Changes in Community Structure of Sediment Bacteria Along the Florida Coastal Everglades Marsh–Mangrove–Seagrass Salinity Gradient

Community structure of sediment bacteria in the Everglades freshwater marsh, fringing mangrove forest, and Florida Bay seagrass meadows were described based on polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) patterns of 16S rRNA gene fragments and by sequencing analysis of DGGE bands. The DGGE patterns were correlated with the environmental variables by means of canonical correspondence analysis. There was no significant trend in the Shannon–Weiner index among the sediment samples along the salinity gradient. However, cluster analysis based on DGGE patterns revealed that the bacterial community structure differed according to sites. Not only were these salinity/vegetation regions distinct but the sediment bacteria communities were consistently different along the gradient from freshwater marsh, mangrove forest, eastern-central Florida Bay, and western Florida Bay. Actinobacteria- and Bacteroidetes/Chlorobi-like DNA sequences were amplified throughout all sampling sites. More Chloroflexi and members of candidate division WS3 were found in freshwater marsh and mangrove forest sites than in seagrass sites. The appearance of candidate division OP8-like DNA sequences in mangrove sites distinguished these communities from those of freshwater marsh. The seagrass sites were characterized by reduced presence of bands belonging to Chloroflexi with increased presence of those bands related to Cyanobacteria, γ-Proteobacteria, Spirochetes, and Planctomycetes. This included the sulfate-reducing bacteria, which are prevalent in marine environments. Clearly, bacterial communities in the sediment were different along the gradient, which can be explained mainly by the differences in salinity and total phosphorus.

(Table S2) Relative abundance of archaeal 16S rRNA genes in sediment cores

Deep drilling into the marine sea floor has uncovered a vast sedimentary ecosystem of microbial cells (Parkes et al., 1994, doi:10.1038/371410a0; D'Hondt et al., 2004, doi:10.1126/science.1101155). Extrapolation of direct counts of stained microbial cells to the total volume of habitable marine subsurface sediments suggests that between 56 Pg (Parkes et al., 1994, doi:10.1038/371410a0) and 303 Pg (Whitman et al., 1998) of cellular carbon could be stored in this largely unexplored habitat. From recent studies using various culture-independent techniques, no clear picture has yet emerged as to whether Archaea or Bacteria are more abundant in this extensive ecosystem (Schippers et al., doi:10.1038/nature03302; Inagaki et al., doi:10.1073/pnas.0511033103 ; Mauclaire et al., doi:10.1111/j.1472-4677.2004.00035.x; Biddle et al., doi:10.1073/pnas.0600035103). Here we show that in subsurface sediments buried deeper than 1 m in a wide range of oceanographic settings at least 87% of intact polar membrane lipids, biomarkers for the presence of live cells (Biddle et al., doi:10.1073/pnas.0600035103; Sturt et al., 2004, doi:10.1002/rcm.1378), are attributable to archaeal membranes, suggesting that Archaea constitute a major fraction of the biomass. Results obtained from modified quantitative polymerase chain reaction and slot-blot hybridization protocols support the lipid-based evidence and indicate that these techniques have previously underestimated archaeal biomass. The lipid concentrations are proportional to those of total organic carbon. On the basis of this relationship, we derived an independent estimate of amounts of cellular carbon in the global marine subsurface biosphere. Our estimate of 90 Pg of cellular carbon is consistent, within an order of magnitude, with previous estimates, and underscores the importance of marine subsurface habitats for global biomass budgets.

Pore water measurements of sediment cores from the Helgoland mud area, North Sea

Iron reduction in subseafloor sulfate-depleted and methane-rich marine sediments is currently a subject of interest in subsurface geomicrobiology. While iron reduction and microorganisms involved have been well studied in marine surface sediments, little is known about microorganisms responsible for iron reduction in deep methanic sediments. Here, we used quantitative PCR (Q-PCR)-based 16S rRNA gene copy numbers and pyrosequencing-based relative abundances of bacteria and archaea to investigate covariance between distinct microbial populations and specific geochemical profiles in the top 5 m of sediment cores from the Helgoland mud area, North Sea. We found that gene copy numbers of bacteria and archaea were specifically higher around the peak of dissolved iron in the methanic zone (250-350 cm. The higher copy numbers at these depths were also reflected by the relative sequence abundances of members of the candidate division JS1, methanogenic and Methanohalobium/ANME-3 related archaea. The distribution of these populations was strongly correlated to the profile of pore-water Fe2+ while that of Desulfobacteraceae corresponded to the pore-water sulfate profile. Furthermore, specific JS1 populations also strongly co-varied with the distribution of Methanosaetaceae in the methanic zone. Our data suggest that the interplay among JS1 bacteria, methanogenic archaea and Methanohalobium/ANME-3-related archaea may be important for iron reduction and methane cycling in deep methanic sediments of the Helgoland mud area and perhaps in other methane-rich depositional environments. .

Antibody Signatures Reflect Different Disease Pathologies in Patients With Schistosomiasis Due to Schistosoma japonicum

Infection with Schistosoma japonicum causes high levels of pathology that is predominantly determined by the cellular and humoral response of the host. However, the specific antibody response that arises during the development of disease is largely undescribed in Asian schistosomiasis-endemic populations. A schistosome protein microarray was used to compare the antibody profiles of subjects with acute infection, with early or advanced disease associated with severe pathology, with chronic infection, and subjects exposed but stool negative for S. japonicum eggs to the antibody profiles of nonexposed controls. Twenty-five immunodominant antigens were identified, including vaccine candidates, tetraspanin-related proteins, transporter molecules, and unannotated proteins. Additionally, individuals with severe pathology had a limited specific antibody response, suggesting that individuals with mild disease may use a broad and strong antibody response, particularly against surface-exposed proteins, to control pathology and/or infection. Our study has identified specific antigens that can discriminate between S. japonicum-exposed groups with different pathologies and may also allow the host to control disease pathology and provide resistance to parasite infection.

Analyses of the community compositions of root rot pathogenic fungi in the soybean rhizosphere soil

Soybean ( Glycine max [L.] Merr.) root rot is an important disease of soybean under continuous cropping, and root rot is widely distributed throughout the world. This disease is extremely harmful, and it is difficult to prevent and control. The study aimed to elucidate the composition of root rot pathogenic fungal communities in the continuous cropping of soybean. In this study, we employed PCRDGGE technology to analyze the communities of root rot pathogenic fungi in soybean rhizosphere soil subjected to continuous cropping during a season with a high incidence of root rot in Heilongjiang province, China, the main soybean producing area in China. The results of 13 DGGE bands were analyzed by phylogenetic revealed that the predominant root rot pathogenic fungi in rhizosphere soil in the test area were Pythium ultimum and Fusarium species. The results of cluster analysis showed that the duration of continuous cropping, the soybean variety and the plant growth stage all had significant effects on the diversity of root rot pathogenic fungi in rhizosphere soil.

Naturally Occurring Resistance-Associated Variants of Hepatitis C Virus Protease Inhibitors in Poor Responders to Pegylated Interferon-Ribavirin

International audience

Resposta da lagarta-do-cartucho à aplicação do fosfito em milho doce e divergência genética de populações de lagartas-da-espiga

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Agronomia e Medicina Veterinária, Programa de Pós-Graduação em Agronomia, 2016.

Association of kinase insert domain-containing receptor (KDR) gene polymorphism/ haplotypes with recurrent spontaneous abortion and genetic structure

Background: Recurrent spontaneous abortion is one of the diseases that can lead to physical, psychological, and, economical problems for both individuals and society. Recently a few numbers of genetic polymorphisms in kinase insert domain-containing receptor (KDR) gene are examined that can endanger the life of the fetus in pregnant women. Objective: The risk of KDR gene polymorphisms was investigated in Iranian women with idiopathic recurrent spontaneous abortion (RSA). Materials and Methods: A case controlled study was performed. One hundred idiopathic recurrent spontaneous abortion patients with at least two consecutive pregnancy losses before 20 weeks of gestational age with normal karyotypes were included in the study. Also, 100 healthy women with at least one natural pregnancy were studied as control group. Two functional SNPs located in KDR gene; rs1870377 (Q472H), and rs2305948 (V297I) as well as one tag SNP in the intron region (rs6838752) were genotyped by using PCR based restriction fragment length polymorphism (PCR-RFLP) technique. Haplotype frequency was determined for these three SNPs’ genotypes. Analysis of genetic STRUCTURE and K means clustering were performed to study genetic variation. Results: Functional SNP (rs1870377) was highly linked to tag SNP (rs6838752) (D´ value=0. 214; χ2 = 16.44, p<0. 001). K means clustering showed that k = 8 as the best fit for the optimal number of genetic subgroups in our studied materials. This result was in agreement with Neighbor Joining cluster analysis. Conclusion: In our study, the allele and genotype frequencies were not associated with RSA between patient and control individuals. Inconsistent results in different populations with different allele frequencies among RSA patients and controls may be due to ethnic variation and used sample size.

Preference Mapping Of Dulce De Leche Commercialized In Brazilian Markets.

Dulce de leche samples available in the Brazilian market were submitted to sensory profiling by quantitative descriptive analysis and acceptance test, as well sensory evaluation using the just-about-right scale and purchase intent. External preference mapping and the ideal sensory characteristics of dulce de leche were determined. The results were also evaluated by principal component analysis, hierarchical cluster analysis, partial least squares regression, artificial neural networks, and logistic regression. Overall, significant product acceptance was related to intermediate scores of the sensory attributes in the descriptive test, and this trend was observed even after consumer segmentation. The results obtained by sensometric techniques showed that optimizing an ideal dulce de leche from the sensory standpoint is a multidimensional process, with necessary adjustments on the appearance, aroma, taste, and texture attributes of the product for better consumer acceptance and purchase. The optimum dulce de leche was characterized by high scores for the attributes sweet taste, caramel taste, brightness, color, and caramel aroma in accordance with the preference mapping findings. In industrial terms, this means changing the parameters used in the thermal treatment and quantitative changes in the ingredients used in formulations.

Efeitos do treinamento com pesos sobre a densidade mineral ossea, força muscular e variaveis funcionais na menopausa

Universidade Estadual de Campinas . Faculdade de Educação Física

A contribution to the phytogeography of Brazilian campos: an analysis based on Poaceae

Twenty areas from eight Brazilian states were compared according to a list of 224 species of Poaceae. In order to determinate affinity patterns between the areas, a binary matrix was submitted to cluster and ordination analysis. The patterns found were then faced to climate and geographic position. The scores corresponding to the areas obtained from the cluster analysis showed a strong correlation to temperature. The scores corresponding to the species suggest a gradient that associates distribution patterns to the photosynthetic pathway (C3 or C4). The current results suggest that the traditional classification of the Southern American grasslands might require some modification in order to be broadly applicable in the Brazilian context.

Chicken skeletal muscle-associated macroarray for gene discovery

Macro- and microarrays are well-established technologies to determine gene functions through repeated measurements of transcript abundance. We constructed a chicken skeletal muscle-associated array based on a muscle-specific EST database, which was used to generate a tissue expression dataset of similar to 4500 chicken genes across 5 adult tissues (skeletal muscle, heart, liver, brain, and skin). Only a small number of ESTs were sufficiently well characterized by BLAST searches to determine their probable cellular functions. Evidence of a particular tissue-characteristic expression can be considered an indication that the transcript is likely to be functionally significant. The skeletal muscle macroarray platform was first used to search for evidence of tissue-specific expression, focusing on the biological function of genes/transcripts, since gene expression profiles generated across tissues were found to be reliable and consistent. Hierarchical clustering analysis revealed consistent clustering among genes assigned to 'developmental growth', such as the ontology genes and germ layers. Accuracy of the expression data was supported by comparing information from known transcripts and tissue from which the transcript was derived with macroarray data. Hybridization assays resulted in consistent tissue expression profile, which will be useful to dissect tissue-regulatory networks and to predict functions of novel genes identified after extensive sequencing of the genomes of model organisms. Screening our skeletal-muscle platform using 5 chicken adult tissues allowed us identifying 43 'tissue-specific' transcripts, and 112 co-expressed uncharacterized transcripts with 62 putative motifs. This platform also represents an important tool for functional investigation of novel genes; to determine expression pattern according to developmental stages; to evaluate differences in muscular growth potential between chicken lines, and to identify tissue-specific genes.

Effect of eight weeks of strength training on fatigue resistance in men and women

The purpose of the present study was to compare the effects of eight weeks of strength training on fatigue resistance in men and women. Thirty-three men and twenty-three women performed eight weeks of strength training in three weekly sessions. Subjects performed four sets using 80% of 1-RM tests on bench press, squat and arm curl. Fatigue index (FI) was used for analysis of decline in motor performance along the sets. The sum of the number of repetitions accomplished in the four sets in each exercise was used to indicate the fatigue resistance. Anova or Ancova two-way ( time x gender) was employed for statistical analysis ( P < 0.05). Eight weeks of strength training increased significantly 1-RM strength, fatigue resistance and total number of repetitions in both genders. FI decreased significantly in both genders after training ( men = 50% vs. women = Time x gender interaction was observed in the total number of repetitions in squat ( P = 0.04) and arm curl exercises, regarding gains to women ( P = 0.01). In conclusion, eight weeks of ST improved strength, FR, FI and total number of repetitions performed. However, women obtained greater adaptations than men.

An exploratory analysis of relationships between socioeconomic, land use, activity participation variables and travel patterns

This paper aims to find relations between the socioeconomic characteristics, activity participation, land use patterns and travel behavior of the residents in the Sao Paulo Metropolitan Area (SPMA) by using Exploratory Multivariate Data Analysis (EMDA) techniques. The variables influencing travel pattern choices are investigated using: (a) Cluster Analysis (CA), grouping and characterizing the Traffic Zones (17), proposing the independent variable called Origin Cluster and, (b) Decision Tree (DT) to find a priori unknown relations among socioeconomic characteristics, land use attributes of the origin TZ and destination choices. The analysis was based on the origin-destination home-interview survey carried out in SPMA in 1997. The DT application revealed the variables of greatest influence on the travel pattern choice. The most important independent variable considered by DT is car ownership, followed by the Use of Transportation ""credits"" for Transit tariff, and, finally, activity participation variables and Origin Cluster. With these results, it was possible to analyze the influence of a family income, car ownership, position of the individual in the family, use of transportation ""credits"" for transit tariff (mainly for travel mode sequence choice), activities participation (activity sequence choice) and Origin Cluster (destination/travel distance choice). (c) 2010 Elsevier Ltd. All rights reserved.

A chemometric study on the analgesic activity of cannabinoid compounds using SDA, KNN and SIMCA methods

The supervised pattern recognition methods K-Nearest Neighbors (KNN), stepwise discriminant analysis (SDA), and soft independent modelling of class analogy (SIMCA) were employed in this work with the aim to investigate the relationship between the molecular structure of 27 cannabinoid compounds and their analgesic activity. Previous analyses using two unsupervised pattern recognition methods (PCA-principal component analysis and HCA-hierarchical cluster analysis) were performed and five descriptors were selected as the most relevants for the analgesic activity of the compounds studied: R (3) (charge density on substituent at position C(3)), Q (1) (charge on atom C(1)), A (surface area), log P (logarithm of the partition coefficient) and MR (molecular refractivity). The supervised pattern recognition methods (SDA, KNN, and SIMCA) were employed in order to construct a reliable model that can be able to predict the analgesic activity of new cannabinoid compounds and to validate our previous study. The results obtained using the SDA, KNN, and SIMCA methods agree perfectly with our previous model. Comparing the SDA, KNN, and SIMCA results with the PCA and HCA ones we could notice that all multivariate statistical methods classified the cannabinoid compounds studied in three groups exactly in the same way: active, moderately active, and inactive.