THP-1 monocyte, which can be differentiated into macrophages by PMA, is widely used in researches on pathogen infection and host innate immunity, but reports on the induction methods of PMA are different and lack a unified standard, and the transcriptome characteristics of macrophage compared with THP-1 cells remains unclear. In this research, we examined the differentiation effect of three factors including induction time, cell seeding density and PMA concentration by detecting the positive rate of CD14 expression. The concentration of 80ng/ml of PMA, the induction time of 24h, and the cell seeding density of 5×10⁵ cells/ml, could respectively facilitates a relatively higher CD14 positive rate in THP-1 cells. Under this optimized conditions, the CD14 positive rate of THP-1 cells can reach 66.52%. Transcriptome sequencing showed that after the above induction, the mRNA expression of 3113 genes which were closely related to cell communication, signal transduction, cell response to stimulus, signaling receptor binding and cytokine activity were up-regulated, and the top 10 genes were RGS1, SPP1, GDF15, IL-1B, HAVCR2, SGK1, EGR2, TRAC, IL-8 and EBI3. While the mRNA expression of 2772 genes which were associated with cell cycle process, DNA binding and replication and cell division, were down-regulated, and the top genes were SERPINB10, TRGC2, SERPINB2, TRGC1, MS4A3, MS4A4E, TRGJP1, MS4A6A, TRGJP2, MS4A4A. This research optimized the induction method on THP-1 cell differentiation from three aspects and delineated the transcriptomic profile of PMA-induced THP-1 cells, laying a foundation for the construction method of cell model and for the functional study of macrophage.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease and that is a severe threat to public health considering its high fatality and person-to-person transmission. In order to obtain an updated and deep understanding of the epidemiological characteristics of SFTS in mainland China, we used Pearson’s chi-squared test to compare the fatality rate and demographic characteristics in different groups. Data were analyzed in R3.6.1 (R Development Core Team 2018), while the visualization was performed in ArcGIS 10 (ESRI, Redlands, CA, USA), and the statistical significance was set at p < 0.05. A total of 13,824 SFTS cases involving 8899 lab-confirmed cases and 4925 probable cases were reported and included in the epidemiological analysis. Our study found that the number of SFTS cases showed an increasing trend with a small decrease in the past three years. The laboratory-confirmed rate was about 64.4%, which varied between different years and areas. Although most cases (99.3%) were distributed in 7 provinces (Henan, Shandong, Anhui, Hubei, Liaoning, Zhejiang, and Jiangsu), the regional distribution of SFTS gradually expanded from 5 provinces in 2010 to 25 provinces by 2019, especially at the town level. The SFTS cases were mainly sporadic. A total of 96.5% occurred from April to October, and 93.3% of cases were concentrated in middle-aged and elderly people (40–84 years old). Farmers were the main high-risk population. Female cases were slightly more than male cases; however, there were differences between different provinces. The mortality rate showed an increasing trend with age. Overall, the SFTS cases were mainly middle-aged and elderly farmers that sporadically distributed throughout seven provinces with a spatially expanding trend. The laboratory-confirmed rate varied in different years and provinces, which implied that the diagnosis and report criteria for SFTS should be further updated and unified in order to get a better understanding of its epidemiological characteristics and provide scientific data for SFTS control.

High rate of cardiovascular disease (CVD) has been reported among patients with coronavirus disease 2019 (COVID-19). Importantly, CVD, as one of the comorbidities, could also increase the risks of the severity of COVID-19. Here we identified phospholipase A2 group VII (PLA2G7), a well-studied CVD biomarker, as a hub gene in COVID-19 though an integrated hypothesis-free genomic analysis on nasal swabs (n = 486) from patients with COVID-19. PLA2G7 was further found to be predominantly expressed by proinflammatory macrophages in lungs emerging with progression of COVID-19. In the validation stage, RNA level of PLA2G7 was identified in nasal swabs from both COVID-19 and pneumonia patients, other than health individuals. The positive rate of PLA2G7 were correlated with not only viral loads but also severity of pneumonia in non-COVID-19 patients. Serum protein levels of PLA2G7 were found to be elevated and beyond the normal limit in COVID-19 patients, especially among those re-positive patients. We identified and validated PLA2G7, a biomarker for CVD, was abnormally enhanced in COVID-19 at both nucleotide and protein aspects. These findings provided indications into the prevalence of cardiovascular involvements seen in patients with COVID-19. PLA2G7 could be a potential prognostic and therapeutic target in COVID-19.

Hantaan virus (HTNV; family Hantaviridae, order Bunyavirales) causes hemorrhagic fever with renal syndrome (HFRS), which has raised serious concerns in Eurasia, especially in China, Russia, and South Korea. Previous studies reported genetic diversity and phylogenetic features of HTNV in different parts of China, but the analyses from the holistic perspective are rare. To better understand HTNV genetic diversity and gene evolution, we analyzed all available complete sequences derived from the small (S) and medium (M) segments with bioinformatic tools. Eleven phylogenetic groups were defined and showed geographic clustering; 42 significant amino acid variant sites were found, and 19 of them were located in immune epitopes; nine recombinant events and eight reassortments with highly divergent sequences were found and analyzed. We found that sequences from Guizhou showed high genetic divergence, contributing to multiple lineages of the phylogenetic tree and also to the recombination and reassortment events. Bayesian stochastic search variable selection analysis revealed that Heilongjiang, Shaanxi, and Guizhou played important roles in HTNV evolution and migration; the virus may originate from Zhejiang Province in the eastern part of China; and the virus population size expanded from the 1980s to 1990s. These findings revealed the original and evolutionary features of HTNV, which will help to illustrate hantavirus epidemic trends, thus aiding in disease control and prevention. Hemorrhagic fever with renal syndrome (HFRS) and hantavirus pulmonary syndrome are endemic zoonotic infectious diseases caused by hantaviruses, which have threatened public health worldwide for decades. However, our knowledge about the emergence and evolution of HTNV still need to be improved. To get more information about HTNV genetic diversity and phylogenetic features with a holistic perspective, we investigated the genetic diversity and spatial distribution of HTNV using all available whole-genome sequences of small (S) and medium (M) segments collected from 18 different regions and using a larger timescale; 11 phylogenetic groups were defined. The sequences showed geographic clustering, and divergence with recombinant or reassortment events occurred. Using the Bayesian stochastic search variable selection method, geographic origins and migration patterns of HTNV epidemics were deduced. Our data provided important biological information to better understand hantavirus evolution, transmission, and epidemics.

Severe fever with thrombocytopenia syndrome (SFTS) is a newly identified severe infectious disease caused by SFTS phlebovirus (SFTSV). SFTS monitoring has been carried out since 2010 in mainland China. We analysed the detection results of SFTSV RNA and antibody in SFTS surveillance cases to provide basic data for SFTS diagnosis. This study was conducted in Shandong Province. Sera of SFTS surveillance cases were collected to detect SFTSV RNA and antibody by real-time RT-PCR and enzyme-linked immunosorbent assay, respectively. Detection rates were calculated. SPSS 18.0 (Chicago, IL, USA) was used for statistical analysis to compare the detection rates of SFTSV RNA and antibodies among different sera groups. A total of 374 SFTS surveillance cases were enrolled. Overall, 93.3% (349/374) of the sera samples were collected within 2 weeks after onset, and 6.7% (25/374) were collected between 15 days and 45 days. Of these, 183 (48.9%) were positive for SFTSV RNA. The SFTSV RNA-positive rate peaked (52.2%) in samples collected ≤7 days after onset and then showed a decreasing trend. The detection rate of SFTSV-specific IgM antibody was 30.5% (46/151) and was highest in samples collected between 8 and 14 days (43.3%, 26/60). The positive rate of SFTSV-specific IgG antibody (17.9%, 27/151) showed an increasing trend with the specimen collection time. In total, 74.8% (113/151) of sera samples had the same SFTSV RNA and IgM antibody detection results. However, 23.2% (29/125) of SFTSV RNA-negative cases were IgM antibody-positive, and 8.6% (9/105) of IgM antibody-negative cases were SFTSV RNA-positive. SFTSV RNA detection was preferred for SFTSV infection during disease surveillance. For highly suspected SFTS cases, IgM antibody is suggested to make a comprehensive judgement.