Difference analysis of intestinal microbiota and metabolites in piglets of different breeds exposed to porcine epidemic diarrhea virus infection.

The gut microbial composition of the Luchuan (LC) piglet, one of China's native breeds, has rarely been studied, especially when compared to other breeds. This study developed a porcine epidemic diarrhea virus (PEDV) infection model in LC and Largewhite (LW) piglets, and analyzed the patterns and differences of intestinal microbial communities and metabolites in piglets of these two breeds after infection. The diarrhea score, survival time, and distribution of viral antigens in the intestine of piglets infected with PEDV differed among breeds, with the jejunal immunohistochemistry score of LW piglets being significantly higher than that of LC piglets (P < 0.001). The results of 16S rRNA sequencing showed differences in microbial diversity and community composition in the intestine of piglets with different breeds between PEDV infection piglets and the healthy controls. There were differences in the species and number of dominant phyla and dominant genera in the same intestinal segment. The relative abundance of Shigella in the jejunum of LC piglets after PEDV infection was significantly lower than that of LW piglets (P < 0.05). The key microorganisms differed in the microbiota were Streptococcus alactolyticus, Roseburia faecis, Lactobacillus iners, Streptococcus equi, and Lactobacillus mucosae (P < 0.05). The non-targeted metabolite analysis revealed that intestinal metabolites showed great differences among the different breeds related to infection. Spearman correlation analysis was conducted to examine any links between the microbiota and metabolites. The metabolites in the intestine of different breeds related to infection were mainly involved in arginine biosynthesis, synaptic vesicle cycle, nicotinic acid and nicotinamide metabolism and mTOR signaling pathway, with significantly positive or negative correlations (P < 0.05) between the various microorganisms. This study provides a theoretical foundation for investigating the application of core microorganisms in the gut of piglets of different breeds in the digestive tracts of those infected with PEDV, and helps to tackle the antimicrobial resistance problem further.

An ultrasensitive electrochemical sensor for detecting porcine epidemic diarrhea virus based on a Prussian blue-reduced graphene oxide modified glassy carbon electrode.

This study developed a novel, ultrasensitive sandwich-type electrochemical immunosensor for detecting the porcine epidemic diarrhea virus (PEDV). By electrochemical co-deposition of graphene and Prussian blue, a Prussian blue-reduced graphene oxide-modified glassy carbon electrode was made, further modified with PEDV-monoclonal antibodies (mAbs) to create a new PEDV immunosensor using the double antibody sandwich technique. The electrochemical characteristics of several modified electrodes were investigated using cyclic voltammetry (CV). We optimized the pH levels and scan rate. Additionally, we examined specificity, reproducibility, repeatability, accuracy, and stability. The study indicates that the immunosensor has good performance in the concentration range of 1 × 101.88 to 1 × 105.38 TCID50/mL of PEDV, with a detection limit of 1 × 101.93 TCID50/mL at a signal-to-noise ratio of 3σ. The composite membranes produced via co-deposition of graphene and Prussian blue effectively increased electron transport to the glassy carbon electrode, boosted response signals, and increased the sensitivity, specificity, and stability of the immunosensor. The immunosensor could accurately detect PEDV, with results comparable to real-time quantitative PCR. This technique was applied to PEDV detection and served as a model for developing additional immunosensors for detecting hazardous chemicals and pathogenic microbes.

Detection and genetic characterization of novel infectious bronchitis viruses from recent outbreaks in broiler and layer chicken flocks in southern China, 2021.

Avian infectious bronchitis virus (IBV) is a prevalent RNA virus that causes respiratory distress, nephritis, salpingitis, and egg production decline in chickens, resulting in significant economic loss. IBV is composed of complex genotypes and serotypes, which poses a great challenge for disease control. The current study reports 2 IBV outbreaks which were characterized by respiratory symptoms in IBV vaccinated commercial broilers and layers in Guangdong, China, in 2021. Two IBV strains, ZH01 and HH09, were identified via a RT-PCR assay through targeting the N gene and further characterization through full-length spike (S) gene sequence analysis. Phylogenetic analysis of S1 gene revealed that both ZH01 and HH09 belonged to the GI-19 lineage but contained a certain genetic distance from the GI-19 strain. Of note, the ZH01 and HH09 strains share a low homology of 70 and 86%, respectively, with common vaccine strains (H120), resulting in low vaccine protection. Further recombination analysis based on the S1 sequence suggested the newly identified IBV strains emerged through an intragroup recombination events between CK/CH/SCDY2003-2 and I0305/19 from G1-19 lineage. In addition, a number of novel mutations such as T273I, T292A, and S331K were found in the emerging IBV strains. Taken together, this study reports the genetic characteristics of 2 recent IBV outbreaks in southern China and emphasizes the urgent need for enhanced surveillance and development of novel vaccines for the control of IBV.

Assessing Asymptomatic, Presymptomatic, and Symptomatic Transmission Risk of Severe Acute Respiratory Syndrome Coronavirus 2.

BACKGROUND: The relative contributions of asymptomatic, presymptomatic, and symptomatic transmission of severe acute respiratory syndrome coronavirus 2 have not been clearly measured, although control measures may differ in response to the risk of spread posed by different types of cases. METHODS: We collected detailed information on transmission events and symptom status based on laboratory-confirmed patient data and contact tracing data from 4 provinces and 1 municipality in China. We estimated the variation in risk of transmission over time and the severity of secondary infections by symptomatic status of the infector. RESULTS: There were 393 symptomatic index cases with 3136 close contacts and 185 asymptomatic index cases with 1078 close contacts included in the study. The secondary attack rates among close contacts of symptomatic and asymptomatic index cases were 4.1% (128 of 3136) and 1.1% (12 of 1078), respectively, corresponding to a higher transmission risk from symptomatic cases than from asymptomatic cases (odds ratio, 3.79; 95% confidence interval, 2.06-6.95). Approximately 25% (32 of 128) and 50% (6 of 12) of the infected close contacts were asymptomatic from symptomatic and asymptomatic index cases, respectively, while more than one third (38%) of the infections in the close contacts of symptomatic cases were attributable to exposure to the index cases before symptom onset. CONCLUSIONS: Asymptomatic and presymptomatic transmissions play an important role in spreading infection, although asymptomatic cases pose a lower risk of transmission than symptomatic cases. Early case detection and effective test-and-trace measures are important to reduce transmission.

Estimating the Latent Period of Coronavirus Disease 2019 (COVID-19).

Using detailed exposure information on COVID-19 cases, we estimated the mean latent period to be 5.5 (95% CI: 5.1-5.9) days, shorter than the mean incubation period (6.9 days). Laboratory testing may allow shorter quarantines since 95% of COVID-19 cases shed virus within 10.6 (95% CI: 9.6-11.6) days of infection.

Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 to Close Contacts, China, January-February 2020.

We estimated the symptomatic, PCR-confirmed secondary attack rate (SAR) for 2,382 close contacts of 476 symptomatic persons with coronavirus disease in Yichang, Hubei Province, China, identified during January 23-February 25, 2020. The SAR among all close contacts was 6.5%; among close contacts who lived with an index case-patient, the SAR was 10.8%; among close-contact spouses of index case-patients, the SAR was 15.9%. The SAR varied by close contact age, from 3.0% for those <18 years of age to 12.5% for those >60 years of age. Multilevel logistic regression showed that factors significantly associated with increased SAR were living together, being a spouse, and being >60 years of age. Multilevel regression did not support SAR differing significantly by whether the most recent contact occurred before or after the index case-patient's onset of illness (p = 0.66). The relatively high SAR for coronavirus disease suggests relatively high virus transmissibility.

Evidence for pre-symptomatic transmission of coronavirus disease 2019 (COVID-19) in China.

BACKGROUND: Between mid-January and early February, provinces of mainland China outside the epicentre in Hubei province were on high alert for importations and transmission of COVID-19. Many properties of COVID-19 infection and transmission were still not yet established. METHODS: We collated and analysed data on 449 of the earliest COVID-19 cases detected outside Hubei province to make inferences about transmission dynamics and severity of infection. We analysed 64 clusters to make inferences on serial interval and potential role of pre-symptomatic transmission. RESULTS: We estimated an epidemic doubling time of 5.3 days (95% confidence interval (CI): 4.3, 6.7) and a median incubation period of 4.6 days (95% CI: 4.0, 5.2). We estimated a serial interval distribution with mean 5.7 days (95% CI: 4.7, 6.8) and standard deviation 3.5 days, and effective reproductive number was 1.98 (95% CI: 1.68, 2.35). We estimated that 32/80 (40%) of transmission events were likely to have occurred prior to symptoms onset in primary cases. Secondary cases in clusters had less severe illness on average than cluster primary cases. CONCLUSIONS: The majority of transmissions are occurring around illness onset in an infected person, and pre-symptomatic transmission does play a role. Detection of milder infections among the secondary cases may be more reflective of true disease severity.