Function Prediction Research Articles

Identification of a Missense Mutation in the FLNC Gene from a Chinese Family with Restrictive Cardiomyopathy.

Restrictive cardiomyopathy (RCM) is a heterogenous cardiomyopathy with various causes, and genetic variants take an important part of the pathogenesis. Whole-exome sequencing (WES) is effective to discover genes that cause genetic diseases. By using WES, we attempted to identify the genetic cause of an RCM family and clarify the clinical diagnosis of the patient and then provide a personalized treatment plan. Blood samples were obtained from the proband and his healthy parents. WES and Sanger sequencing were performed to identify the possible pathogenic gene. Co-segregation analysis was conducted for candidate variants, and the allele frequency was checked in databases including Ensembl, Exome Aggregation Consortium (ExAC) and Human Gene Mutation Database (HGMD). Furthermore, the potential effect of variant was predicted using various-free software such as SIFT, Polyphen-2 and Mutation Taster and the conservation was tested using multiple sequence alignments by ClustalX. The proband was a 20 years old boy with severe heart failure symptoms including dyspnea, massive ascites, edema of both lower limbs and chestcongestion. Echocardiography showed significant biatrial enlargement, normal left ventricular wall thickness and preserved systolic function of both ventricles. A missense mutation in FLNC (c.6451G>A, p.G2151S), encoded filamin-C was detected in proband by WES and Sanger sequencing, while it was not be found in his parents, we supposed that the FLNC mutation (c.6451G>A, p.G2151S) may be a de-novo mutation. Through multiple functional predictions, we found that it is a deleterious mutation and the mutation in filamin-C could alter its structure and normal function, contributing to RCM. Here, an FLNC missense mutation (c.6451G>A, p.G2151S) known to be pathogenic in hypertrophic cardiomyopathy, was found to be associated with RCM, indicating the genetic overlap among cardiomyopathies. This study provides insights into Phenotype-Genotype Correlations of RCM in patients with FLNC mutations.

Dysbiosis and interactions of the salivary bacteriome in obese individuals: A human cross-sectional study

IntroductionThe prevalence of obesity is continually rising worldwide, posing a risk for the development of various serious diseases. The pathogenesis of obesity is complex and recent research suggests a link between obesity and the oral microbiome, though the specific mechanisms remain unclear. Material and methodsWe collected saliva samples from 9 non-obese and 13 obese participants and conducted 16S rRNA sequencing to analyze the differences in oral microbiota between obese and non-obese individuals in terms of microbial abundance, functionality, and interaction networks. ResultsObese participants exhibited a distinct composition of salivary microbiota compared to non-obese participants, with a greater number of ASVs detected and higher α diversity indices. Specifically, Haemophilus, Aggregatibacter, and Actinobacillus were significantly enriched, while Actinomyces showed significant depletion. Functional prediction analysis indicated that biofilm formation pathways were significantly more abundant in the obese group. Random forest regression model analysis identified Bergeyella as the most contributive genus, and interaction network analysis suggested that Bergeyella may function as a bridge node, linking the obese group-enriched genera to the broader microbial community and facilitating the exchange of information and resources. DiscussionOur study suggests that obesity may be closely associated with salivary microbiota dysbiosis and functional changes. Further research is needed to elucidate the causal relationship and underlying molecular mechanisms between obesity and oral microbiota dysbiosis, or to determine if they mutually influence each other.

Demonstrating the key role of Bacillus in poly lactic acid film degradation through statistical analysis and strain screening

Plastic films are extensively utilized in agriculture, construction, and manufacturing, with their annual production reaching staggering figures. Addressing the global plastic pollution crisis is imperative. One promising approach is the augmentation of plastic films degradation through microbial agents. Consequently, we undertook composting experiments employing various plastics, including Polyethylene (PE), Poly lactic acid (PLA), and a treatment without plastic films addition (CK), mixed with kitchen waste. Employing bipartite association networks and difference significance analysis methods, we scrutinized the impact of different plastics on the microbial community within the compost piles. There were significant disparities in the microbial community composition among three composting piles. To pinpoint the key microorganisms responsible for PLA degradation, we conducted a comparative analysis of microbial species present on PLA compost piles and PLA film surfaces (PLAS), utilizing variance analysis, co-occurrence network analysis, and Spearman's correlation analysis. Our findings identified Bacillus as the pivotal microorganism involved in PLA degradation. Furthermore, employing function prediction by PICRUSt 2, we identified K00016 as the crucial gene facilitating PLA degradation by Bacillus. Subsequently, employing strain screening techniques, we isolated a highly effective PLA-degrading bacterium, Bacillus amyloliquefaciens strain ML274. The PLA films degradation rate of ML274 reached 3.18%. and other strains was lower than 3.0%. Thus, Bacillus emerges as the primary microorganism driving PLA degradation, emphasizing the significance of focusing on Bacillus genus microorganisms in the development of plastic-degrading bacterial agents for future endeavors.

Proteome characterization of extracellular vesicles from human milk: Uncovering the surfaceome by a lipid-based protein immobilization technology.

Breast milk is an essential source of nutrition and hydration for the infant. In addition, this highly complex fluid is rich in extracellular vesicles (EVs). Here, we have applied a microfluidic technology, lipid-based protein immobilization (LPI) and liquid chromatography with tandem mass spectrometry (LC-MS/MS) to characterize the proteome of human milk EVs. Mature milk from six mothers was subjected to EV isolation by ultracentrifugation followed by size exclusion chromatography. Three of the samples were carefully characterized; suggesting a subset enriched by small EVs. The EVs were digested by trypsin in an LPI flow cell and in-solution digestion, giving rise to two fractions of peptides originating from the surface proteome (LPI fraction) or the complete proteome (in-solution digestion). LC-MS/MS recovered peptides corresponding to 582 proteins in the LPI fraction and 938 proteins in the in-solution digested samples; 400 of these proteins were uniquely found in the in-solution digested samples and were hence denoted "cargo proteome". GeneOntology overrepresentation analysis gave rise to distinctly different functional predictions of the EV surfaceome and the cargo proteome. The surfaceome tends to be overrepresented in functions and components of relevance for the immune system, while the cargo proteome primarily seems to be associated with EV biogenesis.

InterLabelGO+: unraveling label correlations in protein function prediction.

Accurate protein function prediction is crucial for understanding biological processes and advancing biomedical research. However, the rapid growth of protein sequences far outpaces the experimental characterization of their functions, necessitating the development of automated computational methods. We present InterLabelGO+, a hybrid approach that integrates a deep learning-based method with an alignment-based method for improved protein function prediction. InterLabelGO+ incorporates a novel loss function that addresses label dependency and imbalance and further enhances performance through dynamic weighting of the alignment-based component. A preliminary version of InterLabelGO+ achieved a strong performance in the CAFA5 challenge, ranking sixth out of 1625 participating teams. Comprehensive evaluations on large-scale protein function prediction tasks demonstrate InterLabelGO+'s ability to accurately predict Gene Ontology terms across various functional categories and evaluation metrics. The source code and datasets for InterLabelGO+ are freely available on GitHub at https://github.com/QuanEvans/InterLabelGO. A web-server is available at https://seq2fun.dcmb.med.umich.edu/InterLabelGO/. The software is implemented in Python and PyTorch, and is supported on Linux and macOS.

The microbiota comparative analysis of the characteristics between colorectal adenomatous polyps and normal mucosal intestinal.

The aim of this study is to systematically examine and compare the characteristics distinguishing colorectal adenomatous polyps from normal mucosal intestinal microbiota. A total of 30 specimens were obtained from patients diagnosed with colorectal adenomatous polyps (adenoma group) who underwent endoscopic removal at Wenzhou People's Hospital between September 2021 and November 2021. Concurrently, 30 normal mucosal specimens were collected from patients without adenomatous polyps (control group). Subsequently, microbiome total DNA extraction was carried out, followed by PCR amplification targeting the V3-V4 region of the 16S rDNA. High-throughput sequencing was conducted using the Illumina MiSeq platform. Subsequent to sequencing, bioinformatics analysis was used to assess the diversity, composition, and functional aspects of the intestinal microbiota in both study groups. A notable dissimilarity in the microbiota structure was identified, specifically within the transverse colon, between these two groups ( P < 0.05). Species composition analysis revealed that Escherichia , Fusobacterium , and Bacteroides were predominant bacteria in both groups, with Escherichia and Enterobacter displaying significant differences at the genera level between the control group and the adenoma group ( P < 0.05). Correlation analysis and functional prediction demonstrated substantial disparities in interactions among dominant intestinal microbial genera within patients from both groups. Additionally, it was discovered that the intestinal microbiomes in patients in the adenoma group exhibited a significantly higher pathogenic potential. Upon conducting a comprehensive analysis, it was discerned that the microbiota present in the transverse colon of the control group exhibited distinctive characteristics that may contribute to the maintenance of intestinal health.

DeepSurv landmarking: a deep learning approach for dynamic survival analysis with longitudinal data

Risk prediction models quantify the probability of an individual experiencing specified events, there has significant attention to utilize longitudinal data during follow-up to dynamically update risk estimates. This paper devotes to a dynamic prediction model that combines survival analysis and deep learning techniques, which integrates the deep learning network-DeepSurv into the landmarking framework, to predict time-to-event outcomes with longitudinal covariates. Precisely, at each landmark time point, new information of the dataset is reconstructed, and the DeepSurv network is employed to capture the non-linear relationship between covariates and hazard rates, thereby give the dynamic prediction of survival functions. Furthermore, the importance of different features at each landmark time point is evaluated and ranked to estimate the impact of covariates on predictive outcomes over time. Performances on simulation experiments demonstrate that the proposed DeepSurv landmarking model outperforms state-of-art landmark methods, especially when the dependencies between covariates and the survival process are unknown. Additionally, the model exhibits remarkable dynamic prediction capabilities in the real heart-valve-transplantation-surgery data.

Common carp Peptidoglycan Gecognition Protein 2 (CcPGRP2) alleviates gut dysbiosis induced by Aeromonas hydrophila

ObjectivesPeptidoglycan recognition protein 2 (PGRP2) plays a role in regulating immune defense in fish. Our previous studies found that CcPGRP2 helped maintain the integrity of the intestinal mucosa of carp and could bind and agglutinate bacteria when infected with A. hydrophila. However, its effect on the structure of the microbiota has not yet been clarified. Therefore, it is necessary to explore the effect of CcPGRP2 on the intestinal microbiota structure in fish. MethodsIn the present study, common carp were injected with CcPGRP2 protein intraperitoneally and high-throughput sequencing technology was used to study the difference in intestinal microbiota structure. Firstly, the variations in α- and β-diversity of the intestinal microbiota of common carp in control and treatment groups were tested, and the results indicated that intraperitoneal injection of A. hydrophila significantly reduced the microbial α-diversity (within-samples) and β-diversity (between-samples) in common carp gut samples, but CcPGRP2 protein could alleviate these reduction, no matter in the case of simultaneous injection of CcPGRP2 protein and A. hydrophila or a intermitted injection with first injection of CcPGRP2 and then A. hydrophila after 6 h. Subsequently, the intestinal microbiota structures of common carp on various taxonomic levels were interrogated under the treatments. ResultsThe data revealed that the abundance of intestinal pathogen Aeromonas was reduced when CcPGRP2 was injected in the common carp, and the alleviation effect was better when CcPGRP2 was injected with A. hydrophila at the same time, implying the function of CcPGRP2 in inhibiting intestinal dysbiosis. Moreover, the functional prediction demonstrated the possible physiological shifts and the influences of microbes on the environment after the common carp is injected with A. hydrophila and CcPGRP2. Finally, the bacterial interaction patterns results showed that the groups injected with A. hydrophila were diverted away from the control group in terms of clustering relationship, while the injection of CcPGRP2 could reverse the effect of A. hydrophila and keep the microbial structure closer to that of the control group; meanwhile, the effect of simultaneous injection of A. hydrophila and CcPGRP2 was better than that of intermitted injections. ConclusionsAll the results in this study suggest that the CcPGRP2 could alleviate the internal dysbiosis under pathogen infection, which will provide a foundation for disease resistance breeding.

Theoretical wavelet ℓ1-norm from one-point probability density function prediction

Context. Weak gravitational lensing, which results from the bending of light by matter along the line of sight, is a potent tool for exploring large-scale structures, particularly in quantifying non-Gaussianities. It is a pivotal objective for upcoming surveys. In the realm of current and forthcoming full-sky weak-lensing surveys, convergence maps, which represent a line-of-sight integration of the matter density field up to the source redshift, facilitate field-level inference. This provides an advantageous avenue for cosmological exploration. Traditional two-point statistics fall short of capturing non-Gaussianities, necessitating the use of higher-order statistics to extract this crucial information. Among the various available higher-order statistics, the wavelet ℓ1 -norm has proven its efficiency in inferring cosmology. However, the lack of a robust theoretical framework mandates reliance on simulations, which demand substantial resources and time. Aims. Our novel approach introduces a theoretical prediction of the wavelet ℓ1-norm for weak-lensing convergence maps that is grounded in the principles of large-deviation theory. This method builds upon recent work and offers a theoretical prescription for an aperture mass one-point probability density function. Methods. We present for the first time a theoretical prediction of the wavelet ℓ1-norm for convergence maps that is derived from the theoretical prediction of their one-point probability distribution. Additionally, we explored the cosmological dependence of this prediction and validated the results on simulations. Results. A comparison of our predicted wavelet ℓ1 -norm with simulations demonstrates a high level of accuracy in the weakly nonlinear regime. Moreover, we show its ability to capture cosmological dependence. This paves the way for a more robust and efficient parameter-inference process.

Effects of wildfire on soil microbial communities in karst forest ecosystems of southern Guizhou Province, China.

Wildfires are unpredictable disturbances with profound effects on soil properties and microbial communities within forest ecosystems. However, knowledge of post-fire microbial communities in karst forests remains limited. In this study, microbial amplicon sequencing techniques were employed to investigate the impact of wildfires on the composition, diversity, function, and co-occurrence network of soil microbial communities in karst forest landscapes and to identify the key soil physicochemical factors affecting the post-fire microbial communities. The wildfire affected the fungal community to a greater extent than the bacterial community, with the former shifting from a dominance of Basidiomycota to Ascomycota at the phylum level, while the relative abundance of Actinobacteria increased significantly in the bacterial community. Moreover, the wildfire increased the α-diversity of the microbial community and changed the β-diversity. Network analysis indicated significant reductions in the complexity of microbial community networks and the hub microbiome in burned soils compared to those of unburned soils. Functional predictions indicated an increase in the highly abundant functional taxa of chemoheterotrophic and aerobic chemoheterotrophic bacteria, along with a significant rise in saprotrophic functional fungal taxa following the fire. In addition, soil organic matter, total nitrogen, total phosphorus, and soil water content emerged as key soil physicochemical factors affecting post-fire soil microbial communities in the karst forest. Overall, this study revealed the structural and functional characteristics of soil microbial communities and their key influencing factors after a fire in a karst forest, which will provide a valuable theoretical basis for ecosystem restoration after a wildfire.IMPORTANCEDespite the significant impacts of wildfires on forest ecosystems, most existing studies have largely focused on boreal and Mediterranean coniferous forest types, with limited research on the impacts of coniferous and broadleaf forest types in subtropical karst regions. This study reveals the effects of wildfires on soil microbial communities of coniferous and broadleaf forest types in a karst forest. The results of this study not only improve the understanding of the effects of wildfires on the composition, diversity, function, and network of soil microbial communities but also provide a meaningful theoretical basis for post-fire ecosystem restoration in the karst forest.

Exploration of Bacterial Community Structure Profiling and Functional Characteristics in the Vermicomposting of Wasted Sludge and Kitchen Waste

Nowadays, the enormously growing amount of kitchen waste and wasted sludge has greatly received global attention. Vermicomposting has been represented as an eco-friendly and sustainable alternative for organic waste management. This study utilized kitchen waste generated by the university canteen and excess sludge from municipal wastewater treatment to collaboratively realize waste to resource through vermicomposting with a composting control. The results indicated that the treatment utilizing an equal mass ratio of wasted sludge and kitchen waste (T3) exhibited the greatest reduction in total organic carbon and the highest increase in total nitrogen. Furthermore, the predominant phyla observed were Proteobacteria, Actinobacteriota, Bacteroidetes, and Firmicutes. Functional prediction analysis demonstrated higher relative abundances of β-glucosidase (ascF) and 6-phospho-β-glucosidase (bglA, celF) in the vermicomposting, suggesting that the earthworms essentially enhanced the cellulose degradation. More importantly, the co-occurrence network analysis demonstrated that the vermicomposting showed a stronger interaction between Gordonia and other bacteria, thereby enhancing its ability to degrade macromolecular compounds. In general, the vermicomposting can smoothly and remarkably stabilize the kitchen waste, assisted by excess sludge and sawdust.

PhyKIT: A Multitool for Phylogenomics.

Multiple sequence alignments and phylogenetic trees are rich in biological information and are fundamental to research in biology. PhyKIT is a tool for processing and analyzing the information content of multiple sequence alignments and phylogenetic trees. Here, we describe how to use PhyKIT for diverse analyses, including (i) constructing a phylogenomic supermatrix, (ii) detecting errors in orthology inference, (iii) quantifying biases in phylogenomic data sets, (iv) identifying radiation events or lack of resolution using gene support frequencies, and (v) conducting evolution-based screens to facilitate gene function prediction. Several PhyKIT functions that streamline multiple sequence alignment and phylogenetic processing-such as renaming FASTA entries or tree tips-are also discussed. These protocols demonstrate how simple command-line operations in the unified framework of PhyKIT facilitate diverse phylogenomic data analysis and processing, from supermatrix construction and diagnosis to gaining clues about gene function. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Installing PhyKIT and syntax for usage Basic Protocol 2: Constructing a phylogenomic supermatrix Basic Protocol 3: Detecting anomalies in orthology relationships Basic Protocol 4: Quantifying biases in phylogenomic data matrices and related measures Basic Protocol 5: Identifying polytomies Basic Protocol 6: Assessing gene-gene coevolution as a genetic screen.

Comparative analysis of the intestinal microbiota diversity in wild and farmed Gryllus bimaculatus

Abstract This study aims to investigate the structure and diversity of the intestinal microbiome of Gryllus bimaculatus from wild and farmed environments. Additionally, we sought to identify the core microbes to get information on the microbial diversity of the gut microbiome to the farm condition. We analyzed the microbial community diversity in intestinal samples of both wild and farmed G. bimaculatus using high-throughput sequencing of 16S rRNA gene and ITS rRNA amplicons. Using the PICRUSt2 software, we predicted the functional capabilities of bacterial communities. The analysis indicated significant differences in the diversity of the microbial communities (bacteria) within the gut of crickets under farmed and wild conditions, with notably higher bacterial diversity observed in the gut of farmed crickets compared to those in the wild. The gut bacterial communities exhibited significant similarity across the two conditions, and the variations in diversity are primarily influenced by species with low abundance. Genus-level analysis revealed that the abundance of pathogens, including genera Listeria, Staphylococcus, and Candida, was significantly higher in the gut microbiota of farmed crickets than in the wild ones. By identifying core genera (present in over 80% of the samples), we discovered 19 bacterial genera and 1 fungal genus. The core bacterial genera constituted 60.35% and 87.10% of the cricket’s gut bacterial abundance in farmed and wild environments, respectively. The functional prediction analysis performed using PICRUSt2 identified a significant increase of pathways about “Terpenoids and polyketides metabolism”, and “Infectious disease: bacterial” in the farmed group; as well as a significant decrease in pathways about “Environmental adaptation”, “Development and regeneration”, and the “Nervous system”, compared to the wild group. In conclusion our results showed that the gut microbial community of the G. bimaculatus could be influenced by its environment and diet. However, this influence is primarily manifested in the variation of low-abundance genera, with the gut microbial community remains dominated by a few microbial groups. Therefore, it is speculated that the combination of core and edge species in the gut microbial community of the G. bimaculatus may constitute an effective strategy that not only maintains the core functions of the community but also adapts to environmental changes through the diversity of edge species. The high population density and excessive feeding in the farmed condition could have allowed for the creation of a more diverse gut microbiota for G. bimaculatus, including potential pathogens. Therefore, when breeding G. bimaculatus, the environmental hygiene management should be strengthened to reduce the carrying and transmission of pathogens.

Effects of high-dose glucose oxidase on broiler growth performance, antioxidant function, and intestinal microbiota in broilers.

Glucose oxidase (GOD) has been investigated as a potential additive for enhancing intestinal health and growth performance in poultry. However, limited research exists on the effects of ultra-high doses of GOD in practical poultry production. This study aimed to investigate the impact of high dietary GOD levels on broiler growth performance, antioxidant capacity, and intestinal microbiota. A total of 400 healthy, 1-day-old, slow-growing broiler chickens were randomly assigned to four treatment groups. The control group was fed a standard basal diet, while the other groups (G1, G2, and G3) were fed the basal diet supplemented with 4 U/g, 20 U/g, and 100 U/g of VTR GOD, respectively. The results showed that a dose of 100 U/g GOD significantly improved the final body weight and average daily feed intake (ADFI) (p < 0.05). Additionally, the G3 group exhibited a marked increase in glutathione peroxidase (GSH-Px) activity (p < 0.05), reflecting enhanced antioxidant function. Gut morphology remained intact across all groups, indicating no adverse effects on intestinal barrier integrity. Microbiota analysis revealed significant increases (p < 0.05) in Firmicutes and Verrucomicrobiota abundance at the phylum level in the GOD-supplemented groups. Moreover, GOD treatments significantly increased the abundance of Faecalibacterium, Mucispirllum, and CHKCI001 at the genus level. Metabolic function predictions suggested that high-dose GOD supplementation enriched carbohydrate metabolism, particularly starch and sucrose metabolism. Correlation analysis indicated that Faecalibacterium and CHCKI001 were two bacteria strongly influenced by GOD supplementation and were associated with enhanced growth performance and improved gut health. In conclusion, high-dose GOD supplementation had no adverse effects and demonstrated significant benefits, promoting both growth performance and gut health in broilers.

Microbe-aided thermophilic composting accelerates manure fermentation.

Aerobic composting is a key strategy to the sustainable use of livestock manure, which is however constrained by the slow kinetics. Microbe-aided thermophilic composting provides an attractive solution to this problem. In this study, we identified key thermophilic bacteria capable of accelerating manure composting based on the deciphering of manure bacterial community evolution in a thermophilic system. High-throughput sequencing showed a significant evolution of manure bacterial community structure with the increasing heating temperature. Firmicutes were substantially enriched by the heating, particularly some known thermotolerant bacterial species, such as Novibacillus thermophiles, Bacillus thermolactis, and Ammoniibacillus agariperforans. Correspondingly, through function prediction, we found bacterial taxa with cellulolytic and xylanolytic activities were significantly higher in the thermophilic process relative to the initial stage. Subsequently, a total of 47 bacteria were isolated in situ and their phylogenetic affiliation and degradation capacity were determined. Three isolates were back inoculated to the manure, resulting in shortened composting process from 5 to 3 days with Germination Index increased up to 134%, and improved compost quality particularly in wheat growth promoting. Comparing to the mesophilic and thermophilic Bacillus, the genomes of the three isolates manifested some features similar to the thermophiles, including smaller genome size and mutation of specific genes that enhance heat tolerance. This study provide robust evidence that microbe-aided thermophilic composting is capable to accelerate manure composting and improve the quality of compost, which represents a new hope to the sustainable use of manure from the meat industry.

Evolutionary-Scale Enzymology Enables Biochemical Constant Prediction Across a Multi-Peaked Catalytic Landscape.

Quantitatively mapping enzyme sequence-catalysis landscapes remains a critical challenge in understanding enzyme function, evolution, and design. Here, we expand an emerging microfluidic platform to measure catalytic constants- k cat and K M -for hundreds of diverse naturally occurring sequences and mutants of the model enzyme Adenylate Kinase (ADK). This enables us to dissect the sequence-catalysis landscape's topology, navigability, and mechanistic underpinnings, revealing distinct catalytic peaks organized by structural motifs. These results challenge long-standing hypotheses in enzyme adaptation, demonstrating that thermophilic enzymes are not slower than their mesophilic counterparts. Combining the rich representations of protein sequences provided by deep-learning models with our custom high-throughput kinetic data yields semi-supervised models that significantly outperform existing models at predicting catalytic parameters of naturally occurring ADK sequences. Our work demonstrates a promising strategy for dissecting sequence-catalysis landscapes across enzymatic evolution and building family-specific models capable of accurately predicting catalytic constants, opening new avenues for enzyme engineering and functional prediction.

The impact of pine wilt disease on the endophytic microbial communities structure of Pinus koraiensis.

Pine Wilt Disease (PWD) is a devastating pine tree disease characterized by rapid onset, high mortality rate, quick spread, and difficulty in control. Plant microbiome plays a significant role in the development of PWD. However, the endophytic microbial communities of Pinus koraiensis infected by pine wood nematode (PWN) Bursaphelenchus xylophilus remain largely unexplored. In this study, we analyzed the structural changes of endophytic communities of P. koraiensis after infection by the PWN using high-throughput sequencing technology. The results showed that the community structure underwent significant changes as the degree of PWN infection intensified. The diversity and abundance of endophytic fungi in P. koraiensis increased, while those of endophytic bacteria in P. koraiensis decreased during the infection process. Meanwhile, the abundance of some dominant microorganisms has also changed, including species such as Graphilbum and Pseudoalteromonas. Functional prediction analysis showed that the functional composition of endophytic fungi in P. koraiensis was significantly different across the development of PWD, while the composition of endophytic bacteria remained essentially similar. The results indicated that PWN infection had a significant impact on the structure, diversity, abundance, and functional gene composition of endophytic microbial communities in P. koraiensis, and most of the main endophytic microbial groups tended to coordinate with each other. This work provides a better understanding of the changes in endophytic community structure and function caused by PWD infection of P. koraiensis, which may benefit the exploration of potential endophytes for PWN biocontrol.

Gender and age-related variations in rumen fermentation and microbiota of Qinchuan cattle.

Our study aimed to investigate the gender and age-related variations in rumen fermentation, serum metabolites, and microbiota in Qinchuan cattle. A total of 38 Qinchuan beef cattle were selected and maintained on a uniform diet for three months. Rumen fluid and blood samples were collected to determine rumen fermentation, serum metabolites, and microbial 16S rRNA sequencing. The results revealed that the concentration of rumen butyrate in female Qinchuan cattle was significantly higher than in males (P<0.05). Isobutyrate, butyrate, and isovalerate exhibited significant age-related differences. Females exhibited lower serum GLU and higher TG, NEFA levels compared to males (P<0.05). Serum ALB and UREA levels increased with age (P<0.05). Furthermore, the alpha diversity of rumen bacteria improved with age (P<0.05), with no gender differences observed. Males had higher relative abundances of Bacteroidota, Verrucomicrobiota, and Cyanobacteria, while females had higher Firmicutes and Desulfobacterota (P<0.05). The cellulose-degrading genus Ruminococcus and propionate-producing genus Succiniclasticum were more abundant in females, whereas the anti-inflammatory genus Lachnospiraceae_NK4A136_group and the hemicellulose-degrading genus Prevotella were more abundant in males (P<0.05). Age-related differences in bacteria were found in Pseudobutyrivibrio and several members of the Lachnospiraceae. Functional prediction indicated that "Amino acid metabolism" and "Lipid metabolism" were mainly enriched in females, whereas "Carbohydrate metabolism" and "Glycan biosynthesis and metabolism" were enriched in males (P<0.05). RDA analysis highlighted butyrate as a key factor influencing the rumen bacterial community. NK4A214_group and Ruminococcus were positively correlated with butyrate, while Prevotella and Pseudobutyrivibrio were negatively correlated with butyrate (P<0.05). We observed a significant improvement in the diversity and stability of rumen microbiota as age increased. Ruminococcus, NK4A214_group, and Prevotella were likely contributors to variations in energy utilization and fat deposition between male and female Qinchuan cattle.

Changes functional prediction of ear canal flora in chronic bacterial otitis externa.

To investigate ear canal microflora's structure, composition and function in patients with chronic bacterial otitis externa. A case-control study design method was used to collect the ear canal secretions from 14 patients with chronic bacterial external otitis (CB group) and 14 healthy controls (H group) treated in the Department of Otolaryngology and Head and Neck Surgery in the First Affiliated Hospital of Hainan Medical University. 16S rRNA high-throughput sequencing technology was used to sequence the ear canal microflora's V3 ~ V4 region gene amplification products in the participating population. The α diversity of ear canal microflora in 2 groups was analyzed. Based on the weighted Unifrac distance, principal coordinate analysis was performed to compare the β diversity of ear tract microflora between the two groups. The differences in ear microflora at phylum and genus levels were analyzed. PICRUSt2 function prediction and BugBase phenotype prediction were also performed. α diversity analysis showed that the diversity and richness of auricular microflora in the CB group were significantly lower than those in the H group. β diversity analysis showed that there were some differences between the two groups. At the phylum level, the relative abundance of Bdellovibrionota, Campylobacterota, and WPS-2 in the microbiota of patients in the CB group was significantly lower than that in the H group, and the differences were statistically significant. At the genus level, the relative abundance of Pseudomonas, Acinetobacter, Pelomonas, Sphingomonas, Bradyrhizobium, Brevundimonas, Enhydrobacter, Actinomyces, Paracoccus and Chryseobacterium in the ear canal of Group H is significantly higher than that of Group CB. Functional prediction of PICRUSt2 suggests that amino acid biosynthesis and bacterial microbiota may be related. In BugBase phenotypic prediction, the contribution of aerobic phenotype in group CB was significantly lower than that in group H. The diversity and abundance of the ear canal flora of patients with chronic bacterial otitis externa were significantly lower than those of the healthy population, and their bacterial colony structure was significantly altered. Dysbiosis of the ear canal flora may be an important cause of chronic bacterial otitis externa.

The Pb capture mechanism of soil prophylactic agents prepared from phosphorus tailings and the influence of phosphorus speciation on its slow-release mechanism

This research activated phosphorus tailings to prepare a high‑phosphorus core (HPC) for multi-species composite slow-release heavy metal soil prophylactic agents (MCP), aiming to extend the slow-release period of MCP and enhance the efficiency of Pb stabilization. During the preparation of HPC, the proportion of non-apatitic inorganic phosphorus (NAIP) and apatite phosphorus (AP) continuously decreased with increasing polymerization temperature. At 400 °C, polyphosphates (PP) began to form, reaching 74.26 % at 600 °C. Initially, the rapidly soluble NAIP remained the major component of HPC, but the proportion of AP increased with higher polymerization temperatures, reaching 40.8 % at 600 °C. After 120 days of cultivation with four MCPs (MCP 300-21, MCP 400-12, MCP 500-14, MCP 600-14), the total soil phosphorus (TSP), soil organic matter (SOM), and Pb stabilization capacity of the cultivated soil showed significant improvements, reaching maximum values of 2.39 mg/g, 38.16 mg/g, and 45.4 mg/g, respectively, which are 9.9, 4.4, and 5.9 times higher than those of the CK soil. KEGG (Kyoto Encyclopedia of Genes and Genomes) functional prediction analysis indicated that MCPs contribute directly or indirectly to the forms and chemical stability of Pb by stimulating soil physiological and biochemical processes. This research proposes a novel approach for using phosphates in soil heavy metal management strategies and provides new insights into the mechanisms of heavy metal stabilization in soil using environmental functional materials.