Eukaryotic Protein Kinases (ePKs) of the Helminth Parasite Schistosoma mansoni

<p>Abstract</p> <p>Background</p> <p>Schistosomiasis remains an important parasitic disease and a major economic problem in many countries. The <it>Schistosoma mansoni </it>genome and predicted proteome sequences were recently published providing the opportunity to identify new drug candidates. Eukaryotic protein kinases (ePKs) play a central role in mediating signal transduction through complex networks and are considered druggable targets from the medical and chemical viewpoints. Our work aimed at analyzing the <it>S. mansoni </it>predicted proteome in order to identify and classify all ePKs of this parasite through combined computational approaches. Functional annotation was performed mainly to yield insights into the parasite signaling processes relevant to its complex lifestyle and to select some ePKs as potential drug targets.</p> <p>Results</p> <p>We have identified 252 ePKs, which corresponds to 1.9% of the <it>S. mansoni </it>predicted proteome, through sequence similarity searches using HMMs (Hidden Markov Models). Amino acid sequences corresponding to the conserved catalytic domain of ePKs were aligned by MAFFT and further used in distance-based phylogenetic analysis as implemented in PHYLIP. Our analysis also included the ePK homologs from six other eukaryotes. The results show that <it>S. mansoni </it>has proteins in all ePK groups. Most of them are clearly clustered with known ePKs in other eukaryotes according to the phylogenetic analysis. None of the ePKs are exclusively found in <it>S. mansoni </it>or belong to an expanded family in this parasite. Only 16 <it>S. mansoni </it>ePKs were experimentally studied, 12 proteins are predicted to be catalytically inactive and approximately 2% of the parasite ePKs remain unclassified. Some proteins were mentioned as good target for drug development since they have a predicted essential function for the parasite.</p> <p>Conclusions</p> <p>Our approach has improved the functional annotation of 40% of <it>S. mansoni </it>ePKs through combined similarity and phylogenetic-based approaches. As we continue this work, we will highlight the biochemical and physiological adaptations of <it>S. mansoni </it>in response to diverse environments during the parasite development, vector interaction, and host infection.</p

Minocycline and the SPR741 Adjuvant Are an Efficacious Antibacterial Combination for Acinetobacter baumannii Infections

Antibiotic resistance, when it comes to bacterial infections, is not a problem that is going to disappear anytime soon. With the lack of larger investment in novel antibiotic research and the ever-growing increase of resistant isolates amongst the ESKAPEE pathogens (Enterobacter cloacae, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterococcus sp., and Escherichia coli), it is inevitable that more and more infections caused by extensively drug-resistant (XDR) and pandrug-resistant (PDR) strains will arise. One strategy to counteract the growing threat is to use antibiotic adjuvants, a drug class that on its own lacks significant antibiotic activity, but when mixed with another antibiotic, can potentiate increased killing of bacteria. Antibiotic adjuvants have various mechanisms of action, but polymyxins and polymyxin-like molecules can disrupt the Gram-negative outer membrane and allow other drugs better penetration into the bacterial periplasm and cytoplasm. Previously, we showed that SPR741 had this adjuvant effect with regard to rifampin; however, rifampin is often not used clinically because of easily acquired resistance. To find additional, appropriate clinical partners for SPR741 with respect to pulmonary and wound infections, we investigated tetracyclines and found a previously undocumented synergy with minocycline in vitro and in vivo in murine models of infection

Optomagnetic Imaging Spectroscopy (OMIS) for in situ detection of bacteria in blood – feasibility study

Introduction: Sepsis is one of the leading causes of death in military and civilian hospitals. Rapid identification of involved pathogens is a key step for appropriate diagnosis, treatment and ultimately survival. Current diagnostics tools are either very bulky and not deployment ready, or require a long time to provide results. Given these obstacles, new solutions are urgently needed. Optomagnetic Imaging Spectroscopy (OMIS) is novel technology successfully used for the detection of cancer cells and viruses. OMIS has high sensitivity due to recording the unpaired and paired electrons of sample material. Furthermore, machine learning that uses the algorithms random forest (RF) classifier and artificial neural network (ANN) is integrated into the technology to enhance detection. Here we evaluated the feasibility of OMIS for the detection of bacteria in blood. Methods: We used commercially available human blood spiked with a defined concentration multidrug resistant Staphylococcus aureus derived from a clinical isolate. Final concentrations of bacteria of 1 × 106, 1 × 105 and 1 × 104 CFU/mL corresponding to High (H), Medium (M) and Low (L) concentrations respectively. A total of 240 samples (60 samples per concentration as well as 60 samples of sterile blood (N)) was imaged, and the data were analyzed using random forest classifier and artificial neural network. Images for the training set and validation sets were separately obtained and used for comparison against true positive values (confirmatory plating on the nutrient agar). Results: The average score of classification samples in the correct category (N, L, M, H) one-by-one was 94% for the ANN algorithm, while for the RF algorithm accuracy was 93% (average means that three times different 40 samples (of 240 samples) were chosen, and each prediction test had different sample mixtures). The closeness of the two values of accuracy strongly indicates that the input data (interaction of light with paired and unpaired electrons) and output data (classification N, L, M, H concentration of bacteria) are correlated

Design of a Bacteriophage Cocktail Active against Shigella Species and Testing of Its Therapeutic Potential in Galleria mellonella

Shigellosis is a leading global cause of diarrheal disease and travelers&rsquo; diarrhea now being complicated by the dissemination of antibiotic resistance, necessitating the development of alternative antibacterials such as therapeutic bacteriophages (phages). Phages with lytic activity against Shigella strains were isolated from sewage. The genomes of 32 phages were sequenced, and based on genomic comparisons belong to seven taxonomic genera: Teetrevirus, Teseptimavirus, Kayfunavirus, Tequatrovirus, Mooglevirus, Mosigvirus and Hanrivervirus. Phage host ranges were determined with a diverse panel of 95 clinical isolates of Shigella from Southeast Asia and other geographic regions, representing different species and serotypes. Three-phage mixtures were designed, with one possessing lytic activity against 89% of the strain panel. This cocktail exhibited lytic activity against 100% of S. sonnei isolates, 97.2% of S. flexneri (multiple serotypes) and 100% of S. dysenteriae serotypes 1 and 2. Another 3-phage cocktail composed of two myophages and one podophage showed both a broad host range and the ability to completely sterilize liquid culture of a model virulent strain S. flexneri 2457T. In a Galleria mellonella model of lethal infection with S. flexneri 2457T, this 3-phage cocktail provided a significant increase in survival

Antimicrobial resistance in Africa: a systematic review

Background: Antimicrobial resistance (AMR) is widely acknowledged as a global problem, yet in many parts of the world its magnitude is still not well understood. This review, using a public health focused approach, aimed to understand and describe the current status of AMR in Africa in relation to common causes of infections and drugs recommended in WHO treatment guidelines. Methods: PubMed, EMBASE and other relevant databases were searched for recent articles (2013–2016) in accordance with the PRISMA guidelines. Article retrieval and screening were done using a structured search string and strict inclusion/exclusion criteria. Median and interquartile ranges of percent resistance were calculated for each antibiotic-bacterium combination. Results: AMR data was not available for 42.6% of the countries in the African continent. A total of 144 articles were included in the final analysis. 13 Gram negative and 5 Gram positive bacteria were tested against 37 different antibiotics. Penicillin resistance in Streptococcus pneumoniae was reported in 14/144studies (median resistance (MR): 26.7%). Further 18/53 (34.0%) of Haemophilus influenza isolates were resistant to amoxicillin. MR of Escherichia coli to amoxicillin, trimethoprim and gentamicin was 88.1%, 80.7% and 29.8% respectively. Ciprofloxacin resistance in Salmonella Typhi was rare. No documented ceftriaxone resistance in Neisseria gonorrhoeae was reported, while the MR for quinolone was 37.5%. Carbapenem resistance was common in Acinetobacter spp. and Pseudomonas aeruginosa but uncommon in Enterobacteriaceae. Conclusion: Our review highlights three important findings. First, recent AMR data is not available for more than 40% of the countries. Second, the level of resistance to commonly prescribed antibiotics was significant. Third, the quality of microbiological data is of serious concern. Our findings underline that to conserve our current arsenal of antibiotics it is imperative to address the gaps in AMR diagnostic standardization and reporting and use available information to optimize treatment guidelines.</p