Phylogenetic and functional diversity of metagenomic libraries of phenol degrading sludge from petroleum refinery wastewater treatment system

In petrochemical refinery wastewater treatment plants (WWTP), different concentrations of pollutant compounds are received daily in the influent stream, including significant amounts of phenolic compounds, creating propitious conditions for the development of particular microorganisms that can rapidly adapt to such environment. In the present work, the microbial sludge from a refinery WWTP was enriched for phenol, cloned into fosmid vectors and pyrosequenced. The fosmid libraries yielded 13,200 clones and a comprehensive bioinformatic analysis of the sequence data set revealed a complex and diverse bacterial community in the phenol degrading sludge. The phylogenetic analyses using MEGAN in combination with RDP classifier showed a massive predominance of Proteobacteria, represented mostly by the genera Diaphorobacter, Pseudomonas, Thauera and Comamonas. The functional classification of phenol degrading sludge sequence data set generated by MG-RAST showed the wide metabolic diversity of the microbial sludge, with a high percentage of genes involved in the aerobic and anaerobic degradation of phenol and derivatives. In addition, genes related to the metabolism of many other organic and xenobiotic compounds, such as toluene, biphenyl, naphthalene and benzoate, were found. Results gathered herein demonstrated that the phenol degrading sludge has complex phylogenetic and functional diversities, showing the potential of such community to degrade several pollutant compounds. This microbiota is likely to represent a rich resource of versatile and unknown enzymes which may be exploited for biotechnological processes such as bioremediation

Dye-sensitized solar cells based on dimethylamino-π-bridge-pyranoanthocyanin dyes

UID/QUI/50006/2019 PTDC/QEQ-QFI/1971/2014 PD/BD/135087/2017 SFRH/BD/136556/2018 SFRH/BD/143309/2019 IF/00225/2015 DL57/2016 Program Contract (HC). UID/CTM/50025/2019 PTDC/CTM-ENE/5125/2014 CNPq 444061/2018-5 Universal grant 408181/2016-3The pyranoanthocyanins present in red wine display great potential as photosensitizers in bio-inspired Dye-Sensitized Solar Cells (DSSCs). Following a biomimetic approach, a series of amino-π-bridge-pyranoanthocyanin derivatives were employed as dye sensitizers in DSSCs. The dimethylamine group was selected to take advantage of its electron-donor character and the possibility of ‘dual-mode anchoring’ ([sbnd]OH vs. dimethylamino) to titanium dioxide. The increase in π-conjugation via insertion of C[dbnd]C bonds affected molecule flexibility, electron-donor ability and the pH-dependent equilibria of the pyranoanthocyanin derivatives. The current vs. potential properties of photoanodes using these dyes pointed to essential features of the relationship between power conversion efficiency and dye structure. These included the influences of the dimethylamine group, of π-conjugation and of substitution in ring B on the adsorption of the dyes to TiO2 and on the overall performance of the DSSCs prepared from them with and without added acid. An overall efficiency of 2.55% was obtained for the best performing compound, 4-(dimethylamino)-cinnamyl-pyranocyanidin-3-O-glucoside (JO3), which consolidates the importance of this family of compounds as potential dye-sensitizers for DSSC applications.authorsversionpublishe

Expressed sequence tag analysis of the human pathogen Paracoccidioides brasiliensis yeast phase: Identification of putative homologues of Candida albicans virulence and pathogenicity genes

Paracoccidioides brasiliensis, a thermodimorphic fungus, is the causative agent of the prevalent systemic mycosis in Latin America, paracoccidioidomycosis. We present here a survey of expressed genes in the yeast pathogenic phase of P. brasiliensis. We obtained 13,490 expressed sequence tags from both 5' and 3' ends. Clustering analysis yielded the partial sequences of 4,692 expressed genes that were functionally classified by similarity to known genes. We have identified several Candida albicans virulence and pathogenicity homologues in P. brasiliensis. Furthermore, we have analyzed the expression of some of these genes during the dimorphic yeast-mycelium-yeast transition by real-time quantitative reverse transcription-PCR. Clustering analysis of the mycelium-yeast transition revealed three groups: (i) RBT, hydrophobin, and isocitrate lyase; (ii) malate dehydrogenase, contigs Pb1067 and Pb1145, GPI, and alternative oxidase; and (iii) ubiquitin, delta-9-desaturase, HSP70, HSP82, and HSP104. the first two groups displayed high mRNA expression in the mycelial phase, whereas the third group showed higher mRNA expression in the yeast phase. Our results suggest the possible conservation of pathogenicity and virulence mechanisms among fungi, expand considerably gene identification in P. brasiliensis, and provide a broader basis for further progress in understanding its biological peculiarities.Univ São Paulo, Dept Ciencias Farmaceut, Fac Ciencias Farmaceut Ribeirao Preto, BR-14040903 Ribeirao Preto, SP, BrazilUniv São Paulo, Fac Filosofia Ciencias & Letras Ribeirao Pret, BR-14040903 Ribeirao Preto, SP, BrazilInst Pasteur, Unite Genet Mol Levures, Paris, FranceUniv Vale do Paraiba, UNIVAP, Vale Do Paraiba, BrazilUniv Mogi das Cruzes, Nucleo Integrado Biotecnol, Mogi Das Cruzes, BrazilUniversidade Federal de São Paulo, Dept Microbiol Imunol & Parasitol, São Paulo, BrazilUniversidade Federal de São Paulo, Dept Microbiol Imunol & Parasitol, São Paulo, BrazilWeb of Scienc

Genome of the Avirulent Human-Infective Trypanosome—Trypanosoma rangeli

Background: Trypanosoma rangeli is a hemoflagellate protozoan parasite infecting humans and other wild and domestic mammals across Central and South America. It does not cause human disease, but it can be mistaken for the etiologic agent of Chagas disease, Trypanosoma cruzi. We have sequenced the T. rangeli genome to provide new tools for elucidating the distinct and intriguing biology of this species and the key pathways related to interaction with its arthropod and mammalian hosts.  Methodology/Principal Findings: The T. rangeli haploid genome is ,24 Mb in length, and is the smallest and least repetitive trypanosomatid genome sequenced thus far. This parasite genome has shorter subtelomeric sequences compared to those of T. cruzi and T. brucei; displays intraspecific karyotype variability and lacks minichromosomes. Of the predicted 7,613 protein coding sequences, functional annotations could be determined for 2,415, while 5,043 are hypothetical proteins, some with evidence of protein expression. 7,101 genes (93%) are shared with other trypanosomatids that infect humans. An ortholog of the dcl2 gene involved in the T. brucei RNAi pathway was found in T. rangeli, but the RNAi machinery is non-functional since the other genes in this pathway are pseudogenized. T. rangeli is highly susceptible to oxidative stress, a phenotype that may be explained by a smaller number of anti-oxidant defense enzymes and heatshock proteins.  Conclusions/Significance: Phylogenetic comparison of nuclear and mitochondrial genes indicates that T. rangeli and T. cruzi are equidistant from T. brucei. In addition to revealing new aspects of trypanosome co-evolution within the vertebrate and invertebrate hosts, comparative genomic analysis with pathogenic trypanosomatids provides valuable new information that can be further explored with the aim of developing better diagnostic tools and/or therapeutic targets

Measurement of the cosmic ray spectrum above 4×10184{\times}10^{18} eV using inclined events detected with the Pierre Auger Observatory

A measurement of the cosmic-ray spectrum for energies exceeding $4{\times}10^{18}$ eV is presented, which is based on the analysis of showers with zenith angles greater than $60^{\circ}$ detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above $5.3{\times}10^{18}$ eV, the "ankle", the flux can be described by a power law $E^{-\gamma}$ with index $\gamma=2.70 \pm 0.02 \,\text{(stat)} \pm 0.1\,\text{(sys)}$ followed by a smooth suppression region. For the energy ($E_\text{s}$) at which the spectral flux has fallen to one-half of its extrapolated value in the absence of suppression, we find $E_\text{s}=(5.12\pm0.25\,\text{(stat)}^{+1.0}_{-1.2}\,\text{(sys)}){\times}10^{19}$ eV.Comment: Replaced with published version. Added journal reference and DO

Energy Estimation of Cosmic Rays with the Engineering Radio Array of the Pierre Auger Observatory

The Auger Engineering Radio Array (AERA) is part of the Pierre Auger Observatory and is used to detect the radio emission of cosmic-ray air showers. These observations are compared to the data of the surface detector stations of the Observatory, which provide well-calibrated information on the cosmic-ray energies and arrival directions. The response of the radio stations in the 30 to 80 MHz regime has been thoroughly calibrated to enable the reconstruction of the incoming electric field. For the latter, the energy deposit per area is determined from the radio pulses at each observer position and is interpolated using a two-dimensional function that takes into account signal asymmetries due to interference between the geomagnetic and charge-excess emission components. The spatial integral over the signal distribution gives a direct measurement of the energy transferred from the primary cosmic ray into radio emission in the AERA frequency range. We measure 15.8 MeV of radiation energy for a 1 EeV air shower arriving perpendicularly to the geomagnetic field. This radiation energy -- corrected for geometrical effects -- is used as a cosmic-ray energy estimator. Performing an absolute energy calibration against the surface-detector information, we observe that this radio-energy estimator scales quadratically with the cosmic-ray energy as expected for coherent emission. We find an energy resolution of the radio reconstruction of 22% for the data set and 17% for a high-quality subset containing only events with at least five radio stations with signal.Comment: Replaced with published version. Added journal reference and DO

A comprehensive analysis of autocorrelation and bias in home range estimation

Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated-Gaussian reference function [AKDE], Silverman´s rule of thumb, and least squares cross-validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half-sample cross-validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ((Formula presented.)) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID-based estimates by a mean factor of 2. The median number of cross-validated locations included in the hold-out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing (Formula presented.). To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal´s movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small (Formula presented.). While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an (Formula presented.) >1,000, where 30% had an (Formula presented.) <30. In this frequently encountered scenario of small (Formula presented.), AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.Fil: Noonan, Michael J.. National Zoological Park; Estados Unidos. University of Maryland; Estados UnidosFil: Tucker, Marlee A.. Senckenberg Gesellschaft Für Naturforschung; . Goethe Universitat Frankfurt; AlemaniaFil: Fleming, Christen H.. University of Maryland; Estados Unidos. National Zoological Park; Estados UnidosFil: Akre, Thomas S.. National Zoological Park; Estados UnidosFil: Alberts, Susan C.. University of Duke; Estados UnidosFil: Ali, Abdullahi H.. Hirola Conservation Programme. Garissa; KeniaFil: Altmann, Jeanne. University of Princeton; Estados UnidosFil: Antunes, Pamela Castro. Universidade Federal do Mato Grosso do Sul; BrasilFil: Belant, Jerrold L.. State University of New York; Estados UnidosFil: Beyer, Dean. Universitat Phillips; AlemaniaFil: Blaum, Niels. Universitat Potsdam; AlemaniaFil: Böhning Gaese, Katrin. Senckenberg Gesellschaft Für Naturforschung; Alemania. Goethe Universitat Frankfurt; AlemaniaFil: Cullen Jr., Laury. Instituto de Pesquisas Ecológicas; BrasilFil: de Paula, Rogerio Cunha. National Research Center For Carnivores Conservation; BrasilFil: Dekker, Jasja. Jasja Dekker Dierecologie; Países BajosFil: Drescher Lehman, Jonathan. George Mason University; Estados Unidos. National Zoological Park; Estados UnidosFil: Farwig, Nina. Michigan State University; Estados UnidosFil: Fichtel, Claudia. German Primate Center; AlemaniaFil: Fischer, Christina. Universitat Technical Zu Munich; AlemaniaFil: Ford, Adam T.. University of British Columbia; CanadáFil: Goheen, Jacob R.. University of Wyoming; Estados UnidosFil: Janssen, René. Bionet Natuuronderzoek; Países BajosFil: Jeltsch, Florian. Universitat Potsdam; AlemaniaFil: Kauffman, Matthew. University Of Wyoming; Estados UnidosFil: Kappeler, Peter M.. German Primate Center; AlemaniaFil: Koch, Flávia. German Primate Center; AlemaniaFil: LaPoint, Scott. Max Planck Institute für Ornithologie; Alemania. Columbia University; Estados UnidosFil: Markham, A. Catherine. Stony Brook University; Estados UnidosFil: Medici, Emilia Patricia. Instituto de Pesquisas Ecológicas (IPE) ; BrasilFil: Morato, Ronaldo G.. Institute For Conservation of The Neotropical Carnivores; Brasil. National Research Center For Carnivores Conservation; BrasilFil: Nathan, Ran. The Hebrew University of Jerusalem; IsraelFil: Oliveira Santos, Luiz Gustavo R.. Universidade Federal do Mato Grosso do Sul; BrasilFil: Olson, Kirk A.. Wildlife Conservation Society; Estados Unidos. National Zoological Park; Estados UnidosFil: Patterson, Bruce. Field Museum of National History; Estados UnidosFil: Paviolo, Agustin Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; ArgentinaFil: Ramalho, Emiliano Esterci. Institute For Conservation of The Neotropical Carnivores; Brasil. Instituto de Desenvolvimento Sustentavel Mamirauá; BrasilFil: Rösner, Sascha. Michigan State University; Estados UnidosFil: Schabo, Dana G.. Michigan State University; Estados UnidosFil: Selva, Nuria. Institute of Nature Conservation of The Polish Academy of Sciences; PoloniaFil: Sergiel, Agnieszka. Institute of Nature Conservation of The Polish Academy of Sciences; PoloniaFil: Xavier da Silva, Marina. Parque Nacional do Iguaçu; BrasilFil: Spiegel, Orr. Universitat Tel Aviv; IsraelFil: Thompson, Peter. University of Maryland; Estados UnidosFil: Ullmann, Wiebke. Universitat Potsdam; AlemaniaFil: Ziḝba, Filip. Tatra National Park; PoloniaFil: Zwijacz Kozica, Tomasz. Tatra National Park; PoloniaFil: Fagan, William F.. University of Maryland; Estados UnidosFil: Mueller, Thomas. Senckenberg Gesellschaft Für Naturforschung; . Goethe Universitat Frankfurt; AlemaniaFil: Calabrese, Justin M.. National Zoological Park; Estados Unidos. University of Maryland; Estados Unido

Measurement of the Radiation Energy in the Radio Signal of Extensive Air Showers as a Universal Estimator of Cosmic-Ray Energy

We measure the energy emitted by extensive air showers in the form of radio emission in the frequency range from 30 to 80 MHz. Exploiting the accurate energy scale of the Pierre Auger Observatory, we obtain a radiation energy of 15.8 \pm 0.7 (stat) \pm 6.7 (sys) MeV for cosmic rays with an energy of 1 EeV arriving perpendicularly to a geomagnetic field of 0.24 G, scaling quadratically with the cosmic-ray energy. A comparison with predictions from state-of-the-art first-principle calculations shows agreement with our measurement. The radiation energy provides direct access to the calorimetric energy in the electromagnetic cascade of extensive air showers. Comparison with our result thus allows the direct calibration of any cosmic-ray radio detector against the well-established energy scale of the Pierre Auger Observatory.Comment: Replaced with published version. Added journal reference and DOI. Supplemental material in the ancillary file

Predicting the Proteins of Angomonas deanei, Strigomonas culicis and Their Respective Endosymbionts Reveals New Aspects of the Trypanosomatidae Family

Endosymbiont-bearing trypanosomatids have been considered excellent models for the study of cell evolution because the host protozoan co-evolves with an intracellular bacterium in a mutualistic relationship. Such protozoa inhabit a single invertebrate host during their entire life cycle and exhibit special characteristics that group them in a particular phylogenetic cluster of the Trypanosomatidae family, thus classified as monoxenics. in an effort to better understand such symbiotic association, we used DNA pyrosequencing and a reference-guided assembly to generate reads that predicted 16,960 and 12,162 open reading frames (ORFs) in two symbiont-bearing trypanosomatids, Angomonas deanei (previously named as Crithidia deanei) and Strigomonas culicis (first known as Blastocrithidia culicis), respectively. Identification of each ORF was based primarily on TriTrypDB using tblastn, and each ORF was confirmed by employing getorf from EMBOSS and Newbler 2.6 when necessary. the monoxenic organisms revealed conserved housekeeping functions when compared to other trypanosomatids, especially compared with Leishmania major. However, major differences were found in ORFs corresponding to the cytoskeleton, the kinetoplast, and the paraflagellar structure. the monoxenic organisms also contain a large number of genes for cytosolic calpain-like and surface gp63 metalloproteases and a reduced number of compartmentalized cysteine proteases in comparison to other TriTryp organisms, reflecting adaptations to the presence of the symbiont. the assembled bacterial endosymbiont sequences exhibit a high A+T content with a total of 787 and 769 ORFs for the Angomonas deanei and Strigomonas culicis endosymbionts, respectively, and indicate that these organisms hold a common ancestor related to the Alcaligenaceae family. Importantly, both symbionts contain enzymes that complement essential host cell biosynthetic pathways, such as those for amino acid, lipid and purine/pyrimidine metabolism. These findings increase our understanding of the intricate symbiotic relationship between the bacterium and the trypanosomatid host and provide clues to better understand eukaryotic cell evolution.Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)ERC AdG SISYPHEUniv Fed Rio de Janeiro, Inst Biofis Carlos Chagas Filho, Lab Ultraestrutura Celular Hertha Meyer, BR-21941 Rio de Janeiro, BrazilUniv Fed Rio de Janeiro, Inst Biofis Carlos Chagas Filho, Lab Metab Macromol Firmino Torres de Castro, BR-21941 Rio de Janeiro, BrazilLab Bioinformat, Lab Nacl Computacao Cient, Rio de Janeiro, BrazilINRIA Grenoble Rhone Alpes, BAMBOO Team, Villeurbanne, FranceUniv Lyon 1, CNRS, UMR5558, Lab Biometrie & Biol Evolut, F-69622 Villeurbanne, FranceUniv Estadual Campinas, Inst Biol, Dept Genet Evolucao & Bioagentes, São Paulo, BrazilUniv São Paulo, Fac Ciencias Farmaceut Ribeirao Preto, Dept Ciencias Farmaceut, São Paulo, BrazilLab Nacl Ciencia & Tecnol Bioetano, São Paulo, BrazilUniv Fed Minas Gerais, Inst Ciencias Biol, Dept Bioquim & Imunol, Belo Horizonte, MG, BrazilUniv Fed Goias, Inst Ciencias Biol, Mol Biol Lab, Goiania, Go, BrazilFundacao Oswaldo Cruz, Inst Carlos Chagas, Lab Biol Mol Tripanossomatideos, Curitiba, Parana, BrazilFundacao Oswaldo Cruz, Inst Carlos Chagas, Lab Genom Func, Curitiba, Parana, BrazilUniv Estadual Campinas, Ctr Pluridisciplinar Pesquisas Quim Biol & Agr, São Paulo, BrazilUniv Fed Minas Gerais, Inst Ciencias Biol, Dept Parasitol, Belo Horizonte, MG, BrazilUniv Fed Santa Catarina, Dept Microbiol Imunol & Parasitol, Ctr Ciencias Biol, Lab Protozool & Bioinformat, Florianopolis, SC, BrazilUniv Fed Vicosa, Dept Bioquim & Biol Mol, Ctr Ciencias Biol & Saude, Vicosa, MG, BrazilInst Butantan, Lab Especial Ciclo Celular, São Paulo, BrazilUniv São Paulo, Dept Biol, Fac Filosofia Ciencias & Letras Ribeirao Preto, São Paulo, BrazilUniversidade Federal de São Paulo, Escola Paulista Med, Dept Microbiol Imunol & Parasitol, São Paulo, BrazilUniversidade Federal de São Paulo, Escola Paulista Med, Dept Microbiol Imunol & Parasitol, São Paulo, BrazilWeb of Scienc