The oxidative stress response of Streptococcus pneumoniae: its contribution to both extracellular and intracellular survival.

Streptococcus pneumoniae is a gram-positive, aerotolerant bacterium that naturally colonizes the human nasopharynx, but also causes invasive infections and is a major cause of morbidity and mortality worldwide. This pathogen produces high levels of H2O2 to eliminate other microorganisms that belong to the microbiota of the respiratory tract. However, it also induces an oxidative stress response to survive under this stressful condition. Furthermore, this self-defense mechanism is advantageous in tolerating oxidative stress imposed by the host's immune response. This review provides a comprehensive overview of the strategies employed by the pneumococcus to survive oxidative stress. These strategies encompass the utilization of H2O2 scavengers and thioredoxins, the adaptive response to antimicrobial host oxidants, the regulation of manganese and iron homeostasis, and the intricate regulatory networks that control the stress response. Here, we have also summarized less explored aspects such as the involvement of reparation systems and polyamine metabolism. A particular emphasis is put on the role of the oxidative stress response during the transient intracellular life of Streptococcus pneumoniae, including coinfection with influenza A and the induction of antibiotic persistence in host cells.

Host Cell Oxidative Stress Promotes Intracellular Fluoroquinolone Persisters of Streptococcus pneumoniae.

Bacterial persisters represent a small subpopulation that tolerates high antibiotic concentrations without acquiring heritable resistance, and it may be generated by environmental factors. Here, we report the first antibiotic persistence mechanism in Streptococcus pneumoniae, which is induced by oxidative stress conditions and allows the pneumococcus to survive in the presence of fluoroquinolones. We demonstrated that fluoroquinolone persistence is prompted by both the impact of growth arrest and the oxidative stress response induced by H2O2 in bacterial cells. This process protected pneumococci against the deleterious effects of high ROS levels induced by fluoroquinolones. Importantly, S. pneumoniae develops persistence during infection, and is dependent on the oxidative stress status of the host cells, indicating that its transient intracellular life contributes to this mechanism. Furthermore, our findings suggest persistence may influence the outcome of antibiotic therapy and be part of a multistep mechanism in the evolution of fluoroquinolone resistance. IMPORTANCE In S. pneumoniae, different mechanisms that counteract antibiotic effects have been described, such as vancomycin tolerance, heteroresistance to penicillin and fluoroquinolone resistance, which critically affect the therapeutic efficacy. Antibiotic persistence is a type of antibiotic tolerance that allows a bacterial subpopulation to survive lethal antimicrobial concentrations. In this work, we used a host-cell infection model to reveal fluoroquinolone persistence in S. pneumoniae. This mechanism is induced by oxidative stress that the pneumococcus must overcome to survive in host cells. Many fluoroquinolones, such as levofloxacin and moxifloxacin, have a broad spectrum of activity against bacterial pathogens of community-acquired pneumonia, and they are used to treat pneumococcal diseases. However, the emergence of fluoroquinolone-resistant strains complicates antibiotic treatment of invasive infections. Consequently, antibiotic persistence in S. pneumoniae is clinically relevant due to prolonged exposure to fluoroquinolones likely favors the acquisition of mutations that generate antibiotic resistance in persisters. In addition, this work contributes to the knowledge of antibiotic persistence mechanisms in bacteria.

Phylogenetic analysis and comparative genomics of SARS-CoV-2 from survivor and non-survivor COVID-19 patients in Cordoba, Argentina.

BACKGROUND: The SARS-CoV-2 virus is responsible for the COVID-19 pandemic. To better understand the evolution of SARS-CoV-2 early in the pandemic in the Province of Cordoba, Argentina, we performed a comparative genomic analysis of SARS-CoV-2 strains detected in survivors and non-survivors of COVID-19. We also carried out an epidemiological study to find a possible association between the symptoms and comorbidities of these patients with their clinical outcomes. RESULTS: A representative sampling was performed in different cities in the Province of Cordoba. Ten and nine complete SARS-CoV-2 genomes were obtained by next-generation sequencing of nasopharyngeal specimens from non-survivors and survivors, respectively. Phylogenetic and phylodynamic analyses revealed multiple introductions of the most common lineages in South America, including B.1, B.1.1.1, B.1.499, and N.3. Fifty-six mutations were identified, with 14% of those in common between the non-survivor and survivor groups. Specific SARS-CoV-2 mutations for survivors constituted 25% whereas for non-survivors they were 41% of the repertoire, indicating partial selectivity. The non-survivors' variants showed higher diversity in 9 genes, with a majority in Nsp3, while the survivors' variants were detected in 5 genes, with a higher incidence in the Spike protein. At least one comorbidity was present in 60% of non-survivor patients and 33% of survivors. Age 75-85 years (p = 0.018) and hospitalization (p = 0.019) were associated with non-survivor patients. Related to the most common symptoms, the prevalence of fever was similar in both groups, while dyspnea was more frequent among non-survivors and cough among survivors. CONCLUSIONS: This study describes the association of clinical characteristics with the clinical outcomes of survivors and non-survivors of COVID-19 patients, and the specific mutations found in the genome sequences of SARS-CoV-2 in each patient group. Future research on the functional characterization of novel mutations should be performed to understand the role of these variations in SARS-CoV-2 pathogenesis and COVID-19 disease outcomes. These results add new genomic data to better understand the evolution of the SARS-CoV-2 variants that spread in Argentina during the first wave of the COVID-19 pandemic.

The pneumococcal two-component system SirRH is linked to enhanced intracellular survival of Streptococcus pneumoniae in influenza-infected pulmonary cells.

The virus-bacterial synergism implicated in secondary bacterial infections caused by Streptococcus pneumoniae following infection with epidemic or pandemic influenza A virus (IAV) is well documented. However, the molecular mechanisms behind such synergism remain largely ill-defined. In pneumocytes infected with influenza A virus, subsequent infection with S. pneumoniae leads to enhanced pneumococcal intracellular survival. The pneumococcal two-component system SirRH appears essential for such enhanced survival. Through comparative transcriptomic analysis between the ΔsirR and wt strains, a list of 179 differentially expressed genes was defined. Among those, the clpL protein chaperone gene and the psaB Mn+2 transporter gene, which are involved in the stress response, are important in enhancing S. pneumoniae survival in influenza-infected cells. The ΔsirR, ΔclpL and ΔpsaB deletion mutants display increased susceptibility to acidic and oxidative stress and no enhancement of intracellular survival in IAV-infected pneumocyte cells. These results suggest that the SirRH two-component system senses IAV-induced stress conditions and controls adaptive responses that allow survival of S. pneumoniae in IAV-infected pneumocytes.

Larvicidal activity prediction against Aedes aegypti mosquito using computational tools.

BACKGROUND & OBJECTIVES: Aedes aegypti is an important vector for transmission of dengue, yellow fever, chikun- gunya, arthritis, and Zika fever. According to the World Health Organization, it is estimated that Ae. aegypti causes 50 million infections and 25,000 deaths per year. Use of larvicidal agents is one of the recommendations of health organizations to control mosquito populations and limit their distribution. The aim of present study was to deduce a mathematical model to predict the larvicidal action of chemical compounds, based on their structure. METHODS: A series of different compounds with experimental evidence of larvicidal activity were selected to develop a predictive model, using multiple linear regression and a genetic algorithm for the selection of variables, implemented in the QSARINS software. The model was assessed and validated using the OECDs principles. RESULTS: The best model showed good value for the determination coefficient (R2 = 0.752), and others parameters were appropriate for fitting (s = 0.278 and RMSEtr = 0.261). The validation results confirmed that the model hasgood robustness (Q2LOO = 0.682) and stability (R2-Q2LOO = 0.070) with low correlation between the descriptors (KXX = 0.241), an excellent predictive power (R2 ext = 0.834) and was product of a non-random correlation R2 Y-scr = 0.100). INTERPRETATION & CONCLUSION: The present model shows better parameters than the models reported earlier in the literature, using the same dataset, indicating that the proposed computational tools are more efficient in identifying novel larvicidal compounds against Ae. aegypti.