Actinobacteria are known for their metabolic potential of producing diverse secondary metabolites such as antibiotics. Actinobacteria also playimportant roles in biogeochemical cycling and how soils ...develop. However, little is known about the effect of the vegetation type on the actinobacterial community structures in soils from arid regions. For these reasons, we have analyzed the actinobacterial communities of five types of ecosystem (tree grove, shrub, meadow, desert, and farm) in the Heihe river basin. Using 16S rRNA high-throughput sequencing, we found 11 classes of Actinobacteria, with dominant classes of Actinobacteria (36.2%), Thermoleophilia (28.3%), Acidimicrobiia (19.4%). Five classes, 15 orders, 20 families and 36 genera were present in all samples. The dominant generalist genera were
Gaiella
,
Solirubrobacter
,
Nocardioides
,
Mycobacterium
, and
Pseudonocardia
. The actinobacterial community structures were significantly affected by the environment and vegetation type. The diversity of the actinobacterial community in the desert ecosystem was high, and this ecosystem harbored the highest proportion of unclassified sequences, representing rare Actinobacteria. Functional metagenomic prediction, using PICRUSt, indicated that Actinobacteria play an important role in nitrogen cycling in both desert and cultivated farm ecosystems.
D-amino acids are toxic for life on Earth. Yet, they form constantly due to geochemical racemization and bacterial growth (the cell walls of which contain D-amino acids), raising the fundamental ...question of how they ultimately are recycled. This study provides evidence that bacteria use D-amino acids as a source of nitrogen by running enzymatic racemization in reverse. Consequently, when soils are inundated with racemic amino acids, resident bacteria consume D- as well as L-enantiomers, either simultaneously or sequentially depending on the level of their racemase activity. Bacteria thus protect life on Earth by keeping environments D-amino acid free.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Glioma is the most common malignant tumor of the central nervous system and resistance is easily developed to chemotherapy drugs during the treatment process, resulting in high mortality and short ...survival in glioma patients. Novel therapeutic approaches are urgently needed to improve the therapeutic efficacy of chemotherapeutic drugs and to improve the prognosis of patients with glioma. Ferroptosis is a novel regulatory cell death mechanism that plays a key role in cancer, neurodegenerative diseases, and other diseases. Studies have found that ferroptosis-related regulators are closely related to the survival of patients with glioma, and induction of ferroptosis can improve glioma resistance to chemotherapy drugs. Therefore, induction of tumor cell ferroptosis may be an effective therapeutic strategy for glioma. This review summarizes the relevant mechanisms of ferroptosis, systematically summarizes the key role of ferroptosis in the treatment of glioma and outlines the relationship between ferroptosis-related ncRNAs and the progression of glioma.
Introduction T-sheep and H-sheep exhibit different environmental adaptability and production performance. The rumen microbiome has co-evolved with hosts and plays a vital role in nutrient digestion ...and energy metabolism. In our previous study, we found that T-sheep have a higher efficiency in energy metabolism than H-sheep, but the rumen microbial community remains unclear. Methods In this study, we determined the rumen bacterial profile and rumen fermentation parameters to reveal the bacterial profiles and predictive functions among breeds and diets with four different energy levels, as well as the correlation between bacterial profiles and rumen fermentation characteristics. Results The results showed that the rumen total volatile fatty acids (VFAs), acetate, butyrate, total branched-chain VFAs, iso-butyrate, and iso-valerate were higher in T-sheep than H-sheep. The alpha diversity of ruminal bacteria is not affected by dietary energy, but it shows a distinction between the sheep breeds. Specifically, T-sheep rumen bacteria exhibit higher alpha diversity than H-sheep. The beta diversity of ruminal bacteria is not influenced by dietary energy or sheep breeds, indicating similar communities of ruminal bacteria between different diets and sheep breeds. The phyla of Bacteroidetes and Firmicutes predominate in the rumen, with a higher relative abundance of Firmicutes observed in T-sheep than H-sheep. The two most abundant genera in the rumen were Prevotella 1 and Rikenellaceae RC9 gut group. Prevotella 1 is the predominant bacterial genus in the rumen of H-sheep, while the Rikenellaceae RC9 gut group dominates in the rumen of T-sheep. Microbial co-occurrence network analysis reveals that variations in rumen fermentation characteristics result from differences in module abundance, with a higher abundance of VFA-producing modules observed in the rumen of T-sheep. Microbial function prediction analysis showed that dietary energy rarely alters the functional composition of rumen bacteria. However, there were differences in the functions of rumen bacteria between sheep breeds, with T-sheep showing a greater emphasis on energy metabolism-related functions, while H-sheep showed a greater emphasis on protein metabolism-related functions. Discussion These findings provide evidence of the special rumen microbial community that helps T-sheep efficiently obtain energy from low-protein and low-energy diets, enabling them to survive in the extreme environment of the Qinghai–Tibet Plateau.
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•Forest managements reshaped the phyllosphere bacterial community.•The α-diversity increased, and β-diversity decreased.•The community stability and resistance increased, while the ...complexity decreased.•The keystone species altered following forest management.•Select-driven community assembly mechanisms increased in the managed forest.
Research has shown that forest management can improve the post-drought growth and resilience of Qinghai spruce in the eastern Qilian Mountains, located on the northeastern Tibetan Plateau. However, the impact of such management on the tree-associated phyllosphere microbiome is not yet fully understood. This study provides new evidence of positive forest management effects on the phyllosphere microbiome after extreme drought, from the perspectives of community diversity, structure, network inference, keystone species, and assembly processes. In managed Qinghai spruce forest, the α-diversity of the phyllosphere bacterial communities increased, whereas the β-diversity decreased. In addition, the phyllosphere bacterial community became more stable and resistant, yet less complex, following forest management. Keystone species inferred from a bacterial network also changed under forest management. Furthermore, forest management mediated changes in community assembly processes, intensifying the influence of determinacy, while diminishing that of stochasticity. These findings support the hypothesis that management can re-assemble the phyllosphere bacterial community, enhance community stability, and ultimately improve tree growth. Overall, the study highlights the importance of forest management on the phyllosphere microbiome and furnishes new insights into forest conservation from the perspective of managing microbial processes and effects.
Limited knowledge about the variation patterns of bacterial community composition in the sand and vegetative ecosystems confines our understanding regarding the contribution of the sand dune to ...desert areas. In this study, 454 pyrosequencing platforms were adopted to determine the community structure of bacteria and diversity of sand dunes in northeastern Qinghai-Tibet Plateau, China: 50 cm deep, rhizosphere, physical crusts, and biological crusts representing sand and vegetative ecosystems, respectively. The findings revealed significant variation in bacterial diversities and the structure of communities in the sand and vegetative ecosystems. The dominant bacterial phyla of sand and vegetative ecosystems were Firmicutes (47%), Actinobacteria (21%), Proteobacteria (16%), and Bacteroidetes (13%), while
Lactococcus
(50%) was found to be the dominant genus. Furthermore, samples with high alpha-diversity indices (Chao 1 and Shannon) for the vegetative ecosystem have the lowest modularity index and the largest number of biomarkers, with some exceptions. Redundancy analysis exhibited that environmental factors could explain 72% (phyla) and 67% (genera) of the bacterial communities, with EC, TC, and TOC being the major driving factors. This study expands our understanding of bacterial community composition in the desert ecosystem. The findings suggest that variations in the sand and vegetative ecosystems, such as those predicted by environmental factors, may reduce the abundance and diversity of bacteria, a response that likely affects the provision of key ecosystem processes by desert regions.
Coastal salinity typically alters the soil microbial communities, which subsequently affect the biogeochemical cycle of nutrients in the soil. The seasonal variation of the soil fungal communities in ...the coastal area, closely associated with plant population, is poorly understood. This study provides an insight into the fungal community’s variations from autumn to winter and spring to summer at a well-populated area of salt-tolerant
Tamarix chinensis
and beach. The richness and diversity of fungal community were higher in the spring season and lower in the winter season, as showed by high throughput sequencing of the 18S rRNA gene. Ascomycota was the predominant phylum reported in all samples across the region, and higher difference was reported at order level across the seasonal variations. The redundancy analysis suggested that the abundance and diversity of fungal communities in different seasons are mainly correlated to total organic carbon and total nitrogen. Additionally, the saprotrophic and pathotrophic fungi decreased while symbiotic fungi increased in the autumn season. This study provides a pattern of seasonal variation in fungal community composition that further broadens our limited understanding of how the density of the salt-tolerant
T. chinensis
population of the coastal saline soil could respond to their seasonal variations.
Background
This study aimed to determine an optimal machine learning (ML) model for evaluating the preoperative diagnostic value of ultrasound signs of breast cancer lesions for sentinel lymph node ...(SLN) status.
Method
This study retrospectively analyzed the ultrasound images and postoperative pathological findings of lesions in 952 breast cancer patients. Firstly, the univariate analysis of the relationship between the ultrasonographic features of breast cancer morphological features and SLN metastasis. Then, based on the ultrasound signs of breast cancer lesions, we screened ten ML models: support vector machine (SVM), extreme gradient boosting (XGBoost), random forest (RF), linear discriminant analysis (LDA), logistic regression (LR), naive bayesian model (NB), k-nearest neighbors (KNN), multilayer perceptron (MLP), long short-term memory (LSTM), and convolutional neural network (CNN). The diagnostic performance of the model was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC), Kappa value, accuracy, F1-score, sensitivity, and specificity. Then we constructed a clinical prediction model which was based on the ML algorithm with the best diagnostic performance. Finally, we used SHapley Additive exPlanation (SHAP) to visualize and analyze the diagnostic process of the ML model.
Results
Of 952 patients with breast cancer, 394 (41.4%) had SLN metastasis, and 558 (58.6%) had no metastasis. Univariate analysis found that the shape, orientation, margin, posterior features, calculations, architectural distortion, duct changes and suspicious lymph node of breast cancer lesions in ultrasound signs were associated with SLN metastasis. Among the 10 ML algorithms, XGBoost had the best comprehensive diagnostic performance for SLN metastasis, with Average-AUC of 0.952, Average-Kappa of 0.763, and Average-Accuracy of 0.891. The AUC of the XGBoost model in the validation cohort was 0.916, the accuracy was 0.846, the sensitivity was 0.870, the specificity was 0.862, and the F1-score was 0.826. The diagnostic performance of the XGBoost model was significantly higher than that of experienced radiologists in some cases (P<0.001). Using SHAP to visualize the interpretation of the ML model screen, it was found that the ultrasonic detection of suspicious lymph nodes, microcalcifications in the primary tumor, burrs on the edge of the primary tumor, and distortion of the tissue structure around the lesion contributed greatly to the diagnostic performance of the XGBoost model.
Conclusions
The XGBoost model based on the ultrasound signs of the primary breast tumor and its surrounding tissues and lymph nodes has a high diagnostic performance for predicting SLN metastasis. Visual explanation using SHAP made it an effective tool for guiding clinical courses preoperatively.
The Qaidam Basin of the Qinghai–Tibet Plateau is a cold, hyper-arid desert that presents extreme challenges to microbial communities. As little is known about variations between surface and ...subsurface microbial communities, high-throughput DNA sequencing was used in this study to profile bacterial communities of the soil samples collected at different depths in three regions in the Qaidam Basin. The α-diversity indices (Chao, Shannon, and Simpson) indicated that bacterial abundance and diversity were higher in the east and the high-elevation regions compared to the west region. In general,
Firmicutes
was dominant in the west region, while
Proteobacteria
and
Acidobacteria
were dominant in the east and the high-elevation regions. The structure of the bacterial communities differed greatly across regions, being strongly correlated with total organic carbon (TOC) and total nitrogen (TN) content. The differences in bacterial communities between the surface and the subsurface soil samples were smaller than the differences across the regions. Network analyses of environmental factors and bacterial genera indicated significant positive correlations in all regions. Overall, our study provides evidence that TOC and TN are the best predictors of both surface and subsurface bacterial communities across the Qaidam Basin. This study concludes that the bacterial community structure is influenced by both the spatial distance and the local environment, but environmental factors are the primary drivers of bacterial spatial patterns in the Qaidam Basin.
A Gram-staining-positive and aerobic coccus with the ability to degrade petroleum bacterium, designated Y42
T
, was isolated from the Lenghu oil field located in the northern margin of the Qaidam ...Basin. Phylogenetic and signature nucleotides analyses revealed that strain Y42
T
belongs to the genus
Planococcus
. The multiple sequence alignments of 16S rRNA and housekeeping genes showed that strain Y42
T
formed a distinct lineage with the other
Planococcus
clade. The average nucleotide identity (ANI) and DNA–DNA hybridization values (DDH) between strain Y42
T
and the reference strains were 69.5–70.1 and 19.4–21.7%, respectively, which values were below the threshold for species delineation. The major fatty acids of strain Y42
T
were anteiso-C
15:0
. The respiratory quinone was MK-7 (71.8%) as the predominant menaquinone followed the MK-6 (28.2%) and the cell-wall hydrolysates contained LL-diaminopimelic acid. The polar lipid was composed of diphosphatidyl glycerol, phosphatidyl glycerol, phosphoglycolipid, aminophospholipid and four unidentified lipids. The peptidoglycan type was A4α (
l
-Lys–
d
-Glu). The strain Y42
T
possessed larger genome (approximately 4 MB) and revealed obvious differences for the abundance of the COG categories compared with the other
Planococcus
bacteria. Also, the strain Y42
T
also possessed more unique orthologous proteins. The structural characteristics of the strain Y42
T
genome provided a competitive advantage for better survival in petroleum-polluted environments. Combined with the 16S rRNA gene and genome sequence, phenotypic as well as chemotaxonomic characterisations, strain Y42
T
is considered to represent a novel species of the genus
Planococcus
, for which the name
Planococcus lenghuensis
sp. nov. be proposed. The type strain is Y42
T
(= CGMCC 1.15921
T
= JCM 32719
T
).
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