Rhodoferax potami sp. nov. and Rhodoferax mekongensis sp. nov., isolated from the Mekong River in Thailand.

Four newly discovered Gram-stain-negative bacteria, designated as BL00010T, BL00058, D8-11T and BL00200, were isolated from water samples collected at three hydrological monitoring stations (namely Chiang Saen, Chiang Khan and Nong Khai) located along the Mekong River in Thailand. An investigation encompassing phenotypic, chemotaxonomic and genomic traits was conducted. The results of phylogenetic analysis based on 16S rRNA gene sequences indicated that all four isolates represented members of the genus Rhodoferax. These isolates were closely related to Rhodoferax bucti KCTC 62564T with a similarity of 99.59%. The major fatty acids of the four novel isolates included C16:0 and C16:1ω7c and/or C16 : 1ω6c, whereas the major respiratory quinone was identified as ubiquinone Q-8. In addition, phosphatidylethanolamine was identified as a major polar lipid in these bacteria. The genomes of BL00010T, BL00058, D8-11T and BL00200 were similar in size (3.88-4.01 Mbp) and DNA G+C contents (59.5, 59.3, 59.5 and 59.3 mol%, respectively). In contrast to R. bucti KCTC 62564T and Rhodoferax aquaticus KCTC 32394T, the newly discovered species possessed several genes involved in nitrite and nitrile metabolism, which may be related to their unique adaptation to nitrile-rich environments. From the results of the pairwise analysis of average nucleotide identity of the whole genome and digital DNA-DNA hybridisation, it was evident that BL00010T and D8-11T represented two novel species, for which we propose the nomenclature Rhodoferax potami sp. nov., with the type strain BL00010T (TBRC 17198T = NBRC 116413T), and Rhodoferax mekongensis sp. nov., with the type strain D8-11T (TBRC 17307T = NBRC 116415T).

Fungal communities as dual indicators of river biodiversity and water quality assessment.

Given their ecological importance, bioindicators are used for the assessment of the health of river ecosystems. This study explored the fungal compositions and the potential of fungal taxa as bioindicators for indicating the water quality of the Mekong River, as the use of fungal indicators of the Mekong River was not previously well characterized. The Mekong River exhibited dynamic variations in both physicochemical/hydrochemical properties and fungal communities according to seasons and locations. The results revealed the dominance of alkaline earth metal ions and weak acids in the water. The magnesium-bicarbonate water type was found in the dry season, but the water became the chloride-calcium type or mixed type of magnesium-bicarbonate and chloride-calcium in the rainy season at downstream sites. Fungal composition analysis revealed the dominance of Chytridiomycota in the dry season and intermediate periods, and Ascomycota and Basidiomycota in the rainy season. The fungal communities were influenced by stochastic and deterministic assembly processes, mainly homogeneous selection, heterogeneous selection, and dispersal limitation. The extent of environmental filtering implied that some fungal taxa were affected by environmental conditions, suggesting the possibility of identifying certain fungal taxa suitable for being bioindicators of water quality. Subsequently, machine learning with recursive feature elimination identified specific fungal bins mostly consisting of Agaricomycetes (mainly Polyporales, Agaricales, and Auriculariales), Dothideomycetes (mainly Pleosporales), Saccharomycetes (mainly Saccharomycetales), Chytridiomycota, and Rozellomycota as bioindicators that could predict ambient and irrigation water quality with high selectivity and sensitivity. These results thus promote the use of fungal indicators to assess the health of the river.

Interplay of xenobiotic-degrading and antibiotic-resistant microorganisms among the microbiome found in the air, handrail, and floor of the subway station.

Investigating the quality of the subway environment, especially regarding antibiotic resistance genes (ARGs) and xenobiotics, conveys ecological and health impacts. In this study, compositions and relations of microorganisms harboring ARGs and xenobiotic degradation and metabolism genes (XDGs) in the Sukhumvit subway station (MRT-SKV) in Bangkok was assessed by analyzing the taxonomic and genetic diversity of the microbiome in the air and on the surfaces of floor and handrail. The major bacteria in the MRT-SKV (including Moraxella, which was abundant in the bioaerosol and handrail samples, and Staphylococcus, which was abundant in the bioaerosol samples) were found to contain both ARGs and XDGs. The co-abundance correlation network revealed notable relationships among bacteria harboring antibiotic resistance genes (ARGs) and xenobiotic degradation genes (XDGs). Significant associations were observed between ARGs linked to glycopeptide and fluoroquinolone resistance and genes associated with benzoate, styrene, and atrazine degradation pathways, as well as between ARGs related to cephamycin, cephalosporin, and MLS resistance and XDGs associated with the cytochrome P450-dependent drug metabolism pathway. These correlations suggested that selective pressure exerted by certain xenobiotics and antibiotics can simultaneously affect both ARGs and XDGs in the environment and should favor correlations and co-survival among ARG- and XDG-containing bacteria in the environments. The correlations may occur via shared mechanisms of resistance to both xenobiotics and antibiotics. Finally, different correlation pairs were seen in different niches (air, handrail, floor) of the subway environment or different geolocations. Thus, the relationship between ARG and XDG pairs most likely depends on the unique characteristics of the niches and on the prominent types of xenobiotics and antibiotics in the subway environment. The results indicated that interactions and connections between microbial communities can impact how they function. These microorganisms can have profound effects on accumulation of xenobiotics and ARGs in the MRT-SKV.

Elucidating potential bioindicators from insights in the diversity and assembly processes of prokaryotic and eukaryotic communities in the Mekong River.

Drivers for spatio-temporal distribution patterns of overall planktonic prokaryotes and eukaryotes in riverine ecosystems are generally not fully understood. This study employed amplicon metabarcoding to investigate the distributions and assembly mechanisms of bacterial and eukaryotic communities in the Mekong River. The prevailing bacteria taxa were found to be Betaproteobacteria, Actinobacteria, and Bacteroidetes, while the dominant eukaryotic organisms were cryptophytes, chlorophytes, and diatoms. The community assemblages were influenced by a combination of stochastic and deterministic processes. Drift (DR) and dispersal limitation (DL), signifying the stochastic mechanism, were the main processes shaping the overall prokaryotic and eukaryotic communities. However, homogeneous selection (HoS), indicating deterministic mechanism, played a major role in the assembly process of core prokaryotic communities, especially in the wet season. In contrast, the core eukaryotic communities including Opisthokonta, Sar, and Chlorophyta were dominated by stochastic processes. The significance of HoS within prokaryotic communities was also found to exhibit a decreasing trend from the upstream sampling sites (Chiang Saen and Chiang Khan, Nong Khai) towards the downstream sites (Mukdahan, and Khong Chiam) of the Mekong River. The environmental gradients resulting from the site-specific variations and the gradual decrease in elevation along the river may have a potential influence on the role of HoS in community assembly. Crucial environmental factors that shape the phylogenetic structure within distinct bins of the core prokaryotic communities including water depth, temperature, chloride, sodium, and sulphate were identified, as inferred by their correlation with the beta Net Relatedness Index (betaNRI) during the wet season. Overall, these findings enhance understanding of the complex mechanisms governing the spatio-temporal dynamics of prokaryotic and eukaryotic communities in the Mekong River. Finally, insights gained from this study could provide information on further use of specific core bacteria as microbial-based bioindicators that are effective for the assessment and conservation of the Mekong River ecosystem.

AirDNA sampler: An efficient and simple device enabling high-yield, high-quality airborne environment DNA for metagenomic applications.

Analyzing temporal and spatial distributions of airborne particles of biological origins is vital for the assessment and monitoring of air quality, especially with regard to public health, environmental ecology, and atmospheric chemistry. However, the analysis is frequently impeded by the low levels of biomass in the air, especially with metagenomic DNA analysis to explore diversity and composition of living organisms and their components in the air. To obtain sufficient amounts of metagenomic DNA from bioaerosols, researchers usually need a long sampling time with an expensive high-volume air sampler. This work shows the utilization of an air sampling device containing an economical, high-volume portable ventilation fan in combination with customized multi-sheet filter holders to effectively obtain high yields of genomic DNA in a relatively short time. The device, named 'AirDNA' sampler, performed better than other commercial air samplers, including MD8 Airport and Coriolis compact air samplers. Using the AirDNA sampler, an average DNA yield of 40.49 ng (12.47-23.24 ng at 95% CI) was obtained in only 1 hour of air sampling with a 0.85 probability of obtaining ≥10 ng of genomic DNA. The genomic DNA obtained by the AirDNA system is of suitable quantity and quality to be further used for amplicon metabarcoding sequencing of 16S, 18S, and cytochrome c oxidase I (COI) regions, indicating that it can be used to detect various prokaryotes and eukaryotes. Our results showed the effectiveness of our AirDNA sampling apparatus with a simple setup and affordable devices to obtain metagenomic DNA for short-term or long-term spatiotemporal analysis. The technique is well suited for monitoring air in built environments, especially monitoring bioaerosols for health purposes and for fine-scale spatiotemporal environmental studies.

Temporal, compositional, and functional differences in the microbiome of Bangkok subway air environment.

With the growing numbers of the urban population, an increasing number of commuters have relied on subway systems for rapid transportation in daily life. Analyzing the temporal distribution of air microbiomes in subway environments is crucial for the assessment and monitoring of air quality in the subway system, especially with regard to public health. This study employed culture-independent metabarcode sequencing to analyze bacterial diversity and variations in bacterial compositions associated with bioaerosols collected from a subway station in Bangkok over a four-month period. The bacteria obtained were found to consist primarily of Proteobacteria, Firmicutes, and Actinobacteria, with variations at the family, genus, and species levels among samples obtained in different months. The vast majority of these bacteria are most likely derived from outside environments and human body sources. Many of the bacteria found in Bangkok subway station were also identified as "core microorganisms" of subway environments around the world, as suggested by the MetaSUB Consortium. The diversity of bacterial communities was shown to be influenced by several air quality variables, especially ambient temperature and the quantity of particulate matters, which showed positive correlations with several bacterial species such as Acinetobacter lwoffii, Staphylococcus spp., and Moraxella osloensis. In addition, metabolic profiles inferred from metabarcode-derived bacterial diversity showed significant variations across different sampling times and sites and can be used as a starting point to further explore the functional roles of specific groups of bacteria in the subway environment. This study thus introduced the information required for surveillance of microbiological impacts and their contributions to the well-being of subway commuters in Bangkok.

Beneficial bacterial-Auricularia cornea interactions fostering growth enhancement identified from microbiota present in spent mushroom substrate.

Complex dynamic bacterial-fungal interactions play key roles during mushroom growth, ranging from mutualism to antagonism. These interactions convey a large influence on mushroom's mycelial and fruiting body formation during mushroom cultivation. In this study, high-throughput amplicon sequencing was conducted to investigate the structure of bacterial communities in spent mushroom substrates obtained from cultivation of two different groups of Auricularia cornea with (A) high yield and (B) low yield of fruiting body production. It was found that species richness and diversity of microbiota in group (A) samples were significantly higher than in group (B) samples. Among the identified 765 bacterial OTUs, 5 bacterial species found to exhibit high differential abundance between group (A) and group (B) were Pseudonocardia mangrovi, Luteimonas composti, Paracoccus pantotrophus, Sphingobium jiangsuense, and Microvirga massiliensis. The co-cultivation with selected bacterial strains showed that A. cornea TBRC 12900 co-cultivated with P. mangrovi TBRC-BCC 42794 promoted a high level of mycelial growth. Proteomics analysis was performed to elucidate the biological activities involved in the mutualistic association between A. cornea TBRC 12900 and P. mangrovi TBRC-BCC 42794. After co-cultivation of A. cornea TBRC 12900 and P. mangrovi TBRC-BCC 42794, 1,616 proteins were detected including 578 proteins of A. cornea origin and 1,038 proteins of P. mangrovi origin. Functional analysis and PPI network construction revealed that the high level of mycelial growth in the co-culture condition most likely resulted from concerted actions of (a) carbohydrate-active enzymes including hydrolases, glycosyltransferases, and carbohydrate esterases important for carbohydrate metabolism and cell wall generation/remodeling, (b) peptidases including cysteine-, metallo-, and serine-peptidases, (c) transporters including the ABC-type transporter superfamily, the FAT transporter family, and the VGP family, and (d) proteins with proposed roles in formation of metabolites that can act as growth-promoting molecules or those normally contain antimicrobial activity (e.g., indoles, terpenes, ß-lactones, lanthipeptides, iturins, and ectoines). The findings will provide novel insights into bacterial-fungal interactions during mycelial growth and fruiting body formation. Our results can be utilized for the selection of growth-promoting bacteria to improve the cultivation process of A. cornea with a high production yield, thus conveying potentially high socio-economic impact to mushroom agriculture.

Uncovering multi-faceted taxonomic and functional diversity of soil bacteriomes in tropical Southeast Asian countries.

Environmental microbiomes encompass massive biodiversity and genetic information with a wide-ranging potential for industrial and agricultural applications. Knowledge of the relationship between microbiomes and environmental factors is crucial for translating that information into practical uses. In this study, the integrated data of Southeast Asian soil bacteriomes were used as models to assess the variation in taxonomic and functional diversity of bacterial communities. Our results demonstrated that there were differences in soil bacteriomes across different geographic locality with different soil characteristics: soil class and pH level. Such differences were observed in taxonomic diversity, interspecific association patterns, and functional diversity of soil bacteriomes. The bacterial-mediated biogeochemical cycles of nitrogen, sulfur, carbon, and phosphorus illustrated the functional relationship of soil bacteriome and soil characteristics, as well as an influence from bacterial interspecific interaction. The insights from this study reveal the importance of microbiome data integration for future microbiome research.