This study investigates the epidemic trend of pyrazinamide (PZA)-resistant tuberculosis in Southern China over 11 years (2012–2022) and evaluates the mutation characteristics of PZA resistance-related genes (pncA, rpsA, and panD) in clinical Mycobacterium tuberculosis (M. tuberculosis) isolates. To fulfil these goals, we analyzed the phenotypic PZA resistance characteristics of 14,927 clinical isolates for which Bactec MGIT 960 PZA drug susceptibility testing (DST) results were available, revealing that 2,054 (13.76%) isolates were resistant to PZA. After evaluating the annual variation in the PZA resistance rate among tuberculosis cases in this region, it was observed that it decreased from 37.21% to 6.45% throughout the initial 7 years (2012–2018) and then increased from 8.01% to 12.12% over the subsequent 4 years (2019–2022). Sequences of pncA were obtained from 402 clinical M. tuberculosis complex isolates. For rpsA and panD, sequences were obtained from 360 clinical M. tuberculosis complex isolates. Mutations in pncA were found in 8 out of 223 PZA-sensitive isolates (3.59%) and 105 of 179 (58.66%) PZA-resistant isolates. Conversely, non-synonymous mutations in rpsA were identified in 5 of 137 (3.65%) PZA-resistant isolates, whereas the mutation ratio of rpsA among PZA-sensitive isolates was high at 14.03% (31/221). This difference in the rpsA mutation rate was statistically significant (P = 0.001, chi-square test). No panD mutations were observed in the 137 PZA-resistant isolates, whereas two PZA-sensitive isolates harboured point mutations in panD, including one nonsense mutation (C433 T) and another C-69 T mutation. These findings indicate that rpsA and panD may not significantly contribute to the development of PZA resistance in clinical M. tuberculosis isolates.

This study investigates the epidemic trend of pyrazinamide (PZA)-resistant tuberculosis in Southern China over 11 years (2012–2022) and evaluates the mutation characteristics of PZA resistance-related genes (pncA, rpsA, and panD) in clinical Mycobacterium tuberculosis (M. tuberculosis) isolates. To fulfil these goals, we analyzed the phenotypic PZA resistance characteristics of 14,927 clinical isolates for which Bactec MGIT 960 PZA drug susceptibility testing (DST) results were available, revealing that 2,054 (13.76%) isolates were resistant to PZA. After evaluating the annual variation in the PZA resistance rate among tuberculosis cases in this region, it was observed that it decreased from 37.21% to 6.45% throughout the initial 7 years (2012–2018) and then increased from 8.01% to 12.12% over the subsequent 4 years (2019–2022). Sequences of pncA were obtained from 402 clinical M. tuberculosis complex isolates. For rpsA and panD, sequences were obtained from 360 clinical M. tuberculosis complex isolates. Mutations in pncA were found in 8 out of 223 PZA-sensitive isolates (3.59%) and 105 of 179 (58.66%) PZA-resistant isolates. Conversely, non-synonymous mutations in rpsA were identified in 5 of 137 (3.65%) PZA-resistant isolates, whereas the mutation ratio of rpsA among PZA-sensitive isolates was high at 14.03% (31/221). This difference in the rpsA mutation rate was statistically significant (P = 0.001, chi-square test). No panD mutations were observed in the 137 PZA-resistant isolates, whereas two PZA-sensitive isolates harboured point mutations in panD, including one nonsense mutation (C433 T) and another C-69 T mutation. These findings indicate that rpsA and panD may not significantly contribute to the development of PZA resistance in clinical M. tuberculosis isolates.

Objective: Most research reports on COVID-19 infections have focused on thecorrelation between the severity of the disease symptoms and immune deficits,while the mechanisms affecting the susceptibility to SARS-CoV-2 remain largelyunknown. The study aimed to comprehensively analyze the differences inimmunity, gut microbiota, metabolism, and proteomics between the SARS-CoV-2 resistant population and susceptible population.Methods and results: In this cohort comparison study, participants wererigorously selected based on inclusion and exclusion criteria in a continuousenrollment manner through continuous enrollment using combinedquestionnaires and clinical data, ultimately including 25 SARS-CoV-2 resistantvolunteers versus 16 SARS-CoV-2 infected patients. The clinical informationof the participants was recorded in detail, and fecal and blood samples werecollected in a standardized manner for subsequent multi omics analysis,including gut microbiota sequencing, metabolomics, and proteomics. Thisstudy has preliminarily elucidated the characteristics of the gut microbiota,serum metabolites, and serum proteins in the SARS-CoV-2 resistant population.It exhibits a unique metabolic signature characterized by elevated levels ofserum phosphatidylinositol and the abundance of Prevotella, which may serveas a potential predictive biomarker for resistance to SARS-CoV-2.Conclusion: Given the crucial role of phosphatidylinositol in cell membranearchitecture and viral infectivity, this study provides a promising entry point forfurther research into the pathogenesis and prevention strategies of COVID-19.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

Objective: Most research reports on COVID-19 infections have focused on thecorrelation between the severity of the disease symptoms and immune deficits,while the mechanisms affecting the susceptibility to SARS-CoV-2 remain largelyunknown. The study aimed to comprehensively analyze the differences inimmunity, gut microbiota, metabolism, and proteomics between the SARS-CoV-2 resistant population and susceptible population.Methods and results: In this cohort comparison study, participants wererigorously selected based on inclusion and exclusion criteria in a continuousenrollment manner through continuous enrollment using combinedquestionnaires and clinical data, ultimately including 25 SARS-CoV-2 resistantvolunteers versus 16 SARS-CoV-2 infected patients. The clinical informationof the participants was recorded in detail, and fecal and blood samples werecollected in a standardized manner for subsequent multi omics analysis,including gut microbiota sequencing, metabolomics, and proteomics. Thisstudy has preliminarily elucidated the characteristics of the gut microbiota,serum metabolites, and serum proteins in the SARS-CoV-2 resistant population.It exhibits a unique metabolic signature characterized by elevated levels ofserum phosphatidylinositol and the abundance of Prevotella, which may serveas a potential predictive biomarker for resistance to SARS-CoV-2.Conclusion: Given the crucial role of phosphatidylinositol in cell membranearchitecture and viral infectivity, this study provides a promising entry point forfurther research into the pathogenesis and prevention strategies of COVID-19.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.