Relationships within the Proteobacteria of plant pathogenic Acidovorax species and subspecies, Burkholderia species, and Herbaspirillum rubrisubalbicans by sequence analysis of 16S rDNA, numerical analysis and determinative tests

Metagenomic analysis of drinking water samples collected from treatment plants of Hyderabad City and Mehran University Employees Cooperative Housing Society

The quality assessment of water, supplied to the end user, is an essential part to assess the physical, chemical, and biological status of water, which impacts on human health. For the quality assessment of drinking water treatment plants and distribution systems of Hyderabad City and Mehran University of Engineering and Technology, Jamshoro, Pakistan, 13 surface drinking water samples were collected from three treatment plants, two of Hyderabad City, including WASA treatment plant and its distribution system (n = 5), Hala Nakka treatment plant and its distribution system (n = 6), and Mehran University Employees Cooperative Housing Society (MUECHS) treatment plant and its distribution system (n = 2). Physicochemical parameters of all drinking water samples were in the range compared to EPA and WHO guidelines, except in L-12 sample. Notably, no free-chlorine was detected in all samples. In metagenomics analysis, targeting V3-V4 hypervariable region of 16S rRNA gene, in QIIME2 environment, high bacterial prevalence was observed in all samples. On average, 348 OTUs were observed per sample. Among all samples, treated water sample from the Hala Nakka Treatment Plant (HNTR) was the most diverse sample in bacterial composition (Shannon 7.51 and Simpsons reciprocal indices 0.98). Overall, Proteobacteria, Bacteroidetes, Cyanobacteria, Verrucomicrobia, and Actinobacteria were the five most abundant phyla (relative abundances of 43.6, 37.9, 8.5, 2.5, and 2.4 percent, respectively). Notably, Cyanobacteria are well-known toxin producers which effect the human, and animal health. At genus level, Flavobacterium (4.86%) and Aquirestis (3.77%) were the most abundant genera. Functional predictions, based on 16S rRNA gene by PICRUSt, predicted 6909 KEGG orthologies, relating to 245 KEGG pathways. Among the predicted pathways of KEGG orthologies, pathways to human infections were also found. In conclusion, this study gave a deep insight into bacterial contamination in drinking water samples of Hyderabad City and MUECHS treatment plants and water quality status in Hyderabad and Mehran University of Engineering and Technology.

Evaluation of fimC and bdha based duplex PCR for specific identification and differentiation of Burkholderia pseudomallei from near-neighbor Burkholderia species

Assays for the rapid detection and accurate differentiation of Burkholderia pseudomallei from near-neighbor species are urgently needed in melioidosis endemic regions due to the high associated mortality and biowarfare importance of the pathogen. PCR-based methods have revolutionized this field due to the accuracy, sensitivity, and specificity that are achievable in a rapid way. In this study, a compound molecular detection system, consisting of a duplex PCR assay, was developed for the specific identification of Burkholderia pseudomallei and differentiation from other Burkholderia species. For accurate identification of B. pseudomallei, we deciphered and adopted a novel gene termed putative fimbrial chaperone (fimC). d-beta hydroxybutyrate dehydrogenase (bdha), reported previously by our group for sequence-based differentiation of B. pseudomallei from other Burkholderia species, was employed as a genus-specific target. Enforcement of an internal amplification control in the PCR format ruled out possible false negative results in the assay. Thus, the developed PCR assay was highly specific (100%) in its detection features, and a clear detection sensitivity of 10 pg/μl for purified gDNA and 3 × 10³ CFU/ml for B. pseudomallei spiked urine was recorded. Successful identification of B. pseudomallei from an experimental mouse model at both the genus and species level revealed the accurate diagnostic efficiency of the duplex PCR method.

Phylogenetic study and multiplex PCR-based detection of Burkholderia plantarii, Burkholderia glumae and Burkholderia gladioli using gyrB and rpoD sequences

In order to develop a detection method for the rice pathogens Burkholderia plantarii, Burkholderia glumae and Burkholderia gladioli, the phylogeny of six plant-pathogenic Burkholderia species was analysed using the combined nucleotide sequences of gyrB and rpoD. B. plantarii, B. glumae and B. gladioli formed tight monophyletic branches supported by high bootstrap probabilities. The high sequence similarity revealed a close phylogenetic relationship between B. glumae and B. plantarii. B. plantarii strains were divided into three subclusters comprising rice strains, whereas the single Vanda strain occupied a unique position in the phylogenetic tree. The gyrB and rpoD sequences of all B. glumae strains examined were highly conserved. In contrast, B. gladioli strains demonstrated a far greater sequence diversity, but this diversity did not correlate with pathovar, host plant or geographical origin of the strains. A multiplex-PCR protocol using specific primers from the gyrB sequences was designed that allowed the specific detection and identification of B. plantarii, B. glumae and B. gladioli in rice seeds infected with these pathogenic species.

Integrated approaches for detection of plant pathogenic bacteria and diagnosis of bacterial diseases

Disease diagnosis is based on a number of factors, including laboratory tests for pathogen identification. Rapid development of genomic techniques for characterization of bacteria over the past decade has greatly simplified and improved pathogen detection and identification, but DNA-based methods have not yet entirely replaced traditional culture and phenotypic tests in the plant industry. The first section of this review focuses on rapid immunodiagnostic and DNA-based detection methods for known bacterial pathogens in plants or plant products, which often manifest no symptoms of disease. The second section covers the broader topic of disease diagnosis and new methods for identifying and characterizing bacteria.