| 1. |
|
|
| 2. |
|
|
| 3. |
- Engström, Patrik, 1982-, et al.
(författare)
-
Mutations in hemG Mediate Resistance to Salicylidene Acylhydrazides, Demonstrating a Novel Link between Protoporphyrinogen Oxidase (HemG) and Chlamydia trachomatis Infectivity
- 2013
-
Ingår i: Journal of Bacteriology. - Washington DC, USA : American Society for Microbiology. - 0021-9193 .- 1098-5530. ; 195:18, s. 4221-4230
-
Tidskriftsartikel (refereegranskat)abstract
- Salicylidene acylhydrazides (SAHs) inhibit the type III secretion system (T3S) of Yersinia and other Gram-negative bacteria. In addition, SAHs restrict the growth and development of Chlamydia species. However, since the inhibition of Chlamydia growth by SAH is suppressed by the addition of excess iron and since SAHs have an iron-chelating capacity, their role as specific T3S inhibitors is unclear. We investigated here whether SAHs exhibit a function on C. trachomatis that goes beyond iron chelation. We found that the iron-saturated SAH INP0341 (IS-INP0341) specifically affects C. trachomatis infectivity with reduced generation of infectious elementary body (EB) progeny. Selection and isolation of spontaneous SAH-resistant mutant strains revealed that mutations in hemG suppressed the reduced infectivity caused by IS-INP0341 treatment. Structural modeling of C. trachomatis HemG predicts that the acquired mutations are located in the active site of the enzyme, suggesting that IS-INP0341 inhibits this domain of HemG and that protoporphyrinogen oxidase (HemG) and heme metabolism are important for C. trachomatis infectivity.
|
|
| 4. |
- Mojica, Sergio A., et al.
(författare)
-
N-acylated derivatives of sulfamethoxazole block Chlamydia fatty acid synthesis and interact with FabF
- 2017
-
Ingår i: Antimicrobial Agents and Chemotherapy. - : American society for microbiology. - 0066-4804 .- 1098-6596. ; 61:10
-
Tidskriftsartikel (refereegranskat)abstract
- The type II fatty acid synthesis (FASII) pathway is essential for bacterial lipid biosynthesis and continues to be a promising target for novel antibacterial compounds. Recently, it has been demonstrated that Chlamydia is capable of FASII and this pathway is indispensable for Chlamydia growth. Previously, a high-content screen with Chlamydia trachomatis-infected cells was performed, and acylated sulfonamides were identified to be potent growth inhibitors of the bacteria. C. trachomatis strains resistant to acylated sulfonamides were isolated by serial passage of a wild-type strain in the presence of low compound concentrations. Results from whole-genome sequencing of 10 isolates from two independent drug-resistant populations revealed that mutations that accumulated in fabF were predominant. Studies of the interaction between the FabF protein and small molecules showed that acylated sulfonamides directly bind to recombinant FabF in vitro and treatment of C. trachomatis-infected HeLa cells with the compounds leads to a decrease in the synthesis of Chlamydia fatty acids. This work demonstrates the importance of FASII for Chlamydia development and may lead to the development of new antimicrobials.
|
|
| 5. |
- Zalakeviciute, R., et al.
(författare)
-
A Traffic-based method to predict and map urban air quality
- 2020
-
Ingår i: Applied Sciences (Switzerland). - : MDPI. - 2076-3417. ; 10:6
-
Tidskriftsartikel (refereegranskat)abstract
- As global urbanization, industrialization, and motorization keep worsening air quality, a continuous rise in health problems is projected. Limited spatial resolution of the information on air quality inhibits full comprehension of urban population exposure. Therefore, we propose a method to predict urban air pollution from traffic by extracting data from Web-based applications (Google Traffic). We apply a machine learning approach by training a decision tree algorithm (C4.8) to predict the concentration of PM2.5 during the morning pollution peak from: (i) an interpolation (inverse distance weighting) of the value registered at the monitoring stations, (ii) traffic flow, and (iii) traffic flow + time of the day. The results show that the prediction from traffic outperforms the one provided by the monitoring network (average of 65.5% for the former vs. 57% for the latter). Adding the time of day increases the accuracy by an average of 6.5%. Considering the good accuracy on different days, the proposed method seems to be robust enough to create general models able to predict air pollution from traffic conditions. This affordable method, although beneficial for any city, is particularly relevant for low-income countries, because it offers an economically sustainable technique to address air quality issues faced by the developing world.
|
|
