Drug-Online: an online platform for drug-target interaction, affinity, and binding sites identification using deep learning.

BACKGROUND: Accurately identifying drug-target interaction (DTI), affinity (DTA), and binding sites (DTS) is crucial for drug screening, repositioning, and design, as well as for understanding the functions of target. Although there are a few online platforms based on deep learning for drug-target interaction, affinity, and binding sites identification, there is currently no integrated online platforms for all three aspects. RESULTS: Our solution, the novel integrated online platform Drug-Online, has been developed to facilitate drug screening, target identification, and understanding the functions of target in a progressive manner of "interaction-affinity-binding sites". Drug-Online platform consists of three parts: the first part uses the drug-target interaction identification method MGraphDTA, based on graph neural networks (GNN) and convolutional neural networks (CNN), to identify whether there is a drug-target interaction. If an interaction is identified, the second part employs the drug-target affinity identification method MMDTA, also based on GNN and CNN, to calculate the strength of drug-target interaction, i.e., affinity. Finally, the third part identifies drug-target binding sites, i.e., pockets. The method pt-lm-gnn used in this part is also based on GNN. CONCLUSIONS: Drug-Online is a reliable online platform that integrates drug-target interaction, affinity, and binding sites identification. It is freely available via the Internet at http://39.106.7.26:8000/Drug-Online/ .

GNNGL-PPI: multi-category prediction of protein-protein interactions using graph neural networks based on global graphs and local subgraphs.

Most proteins exert their functions by interacting with other proteins, making the identification of protein-protein interactions (PPI) crucial for understanding biological activities, pathological mechanisms, and clinical therapies. Developing effective and reliable computational methods for predicting PPI can significantly reduce the time-consuming and labor-intensive associated traditional biological experiments. However, accurately identifying the specific categories of protein-protein interactions and improving the prediction accuracy of the computational methods remain dual challenges. To tackle these challenges, we proposed a novel graph neural network method called GNNGL-PPI for multi-category prediction of PPI based on global graphs and local subgraphs. GNNGL-PPI consisted of two main components: using Graph Isomorphism Network (GIN) to extract global graph features from PPI network graph, and employing GIN As Kernel (GIN-AK) to extract local subgraph features from the subgraphs of protein vertices. Additionally, considering the imbalanced distribution of samples in each category within the benchmark datasets, we introduced an Asymmetric Loss (ASL) function to further enhance the predictive performance of the method. Through evaluations on six benchmark test sets formed by three different dataset partitioning algorithms (Random, BFS, DFS), GNNGL-PPI outperformed the state-of-the-art multi-category prediction methods of PPI, as measured by the comprehensive performance evaluation metric F1-measure. Furthermore, interpretability analysis confirmed the effectiveness of GNNGL-PPI as a reliable multi-category prediction method for predicting protein-protein interactions.

MMDTA: A Multimodal Deep Model for Drug-Target Affinity with a Hybrid Fusion Strategy.

The prediction of the drug-target affinity (DTA) plays an important role in evaluating molecular druggability. Although deep learning-based models for DTA prediction have been extensively attempted, there are rare reports on multimodal models that leverage various fusion strategies to exploit heterogeneous information from multiple different modalities of drugs and targets. In this study, we proposed a multimodal deep model named MMDTA, which integrated the heterogeneous information from various modalities of drugs and targets using a hybrid fusion strategy to enhance DTA prediction. To achieve this, MMDTA first employed convolutional neural networks (CNNs) and graph convolutional networks (GCNs) to extract diverse heterogeneous information from the sequences and structures of drugs and targets. It then utilized a hybrid fusion strategy to combine and complement the extracted heterogeneous information, resulting in the fused modal information for predicting drug-target affinity through the fully connected (FC) layers. Experimental results demonstrated that MMDTA outperformed the competitive state-of-the-art deep learning models on the widely used benchmark data sets, particularly with a significantly improved key evaluation metric, Root Mean Square Error (RMSE). Furthermore, MMDTA exhibited excellent generalization and practical application performance on multiple different data sets. These findings highlighted MMDTA's accuracy and reliability in predicting the drug-target binding affinity. For researchers interested in the source data and code, they are accessible at http://github.com/dldxzx/MMDTA.

Identify Regioselective Residues of Ginsenoside Hydrolases by Graph-Based Active Learning from Molecular Dynamics.

Identifying the catalytic regioselectivity of enzymes remains a challenge. Compared to experimental trial-and-error approaches, computational methods like molecular dynamics simulations provide valuable insights into enzyme characteristics. However, the massive data generated by these simulations hinder the extraction of knowledge about enzyme catalytic mechanisms without adequate modeling techniques. Here, we propose a computational framework utilizing graph-based active learning from molecular dynamics to identify the regioselectivity of ginsenoside hydrolases (GHs), which selectively catalyze C6 or C20 positions to obtain rare deglycosylated bioactive compounds from Panax plants. Experimental results reveal that the dynamic-aware graph model can excellently distinguish GH regioselectivity with accuracy as high as 96-98% even when different enzyme-substrate systems exhibit similar dynamic behaviors. The active learning strategy equips our model to work robustly while reducing the reliance on dynamic data, indicating its capacity to mine sufficient knowledge from short multi-replica simulations. Moreover, the model's interpretability identified crucial residues and features associated with regioselectivity. Our findings contribute to the understanding of GH catalytic mechanisms and provide direct assistance for rational design to improve regioselectivity. We presented a general computational framework for modeling enzyme catalytic specificity from simulation data, paving the way for further integration of experimental and computational approaches in enzyme optimization and design.

Characteristics of a new carotenoid cleavage dioxygenase NtCCD10 derived from Nicotiana tabacum.

MAIN CONCLUSION: A new carotenoid cleavage dioxygenase NtCCD10 from tobacco was characterized. There is some difference between NtCCD10 and CCD1 in structure. NtCCD10 can cleave the C5-C6 (C5'-C6') and C9-C10 (C9'-C10') double bonds of carotenoids and has high catalytic activity. Carotenoid cleavage dioxygenases (CCDs) cleave carotenoids to produce a variety of apocarotenoids, which have important biological functions for organisms in nature. There are eleven CCDs subfamilies in the plant kingdom, many of which have been extensively characterized in their functions. However, as a newly classified subfamily, the function of CCD10 has rarely been studied. In this work, the function of an NtCCD10 gene from dicotyledonous Nicotiana tabacum was cloned and characterized, and its phylogeny, molecular structural modeling and protein structure were also systematically analyzed. Like other CCDs, NtCCD10 also possesses a seven bladed ß-propeller with Fe2+ cofactor in its center constituting the active site of the enzyme. The Fe2+ is also coordinated bonding with four conserved histidine residues. Meanwhile, NtCCD10 also has many unique features, such as its α1 and α3 helixes are not anti-parallel, a special ß-sheet and a longer access tunnel for substrates. When expressed in engineered Escherichia coli (producing phytoene, lycopene, ß-carotene, and zeaxanthin) and Saccharomyces cerevisiae (producing ß-carotene), NtCCD10 could symmetrically cleave phytoene and ß-carotene at the C9-C10 and C9'-C10' positions to produce geranylacetone and ß-ionone, respectively. In addition, NtCCD10 could also cleave the C5-C6 and C5'-C6' double bonds of lycopene to generate 6-methyl-5-heptene-2-one (MHO). NtCCD10 has higher catalytic activity than PhCCD1 in yeast, which provides a good candidate CCD for biosynthesis of ß-ionone and has potential applications in biotechnological industry. This study identified the taxonomic position and catalytic activity of the first NtCCD10 in dicotyledonous plants. This will provide a reference for the discovery and functional identification of CCD10 enzymes in dicotyledons.

Viridibacillus soli sp. nov., isolated from forest soil in Ailaoshan National Nature Reserve.

A Gram stain-positive, rod-shaped, and subterminal endospore-forming bacterium, designated strain YIM B01967T, was isolated from a forest soil sample collected in Ailaoshan National Nature Reserve, Yuxi City, Xinpin county, Yunnan province, China. Strain YIM B01967T showed the highest 16S rRNA gene sequence similarity with Viridibacillus arvi (99.1%) and Viridibacillus arenosi (98.9%). Based on the phylogenetic and 16S rRNA gene sequence results, strain YIM B01967T was affiliated to the genus Viridibacillus. The growth of YIM B01967T was observed at 15-35 °C (optimum, 28 °C), pH 7.0-9.0 (optimum, pH 7.5) and in the presence of 0-2% (w/v) NaCl (optimum in 2% NaCl). The cell wall sugars include ribose, glucose, arabinose, galactose, and mannose. The quinone system consisted of the major compound MK-8 and moderate amounts of MK-7. The major fatty acids (> 10%) included iso-C15:0, anteiso-C15:0, C16:1 ω10c. The major polar lipids profile included DPG, PME. The cell wall peptidoglycan was most likely of the type A4α with an L-Lys-D-Asp interpeptide bridge. The genomic DNA G + C content of strain YIM B01967T was 36.3 mol%. The ANI and digital DNA-DNA hybridization (dDDH) values between strain YIM B01967T and Viridibacillus arvi DSM 16317 T, Viridibacillus arenosi DSM 16319 T were 61.0% and 32.1%, 60.0% and 33.1% based on the draft genome sequence. The results support the conclusion that strain YIM B01967T represents a novel species of the genus Viridibacillus, for which the name Viridibacillus soli sp. nov., is proposed. The type strain is YIM B01967T (= KCTC 43249 T = CGMCC 1.18436 T).

Aestuariimicrobium ganziense sp. nov., a new Gram-positive bacterium isolated from soil in the Ganzi Tibetan autonomous prefecture, China.

A novel Gram-stain positive, oval-shaped, and non-flagellated bacterium, designated YIM S02566T, was isolated from alpine soil in Shadui Towns, Ganzi County, Ganzi Tibetan Autonomous Prefecture, Sichuan Province, PR China. Growth occurred at 23-35 °C (optimum, 30 °C) in the presence of 0.5-4% (w/v) NaCl (optimum, 1%) and at pH 7.0-8.0 (optimum, pH 7.0). The phylogenetic analysis based on 16S rRNA gene sequence revealed that strain YIM S02566T was most closely related to the genus Aestuariimicrobium, with Aestuariimicrobium kwangyangense R27T and Aestuariimicrobium soli D6T as its closest relative (sequence similarities were 96.3% and 95.4%, respectively). YIM S02566T contained LL-diaminopimelic acid in the cell wall. MK-9(H4) was the predominant menaquinone. The major fatty acid patterns were anteiso-C15:0 (60.0%). The major polar lipid was DPG. The genome size of strain YIM S02566T was 3.1 Mb, comprising 3078 predicted genes with a DNA G + C content of 69.0 mol%. Based on these genotypic, chemotaxonomic and phenotypic evidences, strain YIM S02566T was identified as a novel species in the genus Aestuariimicrobium, for which the name Aestuariimicrobium ganziense sp. nov. is proposed. The type strain is YIM S02566T (= CGMCC 1.18751 T = KCTC 49,477 T).

Propioniciclava soli sp. nov., isolated from forest soil, Yunnan, China, and reclassification of the genus Brevilactibacter into the genus Propioniciclava, and Brevilactibacter sinopodophylli, Brevilactibacter flavus, and Brevilactibacter coleopterorum as Propioniciclava sinopodophylli comb. nov., Propioniciclava flava comb. nov., and Propioniciclava coleopterorum comb. nov., respectively.

A Gram-stain-positive, coccus-shaped, facultatively anaerobic, non-motile bacterial strain, designated YIM S02567T, was isolated from a forest soil sample collected from Gejiu City, Yunnan Province, southwest PR China. Growth was observed at 10-45 °C, at pH 6.0-9.5, in the presence of up to 4.0% (w/v) NaCl on R2A medium. The results of 16S rRNA gene sequence similarity analysis showed that strain YIM S02567T was most closely related to the type strain of Brevilactibacter sinopodophylli (95.4%) and Propioniciclava tarda (94.7%), and phylogenetic analysis based on genome data showed that strain YIM S02567T should be assigned to the genus Propioniciclava. The cell-wall diamino acid was meso-diaminopimelic acid. The major cellular fatty acids were identified as anteiso-C15:0 and C16:0, and the major polar lipids were diphosphatidylglycerol, phosphatidylglycerol, and two unidentified glycolipids. The predominant menaquinone was MK-9(H4). The genomic DNA G + C content was 71.2 mol%. Based on the polyphasic taxonomic evidence, strain YIM S02567T is assigned to a novel member of the genus Propioniciclava, for which the name Propioniciclava soli sp. nov., (type strain YIM S02567T = CCTCC AB 2020128T = CGMCC 1.18504T = KCTC 49478T) is proposed. Furthermore, we propose the reclassification of Brevilactibacter as Propioniciclava gen. nov.

Optimized biosynthesis of santalenes and santalols in Saccharomyces cerevisiae.

Santalenes and santalols from Santalum album are the main components of the valuable spice sandalwood essential oil, which also has excellent pharmacological activities such as antibacterial, anti-inflammatory, and antitumor. Firstly, we constructed biosynthesis pathways of santalenes by synthetic biology strategy. The assembled biosynthetic cassettes were integrated into the multiple copy loci of δ gene in S. cerevisiae BY4742 with assistance of pDi-CRISPR, and 94.6 mg/L santalenes was obtained by shake flask fermentation of engineered yeast. Secondly, a selected optimized P450-CPR redox system was integrated into the chromosome of the santalenes-producing strain with a single copy, and 24.6 mg/L santalols were obtained. Finally, the yields of santalenes and santalols were increased to 164.7 and 68.8 mg/L, respectively, by downregulating ERG9 gene. This is the first report on the de novo synthesis of santalols by P450-CPR chimera in S. cerevisiae. Meanwhile, the optimized chimeric CYP736A167opt-46tATR1opt exhibits higher activity to oxidize santalenes into santalols. It would provide a feasible solution for the optimal biosynthesis of santalols. KEY POINTS: • First-time de novo synthesis of santalols by P450-CPR chimera in S. cerevisiae. • Truncated 46tATR1 has higher activity than that of CPR2. • Yields of santalenes and santalols were increased by downregulating ERG9 gene.

Cloning and Characterization of a Ginsenoside-Hydrolyzing α-L-Arabinofuranosidase, CaAraf51, From Cellulosimicrobium aquatile Lyp51.

Moutai Jiuqu is a famous aromatic raw material of Maotai flavor liquor in China. It is brewed at high temperature and contains many kinds of bacteria, molds, and yeasts. There are many useful glycoside hydrolases in these microfloras, from which efficient glycoside hydrolases can be screened for biotransformation of natural saponins. In this study, an α-L-arabinofuranosidase gene (CaAraf51, 1524 bp, 507 amino acid, 55.07 kDa, and pI = 4.8) was cloned from Cellulosimicrobium aquatile Lyp51, which was isolated from the Maotai Jiuqu. The CaAraf51 was heterogeneously expressed in E. coli BL21 (DE3) and purified by N-terminal His-tag with the Ni2+-affinity column chromatography. The results show that purified CaAraf51 has a 6.8-fold purification factor and specific activity of 15 U/mg. Under optimal conditions (pH 5.0, temperature 40 °C), kinetic parameters Km of CaAraf51 for pNPαAraf and Rc were 1.1 and 0.57 mM, the Vmax were 25 and 6.25 µmol/min/mg, respectively. 90% of 0.87 mg Rc substrate can be transformed by 9.6 U purified CaAraf51 in 1 mL reaction system under suitable conditions (30 °C, pH 7.5 phosphate buffer, 1 h). In addition, we also tested the effects of metal ions and chemical agents on the activity of CaAraf51. According to systematically studied its function and enzymatic properties, CaAraf51 has excellent value and potential of biotransformation Rc into Rd.

[Recent advances in biosynthesis of forskolin].

Forskolin is a complex labdane plant diterpenoid, which has been used in the treatment of a variety of diseases based on its activity as an activator of adenosine monophosphate(cAMP) cyclase. Natural forskolin exists only in the cork layer of the root of Coleus forskohlii. Due to the complexity of the extraction and chemical synthesis processes, the yield and purity of forskolin cannot meet commercial requirements. In recent years, with the rapid development of synthetic biology and the analysis and interpretation of many diterpene biosynthetic pathways, a new approach has been provided for the green production of forskolin. In this paper, the structure, activity, biosynthetic pathway and the heterologous biosynthesis of forskolin were reviewed. The problems and solutions in the heterologous biosynthesis of forskolin were also discussed and summarized, which will provide references for the construction of high-yielding forskolin engineering strains.

[Screening siderophore activity of four strains from alkaline environment].

Objective: Siderophore is a low molecular iron chelate produced by microorganisms. It has broad application prospects in medicine, environmental restoration, health food and other fields. According to the literature survey so far, no siderophore was found from alkaline environment eukaryotes. Therefore, screening of fungi with high siderophore activity is of great significance. Methods: By chromium azure S coloration, we screened 99 fungi isolated from Cheng Hai (an alkaline lakes in Yunnan province) and Datun alkaline tailings (Gejiu, Yunnan province). By spectrophotometric detection, we investigated the strain capacity of siderophore and type of siderophore. By solid phase extraction, we investigated the siderophore enrichment effect. Based on electron microscopy morphologic observation and ITS gene phylogenetic tree construction, we identified the strain. Results: Strains FEDT-866, FEDT-145, FECH-998 and FECH-595 were siderophore high-yield ones. Except for strain FEDT-866, the siderophore active substances were suitable for solid phase extraction (SPE). Strains FEDT-866 and FECH-998 belong to Aspergillus and have higher similarity with Aspergillus tubigensis and A. nomius, respectively. Strains FECH-595, FEDT-145 belong to Penicillium and have higher similarity with P. svalbardense and P. chrysogenum. Conclusion: We isolated and identified four fungi for possible siderophore production.

Identification of anti-inflammatory fractions of Geranium wilfordii using tumor necrosis factor-alpha as a drug target on Herbochip® - an array-based high throughput screening platform.

BACKGROUND: Geranium wilfordii is one of the major species used as Herba Geranii (lao-guan-cao) in China, it is commonly used solely or in polyherbal formulations for treatment of joint pain resulted from rheumatoid arthritis (RA) and gout. This herb is used to validate a target-based drug screening platform called Herbochip® and evaluate anti-inflammatory effects of Geranium wilfordii ethanolic extract (GWE) using tumor necrosis factor-alpha (TNF-α) as a drug target together with subsequent in vitro and in vivo assays. METHODS: A microarray-based drug screening platform was constructed by arraying HPLC fractions of herbal extracts onto a surface-activated polystyrene slide (Herbochip®). Using TNF-α as a molecular probe, fractions of 82 selected herbal extracts, including GWE, were then screened to identify plant extracts containing TNF-α-binding agents. Cytotoxicity of GWE and modulatory effects of GWE on TNF-α expression were evaluated by cell-based assays using TNF-α sensitive murine fibrosarcoma L929 cells as an in vitro model. RESULTS: The in vivo anti-inflammatory effects of GWE were further assessed by animal models including carrageenan-induced hind paw edema in rats and xylene-induced ear edema in mice, in comparison with aspirin. The hybridization data obtained by Herbochip® analysis showed unambiguous signals which confirmed TNF-α binding activity in 46 herbal extracts including GWE. In L929 cells GWE showed significant inhibitory effect on TNF-α expression with negligible cytotoxicity. GWE also significantly inhibited formation of carrageenan-induced hind paw edema and xylene-induced ear edema in animal models, indicating that it indeed possessed anti-inflammatory activity. CONCLUSION: We have thus validated effectiveness of the Herbochip® drug screening platform using TNF-α as a molecular target. Subsequent experiments on GWE lead us to conclude that the anti-RA activity of GWE can be attributed to inhibitory effect of GWE on the key inflammatory factor, TNF-α. Our results contribute towards validation of the traditional use of GWE in the treatment of RA and other inflammatory joint disorders.

Sequence-Structure Analysis Unlocking the Potential Functional Application of the Local 3D Motifs of Plant-Derived Diterpene Synthases.

Plant-derived diterpene synthases (PdiTPSs) play a critical role in the formation of structurally and functionally diverse diterpenoids. However, the specificity or functional-related features of PdiTPSs are not well understood. For a more profound insight, we collected, constructed, and curated 199 functionally characterized PdiTPSs and their corresponding 3D structures. The complex correlations among their sequences, domains, structures, and corresponding products were comprehensively analyzed. Ultimately, our focus narrowed to the geometric arrangement of local structures. We found that local structural alignment can rapidly localize product-specific residues that have been validated by mutagenesis experiments. Based on the 3D motifs derived from the residues around the substrate, we successfully searched diterpene synthases (diTPSs) from the predicted terpene synthases and newly characterized PdiTPSs, suggesting that the identified 3D motifs can serve as distinctive signatures in diTPSs (I and II class). Local structural analysis revealed the PdiTPSs with more conserved amino acid residues show features unique to class I and class II, whereas those with fewer conserved amino acid residues typically exhibit product diversity and specificity. These results provide an attractive method for discovering novel or functionally equivalent enzymes and probing the product specificity in cases where enzyme characterization is limited.

A comprehensive review of the recent advances on predicting drug-target affinity based on deep learning.

Accurate calculation of drug-target affinity (DTA) is crucial for various applications in the pharmaceutical industry, including drug screening, design, and repurposing. However, traditional machine learning methods for calculating DTA often lack accuracy, posing a significant challenge in accurately predicting DTA. Fortunately, deep learning has emerged as a promising approach in computational biology, leading to the development of various deep learning-based methods for DTA prediction. To support researchers in developing novel and highly precision methods, we have provided a comprehensive review of recent advances in predicting DTA using deep learning. We firstly conducted a statistical analysis of commonly used public datasets, providing essential information and introducing the used fields of these datasets. We further explored the common representations of sequences and structures of drugs and targets. These analyses served as the foundation for constructing DTA prediction methods based on deep learning. Next, we focused on explaining how deep learning models, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transformer, and Graph Neural Networks (GNNs), were effectively employed in specific DTA prediction methods. We highlighted the unique advantages and applications of these models in the context of DTA prediction. Finally, we conducted a performance analysis of multiple state-of-the-art methods for predicting DTA based on deep learning. The comprehensive review aimed to help researchers understand the shortcomings and advantages of existing methods, and further develop high-precision DTA prediction tool to promote the development of drug discovery.

Aliifodinibius roseus gen. nov., sp. nov., and Aliifodinibius sediminis sp. nov., two moderately halophilic bacteria isolated from salt mine samples.

Two rod-shaped, non-motile bacteria were isolated from two separate salt mines in Yunnan, south-western China. These strains, designated YIM D15(T) and YIM J21(T), were Gram-negative and moderately halophilic. The two strains required 6-10 % NaCl (w/v; optimal) for growth. The DNA G+C contents of strains YIM D15(T) and YIM J21(T) were 49.0 mol% and 48.4 mol%, respectively. The predominant isoprenoid quinone was MK-7. The polar lipid profiles of strains YIM D15(T) and YIM J21(T) were composed predominantly of diphosphatidylglycerol, phosphatidylcholine, phosphatidylethanolamine, three unknown polar lipids and one glycolipid. Minor amounts of other lipids were also detectable. The predominant cellular fatty acids were iso-C15 : 0, anteiso-C15 : 0, iso-C17 : 1ω9c/10 methyl-C16 : 0 and C16 : 1ω7c/C16 : 1ω6c. Phylogenetic analysis based on 16S rRNA gene sequence comparisons showed that the two isolates formed a distinct clade with the genus Fodinibius (in the phylum Bacteroidetes) and were related to the species Fodinibius salinus, with sequence similarities of 91.9-92.4 %. Analyses of 16S rRNA gene sequences revealed that strains YIM D15(T) and YIM J21(T) were related to each other (97.3 % sequence similarity). The DNA-DNA hybridization relatedness between the two isolates was 34 %. On the basis of the phylogenetic analysis, DNA-DNA hybridization relatedness, phenotypic and chemotaxonomic characteristics, strains YIM D15(T) and YIM J21(T) should be classified as members of a novel genus and as two novel species, for which the names Aliifodinibius roseus gen. nov., sp. nov. (type strain YIM D15(T) = ACCC 10715(T) = KCTC 23442(T)) and Aliifodinibius sediminis sp. nov. (type strain YIM J21(T) = ACCC 10714(T) = DSM 21194(T)) are proposed.

Gracilimonas mengyeensis sp. nov., a moderately halophilic bacterium isolated from a salt mine in Yunnan, south-western China.

A facultatively anaerobic, Gram-staining-negative, pale red-pigmented, non-motile, rod-shaped, moderately halophilic bacterium, designated strain YIM J14(T), was isolated from a sediment sample from a salt mine in Yunnan, south-western China. Growth occurred at NaCl concentrations of between 2 % and 15 % (w/v) and optimally with 5-9 % NaCl. The optimum temperature and pH for growth of the strain were 28 °C and pH 7.5. The major cellular fatty acids were iso-C15 : 0, anteiso-C15 : 0 and iso-C17 : 1ω9c/10-methyl-C16 : 0. The polar lipid profile was composed predominantly of diphosphatidylglycerol, phosphatidylcholine and one unknown phospholipid. Minor amounts of other lipids were also detectable. The genomic DNA G+C content was 47.2 mol%. Phylogenetic analysis based on 16S rRNA gene sequence comparisons indicated that strain YIM J14(T) was related to Gracilimonas tropica in the phylum Bacteroidetes. The level of 16S rRNA gene sequence similarity between strain YIM J14(T) and Gracilimonas tropica CL-CB462(T) was 96.9 %. A DNA-DNA hybridization experiment between strain YIM J14(T) and Gracilimonas tropica indicated levels of relatedness of 28 %. Chemotaxonomic data supported the placement of strain YIM J14(T) in the genus Gracilimonas. DNA-DNA hybridization and biochemical and physiological characterization allowed strain YIM J14(T) to be differentiated from Gracilimonas tropica. It is therefore considered to represent a novel species of the genus Gracilimonas, for which the name Gracilimonas mengyeensis sp. nov. is proposed. The type strain YIM J14(T) ( = ACCC 10717(T) = DSM 21985(T)).

Comparative molecular analysis of the prokaryotic diversity of two salt mine soils in southwest China.

While much is known about the microbial diversity in some hypersaline environments, little is known about those of salt mine tunnel soils. The objective of this study was to conduct a comprehensive phylogenetic comparison of the archaeal and bacterial communities present in Yipinglang salt mine (YPL) and Qiaohou salt mine (QH) tunnels differing in salinity and salt composition using 16S rRNA gene clone libraries. Two hundred twenty-eight sequences for QH and 182 sequences for YPL were analyzed by amplified ribosomal DNA-restriction analysis. Libraries revealed 44 bacterial and 57 archaeal different operational taxonomic units belonging to at least 8 bacterial and 3 archaeal divisions, but not all divisions were observed in both salt mines. The bacterial community affiliated with the Bacteroidetes was the most abundant (60% of clones) in QH, while the community in YPL was dominated by δ-Proteobacteria (45% of clones). All archaeal clones from QH were affiliated with Halobacteriaceae. In contrast, in the YPL library, 49% of clones belonged to Halobacteriaceae, 31% of clones related to unclassified archaea, and 21% of clones belonged to Crenarchaeota. Bioinformatic analysis and comparisons showed that the clone libraries were significantly different between two salt mines.

Research Progress of Nervonic Acid Biosynthesis.

Nervonic acid (NA) is a very-long-chain monounsaturated fatty acid with great application values. It plays a vital role in the development of brain nervous system and the treatment of neurological diseases, so it has attracted much attention from all walks of life. Although NA has a wide range of sources, its current acquisition methods are still mainly relied on chemical synthesis and plant extraction, which are challenging to meet the market and green industry demands, limiting its development and application. In recent years, with the rapid development of synthetic biology technology, NA biosynthesis has become an alternative production strategy. In this study, we summarize the physicochemical properties, pharmacological activities, resources, biosynthetic pathways and heterologous biosynthesis of NA, and discuss the challenges and prospects of NA biosynthesis. The application prospects of cell-free systems and retrobiosynthesis in NA synthesis were also reviewed.

Genome sequence of Streptomyces auratus strain AGR0001, a phoslactomycin-producing actinomycete.

Streptomyces auratus strain AGR0001 produces neophoslactomycin A, a novel analog of phoslactomycin that possesses potent activity against some phytopathogenic fungi. Here, the draft genome sequence of S. auratus strain AGR0001 is presented, which would provide insight into the biosynthetic mechanism of neophoslactomycin A.