Analysis of endophytic bacterial diversity in seeds of different genotypes of cotton and the suppression of Verticillium wilt pathogen infection by a synthetic microbial community.

BACKGROUND: In agricultural production, fungal diseases significantly impact the yield and quality of cotton (Gossypium spp.) with Verticillium wilt posing a particularly severe threat. RESULTS: This study is focused on investigating the effectiveness of endophytic microbial communities present in the seeds of disease-resistant cotton genotypes in the control of cotton Verticillium wilt. The technique of 16S ribosomal RNA (16S rRNA) amplicon sequencing identified a significant enrichment of the Bacillus genus in the resistant genotype Xinluzao 78, which differed from the endophytic bacterial community structure in the susceptible genotype Xinluzao 63. Specific enriched strains were isolated and screened from the seeds of Xinluzao 78 to further explore the biological functions of seed endophytes. A synthetic microbial community (SynCom) was constructed using the broken-rod model, and seeds of the susceptible genotype Xinluzao 63 in this community that had been soaked with the SynCom were found to significantly control the occurrence of Verticillium wilt and regulate the growth of cotton plants. Antibiotic screening techniques were used to preliminarily identify the colonization of strains in the community. These techniques revealed that the strains can colonize plant tissues and occupy ecological niches in cotton tissues through a priority effect, which prevents infection by pathogens. CONCLUSION: This study highlights the key role of seed endophytes in driving plant disease defense and provides a theoretical basis for the future application of SynComs in agriculture.

Use of Raman spectroscopy to study rat lung tissues for distinguishing asphyxia from sudden cardiac death.

Determining asphyxia as the cause of death is crucial but is based on an exclusive strategy because it lacks sensitive and specific morphological characteristics in forensic practice. In some cases where the deceased has underlying heart disease, differentiation between asphyxia and sudden cardiac death (SCD) as the primary cause of death can be challenging. Herein, Raman spectroscopy was employed to detect pulmonary biochemical differences to discriminate asphyxia from SCD in rat models. Thirty-two rats were used to build asphyxia and SCD models, with lung samples collected immediately or 24 h after death. Twenty Raman spectra were collected for each lung sample, and 640 spectra were obtained for further data preprocessing and analysis. The results showed that different biochemical alterations existed in the lung tissues of the rats that died from asphyxia and SCD and could be used to distinguish between the two causes of death. Moreover, we screened and used 8 of the 11 main differential spectral features that maintained their significant differences at 24 h after death to successfully determine the cause of death, even with decomposition and autolysis. Eventually, seven prevalent machine learning classification algorithms were employed to establish classification models, among which the support vector machine exhibited the best performance, with an area under the curve value of 0.9851 in external validation. This study shows the promise of Raman spectroscopy combined with machine learning algorithms to investigate differential biochemical alterations originating from different deaths to aid determining the cause of death in forensic practice.

Associations between impulsivity and fecal microbiota in individuals abstaining from methamphetamine.

INTRODUCTION: Methamphetamine (MA) abuse is a major public problem, and impulsivity is both a prominent risk factor and a consequence of addiction. Hence, clarifying the biological mechanism of impulsivity may facilitate the understanding of addiction to MA. The microbiota-gut-brain axis was suggested to underlie a biological mechanism of impulsivity induced by MA. METHODS: We therefore recruited 62 MA addicts and 50 healthy controls (HCs) to investigate the alterations in impulsivity and fecal microbiota and the associations between them in the MA group. Thereafter, 25 MA abusers who abstained from MA for less than 3 months were followed up for 2 months to investigate the relationship between impulsivity and microbiota as abstinence became longer. 16S rRNA sequencing was conducted for microbiota identification. RESULTS: Elevated impulsivity and dysbiosis characterized by an increase in opportunistic pathogens and a decrease in probiotics were identified in MA abusers, and both the increased impulsivity and disrupted microbiota tended to recover after longer abstinence from MA. Impulsivity was related to microbiota, and the effect of MA abuse on impulsivity was mediated by microbiota. CONCLUSION: Our findings potentially highlighted the importance of abstention and implicated the significant role of the microbiota-gut-brain axis in the interrelationship between microbiota and behaviors, as well as the potential of microbiota as a target for intervention of impulsivity.

The gut microbiota as a potential biomarker for methamphetamine use disorder: evidence from two independent datasets.

Background: Methamphetamine use disorder (MUD) poses a considerable public health threat, and its identification remains challenging due to the subjective nature of the current diagnostic system that relies on self-reported symptoms. Recent studies have suggested that MUD patients may have gut dysbiosis and that gut microbes may be involved in the pathological process of MUD. We aimed to examine gut dysbiosis among MUD patients and generate a machine-learning model utilizing gut microbiota features to facilitate the identification of MUD patients. Method: Fecal samples from 78 MUD patients and 50 sex- and age-matched healthy controls (HCs) were analyzed by 16S rDNA sequencing to identify gut microbial characteristics that could help differentiate MUD patients from HCs. Based on these microbial features, we developed a machine learning model to help identify MUD patients. We also used public data to verify the model; these data were downloaded from a published study conducted in Wuhan, China (with 16 MUD patients and 14 HCs). Furthermore, we explored the gut microbial features of MUD patients within the first three months of withdrawal to identify the withdrawal period of MUD patients based on microbial features. Results: MUD patients exhibited significant gut dysbiosis, including decreased richness and evenness and changes in the abundance of certain microbes, such as Proteobacteria and Firmicutes. Based on the gut microbiota features of MUD patients, we developed a machine learning model that demonstrated exceptional performance with an AUROC of 0.906 for identifying MUD patients. Additionally, when tested using an external and cross-regional dataset, the model achieved an AUROC of 0.830. Moreover, MUD patients within the first three months of withdrawal exhibited specific gut microbiota features, such as the significant enrichment of Actinobacteria. The machine learning model had an AUROC of 0.930 for identifying the withdrawal period of MUD patients. Conclusion: In conclusion, the gut microbiota is a promising biomarker for identifying MUD and thus represents a potential approach to improving the identification of MUD patients. Future longitudinal studies are needed to validate these findings.

Enrichment and ecological risks of microplastics in mangroves of southern Hainan Island, China.

Mangroves have recently been identified as one of the most threatened ecosystems by microplastics (MPs) pollution from terrestrial and marine sources, while little is known regarding the MPs enrichment, influencing factors and associated ecological risks in mangroves. The present investigation aims to evaluate the accumulation, characteristics, and ecological risks of MPs in various environmental matrices from three mangroves of southern Hainan Island during dry and wet seasons. The results revealed the prevalence of MPs pollution in the surface seawater and sediment from all studied mangroves during two seasons, where the highest MPs abundance was observed at Sanyahe mangrove. The abundance of MPs varied considerably in surface seawater by seasons and were distinctly modulated by rhizosphere effect. The characteristics of MPs also exhibited some pronounced variations across mangroves, seasons and environmental compartments, but the detected MPs were dominated by fiber-shaped, transparent-colored, and smaller-sized (100-500 µm) MPs. The most prevalent polymer types were polypropylene, polyethylene terephthalate and polyethylene. Further analyses revealed positive correlations between MPs abundance and contents of nutrient salts in surface seawater but negative relationships between MPs abundance and water physicochemical properties, including temperature, salinity, pH and conductivity (p < 0.05). The joint use of three evaluation models indicated MPs posed varying degrees of ecological risks to all studied mangroves, whereas Sanyahe mangrove exhibited the highest ecological risk of MPs pollution. This study provided new insights into the spatial-seasonal variations, influencing factors and risk assessment of MPs in mangroves, which would be helpful for source tracing, pollution monitoring and policy formulation.

Tissue accumulation of polystyrene microplastics causes oxidative stress, hepatopancreatic injury and metabolome alterations in Litopenaeus vannamei.

Microplastics (MPs) pose one of the major environmental threats to marine organisms and ecosystems on a global scale. Although many marine crustaceans are highly susceptible to MPs pollution, the toxicological effects and mechanisms of MPs on crustaceans are poorly understood. The current study focused on the impacts of MPs accumulation in shrimp Litopenaeus vannamei at the behavioral, histological and biochemical levels. The results demonstrated the accumulation of polystyrene MPs in various organs of L. vannamei, with highest MPs abundance in the hepatopancreas. The MPs accumulated in shrimp caused growth inhibition, abnormal swimming behavior and reduced swimming performance of L. vannamei. Following MPs exposure, oxidative stress and lipid peroxidation were also observed, which were strongly linked to attenuated swimming activity of L. vannamei. The above MPs-induced disruption in balance of antioxidant system triggered the hepatopancreatic damage in L. vannamei, which was exacerbated with increasing MPs concentrations (from 0.02 to 1 mg L-1). Furthermore, metabolomics revealed that MPs exposure resulted in alterations of metabolic profiles and disturbed glycolysis, lipolysis and amino acid metabolism pathways in hepatopancreas of L. vannamei. This work confirms and expands the knowledge on the sublethal impacts and toxic modes of action of MPs in L. vannamei.

Dissecting the microbial community structure of internal organs during the early postmortem period in a murine corpse model.

BACKGROUND: Microorganisms distribute and proliferate both inside and outside the body, which are the main mediators of decomposition after death. However, limited information is available on the postmortem microbiota changes of extraintestinal body sites in the early decomposition stage of mammalian corpses. RESULTS: This study investigated microbial composition variations among different organs and the relationship between microbial communities and time since death over 1 day of decomposition in male C57BL/6 J mice by 16S rRNA sequencing. During 1 day of decomposition, Agrobacterium, Prevotella, Bacillus, and Turicibacter were regarded as time-relevant genera in internal organs at different timepoints. Pathways associated with lipid, amino acid, carbohydrate and terpenoid and polyketide metabolism were significantly enriched at 8 h than that at 0.5 or 4 h. The microbiome compositions and postmortem metabolic pathways differed by time since death, and more importantly, these alterations were organ specific. CONCLUSION: The dominant microbes differed by organ, while they tended toward similarity as decomposition progressed. The observed thanatomicrobiome variation by body site provides new knowledge into decomposition ecology and forensic microbiology. Additionally, the microbes detected at 0.5 h in internal organs may inform a new direction for organ transplantation.

Kingella pumchi sp. nov., an organism isolated from human vertebral puncture tissue.

A Gram-negative, non-motile rod and strictly aerobic bacterium, designated as 18B16333T, was isolated from vertebral puncture tissue of a patient at Peking union medical college hospital in China. Growth occurred in NaCl concentrations of 0-1% (w/v) (optimum growth at 0% NaCl), at temperatures of 25-40 °C (optimum growth at 37 °C) and at pH 6.0-9.0 (optimum growth at pH 8.0). Diphosphatidylglycerol, phosphatidylglycerol and phosphatidylethanolamine were the predominant polar lipids, and the major fatty acids were C16:0, C18:1 ω7c/C18:1 ω6c and C16:1 ω7c/C16:1 ω6c. Phylogenetic analysis based on 16S rRNA gene sequence comparisons indicated that strain 18B16333T was most closely related to Kingella potus CCUG 49773 T (97.3%, 16S rRNA gene sequence identity) and Neisseria bacilliformis CCUG 50858 T (96.8%). The ANI values between strain 18B16333T and the type strains K. potus CCUG 49773 T, N. bacilliformis CCUG 50858 T, Kingella kingae CCUG 352 T and Neisseria gonorrhoeae CCUG 26876 T were 77.3%, 79.1%, 72.1% and 75.4%, respectively. The dDDH values between strain 18B16333T and the four reference strains mentioned above were 24.8%, 26.9%, 24.2% and 20.7%. Further core gene analysis distinctively clustered strain 18B16333T with four Kingella species but not with Neisseria species. Based on the phenotypic, chemotaxonomic, and phylogenetic properties, strain 18B16333T represents a novel species of the genus Kingella, for which the name Kingella pumchi sp. nov. is proposed. The type strain is Kingella pumchi 18B16333T (= CICC 24913 T = CCUG 75125 T).

Efficient removal of Cr(VI) by a 3D Z-scheme TiO2-ZnxCd1-xS graphene aerogel via synergy of adsorption and photocatalysis under visible light.

Efficient and robust photocatalysts for environmental pollutants removal with outstanding stability have great significance. Herein, we report a kind of three dimensional (3D) photocatalyst presented as Z-scheme heterojunction, which combining TiO2 and ZnxCd1-xS with graphene aerogel to contrast TiO2-ZnxCd1-xS graphene aerogel (TSGA, x=0.5) through a moderate hydrothermal process. The as-prepared Z-scheme TSGA was used to remove aqueous Cr(VI) via a synergistic effect of adsorption and visible light photocatalysis. The adsorption equilibrium can be reached about 40 min, then after about 30 min irradiation under visible light (wavelength (λ) > 420 nm) the removal rate of Cr(VI) almost reached 100%, which is much better than the performance of pristine TiO2 and Zn0.5Cd0.5S, as well as TiO2 graphene aerogel (TGA) and Zn0.5Cd0.5S graphene aerogel (SGA). The virulent Cr(VI) was reduced to Cr(III) with hypotoxicity after photocatalysis on TSGA, meanwhile the as-synthesized TSGA presented a good stability and reusability. The reduced graphene oxide (rGO) sheets between TiO2 and Zn0.5Cd0.5S played a role as charge transfer mediator, promoting the photoinduced electrons transfer and photocatalysis ability of TSGA was enhanced significantly. Hence, such photocatalyst exhibits a potential application on removing heavy metals with high efficiency and stability from polluted aqueous environment.

Saussurea involucrata PIP2;4 improves growth and drought tolerance in Nicotiana tabacum by increasing stomatal density and sensitivity.

Aquaporins, the major facilitators of water transport across membranes, are involved in growth and development and adaptation to drought stress in plants. In this study, a plasma membrane intrinsic protein (SiPIP2;4) was cloned from Saussurea involucrata, a cold-tolerant hardy herb. The expression of SiPIP2;4 increased the stomatal density and sensitivity of tobacco (Nicotiana tabacum), thus, affecting the plant's growth and resistance to the diverse water environment. The higher stomatal density under well-watered conditions effectively promoted the photosynthetic rate, which led to the rapid growth of transgenic lines. The stomata in the transgenic lines responded more sensitively to the vapor pressure deficit than the wild-type under different levels of ambient humidity. Their stomatal apertures positively correlated with the ambient humidity. Under drought conditions, the overexpression of SiPIP2;4 promoted rapid stomatal closure, reduced water dissipation, and enhanced drought tolerance. These results indicate that SiPIP2;4 regulates the density and sensitivity of plant stomata, thus, playing an important role in balancing plant growth and stress tolerance. This suggests that SiPIP2;4 has the potential to serve as a genetic resource for crop improvement.

Accurate identification of traumatic lung injury (TLI) by ATR-FTIR spectroscopy combined with chemometrics.

Traumatic lung injury (TLI), which is a common mechanical injury, is receiving increasing attention because of its serious hazards. In forensic practices, accurately identifying TLI is of great importance for investigations and case trials. The main goal of this research was to identify TLI utilizing attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy in combination with chemometrics. The macroscopic appearance of lung tissue showed that identifying TLI in lung tissue at the decomposition stage is not feasible by only visualization, and significant pulmonary hypostasis was observed in the lungs regardless of whether the lung tissue was injured. Average spectra and principal component analysis (PCA) suggested that the biochemical difference between injured lung tissue samples from the TLI group and noninjured lung tissue samples from the negative control group was mainly attributed to the different structures and contents of proteins. Partial least squares discriminant analysis (PLS-DA) was then utilized to identify TLI with an accuracy of 96.4% and 98.6% based on the training set and the test set, respectively. Next, we focused on samples that were misclassified in the model and proposed that the misclassification could be caused by the pulmonary hypostasis effect. Therefore, two additional PCA and PLS-DA models were created to identify the pulmonary hypostatic areas between the TLI group and the negative control group and the nonpulmonary hypostatic areas between the TLI group and the negative control group. The PCA results indicated that the biochemical difference between the two groups was still associated with proteins, and the two PLS-DA models achieved 100% accuracy based on both the training and test sets. This result indicated that when pulmonary hypostasis was considered and the lung tissue was divided into pulmonary hypostatic areas and nonpulmonary hypostatic areas for separate comparisons, TLI identification was achieved with a greater accuracy than that obtained when the two areas were combined. This research confirms that the combined application of ATR-FTIR spectroscopy and chemometrics can be utilized to accurately identify TLI.

Vertical transfer and functional characterization of cotton seed core microbiome.

Introduction: Microbiome within plant tissues is pivotal for co-evolution with host plants. This microbiome can colonize the plant, with potential transmission via seeds between parents and offspring, affecting seedling growth and host plant adaptability to the environment. Methods: We employed 16S rRNA gene amplicon analysis to investigate the vertical distribution of core microbiome in cotton seeds across ecological niches [rhizosphere, root, stem, leaf, seed and seed-P (parental seed)] of the three cotton genotypes. Results: The findings demonstrated a significant decrease in microbiome diversity and network complexity from roots, stems, and leaves to seeds. The microenvironment exerted a more substantial influence on the microbiome structure of cotton than the genotypes. The core endophytic microorganisms in cotton seeds comprised 29 amplicon sequence variants (ASVs) affiliated with Acidimicrobiia, Alphaproteobacteria, Bacilli, Bacteroidia, Clostridia, Gammaproteobacteria, and unclassified_Proteobacteria. These vertically transmitted taxa are widely distributed in cotton plants. Through 16S rRNA gene-based function prediction analysis of the cotton microbiome, we preliminarily understood that there are potential differences in metabolic capabilities and phenotypic traits among microbiomes in different microhabitats. Discussion: In conclusion, this study demonstrated the crucial role of the microenvironment in influencing the cotton microbiome and offered insights into the structures and functions of the cotton seed microbiome, facilitating future crop yield enhancement through core seed microbiome regulation.

Distinguishing Asphyxia from Sudden Cardiac Death as the Cause of Death from the Lung Tissues of Rats and Humans Using Fourier Transform Infrared Spectroscopy.

The ability to determine asphyxia as a cause of death is important in forensic practice and helps us to judge whether a case is criminal. However, in some cases where the deceased has underlying heart disease, death by asphyxia cannot be determined by traditional autopsy and morphological observation under a microscope because there are no specific morphological features for either asphyxia or sudden cardiac death (SCD). Here, Fourier transform infrared (FTIR) spectroscopy was employed to distinguish asphyxia from SCD. A total of 40 lung tissues (collected at 0 h and 24 h postmortem) from 20 rats (10 died from asphyxia and 10 died from SCD) and 16 human lung tissues from 16 real cases were used for spectral data acquisition. After data preprocessing, 2675 spectra from rat lung tissues and 1526 spectra from human lung tissues were obtained for subsequent analysis. First, we found that there were biochemical differences in the rat lung tissues between the two causes of death by principal component analysis and partial least-squares discriminant analysis (PLS-DA), which were related to alterations in lipids, proteins, and nucleic acids. In addition, a PLS-DA classification model can be built to distinguish asphyxia from SCD. Second, based on the spectral data obtained from lung tissues allowed to decompose for 24 h, we could still distinguish asphyxia from SCD even when decomposition occurred in animal models. Nine important spectral features that contributed to the discrimination in the animal experiment were selected and further analyzed. Third, 7 of the 9 differential spectral features were also found to be significantly different in human lung tissues from 16 real cases. A support vector machine model was finally built by using the seven variables to distinguish asphyxia from SCD in the human samples. Compared with the linear PLS-DA model, its accuracy was significantly improved to 0.798, and the correct rate of determining the cause of death was 100%. This study shows the application potential of FTIR spectroscopy for exploring the subtle biochemical differences resulting from different death processes and determining the cause of death even after decomposition.

An Emerging Strategy for Muscle Evanescent Trauma Discrimination by Spectroscopy and Chemometrics.

Trauma is one of the most common conditions in the biomedical field. It is important to identify it quickly and accurately. However, when evanescent trauma occurs, it presents a great challenge to professionals. There are few reports on the establishment of a rapid and accurate trauma identification and prediction model. In this study, Fourier transform infrared spectroscopy (FTIR) and microscopic spectroscopy (micro-IR) combined with chemometrics were used to establish prediction models for the rapid identification of muscle trauma in humans and rats. The results of the average spectrum, principal component analysis (PCA) and loading maps showed that the differences between the rat muscle trauma group and the rat control group were mainly related to biological macromolecules, such as proteins, nucleic acids and carbohydrates. The differences between the human muscle trauma group and the human control group were mainly related to proteins, polysaccharides, phospholipids and phosphates. Then, a partial least squares discriminant analysis (PLS-DA) was used to evaluate the classification ability of the training and test datasets. The classification accuracies were 99.10% and 93.69%, respectively. Moreover, a trauma classification and recognition model of human muscle tissue was constructed, and a good classification effect was obtained. The classification accuracies were 99.52% and 91.95%. In conclusion, spectroscopy and stoichiometry have the advantages of being rapid, accurate and objective and of having high resolution and a strong recognition ability, and they are emerging strategies for the identification of evanescent trauma. In addition, the combination of spectroscopy and stoichiometry has great potential in the application of medicine and criminal law under practical conditions.

Synthesis and in vitro synergistic antifungal activity of analogues of Panax stipulcanatus saponin against fluconazole-resistant Candida albicans.

Oleanolic acid 3-O-ß-d-glucopyranosyl-(1 â†’ 3)-ß-d-glucopyranoside (1) and oleanolic acid 3-O-ß-d-glucopyranosyl-(1 â†’ 3)-[α-l-arabinofuranosyl-(1 â†’ 4)]-ß-d-glucopyranoside (2), novel Panax stipulcanatus saponin analogues, were synthesized for the first time starting from commercially available oleanolic acid, d-glucose, and L-(+)-arabinose. Glycosyl N-phenyltrifluoroacetimidates as donors and two-step consecutive glycosylation reactions are crucial in the synthesis. In vitro antifungal activity results indicated that analogue 2 combined with fluconazole showed synergistic antifungal activity against fluconazole-resistant Candida albicans, with MIC50 values 31.80 µg/mL and FICI values 0.32. We also found that intermediate compounds 16 and 17 revealed synergistic antifungal activity against susceptible Candida albicans when combined with fluconazole, with MIC50 values 1.43 µg/mL and 1.59 µg/mL, FICI values 0.29 and 0.32, respectively.

Species identification of teeth of human and non-human.

Species identification is very important in forensic science case. However, the existing methods in forensic practice to identifying the species of bone and teeth are not objective, accurate or brief enough. We have reported the classification of bone species by Fourier transform infrared (FT-IR) and chemometric methods. Here we further use this method to realize the rapid detection of teeth species. 50 teeth samples from human and non-human (bovine, dog, rat, rabbit) were used in this study. Uncontrolled environment conditions were set to simulate real forensic casework. Teeth sample were prepared by grinding powder and pressed into KBr tablet, then the spectral data were collected. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used in the study. The internal and external validations of PLS-DA results were 97.1% and 93.3% accuracy, respectively. The results illustrate that FT-IR spectroscopy be used as a practical tool to identify species of unknown teeth.

Analysis of Postmortem Intestinal Microbiota Successional Patterns with Application in Postmortem Interval Estimation.

Microorganisms play a vital role in the decomposition of vertebrate remains in natural nutrient cycling, and the postmortem microbial succession patterns during decomposition remain unclear. The present study used hierarchical clustering based on Manhattan distances to analyze the similarities and differences among postmortem intestinal microbial succession patterns based on microbial 16S rDNA sequences in a mouse decomposition model. Based on the similarity, seven different classes of succession patterns were obtained. Generally, the normal intestinal flora in the cecum was gradually decreased with changes in the living conditions after death, while some facultative anaerobes and obligate anaerobes grew and multiplied upon oxygen consumption. Furthermore, a random forest regression model was developed to predict the postmortem interval based on the microbial succession trend dataset. The model demonstrated a mean absolute error of 20.01 h and a squared correlation coefficient of 0.95 during 15-day decomposition. Lactobacillus, Dubosiella, Enterococcus, and the Lachnospiraceae NK4A136 group were considered significant biomarkers for this model according to the ranked list. The present study explored microbial succession patterns in terms of relative abundances and variety, aiding in the prediction of postmortem intervals and offering some information on microbial behaviors in decomposition ecology.

The Novel Interplay between Commensal Gut Bacteria and Metabolites in Diet-Induced Hyperlipidemic Rats Treated with Simvastatin.

Hyperlipidemia is one kind of metabolic syndrome for which the treatment commonly includes simvastatin (SV). Individuals vary widely in statin responses, and growing evidence implicates gut microbiome involvement in this variability. However, the associated molecular mechanisms between metabolic improvement and microbiota composition following SV treatment are still not fully understood. In this study, combinatory approaches using ultrahigh-performance liquid chromatography coupled with hybrid triple quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF MS/MS)-based metabolomic profiling, PCR-denaturing gradient gel electrophoresis (PCR-DGGE), quantitative PCR (qPCR), and 16S rRNA gene sequencing-based gut microbiota profiling were performed to investigate the interplay of endogenous metabolites and the gut microbiota related to SV treatment. A total of 6 key differential endogenous metabolites were identified that affect the metabolism of amino acids (phenylalanine and tyrosine), unsaturated fatty acids (linoleic acid and 9-hydroxyoctadecadienoic acid (9-HODE)), and the functions of gut microbial metabolism. Moreover, a total of 22 differentially abundant taxa were obtained following SV treatment. Three bacterial taxa were identified to be involved in SV treatment, namely, Bacteroidaceae, Prevotellaceae, and Porphyromonadaceae. These findings suggested that the phenylalanine and tyrosine-associated amino acid metabolism pathways, as well as the linoleic acid and 9-HODE-associated unsaturated fatty acid metabolism pathways, which are involved in gut flora interactions, might be potential therapeutic targets for improvement in SV hypolipidemic efficacy. The mass spectrometric data have been deposited to MassIVE (https://massive.ucsd.edu/ProteoSAFe/static/massive.jsp). Username: MSV000087842_reviewer. Password: hardworkingzsr.

Paenibacillus tianjinensis sp. nov., isolated from corridor air.

A Gram-stain-positive, facultatively anaerobic, non-motile, endospore-forming and rod-shaped bacterium, occurring singly or in pairs, designated TB2019T, was isolated from environmental monitoring samples of corridor air collected at the Tianjin Institute for Drug Control, Tianjin Province (PR China). The isolate was able to grow at 15-40 °C (optimum growth at 37 °C), pH 6.0-8.0 (pH 7.0) and in the presence of 0-2% (w/v) NaCl (0% NaCl). Comparison of 16S rRNA gene sequences indicated that TB2019T was most closely related to Paenibacillus typhae CGMCC 1.11012T (98.63%), Paenibacillus albidus Q4-3T (98.19%), Paenibacillus borealis DSM 13188T (97.55%), Paenibacillus helianthi P26ET (97.33%) and Paenibacillus odorifer DSM 15391T (97.19%). The digital DNA-DNA hybridization and the average nucleotide identity values between TB2019T and the five type strains mentioned above ranged from 20.7 to 25.0% and 75.2 to 81.3%, respectively, and the genomic DNA G+C content was 49.52 mol%. The diagnostic cell-wall sugar was ribose, and the diagnostic amino acid was meso-diaminopimelic acid. The polar lipids of TB2019T included diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, three unidentified aminophospholipids and one unidentified phospholipid. MK-7 was the predominant menaquinone, and anteiso-C15:0 (30.6%) was the major fatty acid. Based on the polyphasic taxonomic data, strain TB2019T represents a novel species of the genus Paenibacillus, for which the name Paenibacillus tianjinensis sp. nov. is proposed. The type strain is TB2019T (=CICC 25065T=JCM 34610T).

Qingbo, a common cyprinid fish, responds diversely in behavior and locomotion to predators with different hunting modes.

Almost all prey live in habitats with predators with different hunting modes; however, most studies on predation have investigated the effects of only one predator at a time. In this study, we aimed to investigate whether qingbo (Spinibarbus sinensis), a common cyprinid fish, responds differently to active hunting and ambush predators and how qingbo responds when both types of predators coexist. Juvenile qingbo were subjected to catfish (Clarias fuscus, active hunter) exposure, snakehead fish (Channa argus, ambush hunter) exposure, or mixed predator exposure (catfish and snakehead coexistence) for a duration of 60 days. Then, their growth, behaviors, swimming performance, and metabolism were measured. Qingbo subjected to active hunting predator exposure exhibited decreased activity and predator inspection and improved fast-start escape performance compared to those in the control group. However, none of the parameters of the fish subjected to ambush predator exposure changed significantly. Fish subjected to mixed predator exposure exhibited improved fast-start escape performance but increased maintenance energy expenditure, whereas no changes were observed in any of the behavioral variables. Qingbo showed a stronger anti-predator response to active hunting predators than to ambush predators, suggesting that the fish exhibit a stronger anti-predator response to a current direct threat than to a potential threat (a predator exists nearby but seldom presents in attack behavior). Additionally, the response of prey fish to multiple predators was quite complex, and the coexistence and interaction of multiple predator species with different hunting modes may lead to serious stress responses and confound the prey's behavioral responses to each predator.