The exception to the rule: retreating ice front makes Bewick's swans Cygnus columbianus bewickii migrate slower in spring than in autumn

In the vast majority of migratory bird species studied so far, spring migration has been found to proceed faster than autumn migration. In spring, selection pressures for rapid migration are purportedly higher, and migratory conditions such as food supply, daylength, and/or wind support may be better than in autumn. In swans, however, spring migration appears to be slower than autumn migration. Based on a comparison of tundra swan Cygnus columbianus tracking data with long‐term temperature data from wheather stations, it has previously been suggested that this was due to a capital breeding strategy (gathering resources for breeding during spring migration) and/or to ice cover constraining spring but not autumn migration. Here we directly test the hypothesis that Bewick's swans Cygnus columbianus bewickii follow the ice front in spring, but not in autumn, by comparing three years of GPS tracking data from individual swans with concurrent ice cover data at five important migratory stop‐over sites. In general, ice constrained the swans in the middle part of spring migration, but not in the first (no ice cover was present in the first part) nor in the last part. In autumn, the swans migrated far ahead of ice formation, possibly in order to prevent being trapped by an early onset of winter. We conclude that spring migration in swans is slower than autumn migration because spring migration speed is constrained by ice cover. This restriction to spring migration speed may be more common in northerly migrating birds that rely on freshwater resources.     

Diversity of dechlorination pathways and organohalide respiring bacteria in chlorobenzene dechlorinating enrichment cultures originating from river sludge

Anaerobic reductive dechlorination of hexachlorobenzene (HCB) and three isomers of tetrachlorobenzene (TeCB) (1,2,3,4-, 1,2,3,5- and 1,2,4,5-TeCB) was investigated in microcosms containing chloroaromatic contaminated river sediment. All chlorobenzenes were dechlorinated to dichlorobenzene (DCB) or monochlorobenzene. From the sediment, a methanogenic sediment-free culture was obtained which dechlorinated HCB, pentachlorobenzene, three TeCB isomers, three trichlorobenzene (TCB) isomers (1,2,3-, 1,2,4- and 1,3,5-TCB) and 1,2-DCB. Dechlorination involved multiple pathways including the removal of doubly flanked, singly flanked and isolated chlorine substituents. 454-pyrosequencing of partial bacterial 16S rRNA genes amplified from selected chlorobenzene dechlorinating sediment-free enrichment cultures revealed the presence of a variety of bacterial species, including Dehalobacter and Dehalococcoides mccartyi, that were previously documented as organohalide respiring bacteria. A genus with apparent close relationship to Desulfitobacterium that also has been associated with organohalide respiration, composed the major fraction of the operational taxonomic units (OTUs). Another major OTU was linked with Sedimentibacter sp., a genus that was previously identified in strict co-cultures of consortia reductively dehalogenating chlorinated compounds. Our data point towards the existence of multiple interactions within highly chlorinated benzene dechlorinating communities.     

A new species of Trichieurina (Diptera,Chloropidae) with a key to the world species of the genus

Trichieurina haladai sp. n. (Diptera, Chloropidae), is described from Zambia. All known Trichieurina species are keyed and main differential characters are illustrated.     

Characterization of two homologous 2′-O-methyltransferases showing different specificities for their tRNA substrates

The 2′-O-methylation of the nucleoside at position 32 of tRNA is found in organisms belonging to the three domains of life. Unrelated enzymes catalyzing this modification in Bacteria (TrmJ) and Eukarya (Trm7) have already been identified, but until now, no information is available for the archaeal enzyme. In this work we have identified the methyltransferase of the archaeon Sulfolobus acidocaldarius responsible for the 2′-O-methylation at position 32. This enzyme is a homolog of the bacterial TrmJ. Remarkably, both enzymes have different specificities for the nature of the nucleoside at position 32. While the four canonical nucleosides are substrates of the Escherichia coli enzyme, the archaeal TrmJ can only methylate the ribose of a cytidine. Moreover, the two enzymes recognize their tRNA substrates in a different way. We have solved the crystal structure of the catalytic domain of both enzymes to gain better understanding of these differences at a molecular level.     

Plant–community responses to shrub cover in a páramo grassland released from grazing and burning

Shrub encroachment can follow grazing or burning release in páramo grasslands. While encroachment decreases herbaceous species richness in some grassland systems, the effects of this process on the herbaceous community in páramo grasslands are currently unknown. We collected data on shrub cover, herbaceous‐species cover and species composition in a páramo grassland 12 years after release from burning and cattle grazing near Zuleta, Ecuador. Topographic and soil measures were also included as predictor variables of differences in community composition. Contrary to studies in other systems, shrub cover did not have a significant effect on herbaceous‐species richness, whereas shrub‐species richness significantly increased with shrub cover. However, shrub cover was associated with significant shifts in herbaceous–community composition. Most notably, there was an increase in some shade‐tolerant forbs and tall‐statured wetland grasses with increasing shrub cover, and a corresponding decrease in some short‐statured grasses and early successional forbs. These results could indicate that the ameliorative effects of shrubs (e.g. frost and wind protection) in harsh alpine environments may partially compensate for the expected competitive effect of shrubs due to shading.     

Impact of variance components on reliability of absolute quantification using digital PCR

Background

Digital polymerase chain reaction (dPCR) is an increasingly popular technology for detecting and quantifying target nucleic acids. Its advertised strength is high precision absolute quantification without needing reference curves. The standard data analytic approach follows a seemingly straightforward theoretical framework but ignores sources of variation in the data generating process. These stem from both technical and biological factors, where we distinguish features that are 1) hard-wired in the equipment, 2) user-dependent and 3) provided by manufacturers but may be adapted by the user. The impact of the corresponding variance components on the accuracy and precision of target concentration estimators presented in the literature is studied through simulation.

Results

We reveal how system-specific technical factors influence accuracy as well as precision of concentration estimates. We find that a well-chosen sample dilution level and modifiable settings such as the fluorescence cut-off for target copy detection have a substantial impact on reliability and can be adapted to the sample analysed in ways that matter. User-dependent technical variation, including pipette inaccuracy and specific sources of sample heterogeneity, leads to a steep increase in uncertainty of estimated concentrations. Users can discover this through replicate experiments and derived variance estimation. Finally, the detection performance can be improved by optimizing the fluorescence intensity cut point as suboptimal thresholds reduce the accuracy of concentration estimates considerably.

Conclusions

Like any other technology, dPCR is subject to variation induced by natural perturbations, systematic settings as well as user-dependent protocols. Corresponding uncertainty may be controlled with an adapted experimental design. Our findings point to modifiable key sources of uncertainty that form an important starting point for the development of guidelines on dPCR design and data analysis with correct precision bounds. Besides clever choices of sample dilution levels, experiment-specific tuning of machine settings can greatly improve results. Well-chosen data-driven fluorescence intensity thresholds in particular result in major improvements in target presence detection. We call on manufacturers to provide sufficiently detailed output data that allows users to maximize the potential of the method in their setting and obtain high precision and accuracy for their experiments.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-283) contains supplementary material, which is available to authorized users.     

Predicting breast cancer using an expression values weighted clinical classifier

Background

Clinical data, such as patient history, laboratory analysis, ultrasound parameters-which are the basis of day-to-day clinical decision support-are often used to guide the clinical management of cancer in the presence of microarray data. Several data fusion techniques are available to integrate genomics or proteomics data, but only a few studies have created a single prediction model using both gene expression and clinical data. These studies often remain inconclusive regarding an obtained improvement in prediction performance. To improve clinical management, these data should be fully exploited. This requires efficient algorithms to integrate these data sets and design a final classifier.LS-SVM classifiers and generalized eigenvalue/singular value decompositions are successfully used in many bioinformatics applications for prediction tasks. While bringing up the benefits of these two techniques, we propose a machine learning approach, a weighted LS-SVM classifier to integrate two data sources: microarray and clinical parameters.

Results

We compared and evaluated the proposed methods on five breast cancer case studies. Compared to LS-SVM classifier on individual data sets, generalized eigenvalue decomposition (GEVD) and kernel GEVD, the proposed weighted LS-SVM classifier offers good prediction performance, in terms of test area under ROC Curve (AUC), on all breast cancer case studies.

Conclusions

Thus a clinical classifier weighted with microarray data set results in significantly improved diagnosis, prognosis and prediction responses to therapy. The proposed model has been shown as a promising mathematical framework in both data fusion and non-linear classification problems.     

Genome-wide association and biological pathway analysis for milk-fat composition in Danish Holstein and Danish Jersey cattle

Background

The milk fat profile of the Danish Holstein (DH) and Danish Jersey (DJ) show clear differences. Identification of the genomic regions, genes and biological pathways underlying the milk fat biosynthesis will improve the understanding of the biology underlying bovine milk fat production and may provide new possibilities to change the milk fat composition by selective breeding. In this study a genome wide association scan (GWAS) in the DH and DJ was performed for a detailed milk fatty acid (FA) profile using the HD bovine SNP array and subsequently a biological pathway analysis based on the SNP data was performed.

Results

The GWAS identified in total 1,233 SNPs (FDR < 0.10) spread over 18 chromosomes for nine different FA traits for the DH breed and 1,122 SNPs (FDR < 0.10) spread over 26 chromosomes for 13 different FA traits were detected for the DJ breed. Of these significant SNPs, 108 SNP markers were significant in both DH and DJ (C14-index, BTA26; C16, BTA14; fat percentage (FP), BTA14). This was supported by an enrichment test. The QTL on BTA14 and BTA26 represented the known candidate genes DGAT and SCD. In addition we suggest ACSS3 to be a good candidate gene for the QTL on BTA5 for C10:0 and C15:0. In addition, genetic correlations between the FA traits within breed showed large similarity across breeds. Furthermore, the biological pathway analysis revealed that fat digestion and absorption (KEGG04975) plays a role for the traits FP, C14:1, C16 index and C16:1.

Conclusion

There was a clear similarity between the underlying genetics of FA in the milk between DH and DJ. This was supported by the fact that there was substantial overlap between SNPs for FP, C14 index, C14:1, C16 index and C16:1. In addition genetic correlations between FA showed a similar pattern across DH and DJ. Furthermore the biological pathway analysis suggested that fat digestion and absorption KEGG04975 is important for the traits FP, C14:1, C16 index and C16:1.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1112) contains supplementary material, which is available to authorized users.     

Environmental Stress Affects the Activity of Metabolic and Growth Factor Signaling Networks and Induces Autophagy Markers in MCF7 Breast Cancer Cells

Phosphoproteomic techniques are contributing to our understanding of how signaling pathways interact and regulate biological processes. This technology is also being used to characterize how signaling networks are remodeled during disease progression and to identify biomarkers of signaling pathway activity and of responses to cancer therapy. A potential caveat in these studies is that phosphorylation is a very dynamic modification that can substantially change during the course of an experiment or the retrieval and processing of cellular samples. Here, we investigated how exposure of cells to ambient conditions modulates phosphorylation and signaling pathway activity in the MCF7 breast cancer cell line. About 1.5% of 3,500 sites measured showed a significant change in phosphorylation extent upon exposure of cells to ambient conditions for 15 min. The effects of this perturbation in modifying phosphorylation patterns did not involve random changes due to stochastic activation of kinases and phosphatases. Instead, exposure of cells to ambient conditions elicited an environmental stress reaction that involved a coordinated response to a metabolic stress situation, which included: (1) the activation of AMPK; (2) the inhibition of PI3K, AKT, and ERK; (3) an increase in markers of protein synthesis inhibition at the level of translation elongation; and (4) an increase in autophagy markers. We also observed that maintaining cells in ice modified but did not completely abolish this metabolic stress response. In summary, exposure of cells to ambient conditions affects the activity of signaling networks previously implicated in metabolic and growth factor signaling. Mass spectrometry data have been deposited to the ProteomeXchange with identifier PXD000472.Phosphorylation is a posttranslational modification involving the addition of phosphate groups to serine, threonine and tyrosine residues on target proteins. This modification, regulated by kinases and phosphatases that phosphorylate and dephosphorylate these amino acids respectively, controls many aspects of protein biochemistry including stability, localization, ability to interact with other molecules and enzymatic activity (1, 2). In addition to playing a pivotal role in regulating most biological processes, alterations in biochemical pathways regulated by protein phosphorylation contribute to the pathophysiology of various diseases including cancer, diabetes and neurodegeneration (2–6).In recent years the development of MS techniques has allowed the study of protein phosphorylation on an untargeted and global scale. As a consequence, signaling processes can now be studied with unprecedented depth and coverage (7–10). Phosphoproteomics has also been applied to investigate how signaling networks are modulated during disease progression and for the identification of biomarkers that classify patients according to prognosis or treatment response (11–15). A potential caveat in the interpretation of such experiments is that protein phosphorylation is a dynamic modification that can be affected by variables difficult to control including cell confluence, circadian rhythms, shear stress and other types of environmental stresses including exposure to ambient conditions (16–22). Thus, during the course of an experiment variations or delays in sample retrieval and processing can potentially alter the quantitative characteristics of the phosphoproteome (17, 18, 22). Similar problems could in principle occur in a clinical environment where several hours may elapse from patient sample collection to processing or preservation (16, 17, 23). Delays because of ethical and practical considerations may also affect collection and preservation of post-mortem samples (24, 25). As a consequence, it can in principle be introduced variability and artifacts that may potentially confound the interpretation of data obtained from large-scale as well as targeted phosphoproteomics experiments (16).To our knowledge, there are no reports that systematically evaluate, in an untargeted manner, how exposure to environmental stress modulates the phosphoproteome of human cells in culture. Here, we used the MCF7 breast cancer cell line to investigate how ambient conditions alter phosphorylation and to evaluate signaling pathways that may be modulated by environmental stress. We found several phosphorylation events that increased or decreased after 15 min exposure of cells to ambient conditions at room temperature (RT)¹. We then studied whether these changes in phosphorylation were a random effect due to stochastic inactivation of kinases and phosphatases or whether these were the consequence of actual responses involving specific signaling pathways. Our data indicate that the phosphorylations regulated by environmental conditions at RT are the initial steps of a complex adaptive response to a metabolic stress. Data supporting these conclusions include the observation that ambient conditions at RT activated catabolic pathways regulated by AMPK and GSK3β and inactivated anabolic pathways involving the AKT, ERK and mTOR signaling nodes. When we compared the responses to ambient conditions at RT or on ice, we found that maintaining cells on ice induced a different adaptive response rather than an attenuated one. We also found that the adaptation response to ambient conditions at RT triggered a functional biological process that involved the initiation of macroautophagy (hereafter referred as autophagy) and the activation of a pathway known to inhibit protein synthesis at the level of translation elongation. Thus our study also defines experimental conditions that can be used to study the mechanisms involved in the process of autophagy.     

Metagenomic Survey for Viruses in Western Arctic Caribou,Alaska, through Iterative Assembly of Taxonomic Units

Pathogen surveillance in animals does not provide a sufficient level of vigilance because it is generally confined to surveillance of pathogens with known economic impact in domestic animals and practically nonexistent in wildlife species. As most (re-)emerging viral infections originate from animal sources, it is important to obtain insight into viral pathogens present in the wildlife reservoir from a public health perspective. When monitoring living, free-ranging wildlife for viruses, sample collection can be challenging and availability of nucleic acids isolated from samples is often limited. The development of viral metagenomics platforms allows a more comprehensive inventory of viruses present in wildlife. We report a metagenomic viral survey of the Western Arctic herd of barren ground caribou (Rangifer tarandus granti) in Alaska, USA. The presence of mammalian viruses in eye and nose swabs of 39 free-ranging caribou was investigated by random amplification combined with a metagenomic analysis approach that applied exhaustive iterative assembly of sequencing results to define taxonomic units of each metagenome. Through homology search methods we identified the presence of several mammalian viruses, including different papillomaviruses, a novel parvovirus, polyomavirus, and a virus that potentially represents a member of a novel genus in the family Coronaviridae.