Helicobacter pylori (H. pylori) is an infectious bacterium that colonizes the stomach of approximately half of the global population. It has been classified as a Group I carcinogen by the World Health Organization due to its strong association with an increased incidence of gastric cancer and exacerbation of stomach diseases. The primary treatment for H. pylori infection currently involves triple or quadruple therapy, primarily consisting of antibiotics and proton pump inhibitors. However, the increasing prevalence of antibiotic resistance poses significant challenges to this approach, underscoring the urgent need for an effective vaccine. In this study, a novel multi-epitope H. pylori vaccine was designed using immunoinformatics. The vaccine contains epitopes derived from nine essential proteins. Software tools and online servers were utilized to predict, evaluate, and analyze the physiochemical properties, secondary and tertiary structures, and immunogenicity of the candidate vaccine. These comprehensive assessments ultimately led to the formulation of an optimal design scheme for the vaccine. Through constructing a novel multi-epitope vaccine based on immunoinformatics, this study offers promising prospects and great potential for the prevention of H. pylori infection. This study also provides a reference strategy to develop multi-epitope vaccines for other pathogens.

Tuberculosis (TB) remains one of the gravest global health challenges. Mycobacterium tuberculosis (M. tuberculosis), the causative agent, employs sophisticated immune evasion and pathogenesis strategies. Its capability to thrive within immune cells and incite robust inflammatory responses prolongs infection and dissemination. Mycobacterial advanced adaptations facilitate navigation through the human immune system and present a variable antigenic profile throughout different infection stages. Investigating these strategies unfolds targeted approaches to effective vaccine development against TB. This review delves into the most advanced and exhaustive insights into the immune evasion tactics and pathogenic processes of M. tuberculosis across various infection stages. The knowledge distilled from this analysis holds the promise of guiding the creation of innovative TB vaccines and translating theoretical groundwork into practical immunological defenses.

The global burden of tuberculosis (TB), exacerbated by the rise of drug-resistant Mycobacterium tuberculosis (M. tuberculosis), underscores the need for alternative intervention strategies. One promising approach is to block the infection at its earliest stage—bacterial adhesion to host cells—thereby preventing colonization and transmission without exerting selective pressure. Adhesins, surface-exposed molecules mediating this critical interaction, have therefore emerged as attractive targets for early prevention. This review outlines the infection process driven by bacterial adhesion and describes the architecture of the M. tuberculosis outer envelope, emphasizing components that contribute to host interaction. We comprehensively summarize both non-protein and protein adhesins, detailing their host receptors, biological roles, and experimental evidence. Recent progress in the computational prediction of adhesins, particularly neural network-based tools like SPAAN, is also discussed, highlighting its potential to accelerate adhesin discovery. Additionally, we present a detailed, generalized workflow for predicting M. tuberculosis adhesins, which synthesizes current approaches and provides a comprehensive framework for future studies. Targeting bacterial adhesion presents a therapeutic strategy that interferes with the early stages of infection while minimizing the risk of developing drug resistance. Consequently, anti-adhesion strategies may serve as valuable complements to conventional therapies and support the development of next-generation TB vaccines and treatments.

Introduction: Adhesion to host cells is the first and essential step in Mycobacterium tuberculosis ( M. tuberculosis ) infection. Among adhesion molecules, the PGRS domain of PE_PGRS33 plays a critical role in invasion but is dominated by B cell epitopes and lacks sufficient T cell epitopes, restricting its capacity to induce a balanced immune response. Methods: To overcome this limitation, we employed an integrative reverse vaccinology pipeline combining computational prediction and experimental validation. Helper and cytotoxic T lymphocyte epitopes were incorporated from multiple M. tuberculosis adhesins as well as other virulence-associated proteins, and adjuvant sequences were systematically evaluated in silico. Results: Among three multi-epitope constructs, the Toll-like receptor 2 (TLR2)-agonist and pan HLA DR-binding epitope (PADRE)-adjuvanted vaccine (TLR2-vaccine) emerged as the most promising candidate. In murine models, TLR2-vaccine induced strong antigen-specific antibody and IFN-γ responses, significantly reduced bacterial loads following H37Ra challenge, and effectively prevented extrapulmonary dissemination. Discussion: These findings highlight the potential of adhesin-inclusive multi-epitope vaccines to elicit both humoral and cellular immunity and demonstrate how computational vaccinology can accelerate the development of targeted interventions against tuberculosis.

Helicobacter pylori (Hp) is a major pathogenic bacterium responsible for gastritis, peptic ulcers, and gastric cancer. The prevention and control of Hp infection pose significant global health challenges, particularly due to the rising antibiotic resistance alongside the current absence of an effective vaccine. This review synthesizes the key elements governing successful model establishment, including strain characteristics, animal host species selection, pre-treatment methods, and infection protocols. It further elaborates on the methods for detecting and quantifying Hp in animal models, including invasive and non-invasive detection techniques for model validation, and explores the potential applications of spatial transcriptomics in this field. Furthermore, the review outlines current progress and limitations in Hp infection modeling. Aimed at supporting preclinical research, this review serves as a practical reference for establishing stable and reproducible animal models that mimic human infection and disease progression, thereby facilitating the evaluation of novel therapeutics and vaccine candidates.