Metabolic analyses reveal common adaptations in two invasive Haemophilus influenzae strains

Non-typeable Haemophilus influenzae (NTHi) is a major pathogen in upper and lower respiratory tract infections in humans, and is increasingly also associated with invasive disease. We have examined two unrelated NTHi invasive disease isolates, R2866 and C188, in order to identify metabolic and physiological properties that distinguish them from respiratory tract disease isolates such as Hi2019. While the general use of the Hi metabolic network was similar across all three strains, the two invasive isolates secreted increased amounts of succinate which can have anti-inflammatory properties. In addition, they showed a common shift in their carbon source utilization patterns, with strongly enhanced metabolism of nucleoside substrates, glucose and sialic acid. The latter two are major compounds present in blood and CSF. Interestingly, C188 and R2866 also shared a reduced ability to invade or survive intracellularly in 16HBE14 bronchial epithelial cells relative to Hi2019 (4-fold (4 h), 25-fold (24 h) reduction). Altered metabolic properties such as the ones observed here could arise from genomic adaptations that NTHi undergo during infection. Together these data indicate that shifts in substrate preferences in otherwise conserved metabolic pathways may underlie strain niche specificity and thus have the potential to alter the outcomes of host-NTHi interactions

Random amplified polymorphism DNA profile of Listeria monocytogenes from raw and ready-to-eat foods in Malaysia

Listeria monocytogenes subtyping is important in food processing environment or in epidemiological studies in order to identify the contamination sources and spreading routes, and to investigate the food-borne outbreaks. This study employs the combination of serotyping and random amplified polymorphism DNA (RAPD) analysis methods to characterize the isolated L. monocytogenes strains in food samples from local markets. Listeria antisera kit was used in serotyping which grouped L. monocytogenes isolates based on the expression of somatic and flagellar antigens. The L. monocytogenes serovars were further classified into RAPD types based on polymorphic banding patterns generated by using 10 random RAPD primers. The 23 isolated strains were divided into four different serotypes consisting 4b (43.5%), 1/2b (34.8%), 4d (8.70%) and 4e (4.35%) with two untypable isolates (8.70%). 11 banding patterns were obtained from each selected primer, OPA10 and OPA14 with DNA fragments ranging from approximately 0.15 kb to 1.1 kb. The constructed dendograms showed similarity percentage of 4% to 100% for OPA10, 12% to 100% for OPA14 and 4% to 100% for combination of primers. At a comparative genetic similarity of more than 90%, 21 distinguish RAPD profiles were obtained. The discriminatory of RAPD analysis method was proven as it could distinguish the isolates from the same serovar. However, between the two primers used, OPA14 provide better discriminatory results than OPA10 although it failed to type one isolate. These findings suggest that the application of RAPD analysis could be a useful tool in characterization of L. monocytogenes isolated from foods as it may provide important information on cross-contamination potential sites. Thus, the microbial monitoring should be applied and continuously performed in order to control listeriosis infection. The data may be useful for the food producers or epidemiological and public health studies of Listeria spp