Extending the reservoir of bla IMP-5: the emerging pathogen Acinetobacter bereziniae

Acinetobacter bereziniae clinical relevance is starting to be recognized; however, very few descriptions of its carbapenem resistance currently exist. Here we characterize two carbapenem-resistant A. bereziniae isolates. Materials & methods: Isolates were obtained from environmental and clinical samples. Carbapenemases were searched by phenotypic, biochemical and PCR assays. Clonality was studied by ApaI-PFGE and genetic location for carbapenemase genes were assessed by I-CeuI and S1 hybridizations. Results: Isolates were not clonally related but both produced the exclusively Portuguese IMP-5, with the clinical isolate also producing an OXA-58. The carbapenemase genes were plasmid located. Conclusion: Our results emphasize the role of non-baumannii Acinetobacter species as important reservoirs of clinically relevant resistance genes that could also contribute to their emergence as nosocomial pathogens

UV-visible scanning spectrophotometry and chemometric analysis as tools for carotenoids analysis in cassava genotypes (Manihot esculenta Crantz)

In this study, the metabolomics characterization focusing on the carotenoid composition of ten cassava (Manihot esculenta) genotypes cultivated in southern Brazil by UV-visible scanning spectrophotometry and reverse phase-high performance liquid chromatography was performed. Cassava roots rich in -carotene are an important staple food for populations with risk of vitamin A deficiency. Cassava genotypes with high pro-vitamin A activity have been identified as a strategy to reduce the prevalence of deficiency of this vitamin. The data set was used for the construction of a descriptive model by chemometric analysis. The genotypes of yellow-fleshed roots were clustered by the higher concentrations of cis--carotene and lutein. Inversely, cream-fleshed roots genotypes were grouped precisely due to their lower concentrations of these pigments, as samples rich in lycopene (redfleshed) differed among the studied genotypes. The analytical approach (UV-Vis, HPLC, and chemometrics) used showed to be efficient for understanding the chemodiversity of cassava genotypes, allowing to classify them according to important features for human health and nutrition.

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Extracting kinetic information from literature with KineticRE

To better understand the dynamic behavior of metabolic networks in a wide variety of conditions, the field of Systems Biology has increased its interest in the use of kinetic models. The different databases, available these days, do not contain enough data regarding this topic. Given that a significant part of the relevant information for the development of such models is still wide spread in the literature, it becomes essential to develop specific and powerful text mining tools to collect these data. In this context, this work has as main objective the development of a text mining tool to extract, from scientific literature, kinetic parameters, their respective values and their relations with enzymes and metabolites. The approach proposed integrates the development of a novel plug-in over the text mining framework @Note2. In the end, the pipeline developed was validated with a case study on Kluyveromyces lactis, spanning the analysis and results of 20 full text documents.

Integrating data from heterogeneous DNA microarray platforms

DNA microarrays are one of the most used technologies for gene expression measurement. However, there are several distinct microarray platforms, from different manufacturers, each with its own measurement protocol, resulting in data that can hardly be compared or directly integrated. Data integration from multiple sources aims to improve the assertiveness of statistical tests, reducing the data dimensionality problem. The integration of heterogeneous DNA microarray platforms comprehends a set of tasks that range from the re-annotation of the features used on gene expression, to data normalization and batch effect elimination. In this work, a complete methodology for gene expression data integration and application is proposed, which comprehends a transcript-based re-annotation process and several methods for batch effect attenuation. The integrated data will be used to select the best feature set and learning algorithm for a brain tumor classification case study. The integration will consider data from heterogeneous Agilent and Affymetrix platforms, collected from public gene expression databases, such as The Cancer Genome Atlas and Gene Expression Omnibus.

Terahertz response of patterned epitaxial graphene

We study the interaction between polarized terahertz (THz) radiation and micro-structured large-area graphene in transmission geometry. In order to efficiently couple the radiation into the two-dimensional material, a lateral periodic patterning of a closed graphene sheet by intercalation doping into stripes is chosen. We observe unequal transmittance of the radiation polarized parallel and perpendicular to the stripes. The relative contrast, partly enhanced by Fabry-Perot oscillations reaches 20 %. The effect even increases up to 50 % when removing graphene stripes in analogy to a wire grid polarizer. The polarization dependence is analyzed in a large frequency range from < 80 GHz to 3 THz, including the plasmon-polariton resonance. The results are in excellent agreement with theoretical calculations based on the electronic energy spectrum of graphene and the electrodynamics of the patterned structure

Towards the design and implementation of aspect-oriented programming for spreadsheets

A spreadsheet usually starts as a simple and singleuser software artifact, but, as frequent as in other software systems, quickly evolves into a complex system developed by many actors. Often, different users work on different aspects of the same spreadsheet: while a secretary may be only involved in adding plain data to the spreadsheet, an accountant may define new business rules, while an engineer may need to adapt the spreadsheet content so it can be used by other software systems.Unfortunately,spreadsheetsystemsdonotoffermodular mechanisms, and as a consequence, some of the previous tasks may be defined by adding intrusive “code” to the spreadsheet. In this paper we go through the design and implementation of an aspect-oriented language for spreadsheets so that users can work on different aspects of a spreadsheet in a modular way. For example, aspects can be defined in order to introduce new business rules to an existing spreadsheet, or to manipulate the spreadsheet data to be ported to another system. Aspects are defined as aspect-oriented program specifications that are dynamically woven into the underlying spreadsheet by an aspect weaver. In this aspect-oriented style of spreadsheet development, differentusers develop,orreuse,aspects withoutaddingintrusive code to the original spreadsheet. Such code is added/executed by the spreadsheet weaving mechanism proposed in this paper.

BiYacc: Roll your parser and reflective printer into one

In: A. Cunha, E. Kindler (eds.): Proceedings of the Fourth International Workshop on Bidirectional Transformations (Bx 2015), L’Aquila, Italy, July 24, 2015, published at http://ceur-ws.org

Superhydrophobic surfaces as a tool for the fabrication of hierarchical spherical polymeric carriers

Hierarchical polymeric carriers with high encapsulation efficiencies are fabricated via a biocompatible strategy developed using superhydrophobic (SH) surfaces. The carries are obtained by the incorporation of cell/BSA-loaded dextran-methacrylate (DEXT-MA) microparticles into alginate (ALG) macroscopic beads. Engineered devices like these are expected to boost the development of innovative and customizable systems for biomedical and biotechnological purposes.

Effect of sulfate and iron (III) on LCFA degradation by a methanogenic community

[Excerpt] Under anaerobic conditions long chain fatty acids (LCFA) can be converted to methane by syntrophic bacteria and methanogenic archaea. LCFA degradation was also reported in the presence of alternative hydrogenotrophic partners, such as sulfate-reducing bacteria (SRB) and iron-reducing bacteria (IRB), which generally show higher affinity for H2 than methanogens and are more resistant to LCFA [1,2,3]. Their presence in a microbial culture degrading LCFA can be advantageous to reduce LCFA toxicity towards methanogens, although high concentrations of external electron acceptor (EEA) can lead to outcompetition of methanogens and cease methane production. In this work, we tested the effect of adding sub-stoichiometric concentrations of sulfate and iron(III) to methanogenic communities degrading LCFA. (...)

Energy production from lipids by novel anaerobes

[Excerpt] Anaerobic microbial diversity encloses a very high potential that can be used for biotechnological applications. This potential is still largely unexplored, since the majority of the microorganisms in Nature are unknown or poorly characterized. This work is focused on the study of novel anaerobic microorganisms that participate in the metabolism of lipids, long chain fatty acids (LCFA) and glycerol, with the main goal of producing valuable energy-rich organic compounds. For that, conventional anaerobic culturing procedures were combined with continuous bioreactors operation and allied to microbial ecology approaches. Two main examples of the work performed will be presented. (...)

Who is who in anaerobic oil biodegradation?

[Excerpt] Anaerobic bioremediation is an important alternative for the common aerobic cleanup of subsurface petroleum-contaminated soil and water. Microbial communities involved in anaerobic oil biodegradation are scarcely studied, and only few mechanisms of anaerobic hydrocarbons degradation are described. In this work, microbial degradation of aliphatic hydrocarbons (AHC) was studied by using culture-dependent and culture-independent approaches. Hexadecane and hexadecene-degrading microbial communities were enriched under sulfate-reducing and methanogenic conditions. The microorganisms present in the enriched cultures were identified by 16S rRNA gene sequencing. (...)

Proteomic analysis of nitrate-dependent acetone degradation by Alicycliphilus denitrificans strain BC

Alicycliphilus denitrificans strain BC grows anaerobically on acetone with nitrate as electron acceptor. Comparative proteomics of cultures of A. denitrificans strain BC grown on either acetone or acetate with nitrate was performed to study the enzymes involved in the acetone degradation pathway. In the proposed acetone degradation pathway, an acetone carboxylase converts acetone to acetoacetate, an AMP-dependent synthetase/ligase converts acetoacetate to acetoacetyl-CoA, and an acetyl-CoA acetyltransferase cleaves acetoacetyl-CoA to two acetyl-CoA. We also found a putative aldehyde dehydrogenase associated with acetone degradation. This enzyme functioned as a -hydroxybutyrate dehydrogenase catalyzing the conversion of surplus acetoacetate to -hydroxybutyrate that may be converted to the energy and carbon storage compound, poly--hydroxybutyrate. Accordingly, we confirmed the formation of poly-?-hydroxybutyrate in acetone-grown cells of strain BC. Our findings provide insight in nitrate-dependent acetone degradation that is activated by carboxylation of acetone. This will aid studies of similar pathways found in other microorganisms degrading acetone with nitrate or sulfate as electron acceptor.

Anaerobic oxidation of methane associated with sulfate reduction in a natural freshwater gas source

The occurrence of anaerobic oxidation of methane (AOM) and trace methane oxidation (TMO) was investigated in a freshwater natural gas source. Sediment samples were taken and analyzed for potential electron acceptors coupled to AOM. Long-term incubations with 13C-labeled CH4 (13CH4) and different electron acceptors showed that both AOM and TMO occurred. In most conditions, 13C-labeled CO2 (13CO2) simultaneously increased with methane formation, which is typical for TMO. In the presence of nitrate, neither methane formation nor methane oxidation occurred. Net AOM was measured only with sulfate as electron acceptor. Here, sulfide production occurred simultaneously with 13CO2 production and no methanogenesis occurred, excluding TMO as a possible source for 13CO2 production from 13CH4. Archaeal 16S rRNA gene analysis showed the highest presence of ANME-2a/b (ANaerobic MEthane oxidizing archaea) and AAA (AOM Associated Archaea) sequences in the incubations with methane and sulfate as compared with only methane addition. Higher abundance of ANME-2a/b in incubations with methane and sulfate as compared with only sulfate addition was shown by qPCR analysis. Bacterial 16S rRNA gene analysis showed the presence of sulfate-reducing bacteria belonging to SEEP-SRB1. This is the first report that explicitly shows that AOM is associated with sulfate reduction in an enrichment culture of ANME-2a/b and AAA methanotrophs and SEEP-SRB1 sulfate reducers from a low-saline environment.