Species richness, community structure and taxonomic composition are important characteristics of biodiversity. Beetle communities show distinct diversity patterns according to habitat attributes. Tropical rainforest canopies, which are well known for their richness in Coleoptera, represent such a conspicuous life zone. Here, I describe a canopy-inhabiting beetle community associated with 23 tree species in a Neotropical lowland rainforest. Adult beetles were sampled manually and in aerial traps using a large tower crane for a cumulative year. The sample revealed 6738 adult beetles, which were assigned to 862 (morpho-)species in 45 families. The most species-rich beetle families were Curculionidae (n = 246), Chrysomelidae (n = 121) and Cerambycidae (n = 89). The most abundant families were Curculionidae (n = 2746) and Chrysomelidae (n = 1409). Dominant beetle families were found in most assemblages. The beetle community consisted of 400 singletons (46.4%). A similar proportion was evident for assemblages of single tree species. I found that 74.5% of all beetle species were restricted in their occurrence on host trees to the phenological season and time of the day. This daily and seasonal migration causes patterns similar to mass effects and therefore accounts for the high proportion of singletons.

Diatom cell-size composition is an indicator of aquatic environmental changes but has been rarely investigated, especially in semi-terrestrial peatlands. In this study, both taxonomic composition and cell-size composition of diatoms were analysed in 41 samples from two montane peatlands, northeastern China. Redundancy analyses revealed that diatom taxonomic composition was significantly related to the depth to the water table (DWT) and Ca2+, while cell-size composition was significantly associated with DWT and Si. DWT was the most important factor and its sole effect explained 26.2% and 17.9% of the total variance in taxonomic composition and cell-size composition, respectively. Accordingly, diatom-based water-table transfer functions were developed based on taxonomic composition and cell-size composition, respectively. The maximum-likelihood (ML) model based on diatom taxonomic composition had the best performance, with a correlation coefficient value (R2) of 0.78 and the root mean squared error of prediction (RMSEP) of 6.66 cm. The ML model based on cell-size composition had similar performance, with an R2 of 0.78 and the RMSEP of 6.87 cm, suggesting that diatom cell-size composition can be a new quantitative means to track past water-table changes. This method requires further appraisal with palaeoecological data but offers a new option that deserves exploration.

Historically, our understanding of bacterial ecology in the Indian Ocean has been limited to regional studies that place emphasis on community structure and function within oxygen minimum zones. Thus, bacterial community dynamics across the wider Indian Ocean are largely undescribed. As part of Bio-GO-SHIP, we sequenced the 16S rRNA gene from 465 samples collected on sections I07N and I09N. We found that (i) there were 23 distinct bioregions within the Indian Ocean, (ii) the southeastern gyre had the largest gradient in bacterial alpha-diversity, (iii) the Indian Ocean surface microbiome was primarily composed of a core set of taxa, and (iv) bioregions were characterized by transitions in physical and geochemical conditions. Overall, we showed that bacterial community structure spatially delineated the surface Indian Ocean and that these microbially-defined regions were reflective of subtle ocean physical and geochemical gradients. Therefore, incorporating metrics of in-situ microbial communities into marine ecological regions traditionally defined by remote sensing will improve our ability to delineate warm, oligotrophic regions.

Modern microbial mats are relictual communities mostly found in extreme environments worldwide. Despite their significance as representatives of the ancestral Earth and their important roles in biogeochemical cycling, research on microbial mats has largely been localized, focusing on site-specific descriptions and environmental change experiments. Here, we present a global comparative analysis of non-lithifying microbial mats, integrating environmental measurements with metagenomic data from 62 samples across eight sites, including two new samples from the recently discovered Archaean Domes from Cuatro Ciénegas, Mexico. Our results revealed a notable influence of environmental filtering on both taxonomic and functional compositions of microbial mats. Functional redundancy appears to confer resilience to mats, with essential metabolic pathways conserved across diverse and highly contrasting habitats. We identified six highly correlated clusters of taxa performing similar ecological functions, suggesting niche partitioning and functional specialization as key mechanisms shaping community structure. Our findings provide insights into the ecological principles governing microbial mats, and lay the foundation for future research elucidating the intricate interplay between environmental factors and microbial community dynamics.

Over the last decades, the analysis of complex microbial communities by high-throughput sequencing of marker gene amplicons has become routine work for many research groups. However, the main challenges faced by scientists who want to make use of the generated sequencing datasets are the lack of expertise to select a suitable pipeline and the need for bioinformatics or programming skills to apply it. Here, we present MetaXplore, an interactive, user-friendly platform that enables the discovery and visualization of amplicon sequencing data. Currently, it provides a set of well-documented choices for downstream analysis, including alpha and beta diversity analysis, taxonomic composition, differential abundance analysis, identification of the core microbiome within a population, and biomarker analysis. These features are presented in a user-friendly format that facilitates easy customization and the generation of publication-quality graphics. MetaXplore is implemented entirely in the R language using the Shiny framework. It can be easily used locally on any system with R installed, including Windows, Mac OS, and most Linux distributions, or remotely via a web server without bioinformatic expertise. It can also be used as a framework for advanced users who can modify and expand the tool.

Polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) is a traditional non-culture technique that can provide a fingerprint of the microbial community. In the field of gut microbiota analysis, PCR-DGGE still holds potential for development. In the present study, we utilized an improved nested PCR-DGGE approach targeting the V3 region of 16S ribosomal DNA to investigate the impact of whole grain highland hull-less barley (WHLB), a cereal known for its significant hypocholesterolemic effect, on the gut microbiota profiles of high-fat diet rats. Seventy-two male Sprague-Dawley rats were divided into four groups and fed a normal control diet, a high-fat diet, or a high-fat diet supplemented with a low or high dose of WHLB for 4 or 8 weeks. The results revealed that the dominant bands varied among different dose groups and further changed with different treatment times. The compositions of bacterial communities in feces and cecal content were similar, but the dominant bacterial bands differed. After performing double DGGE, extracting the bands, sequencing the DNA, and aligning the sequences, a total of 19 bands were classified under the Firmicutes and Bacteroidetes phyla, while two bands were identified as unclassified uncultured bacteria. The relative abundance of Lactobacillus gasseri, Uncultured Prevotella sp., and Clostridium sp. increased following the administration of WHLB. Illumina-based sequencing was employed to assess the reliability of DGGE, demonstrating its reliability in analyzing the dominant taxonomic composition, although it may have limitations in accurately detecting the alpha diversity of bacterial species.
OBJECTIVE: While next-generation sequencing has overshadowed polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE), the latter still holds promise for advancing gut microbiota analysis due to its unique advantages. In this study, we used optimized nested PCR-DGGE to investigate the gut microbiota profile of high-fat diet rats after administering whole grain highland hull-less barley. High-throughput sequencing was employed to validate the DGGE results. Our results proved the reliability of PCR-DGGE for analyzing the dominant taxonomic composition while also providing visual evidence of a notable relationship between the composition of cecal and fecal microbial communities, highlighting substantial differences in both richness and abundance.

Recent studies have shown that the bacterial microbiome of the respiratory tract influences the development of lung cancer. Changes in the composition of the microbiome are observed in patients with chronic inflammatory processes. Such microbiome changes may include the occurrence of bacteria that cause oxidative stress and that are capable of causing genome damage in the cells of the host organism directly and indirectly. To date, the composition of the respiratory microbiome in patients with various histological variants of lung cancer has not been studied. In the present study, we determined the taxonomic composition of the sputum microbiome of 52 patients with squamous cell carcinoma of the lung, 52 patients with lung adenocarcinoma and 52 healthy control donors, using next-generation sequencing (NGS) on the V3-V4 region of the bacterial gene encoding 16S rRNA. The sputum microbiomes of patients with different histological types of lung cancer and controls did not show significant differences in terms of the species richness index (Shannon); however, the patients differed from the controls in terms of evenness index (Pielou). The structures of bacterial communities (beta diversity) in the adenocarcinoma and squamous cell carcinoma groups were also similar; however, when analyzed according to the matrix constructed by the Bray-Curtis method, there were differences between patients with squamous cell carcinoma and healthy subjects, but not between those with adenocarcinoma and controls. Using the LEFse method it was possible to identify an increase in the content of Bacillota (Streptococcus and Bacillus) and Actinomycetota (Rothia) in the sputum of patients with squamous cell carcinoma when compared with samples from patients with adenocarcinoma. There were no differences in the content of bacteria between the samples of patients with adenocarcinoma and the control ones. The content of representatives of the genera Streptococcus, Bacillus, Peptostreptococcus (phylum Bacillota), Prevotella, Macellibacteroides (phylum Bacteroidota), Rothia (phylum Actinomycetota) and Actinobacillus (phylum Pseudomonadota) was increased in the microbiome of sputum samples from patients with squamous cell carcinoma, compared with the control. Thus, the sputum bacterial microbiome of patients with different histological types of non-small-cell lung cancer has significant differences. Further research should be devoted to the search for microbiome biomarkers of lung cancer at the level of bacterial species using whole-genome sequencing.
Исследования последних лет показали, что бактериальный микробиом респираторного тракта влияет на развитие рака легкого. Изменение состава микробиома у пациентов связывают с хроническими воспалительными процессами, так как многие бактерии вызывают окислительный стресс, а также способны прямо или опосредованно повреждать геном в клетках организма хозяина. До настоящего времени состав респираторного микробиома у больных с различными гистологическими вариантами рака легкого не изучен. В настоящем исследовании для анализа таксономического состава микробиома мокроты 52 пациентов с плоскоклеточным раком легкого, 52 пациентов с аденокарциномой легкого и 52 здоровых доноров контрольной группы использовали технологию массового параллельного секвенирования региона V3-V4 16S рРНК. Микробиомы мокроты больных с разными гистологическими типами рака легкого и контроля не имели значимых различий по индексу видового богатства (Шеннона), однако у пациентов они отличались от контроля по индексу выравненности (Пиелу). Структуры бактериальных сообществ (бета-разнообразие) между аденокарциномой и плоскоклеточным раком также были близкими. Тем не менее матрица, построенная по Брэю–Кёртису, позволила выявить различия между пациентами с плоскоклеточным раком и здоровыми субъектами, но не между аденокарциномой и контролем. Метод LEFse позволил идентифицировать в мокроте больных плоскоклеточным раком увеличение содержания Bacillota (Streptococcus и Bacillus) и Actinomycetota (Rothia) при сопоставлении с образцами пациентов с аденокарциномой. Не найдено различий в содержании бактерий между образцами больных аденокарциномой и контроля. В микробиоме образцов мокроты пациентов с плоскоклеточным раком по сравнению с контролем было повышено содержание представителей родов Streptococcus, Bacillus, Peptostreptococcus (филум Bacillota), Prevotella, Macellibacteroides (филум Bacteroidota), Rothia (филум Actinomycetota) и Actinobacillus (филум Pseudomonadota). Таким образом, бактериальный микробиом мокроты пациентов с разными гистологическими типами немелкоклеточного рака легкого имеет существенные различия. Дальнейшие исследования должны быть посвящены поиску микробиомных биомаркеров рака легкого на уровне бактериальных видов с использованием полногеномного секвенирования.

Changes in phytoplankton abundance and biomass during the period 1933-2020 were examined by statistical modeling using data from the Inner Oslofjorden phytoplankton database. The phytoplankton abundances increased with eutrophication from 1930s to 1970s, but with the implementation of sewage cleaning measures and a resulting reduction in nutrient releases, the phytoplankton abundance has since then decreased significantly. The onset of the seasonal blooms has started progressively later during the last 15 years, especially the spring bloom. The delayed spring bloom co-occurred with increasing temperature in winter and spring. The diatom biomass decreased more than that of dinoflagellates and other microeukaryotes. The diatom genus Skeletonema dominated the spring bloom and was found to be the key taxa in explaining these changes in abundance and phenology. Extensive summer blooms of the coccolithophore Emiliania huxleyi, which has been characteristic for the inner Oslofjorden, has also gradually decreased during the last decades, along with reducing eutrophication. Dinoflagellates have not had the same reduction in abundance as the other groups. Despite an increasing proportion of dinoflagellates compared with other taxa, there are no clear indications of increased occurrence of toxic algal blooms in inner Oslofjorden. However, the introduction of new \"toxin-producing\" species may cause concern.

Intense conversion of tropical forests into agricultural systems contributes to habitat loss and the decline of ecosystem functions. Plant-pollinator interactions buffer the process of forest fragmentation, ensuring gene flow across isolated patches of forests by pollen transfer. In this study, we identified the composition of pollen grains stored in pot-pollen of stingless bees, Tetragonula laeviceps, via dual-locus DNA metabarcoding (ITS2 and rbcL) and light microscopy, and compared the taxonomic coverage of pollen sampled in distinct land-use systems categorized in four levels of management intensity (forest, shrub, rubber, and oil palm) for landscape characterization.
Plant composition differed significantly between DNA metabarcoding and light microscopy. The overlap in the plant families identified via light microscopy and DNA metabarcoding techniques was low and ranged from 22.6 to 27.8%. Taxonomic assignments showed a dominance of pollen from bee-pollinated plants, including oil-bearing crops such as the introduced species Elaeis guineensis (Arecaceae) as one of the predominant taxa in the pollen samples across all four land-use types. Native plant families Moraceae, Euphorbiaceae, and Cannabaceae appeared in high proportion in the analyzed pollen material. One-way ANOVA (p > 0.05), PERMANOVA (R² values range from 0.14003 to 0.17684, for all tests p-value > 0.5), and NMDS (stress values ranging from 0.1515 to 0.1859) indicated a lack of differentiation between the species composition and diversity of pollen type in the four distinct land-use types, supporting the influx of pollen from adjacent areas.
Stingless bees collected pollen from a variety of agricultural crops, weeds, and wild plants. Plant composition detected at the family level from the pollen samples likely reflects the plant composition at the landscape level rather than the plot level. In our study, the plant diversity in pollen from colonies installed in land-use systems with distinct levels of forest transformation was highly homogeneous, reflecting a large influx of pollen transported by stingless bees through distinct land-use types. Dual-locus approach applied in metabarcoding studies and visual pollen identification showed great differences in the detection of the plant community, therefore a combination of both methods is recommended for performing biodiversity assessments via pollen identification.

OBJECTIVE: To identify the specific microbial community compositions in saliva associated with periodontitis during pregnancy.
METHODS: Unstimulated saliva samples were collected from 53 pregnant women during weeks 24-28 of gestation, and the V3-V4 regions of the 16S rRNA gene were amplified from isolated saliva DNA and sequenced. Phylum-, genus-, and species-level taxonomic compositions were separately compared between subjects with (n = 12) and without (n = 41) periodontitis.
RESULTS: Taxa were selected using the random forest algorithm to distinguish subjects with periodontitis at each taxonomic level, and principal component biplots were constructed to visualize the composition of selected taxa in each subject. The genus-level biplot indicated that 44 subjects clustered around the origin. The prevalence of periodontitis was significantly higher among subjects outside the cluster compared with subjects inside the cluster (6/9 [67%] vs. 6/44 [14%], respectively; p = 0.002). Subjects outside the cluster also had significantly decreased abundance of Neisseria and increased abundances of several putative periodontopathic genera. Phylum- and species-level biplots failed to discriminate subjects with periodontitis more efficiently than the genus-level biplot.
CONCLUSIONS: The specific taxonomic composition of the saliva microbiota in pregnant women with periodontitis could be clearly identified at the genus level.
CONCLUSIONS: The formula developed based on the present findings, (%Treponema + %Tannerella + %Filifactor + %Anaeroglobus)/%Neisseria, can be used to predict periodontitis during pregnancy with sensitivity and specificity values of 0.67 (8/12) and 0.95 (39/41), respectively.