The early diagnosis and investigation of the pathogenic mechanisms of complex diseases are the most challenging problems in the fields of biology and medicine. Network-based systems biology is an important technique for the study of complex diseases. The present study constructed dynamic protein-protein interaction (PPI) networks to identify dynamical network biomarkers (DNBs) and analyze the underlying mechanisms of complex diseases from a systems level. We developed a model-based framework for the construction of a series of time-sequenced networks by integrating high-throughput gene expression data into PPI data. By combining the dynamic networks and molecular modules, we identified significant DNBs for four complex diseases, including influenza caused by either H3N2 or H1N1, acute lung injury and type 2 diabetes mellitus, which can serve as warning signals for disease deterioration. Function and pathway analyses revealed that the identified DNBs were significantly enriched during key events in early disease development. Correlation and information flow analyses revealed that DNBs effectively discriminated between different disease processes and that dysfunctional regulation and disproportional information flow may contribute to the increased disease severity. This study provides a general paradigm for revealing the deterioration mechanisms of complex diseases and offers new insights into their early diagnoses.

Background: Salmonella is an important zoonotic pathogen, and chickens are one of its main hosts. Every year, Salmonella infections pose a serious threat to the poultry industry in developing countries, especially China. In this study, a total of 84 Salmonella isolates recovered from sick and healthy-looking chickens in central China were characterized by serotyping, MLST-based strain typing, presence of potential virulence factors, and antimicrobial resistance profiles. Result: Data showed that the main serotypes of Salmonella isolates in central China were Salmonella enterica serovar Gallinarum biovar Pullorum, Salmonella enterica serovar Gallinarum biovar Gallinarum, Salmonella enterica serovar Enteritidis and Salmonella enterica serovar Typhimurium, and among them, S. Pullorum was the dominant type in both sick and healthy-looking chickens, accounting for 43.9 and 46.5%, respectively, while S. Enteritidis was only found in healthy-looking chickens. All isolates exhibited higher resistance rates to ampicillin (97.6%), tetracycline (58.3%) and colistin (51.2%), and among these isolates, 49.5% were resistant to more than three drugs in different combinations. S. Enteritidis was the most severe multidrug-resistant serotype, which showed higher resistance rates to colistin, meropenem and ciprofloxacin. Multilocus sequence typing (MLST) revealed that S. Gallinarum and S. Enteritidis isolates were clustered in clade 1, which belonged to two and one STs, respectively. All S. Typhimurium isolates were clustered in clade 3, and belonged to three STs. However, S. Pullorum were distributed in three clades, which belonged to 7 STs. Twenty-seven virulence-associated genes were detected, and expected cdtB, which was absent in all the isolates, the other 26 genes were conserved in the closely related Salmonella serogroup D (S. Enteritidis, S. Pullorum, and S. Gallinarum). Conclusion: Salmonella serogroup D was the major subgroup, and S. Pullorum was the most common type in sick and healthy-looking chickens in central China. Drug resistance assays showed serious multiple antimicrobial resistances, and S. Enteritidis was the most severe drug-resistant serotype. MLST showed that there was correlation between serotypes and genotypes in most Salmonella isolates, except S. Pullorum, which showed complicated genetic diversity firstly. These results provide important epidemiological information for us to control Salmonella in chickens.

The investigation of the dynamics and regulation of virus-triggered innate immune signaling pathways at a system level will enable comprehensive analysis of the complex interactions that maintain the delicate balance between resistance to infection and viral disease. In this study, we developed a delayed mathematical model to describe the virus-induced interferon (IFN) signaling process by considering several key players in the innate immune response. Using dynamic analysis and numerical simulation, we evaluated the following predictions regarding the antiviral responses: (1) When the replication ratio of virus is less than 1, the infectious virus will be eliminated by the immune system’s defenses regardless of how the time delays are changed. (2) The IFN positive feedback regulation enhances the stability of the innate immune response and causes the immune system to present the bistability phenomenon. (3) The appropriate duration of viral replication and IFN feedback processes stabilizes the innate immune response. The predictions from the model were confirmed by monitoring the virus titer and IFN expression in infected cells. The results suggest that the balance between viral replication and IFN-induced feedback regulation coordinates the dynamical behavior of virus-triggered signaling and antiviral responses. This work will help clarify the mechanisms of the virus-induced innate immune response at a system level and provide instruction for further biological experiments.

Respiratory syncytial virus (RSV) is a serious respiratory pathogen in infants and young children worldwide. Currently, no licensed RSV vaccines are available. In this study, we explored stable prefusion conformation virus-like particles (Pre-F VLPs) as RSV vaccine candidates. RSV fusion (F) protein mutants were constructed to form stabilized Pre-F or postfusion (Post-F) configurations. VLPs containing Pre-F or Post-F protein were generated using a recombinant baculovirus (rBV)-insect cell expression system. The assembly and immunological properties of Pre-F or Post-F VLPs were investigated. Pre-F and Post-F VLPs contained antigenic sites Ø and I of pre- and postfusion conformations, respectively. Compared with Post-F VLPs, immunization with Pre-F VLPs elicited upregulation of IFN-γ, IL-2 and IL-10 and downregulation of IL-4 and IL-5 cytokine production in mice. A high percentage of CD25⁺ Foxp3⁺ cells or a low percentage of IL-17A-producing cells among CD4⁺ T cells was observed in the lungs of mice vaccinated with Pre-F VLPs. Importantly, immunization with Pre-F VLPs induced a high level of RSV neutralizing antibody and a balanced immune response, which protected mice against RSV infection without evidence of immunopathology. Our results suggested that Pre-F VLPs generated from rBV-insect cells represent promising RSV vaccine candidates.