[Analysis of chemical compositions in different parts of Isodon japonicus using UPLC-Q-TOF-MS technique combined with chemometrics].

In order to analyze the similarities and differences of chemical compositions between the roots and stems and leaves of Isodon japonicus(IJ), this study utilized UPLC-Q-TOF-MS technology to systematically characterize its chemical compositions, analyzed and identified the structure of its main compounds, and established a method for simultaneous determination of its content by refe-rence substance. A total of 34 major compounds in IJ, including 14 reference compounds, were identified or predicted online. Moreover, an UPLC-UV content determination method was developed for 11 compounds [danshensu, caffeic acid, vicenin-2,(1S,2S)-globoidnan B, rutin,(+)-rabdosiin,(-)-rabdosiin,(1S,2S)-rabdosiin, shimobashiric acid C, rosmarinic acid, and pedalitin]. The method exhibited excellent separation, stability, and repeatability, with a wide linear range(0.10-520.00 µg·mL~(-1)) and high linearity(R~2>0.999). The average recovery rates ranged from 94.72% to 104.2%. The principal component analysis(PCA) demonstrated a clear difference between the roots and stems and leaves of IJ, indicating good separation by cluster. Furthermore, the orthogonal partial least squares discriminant analysis(OPLS-DA) model was employed, and six main differentially identified compounds were identified: rosmarinic acid, shimobashiric acid C, epinodosin, pedalitin, rutin, and(1S,2S)-rabdosiin. In summary, this study established a strategy and method for distinguishing different parts of IJ, providing a valuable tool for quality control of IJ and a basis for the ratio-nal utilization and sustainable development of IJ.

Exploring the bi-directional relationship between periodontitis and dyslipidemia: a comprehensive systematic review and meta-analysis.

AIM: As periodontitis and dyslipidemia are diseases that occur with high incidence, the relationship between them has attracted much attention. Previous studies on these diseases have tended to focus on lipid parameters and periodontitis, we aimed to investigate the relationship between dyslipidemia and periodontitis. MATERIALS AND METHODS: A comprehensive search to identify the studies investigating the relationship between dyslipidemia and periodontitis was performed on PubMed, Web of Science and Cochrane Library before the date of August, 2023. Studies were considered eligible if they contained data on abnormal blood lipid parameters and periodontitis. Studies that reported mean differences and 95% confidence intervals or odds ratios were used. RESULTS: A total of 73 publications were included in the meta-analysis. Hyper total cholesterol (TC), triglycerides (TGs), low-density lipoprotein (LDL), very low-density lipoprotein (VLDL) and lower high-density lipoprotein (HDL) levels are risk factors for periodontitis. Periodontal disease is a risk factor for high TG and low HDL levels. Three months after periodontal treatment, the levels of TC, TG and HDL were significantly improved, and statin treatment only improved gingival index (GI) levels compared to that of the dietary control. CONCLUSIONS: The findings reported here suggest that the mutual promotion of periodontitis and dyslipidemia can be confirmed. Non-surgical periodontal therapy may improve lipid abnormalities. It can't be demonstrated whether systematic application of statins have a better effect on the improvement in periodontal status in patients with dyslipidemia compared to that of the control.

High-throughput prediction of enzyme promiscuity based on substrate-product pairs.

The screening of enzymes for catalyzing specific substrate-product pairs is often constrained in the realms of metabolic engineering and synthetic biology. Existing tools based on substrate and reaction similarity predominantly rely on prior knowledge, demonstrating limited extrapolative capabilities and an inability to incorporate custom candidate-enzyme libraries. Addressing these limitations, we have developed the Substrate-product Pair-based Enzyme Promiscuity Prediction (SPEPP) model. This innovative approach utilizes transfer learning and transformer architecture to predict enzyme promiscuity, thereby elucidating the intricate interplay between enzymes and substrate-product pairs. SPEPP exhibited robust predictive ability, eliminating the need for prior knowledge of reactions and allowing users to define their own candidate-enzyme libraries. It can be seamlessly integrated into various applications, including metabolic engineering, de novo pathway design, and hazardous material degradation. To better assist metabolic engineers in designing and refining biochemical pathways, particularly those without programming skills, we also designed EnzyPick, an easy-to-use web server for enzyme screening based on SPEPP. EnzyPick is accessible at http://www.biosynther.com/enzypick/.

RCN1 deficiency inhibits oral squamous cell carcinoma progression and THP-1 macrophage M2 polarization.

Reticulocalbin 1 (RCN1), a calcium-binding protein located in the endoplasmic reticulum (ER) lumen, contains six conserved regions. Its main functions include maintaining intracellular homeostasis and regulating cell proliferation and apoptosis, and it plays an important role in the development of various tumours. However, the exact function of RCN1 in oral squamous cell carcinoma (OSCC) is not fully understood. Therefore, the aim of this study was to investigate the effects of RCN1 on the biological behaviour of OSCC and the regulation of tumour-associated macrophage (TAM) polarization. The expression of RCN1 in OSCC and normal oral mucosa was evaluated through bioinformatics analysis and immunohistochemical staining. The growth, migration, and invasion of OSCC cells were observed after knockdown of RCN1 using CCK-8 and Transwell assays. Apoptosis was detected by flow cytometry. The effect of tumour cell-derived RCN1 on the polarization of THP-1 macrophages was investigated by establishing a coculture model of THP-1 macrophages and OSCC cells. Additionally, changes in the expression levels of relevant proteins were detected using Western blotting. The upregulation of RCN1 in tumour tissues compared to normal oral mucosal tissues is associated with a poor prognosis and can be utilized as a prognostic indicator for OSCC. Knockdown of RCN1 inhibited the proliferation, migration, and invasion of OSCC cells. Additionally, knockdown of RCN1 in Cal-27 and SCC-25 cells resulted in inhibition of the M2 polarization of THP-1 macrophages. RCN1 knockdown inhibits OSCC progression and M2 macrophage polarization. Targeting RCN1 may be a promising approach for OSCC treatment.

MCF2Chem: A manually curated knowledge base of biosynthetic compound production.

BACKGROUND: Microbes have been used as cell factories to synthesize various chemical compounds. Recent advances in synthetic biological technologies have accelerated the increase in the number and capacity of microbial cell factories; the variety and number of synthetic compounds produced via these cell factories have also grown substantially. However, no database is available that provides detailed information on the microbial cell factories and the synthesized compounds. RESULTS: In this study, we established MCF2Chem, a manually curated knowledge base on the production of biosynthetic compounds using microbial cell factories. It contains 8888 items of production records related to 1231 compounds that were synthesizable by 590 microbial cell factories, including the production data of compounds (titer, yield, productivity, and content), strain culture information (culture medium, carbon source/precursor/substrate), fermentation information (mode, vessel, scale, and condition), and other information (e.g., strain modification method). The database contains statistical analyses data of compounds and microbial species. The data statistics of MCF2Chem showed that bacteria accounted for 60% of the species and that "fatty acids", "terpenoids", and "shikimates and phenylpropanoids" accounted for the top three chemical products. Escherichia coli, Saccharomyces cerevisiae, Yarrowia lipolytica, and Corynebacterium glutamicum synthesized 78% of these chemical compounds. Furthermore, we constructed a system to recommend microbial cell factories suitable for synthesizing target compounds and vice versa by combining MCF2Chem data, additional strain- and compound-related data, the phylogenetic relationships between strains, and compound similarities. CONCLUSIONS: MCF2Chem provides a user-friendly interface for querying, browsing, and visualizing detailed statistical information on microbial cell factories and their synthesizable compounds. It is publicly available at https://mcf.lifesynther.com . This database may serve as a useful resource for synthetic biologists.

CCIBP: a comprehensive cosmetic ingredients bioinformatics platform.

SUMMARY: Cosmetics form an important part of our daily lives, and it is therefore important to understand the basic physicochemical properties, metabolic pathways, and toxicological and safe concentrations of these cosmetics molecules. Therefore, comprehensive cosmetic ingredients bioinformatics platform (CCIBP) was developed here, which is a unique comprehensive cosmetic database providing information on regulations, physicochemical properties, and human metabolic pathways for cosmetic molecules from major regions of the world, whilst also correlating plant information in natural products. CCIBP supports formulation analysis, efficacy component analysis, and also combines knowledge of synthetic biology to facilitate access to natural molecules and biosynthetic production. CCIBP, empowered with chemoinformatics, bioinformatics, and synthetic biology data and tools, presents a very helpful platform for cosmetic research and development of ingredients. AVAILABILITY AND IMPLEMENTATION: CCIBP is available at: http://design.rxnfinder.org/cosing/.

RDBridge: a knowledge graph of rare diseases based on large-scale text mining.

MOTIVATION: Despite low prevalence, rare diseases affect 300 million people worldwide. Research on pathogenesis and drug development lags due to limited commercial potential, insufficient epidemiological data, and a dearth of publications. The unique characteristics of rare diseases, including limited annotated data, intricate processes for extracting pertinent entity relationships, and difficulties in standardizing data, represent challenges for text mining. RESULTS: We developed a rare disease data acquisition framework using text mining and knowledge graphs and constructed the most comprehensive rare disease knowledge graph to date, Rare Disease Bridge (RDBridge). RDBridge offers search functions for genes, potential drugs, pathways, literature, and medical imaging data that will support mechanistic research, drug development, diagnosis, and treatment for rare diseases. AVAILABILITY AND IMPLEMENTATION: RDBridge is freely available at http://rdb.lifesynther.com/.

Porphyromonas gingivalis Gingipains Destroy the Vascular Barrier and Reduce CD99 and CD99L2 Expression To Regulate Transendothelial Migration.

Porphyromonas gingivalis is an important periodontal pathogen that can cause vascular injury and invade local tissues through the blood circulation, and its ability to evade leukocyte killing is critical to its distal colonization and survival. Transendothelial migration (TEM) is a series of that enable leukocytes to squeeze through endothelial barriers and migrate into local tissues to perform immune functions. Several studies have shown that P. gingivalis-mediated endothelial damage initiates a series of proinflammatory signals that promote leukocyte adhesion. However, whether P. gingivalis is involved in TEM and thus influences immune cell recruitment remains unknown. In our study, we found that P. gingivalis gingipains could increase vascular permeability and promote Escherichia coli penetration by downregulating platelet/endothelial cell adhesion molecule 1 (PECAM-1) expression in vitro. Furthermore, we demonstrated that although P. gingivalis infection promoted monocyte adhesion, the TEM capacity of monocytes was substantially impaired, which might be due to the reduced CD99 and CD99L2 expression on gingipain-stimulated endothelial cells and leukocytes. Mechanistically, gingipains mediate CD99 and CD99L2 downregulation, possibly through the inhibition of the phosphoinositide 3-kinase (PI3K)/Akt pathway. In addition, our in vivo model confirmed the role of P. gingivalis in promoting vascular permeability and bacterial colonization in the liver, kidney, spleen, and lung and in downregulating PECAM-1, CD99, and CD99L2 expression in endothelial cells and leukocytes. IMPORTANCE P. gingivalis is associated with a variety of systemic diseases and colonizes in distal locations in the body. Here, we found that P. gingivalis gingipains degrade PECAM-1 to promote bacterial penetration while simultaneously reducing leukocyte TEM capacity. A similar phenomenon was also observed in a mouse model. These findings established P. gingivalis gingipains as the key virulence factor in modulating the permeability of the vascular barrier and TEM processes, which may provide a new rationale for the distal colonization of P. gingivalis and its associated systemic diseases.

Factors impacting the behavior of phytoremediation in pesticide-contaminated environment: A meta-analysis.

Phytoremediation provides substantial advantages, including eco-friendliness, cost-effectiveness, efficiency, and visual appeal. However, the current knowledge of the factors influencing phytoremediation in pesticide-contaminated environments remains limited. It is critical to understand phytoremediation and the factors affecting the variation in removal efficiency. In this study, we compiled 72 previous research articles to quantify plant-induced improvements in removal efficiency and identify factors that influence variations in phytoremediation behavior through meta-analysis. We observed a significant increase in the removal efficiency of phytoremediation compared to the control group which did not involve phytoremediation. Pesticides significantly affect removal efficiency in terms of their modes of action, substance group, and properties. Plants demonstrated higher efficiency in remediating environments contaminated with pesticides possessing lower molecular masses and log Kow values. Plant species emerged as a crucial determinant of variations in removal efficiency. Annual plants exhibited a 1.45-fold higher removal efficiency than perennial plants. The removal efficiencies of different plant types decreased in the following order: agri-food crops > aquatic macrophytes > turfgrasses > medicinal plants > forage crops > woody trees. The Gramineae family, which was the most prevalent, demonstrated a robust and consistent phytoremediation ability. This study offers a more comprehensive triangular relationship between removal efficiency, pesticides, and plants, expanding the traditional linear model. Our findings offer valuable insights into the behavior of phytoremediation in pesticide-contaminated environments and the factors determining its success, ultimately guiding further research toward developing strategies for higher removal efficiency in phytoremediation.

Data-Driven Prediction of Molecular Biotransformations in Food Fermentation.

Fermentation products, together with food components, determine the sense, nutrition, and safety of fermented foods. Traditional methods of fermentation product identification are time-consuming and cumbersome, which cannot meet the increasing need for the identification of the extensive bioactive metabolites produced during food fermentation. Hence, we propose a data-driven integrated platform (FFExplorer, http://www.rxnfinder.org/ffexplorer/) based on machine learning and data on 2,192,862 microbial sequence-encoded enzymes for computational prediction of fermentation products. Using FFExplorer, we explained the mechanism behind the disappearance of spicy taste during pepper fermentation and evaluated the detoxification effects of microbial fermentation for common food contaminants. FFExplorer will provide a valuable reference for inferring bioactive "dark matter" in fermented foods and exploring the application potential of microorganisms.

Proteomic investigation and biomarker identification of lung and spleen deficiency syndrome in HIV/AIDS immunological nonresponders.

Background: Human immunodeficiency virus (HIV) and acquired immune deficiency syndrome (AIDS) immunological nonresponders (HIV/AIDS-INRs) whose CD4+ cell counts do not rebound after highly active antiretroviral therapy (HAART) treatment usually experience severely impaired immune function and high mortality. Traditional Chinese medicine (TCM) has many advantages in the field of AIDS, especially its promotion of patients' immune reconstitution. Accurate differentiation of TCM syndromes is a prerequisite for guiding an effective TCM prescription. However, the objective and biological evidence for identification of the TCM syndromes in HIV/AIDS-INRs remains lacking. Lung and spleen deficiency (LSD) syndrome, a typical HIV/AIDS-INR syndrome, was examined on in this study. Methods: We first performed a proteomic study of LSD syndrome in INRs (INRs-LSD) using tandem mass tag combined with liquid chromatography-tandem mass spectrometry (TMT-LC-MS/MS) and screened them against the healthy and undocumented identifiable groups. The TCM syndrome-specific proteins were subsequently validated based on bioinformatics analysis and enzyme-linked immunosorbent assay (ELISA). Results: A total of 22 differentially expressed proteins (DEPs) were screened in INRs-LSD compared to the healthy group. Based on bioinformatic analysis, these DEPs were found to be mainly associated with the immunoglobin A (IgA)-generated intestinal immune network. In addition, we examined the TCM syndrome-specific proteins alpha-2-macroglobulin (A2M) and human selectin L (SELL) with ELISA and found that they were both upregulated, which was consistent with the proteomic screening results. Conclusions: A2M and SELL were finally identified as potential biomarkers for INRs-LSD, providing a scientific and biological basis for identifying typical TCM syndromes in HIV/AIDS-INRs and an opportunity to build a more effective TCM treatment system for HIV/AIDS-INRs.

SynBioTools: a one-stop facility for searching and selecting synthetic biology tools.

BACKGROUND: The rapid development of synthetic biology relies heavily on the use of databases and computational tools, which are also developing rapidly. While many tool registries have been created to facilitate tool retrieval, sharing, and reuse, no relatively comprehensive tool registry or catalog addresses all aspects of synthetic biology. RESULTS: We constructed SynBioTools, a comprehensive collection of synthetic biology databases, computational tools, and experimental methods, as a one-stop facility for searching and selecting synthetic biology tools. SynBioTools includes databases, computational tools, and methods extracted from reviews via SCIentific Table Extraction, a scientific table-extraction tool that we built. Approximately 57% of the resources that we located and included in SynBioTools are not mentioned in bio.tools, the dominant tool registry. To improve users' understanding of the tools and to enable them to make better choices, the tools are grouped into nine modules (each with subdivisions) based on their potential biosynthetic applications. Detailed comparisons of similar tools in every classification are included. The URLs, descriptions, source references, and the number of citations of the tools are also integrated into the system. CONCLUSIONS: SynBioTools is freely available at https://synbiotools.lifesynther.com/ . It provides end-users and developers with a useful resource of categorized synthetic biology databases, tools, and methods to facilitate tool retrieval and selection.

Plant species shape the bacterial communities on the phyllosphere in a hyper-arid desert.

Microorganisms are an important component of global biodiversity. However, they are vulnerable to hyper-arid climates in desert regions. Xerophytes are desert vegetation with unique biodiversity. However, little is known about the identities and communities of phyllosphere epiphytic microorganisms inhabiting the xerophyte leaf surface in the hot and dry environment. The diversity and community composition of phyllosphere epiphytes on different desert plants in Gansu, China, was investigated using the next-generation sequencing technique, revealing the diversity and community composition of the phyllosphere epiphytic bacteria associated with desert xerophytes. In addition, the ecological functions of the bacterial communities were investigated by combining the sequence classification information and prokaryotic taxonomic function annotation (FAPROTAX). This study determined the phyllosphere bacterial community composition, microbial interactions, and their functions. Despite harsh environments in the arid desert, we found that there are still diverse epiphytic bacteria on the leaves of desert plants. The bacterial communities mainly included Actinobacteria (52.79%), Firmicutes (31.62%), and Proteobacteria (12.20%). Further comparisons revealed different microbial communities, including Firmicutes at the phylum and Paenibacillaceae at the family level, in the phyllosphere among different plants, suggesting that the host plants had strong filter effects on bacteria. Co-occurrence network analysis revealed positive relationships were dominant among different bacterial taxa. The abundance of Actinobacteria and Proteobacteria was positively correlated, demonstrating their mutual relationship. On the other hand, the abundance of Firmicutes was negatively correlated, which suggested that they inhibit the growth of other bacterial taxa. FAPROTAX prediction revealed that chemoheterotrophy (accounting for 39.02% of the community) and aerobic chemoheterotrophy (37.01%) were the main functions of the leaf epiphytic bacteria on desert plants. This study improves our understanding of the community composition and ecological functions of plant-associated microbial communities inhabiting scattered niches in the desert ecosystem. In addition, the study provides insight into the biodiversity assessment in the desert region.

Epidemiological investigation and proteomic profiling of typical TCM syndrome in HIV/AIDS immunological nonresponders.

HIV/AIDS pandemic remains the world's most severe public health challenge, especially for HIV/AIDS immunological nonresponders (HIV/AIDS-INRs), who tend to have higher mortality. Due to the advantages in promoting patients' immune reconstitution, Traditional Chinese medicine (TCM) has become one of the mainstays of complementary treatments for HIV/AIDS-INRs. Given that effective TCM treatments largely depend on precise syndrome differentiation, there is an increasing interest in exploring biological evidence for the classification of TCM syndromes in HIV/AIDS-INRs. In our study, to identify the typical HIV/AIDS-INRs syndrome, an epidemiological survey was first conducted in the Liangshan prefecture (China), a high HIV/AIDS prevalence region. The key TCM syndrome, Yang deficiency of spleen and kidney (YDSK), was evaluated by using a tandem mass tag combined with liquid chromatography-tandem mass spectrometry (TMT-LC-MS/MS). A total of 62 differentially expressed proteins (DEPs) of YDSK syndrome compared with healthy people were screened out. Comparative bioinformatics analyses showed that DEPs in YDSK syndrome were mainly associated with response to wounding and acute inflammatory response in the biological process. The pathway annotation is mainly enriched in complement and coagulation cascades. Finally, the YDSK syndrome-specific DEPs such as HP and S100A9 were verified by ELISA, and confirmed as potential biomarkers for YDSK syndrome. Our study may lay the biological and scientific basis for the specificity of TCM syndromes in HIV/AIDs-INRs, and may provide more opportunities for the deep understanding of TCM syndromes and the developing more effective and stable TCM treatment for HIV/AIDS-INRs.

The interaction of CD300lf and ceramide reduces the development of periodontitis by inhibiting osteoclast differentiation.

AIM: The regulation of osteoclasts (OCs) by inhibitory immunoreceptors maintains bone homeostasis and is considered an important determinant of the extent of periodontal pathology. The aim of this study was to investigate the role of the inhibitory immunoreceptor CD300lf and its ligand ceramide in osteoclastogenesis in periodontitis. MATERIALS AND METHODS: The expression of CD300lf was measured in vitro and in a ligature-induced periodontitis model. The effect of CD300lf ablation on osteoclastogenesis was examined in ligature-retained and ligature removal periodontitis models. The effect of ceramide, the ligand of CD300lf, was examined in osteoclastogenesis in vitro and in vivo by smearing 20 µg of ceramide dissolved in carboxymethylcellulose on teeth and gingiva every other day in an experimental periodontitis model and ligature removal model. RESULTS: CD300lf expression was downregulated during osteoclastogenesis. Ablation of CD300lf in the ligature-induced periodontitis model increased the number of OCs and exacerbated bone damage. Bone resorption caused by CD300lf ablation was reversible following ligature removal. CD300lf-ceramide binding suppressed osteoclastogenesis in vitro and inhibited alveolar bone loss in a mouse periodontitis model. CONCLUSIONS: Our findings reveal that CD300lf-ceramide binding plays a critical negative role in alveolar bone loss in periodontitis by inhibiting OCs differentiation.

Oxidative Damage in Roots of Rice (Oryza sativa L.) Seedlings Exposed to Microplastics or Combined with Cadmium.

This study aimed to investigate the effect of 10-40 mg L-1 polystyrene microplastics (PS-MPs), 0.05 mg L-1 cadmium (Cd) and their combination on the growth and related physiological and toxicological responses in Oryza sativa L. seedling roots. Results showed that the fresh weight, dry weight and root lengths of treatments by PS-MPs, Cd single and combinative were all lower than the control, and opposite phenomenon appeared in production of superoxide radical (O2-.), malondialdehyde (MDA) and carbonylated protein. Superoxide dismutase (SOD) and guaiacol peroxidase (POD) activities induced by 10-40 mg L-1 PS-MPs and combination with Cd were almost higher than those by Cd alone, expression of heat shock protein (HSP)70 and carbonylated protein slightly decreased. In compound exposure, 10-20 mg L-1 PS-MPs alleviated Cd damage and promoted root growth by increasing SOD and POD activities, but 40 mg L-1 PS-MPs accelerated the accumulation of Cd, MDA, and O2-., which was responsible for decreasing root biomass and the aggravating necrosis of root tip cells.

Genome-wide identification, characterization, and expression analysis of UDP-glycosyltransferase genes associated with secondary metabolism in alfalfa (Medicago sativa L.).

Uridine diphosphate glycosyltransferases (UGTs) are enzymes that catalyze glycosylation modifications and play an essential role in regulating plant metabolism. Alfalfa (Medicago sativa L.) is the most important legume in the world due to its high yields and protein content; however, the UGT genes in alfalfa have not yet been studied. Identifying UGT genes with metabolic roles in alfalfa is essential for identifying and modifying genetic traits that are relevant to yield and quality. In this study, 90 of the 239 UGT genes identified from the alfalfa "Zhongmu No. 1" genome database were found to be related to secondary metabolism, and a series of gene family characterization analyses were conducted on each. The results demonstrated that all 90 UGT genes were unevenly distributed on eight chromosomes with few introns and that tandem duplications were the crucial driving force expanding the UGT family in alfalfa. Notably, the 90 UGT genes can be clustered into ten evolutionary groups which contain specific PSPG motifs, and genes in these ten groups have specific tissue expressions. This suggests that the UGT genes in each group could have similar glycosylation roles corresponding to analogous secondary metabolites in alfalfa. Additionally, multiple cis-acting elements found in MsUGT promoter regions, such as phytohormone and flavonoids, indicate that 90 UGT members could be induced by these features, which are also related to secondary metabolism. Therefore, our study identified 90 UGT members inten evolutionary groups that are likely related to glycosylation modifications with secondary metabolites in alfalfa. These findings help uncover pivotal regulatory mechanisms associated with secondary metabolism in plant yield and quality and contribute to genetic modification and breeding in alfalfa and other plant species.

Species identity and combinations differ in their overall benefits to Astragalus adsurgens plants inoculated with single or multiple endophytic fungi under drought conditions.

Although desert plants often establish multiple simultaneous symbiotic associations with various endophytic fungi in their roots, most studies focus on single fungus inoculation. Therefore, combined inoculation of multiple fungi should be applied to simulate natural habitats with the presence of a local microbiome. Here, a pot experiment was conducted to test the synergistic effects between three extremely arid habitat-adapted root endophytes (Alternaria chlamydospora, Sarocladium kiliense, and Monosporascus sp.). For that, we compared the effects of single fungus vs. combined fungi inoculation, on plant morphology and rhizospheric soil microhabitat of desert plant Astragalus adsurgens grown under drought and non-sterile soil conditions. The results indicated that fungal inoculation mainly influenced root biomass of A. adsurgens, but did not affect the shoot biomass. Both single fungus and combined inoculation decreased plant height (7-17%), but increased stem branching numbers (13-34%). However, fungal inoculation influenced the root length and surface area depending on their species and combinations, with the greatest benefits occurring on S. kiliense inoculation alone and its co-inoculation with Monosporascus sp. (109% and 61%; 54% and 42%). Although A. chlamydospora and co-inoculations with S. kiliense and Monosporascus sp. also appeared to promote root growth, these inoculations resulted in obvious soil acidification. Despite no observed root growth promotion, Monosporascus sp. associated with its combined inoculations maximally facilitated soil organic carbon accumulation. However, noticeably, combined inoculation of the three species had no significant effects on root length, surface area, and biomass, but promoted rhizospheric fungal diversity and abundance most, with Sordariomycetes being the dominant fungal group. This indicates the response of plant growth to fungal inoculation may be different from that of the rhizospheric fungal community. Structural equation modeling also demonstrated that fungal inoculation significantly influenced the interactions among the growth of A. adsurgens, soil factors, and rhizospheric fungal groups. Our findings suggest that, based on species-specific and combinatorial effects, endophytic fungi enhanced the plant root growth, altered soil nutrients, and facilitated rhizospheric fungal community, possibly contributing to desert plant performance and ecological adaptability. These results will provide the basis for evaluating the potential application of fungal inoculants for developing sustainable management for desert ecosystems.

BioBulkFoundary: a customized webserver for exploring biosynthetic potentials of bulk chemicals.

SUMMARY: Advances in metabolic engineering have boosted the production of bulk chemicals, resulting in tons of production volumes of some bulk chemicals with very low prices. A decrease in the production cost and overproduction of bulk chemicals makes it necessary and desirable to explore the potential to synthesize higher-value products from them. It is also useful and important for society to explore the use of design methods involving synthetic biology to increase the economic value of these bulk chemicals. Therefore, we developed 'BioBulkFoundary', which provides an elaborate analysis of the biosynthetic potential of bulk chemicals based on the state-of-art exploration of pathways to synthesize value-added chemicals, along with associated comprehensive technology and economic database into a user-friendly framework. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://design.rxnfinder.org/biobulkfoundary/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

AddictedChem: A Data-Driven Integrated Platform for New Psychoactive Substance Identification.

The mechanisms underlying drug addiction remain nebulous. Furthermore, new psychoactive substances (NPS) are being developed to circumvent legal control; hence, rapid NPS identification is urgently needed. Here, we present the construction of the comprehensive database of controlled substances, AddictedChem. This database integrates the following information on controlled substances from the US Drug Enforcement Administration: physical and chemical characteristics; classified literature by Medical Subject Headings terms and target binding data; absorption, distribution, metabolism, excretion, and toxicity; and related genes, pathways, and bioassays. We created 29 predictive models for NPS identification using five machine learning algorithms and seven molecular descriptors. The best performing models achieved a balanced accuracy (BA) of 0.940 with an area under the curve (AUC) of 0.986 for the test set and a BA of 0.919 and an AUC of 0.968 for the external validation set, which were subsequently used to identify potential NPS with a consensus strategy. Concurrently, a chemical space that included the properties of vectorised addictive compounds was constructed and integrated with AddictedChem, illustrating the principle of diversely existing NPS from a macro perspective. Based on these potential applications, AddictedChem could be considered a highly promising tool for NPS identification and evaluation.