-length EBOV genome sequences from five severely stricken districts in Sierra Leone from 28 September to 11 November 2014. We found that the 2014 EBOV has become more phylogenetically and genetically diverse from July to November 2014, characterized by the emergence of multiple novel lineages. The substitution rate for the 2014 EBOV was estimated to be 1.23 × 10(-3) substitutions per site per year (95% highest posterior density interval, 1.04 × 10(-3) to 1.41 × 10(-3) substitutions per site per year), approximating to that observed between previous EBOV outbreaks. The sharp increase in genetic diversity of the 2014 EBOV warrants extensive EBOV surveillance in Sierra Leone, Guinea and Liberia to better understand the viral evolution and transmission dynamics of the ongoing outbreak. These data will facilitate the international efforts to develop vaccines and therapeutics.

Aerosol and Surface Distribution of Severe Acute Respiratory Syndrome Coronavirus 2 in Hospital Wards, Wuhan, China, 2020.

To determine distribution of severe acute respiratory syndrome coronavirus 2 in hospital wards in Wuhan, China, we tested air and surface samples. Contamination was greater in intensive care units than general wards. Virus was widely distributed on floors, computer mice, trash cans, and sickbed handrails and was detected in air ≈4 m from patients.

[Spatial-temporal Variation and Spatial Differentiation Geographic Detection of PM2.5 Concentration in the Shandong Province Based on Spatial Scale Effect].

PM2.5 remote sensing data was applied in this study, and Theil-Sen Median trend analysis and the Mann-Kendall significance test were utilized to analyze the temporal and spatial variation in PM2.5 in the Shandong Province from 2000 to 2021. The influencing power of the influencing factors on the spatial differentiation of PM2.5 concentration in the Shandong Province was detected at the provincial-city-county levels based on Geo-detector data. The results showed that:① on the temporal scale, the mean ρ(PM2.5)in the Shandong Province ranged from 38.15 to 88.63 µg·m-3 from 2000 to 2021, which was slightly higher than the secondary limit of inhalable particulate matter (35 µg·m-3) in the Ambient Air Quality Standards. On the interannual scale, 2013 was the peak year for the variation in ρ(PM2.5) with a value of 83.36 µg·m-3, according to which the trend of PM2.5 concentrations in the Shandong Province was divided into two phases:a continuous increase and a rapid decrease. On the seasonal scale, PM2.5 concentration presented the distribution characteristics of "low in summer and high in winter and moderate in spring and autumn" and the U-shaped change rule of first decreasing and then increasing. ② On the spatial scale, the PM2.5 concentration in the Shandong Province presented a spatial distribution pattern of "high in the west and low in the east." The areas with high PM2.5 concentration were distributed in the western area of the Shandong Province, whereas the areas with low PM2.5 concentration were distributed in the eastern peninsula region. The spatial variation in the changing trend of PM2.5 concentration showed significant spatial heterogeneity, and the extremely significant decrease was mainly distributed in the eastern peninsula region. ③ The results of factor detection showed that climate factor was an important factor affecting the spatial differentiation of PM2.5 concentration in the Shandong Province. Mean temperature had the highest influence on the spatial differentiation of PM2.5 concentration in the Shandong Province, with a q value of 0.512. Provincial-city-county multi-scale detection results showed that the influencing factors affecting the spatial differentiation of PM2.5 concentration and their influencing power differed at different spatial scales. At the provincial scale, mean temperature, sunshine duration, and slope were the main factors affecting the spatial differentiation of PM2.5 concentration. At the city level, precipitation, elevation, and relative humidity were the main factors affecting the spatial differentiation of PM2.5. At the county level, precipitation, mean temperature, and sunshine duration were the main factors affecting the spatial variation in PM2.5 concentration.

[Spatio-temporal Variation in Net Primary Productivity of Different Vegetation Types and Its Influencing Factors Exploration in Southwest China].

Studying the spatiotemporal variation in vegetation net primary productivity (NPP) and exploring its influencing factors are of considerable practical significance for understanding the spatiotemporal variation in vegetation and for guiding ecological restoration and management projects based on local conditions. Based on MODIS NPP data, combined with in situ meteorological data, land use data, and vegetation type data, this study explores the spatiotemporal variation in different types of vegetation NPP in southwest China via the Mann-Kendall significance test and Theil-Sen Median slope estimator. It reveals the influencing factors of spatial differentiation of different types of vegetation NPP and the interaction between influencing factors in combination with stability analysis and Geo Detectors. The results revealed that on the temporal scale, from 2000 to 2021, vegetation NPP, NPPPre (vegetation NPP exclusively under the influence of climate change), and NPPRes (vegetation NPP exclusively under the influence of human activities) in southwest China showed a fluctuating upward trend. Among different vegetation types, NPP, NPPPre, and NPPRes exhibited an upward trend, except for a minor decline in NPPRes of tree vegetation at a rate of -0.183 g·(m2·a)-1. Among them, NPP, NPPPre, and NPPRes of economic vegetation showed the most significant upward rates, 5.96, 3.09, and 2.94 g·(m2·a)-1, respectively. On the spatial scale, the tree vegetation NPP with the most significant downward trend was mainly distributed in Tibet and southern Yunnan, while the economic vegetation NPP with the highest upward trend was primarily distributed in eastern Sichuan Province. The stability of vegetation NPP in southwest China presented a spatial distribution pattern of "low in the south and high in the north," and the average value of the correlation coefficient increased in the ascending order of arbor vegetation (0.101), shrub vegetation (0.105), herb vegetation (0.110), and economic vegetation (0.114). The interaction between surface temperature and relative humidity was the main influencing factor for spatial differentiation of vegetation NPP, while the interaction between sunshine duration and warmth index had the most significant impact on vegetation in southwest China, with an increasing percentage of 30.91%. Different types of vegetation had different requirements for different climatic factors, but their requirements for surface temperature and warmth index were significantly consistent. When the surface temperature was 21.03-28.49℃, and the warmth index was 106.46-167.2, the NPP of different vegetation types peaked. Under natural succession, the impact of climate change on vegetation was inversely proportional to the stability of the vegetation community. The arbor vegetation community with high stability was less affected, while the herb vegetation community with low stability was highly affected by climate. In contrast, the stability of economic vegetation was directly proportional to the impact of climate due to the influence of human activities. This study establishes a theoretical foundation for evaluating the impact of regional climate on the growth of different vegetation types and can be crucial for formulating ecological restoration and management strategies in southwest China that are adapted to the local conditions.

[Quantitative Assessment of the Impact of Climate Change on the Growing Season of Vegetation Gross Primary Productivity in the Middle and Lower Reaches of the Yangtze River].

Quantitatively determining the direct, indirect, and comprehensive effects of climatic factors on the growing season of the vegetation GPP (GPPGS) in the middle and lower reaches of the Yangtze River at the regional and vegetation type scales can provide a scientific basis for the management and restoration of regional vegetation resources under the background of global climate change. Using MODIS GPP data, meteorological data, and vegetation type data, combined with Theil-Sen Median trend analysis and the Mann-Kendall significance test, the spatiotemporal characteristics of the GPPGS in the middle and lower reaches of the Yangtze River were investigated at different temporal and spatial scales. Path analysis was used to further reveal the direct, indirect, and comprehensive effects of climate factors on GPPGS variation in different vegetation types. The results showed that:① from 2000 to 2021, the vegetation GPPGS in the middle and lower reaches of the Yangtze River showed a fluctuating upward trend, with a rising rate (in terms of C, same below) of 2.70 g·(m2·a)-1 (P<0.01). The GPPGS of different vegetation types all showed a significant upward trend (P<0.01), with shrubs having the highest upward rate of 3.31 g·(m2·a)-1 and cultivated vegetation having the lowest upward rate of 2.54 g·(m2·a)-1. ② The proportion of the area with an upward trend in GPPGS in the middle and lower reaches of the Yangtze River was 88.11%. The proportion of the area with an upward trend in GPPGS was greater than 84% for all different vegetation types, with shrubs (49.76%) and cultivated vegetation (44.36%) having significantly higher proportions of the area with an upward trend than that in other vegetation types. ③ The path analysis results showed that precipitation and the maximum temperature had a significant positive direct effect on vegetation GPPGS (P<0.05), whereas solar radiation had a non-significant positive effect (P ≥ 0.05). The indirect effects of maximum temperature, precipitation, and solar radiation on vegetation GPPGS were all non-significantly negative (P ≥ 0.05). Under the combined effects of direct and indirect influences, precipitation and maximum temperature had a non-significant positive effect on vegetation GPPGS (P ≥ 0.05), whereas solar radiation had a non-significant negative effect on vegetation GPPGS (P ≥ 0.05). Among different vegetation types, precipitation was the main climate factor affecting the changes in GPPGS of cultivated vegetation, whereas the maximum temperature was the main climate factor affecting the changes in GPPGS of coniferous forests, broad-leaved forests, shrubs, and grasslands. ④ The changes in vegetation GPPGS in the middle and lower reaches of the Yangtze River were mainly influenced by the direct effects of maximum temperature, precipitation, and solar radiation, with the direct effect of precipitation dominating 56.72% of the changes in GPPGS. The research results can provide a reference for quantifying the carbon sequestration potential of vegetation in the middle and lower reaches of the Yangtze River and formulating ecological restoration governance policies tailored to local conditions under the background of global climate change.

[Spatio-temporal Variation and Multi-dimensional Detection of Driving Mechanism of PM2.5 Concentration in the Chengdu-Chongqing Urban Agglomeration from 2000 to 2021].

Studies on the spatio-temporal variation and driving mechanism of PM2.5 concentration in the Chengdu-Chongqing urban agglomeration are of great significance for regional atmospheric environment protection and national economic sustainable development. Based on PM2.5 remote sensing data, DEM data, in situ meteorological data, MODIS NDVI data, population density data, nighttime lighting data, road network data, and land use type data, a series of mathematical methods such as Theil-Sen Medium analysis and Mann-Kendall significance test, combined with the Geo-detector model were used to analyze the spatio-temporal variation and multi-dimensional detection of the driving mechanism of PM2.5 concentration in the Chengdu-Chongqing urban agglomeration. The results showed that the overall PM2.5 concentration showed a fluctuating downward trend in the Chengdu-Chongqing urban agglomeration from 2000 to 2021, and the PM2.5 pollution was the most prominent in winter. PM2.5 concentration exhibited obvious spatial heterogeneity with "high in the middle and low in the surrounding areas." The high-PM2.5 concentration areas were mainly concentrated in Zigong, Neijiang, Ziyang, and Guang'an, and the areas with a PM2.5 concentration decrease were mainly concentrated in the west of Chongqing. Influencing detection results showed that the spatial heterogeneity of PM2.5 concentration in the Chengdu-Chongqing urban agglomeration was influenced by the combined effects of climate factors, topographic factors, vegetation cover, and anthropogenic factors. Furthermore, elevation, slope, and road network density were regarded as the dominant factors influencing the spatial heterogeneity of PM2.5 concentration in the study area. Topographic factors and climate factors showed the highest and lowest contribution rate to the spatial heterogeneity of PM2.5 concentration, respectively. The contribution rate of topographic factors and anthropogenic factors had gradually increased, and the contribution rate of climate factors and vegetation cover had gradually decreased in the study area from 2000 to 2021. Interaction detection results showed that the spatial heterogeneity of PM2.5 concentration in the Chengdu-Chongqing urban agglomeration was mostly affected by the interaction effects of elevation and road network density, slope, precipitation, sunshine duration, and land use type. The interaction detection results exhibited obvious regional differences on the city level. For instance, the spatial heterogeneity of PM2.5 concentration in Chengdu, Deyang, and Leshan was mostly affected by the interaction between different influencing types, and the spatial heterogeneity of PM2.5 concentration in Dazhou, Meishan, Ya'an, Ziyang, Neijiang, and Zigong was mostly affected by the interaction within a single influencing type.

[Spatio-temporal Variation in Vegetation Cover and Its Driving Mechanism Exploration in Southwest China from 2000 to 2020].

Using the MOD13A3 NDVI time series from 2000 to 2020, climate date from 1999 to 2020, and land use type data in 2000 and 2020, the spatio-temporal variation in vegetation cover and the driving mechanisms of climate change and human activities to vegetation variation were analyzed based on Theil-Sen Median analysis, the Mann-Kendall significance test, the multi-collinearity test, residual analysis, and relative analysis. The results showed that the vegetation cover exhibited a fluctuating and increasing trend with a magnitude of 0.0016 a-1 in southwest China from 2000 to 2020. The increasing trend of vegetation cover was mostly significant in the Guangxi Hills and Yunnan-Guizhou Plateau and slightly significant in the Tibet Plateau. The vegetation cover had increased in the context of climate change and human activities, with an increasing rate of 0.0010 a-1 and 0.0006 a-1, respectively. The vegetation improvement was mostly dominated by the combination effects of climate change and human activities. The vegetation improvement was dominated by climate change, and the relative role of climate change reached 61.86%. What is more, the vegetation degradation was dominated by human activities, and the relative role of human activities reached 58.39%. Vegetation cover was positively related to minimum temperature, precipitation, maximum temperature, potential evapotranspiration rate, and relative humidity and negatively related to mean temperature, atmosphere pressure, sunshine duration, warmth index, and humidity index. As a whole, the minimum temperature, sunshine duration, and precipitation were the dominant climate factors affecting the vegetation variation in southwest China. Furthermore, the land use and land cover change were significantly related to vegetation variation in southwest China. The implementation of ecological afforestation projects could be beneficial to regional vegetation improvement, whereas the vegetation degradation was mostly conducted by the built-up land expansion.

Lipopolysaccharide and lipoteichoic acid regulate the PI3K/AKT pathway through osteopontin/integrin ß3 to promote malignant progression of non-small cell lung cancer.

Background: Lung cancer (LC) is a malignancy with one of the highest mortality rates. Respiratory microbiota is considered to play a key role in the development of LC, but the molecular mechanisms are rarely studied. Methods: We used lipopolysaccharide (LPS) and lipoteichoic acid (LTA) to study human lung cancer cell lines PC9 and H1299. The gene expression of CXC chemokine ligand (CXCL)1/6, interleukin (IL)-6, IL-8, and tumor necrosis factor (TNF)-α were analyzed by quantitative real-time polymerase chain reaction (qRT-PCR). The Cell-Counting Kit 8 (CCK-8) was used to analyze cell proliferation. Transwell assays were performed to analyze cell migration ability. Flow cytometry was used to observe cell apoptosis. Western blot and qRT-PCR were used to analyze the expression of secreted phosphoprotein 1 (SPP1), toll-like receptor (TLR)-2/4, and NLR family pyrin domain containing 3 (NLRP3) to determine the mechanism of LPS + LTA. We evaluated the effect of LPS + LTA on cisplatin sensibility by analyzing cell proliferation, apoptosis, and caspase-3/9 expression levels. We observed the proliferation activity, apoptosis, and migration ability of cells in which SPP1 had been transfected small interfering (si) negative control (NC) and integrin ß3 siRNA. Then the mRNA expression level and protein expression of PI3K, AKT, and ERK were analyzed. Finally, the nude mouse tumor transplantation model was conducted to verify. Results: We studied that in two cell lines, the expression level of inflammatory factors in LPS+LTA group was significantly higher than that in single treatment group (P<0.001). We explored LPS + LTA combined treatment group significantly increased the expression of NLRP3 and genes and proteins. LPS + LTA + Cisplatin group could significantly reduce the inhibitory effect of LPS on cell proliferation (P<0.001), reduce the apoptosis rate (P<0.001) and significantly reduce the expression levels of caspase-3/9 (P<0.001) compared with Cisplatin group. Finally, we verified that LPS and LTA could increase osteopontin (OPN)/integrin ß3 expression and activate the PI3K/AKT pathway to promote malignant progression of LC in vitro studies. Conclusions: This study provides a theoretical basis for further exploration of the influence of lung microbiota on NSCLC and the optimization of LC treatment in the future.

[Spatio-temporal Variation in PM2.5 Concentration and Its Relationship with Vegetation Landscape Patterns in Typical Economic Zones in China from 2000 to 2020].

This study explored the temporal and spatial variation in PM2.5 concentration and its relationship with the vegetation landscape pattern in three typical economic zones in China, which is of great significance for regional PM2.5pollution control and atmospheric environmental protection. In this study, the pixel binary model, Getis-Ord Gi* analysis, Theil-Sen Median analysis, Mann-Kendall significance test, Pearson correlation analysis, and multiple correlation analysis were used to explore the spatial cluster and spatio-temporal variation in PM2.5 and its correlation with the vegetation landscape index in the three economic zones of China on the basis of PM2.5 concentration data and MODIS NDVI data set. The results showed that PM2.5 in the Bohai Economic Rim was mainly dominated by the expansion of hot spots and the reduction in cold spots from 2000 to 2020. The proportion of cold spots and hot spots in the Yangtze River Delta showed insignificant changes. Both cold and hot spots in the Pearl River Delta had expanded. PM2.5 showed a downward trend in the three major economic zones from 2000 to 2020, and the magnitudes of increasing rates were higher in the Pearl River Delta, followed by those in the Yangtze River Delta and Bohai Economic Rim. From 2000 to 2020, PM2.5 exhibited a downward trend in the context of all vegetation coverage grades, and PM2.5 had most significantly improved within extremely low vegetation coverage in the three economic zones. On the landscape scale, PM2.5 values were mostly correlated with aggregation index in the Bohai Economic Rim, with the largest patch index in the Yangtze River Delta and Shannon's diversity in the Pearl River Delta, respectively. Under the context of different vegetation coverage levels, PM2.5showed the highest correlation with aggregation index in the Bohai Economic Rim, landscape shape index in the Yangtze River Delta, and percent of landscape in the Pearl River Delta, respectively. PM2.5 showed significant differences with vegetation landscape indices in the three economic zones. The combined effect of multiple vegetation landscape pattern indices on PM2.5 was stronger than that of the single vegetation landscape pattern index. The above results indicated that the spatial cluster of PM2.5 in the three major economic zones had changed, and PM2.5 showed a decreasing trend in the three economic zones during the study period. The relationship between PM2.5 and vegetation landscape indices exhibited obvious spatial heterogeneity in the three economic zones.

[Spatial-temporal Variation in Net Primary Productivity in Terrestrial Vegetation Ecosystems and Its Driving Forces in Southwest China].

Studying the spatial-temporal variation in net primary productivity (NPP) in terrestrial vegetation ecosystems and its driving forces in southwest China is of great importance for regional eco-environmental protection. The spatial and temporal changes in net primary productivity (NPP) in terrestrial vegetation ecosystems and its responding characteristics to climate change and human activities were explored in this study on the basis of the Moderate Resolution Imaging Spectroradiometer (MODIS) NPP from 2000 to 2021, in situ meteorological data from 1999 to 2021, and land use type datasets from 2000 to 2020 using principal component analysis, residual analysis, Theil-Sen Median analysis, and partial correlation analysis. The results showed that on a temporal scale, the vegetation NPP showed a fluctuating upward trend, with a rate of 3.54 g·(m2·a)-1in southwest China from 2000 to 2021. Meanwhile, under the influence of climate change and human activities, NPP of farmland, grassland, and forests all showed an upward trend, but the magnitude of the increasing trends of farmland NPP was the most significant. On the spatial scale, the areas with an upward trend in vegetation NPP accounted for 89.06% in southwest China, and the areas with significant and extremely significant increases were mainly distributed in southern Guangxi, eastern Sichuan, western Chongqing, and the junction areas of Yunnan and Guizhou. Climate change and human activities had dual effects on vegetation growth in southwest China, and the proportions of the areas with upward trends in farmland NPP were higher than that of grassland and forests both under the influences of climate change and human activities. The correlations between vegetation NPP and climate factors showed obvious regional differences in southwest China. On the regional scale, the areas with a positive correlation between vegetation NPP and temperature, precipitation, and sunshine duration were greater than that of the areas with a negative correlation. However, an opposite relationship could be found between vegetation NPP and biological aridity/humidity index. Among them, the areas with a positive correlation between vegetation NPP and temperature were greater than that with other climate factors. In terms of different vegetation ecosystems, temperature, precipitation, and sunshine duration had a stronger role in promoting NPP variation in the grassland ecosystem than in farmland and forest ecosystems. The transformation of other land use types to forest land had contributed to vegetation improvement in southwest China.

[Dynamic Variation in Vegetation Cover and Its Influencing Factor Detection in the Yangtze River Basin from 2000 to 2020].

Studies on the dynamic variation in vegetation cover and detecting its influencing factors are highly valuable for monitoring regional ecological environment quality and evaluating forestry restoration project effects. In this study, on the basis of the MODIS normalized difference vegetation index (NDVI), in situ climate data, digital elevation model, population density, nighttime lights using Theil-Sen Median analysis, Mann-Kendall significance test, stability analysis, and geographical detector model, the spatiotemporal variation and stability of vegetation cover in the context of multi-spatiotemporal scales were analyzed, and the dominant influencing factors that affect the spatial differentiation of vegetation cover were further detected. The results showed that the vegetation cover showed a fluctuant increasing trend, and the changing trend exhibited obvious spatial heterogeneity with the increasing rate being higher in the middle and lower in the east and west portion of the Yangtze River basin from 2000 to 2020. At the sub-basin scale, except for that in the Taihu Lake basin, the vegetation cover in all sub-basin units exhibited an increasing trend during the study period. The areas with an increasing trend accounted for 84.09% of the study area, in which the areas with extremely significant increases and significant increases accounted for 53.67%, which were mainly distributed in the Wujiang River basin, Yibin-yichang, Jialing River basin, Han River basin, and Dongting Lake basin. The vegetation cover showed lower stability in the upper reaches of the Jinsha-shigu River basin and Taihu Lake basin and higher stability in other sub-basin units of the study area. Elevation was an important factor affecting the vegetation variation in all sub-basin areas. Climatic factors presented the highest impact on vegetation variation in the upper reaches of the Jinsha-shigu River basin, and human activities exhibited the greatest impact on vegetation variation in the Wujiang River basin, lower reaches of Hukou basin, and Taihu Lake basin. The interaction of the two influencing factors on vegetation variation showed mutual and non-linear enhancement, and the interaction between elevation and wind speed presented the highest value, with an explanatory power of 68%. The ecological exploration results showed that human activities combined with topographic factors and climate factors, except for slope and relative humidity, significantly differed in the explanatory power of vegetation variation in the Yangtze River basin. These results can provide a basis for formulating comprehensive vegetation resource management in the Yangtze River basin that takes into account regional climate, topography, and human activities.

[Responding Mechanism of Vegetation Cover to Climate Change and Human Activities in Southwest China from 2000 to 2020].

Studying vegetation cover variation and its responding mechanism to climate change and human activities is of great significance for regional ecological protection and vegetation restoration. In this study, on the basis of MODIS NDVI, in situ climate data, and land use type data using Theil-Sen Median analysis, the Mann-Kendall significance test, residual analysis, partial correlation analysis, and multi-correlation analysis, the spatial and temporal variation in vegetation cover and its response to climate change and the land use/land cover change in each geomorphological unit in southwest China were analyzed. The vegetation cover showed a fluctuant increasing trend, and the changing trend exhibited obvious spatial heterogeneity, with the increasing rate being higher in the southeast and lower in the northwest of southwest China from 2000 to 2020. The vegetation variation was dominated by positive effects of the climate change and human activities in southwest China, and the positive effects were stronger in Guangxi Hill than those in other geomorphological units. Furthermore, from 2000 to 2020 the vegetation cover was positively associated with precipitation and temperature and negatively correlated with relative humidity and sunshine duration in southwest China. Temperature was considered to be the dominate climate factor controlling the vegetation variation in the study area. Urban expansion had decreased the region vegetation cover, but the overall vegetation cover had increased in southwest China due to the suitable regional climate conditions and the implementation of ecological reforestation projection. These results can provide scientific references for ecological protection and economic sustainable development in southwest China.

Genome-Wide Search for Competing Endogenous RNAs Responsible for the Effects Induced by Ebola Virus Replication and Transcription Using a trVLP System.

Understanding how infected cells respond to Ebola virus (EBOV) and how this response changes during the process of viral replication and transcription are very important for establishing effective antiviral strategies. In this study, we conducted a genome-wide screen to identify long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), micro RNAs (miRNAs), and mRNAs differentially expressed during replication and transcription using a tetracistronic transcription and replication-competent virus-like particle (trVLP) system that models the life cycle of EBOV in 293T cells. To characterize the expression patterns of these differentially expressed RNAs, we performed a series cluster analysis, and up- or down-regulated genes were selected to establish a gene co-expression network. Competing endogenous RNA (ceRNA) networks based on the RNAs responsible for the effects induced by EBOV replication and transcription in human cells, including circRNAs, lncRNAs, miRNAs, and mRNAs, were constructed for the first time. Based on these networks, the interaction details of circRNA-chr19 were explored. Our results demonstrated that circRNA-chr19 targeting miR-30b-3p regulated CLDN18 expression by functioning as a ceRNA. These findings may have important implications for further studies of the mechanisms of EBOV replication and transcription. These RNAs potentially have important functions and may be promising targets for EBOV therapy.