Balance between Protection and Pathogenic Response to Aerosol Challenge with Mycobacterium tuberculosis (Mtb) in Mice Vaccinated with TriFu64, a Fusion Consisting of Three Mtb Antigens.
Sadaf SulmanBenjamin O SavidgeKawther AlqaseerMrinal K DasNeda Nezam AbadiJohn E PearlObolbek TurapovGalina V MukamolovaM Waheed AkhtarAndrea May CooperPublished in: Vaccines (2021)
Tuberculosis vaccines capable of reducing disease worldwide have proven difficult to develop. BCG is effective in limiting childhood disease, but adult TB is still a major public health issue. Development of new vaccines requires identification of antigens that are both spatially and temporally available throughout infection, and immune responses to which reduce bacterial burden without increasing pathologic outcomes. Subunit vaccines containing antigen require adjuvants to drive appropriate long-lived responses. We generated a triple-antigen fusion containing the virulence-associated EsxN (Rv1793), the PPE42 (Rv2608), and the latency associated Rv2628 to investigate the balance between bacterial reduction and weight loss in an animal model of aerosol infection. We found that in both a low pattern recognition receptor (PRR) engaging adjuvant and a high PRR-engaging adjuvant (MPL/TDM/DDA) the triple-antigen fusion could reduce the bacterial burden, but also induced weight loss in the mice upon aerosol infection. The weight loss was associated with an imbalance between TNFα and IL-17 transcription in the lung upon challenge. These data indicate the need to assess both protective and pathogenic responses when investigating subunit vaccine activity.
Keyphrases
- mycobacterium tuberculosis
- weight loss
- pulmonary tuberculosis
- bariatric surgery
- public health
- roux en y gastric bypass
- immune response
- gastric bypass
- early stage
- dendritic cells
- escherichia coli
- water soluble
- rheumatoid arthritis
- neoadjuvant chemotherapy
- high fat diet induced
- pseudomonas aeruginosa
- emergency department
- staphylococcus aureus
- glycemic control
- squamous cell carcinoma
- type diabetes
- metabolic syndrome
- antimicrobial resistance
- biofilm formation
- childhood cancer
- obese patients
- inflammatory response
- weight gain
- locally advanced
- big data
- deep learning
- hiv aids
- insulin resistance
- drug induced
- physical activity
- machine learning
- skeletal muscle
- endothelial cells