Using Coexpression Protein Interaction Network Analysis to Identify Mechanisms of Danshensu Affecting Patients with Coronary Heart Disease

Efficient production of salvianic acid A from L-dihydroxyphenylalanine through a tri-enzyme cascade

Salvianic acid A (SAA), used for treating cardiovascular and cerebrovascular diseases, possesses several pharmacological properties. However, the current methods for the enzymatic synthesis of SAA show low efficiency. Here, we constructed a three-enzyme cascade pathway in Escherichia coli BL21 (DE3) to produce SAA from L-dihydroxyphenylalanine (L-DOPA). The phenylpyruvate reductase (LaPPR) from Lactobacillus sp. CGMCC 9967 is a rate-limiting enzyme in this process. Therefore, we employed a mechanism-guided protein engineering strategy to shorten the transfer distances of protons and hydrides, generating an optimal LaPPR mutant, LaPPRMu2 (H89M/H143D/P256C), with a 2.8-fold increase in specific activity and 9.3-time increase in kcat/Km value compared to that of the wild type. Introduction of the mutant LaPPRMu2 into the cascade pathway and the optimization of enzyme levels and transformation conditions allowed the obtainment of the highest SAA titer (82.6 g L-1) ever reported in vivo, good conversion rate (91.3%), excellent ee value (99%) and the highest productivity (6.9 g L-1 h-1) from 90 g L-1 L-DOPA in 12 h. This successful strategy provides a potential new method for the industrial production of SAA.

Introducing Albumin and Interleukin 6 as Common Critical Dysregulated Proteins Between Migraine and Gliosarcoma

Introduction

It is reported that migraine may be a risk factor for brain cancers. Since one of the best ways to assess this possible relationship is to study the molecular mechanism, here the common central dysregulated proteins between these diseases are investigated via network analysis.

Methods

The dysregulated proteins of migraine and gliosarcoma are extracted from the STRING database and interacted via Cytoscape software, version 3.7.2. to form two separate networks. Central nodes of the networks are compared to find the common central district proteins. First neighbors of the common central proteins are studied.

Results

The number of 11 hub bottlenecks was identified for each of the migraine and gliosarcoma cancer networks. Albumin (ALB) and interleukin 6 (IL6) were introduced as common differentially expressed central proteins. Kininogen 1 (KNG1), vascular endothelial growth factor A (VEGFA), and neurofibromatosis type I (NF1) the first neighbors of ALB-IL6 were connected to the central nodes of networks of the two studied diseases.

Conclusion

ALB and IL6 can be considered molecular links between migraine and brain cancers.

Highlights

Differentially expression of albumin (ALB) and interleukin 6 (IL6) is highlighted as the common key events in migraine and gliosarcoma.Kininogen 1 (KNG1), vascular endothelial growth factor A (VEGFA), and neurofibromatosis type I (NF1) are introduced as possible critical players in migraine and gliosarcoma.Based on four centrality parameters, ALB is characterized with stronger centrality properties relative to IL6.

Plain Language Summary

Migraine is considered as a possible risk factor for brain cancers. Therefor exploring of relationship between brain cancers and migraine is attracted attention of researchers. Understanding of diseases molecular mechanism is an important tool to better diagnosis and therapy of the studied disorders. In the present study, the common features of molecular events in migraine and gliosarcoma are studied based on protein expression changes. Analysis indicates that a few numbers of proteins play critical roles in migraine and gliosarcoma. ALB, IL6, KNG1, VEGFA, and NF1 are highlighted as the key proteins which are dysregulated in the two studied diseases. Prominent role of ALB in development of cancers is pointed out by several researchers. Important role of IL6 in promotion of migraine is disused in the previous documents. Since some diseases are risk factors for the other disorders, understanding the common features of two diseases can provide suitable therapeutic protocol to prevent development of diseases. Our finding can be used to provide suitable procedure to prevent conversion of migraine to brain cancer.

Understanding noise in cell signalling in the prospect of drug-targets

The introduction of noise to signals can alter central regulatory switches of cellular processes leading to diseases. Noise is inherently present in the cellular signalling system and plays a decisive role in the input-output (I/O) relation. The current study aims to understand the noise tolerance of motif structures in the cell signalling processes. The vulnerability of a node to noise could be a significant factor in causing signalling error and need to be controlled. We developed stochastic differential equation (SDE) based mathematical models for different network motifs with two nodes and studied the association between motif structure and signal-noise relation. A two-dimensional parameter space analysis on motif sensitivity with noise and input signal variation was performed to classify and rank the motifs. Identifying sensitive motifs and their high druggability infers their significance in screening potential drug-target candidates. Finally, we proposed a theoretical framework to identify nodes from a network as potential drug targets. We applied this mathematical formalism to three cancer networks to identify drug-targets and validated them with existing databases.

Time-dependent Effects of Moderate- and High-intensity Exercises on Myocardial Transcriptomics

The heart is a highly adaptable organ that responds to changes in functional requirements due to exposure to internal and external stimuli. Physical exercise has unique stimulatory effects on the myocardium in both healthy individuals and those with health disorders, where the effects are primarily determined by the intensity and recovery time of exercise. We investigated the time-dependent effects of different exercise intensities on myocardial transcriptional expression in rats. Moderate intensity exercise induced more differentially expressed genes in the myocardium than high intensity exercise, while 16 differentially expressed genes were down-regulated by moderate intensity exercise but up-regulated by high intensity exercise at 12 h post- exercise. Both Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis indicated that moderate intensity exercise specifically regulated gene expression related to heart adaptation, energy metabolism, and oxidative stress, while high intensity exercise specifically regulated gene expression related to immunity, inflammation, and apoptosis. Moreover, there was increased expression of Tbx5, Casq1, Igsf1, and Ddah1 at all time points after moderate intensity exercise, while there was increased expression of Card9 at all time points after high intensity exercise. Our study provides a better understanding of the intensity dependent effects of physical exercise of the molecular mechanisms of cardiac adaptation to physical exercise.

To explore the active constituents of Sedum aizoon L in the treatment of coronary heart disease based on network pharmacology and molecular docking methodology

Background

There is a lack of effective drugs for the treatment of coronary heart disease (CHD). Sedum aizoon L (SL) has multiple effects, and there is no report on CHD in SL at present. The aim of this study is to explore the mechanisms of action of SL in the treatment of CHD based on network pharmacology and molecular docking technology.

Methods

The targets and active ingredients of SL were screened using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, and CHD-related targets were obtained by searching GeneCards and DisGeNet databases. The intersection of LS active ingredient targets and CHD targets was used to construct a "drug-ingredient-disease-target" network using the Cytoscape software. The STRING database was used to construct a protein-protein interaction (PPI) network, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. Key targets and core active ingredients were selected and molecular docking was performed using the AutoDock software.

Results

According to the predicted results, a total of 134 corresponding target genes for LS, 12 active components, 1,704 CHD-related targets, and 52 intersecting targets were obtained. GO function and KEGG pathway analysis showed that the key targets were involved with signal transducer and activator of transcription 3 (STAT3), tumor protein p53 (TP53), and vascular endothelial growth factor A (VEGFA). The molecular docking results showed that the key targets bound to the important active ingredients in a stable conformation. The core active ingredients of LS in the treatment of CHD were determined to be ursolic acid, myricetin, and beta-sitosterol.

Conclusions

SL may act on targets such as STAT3, TP53, and VEGFA through tumor necrosis factor (TNF) signaling pathway, interleukin 17A (IL-17A) signaling pathway, AGE-RAGE signaling pathway in diabetic complications, and other related pathways, thereby playing a role in preventing and treating CHD.

Exploring the Mechanism of Hawthorn Leaves Against Coronary Heart Disease Using Network Pharmacology and Molecular Docking

Hawthorn leaves, which is a traditional Chinese medicine (TCM), has been used for treating coronary heart disease (CHD) for a long time in China. But the limited understanding of the main active components and molecular mechanisms of this traditional medicine has restricted its application and further research. The active compounds of hawthorn leaves were obtained from TCMSP database and SymMap database. The targets of it were predicted based on TCMSP, PubChem, Swiss Target Prediction, and SymMap database. The putative targets of CHD were gathered from multi-sources databases including the Online Mendelian Inheritance in Man (OMIM) database, the DrugBank database, the GeneCards database and the DisGeNet database. Network topology analysis, GO and KEGG pathway enrichment analyses were performed to select the key targets and pathways. Molecular docking was performed to demonstrate the binding capacity of the key compounds to the predicted targets. Furthermore, RAW264.7 cells stimulated by lipopolysaccharides (LPS) were treated with three effective compounds of hawthorn leaves to assess reliability of prediction. Quercetin, isorhamnetin and kaempferol were main active compounds in hawthorn leaves. Forty four candidate therapeutic targets were identified to be involved in protection of hawthorn leaves against CHD. Additionally, the effective compounds of it had good binding affinities to PTGS2, EGFR, and MMP2. Enrichment analyses suggested that immune inflammation related biological processes and pathways were possibly the potential mechanism. Besides, we found that three predicted effective compounds of hawthorn leaves decreased protein expression of PTGS2, MMP2, MMP9, IL6, IL1B, TNFα and inhibited activation of macrophage. In summary, the present study demonstrates that quercetin, kaempferol and isorhamnetin are proved to be the main effective compounds of hawthorn leaves in treatment of CHD, possibly by suppressing expression of PTGS2, MMP2, MMP9, inflammatory cytokines and macrophages viability. This study provides a new understanding of the active components and mechanisms of hawthorn leaves treating CHD from the perspective of network pharmacology.

In silico Methods for Identification of Potential Therapeutic Targets

At the initial stage of drug discovery, identifying novel targets with maximal efficacy and minimal side effects can improve the success rate and portfolio value of drug discovery projects while simultaneously reducing cycle time and cost. However, harnessing the full potential of big data to narrow the range of plausible targets through existing computational methods remains a key issue in this field. This paper reviews two categories of in silico methods—comparative genomics and network-based methods—for finding potential therapeutic targets among cellular functions based on understanding their related biological processes. In addition to describing the principles, databases, software, and applications, we discuss some recent studies and prospects of the methods. While comparative genomics is mostly applied to infectious diseases, network-based methods can be applied to infectious and non-infectious diseases. Nonetheless, the methods often complement each other in their advantages and disadvantages. The information reported here guides toward improving the application of big data-driven computational methods for therapeutic target discovery.

Graphical abstract

A Signature for Smoking Status of Coronary Heart Disease Patients through Weighted Gene Coexpression Network Analysis

Background. Smoking is one of the risk factors of coronary heart disease (CHD), while its underlying mechanism is less well defined. Purpose. To identify and testify 6 key genes of CHD related to smoking through weighted gene coexpression network analysis (WGCNA), protein-protein interaction (PPI) network analysis, and pathway analysis. Methods. CHD patients’ samples were first downloaded from Gene Expression Omnibus (GEO). Then, genes of interest were obtained after analysis of variance (ANOVA). Thereafter, 23 coexpressed modules that were determined after genes with similar expression were incorporated via WGCNA. The biological functions of genes in the modules were researched by enrichment analysis. Pearson correlation analysis and PPI network analysis were used to screen core genes related to smoking in CHD. Results. The violet module was the most significantly associated with smoking ( $r=-0.28$ , $p=0.006$ ). Genes in this module mainly participated in biological functions related to the heart. Altogether, 6 smoking-related core genes were identified through bioinformatics analyses. Their expressions in animal models were detected through the animal experiment. Conclusion. This study identified 6 core genes to serve as underlying biomarkers for monitoring and predicting smoker’s CHD risk.

Efficacy of Yangxin Recipe in Combination with Conventional Western Medicine in Treatment of Angina Pectoris of Coronary Heart Disease

Objective

To study the efficacy of Yangxin Recipe (YXR) in patients with stable angina pectoris of coronary heart disease and its impacts on coronary CT angiography.

Methods

A total of 78 patients with coronary heart disease and angina pectoris were randomly divided into a control group (n = 39) and a YXR group (n = 39). The control group adopted conventional Western medicine while the YXR group received conventional western medicine + oral administration of YXR. After six months of continuous treatment, the clinical efficacy, traditional Chinese medicine (TCM) syndrome scores, Pittsburgh Sleep Quality Index (PSQI), and the level of coronary CT vascular stenosis were observed.

Results

After treatment, the total effective rate of YXR was 92.31%, which was higher than (P < 0.01) that of the western medicine control group. The total score of TCM syndromes in the YXR group was (14.44 ± 9.87), which was significantly lower than (P < 0.001) that in the simple western medicine control group (22.44 ± 13.87). The degree of coronary stenosis in the YXR group decreased to (49.87 ± 7.82) %, which was significantly lower than (P < 0.001) that in the western medicine control group (57.05 ± 9.92) %.

Conclusion

The efficacy of YXR + conventional western medicine in treating coronary heart disease and angina pectoris is significantly improved compared with the simple conventional western medicine.

UPLC/MS-based untargeted metabolomics reveals the changes of metabolites profile of Salvia miltiorrhiza bunge during Sweating processing

Salvia miltiorrhiza has numerous compounds with extensive clinical application. "Sweating", a processing method of Traditional Chinese Medicine (TCM), results in great changes in pharmacology and pharmacodynamics. Previously, chromatogram of 10 characteristic metabolites in S. miltiorrhiza showed a significant difference after "Sweating". Due to the complexity of TCM, changes in metabolites should be investigated metabolome-wide after "Sweating". An untargeted UPLC/MS-based metabolomics was performed to discover metabolites profile variation of S. miltiorrhiza after "Sweating". Multivariate analysis was conducted to screen differential metabolites. Analysis indicated distinct differences between sweated and non-sweated samples. 10,108 substance peaks had been detected altogether, and 4759 metabolites had been identified from negative and positive ion model. 287 differential metabolites were screened including 112 up-regulated and 175 down-regulated and they belong to lipids and lipid-like molecules, and phenylpropanoid and polyketides. KEGG analysis showed the pathway of linoleic acid metabolism, and glyoxylate and dicarboxylate metabolism were mainly enriched. 31 and 49 identified metabolites were exclusively detected in SSM and NSSM, respectively, which mainly belong to carboxylic acids and derivatives, polyketides and fatty acyls. By mapping tanshinones and salvianolic acids to 4759 identified metabolites library, 23 characteristic metabolites had been identified, among which 11 metabolites changed most. We conclude that "Sweating'' has significant effect on metabolites content and composition of S. miltiorrhiza.

UFLC-MS/MS Determination and Population Pharmacokinetic Study of Tanshinol, Ginsenoside Rb1 and Rg1 in Rat Plasma After Oral Administration of Compound Danshen Dripping Pills

BACKGROUND AND OBJECTIVES

As a traditional Chinese Materia Medica (CMM), the Compound Danshen Dripping Pill (CDDP) is widely used for the treatments of cardiovascular diseases. In view of its undefined applicable population and dosage, a population pharmacokinetic (PPK) study is required. The objective of this study was to explore the feasibility of multi-component CMM PPK in rat plasma after oral administration of CDDP based on sparse sampling.

METHODS

In this research, a simple, rapid and highly sensitive UFLC-MS/MS method for the simultaneous determination of tanshinol (TSL), ginsenoside Rb1 (GRb1) and ginsenoside Rg1 (GRg1) has been successfully developed in rat plasma. Moreover, the validated method has been applied to a PPK study of CDDP based on sparse data. We established the PPK models for these three main active constituents using a nonlinear mixed-effects model, taking into account of factors such as gender, age in weeks and weight.

RESULTS

The PPK models of TSL and GRb1 were best described by a one-compartment model with linear elimination and first-order absorption. The model of GRg1 was best described by a two-compartment model with first-order absorption. Bootstrap validation and a visual predictive check confirmed the predictive ability, the model stability and the precision of the parameter estimates from these models.

CONCLUSION

As a preliminary exploration toward the clinical population pharmacokinetic research, this study provides a reference for the population pharmacokinetic study of traditional CMM.

Enzymological characterization of a novel d-lactate dehydrogenase from Lactobacillus rossiae and its application in d-phenyllactic acid synthesis

A novel lactate dehydrogenase gene, named lrldh, was cloned from Lactobacillus rossiae and heterologously expressed in Escherichia coli. The lactate dehydrogenase LrLDH is NADH-dependent with a molecular weight of approximately 39 kDa. It is active at 40 °C and pH 6.5 and stable in a neutral to alkaline environment below 35 °C. The kinetic constants, including maximal reaction rate (V _max), apparent Michaelis-Menten constant (K _m), turnover number (K _cat) and catalytic efficiency (K _cat/K _m) for phenylpyruvic acid were 1.95 U mg^-1, 2.83 mM, 12.29 s^-1, and 4.34 mM^-1 s^-1, respectively. Using whole cells of recombinant E. coli/pET28a-lrldh, without coexpression of a cofactor regeneration system, 20.5 g l^-1 d-phenyllactic acid with ee above 99% was produced from phenylpyruvic acid in a fed-batch biotransformation process, with a productivity of 49.2 g l^-1 d^-1. Moreover, LrLDH has broad substrate specificity to a range of ketones, keto acids and ketonic esters. Taken together, LrLDH is a promising biocatalyst for the efficient synthesis of d-phenyllactic acid and other fine chemicals.

Differential protein profiling of soil diazotroph Rhodococcus qingshengii S10107 towards low-temperature and nitrogen deficiency

Protein-based biomarkers can be a promising approach for identification and real-time monitoring of the bio-inoculants employed under sustainable agricultural plans. In this perspective, differential proteomics of psychrophilic diazotroph Rhodococcus qingshengii S10107 (JX173283) was performed to unravel its adaptive responses towards low-temperature nitrogen deficiency and identification of a biomarker for respective physiological conditions. LC-MS/MS-based proteome analysis mapped more than 4830 proteins including 77 up-regulated and 47 down-regulated proteins (p ≤ 0.05). Differential expression of the structural genes of nif regulon viz. nifH, nifD, and nifK along with their response regulators i.e. nifA, nifL, and nifB indicated that the nitrogenase complex was activated successfully. Besides up-regulating the biosynthesis of certain amino acids viz. Leucine, Lysine, and Alanine; the expression of the peptidoglycan synthesis proteins were also increased; while, the enzymes involved in Lipid biosynthesis were found to decrease. Furthermore, two important enzymes of the pentose phosphate pathway viz. Transketolase and Transaldolase along with Ribose import ATP-binding protein RbsA were also found to induce significantly under low temperature a nitrogen deficient condition, which suggests the cellular need for ample ribose sugar instantly. Additionally, comparative protein profiling of S10107 strain with our previous studies revealed that CowN protein was significantly up-regulated in all the cases under low-temperature nitrogen deficient conditions and therefore, can be developed as a biomarker. Conclusively, present study for the first time provides an in-depth proteome profiling of R. qingshengii S10107 and proclaims CowN as a potential protein biomarker for monitoring BNF under cold niches.

Pharmacokinetics of Active Ingredients of Salvia miltiorrhiza and Carthamus tinctorius in Compatibility in Normal and Cerebral Ischemia Rats: A Comparative Study

Background and Objective

Dan-Hong injection, which comprises extracts of Salvia miltiorrhiza and Carthamus tinctorius, promotes blood circulation and reduces blood stasis. Combination of S. miltiorrhiza and C. tinctorius is more effective in treating cerebral ischemia than S. miltiorrhiza alone. This study aimed to examine the pharmacokinetic characteristics of four active ingredients of S. miltiorrhiza and C. tinctorius, namely danshensu (DSS), hydroxysafflor yellow A (HSYA), and salvianolic acid A (SAA) and B (SAB) in normal and cerebral ischemia rats.

Methods

Normal and cerebral ischemia rats were injected via the tail vein with each active ingredient, and blood was collected through the jaw vein at different time points. The plasma concentration of the compatibility group was analyzed by high-performance liquid chromatography, and pharmacokinetic parameters were determined using Pharmacokinetic Kinetica 4.4 software.

Results

The pharmacokinetics of the four active ingredients in the normal and cerebral ischemia rats were consistent with a two-compartment model. The area under the concentration–time curve was higher in normal rats than in cerebral ischemia rats, with a highly significant difference for SAA (P < 0.01). Clearance rates were lower in normal rats than in cerebral ischemia rats, with DSS showing the most significant difference (P < 0.01). Furthermore, there were significant differences between normal and cerebral ischemia rats in the distribution phase-elimination half life for DSS, SAA, and HSYA, as well as in the apparent volume of distribution for the central compartment for DSS and HSYA (P < 0.01). The plasma concentrations of the four active ingredients were higher in normal rats than in cerebral ischemia rats.

Conclusion

Cerebral ischemia rats showed higher drug clearance rates and longer retention times than normal rats, which may be due to destruction of the blood–brain barrier during cerebral ischemia–reperfusion. The four active ingredients likely integrated and interacted with each other to affect target sites in the brain to protect against cerebral ischemic injury.

A Network of SLC and ABC Transporter and DME Genes Involved in Remote Sensing and Signaling in the Gut-Liver-Kidney Axis

Genes central to drug absorption, distribution, metabolism and elimination (ADME) also regulate numerous endogenous molecules. The Remote Sensing and Signaling Hypothesis argues that an ADME gene-centered network-including SLC and ABC "drug" transporters, "drug" metabolizing enzymes (DMEs), and regulatory genes-is essential for inter-organ communication via metabolites, signaling molecules, antioxidants, gut microbiome products, uremic solutes, and uremic toxins. By cross-tissue co-expression network analysis, the gut, liver, and kidney (GLK) formed highly connected tissue-specific clusters of SLC transporters, ABC transporters, and DMEs. SLC22, SLC25 and SLC35 families were network hubs, having more inter-organ and intra-organ connections than other families. Analysis of the GLK network revealed key physiological pathways (e.g., involving bile acids and uric acid). A search for additional genes interacting with the network identified HNF4α, HNF1α, and PXR. Knockout gene expression data confirmed ~60-70% of predictions of ADME gene regulation by these transcription factors. Using the GLK network and known ADME genes, we built a tentative gut-liver-kidney "remote sensing and signaling network" consisting of SLC and ABC transporters, as well as DMEs and regulatory proteins. Together with protein-protein interactions to prioritize likely functional connections, this network suggests how multi-specificity combines with oligo-specificity and mono-specificity to regulate homeostasis of numerous endogenous small molecules.

Network Pharmacology-Based Prediction and Verification of the Targets and Mechanism for Panax Notoginseng Saponins against Coronary Heart Disease

Coronary heart disease (CHD) is the worldwide leading cause for cardiovascular death. Panax notoginseng saponin (PNS), which is the main bioactive compound of panax notoginseng, has been generally accepted to exert a remarkable effect on CHD for a long time. However, to reveal the underlying treatment target and corresponding mechanism of PNS against CHD is still a substantial challenge. In this work, the targets and mechanism of PNS against CHD were successfully achieved by pharmacology-based prediction and experimental verification. 36 common targets were screened out through integrating the gene expression profile of CHD and the chemical-protein data of PNS. Then, two key nodes were further selected for verification by experiment after analyzing GO function, KEGG pathway, coexpression, and topology analysis. Results showed that PNS has protected the human umbilical vein endothelial cells from H₂O₂-induced oxidative stress by inhibiting early cell apoptosis via upregulating VEGFA mRNA expression. Therefore, our research has successfully pointed out one treatment target and apoptotic inhibition caused by PNS with method of integrating bioinformatics prediction and experimental verification, which has partially explained the pharmacological mechanism of PNS against CHD.

Redox self-sufficient biocatalyst system for conversion of 3,4-Dihydroxyphenyl-L-alanine into (R)- or (S)-3,4-Dihydroxyphenyllactic acid

We developed an efficient multi-enzyme cascade reaction to produce (R)- or (S)-3,4-Dihydroxyphenyllactic acid [(R)- or (S)-Danshensu, (R)- or (S)-DSS] from 3,4-Dihydroxyphenyl-L-alanine (L-DOPA) in Escherichia coli by introducing tyrosine aminotransferase (tyrB), glutamate dehydrogenase (cdgdh) and D-aromatic lactate dehydrogenase (csldhD) or L-aromatic lactate dehydrogenase (tcldhL). First, the genes in the pathway were overexpressed and fine-tuned for (R)- or (S)-DSS production. The resulting strain, E. coli TGL 2.1 and E. coli TGL 2.2, which overexpressed tyrB with the stronger T7 promoter and cdgdh, csldhD or tcldhL with the weaker Trc promoter, E. coli TGL 2.1 yielded 57% increase in (R)-DSS production: 59.8 ± 2.9 mM. Meanwhile, E. coli TGL 2.2 yielded 54% increase in (S)-DSS production: 52.2 ± 2.4 mM. The optimal concentration of L-glutamate was found to be 20 mM for production of (R)- or (S)-DSS. Finally, L-DOPA were transformed into (R)- or (S)-DSS with an excellent enantiopure form (enantiomeric excess > 99.99%) and productivity of 6.61 mM/h and 4.48 mM/h, respectively.

One-pot, three-step cascade synthesis of D-danshensu using engineered Escherichia coli whole cells

D-danshensu (D-DSS), extracted from the plant Salvia miltiorrhiza (Danshen), is widely used to treat cardiovascular and cerebrovascular diseases. Here we engineered Escherichia coli strains to produce D-DSS from catechol, pyruvate and ammonia by one-pot biotransformation. Tyrosin-phenol lyase (TPL), L-amino acid deaminase (aadL), D-lactate dehydrogenase (ldhD) and glucose dehydrogenase (gdh) genes were overexpressed in Escherichia coli strain. First, the expression of genes was regulated by different copy number plasmids combination, the result of E. coli TALG6, with strong overexpression of TPL, aadL, ldhD and moderate overexpression of gdh, exhibited 253.7% increase D-DSS production compared to E. coli TALG1. Second, the optimum concentration of catechol was found to be 50 mM. Finally, a fed-batch biotransformation strategy was proposed, namely the amount of catechol was added to 50 mM every 2 h. The total production of D-DSS reached 55.35 mM within 14 h, which was 1.7 times that without feeding.

Quantitative proteomics of psychotrophic diazotroph in response to nitrogen deficiency and cold stress

Effective protocols and novel biomarkers are the need of this hour to screen potential cold adapted diazotrophs for sustainable mountain agricultural plans. LC-MS/MS based gel less quantitative proteomics was employed to investigate the metabolic response of Himalayan cold adapted diazotroph Pseudomonas palleroniana N26 (JN055435) for nitrogen deficiency and cold stress. More than 5000 proteins were identified, and 125 of them showed significant difference with a 2-fold or greater change (p < .05) between normal and stress conditions, including 29 up-regulated proteins and 35 down-regulated proteins. Expression of nifA, nifL, nifH, nifB, nifD, and nifK during N₂ fixing conditions reveals that nitrogenase system was successfully activated. Further, 8% of the upregulated proteins showed similarity with uncharacterized proteins of several nitrogen fixing genera which suggests their in-depth investigation. Additionally, as per earlier studies, cowN was differentially expressed under nitrogen fixing conditions; thereby, confirming its potential to be a potent biomarker for monitoring the nitrogen fixation in cold niches.

BIOLOGICAL SIGNIFICANCE

Understanding of nitrogenase expression and regulation is essential to employ potential diazotrophs under diverse ecological niches to achieve agricultural as well as environmental sustainability. The molecular mechanisms of cold adapted diazotrophy are still unaddressed. In this scenario, present study, besides characterizing diazotrophic proteins, is helpful in identifying the protein(s) or a biomarker viz. CowN to facilitate the monitoring of nitrogen fixation in cold niches. To the best of our knowledge, this is the first gel-less quantitative free-living diazotrophic proteome study using label free mass spectrometry having high mass accuracy in both MS and MS/MS scans. It enriches the diazotrophic proteome database and will complement the other "omics" technologies for improved crop protection and sustainability strategies.

Salvia miltiorrhizaBurge (Danshen): a golden herbal medicine in cardiovascular therapeutics

Salvia miltiorrhiza Burge (Danshen) is an eminent medicinal herb that possesses broad cardiovascular and cerebrovascular protective actions and has been used in Asian countries for many centuries. Accumulating evidence suggests that Danshen and its components prevent vascular diseases, in particular, atherosclerosis and cardiac diseases, including myocardial infarction, myocardial ischemia/reperfusion injury, arrhythmia, cardiac hypertrophy and cardiac fibrosis. The published literature indicates that lipophilic constituents (tanshinone I, tanshinone IIa, tanshinone IIb, cryptotanshinone, dihydrotanshinone, etc) as well as hydrophilic constituents (danshensu, salvianolic acid A and B, protocatechuic aldehyde, etc) contribute to the cardiovascular protective actions of Danshen, suggesting a potential synergism among these constituents. Herein, we provide a systematic up-to-date review on the cardiovascular actions and therapeutic potential of major pharmacologically active constituents of Danshen. These bioactive compounds will serve as excellent drug candidates in small-molecule cardiovascular drug discovery. This article also provides a scientific rationale for understanding the traditional use of Danshen in cardiovascular therapeutics.

Prioritizing chronic obstructive pulmonary disease (COPD) candidate genes in COPD-related networks

Chronic obstructive pulmonary disease (COPD) is a multi-factor disease, which could be caused by many factors, including disturbances of metabolism and protein-protein interactions (PPIs). In this paper, a weighted COPD-related metabolic network and a weighted COPD-related PPI network were constructed base on COPD disease genes and functional information. Candidate genes in these weighted COPD-related networks were prioritized by making use of a gene prioritization method, respectively. Literature review and functional enrichment analysis of the top 100 genes in these two networks suggested the correlation of COPD and these genes. The performance of our gene prioritization method was superior to that of ToppGene and ToppNet for genes from the COPD-related metabolic network or the COPD-related PPI network after assessing using leave-one-out cross-validation, literature validation and functional enrichment analysis. The top-ranked genes prioritized from COPD-related metabolic and PPI networks could promote the better understanding about the molecular mechanism of this disease from different perspectives. The top 100 genes in COPD-related metabolic network or COPD-related PPI network might be potential markers for the diagnosis and treatment of COPD.