Phages, the natural predators of bacteria, were discovered more than 100 years ago. However, increasing antimicrobial resistance rates have revitalized phage research. Methods that are more time-consuming and efficient than wet-laboratory experiments are needed to help screen phages quickly for therapeutic use. Traditional computational methods usually ignore the fact that phage-bacteria interactions are achieved by key genes and proteins. Methods for intraspecific prediction are rare since almost all existing methods consider only interactions at the species and genus levels. Moreover, most strains in existing databases contain only partial genome information because whole-genome information for species is difficult to obtain. Here, we propose a new approach for interaction prediction by constructing new features from key genes and proteins via the application of K-means sampling to select high-quality negative samples for prediction. Finally, we develop DeepPBI-KG, a corresponding prediction tool based on feature selection and a deep neural network. The results show that the average area under the curve for prediction reached 0.93 for each strain, and the overall AUC and area under the precision-recall curve reached 0.89 and 0.92, respectively, on the independent test set; these values are greater than those of other existing prediction tools. The forward and reverse validation results indicate that key genes and key proteins regulate and influence the interaction, which supports the reliability of the model. In addition, intraspecific prediction experiments based on Klebsiella pneumoniae data demonstrate the potential applicability of DeepPBI-KG for intraspecific prediction. In summary, the feature engineering and interaction prediction approaches proposed in this study can effectively improve the robustness and stability of interaction prediction, can achieve high generalizability, and may provide new directions and insights for rapid phage screening for therapy.

Background: Metabolites are involved in biological process that govern the immune response to infection and vaccination. Knowledge of how metabolites interact with the immune system during immunization with the COVID-19 vaccine is limited. Here, we report that the serum metabolites are correlated with the magnitude of the antibody response in recipients receiving the inactivated COVID-19 vaccine, which provides critical information for studying metabolism regarding the human immune response to vaccination. Methods: 106 healthy volunteers without history of SARS-CoV-2 infection or vaccination were prospectively enrolled to receive the primary series of two doses of inactivated whole-virion SARS-CoV-2 vaccine. The serum samples were collected 2–4 weeks after the second dose. The magnitude of the anti-RBD antibody was quantified using surrogate virus neutralization tests. The profile of metabolites in serum was identified using untargeted metabolomics analysis. Results: The level of anti-RBD antibody 14–28 days after the second dose was significantly elevated and its interpersonal variability was diverse in a wide range. Thirty-two samples at extremes of the anti-RBD antibody titer were selected to discover the metabolic correlates. Two hundred and fifteen differential metabolites associated with antibody response independent of body mass index were identified. Pregnenolone and sphingolipid metabolism might be involved in the modulation of the human antibody response to the inactivated COVID-19 vaccine. Conclusion: We discovered key metabolites as well as those with a related functional significance that might modulate the human immune response to vaccination.

Background: Encephalitis/meningitis brings a heavy disease burden, and the origin of disease remains unknown in 30–40% of patients. It is greatly significant that combinations of nucleic acid amplification and autoimmune antibody testing improves the diagnosis and treatment of encephalitis/meningitis. Moreover, though several diagnostic methods are in clinical use, a recognized and unified diagnosis and treatment process for encephalitis management remains unclear. Methods: IMPROVE is a multicenter, open label, randomized controlled clinical trial that aims to evaluate the diagnostic performance, applications, and impact on patient outcomes of a new diagnostic algorithm that combines metagenomic next-generation sequencing (mNGS), multiplex polymerase chain reaction (PCR) and autoimmune antibody testing. The enrolled patients will be grouped into two parallel groups, multiplex PCR test plus autoimmune antibody group (Group I) or the mNGS plus autoimmune antibody group (Group II) with a patient ratio of 1:1. Both groups will be followed up for 12 months. The primary outcomes include the initial time of targeted treatment and the modified Rankin scale score on the 30th day of the trial. The secondary outcomes are the cerebrospinal fluid index remission rate on the 14th day, mortality rate on the 30th day, and an evaluation of diagnostic efficacy. The two groups are predicted to comprise of 484 people in total. Discussion: To optimize the roadmap of encephalitis/meningitis, precise diagnosis, and treatment are of great significance. The effect of rapid diagnosis undoubtedly depends on the progression of new diagnostic tests, such as the new multiplex PCR, mNGS, and examination of broad-spectrum autoimmune encephalitis antibodies. This randomized-controlled study could allow us to obtain an accurate atlas of the precise diagnostic ability of these tests and their effect on the treatment and prognosis of patients. Trial registration ClinicalTrial.gov, NCT04946682. Registered 29 June 2021, ‘Retrospectively registered’, https://clinicaltrials.gov/ct2/show/NCT04946682?term=NCT04946682&draw=2&rank=1

Background: pGX9501 is a prophylactic DNA vaccine encoding the spike protein of SARS-CoV-2 and can induce immune response in the human body so as to prevent COVID-19. With respect to non-clinical studies, pGX9501 has been demonstrated to induce both cellular and humoral immune responses in various animal models. It was found that the level of antibody titers following a two-dose regimen was higher than that following a single-dose regimen in nonhuman primate challenge model. Methods: In China, a phase I, randomized, double-blind, placebo-controlled clinical trial has been conducted in Huashan Hospital, Shanghai, China to evaluate the safety, tolerability, and immunogenicity of DNA vaccine pGX9501 administered intradermally (ID) followed by electroporation (EP) in 45 Chinese healthy volunteers aged 18 to 59 years old. Results: No adverse events of special interest (AESIs), death, or treatment-related SAEs occurred in this study. All the treatment-related (vaccine or EP) adverse events (TRAEs) were of grade 1 and 2 in severity. The solicited AEs were reported in thirty-two (32/36, 88.9%) and nine (9/9, 100.0%) subjects, respectively, in the DNA vaccine and placebo group. The frequency of solicited AEs did not increase with vaccine dose level and frequency. The DNA vaccine pGX9501 effectively enhanced both humoral and cellular immune responses in a dose-dependent manner, with increased antibody GMTs and peak seroconversion rates observed on day 42. The significant rise in IFN-γ levels confirmed the vaccine’s ability to induce cellular immune responses. Variations in the microbiome structure suggested a tangible impact of the gut microbiota on vaccine immunogenicity. Conclusions: The findings from this study confirm the immunogenicity and safety of the DNA vaccine pGX9501 and point to the potential role of the gut microbiota in vaccine immune responses. These insights provide practical references for the future design and development of DNA vaccines.