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Introduction: The environmental bacterium Burkholderia pseudomallei causes the often fatal and massively underreported infectious disease melioidosis. Antigens inducing protective immunity in experimental models have recently been identified and serodiagnostic tools have been improved. However, further elucidation of the antigenic repertoire of B. pseudomallei during human infection for diagnostic and vaccine purposes is required. The adaptation of B. pseudomallei to very different habitats is reflected by a huge genome and a selective transcriptional response to a variety of conditions. We, therefore, hypothesized that exposure of B. pseudomallei to culture conditions mimicking habitats encountered in the human host might unravel novel antigens that are recognized by melioidosis patients.
Methods and results: In this study, B. pseudomallei was exposed to various stress and growth conditions, including anaerobiosis, acid stress, oxidative stress, iron starvation and osmotic stress. Immunogenic proteins were identified by probing two-dimensional Western blots of B. pseudomallei intracellular and extracellular protein extracts with sera from melioidosis patients and controls and subsequent MALDI-TOF MS. Among B. pseudomallei specific immunogenic signals, 90 % (55/61) of extracellular immunogenic proteins were identified by acid, osmotic or oxidative stress. A total of 84 % (44/52) of intracellular antigens originated from the stationary growth phase, acidic, oxidative and anaerobic conditions. The majority of the extracellular and intracellular protein antigens were identified in only one of the various stress conditions. Sixty-three immunoreactive proteins and an additional 38 candidates from a literature screening were heterologously expressed and subjected to dot blot analysis using melioidosis sera and controls. Our experiments confirmed melioidosis-specific signals in 58 of our immunoproteome candidates. These include 15 antigens with average signal ratios (melioidosis:controls) greater than 10 and another 26 with average ratios greater than 5, including new promising serodiagnostic candidates with a very high signal-to-noise ratio.
Conclusion: Our study shows that a comprehensive B. pseudomallei immunoproteomics approach, using conditions which are likely to be encountered during infection, can identify novel antibody targets previously unrecognized in human melioidosis.
Analysis of volatile organic compounds (VOCs) is a novel approach to accelerate bacterial culture diagnostics of Mycobacterium avium subsp. paratuberculosis (MAP). In the present study, cultures of fecal and tissue samples from MAP-infected and non-suspect dairy cattle and goats were explored to elucidate the effects of sample matrix and of animal species on VOC emissions during bacterial cultivation and to identify early markers for bacterial growth. The samples were processed following standard laboratory procedures, culture tubes were incubated for different time periods. Headspace volume of the tubes was sampled by needle trap-micro-extraction, and analyzed by gas chromatography-mass spectrometry. Analysis of MAP-specific VOC emissions considered potential characteristic VOC patterns. To address variation of the patterns, a flexible and robust machine learning workflow was set up, based on random forest classifiers, and comprising three steps: variable selection, parameter optimization, and classification. Only a few substances originated either from a certain matrix or could be assigned to one animal species. These additional emissions were not considered informative by the variable selection procedure. Classification accuracy of MAP-positive and negative cultures of bovine feces was 0.98 and of caprine feces 0.88, respectively. Six compounds indicating MAP presence were selected in all four settings (cattle vs. goat, feces vs. tissue): 2-Methyl-1-propanol, 2-methyl-1-butanol, 3-methyl-1-butanol, heptanal, isoprene, and 2-heptanone. Classification accuracies for MAP growth-scores ranged from 0.82 for goat tissue to 0.89 for cattle feces. Misclassification occurred predominantly between related scores. Seventeen compounds indicating MAP growth were selected in all four settings, including the 6 compounds indicating MAP presence. The concentration levels of 2,3,5-trimethylfuran, 2-pentylfuran, 1-propanol, and 1-hexanol were indicative for MAP cultures before visible growth was apparent. Thus, very accurate classification of the VOC samples was achieved and the potential of VOC analysis to detect bacterial growth before colonies become visible was confirmed. These results indicate that diagnosis of paratuberculosis can be optimized by monitoring VOC emissions of bacterial cultures. Further validation studies are needed to increase the robustness of indicative VOC patterns for early MAP growth as a pre-requisite for the development of VOC-based diagnostic analysis systems.
Global and even national genome surveillance approaches do not provide the resolution necessary for rapid and accurate direct response by local public health authorities. Hence, a regional network of microbiological laboratories in collaboration with the health departments of all districts of the German federal state of Mecklenburg-Western Pomerania (M-V) was formed to investigate the regional molecular epidemiology of circulating SARS-CoV-2 lineages between 11/2020 and 03/2022. More than 4750 samples from all M-V counties were sequenced using Illumina and Nanopore technologies. Overall, 3493 (73.5%) sequences fulfilled quality criteria for time-resolved and/or spatially-resolved maximum likelihood phylogenic analyses and k-mean/ median clustering (KMC). We identified 116 different Pangolin virus lineages that can be assigned to 16 Nextstrain clades. The ten most frequently detected virus lineages belonged to B.1.1.7, AY.122, AY.43, BA.1, B.1.617.2, BA.1.1, AY.9.2, AY.4, P.1 and AY.126. Time-resolved phylogenetic analyses showed the occurrence of virus clades as determined worldwide, but with a substantial delay of one to two months. Further spatio-temporal phylogenetic analyses revealed a regional outbreak of a Gamma variant limited to western M-V counties. Finally, KMC elucidated a successive introduction of the various virus lineages into M-V, possibly triggered by vacation periods with increased (inter-) national travel activities. The COVID-19 pandemic in M-V was shaped by a combination of several SARS-CoV-2 introductions, lockdown measures, restrictive quarantine of patients and the lineage specific replication rate. Complementing global and national surveillance, regional surveillance adds value by providing a higher level of surveillance resolution tailored to local health authorities.