Enzymatic Fluoromethylation as a Tool for ATP-Independent Ligation.

S-adenosylmethionine-dependent methyltransferases are involved in countless biological processes, including signal transduction, epigenetics, natural product biosynthesis, and detoxification. Only a handful of carboxylate methyltransferases have evolved to participate in amide bond formation. In this report we show that enzyme-catalyzed F-methylation of carboxylate substrates produces F-methyl esters that readily react with N- or S-nucleophiles under physiological conditions. We demonstrate the applicability of this approach to the synthesis of small amides, hydroxamates, and thioesters, as well as to site-specific protein modification and native chemical ligation.

Genome-Wide Characterization and Expression of the Hsf Gene Family in Salvia miltiorrhiza (Danshen) and the Potential Thermotolerance of SmHsf1 and SmHsf7 in Yeast.

Salvia miltiorrhiza Bunge (Danshen) is a traditional Chinese herb with significant medicinal value. The yield and quality of Danshen are greatly affected by climatic conditions, in particular high temperatures. Heat shock factors (Hsfs) play important regulatory roles in plant response to heat and other environmental stresses. However, little is currently known about the role played by the Hsf gene family in S. miltiorrhiza. Here, we identified 35 SmHsf genes and classified them into three major groups: SmHsfA (n = 22), SmHsfB (n = 11), and SmHsfC (n = 2) using phylogenetic analysis. The gene structure and protein motifs were relatively conserved within subgroups but diverged among the different groups. The expansion of the SmHsf gene family was mainly driven by whole-genome/segmental and dispersed gene duplications. The expression profile of SmHsfs in four distinct organs revealed its members (23/35) are predominantly expressed in the root. The expression of a large number of SmHsfs was regulated by drought, ultraviolet, heat and exogenous hormones. Notably, the SmHsf1 and SmHsf7 genes in SmHsfB2 were the most responsive to heat and are conserved between dicots and monocots. Finally, heterologous expression analysis showed that SmHsf1 and SmHsf7 enhance thermotolerance in yeast. Our results provide a solid foundation for further functional investigation of SmHsfs in Danshen plants as a response to abiotic stresses.

[Gene cloning, induction, and prokaryotic expression of a Sm14-3-3 protein from Salvia miltiorrhiza].

14-3-3 proteins are important proteins in plants, as they regulate plant growth and development and the response to biotic or abiotic stresses. In this study, a 14-3-3 gene(GenBank accession: OM683281) was screened from the cDNA library of the medicinal species Salvia miltiorrhiza by yeast two-hybrid and cloned. The open reading frame(ORF) was 780 bp, encoding 259 amino a cids. Bioinformatics analysis predicted that the protein was a non-transmembrane protein with the molecular formula of C_(1287)H_(2046)N_(346)O_(422)S_9, relative molecular weight of 29.4 kDa, and no signal peptide. Homologous sequence alignment and phylogenetic tree analysis proved that the protein belonged to 14-3-3 family and had close genetic relationship with the 14-3-3 proteins from Arabidopsis thaliana, Oryza sativa, and Nicotiana tabacum. The 14-3-3 gene was ligated to the prokaryotic expression vector pGEX-4 T-1 and then transformed into Escherichia coli BL21 for the expression of recombinant protein. Real-time fluorescent quantitative PCR showed that the expression of this gene was different among roots, stems, leaves, and flowers of S. miltiorrhiza. To be specific, the highest expression was found in leaves, followed by stems, and the lowest expression was detected in flowers. S. miltiorrhiza plants were treated with 15% PEG(simulation of drought), and hormones salicylic acid, methyl jasmonate, and ethephon, respectively, and the expression of 14-3-3 gene peaked at the early stage of induction. Therefore, the gene can quickly respond to abiotic stresses such as drought and plant hormone treatments such as salicylic acid, jasmonic acid, and ethylene. This study lays the foundation for revealing the molecular mechanism of 14-3-3 protein regulating tanshinone biosynthesis and responding to biotic and abiotic stresses.

Profiling protein expression in Klebsiella pneumoniae with a carbohydrate-based covalent probe.

We report the application of a covalent probe based on a d-glucosamine scaffold for the profiling of the bacterial pathogen Klebsiella pneumoniae. Incubation of K. pneumoniae lysates with the probe followed by electrophoretic separation and in-gel fluorescence detection allowed the generation of strain-specific signatures and the differentiation of a carbapenem-resistant strain. The labelling profile of the probe was independent of its anomeric configuration and included several low-abundance proteins not readily detectable by conventional protein staining. Initial target identification experiments by mass spectrometry suggest that target proteins include several carbohydrate-recognising proteins, which indicates that the sugar scaffold may have a role for target recognition.

Fluorinated S-Adenosylmethionine as a Reagent for Enzyme-Catalyzed Fluoromethylation.

Strategic replacement of protons with fluorine atoms or functional groups with fluorine-containing fragments has proven a powerful strategy to optimize the activity of therapeutic compounds. For this reason, the synthetic chemistry of organofluorides has been the subject of intense development and innovation for many years. By comparison, the literature on fluorine biocatalysis still makes for a slim chapter. Herein we introduce S-adenosylmethionine (SAM) dependent methyltransferases as a new tool for the production of fluorinated compounds. We demonstrate the ability of halide methyltransferases to form fluorinated SAM (S-adenosyl-S-(fluoromethyl)-L-homocysteine) from S-adenosylhomocysteine and fluoromethyliodide. Fluorinated SAM (F-SAM) is too unstable for isolation, but is accepted as a substrate by C-, N- and O-specific methyltransferases for enzyme-catalyzed fluoromethylation of small molecules.

Enzymatic Fluoromethylation as a Tool for ATP-Independent Ligation.

S-adenosylmethionine-dependent methyltransferases are involved in countless biological processes, including signal transduction, epigenetics, natural product biosynthesis, and detoxification. Only a handful of carboxylate methyltransferases have evolved to participate in amide bond formation. In this report we show that enzyme-catalyzed F-methylation of carboxylate substrates produces F-methyl esters that readily react with N- or S-nucleophiles under physiological conditions. We demonstrate the applicability of this approach to the synthesis of small amides, hydroxamates, and thioesters, as well as to site-specific protein modification and native chemical ligation.

Relaxation spectral analysis in multi-contrast vascular magnetic particle imaging.

BACKGROUND: Magnetic nanoparticles (MNPs) are used as tracers without ionizing radiation in vascular imaging, molecular imaging, and neuroimaging. The relaxation mechanisms of magnetization in response to excitation magnetic fields are important features of MNPs. The basic relaxation mechanisms include internal rotation (Néel relaxation) and external physical rotation (Brownian relaxation). Accurate measurement of these relaxation times may provide high sensitivity for predicting MNP types and viscosity-based hydrodynamic states. It is challenging to separately measure the Néel and Brownian relaxation components using sinusoidal excitation in conventional MPI. PURPOSE: We developed a multi-exponential relaxation spectral analysis method to separately measure the Néel and Brownian relaxation times in the magnetization recovery process in pulsed vascular MPI. METHODS: Synomag-D samples with different viscosities were excited using pulsed excitation in a trapezoidal-waveform relaxometer. The samples were excited at different field amplitudes ranging from 0.5 to 10 mT at intervals of 0.5 mT. The inverse Laplace transform-based spectral analysis of the relaxation-induced decay signal in the field-flat phase was performed by using PDCO, a primal-dual interior method for convex objectives. Néel and Brownian relaxation peaks were elucidated and measured on samples with various glycerol and gelatin concentrations. The sensitivity of viscosity prediction of the decoupled relaxation times was evaluated. A digital vascular phantom was designed to mimic a plaque with viscous MNPs and a catheter with immobilized MNPs. Spectral imaging of the digital vascular phantom was simulated by combining a field-free point with homogeneous pulsed excitation. The relationship between the Brownian relaxation time from different tissues and the number of periods for signal averages was evaluated for a scan time estimation in the simulation. RESULTS: The relaxation spectra of synomag-D samples with different viscosity levels exhibited two relaxation time peaks. The Brownian relaxation time had a positive linear relationship with the viscosity in the range 0.9 to 3.2 mPa · s. When the viscosity was >3.2 mPa · s, the Brownian relaxation time saturated and did not change with increasing viscosity. The Néel relaxation time decreased slightly with an increase in the viscosity. The Néel relaxation time exhibited a similar saturation effect when the viscosity level was >3.2 mPa · s for all field amplitudes. The sensitivity of the Brownian relaxation time increased with the field amplitude and was maximized at approximately 4.5 mT. The plaque and catheter regions were differentiated from the vessel region in the simulated Brownian relaxation time map. The simulation results show that the Néel relaxation time was 8.33±0.09 µs in the plaque region, 8.30±0.08 µs in the catheter region, and 8.46±0.11 µs in the vessel region. The Brownian relaxation time was 36.60±2.31 µs in the plaque region, 30.17±1.24 µs in the catheter region, and 31.21±1.53 µs in the vessel region. If we used 20 excitation periods for image acquisition in the simulation, the total scan time of the digital phantom was approximately 100 s. CONCLUSION: Quantitative assessment of the Néel and Brownian relaxation times through inverse Laplace transform-based spectral analysis in pulsed excitation, highlighting their potential for use in multi-contrast vascular MPI.

Deep learning quantified mucus-tumor ratio predicting survival of patients with colorectal cancer using whole-slide images.

Background: In colorectal cancer (CRC), mucinous adenocarcinoma differs from other adenocarcinomas in gene-phenotype, morphology, and prognosis. However, mucinous components are present in a large number of adenocarcinomas, and the prognostic value of mucus proportion has not been investigated. Artificial intelligence provides a way to quantify mucus proportion on whole-slide images (WSIs) accurately. We aimed to quantify mucus proportion by deep learning and further investigate its prognostic value in two CRC patient cohorts. Methods: Deep learning was used to segment WSIs stained with hematoxylin and eosin. Mucus-tumor ratio (MTR) was defined as the proportion of mucinous component in the tumor area. A training cohort (N = 419) and a validation cohort (N = 315) were used to evaluate the prognostic value of MTR. Survival analysis was performed using the Cox proportional hazard model. Result: Patients were stratified to mucus-low and mucus-high groups, with 24.1% as the threshold. In the training cohort, patients with mucus-high had unfavorable outcomes (hazard ratio for high vs. low 1.88, 95% confidence interval 1.18-2.99, P = 0.008), with 5-year overall survival rates of 54.8% and 73.7% in mucus-high and mucus-low groups, respectively. The results were confirmed in the validation cohort (2.09, 1.21-3.60, 0.008; 62.8% vs. 79.8%). The prognostic value of MTR was maintained in multivariate analysis for both cohorts. Conclusion: The deep learning quantified MTR was an independent prognostic factor in CRC. With the advantages of advanced efficiency and high consistency, our method is suitable for clinical application and promotes precision medicine development.