Chiral-Induced Surface-Enhanced Raman Optical Activity on a Single-Particle Substrate.

Surface-enhanced Raman optical activity (SEROA) is a promising method for analyzing chiral molecules' molecular chirality and structural changes. However, conventional SEROA measurements face challenges related to substrate stability, signal uniformity, and interference from electronic circular dichroism (ECD). Therefore, in this study, we present a uniform and stable substrate for SEROA measurements by utilizing Au nanoparticles on the Au nanofilm structure to confine hotspots to the film-particle junctions and minimize ECD interference. This method also uses the induction of chirality from chiral molecules to achiral molecules to overcome the limitation of chiral molecules in SEROA measurements, specifically their lower signal efficiency. Successful chirality transfer is demonstrated through distinguishable SEROA signals when the l/d-alanine mixture is present. Enantiomeric discrimination of different l/d-alanine ratios was achieved with linear responses in the circular intensity difference (CID). Altogether, the proposed chiral-induced SEROA on the AuNP_on_AuNF substrate shows promising potential for detecting and characterizing structural changes in biomolecules, thus making it a valuable tool for various research applications.

Highly sensitive near-infrared SERS nanoprobes for in vivo imaging using gold-assembled silica nanoparticles with controllable nanogaps.

BACKGROUND: To take advantages, such as multiplex capacity, non-photobleaching property, and high sensitivity, of surface-enhanced Raman scattering (SERS)-based in vivo imaging, development of highly enhanced SERS nanoprobes in near-infrared (NIR) region is needed. A well-controlled morphology and biocompatibility are essential features of NIR SERS nanoprobes. Gold (Au)-assembled nanostructures with controllable nanogaps with highly enhanced SERS signals within multiple hotspots could be a breakthrough. RESULTS: Au-assembled silica (SiO2) nanoparticles (NPs) (SiO2@Au@Au NPs) as NIR SERS nanoprobes are synthesized using the seed-mediated growth method. SiO2@Au@Au NPs using six different sizes of Au NPs (SiO2@Au@Au50-SiO2@Au@Au500) were prepared by controlling the concentration of Au precursor in the growth step. The nanogaps between Au NPs on the SiO2 surface could be controlled from 4.16 to 0.98 nm by adjusting the concentration of Au precursor (hence increasing Au NP sizes), which resulted in the formation of effective SERS hotspots. SiO2@Au@Au500 NPs with a 0.98-nm gap showed a high SERS enhancement factor of approximately 3.8 × 106 under 785-nm photoexcitation. SiO2@Au@Au500 nanoprobes showed detectable in vivo SERS signals at a concentration of 16 µg/mL in animal tissue specimen at a depth of 7 mm. SiO2@Au@Au500 NPs with 14 different Raman label compounds exhibited distinct SERS signals upon subcutaneous injection into nude mice. CONCLUSIONS: SiO2@Au@Au NPs showed high potential for in vivo applications as multiplex nanoprobes with high SERS sensitivity in the NIR region.

Comparison Analysis between the Medication Efficacy of the Milnacipran and Functional Connectivity of Neural Networks in Fibromyalgia Patients.

Milnacipran is a reuptake inhibitor of both serotonin and noradrenaline, used in the treatment of fibromyalgia with severe depression. However, few studies have been conducted on the efficacies of milnacipran drug on the functional connectivity of the neural network. The authors aimed to find the correlation between the drug efficacy and the changes in neural network in fibromyalgia patients. Resting-state-functional magnetic resonance imaging (rs-fMRI) were obtained before and after milnacipran drug administration. Graph theory indexes and small-worldness were calculated using preprocessed blood-oxygen-level-dependent signals from the rs-fMRI scans of 14 brain regions-of-interest. Statistical analyses were conducted to compare the topological network parameters. Significant changes in the neural network indexes appeared in three of the 14 brain regions-of-interest. In the pain network, the average path length on the left side of Brodmann area 32 was shortened. In the default mode network, functional connectivity changes were observed in the left lateral parietal cortex and medial prefrontal cortex. In the left lateral parietal cortex, the degree and betweenness centrality increased, whereas the clustering coefficient decreased. In the medial prefrontal cortex, local efficiency decreased. The small-worldness declined after milnacipran medication. The present results demonstrate that functional connectivity indexes in the brains of female fibromyalgia patients obtained from rs-fMRI data can be used as potential prognosis markers of milnacipran drug treatment.

Two-dimensional SERS encoding method for on-bead peptide sequencing in high-throughput bioanalysis.

We developed a ready-to-read on-bead peptide encoding method for high-throughput screening bioassays. With two-dimensional surface-enhanced Raman scattering nano-identifiers (2D-SERS IDs) which are concurrently labelled with two SERS codes (coupling steps and kinds of amino acid), we could possibly generate more than 10 trillion codes with only 30 Raman label compounds.

Subnanomolar Sensitivity of Filter Paper-Based SERS Sensor for Pesticide Detection by Hydrophobicity Change of Paper Surface.

As a cost-effective approach for detecting trace amounts of pesticides, filter paper-based SERS sensors have been the subject of intensive research. One of the hurdles to overcome is the difficulty of retaining nanoparticles on the surface of the paper because of the hydrophilic nature of the cellulose fibers in paper. This reduces the sensitivity and reproducibility of paper-based SERS sensors due to the low density of nanoparticles and short retention time of analytes on the paper surface. In this study, filter paper was treated with alkyl ketene dimer (AKD) to modify its property from hydrophilic to hydrophobic. AKD treatment increased the contact angle of the aqueous silver nanoparticle (AgNP) dispersion, which consequently increased the density of AgNPs. The retention time of the analyte was also increased by preventing its rapid absorption into the filter paper. The SERS signal was strongly enhanced by the increased number of SERS hot spots owing to the increased density of AgNPs on a small contact area of the filter surface. The reproducibility and sensitivity of the SERS signal were optimized by controlling the distribution of AgNPs on the surface of the filter paper by adjusting the concentration of the AgNP solution. Using this SERS sensor with a hydrophobicity-modified filter paper, the spot-to-spot variation of the SERS intensity of 25 spots of 4-aminothiophenol was 6.19%, and the limits of detection of thiram and ferbam as test pesticides were measured to be 0.46 nM and 0.49 nM, respectively. These proof-of-concept results indicate that this paper-based SERS sensor can serve for highly sensitive pesticide detection with low cost and easy fabrication.

A dual modal silver bumpy nanoprobe for photoacoustic imaging and SERS multiplexed identification of in vivo lymph nodes.

Multimodal imaging can provide complementary biomedical information which has huge potential in pre-clinical and clinical imaging and sensing. In this study, we introduce dual modal NIR silver bumpy nanoprobes for in vivo imaging and multiplexed detection of biomolecules by both photoacoustic imaging (PAI) and surface-enhanced Raman scattering (SERS) techniques. For this study, we used silica-coated silver bumpy nanoshell probes (AgNS@SiO2). AgNS@SiO2 have strong NIR-absorption and scattering properties compared with other nanostructures, and therefore, can be a good candidate for photoacoustic (PA) and SERS multimodal imaging. We obtained PA images of the skin and SLNs of rats by injecting various kinds of Raman-labeled AgNS@SiO2. Multiplexed identification of the injected AgNS@SiO2 was achieved by measuring SERS signals. AgNS@SiO2 have the potential to be applied in detecting cancer biomarkers by locating biomarkers quickly using PA imaging, and identification by multiplexed target measurement using SERS signals in vivo.

Simultaneous Detection of EGFR and VEGF in Colorectal Cancer using Fluorescence-Raman Endoscopy.

Fluorescence endomicroscopy provides quick access to molecular targets, while Raman spectroscopy allows the detection of multiple molecular targets. Using a simultaneous fluorescence-Raman endoscopic system (FRES), we herein demonstrate its potential in cancer diagnosis in an orthotopically induced colorectal cancer (CRC) xenograft model. In the model, epidermal growth factor receptor (EGFR) and vascular endothelial growth factor (VEGF) were targeted with antibody-conjugated fluorescence and surface-enhanced Raman scattering (F-SERS) dots. FRES demonstrated fast signal detection and multiplex targeting ability using fluorescence and Raman signals to detect the F-SERS dots. In addition, FRES showed a multiplex targeting ability even on a subcentimeter-sized CRC after spraying with a dose of 50 µg F-SERS dots. In conclusion, molecular characteristics of tumor cells (EGFR in cancer cell membranes) and tumor microenvironments (VEGF in the extracellular matrix) could be simultaneously investigated when performing a colonoscopy.

Genome-wide analysis of redox reactions reveals metabolic engineering targets for D-lactate overproduction in Escherichia coli.

Most current metabolic engineering applications rely on the inactivation of unwanted reactions and the amplification of product-oriented reactions. All of the biochemical reactions involved with cellular metabolism are tightly coordinated with the electron flow, which depends on the cellular energy status. Thus, the cellular metabolic flux can be controlled either by modulation of the electron flow or the regulation of redox reactions. This study analyzed the genome-wide anaerobic fermentation products of 472 Escherichia coli single gene knockouts, which comprised mainly of dehydrogenases, oxidoreductases, and redox-related proteins. Many metabolic pathways that were located far from anaerobic mixed-acid fermentation significantly affected the profiles of lactic acid, succinic acid, acetic acid, formic acid, and ethanol. Unexpectedly, D-lactate overproduction was determined by a single gene deletion in dehydrogenases (e.g., guaB, pyrD, and serA) involved with nucleotide and amino acid metabolism. Furthermore, the combined knockouts of guaB, pyrD, serA, fnr, arcA, or arcB genes, which are involved with anaerobic transcription regulation, enhanced D-lactate overproduction. These results suggest that the anaerobic fermentation profiles of E. coli can be tuned via the disruption of peripheral dehydrogenases in anaerobic conditions.

Effect of weight-added regulatory networks on constraint-based metabolic models of Escherichia coli.

Though the traditional flux balance analysis (FBA) has successfully predicted intracellular fluxes using stoichiometry, linear programming, and metabolic pathways, it has not automatically reflected any potential genetic effects in response to the environmental changes in the metabolic pathways. Recently, attempts have been made to impose regulatory constraints described as a binary system, such as if-then rules using Boolean logic, on the traditional FBA. Yet this binary system has limited the representation of complex interactions between transcriptional factors and target genes. In addition, it is difficult to intuitively or visually recognize changes to the interactions among stimuli, sensors/regulatory proteins, and target genes due to the properties of the if-then rule systems. Thus, in the current work, in order to improve upon the previous approaches, we have (1) determined weight values after deducing from the inequality signs of the relative strengths of interactions between sensors/regulators and target genes based on the experimental data of gene expression, (2) divided expression level into eight levels, and (3) constructed and incorporated weight-added regulatory networks using the defined symbols within the FBA. Finally, a model system with the central metabolic pathway of Escherichia coli was examined under the aerobic batch culture with glucose and acetate reutilization and the aerobic and anaerobic batch culture with glucose only to demonstrate our suggested approach.

CLAGen: a tool for clustering and annotating gene sequences using a suffix tree algorithm.

Most multiple gene sequence alignment methods rely on conventions regarding the score of a multiple alignment in pairwise fashion. Therefore, as the number of sequences increases, the runtime of sequencing expands exponentially. In order to solve the problem, this paper presents a multiple sequence alignment method using a linear-time suffix tree algorithm to cluster similar sequences at one time without pairwise alignment. After searching for common subsequences, cross-matching common subsequences were generated, and sometimes inexact matching was found. So, a procedure aimed at masking the inexact cross-matching pairs was suggested here. In addition, BLAST was combined with a clustering tool in order to annotate the clusters generated by suffix tree clustering. The proposed method for clustering and annotating genes consists of the following steps: (1) construction of a suffix tree; (2) searching and overlapping common subsequences; (3) grouping subsequence pairs; (4) masking cross-matching pairs; (5) clustering gene sequences; (6) annotating gene clusters by the BLAST search. The performance of the proposed system, CLAGen, was successfully evaluated with 42 gene sequences in a TCA cycle (a citrate cycle) of bacteria. The system generated 11 clusters and found the longest subsequences of each cluster, which are biologically significant.

Development of a software tool for in silico simulation of Escherichia coli using a visual programming environment.

This study describes the development of a software tool, EcoSim, to assist users in implementing quantitative in silico simulation easily. It consists of four parts: extracellular environment and constraints setting mode, table for optimal metabolic flux distribution and chart for changes of substrate concentration, dynamic flux distribution viewer and dynamic hierarchical regulatory network viewer. Representation of a hierarchical regulatory network was constructed with defined modeling symbols and weight in the central Escherichia coli metabolism. All programming procedures for EcoSim were accomplished in a visual programming environment (LabVIEW). To illustrate quantitative in silico simulation with EcoSim, this program was performed on E. coli using glucose and acetate as carbon sources. The simulation results were in agreement with the experimental data obtained from the literature. EcoSim can be used to assist biologists and engineers in predicting and interpreting dynamic behaviors of E. coli under a variety of environmental conditions.