Impact of Land-use Change on Dengue and Malaria in Northern Thailand

Land-use change, a major constituent of global environmental change, potentially has significant consequences for human health in relation to mosquito-borne diseases. Land-use change can influence mosquito habitat, and therefore the distribution and abundance of vectors, and land use mediates human–mosquito interactions, including biting rate. Based on a conceptual model linking the landscape, people, and mosquitoes, this interdisciplinary study focused on the impacts of changes in land use on dengue and malaria vectors and dengue transmission in northern Thailand. Extensive data on mosquito presence and abundance, land-use change, and infection risk determinants were collected over 3 years. The results of the different components of the study were then integrated through a set of equations linking land use to disease via mosquito abundance. The impacts of a number of plausible scenarios for future land-use changes in the region, and of concomitant behavioral change were assessed. Results indicated that land-use changes have a detectable impact on mosquito populations and on infection. This impact varies according to the local environment but can be counteracted by adoption of preventive measures.     

Diversity and Antimicrobial Activity of Endophytic Actinomycetes Isolated from Plant Roots in Thailand

Microbiology - In this study, 37 endophytic actinomycetes were isolated from roots of 14 plant species obtained in Thailand, where biological diversity is known to be high. The isolates were...     

Lactic acid bacteria isolated from soy sauce mash in Thailand

Fourteen sphere-shaped and 30 rod-shaped lactic acid bacteria were isolated from soy sauce mash of two factories in Thailand. These strains were separated into two groups, Group A and Group B, by cell shape and DNA-DNA similarity. Group A contained 14 tetrad-forming strains, and these strains were identified as Tetragenococcus halophilus by DNA similarity. Group B contained 30 rod-shaped bacteria, and they were further divided into four Subgroups, B1, B2, B3, and B4, and three ungrouped strains by phenotypic characteristics and DNA similarity. Subgroup B1 contained 16 strains, and these strains were identified as Lactobacillus acidipiscis by DNA similarity. Subgroup B2 included two strains, and the strains were identified as Lactobacillus farciminis by DNA similarity. Subgroup B3 contained five strains. The strains had meso-diaminopimelic acid in the cell wall, and were identified as Lactobacillus pentosus by DNA similarity. The strains tested produced DL-lactic acid from D-glucose. Subgroup B4 contained four strains. The strains had meso-diaminopimelic acid in the cell wall, and they were identified as Lactobacillus plantarum by DNA similarity. Two ungrouped strains were homofermentative, and one was heterofermentative. They showed a low degree of DNA similarity with the type strains tested, and were left unnamed. The distribution of lactic acid bacteria in soy sauce mash in Thailand is discussed.     

Linkage disequilibrium network analysis (LDna) gives a global view of chromosomal inversions,local adaptation and geographic structure

Recent advances in sequencing allow population‐genomic data to be generated for virtually any species. However, approaches to analyse such data lag behind the ability to generate it, particularly in nonmodel species. Linkage disequilibrium (LD, the nonrandom association of alleles from different loci) is a highly sensitive indicator of many evolutionary phenomena including chromosomal inversions, local adaptation and geographical structure. Here, we present linkage disequilibrium network analysis (LDna), which accesses information on LD shared between multiple loci genomewide. In LD networks, vertices represent loci, and connections between vertices represent the LD between them. We analysed such networks in two test cases: a new restriction‐site‐associated DNA sequence (RAD‐seq) data set for Anopheles baimaii, a Southeast Asian malaria vector; and a well‐characterized single nucleotide polymorphism (SNP) data set from 21 three‐spined stickleback individuals. In each case, we readily identified five distinct LD network clusters (single‐outlier clusters, SOCs), each comprising many loci connected by high LD. In A. baimaii, further population‐genetic analyses supported the inference that each SOC corresponds to a large inversion, consistent with previous cytological studies. For sticklebacks, we inferred that each SOC was associated with a distinct evolutionary phenomenon: two chromosomal inversions, local adaptation, population‐demographic history and geographic structure. LDna is thus a useful exploratory tool, able to give a global overview of LD associated with diverse evolutionary phenomena and identify loci potentially involved. LDna does not require a linkage map or reference genome, so it is applicable to any population‐genomic data set, making it especially valuable for nonmodel species.     

Micromonospora siamensis sp. nov., isolated from Thai peat swamp forest

Morphological and chemotaxonomic characterization of actinomycete strain TT2-4T isolated from peat swamp forest soil in Pattaloong Province, Thailand, clearly demonstrated that this strain belongs to the genus Micromonospora. 16S rDNA sequence analysis for the strain supported the assignment of the strain to the genus Micromonospora and the similarity value of sequences between this strain and the closely related species, Micromonospora mirobrigensis was 99.1%, and M. carbonacea and M. matsumotoense were 98.8%. The DNA-DNA hybridization result and some physiological and biochemical properties indicated that strain TT2-4T was distinguished from the phylogenetically closest relatives. Based on these genotypic and phenotypic data, strain TT2-4T merits a new species in the genus Micromonospora and the name Micromonospora siamensis sp. nov. is proposed for the strain. The type strain is strain TT2-4T (=JCM 12769T =PCU 266T =TISTR 1554T).     

Heterogeneity of strains assigned to Gluconobacter frateurii Mason and Claus 1989 based on restriction analysis of 16S-23S rDNA internal transcribed spacer regions

Twenty-three strains, which were assigned to Gluconobacter frateurii and maintained at Culture Collection NBRC, were re-identified at the species level on the basis of restriction analysis of 16S-23S rDNA ITS regions by digestion with six restriction endonucleases: Bsp1286I, MboII, AvaII, TaqI, BsoBI, and BstNI. The strains examined were divided into six groups, Group III-1, Group III-2, Group III-3, Group III-4, Group III-5, and Group IV. Group III-1 and Group III-4 respectively were divided into two subgroups, Subgroup III-1a, Subgroup III-1b and Subgroup III-4a, Subgroup III-4b. Gluconobacter frateurii NBRC 3264(T) was included in Group III-2, along with strains NBRC 3265 and NBRC 3270, and G. thailandicus BCC 14116(T) was included in Group III-3, along with strains NBRC 3254, NBRC 3256, NBRC 3258, NBRC 3255, and NBRC 3257. These groupings were supported by a phylogenetic tree based on 16S-23S rDNA ITS sequences. Strains of group III-2 and Group IV were unequivocally re-identified as G. frateurii, but strains of Group III-3, Group III-4, and Group III-5 were not necessarily re-identified as G. frateurii. The results obtained indicate that the 23 strains have a taxonomically heterogeneous nature, and they are referred to as the G. frateurii complex.