Automated Data Analysis Software Research Articles

The fate of microplastics from municipal wastewater in a surface flow treatment wetland

Microplastics (MPs) are an anthropogenic pollutant of emerging concern prominent in both raw and treated municipal wastewater as well as urban and agricultural run-off. There is a critical need for the mitigation of both point- and diffuse sources, with treatment wetlands a possible sustainable nature-based solution. In this study, the possible retention of MPs in treatment wetlands of the widely used surface flow (SF) type was investigated. In- and outflow water, as well as atmospheric deposition, at a full-scale reed-based SF wetland (operating as a polishing phase of municipal wastewater treatment) was analyzed for MPs in a size range of 25–1000 μm. FPA-based μFT-IR spectroscopic imaging was used in combination with automated data analysis software, allowing for an unbiased assessment of MP numbers, polymer types and size distribution.Inflow water samples (secondary treated wastewater) contained 104 MPs m−3 and 56 MPs m−3 in sampling campaigns 1 and 2, respectively. Passage through the SF wetland increased the MP concentration in the water by 92 % during a rain intense period (campaign 1) and by 43 % during a low precipitation period (campaign 2). The MP particle numbers, size and polymer type distribution varied between the two sampling campaigns, making conclusions around the fate of specific types of MPs in SF wetlands difficult.Atmospheric deposition was measured to be 590 MPs m−2 week−1 during the rain-intense period. Our findings point towards atmospheric deposited MPs as an important factor in the fate of MPs in SF wetlands, causing an increase of MP concentrations, and potentially explaining the variations observed in MP concentrations in wetland effluent and removal efficiency. Furthermore, atmospheric deposition might also be a reason for the considerable inter-study variation regarding MPs removal efficiency in SF wetlands found in the available literature.

Automating Data Analysis Methods in Epidemiology

Technological advances in software development effectively handled technical details that made life easier for data analysts, but also allowed for nonexperts in statistics and computer science to analyze data. As a result, medical research suffers from statistical errors that could be otherwise prevented such as errors in choosing a hypothesis test and assumption checking of models. Our objective is to create an automated data analysis software package that can help practitioners run non-subjective, fast, accurate and easily interpretable analyses. We used machine learning to predict the normality of a distribution as an alternative to normality tests and graphical methods to avoid their downsides. We implemented methods for detecting outliers, imputing missing values, and choosing a threshold for cutting numerical variables to correct for non-linearity before running a linear regression. We showed that data analysis can be automated. Our normality prediction algorithm outperformed the Shapiro-Wilk test in small samples with Matthews correlation coefficient of 0.5 vs. 0.16. The biggest drawback was that we did not find alternatives for statistical tests to test linear regression assumptions which are problematic in large datasets. We also applied our work to a dataset about smoking in teenagers. Because of the opensource nature of our work, these algorithms can be used in future research and projects.

Current trends in flow cytometry automated data analysis software.

Automated flow cytometry (FC) data analysis tools for cell population identification and characterization are increasingly being used in academic, biotechnology, pharmaceutical, and clinical laboratories. The development of these computational methods is designed to overcome reproducibility and process bottleneck issues in manual gating, however, the take-up of these tools remains (anecdotally) low. Here, we performed a comprehensive literature survey of state-of-the-art computational tools typically published by research, clinical, and biomanufacturing laboratories for automated FC data analysis and identified popular tools based on literature citation counts. Dimensionality reduction methods ranked highly, such as generic t-distributed stochastic neighbor embedding (t-SNE) and its initial Matlab-based implementation for cytometry data viSNE. Software with graphical user interfaces also ranked highly, including PhenoGraph, SPADE1, FlowSOM, and Citrus, with unsupervised learning methods outnumbering supervised learning methods, and algorithm type popularity spread across K-Means, hierarchical, density-based, model-based, and other classes of clustering algorithms. Additionally, to illustrate the actual use typically within clinical spaces alongside frequent citations, a survey issued by UK NEQAS Leucocyte Immunophenotyping to identify software usage trends among clinical laboratories was completed. The survey revealed 53% of laboratories have not yet taken up automated cell population identification methods, though among those that have, Infinicyt software is the most frequently identified. Survey respondents considered data output quality to be the most important factor when using automated FC data analysis software, followed by software speed and level of technical support. This review found differences in software usage between biomedical institutions, with tools for discovery, data exploration, and visualization more popular in academia, whereas automated tools for specialized targeted analysis that apply supervised learning methods were more used in clinical settings.

EZcalcium: Open-Source Toolbox for Analysis of Calcium Imaging Data.

Fluorescence calcium imaging using a range of microscopy approaches, such as two-photon excitation or head-mounted “miniscopes,” is one of the preferred methods to record neuronal activity and glial signals in various experimental settings, including acute brain slices, brain organoids, and behaving animals. Because changes in the fluorescence intensity of genetically encoded or chemical calcium indicators correlate with action potential firing in neurons, data analysis is based on inferring such spiking from changes in pixel intensity values across time within different regions of interest. However, the algorithms necessary to extract biologically relevant information from these fluorescent signals are complex and require significant expertise in programming to develop robust analysis pipelines. For decades, the only way to perform these analyses was for individual laboratories to write their custom code. These routines were typically not well annotated and lacked intuitive graphical user interfaces (GUIs), which made it difficult for scientists in other laboratories to adopt them. Although the panorama is changing with recent tools like CaImAn, Suite2P, and others, there is still a barrier for many laboratories to adopt these packages, especially for potential users without sophisticated programming skills. As two-photon microscopes are becoming increasingly affordable, the bottleneck is no longer the hardware, but the software used to analyze the calcium data optimally and consistently across different groups. We addressed this unmet need by incorporating recent software solutions, namely NoRMCorre and CaImAn, for motion correction, segmentation, signal extraction, and deconvolution of calcium imaging data into an open-source, easy to use, GUI-based, intuitive and automated data analysis software package, which we named EZcalcium.

Abstract 1667: A robust human immune profiling assay using CyTOF technology and automated data analysis software

Abstract Immune monitoring is an essential method for quantifying changes in immune cell population numbers and states over time in health and disease. A cornerstone in translational and clinical research, it is frequently used in the investigation of chronic inflammation, infectious disease, autoimmune diseases, and cancer. The diversity of immune cell populations demands a highparameter approach to more fully and efficiently quantify these changes. Mass cytometry, which utilizes CyTOF® technology, is a single-cell analysis platform that uses metal-tagged antibodies to resolve over 40 markers in a single tube of sample without the need for compensation. It is an ideal solution for routine enumeration of immune cell populations. However, development of a robust, highly multiplexed assay requires panel optimization as well as standardization of instrument setup and an analysis pipeline. We have developed a sample-to-answer solution for human immune profiling using mass cytometry. It includes an optimized 30-marker immune profiling panel provided in a lyophilized, single-tube format, validated SOPs for human whole blood and PBMC staining, an instrument data acquisition template, instructions for data acquisition on a Helios™ system, and automated software for data analysis. The software analyzes FCS 3.0 files generated with the kit; automatically reports cell counts, percentage calculations, and staining intensity; and produces graphical elements such as histograms, dot plots, and a Cen-se′™ (t-SNE variant) graph for 36 immune cell populations. Here we present assay analytical validation data on repeatability, reproducibility, software precision, and software accuracy. We also present a performance comparison of the lyophilized material and a liquid formulation of the same antibodies and clones used in the lyophilized format. This assay provides a robust, complete solution for broad immune profiling using mass cytometry that reduces sources of variability and subjectivity in sample preparation and data analysis. Citation Format: Stephen K. Li, Daniel Majonis, C. Bruce Bagwell, Benjamin C. Hunsberger, Vladimir I. Baranov, Olga I. Ornatsky. A robust human immune profiling assay using CyTOF technology and automated data analysis software [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1667.

A robust human immunophenotyping workflow using CyTOF technology coupled with Maxpar Pathsetter, an automated data analysis software

Abstract Mass cytometry, which utilizes CyTOF® technology, is a single-cell analysis platform that uses metal-tagged antibodies. An advantage of CyTOF is its ability to resolve more than 40 parameters in a single panel without the need for compensation, making mass cytometry an ideal solution for routine enumeration of immune cells. Developing a robust and highly multiplexed assay requires an optimized panel and analysis pipeline, and the analysis of complex panels is time-consuming and difficult to interpret without expertise in immunology. The Maxpar® Direct Immune Profiling Assay™ coupled with Maxpar Pathsetter™ software is a sample-to-answer solution for human immune profiling using mass cytometry. The Maxpar Direct Immune Profiling Assay kit includes an optimized 30-marker panel contained in a lyophilized single-tube format, protocols for human whole blood and PBMC staining, and data acquisition instructions on a Helios™ system. Maxpar Pathsetter is an automated software that accepts FCS 3.0 files and reports cell counts, percentage calculations, and staining intensity. It also produces graphical elements such as histograms, dot plots, and a Cen-se’™ (t-SNE variant) graph for 36 immune cell populations. We present analytical validation data on repeatability and reproducibility for the assay and on the precision and accuracy of Maxpar Pathsetter software. We demonstrate comparative performance between the lyophilized panel and a liquid panel of the same antibodies. Coupling Maxpar Pathsetter software with the Maxpar Direct Immune Profiling Assay reduces variability in sample preparation and subjectivity in data analysis. It allows researchers to have a streamlined solution for broad immune profiling using mass cytometry.

Characterization of Disulfide-Linked Peptides Using Tandem Mass Spectrometry Coupled with Automated Data Analysis Software.

Disulfide bond formation is critical for maintaining structure stability and function of many peptides and proteins. Mass spectrometry has become an important tool for the elucidation of molecular connectivity. However, the interpretation of the tandem mass spectral data of disulfide-linked peptides has been a major challenge due to the lack of appropriate tools. Developing proper data analysis software is essential to quickly characterize disulfide-linked peptides. A thorough and in-depth understanding of how disulfide-linked peptides fragment in mass spectrometer is a key in developing software to interpret the tandem mass spectra of these peptides. Two model peptides with inter- and intra-chain disulfide linkages were used to study fragmentation behavior in both collisional-activated dissociation (CAD) and electron-based dissociation (ExD) experiments. Fragments generated from CAD and ExD can be categorized into three major types, which result from different S-S and C-S bond cleavage patterns. DiSulFinder is a computer algorithm that was newly developed based on the fragmentation observed in these peptides. The software is vendor neutral and capable of quickly and accurately identifying a variety of fragments generated from disulfide-linked peptides. DiSulFinder identifies peptide backbone fragments with S-S and C-S bond cleavages and, more importantly, can also identify fragments with the S-S bond still intact to aid disulfide linkage determination. With the assistance of this software, more comprehensive disulfide connectivity characterization can be achieved. Graphical Abstract ᅟ.

Qualitative analysis of multiple compounds in raw and prepared Semen Cassiae coupled with multiple statistical strategies.

In China, Semen Cassiae is used clinically to improve eyesight, relieve constipation, and to treat headache and dizziness. Prepared Semen Cassiae is obtained by stir-frying raw Semen Cassiae until it turned dark brown, micro dilatancy, and overflow aroma. After processing, the therapeutic effects change-the purgation effect is alleviated and the hepatoprotective effect is enhanced. To explore the changes in chemical compositions of Semen Cassiae after processing and clarify the material basis of the changed therapeutic effects, an ultra-high performance liquid chromatography with quadrupole time-of-flight mass spectrometry coupled with automated data analysis software and statistical strategy was developed. As a result, 53 compounds in raw Semen Cassiae and 43 compounds in prepared Semen Cassiae were found, a total of 55 chemical compounds were identified. Principle component analysis and t-test were processed by Markerview 1.2.1 software. Finally, 39 peaks were found to be the main contributors to the significant difference (p<0.05) between raw and prepared Semen Cassiae. Compared with raw Semen Cassiae, 19 peaks showed a higher intensity in prepared Semen Cassiae, while the contents of 20 compounds in prepared Semen Cassiae were lower, most of which belonged to naphthopyrones glycosides and anthraquinone glycosides.

The Metabolic Profiling of Isorhamnetin-3-O-Neohesperidoside Produced by Human Intestinal Flora Employing UPLC-Q-TOF/MS.

Isorhamnetin-3-O-neohesperidoside is the major active substance of Puhuang, a traditional herb medicine widely used in clinical practice to tackle many chronic diseases. However, little is known about the interactions between this ingredient and intestinal flora. In this study, ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry together with automated data analysis software (Metabolynx™) was used for analysis of the metabolic profile of isorhamnetin-3-O-neohesperidoside by the isolated human intestinal bacteria. The parent and three metabolites isorhamnetin-3-O-glucoside, isorhamnetin and quercetin were detected and identified based on the characteristics of their deprotonated molecules. These metabolites indicated that isorhamnetin-3-O-neohesperidoside was firstly deglycosylated to isorhamnetin-3-O-glucoside and subsequently to the aglycone isorhamnetin, and the latter was demethylated to quercetin. The majority of bacteria such as Escherichia sp. 23 were capable of converting isorhamnetin-3-O-neohesperidoside to considerable amounts of aglycone isorhamnetin and further to minor amounts of quercetin, while minor amounts of isorhamnetin-3-O-glucoside were detected in minority of bacterial samples such as Enterococcus sp. 30. The metabolic pathway and metabolites of isorhamnetin-3-O-neohesperidoside by the different human intestinal bacteria were firstly investigated. Furthermore, the metabolites of isorhamnetin-3-O-neohesperidoside might influence the effects of traditional herb medicines. Thus, our study is helpful to further unravel how isorhamnetin-3-O-neohesperidoside and Puhuang work in vivo.

An Automated High-Throughput Metabolic Stability Assay Using an Integrated High-Resolution Accurate Mass Method and Automated Data Analysis Software.

Advancement of in silico tools would be enabled by the availability of data for metabolic reaction rates and intrinsic clearance (CLint) of a diverse compound structure data set by specific metabolic enzymes. Our goal is to measure CLint for a large set of compounds with each major human cytochrome P450 (P450) isozyme. To achieve our goal, it is of utmost importance to develop an automated, robust, sensitive, high-throughput metabolic stability assay that can efficiently handle a large volume of compound sets. The substrate depletion method [in vitro half-life (t1/2) method] was chosen to determine CLint The assay (384-well format) consisted of three parts: 1) a robotic system for incubation and sample cleanup; 2) two different integrated, ultraperformance liquid chromatography/mass spectrometry (UPLC/MS) platforms to determine the percent remaining of parent compound, and 3) an automated data analysis system. The CYP3A4 assay was evaluated using two long t1/2 compounds, carbamazepine and antipyrine (t1/2 > 30 minutes); one moderate t1/2 compound, ketoconazole (10 < t1/2 < 30 minutes); and two short t1/2 compounds, loperamide and buspirone (t½ < 10 minutes). Interday and intraday precision and accuracy of the assay were within acceptable range (∼12%) for the linear range observed. Using this assay, CYP3A4 CLint and t1/2 values for more than 3000 compounds were measured. This high-throughput, automated, and robust assay allows for rapid metabolic stability screening of large compound sets and enables advanced computational modeling for individual human P450 isozymes.

Profiling and analysis of multiple compounds in rhubarb decoction after processing by wine steaming using UHPLC-Q-TOF-MS coupled with multiple statistical strategies.

Rhubarb is one of the most popular traditional Chinese medicines and has been used for thousands of years in many Asian countries. Prepared rhubarb is obtained by steaming raw rhubarb with glutinous rice wine until it turned black in appearance both inside and outside. After processing, the therapeutic effects of prepared rhubarb change a lot. To find out the exact compound changes of the chemical profile in a decoction of rhubarb after processing and to clarify the material basis of the changed therapeutic effects, an ultra-high performance liquid chromatography with quadrupole time-of-flight mass spectrometry method coupled with automated data analysis software and statistical strategy was developed. As a result, 63 peaks in raw rhubarb and 54 peaks in prepared rhubarb were detected, and a total of 45 chemical compounds were identified. The analysis data were subjected to a principle component analysis and a t-test. Based on the results, 16 peaks were found to be the main contributors to the significant difference (p < 0.05) between raw and prepared rhubarb. Compared with raw rhubarb, the content of 15 components in prepared rhubarb was lower, while only rhein (1,8-dihydroxy-3-carboxy anthraquinone) showed a higher intensity.

Programmable Bio-nanochip Platform: A Point-of-Care Biosensor System with the Capacity To Learn.

The combination of point-of-care (POC) medical microdevices and machine learning has the potential transform the practice of medicine. In this area, scalable lab-on-a-chip (LOC) devices have many advantages over standard laboratory methods, including faster analysis, reduced cost, lower power consumption, and higher levels of integration and automation. Despite significant advances in LOC technologies over the years, several remaining obstacles are preventing clinical implementation and market penetration of these novel medical microdevices. Similarly, while machine learning has seen explosive growth in recent years and promises to shift the practice of medicine toward data-intensive and evidence-based decision making, its uptake has been hindered due to the lack of integration between clinical measurements and disease determinations. In this Account, we describe recent developments in the programmable bio-nanochip (p-BNC) system, a biosensor platform with the capacity for learning. The p-BNC is a "platform to digitize biology" in which small quantities of patient sample generate immunofluorescent signal on agarose bead sensors that is optically extracted and converted to antigen concentrations. The platform comprises disposable microfluidic cartridges, a portable analyzer, automated data analysis software, and intuitive mobile health interfaces. The single-use cartridges are fully integrated, self-contained microfluidic devices containing aqueous buffers conveniently embedded for POC use. A novel fluid delivery method was developed to provide accurate and repeatable flow rates via actuation of the cartridge's blister packs. A portable analyzer instrument was designed to integrate fluid delivery, optical detection, image analysis, and user interface, representing a universal system for acquiring, processing, and managing clinical data while overcoming many of the challenges facing the widespread clinical adoption of LOC technologies. We demonstrate the p-BNC's flexibility through the completion of multiplex assays within the single-use disposable cartridges for three clinical applications: prostate cancer, ovarian cancer, and acute myocardial infarction. Toward the goal of creating "sensors that learn", we have developed and describe here the Cardiac ScoreCard, a clinical decision support system for a spectrum of cardiovascular disease. The Cardiac ScoreCard approach comprises a comprehensive biomarker panel and risk factor information in a predictive model capable of assessing early risk and late-stage disease progression for heart attack and heart failure patients. These marker-driven tests have the potential to radically reduce costs, decrease wait times, and introduce new options for patients needing regular health monitoring. Further, these efforts demonstrate the clinical utility of fusing data from information-rich biomarkers and the Internet of Things (IoT) using predictive analytics to generate single-index assessments for wellness/illness status. By promoting disease prevention and personalized wellness management, tools of this nature have the potential to improve health care exponentially.

Application of ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry to identify curcumin metabolites produced by human intestinal bacteria

Curcumin, a yellow pigment derived from the rhizomes of Curcuma longa Linn, is a natural antioxidant that exhibits a variety of pharmacological activities and therapeutic properties. However, as curcumin is generally conjugated when absorbed through the intestine, free curcumin is present at extremely low levels in the body. Thus, curcumin metabolites are presumed to be responsible for curcumin bioactivity. In this study, we describe a strategy using ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF MS) with automated data analysis software (MetaboLynx(XS)) for rapid analysis of the metabolic profile of curcumin in human intestinal flora. The results show that curcumin undergoes extensive phase I and phase II metabolism. A total of 23 curcumin metabolites were detected and identified in vitro. Furthermore, we identified a number of novel metabolic pathways of curcumin in the human intestinal microflora system.

Echocardiography and Vascular Ultrasound: New Developments and Future Directions

There have been major technological advances in echocardiography over the past decade. New and robust measures of myocardial function, both systolic and diastolic, have been identified and extensively evaluated. Some of the new measures such as annular velocities by tissue Doppler imaging have become an integral part of the echocardiographic examination, and other measures such as strain and strain rate have yet to be widely adopted. Three-dimensional (3D) echocardiography has evolved greatly since its introduction in the 1980s. Currently, its main clinical application is the perioperative assessment of the mitral valve. Though 3D echocardiography provides superior quantification of cardiac chamber size, its adoption has been limited by the lack of robust automated data analysis software with smooth integration of analysis packages into clinical workstations and suboptimal temporal and spatial resolution. With advancement in electronics and miniaturization, these limitations can be overcome. The history of contrast echocardiography is long and arduous. Use of a microbubble contrast for left ventricular opacification has become commonplace in most echocardiographic laboratories, but the routine use of microbubble contrast for myocardial perfusion will require standardization of the procedure and/or development of new contrast agents. The applications of 3D and microbubble contrast are also under active evaluation in vascular ultrasound. This review summarizes the current and future applications of these exciting developments in echocardiography and vascular ultrasound.

Ultra‐performance Liquid Chromatography–High‐definition Mass Spectrometry Analysis of Constituents in the Root of Radix Stemonae and those Absorbed in Blood after Oral Administration of the Extract of the Crude Drug

Radix Stemonae, first recorded in the herbal 'Additional Records of Famous Physicians' (Mingyi Bielu), has been widely used as an oral anti-tussive agent in traditional Chinese medicine (TCM) for thousands of years in China. Current analysis methods are usually time-consuming and inaccurate. The aim of this study was to develop a more rapid and sensitive method to detect the active compounds in Radix Stemonae. A rapid, sensitive and selective ultra-performance liquid chromatography-high-resolution mass spectrometric (UPLC-HDMS) method with automated data analysis software MetaboLynx(TM) was developed for analysis and identification of the bioactive components and their metabolites in rat plasma following oral administration of Radix Stemonae extract. Twenty-nine compounds in the Radix Stemonae extract and 47 compounds in the rat plasma samples were detected in the MS(E) mode in a single injection within 21 min. Among the compounds detected, 23 were identified in vitro and 42 were identified in rat plasma, either by comparing the retention time and mass spectrometry data with those of reference compounds or by mass spectrometry analysis and retrieving the reference literature. It is concluded that the screening capability of MetaboLynx(TM), together with the utilisation of MS(E) in structural elucidation, can facilitate a rapid and comprehensive detection and effective structural characterisation of Stemona alkaloids in Radix Stemonae extract, which could be applied to other Chinese medicine. The results provide helpful chemical information of Radix Stemonae extract for further pharmacology and active mechanism research.

Screening for in vitro metabolites of Abelmoschus manihot extract in intestinal bacteria by ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry

Abelmoschus manihot has drawn much attention recently due to its potential beneficial health effects after oral administration. However, the metabolic fate of A. manihot in intestinal flora is not well understood. In this paper, we describe a strategy using ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC–Q-TOF MS) with automated data analysis software (MetaboLynx™) for fast analysis of the metabolic profile of flavonoids from A. manihot in intestinal flora. The human and rat incubated samples collected 72 h in the anaerobic incubator were analyzed by UPLC–Q-TOF MS within 10 min. A total of 14 metabolites were identified in human and rat incubated solution compared with blank samples. The results indicated that hydrolysis, hydroxylation and acetylation were the major metabolic pathways of flavonoids in A. manihot extract in vitro. MS E was used for simultaneous acquisition of precursor ion information and fragment ion data at high and low collision energy in one analytical run, which facilitated the fast structural characterization of metabolites. This work demonstrated the potential of the UPLC–Q-TOF MS approach using Metabolynx for fast and automated identification of metabolites of natural product in intestinal flora.

Identification of hyperoside metabolites in rat using ultra performance liquid chromatography/quadrupole-time-of-flight mass spectrometry

In this paper, ultra performance liquid chromatography (UPLC)/quadrupole-time-of-flight mass spectrometry (QTOF) with automated data analysis software (Metabolynx™) were applied for fast analysis of hyperoside metabolites in rat after intravenous administration. MS E was used for simultaneous acquisition of precursor ion information and fragment ion data at high and low collision energy in one analytical run, which facilitated the fast structural characterization of 12 metabolites in rat plasma, urine and bile. The results indicated that methylation, sulfation and glucuronidation were the major metabolic pathways of hyperoside in vivo, and among them, 3′- O-methyl-hyperoside was confirmed by matching its fragmentation patterns with standard compound. The present study provided important information about the metabolism of hyperoside which will be helpful for fully understanding the mechanism of this compound's action. Furthermore, this work demonstrated the potential of the UPLC/QTOFMS approach using Metabolynx for fast and automated identification of metabolites of natural product.

Fast and automated characterization of major constituents in rat biofluid after oral administration of Abelmoschus manihot extract using ultra‐performance liquid chromatography/quadrupole time‐of‐flight mass spectrometry and MetaboLynx

In drug metabolism research, the setting up of a complex series of mass spectrometry experiments and the subsequent analysis of the large amounts of data produced are often time-consuming. In this paper, we describe a strategy using ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC/QTOFMS) with automated data analysis software (MetaboLynx) for fast analysis of the metabolic profile of flavonoids in Abelmoschus manihot. Rat plasma and urine samples collected 1 h and 0-12 h after oral administration of Abelmoschus manihot were analyzed by UPLC/QTOFMS within 15 min. The post-acquisition data were processed using MetaboLynx. With key parameters carefully set, MetaboLynx is able to show the presence of a wide range of metabolites with only a limited requirement for manual intervention and data interpretation time. A total of 16 and 38 metabolites were identified in plasma and urine compared with blank samples. The results indicated that methylation and glucuronidation after deglycosylation were the major metabolic pathways of flavonoid glycosides in Abelmoschus manihot. The present study provided important information about the metabolism of flavonoid glycosides in Abelmoschus manihot which will be helpful for fully understanding the mechanism of action of this herb. Furthermore, this work demonstrated the potential of the UPLC/QTOFMS approach using MetaboLynx for fast and automated identification of metabolites from Chinese herbal medicines.

CARMEN - Comparative Analysis and in silico Reconstruction of organism-specific MEtabolic Networks

New sequencing technologies provide ultra-fast access to novel microbial genome data. For their interpretation, an efficient bioinformatics pipeline that facilitates in silico reconstruction of metabolic networks is highly desirable. The software tool CARMEN performs in silico reconstruction of metabolic networks to interpret genome data in a functional context. CARMEN supports the visualization of automatically derived metabolic networks based on pathway information from the KEGG database or from user-defined SBML templates; this software also enables comparative genomics. The reconstructed networks are stored in standardized SBML format. We demonstrated the functionality of CARMEN with a major application example focusing on the reconstruction of glycolysis and related metabolic reactions of Xanthomonas campestris pv. campestris B100. The curation of such pathways facilitates enhanced visualization of experimental results, simulations and comparative genomics. A second application of this software was performed on a set of corynebacteria to compare and to visualize their carbohydrate metabolism. In conclusion, using CARMEN, we developed highly automated data analysis software that rapidly converts sequence data into new knowledge, replacing the time-consuming manual reconstruction of metabolic networks. This tool is particularly useful for obtaining an overview of newly sequenced genomes and their metabolic blueprints and for comparative genome analysis. The generated pathways provide automated access to modeling and simulation tools that are compliant with the SBML standard. A user-friendly web interface of CARMEN is available at http://carmen.cebitec.uni-bielefeld.de.

High-Throughput Analysis of Nucleic Acid Modification Reactions Using Ion-Pair Reverse-Phase High-Performance Liquid Chromatography

Ion-pair reverse-phase high-performance liquid chromatography is presented as a versatile platform for the rapid analysis of nucleic acid modification reactions in a high-throughput manner. This system allows both sensitive and nonradioactive assays to be developed for a variety of nucleic acid modification reactions. Examples presented here include assays for telomerase, uracil DNA glycosylase, polynucleotide kinase, T4 DNA ligase, C5-DNA methyltransferases, and the mismatch endonuclease CEL I. However, this approach is not confined to these reactions. Indeed the ability to perform a variety of nonradioactive assays with throughput times of 10 min per sample in conjunction with automated data analysis software represents a significant improvement in analytical and preparative nucleic acid enzymology.