Changes in Human Fecal Microbiota Due to Chemotherapy Analyzed by TaqMan-PCR, 454 Sequencing and PCR-DGGE Fingerprinting

BACKGROUND: We investigated whether chemotherapy with the presence or absence of antibiotics against different kinds of cancer changed the gastrointestinal microbiota. METHODOLOGY/PRINCIPAL FINDINGS: Feces of 17 ambulant patients receiving chemotherapy with or without concomitant antibiotics were analyzed before and after the chemotherapy cycle at four time points in comparison to 17 gender-, age- and lifestyle-matched healthy controls. We targeted 16S rRNA genes of all bacteria, Bacteroides, bifidobacteria, Clostridium cluster IV and XIVa as well as C. difficile with TaqMan qPCR, denaturing gradient gel electrophoresis (DGGE) fingerprinting and high-throughput sequencing. After a significant drop in the abundance of microbiota (p = 0.037) following a single treatment the microbiota recovered within a few days. The chemotherapeutical treatment marginally affected the Bacteroides while the Clostridium cluster IV and XIVa were significantly more sensitive to chemotherapy and antibiotic treatment. DGGE fingerprinting showed decreased diversity of Clostridium cluster IV and XIVa in response to chemotherapy with cluster IV diversity being particularly affected by antibiotics. The occurrence of C. difficile in three out of seventeen subjects was accompanied by a decrease in the genera Bifidobacterium, Lactobacillus, Veillonella and Faecalibacterium prausnitzii. Enterococcus faecium increased following chemotherapy. CONCLUSIONS/SIGNIFICANCE: Despite high individual variations, these results suggest that the observed changes in the human gut microbiota may favor colonization with C. difficile and Enterococcus faecium. Perturbed microbiota may be a target for specific mitigation with safe pre- and probiotics

Glucose Recovery from Different Corn Stover Fractions Using Dilute Acid and Alkaline Pretreatment Techniques

Background: Limited availability of corn stover due to the competing uses (organic manure, animal feed, bio-materials, and bioenergy) presents a major concern for its future in the bio-economy. Furthermore, biomass research has exhibited different results due to the differences in the supply of enzymes and dissimilar analytical methods. The effect of the two leading pretreatment techniques (dilute acid and alkaline) on glucose yield from three corn stover fractions (cob, stalk, and leaf) sourced from a single harvest in Uganda were studied at temperatures 100, 120, 140, and 160 °C over reaction times of 5, 10, 30, and 60 min. Results: From this study, the highest glucose concentrations obtained from the dilute acid (DA) pretreated cobs, stalks, and leaves were 18.4 g/L (66.8% glucose yield), 16.2 g/L (64.1% glucose yield), and 11.0 g/L (49.5% glucose yield), respectively. The optimal pretreatment settings needed to obtain these yields from the DA pretreated samples were at a temperature of 160 °C over an incubation time of 30 min. The highest glucose concentrations obtained from the alkaline (AL) pretreated cobs, stalks, and leaves were 24.7 g/L (81.73% glucose yield), 21.3 g/L (81.23% glucose yield), and 15.0 g/L (51.92% glucose yield), respectively. To be able to achieve these yields, the optimal pretreatment settings for the cobs and stalks were 140 °C and for a retention time of 30 min, while the leaves require optimal conditions of 140 °C and for a retention time of 60 min. Conclusions: The study recommends that the leaves could be left on the field during harvesting since the recovery of glucose from the pretreated cobs and stalks is higher

The Application of DNA Barcodes for the Identification of Marine Crustaceans from the North Sea and Adjacent Regions

During the last years DNA barcoding has become a popular method of choice for molecular specimen identification. Here we present a comprehensive DNA barcode library of various crustacean taxa found in the North Sea, one of the most extensively studied marine regions of the world. Our data set includes 1,332 barcodes covering 205 species, including taxa of the Amphipoda, Copepoda, Decapoda, Isopoda, Thecostraca, and others. This dataset represents the most extensive DNA barcode library of the Crustacea in terms of species number to date. By using the Barcode of Life Data Systems (BOLD), unique BINs were identified for 198 (96.6%) of the analyzed species. Six species were characterized by two BINs (2.9%), and three BINs were found for the amphipod species Gammarus salinus Spooner, 1947 (0.4%). Intraspecific distances with values higher than 2.2% were revealed for 13 species (6.3%). Exceptionally high distances of up to 14.87% between two distinct but monophyletic clusters were found for the parasitic copepod Caligus elongatus Nordmann, 1832, supporting the results of previous studies that indicated the existence of an overlooked sea louse species. In contrast to these high distances, haplotype-sharing was observed for two decapod spider crab species, Macropodia parva Van Noort & Adema, 1985 and Macropodia rostrata (Linnaeus, 1761), underlining the need for a taxonomic revision of both species. Summarizing the results, our study confirms the application of DNA barcodes as highly effective identification system for the analyzed marine crustaceans of the North Sea and represents an important milestone for modern biodiversity assessment studies using barcode sequence

Analysing and Transforming Graph Structures: The Graph Transformation Framework

Interconnected data or, in particular, graph structures are a valuable source of information. Gaining insights and knowledge from graph structures is applied throughout a wide range of application areas, for which efficient tools are desired. In this work we present an open source Java graph transformation framework. The framework provides a simple fluent Application Programming Interface (API) to transform a provided graph structure to a desired target format and, in turn, allow further analysis. First, we provide an overview on the architecture of the framework and its core components. Second, we provide an illustrative example which shows how to use the framework’s core API for transforming and verifying graph structures. Next to that, we present an instantiation of the framework in the context of analyzing the third-party dependencies amongst open source libraries on the Android platform. The example scenario provides insights on a typical scenario in which the graph transformation framework is applied to efficiently process complex graph structures. The framework is open-source and actively developed, and we further provide information on how to obtain it from its official GitHub page