Genetic diversity and microevolution of Burkholderia pseudomallei in the environment

Background

The soil dwelling Gram-negative pathogen Burkholderia pseudomallei is the cause of melioidosis. The diversity and population structure of this organism in the environment is poorly defined.

Methods and Findings

We undertook a study of B. pseudomallei in soil sampled from 100 equally spaced points within 237.5 m² of disused land in northeast Thailand. B. pseudomallei was present on direct culture of 77/100 sampling points. Genotyping of 200 primary plate colonies from three independent sampling points was performed using a combination of pulsed field gel electrophoresis (PFGE) and multilocus sequence typing (MLST). Twelve PFGE types and nine sequence types (STs) were identified, the majority of which were present at only a single sampling point. Two sampling points contained four STs and the third point contained three STs. Although the distance between the three sampling points was low (7.6, 7.9, and 13.3 meters, respectively), only two STs were present in more than one sampling point. Each of the three samples was characterized by the localized expansion of a single B. pseudomallei clone (corresponding to STs 185, 163, and 93). Comparison of PFGE and MLST results demonstrated that two STs contained strains with variable PFGE banding pattern types, indicating geographic structuring even within a single MLST-defined clone.

Conclusions

We discuss the implications of this extreme structuring of genotype and genotypic frequency in terms of micro-evolutionary dynamics and ecology, and how our results may inform future sampling strategies.     

Development of a Prototype Lateral Flow Immunoassay (LFI) for the Rapid Diagnosis of Melioidosis

Burkholderia pseudomallei is a soil-dwelling bacterium and the causative agent of melioidosis. Isolation of B. pseudomallei from clinical samples is the “gold standard” for the diagnosis of melioidosis; results can take 3–7 days to produce. Alternatively, antibody-based tests have low specificity due to a high percentage of seropositive individuals in endemic areas. There is a clear need to develop a rapid point-of-care antigen detection assay for the diagnosis of melioidosis. Previously, we employed In vivo Microbial Antigen Discovery (InMAD) to identify potential B. pseudomallei diagnostic biomarkers. The B. pseudomallei capsular polysaccharide (CPS) and numerous protein antigens were identified as potential candidates. Here, we describe the development of a diagnostic immunoassay based on the detection of CPS. Following production of a CPS-specific monoclonal antibody (mAb), an antigen-capture immunoassay was developed to determine the concentration of CPS within a panel of melioidosis patient serum and urine samples. The same mAb was used to produce a prototype Active Melioidosis Detect Lateral Flow Immunoassay (AMD LFI); the limit of detection of the LFI for CPS is comparable to the antigen-capture immunoassay (∼0.2 ng/ml). The analytical reactivity (inclusivity) of the AMD LFI was 98.7% (76/77) when tested against a large panel of B. pseudomallei isolates. Analytical specificity (cross-reactivity) testing determined that 97.2% of B. pseudomallei near neighbor species (35/36) were not reactive. The non-reactive B. pseudomallei strain and the reactive near neighbor strain can be explained through genetic sequence analysis. Importantly, we show the AMD LFI is capable of detecting CPS in a variety of patient samples. The LFI is currently being evaluated in Thailand and Australia; the focus is to optimize and validate testing procedures on melioidosis patient samples prior to initiation of a large, multisite pre-clinical evaluation.     

NLRC4 and TLR5 Each Contribute to Host Defense in Respiratory Melioidosis

Burkholderia pseudomallei causes the tropical infection melioidosis. Pneumonia is a common manifestation of melioidosis and is associated with high mortality. Understanding the key elements of host defense is essential to developing new therapeutics for melioidosis. As a flagellated bacterium encoding type III secretion systems, B. pseudomallei may trigger numerous host pathogen recognition receptors. TLR5 is a flagellin sensor located on the plasma membrane. NLRC4, along with NAIP proteins, assembles a canonical caspase-1-dependent inflammasome in the cytoplasm that responds to flagellin (in mice) and type III secretion system components (in mice and humans). In a murine model of respiratory melioidosis, Tlr5 and Nlrc4 each contributed to survival. Mice deficient in both Tlr5 and Nlrc4 were not more susceptible than single knockout animals. Deficiency of Casp1/Casp11 resulted in impaired bacterial control in the lung and spleen; in the lung much of this effect was attributable to Nlrc4, despite relative preservation of pulmonary IL-1β production in Nlrc4^−/− mice. Histologically, deficiency of Casp1/Casp11 imparted more severe pulmonary inflammation than deficiency of Nlrc4. The human NLRC4 region polymorphism rs6757121 was associated with survival in melioidosis patients with pulmonary involvement. Co-inheritance of rs6757121 and a functional TLR5 polymorphism had an additive effect on survival. Our results show that NLRC4 and TLR5, key components of two flagellin sensing pathways, each contribute to host defense in respiratory melioidosis.     

Burkholderia pseudomallei Is Genetically Diverse in Agricultural Land in Northeast Thailand

Background

The soil-dwelling Gram-negative bacterium Burkholderia pseudomallei is the cause of melioidosis. Extreme structuring of genotype and genotypic frequency has been demonstrated for B. pseudomallei in uncultivated land, but its distribution and genetic diversity in agricultural land where most human infections are probably acquired is not well defined.

Methods

Fixed-interval soil sampling was performed in a rice paddy in northeast Thailand in which 100 grams of soil was sampled at a depth of 30 cm from 10×10 sampling points each measuring 2.5 m by 2.5 m. Soil was cultured for the presence of B. pseudomallei and genotyping of colonies present on primary culture plates was performed using a combination of pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing (MLST).

Principal Findings

B. pseudomallei was cultured from 28/100 samples. Genotyping of 630 primary colonies drawn from 11 sampling points demonstrated 10 PFGE banding pattern types, which on MLST were resolved into 7 sequence types (ST). Overlap of genotypes was observed more often between sampling points that were closely positioned. Two sampling points contained mixed B. pseudomallei genotypes, each with a numerically dominant genotype and one or more additional genotypes present as minority populations.

Conclusions

Genetic diversity and structuring of B. pseudomallei exists despite the effects of flooding and the physical and chemical processes associated with farming. These findings form an important baseline for future studies of environmental B. pseudomallei.     

ParallABEL: an R library for generalized parallelization of genome-wide association studies

Background  

Genome-Wide Association (GWA) analysis is a powerful method for identifying loci associated with complex traits and drug response. Parts of GWA analyses, especially those involving thousands of individuals and consuming hours to months, will benefit from parallel computation. It is arduous acquiring the necessary programming skills to correctly partition and distribute data, control and monitor tasks on clustered computers, and merge output files.     

Cyclo(tetrahydroxybutyrate) production is sufficient to distinguish between Xenorhabdus and Photorhabdus isolates in Thailand

Bacteria of the genera Photorhabdus and Xenorhabdus produce a plethora of natural products to support their similar symbiotic life cycles. For many of these compounds, the specific bioactivities are unknown. One common challenge in natural product research when trying to prioritize research efforts is the rediscovery of identical (or highly similar) compounds from different strains. Linking genome sequence to metabolite production can help in overcoming this problem. However, sequences are typically not available for entire collections of organisms. Here, we perform a comprehensive metabolic screening using HPLC-MS data associated with a 114-strain collection (58 Photorhabdus and 56 Xenorhabdus) across Thailand and explore the metabolic variation among the strains, matched with several abiotic factors. We utilize machine learning in order to rank the importance of individual metabolites in determining all given metadata. With this approach, we were able to prioritize metabolites in the context of natural product investigations, leading to the identification of previously unknown compounds. The top three highest ranking features were associated with Xenorhabdus and attributed to the same chemical entity, cyclo(tetrahydroxybutyrate). This work also addresses the need for prioritization in high-throughput metabolomic studies and demonstrates the viability of such an approach in future research.