Comprehensive analysis of correlation coefficients estimated from pooling heterogeneous microarray data

Background The synthesis of information across microarray studies has been performed by combining statistical results of individual studies (as in a mosaic), or by combining data from multiple studies into a large pool to be analyzed as a single data set (as in a melting pot of data). Specific issues relating to data heterogeneity across microarray studies, such as differences within and between labs or differences among experimental conditions, could lead to equivocal results in a melting pot approach. Results We applied statistical theory to determine the specific effect of different means and heteroskedasticity across 19 groups of microarray data on the sign and magnitude of gene-to-gene Pearson correlation coefficients obtained from the pool of 19 groups. We quantified the biases of the pooled coefficients and compared them to the biases of correlations estimated by an effect-size model. Mean differences across the 19 groups were the main factor determining the magnitude and sign of the pooled coefficients, which showed largest values of bias as they approached ±1. Only heteroskedasticity across the pool of 19 groups resulted in less efficient estimations of correlations than did a classical meta-analysis approach of combining correlation coefficients. These results were corroborated by simulation studies involving either mean differences or heteroskedasticity across a pool of N \u3e 2 groups. Conclusions The combination of statistical results is best suited for synthesizing the correlation between expression profiles of a gene pair across several microarray studies

Comparative Genomic Analysis of Human Fungal Pathogens Causing Paracoccidioidomycosis

Paracoccidioides is a fungal pathogen and the cause of paracoccidioidomycosis, a health-threatening human systemic mycosis endemic to Latin America. Infection by Paracoccidioides, a dimorphic fungus in the order Onygenales, is coupled with a thermally regulated transition from a soil-dwelling filamentous form to a yeast-like pathogenic form. To better understand the genetic basis of growth and pathogenicity in Paracoccidioides, we sequenced the genomes of two strains of Paracoccidioides brasiliensis (Pb03 and Pb18) and one strain of Paracoccidioides lutzii (Pb01). These genomes range in size from 29.1 Mb to 32.9 Mb and encode 7,610 to 8,130 genes. To enable genetic studies, we mapped 94% of the P. brasiliensis Pb18 assembly onto five chromosomes. We characterized gene family content across Onygenales and related fungi, and within Paracoccidioides we found expansions of the fungal-specific kinase family FunK1. Additionally, the Onygenales have lost many genes involved in carbohydrate metabolism and fewer genes involved in protein metabolism, resulting in a higher ratio of proteases to carbohydrate active enzymes in the Onygenales than their relatives. To determine if gene content correlated with growth on different substrates, we screened the non-pathogenic onygenale Uncinocarpus reesii, which has orthologs for 91% of Paracoccidioides metabolic genes, for growth on 190 carbon sources. U. reesii showed growth on a limited range of carbohydrates, primarily basic plant sugars and cell wall components; this suggests that Onygenales, including dimorphic fungi, can degrade cellulosic plant material in the soil. In addition, U. reesii grew on gelatin and a wide range of dipeptides and amino acids, indicating a preference for proteinaceous growth substrates over carbohydrates, which may enable these fungi to also degrade animal biomass. These capabilities for degrading plant and animal substrates suggest a duality in lifestyle that could enable pathogenic species of Onygenales to transfer from soil to animal hosts.National Institute of Allergy and Infectious Diseases (U.S.)National Institutes of Health. Department of Health and Human Services (contract HHSN266200400001C)National Institutes of Health. Department of Health and Human Services(contract HHSN2722009000018C)Brazil. National Council for Scientific and Technological Developmen

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Micronutrient deficiencies and plasmodium vivax malaria among children in the Brazilian Amazon

Background: There is a growing body of evidence linking micronutrient deficiencies and malaria incidence arising mostly from P. falciparum endemic areas. We assessed the impact of micronutrient deficiencies on malaria incidence and vice versa in the Brazilian state of Amazonas. Methodology/Principal Findings: We evaluated children <10 years old living in rural communities in the state of Amazonas, Brazil, from May 2010 to May 2011. All children were assessed for sociodemographic, anthropometric and laboratory parameters, including vitamin A, beta-carotene, zinc and iron serum levels at the beginning of the study (May 2010) and one year later (May 2011). Children were followed in between using passive surveillance for detection of symptomatic malaria. Those living in the study area at the completion of the observation period were reassessed for micronutrient levels. Univariate Cox-proportional Hazards models were used to assess whether micronutrient deficiencies had an impact on time to first P. vivax malaria episode. We included 95 children median age 4.8 years (interquartile range [IQR]: 2.3-6.6), mostly males (60.0%) and with high maternal illiteracy (72.6%). Vitamin A deficiencies were found in 36% of children, beta-carotene deficiency in 63%, zinc deficiency in 61% and iron deficiency in 51%. Most children (80%) had at least one intestinal parasite. During follow-up, 16 cases of vivax malaria were diagnosed amongst 13 individuals. Micronutrient deficiencies were not associated with increased malaria incidence: vitamin A deficiency [Hazard ratio (HR): 1.51; P-value: 0.45]; beta-carotene [HR: 0.47; P-value: 0.19]; zinc [HR: 1.41; P-value: 0.57] and iron [HR: 2.31; P-value: 0.16]). Upon reevaluation, children with al least one episode of malaria did not present significant changes in micronutrient levels. Conclusion: Micronutrient serum levels were not associated with a higher malaria incidence nor the malaria episode influenced micronutrient levels. Future studies targeting larger populations to assess micronutrients levels in P. vivax endemic areas are warranted in order to validate these results. © 2016 Benzecry et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

The complete genome sequence of Chromobacterium violaceum reveals remarkable and exploitable bacterial adaptability

Chromobacterium violaceum is one of millions of species of free-living microorganisms that populate the soil and water in the extant areas of tropical biodiversity around the world. Its complete genome sequence reveals (i) extensive alternative pathways for energy generation, (ii) ≈500 ORFs for transport-related proteins, (iii) complex and extensive systems for stress adaptation and motility, and (iv) wide-spread utilization of quorum sensing for control of inducible systems, all of which underpin the versatility and adaptability of the organism. The genome also contains extensive but incomplete arrays of ORFs coding for proteins associated with mammalian pathogenicity, possibly involved in the occasional but often fatal cases of human C. violaceum infection. There is, in addition, a series of previously unknown but important enzymes and secondary metabolites including paraquat-inducible proteins, drug and heavy-metal-resistance proteins, multiple chitinases, and proteins for the detoxification of xenobiotics that may have biotechnological applications

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Kinetic analysis of in vitro production of wild-type Spodoptera frugiperda nucleopolyhedrovirus

In this study, the kinetic behavior of Sf9 and Sf21 cells used in the production of a baculovirus biopesticide to control the pest of corn Spodoptera frugiperda was analyzed. Kinetic variables such as maximum specific growth rate, cell productivity, mean rate of infection, as well as the mean rate of occlusion body production were determined during the infection of these cell-lines with the extracellular virus of the S. frugiperda nucleopolyhedrovirus (SfMNPV). The Sf9 cell-line resulted in better viral production results (5.0 x 10 OB/mL) than the Sf21 cell-line (2.5 x 10 OB/mL)