Europium Ion-Based Magnetic-Trapping and Fluorescence-Sensing Method for Detection of Pathogenic Bacteria.

Europium ions (Eu3+) have been utilized as a fluorescence-sensing probe for a variety of analytes, including tetracycline (TC). When Eu3+ is chelated with TC, its fluorescence can be greatly enhanced. Moreover, Eu3+ possesses 6 unpaired electrons in its f orbital, which makes it paramagnetic. Being a hard acid, Eu3+ can chelate with hard bases, such as oxygen-containing functional groups (e.g., phosphates and carboxylates), present on the cell surface of pathogenic bacteria. Due to these properties, in this study, Eu3+ was explored as a magnetic-trapping and sensing probe against pathogenic bacteria present in complex samples. Eu3+ was used as a magnetic probe to trap bacteria such as Staphylococcus aureus, Escherichia coli, Enterococcus faecalis, Acinetobacter baumannii, Bacillus cereus, and Pseudomonas aeruginosa. The addition of TC facilitated the easy detection of magnetic Eu3+-bacterium conjugates through fluorescence spectroscopy, with a detection limit of approximately ∼104 CFU mL-1. Additionally, matrix-assisted laser desorption/ionization mass spectrometry was employed to differentiate bacteria tapped by our magnetic probes.

Using Magnetic Micelles Combined with Carbon Fiber Ionization Mass Spectrometry for the Screening of Trace Triazine Herbicides from Aqueous Samples.

Triazine herbicides are commonly used in agriculture to eliminate weeds. However, they can persist in the environment. In this study, we explored a new method for detecting triazine herbicides in aqueous samples. We selected two triazine herbicides, namely, prometryn and ametryn, as model herbicides. To generate magnetic probes, we mixed aqueous Gd3+ with aqueous sodium dodecyl sulfate (SDS), which created magnetic probes made of Gd3+-SDS micelles. These probes showed a trapping capacity for the model herbicides. Results indicated that the trapping capacities of our magnetic probes for ametryn and prometryn were approximately 466 and 468 nmol mg-1, respectively. The dissociation constants of our probes toward ametryn and prometryn were 2.92 × 10-5 and 1.27 × 10-5, respectively. This is the first report that the developed magnetic probes can be used to trap triazine herbicides. For detection, we used carbon fiber ionization mass spectrometry (CFI-MS), which can be used to directly detect semi-volatiles from the samples in the condensed phase. Because of the semi-volatility of triazine herbicides, the herbicides trapped by the magnetic probes can be directly analyzed by CFI-MS without any elution steps. In addition, we also demonstrated the feasibility of using our approach for detecting triazine herbicides in lake water and drinking water.

Hydroxyl-Functionalized Covalent Organic Frameworks as High-Performance Supercapacitors.

Covalent organic frameworks (COFs) have attracted significant interest because of their heteroatom-containing architectures, high porous networks, large surface areas, and capacity to include redox-active units, which can provide good electrochemical efficiency in energy applications. In this research, we synthesized two novel hydroxy-functionalized COFs-TAPT-2,3-NA(OH)2, TAPT-2,6-NA(OH)2 COFs-through Schiff-base [3 + 2] polycondensations of 1,3,5-tris-(4-aminophenyl)triazine (TAPT-3NH2) with 2,3-dihydroxynaphthalene-1,4-dicarbaldehyde (2,3-NADC) and 2,6-dihydroxynaphthalene-1,5-dicarbaldehyde (2,6-NADC), respectively. The resultant hydroxy-functionalized COFs featured high BET-specific surface areas up to 1089 m2 g-1, excellent crystallinity, and superior thermal stability up to 60.44% char yield. When used as supercapacitor electrodes, the hydroxy-functionalized COFs exhibited electrochemical redox activity due to the presence of redox-active 2,3-dihydroxynaphthalene and 2,6-dihydroxynaphthalene in their COF skeletons. The hydroxy-functionalized COFs showed specific capacitance of 271 F g-1 at a current density of 0.5 A g-1 with excellent stability after 2000 cycles of 86.5% capacitance retention. Well-known pore features and high surface areas of such COFs, together with their superior supercapacitor performance, make them suitable electrode materials for use in practical applications.

Utilizing AgNPt-SALDI to Classify Edible Oils by Multivariate Statistics of Triacylglycerol Profile.

Edible oils are valuable sources of nutrients, and their classification is necessary to ensure high quality, which is essential to food safety. This study reports the establishment of a rapid and straightforward SALDI-TOF MS platform used to detect triacylglycerol (TAG) in various edible oils. Silver nanoplates (AgNPts) were used to optimize the SALDI samples for high sensitivity and reproducibility of TAG signals. TAG fingerprints were combined with multivariate statistics to identify the critical features of edible oil discrimination. Eleven various edible oils were discriminated using principal component analysis (PCA). The results suggested the creation of a robust platform that can examine food adulteration and food fraud, potentially ensuring high-quality foods and agricultural products.

Rapid detection of perfluorinated sulfonic acids through preconcentration by bubble bursting and surface-assisted laser desorption/ionization.

We developed a preconcentration method in which aerosol droplets containing enriched perfluorinated sulfonic acids (PFSs) are generated through bubble bursting and collected. The droplets were subjected to PFS analysis of perfluorohexane sulfonic acid (PFHxS) and perfluorooctanesulfonic acid (PFOS) through surface-assisted laser desorption/ionization-time-of-flight mass spectrometry; silver nanoplates (AgNPts) were assisting materials. The method was highly efficient, with an approximately three-order magnitude enhancement (5 × 10-13 to 1 × 10-11 M). Ultralow PFS concentrations (0.5 ng/L of PFOS; 0.4 ng/L of PFHxS) were detected in preconcentrated tap water containing PFSs. Our method has potential for rapid real-world PFS detection in water.

Enterotype-based Analysis of Gut Microbiota along the Conventional Adenoma-Carcinoma Colorectal Cancer Pathway.

The dysbiosis of human gut microbiota is strongly associated with the development of colorectal cancer (CRC). The dysbiotic features of the transition from advanced polyp to early-stage CRC are largely unknown. We performed a 16S rRNA gene sequencing and enterotype-based gut microbiota analysis study. In addition to Bacteroides- and Prevotella-dominated enterotypes, we identified an Escherichia-dominated enterotype. We found that the dysbiotic features of CRC were dissimilar in overall samples and especially Escherichia-dominated enterotype. Besides a higher abundance of Fusobacterium, Enterococcus, and Aeromonas in all CRC faecal microbiota, we found that the most notable characteristic of CRC faecal microbiota was a decreased abundance of potential beneficial butyrate-producing bacteria. Notably, Oscillospira was depleted in the transition from advanced adenoma to stage 0 CRC, whereas Haemophilus was depleted in the transition from stage 0 to early-stage CRC. We further identified 7 different CAGs by analysing bacterial clusters. The abundance of microbiota in cluster 3 significantly increased in the CRC group, whereas that of cluster 5 decreased. The abundance of both cluster 5 and cluster 7 decreased in the Escherichia-dominated enterotype of the CRC group. We present the first enterotype-based faecal microbiota analysis. The gut microbiota of colorectal neoplasms can be influenced by its enterotype.

Vaginal microbiome variances in sample groups categorized by clinical criteria of bacterial vaginosis.

BACKGROUND: One of the most common and recurrent vaginal infections is bacterial vaginosis (BV). The diagnosis is based on changes to the "normal" vaginal microbiome; however, the normal microbiome appears to differ according to reproductive status and ethnicity, and even among individuals within these groups. The Amsel criteria and Nugent score test are widely used for diagnosing BV; however, these tests are based on different criteria, and so may indicate distinct changes in the vaginal microbial community. Nevertheless, few studies have compared the results of these test against metagenomics analysis. METHODS: Vaginal flora samples from 77 participants were classified according to the Amsel criteria and Nugent score test. The microbiota composition was analyzed using 16S ribosome RNA gene amplicon sequencing. Bioinformatics analysis and multivariate statistical analysis were used to evaluate the microbial diversity and function. RESULTS: Only 3 % of the participants diagnosed BV negative using the Amsel criteria (A-) were BV-positive according to the Nugent score test (N+), while over half of the BV-positive patients using the Amsel criteria (A+) were BV-negative according to the Nugent score test (N-). Thirteen genera showed significant differences in distribution among BV status defined by BV tests (e.g., A - N-, A + N- and A + N+). Variations in the four most abundant taxa, Lactobacillus, Gardnerella, Prevotella, and Escherichia, were responsible for most of this dissimilarity. Furthermore, vaginal microbial diversity differed significantly among the three groups classified by the Nugent score test (N-, N+, and intermediate flora), but not between the Amsel criteria groups. Numerous predictive microbial functions, such as bacterial chemotaxis and bacterial invasion of epithelial cells, differed significantly among multiple BV test, but not between the A- and A+ groups. CONCLUSIONS: Metagenomics analysis can greatly expand our current understanding of vaginal microbial diversity in health and disease. Metagenomics profiling may also provide more reliable diagnostic criteria for BV testing.

Bacterial alterations in salivary microbiota and their association in oral cancer.

Oral squamous cell carcinoma (OSCC) is the most common malignant neoplasm of the oral cavity and the fourth leading malignancy and cause of cancer-related death in the male population of Taiwan. Most cases are detected at advanced stages, resulting in poor prognosis. Therefore, improved detection of early oral health disorders is indispensable. The involvement of oral bacteria in inflammation and their association with OSCC progression provide a feasible target for diagnosis. Due to the nature of oral neoplasms, the diagnosis of epithelial precursor lesions is relatively easy compared with that of other types of cancer. However, the transition from an epithelial precursor lesion to cancer is slow and requires further and continuous follow-up. In this study, we investigated microbiota differences between normal individuals, epithelial precursor lesion patients, and cancer patients with different lifestyle habits, such as betel chewing and smoking, using next-generation sequencing. Overall, the oral microbiome compositions of five genera, Bacillus, Enterococcus, Parvimonas, Peptostreptococcus, and Slackia, revealed significant differences between epithelial precursor lesion and cancer patients and correlated with their classification into two clusters. These composition changes might have the potential to constitute a biomarker to help in monitoring the oral carcinogenesis transition from epithelial precursor lesion to cancer.

miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database.

MicroRNAs (miRNAs) are small non-coding RNAs of approximately 22 nucleotides, which negatively regulate the gene expression at the post-transcriptional level. This study describes an update of the miRTarBase (http://miRTarBase.mbc.nctu.edu.tw/) that provides information about experimentally validated miRNA-target interactions (MTIs). The latest update of the miRTarBase expanded it to identify systematically Argonaute-miRNA-RNA interactions from 138 crosslinking and immunoprecipitation sequencing (CLIP-seq) data sets that were generated by 21 independent studies. The database contains 4966 articles, 7439 strongly validated MTIs (using reporter assays or western blots) and 348 007 MTIs from CLIP-seq. The number of MTIs in the miRTarBase has increased around 7-fold since the 2014 miRTarBase update. The miRNA and gene expression profiles from The Cancer Genome Atlas (TCGA) are integrated to provide an effective overview of this exponential growth in the miRNA experimental data. These improvements make the miRTarBase one of the more comprehensively annotated, experimentally validated miRNA-target interactions databases and motivate additional miRNA research efforts.

Bacterial communities in semen from men of infertile couples: metagenomic sequencing reveals relationships of seminal microbiota to semen quality.

Some previous studies have identified bacteria in semen as being a potential factor in male infertility. However, only few types of bacteria were taken into consideration while using PCR-based or culturing methods. Here we present an analysis approach using next-generation sequencing technology and bioinformatics analysis to investigate the associations between bacterial communities and semen quality. Ninety-six semen samples collected were examined for bacterial communities, measuring seven clinical criteria for semen quality (semen volume, sperm concentration, motility, Kruger's strict morphology, antisperm antibody (IgA), Atypical, and leukocytes). Computer-assisted semen analysis (CASA) was also performed. Results showed that the most abundant genera among all samples were Lactobacillus (19.9%), Pseudomonas (9.85%), Prevotella (8.51%) and Gardnerella (4.21%). The proportion of Lactobacillus and Gardnerella was significantly higher in the normal samples, while that of Prevotella was significantly higher in the low quality samples. Unsupervised clustering analysis demonstrated that the seminal bacterial communities were clustered into three main groups: Lactobacillus, Pseudomonas, and Prevotella predominant group. Remarkably, most normal samples (80.6%) were clustered in Lactobacillus predominant group. The analysis results showed seminal bacteria community types were highly associated with semen health. Lactobacillus might not only be a potential probiotic for semen quality maintenance, but also might be helpful in countering the negative influence of Prevotella and Pseudomonas. In this study, we investigated whole seminal bacterial communities and provided the most comprehensive analysis of the association between bacterial community and semen quality. The study significantly contributes to the current understanding of the etiology of male fertility.

Systematic analysis of the association between gut flora and obesity through high-throughput sequencing and bioinformatics approaches.

Eighty-one stool samples from Taiwanese were collected for analysis of the association between the gut flora and obesity. The supervised analysis showed that the most, abundant genera of bacteria in normal samples (from people with a body mass index (BMI) ≤ 24) were Bacteroides (27.7%), Prevotella (19.4%), Escherichia (12%), Phascolarctobacterium (3.9%), and Eubacterium (3.5%). The most abundant genera of bacteria in case samples (with a BMI ≥ 27) were Bacteroides (29%), Prevotella (21%), Escherichia (7.4%), Megamonas (5.1%), and Phascolarctobacterium (3.8%). A principal coordinate analysis (PCoA) demonstrated that normal samples were clustered more compactly than case samples. An unsupervised analysis demonstrated that bacterial communities in the gut were clustered into two main groups: N-like and OB-like groups. Remarkably, most normal samples (78%) were clustered in the N-like group, and most case samples (81%) were clustered in the OB-like group (Fisher's P value = 1.61E - 07). The results showed that bacterial communities in the gut were highly associated with obesity. This is the first study in Taiwan to investigate the association between human gut flora and obesity, and the results provide new insights into the correlation of bacteria with the rising trend in obesity.

Clinical detection of human probiotics and human pathogenic bacteria by using a novel high-throughput platform based on next generation sequencing.

BACKGROUND: The human body plays host to a vast array of bacteria, found in oral cavities, skin, gastrointestinal tract and the vagina. Some bacteria are harmful while others are beneficial to the host. Despite the availability of many methods to identify bacteria, most of them are only applicable to specific and cultivable bacteria and are also tedious. Based on high throughput sequencing technology, this work derives 16S rRNA sequences of bacteria and analyzes probiotics and pathogens species. RESULTS: We constructed a database that recorded the species of probiotics and pathogens from literature, along with a modified Smith-Waterman algorithm for assigning the taxonomy of the sequenced 16S rRNA sequences. We also constructed a bacteria disease risk model for seven diseases based on 98 samples. Applicability of the proposed platform is demonstrated by collecting the microbiome in human gut of 13 samples. CONCLUSIONS: The proposed platform provides a relatively easy means of identifying a certain amount of bacteria and their species (including uncultivable pathogens) for clinical microbiology applications. That is, detecting how probiotics and pathogens inhabit humans and how affect their health can significantly contribute to develop a diagnosis and treatment method.