Emerging Microbes & Infections最新文献

During the COVID-19 pandemic, healthcare systems worldwide faced severe strain. This study, utilizing wastewater virus surveillance, identified that periodic spontaneous avoidance behaviours significantly impacted infectious disease transmission during rapid and intense outbreaks. To incorporate these behaviours into disease transmission analysis, we introduced the Su-SEIQR model and validated it using COVID-19 wastewater data from Beijing and Hong Kong. The results demonstrated that the Su-SEIQR model accurately reflected trends in susceptible populations and confirmed cases during the COVID-19 pandemic, highlighting the role of spontaneous collective avoidance behaviours in generating periodic fluctuations. These fluctuations helped reduce infection peaks, thereby alleviating pressure on healthcare systems. However, the effect of these spontaneous behaviours on mitigating healthcare overload was limited. Consequently, we incorporated healthcare capacity constraints into the model, adjusting parameters to further guide population behaviours during the pandemic, aiming to keep the outbreak within manageable limits and reduce strain on healthcare resources. This study provides robust support for the development of environmental and public health policies during pandemics by constructing an innovative transmission model, which effectively prevents healthcare overload. Additionally, this approach can be applied to managing future outbreaks of unknown viruses or "Disease X".

We present the first documented case of highly pathogenic avian influenza virus (HPAIV) subtype H5N5 in an Atlantic walrus (Odobenus rosmarus rosmarus). The animal was found dead in Svalbard, Norway, in 2023. Sequence analysis revealed the highest genetic similarity with virus isolates from different avian hosts.

While morphological examination is the most widely used for Aspergillus identification in clinical laboratories, PCR-sequencing and MALDI-TOF MS are emerging technologies in more financially-competent laboratories. However, mycological expertise, molecular biologists and/or expensive equipment are needed for these. Recently, artificial intelligence (AI), especially image recognition, is being increasingly employed in medicine for fast and automated disease diagnosis. We explored the potential utility of AI in identifying Aspergillus species. In this proof-of-concept study, using 2813, 2814 and 1240 images from four clinically important Aspergillus species for training, validation and testing, respectively; the performances and accuracies of automatic Aspergillus identification using colonial images by three different convolutional neural networks were evaluated. Results demonstrated that ResNet-18 outperformed Inception-v3 and DenseNet-121 and is the best algorithm of choice because it made the fewest misidentifications (n = 8) and possessed the highest testing accuracy (99.35%). Images showing more unique morphological features were more accurately identified. AI-based image recognition using colonial images is a promising technology for Aspergillus identification. Given its short turn-around-time, minimal demand of expertise, low reagent/equipment costs and user-friendliness, it has the potential to serve as a routine laboratory diagnostic tool after the database is further expanded.

Infections caused by Acinetobacter baumannii (A. baumannii) have emerged as a global public health concern because of high pathogenicity of this bacterium. Monoclonal antibodies (mAbs) have a lower likelihood of promoting drug resistance and offer targeted treatment, thereby reducing potential adverse effects; however, the therapeutic potential of mAbs targeting A. baumannii has not been fully characterized. In this study, mAbs against the outer membrane proteins (OMPs) of A. baumannii were isolated in a high-throughput manner. The ability of Omp38-specific mAbs to bind to A. baumannii strains from diverse sources was confirmed via enzyme-linked immunosorbent assay (ELISA). Intravenous administration of the Omp38-specific mAbs significantly improved the survival rate and reduced the bacterial load in a mouse model of lethal A. baumannii infection. Flow cytometry and ELISA confirmed that immune cell infiltration and cytokine production, respectively, decreased in a mouse model of sublethal A. baumannii infection. In addition, analysis of the Omp38-mAb C3 binding conformation revealed the potential mechanism of broad-spectrum binding activity of this mAb against A. baumannii. Taken together, these findings indicate that mAbs against Omp38 facilitate bacterial clearance from host, minimize inflammatory mediator release and reduce host damage, highlighting the potential of Omp38-specific mAbs in the clinical treatment of A. baumannii infection.

The identification of individuals with the greatest risk of progression to active tuberculosis (TB) disease from the huge reservoir of Mycobacterium tuberculosis (Mtb) infected individuals continues to remain an arduous ascent in the global effort to control TB. In a two-year prospective study, we analysed metabolic profiles in the unstimulated and TB antigen stimulated QuantiFERON supernatants of 14 healthy household contacts (HHCs) who progressed to TB disease (Progressors) and 14 HHCs who remained healthy (Non-Progressors). We identified 21 significantly dysregulated metabolites in the TB antigen-stimulated QuantiFERON supernatants of Progressors, of which the combination of Malic acid and N-Arachidonoylglycine had maximum AUC of 0.99. Eighteen significantly dysregulated metabolites were identified in the unstimulated QuantiFERON supernatants of Progressors, among which the combination of Orotic acid and the phosphatidylcholines PC (O-34:1), PC (O-18:1(9Z)/16:0), PC (O-18:1(11Z)/16:0) had the maximum AUC of 0.98. Most of the dysregulated metabolites belonged to the pathways of fatty acid metabolism, lipid metabolism and nitric oxide metabolism. Validation of these metabolic signatures in large, diverse cohorts would pave way for the development of a robust test that can identify individuals at high risk of TB for targetted intervention of TB disease.

ABSTRACTThe current outbreak of HPAI H5N1 virus infections in dairy cattle in the USA underscores the need for easily accessible methods to rapidly assess host susceptibility for infection with known and emerging influenza viruses. Here we show that ex vivo lung slice cultures from calves provide a useful method to rapidly screen host susceptibility to a range of influenza A viruses.

Group B Coxsackieviruses (CVBs) consist of six serotypes, CVB1 to CVB6, which can clinically affect the heart, brain, liver, pancreas and other organs, causing myocarditis, encephalitis, myelitis, pancreatitis, hand-foot-and-mouth disease (HFMD) and other diseases, and can even lead to death. CVBs are widespread globally and highly contagious. However, there are currently no approved CVB vaccines or effective treatments. The construction and optimization of animal models will aid in the in-depth understanding of CVB infections and its pathogenesis, providing essential tools for the exploration of vaccine development and antiviral therapies. This paper reviews the latest research progress and application prospects of CVB animal models.

Hepatitis B virus (HBV) DNA integration into the host cell genome is reportedly a major cause of liver cancer, and a source of hepatitis B surface antigen (HBsAg). High HBsAg levels can alter immune responses which therefore contributes to the progression of HBV-related disease. However, to what extent integration leads to the persistent circulating HBsAg is unclear. Here, we aimed to determine if the extent of HBV DNA integration is associated with the persistence of circulating HBsAg in people exposed to HBV. We established a digital droplet quantitative inverse PCR (dd-qinvPCR) method to quantify integrated HBV DNA in patients who had been exposed to HBV (anti-HBc positive and HBeAg-negative). Total DNA extracts from both liver resections (n = 32; 14 HBsAg-negative and 18 HBsAg-positive) and fine-needle aspirates (FNA, n = 10; 2 HBsAg-negative and 8 HBsAg-positive) were analysed. Using defined in vitro samples for assay establishment, we showed that dd-qinvPCR could detect integrations within an input of <80 cells. The frequency of integrated HBV DNA in those who had undergone HBsAg loss (n = 14, mean ± SD of 1.514 × 10^-3± 1.839 × 10^-3 integrations per cell) was on average 9-fold lower than those with active HBV infection (n = 18, 1.16 × 10^-2± 1.76 × 10^-2 integrations per cell; p = 0.0179). In conclusion, we have developed and validated a highly precise, sensitive and quantitative PCR-based method for the quantification of HBV integrations in clinical samples. Natural clearance of HBV is associated with fewer viral integrations. Future studies are needed to determine if dynamics of integrated HBV DNA can inform the development of curative therapies.

Highly pathogenic avian influenza (HPAI) H5N1 is known for its virulence and zoonotic potential, infecting birds and mammals, thus raising public health concerns. Since 2021 its spread among birds has led to cross-species transmission causing epizootics among mammals, eventually impacting fur animal farms in Finland in 2023. To analyze the infectivity of the Finnish H5N1 isolates in human cells, representatives of diverse H5N1 isolates were selected based on the genetic differences, host animal species, and the year of occurrence. The infection kinetics of the selected H5N1 isolates from wild pheasant and fox, and fur animals blue fox and white mink were examined in human monocyte-derived dendritic cells (moDCs) with H5N1 human isolate as a control. Although the isolate from pheasant (a wild bird) showed weakly reduced replication and viral protein expression in human cells compared to mammalian isolates, no discernible differences in virus replication in moDCs was observed. This study revealed similar infectivity in human moDCs for all five H5N1 isolates, regardless of the observed genetic differences. While H5N1 human infections remain rare, the virus poses a risk for widespread epizootics in mammals such as fur animal farms and, more recently, dairy cattle.