METHODS: Pkdhps were amplified and sequenced from 28 P. knowlesi samples collected in 2008 and 2020 from nine provinces across Thailand. Combining pkdhfr sequencing data from previous work with pkdhps data to analyze polymorphisms of pkdhfr and pkdhps haplotype. Protein modeling and molecular docking were constructed using two inhibitors, sulfadoxine and sulfamethoxazole, and further details were obtained through analyses of protein-ligand interactions by using the Genetic Optimisation for Ligand Docking program. A phylogenetic tree cluster analysis was reconstructed to compare the P. knowlesi Malaysia isolates.
RESULTS: Five nonsynonymous mutations in the pkdhps were detected outside the equivalence of the binding pocket sites to sulfadoxine and sulfamethoxazole, which are at N391S, E421G, I425R, A449S, and N517S. Based on the modeling and molecular docking analyses, the N391S and N517S mutations located close to the enzyme-binding pocket demonstrated a different docking score and protein-ligand interaction in loop 2 of the enzyme. These findings indicated that it was less likely to induce drug resistance. Of the four haplotypes of pkdhfr-pkdhps, the most common one is the R34L pkdhfr mutation and the pkdhps quadruple mutation (GRSS) at E421G, I425R, A449S, and N517S, which were observed in P. knowlesi in southern Thailand (53.57%). Based on the results of neighbor-joining analysis for pkdhfr and pkdhps, the samples isolated from eastern Thailand displayed a close relationship with Cambodia isolates, while southern Thailand isolates showed a long branch separated from the Malaysian isolates.
CONCLUSIONS: A new PCR protocol amplification and evaluation of dihydropteroate synthase mutations in Knowlesi (pkdhps) has been developed. The most prevalent pkdhfr-pkdhps haplotypes (53.57%) in southern Thailand are R34L pkdhfr mutation and pkdhps quadruple mutation. Further investigation requires additional phenotypic data from clinical isolates, transgenic lines expressing mutant alleles, or recombinant proteins.
MATERIALS AND METHODS: For the purpose of this study, bacterial communities during 0, 30 and 70 days of culture (DOC) of L. vannamei grow-out ponds were isolated and identified through phenotypic and 16S rDNA sequences analysis. Phylogenetic relationships between isolated bacteria were then evaluated through phylogenetic tree analysis. One-way analysis of variance (ANOVA) was used to compare the differences of microbial communities at each DOC.
RESULTS: Out of 125 bacterial isolates, nine species of bacteria from biofloc were identified successfully. Those bacteria species were identified as Halomonas venusta, H. aquamarina, Vibrio parahaemolyticus, Bacillus infantis, B. cereus, B. safensis, Providencia vermicola, Nitratireductor aquimarinus and Pseudoalteromonas sp., respectively. Through phylogenetic analysis, these isolates belong to Proteobacteria and Firmicutes families under the genera of Halomonas sp., Vibrio sp., Bacillus sp., Providencia sp., Nitratireductor sp. and Pseudoalteromonas sp.
CONCLUSION: In this study, bioflocculant-producing bacteria were successfully identified which are perfect candidates in forming biofloc to reduce water pollution towards a sustainable aquaculture industry. Presence of Halomonas sp. and Bacillus sp. in all stages of biofloc formation reinforces the need for new development regarding the ability of these species to be used as inoculum in forming biofloc rapidly.
RESULTS: To investigate the genomic properties and taxonomic status of these strains, we employed both 16S rRNA Sanger sequencing and whole-genome sequencing using the Illumina HiSeq X Ten platform with PE151 (paired-end) sequencing. Our analyses revealed that the draft genome of Actinomyces acetigenes ATCC 49340 T was 3.27 Mbp with a 68.0% GC content, and Actinomyces stomatis ATCC 51655 T has a genome size of 3.08 Mbp with a 68.1% GC content. Multi-locus (atpA, rpoB, pgi, metG, gltA, gyrA, and core genome SNPs) sequence analysis supported the phylogenetic placement of strains ATCC 51655 T and ATCC 49340 T as independent lineages. Digital DNA-DNA hybridization (dDDH), average nucleotide identity (ANI), and average amino acid identity (AAI) analyses indicated that both strains represented novel Actinomyces species, with values below the threshold for species demarcation (70% dDDH, 95% ANI and AAI). Pangenome analysis identified 5,731 gene clusters with strains ATCC 49340 T and ATCC 51655 T possessing 1,515 and 1,518 unique gene clusters, respectively. Additionally, genomic islands (GIs) prediction uncovered 24 putative GIs in strain ATCC 49340 T and 16 in strain ATCC 51655 T, contributing to their genetic diversity and potential adaptive capabilities. Pathogenicity analysis highlighted the potential human pathogenicity risk associated with both strains, with several virulence-associated factors identified. CRISPR-Cas analysis exposed the presence of CRISPR and Cas genes in both strains, indicating these strains might evolve a robust defense mechanism against them.
CONCLUSION: This study supports the classification of strains ATCC 49340 T and ATCC 51655 T as novel species within the Actinomyces, in which the name Actinomyces acetigenes sp. nov. (type strain ATCC 49340 T = VPI D163E-3 T = CCUG 34286 T = CCUG 35339 T) and Actinomyces stomatis sp. nov. (type strain ATCC 51655 T = PK606T = CCUG 33930 T) are proposed.