Phylogenetic Analysis of a Spontaneous Cocoa Bean Fermentation Metagenome Reveals New Insights into Its Bacterial and Fungal Community Diversity

This is the first report on the phylogenetic analysis of the community diversity of a single spontaneous cocoa bean box fermentation sample through a metagenomic approach involving 454 pyrosequencing. Several sequence-based and composition-based taxonomic profiling tools were used and evaluated to avoid software-dependent results and their outcome was validated by comparison with previously obtained culture-dependent and culture-independent data. Overall, this approach revealed a wider bacterial (mainly γ-Proteobacteria) and fungal diversity than previously found. Further, the use of a combination of different classification methods, in a software-independent way, helped to understand the actual composition of the microbial ecosystem under study. In addition, bacteriophage-related sequences were found. The bacterial diversity depended partially on the methods used, as composition-based methods predicted a wider diversity than sequence-based methods, and as classification methods based solely on phylogenetic marker genes predicted a more restricted diversity compared with methods that took all reads into account. The metagenomic sequencing analysis identified Hanseniaspora uvarum, Hanseniaspora opuntiae, Saccharomyces cerevisiae, Lactobacillus fermentum, and Acetobacter pasteurianus as the prevailing species. Also, the presence of occasional members of the cocoa bean fermentation process was revealed (such as Erwinia tasmaniensis, Lactobacillus brevis, Lactobacillus casei, Lactobacillus rhamnosus, Lactococcus lactis, Leuconostoc mesenteroides, and Oenococcus oeni). Furthermore, the sequence reads associated with viral communities were of a restricted diversity, dominated by Myoviridae and Siphoviridae, and reflecting Lactobacillus as the dominant host. To conclude, an accurate overview of all members of a cocoa bean fermentation process sample was revealed, indicating the superiority of metagenomic sequencing over previously used techniques

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Using high angular resolution diffusion imaging data to discriminate cortical regions

Brodmann's 100-year-old summary map has been widely used for cortical localization in neuroscience. There is a pressing need to update this map using non-invasive, high-resolution and reproducible data, in a way that captures individual variability. We demonstrate here that standard HARDI data has sufficiently diverse directional variation among grey matter regions to inform parcellation into distinct functional regions, and that this variation is reproducible across scans. This characterization of the signal variation as non-random and reproducible is the critical condition for successful cortical parcellation using HARDI data. This paper is a first step towards an individual cortex-wide map of grey matter microstructure, The gray/white matter and pial boundaries were identified on the high-resolution structural MRI images. Two HARDI data sets were collected from each individual and aligned with the corresponding structural image. At each vertex point on the surface tessellation, the diffusion-weighted signal was extracted from each image in the HARDI data set at a point, half way between gray/white matter and pial boundaries. We then derived several features of the HARDI profile with respect to the local cortical normal direction, as well as several fully orientationally invariant features. These features were taken as a fingerprint of the underlying grey matter tissue, and used to distinguish separate cortical areas. A support-vector machine classifier, trained on three distinct areas in repeat 1 achieved 80-82% correct classification of the same three areas in the unseen data from repeat 2 in three volunteers. Though gray matter anisotropy has been mostly overlooked hitherto, this approach may eventually form the foundation of a new cortical parcellation method in living humans. Our approach allows for further studies on the consistency of HARDI based parcellation across subjects and comparison with independent microstructural measures such as ex-vivo histology

Interactions between Predation and Resources Shape Zooplankton Population Dynamics

Identifying the relative importance of predation and resources in population dynamics has a long tradition in ecology, while interactions between them have been studied less intensively. In order to disentangle the effects of predation by juvenile fish, algal resource availability and their interactive effects on zooplankton population dynamics, we conducted an enclosure experiment where zooplankton were exposed to a gradient of predation of roach (Rutilus rutilus) at different algal concentrations. We show that zooplankton populations collapse under high predation pressure irrespective of resource availability, confirming that juvenile fish are able to severely reduce zooplankton prey when occurring in high densities. At lower predation pressure, however, the effect of predation depended on algal resource availability since high algal resource supply buffered against predation. Hence, we suggest that interactions between mass-hatching of fish, and the strong fluctuations in algal resources in spring have the potential to regulate zooplankton population dynamics. In a broader perspective, increasing spring temperatures due to global warming will most likely affect the timing of these processes and have consequences for the spring and summer zooplankton dynamics

Global transcriptional response to mammalian temperature provides new insight into Francisella tularensis pathogenesis

<p>Abstract</p> <p>Background</p> <p>After infecting a mammalian host, the facultative intracellular bacterium, <it>Francisella tularensis</it>, encounters an elevated environmental temperature. We hypothesized that this temperature change may regulate genes essential for infection.</p> <p>Results</p> <p>Microarray analysis of <it>F. tularensis </it>LVS shifted from 26°C (environmental) to 37°C (mammalian) showed ~11% of this bacterium's genes were differentially-regulated. Importantly, 40% of the protein-coding genes that were induced at 37°C have been previously implicated in virulence or intracellular growth of <it>Francisella </it>in other studies, associating the bacterial response to this temperature shift with pathogenesis. Forty-four percent of the genes induced at 37°C encode proteins of unknown function, suggesting novel <it>Francisella </it>virulence traits are regulated by mammalian temperature. To explore this possibility, we generated two mutants of loci induced at 37°C [FTL_1581 and FTL_1664 (<it>deoB</it>)]. The FTL_1581 mutant was attenuated in a chicken embryo infection model, which was likely attributable to a defect in survival within macrophages. FTL_1581 encodes a novel hypothetical protein that we suggest naming <it>t</it>emperature-<it>i</it>nduced, <it>v</it>irulence-associated locus <it>A</it>, <it>tivA</it>. Interestingly, the <it>deoB </it>mutant showed diminished entry into mammalian cells compared to wild-type LVS, including primary human macrophages and dendritic cells, the macrophage-like RAW 264.7 line, and non-phagocytic HEK-293 cells. This is the first study identifying a <it>Francisella </it>gene that contributes to uptake into both phagocytic and non-phagocytic host cells.</p> <p>Conclusion</p> <p>Our results provide new insight into mechanisms of <it>Francisella </it>virulence regulation and pathogenesis. <it>F. tularensis </it>LVS undergoes considerable gene expression changes in response to mammalian body temperature. This temperature shift is important for the regulation of genes that are critical for the pathogenesis of <it>Francisella</it>. Importantly, the compilation of temperature-regulated genes also defines a rich collection of novel candidate virulence determinants, including <it>tivA </it>(FTL_1581). An analysis of <it>tivA </it>and <it>deoB </it>(FTL_1664) revealed that these genes contribute to intracellular survival and entry into mammalian cells, respectively.</p

A multiple myeloma classification system that associates normal B-cell subset phenotypes with prognosis.

Despite the recent progress in treatment of multiple myeloma (MM), it is still an incurable malignant disease, and we are therefore in need of new risk stratification tools that can help us to understand the disease and optimize therapy. Here we propose a new subtyping of myeloma plasma cells (PCs) from diagnostic samples, assigned by normal B-cell subset associated gene signatures (BAGS). For this purpose, we combined fluorescence-activated cell sorting and gene expression profiles from normal bone marrow (BM) Pre-BI, Pre-BII, immature, naïve, memory, and PC subsets to generate BAGS for assignment of normal BM subtypes in diagnostic samples. The impact of the subtypes was analyzed in 8 available data sets from 1772 patients' myeloma PC samples. The resulting tumor assignments in available clinical data sets exhibited similar BAGS subtype frequencies in 4 cohorts from de novo MM patients across 1296 individual cases. The BAGS subtypes were significantly associated with progression-free and overall survival in a meta-analysis of 916 patients from 3 prospective clinical trials. The major impact was observed within the Pre-BII and memory subtypes, which had a significantly inferior prognosis compared with other subtypes. A multiple Cox proportional hazard analysis documented that BAGS subtypes added significant, independent prognostic information to the translocations and cyclin D classification. BAGS subtype analysis of patient cases identified transcriptional differences, including a number of differentially spliced genes. We identified subtype differences in myeloma at diagnosis, with prognostic impact and predictive potential, supporting an acquired B-cell trait and phenotypic plasticity as a pathogenetic hallmark of MM

The interaction of bacterial pathogens with platelets.

In recent years, the frequency of serious cardiovascular infections such as endocarditis has increased, particularly in association with nosocomially acquired antibiotic-resistant pathogens. Growing evidence suggests a crucial role for the interaction of bacteria with human platelets in the pathogenesis of cardiovascular infections. Here, we review the nature of the interactions between platelets and bacteria, and the role of these interactions in the pathogenesis of endocarditis and other cardiovascular diseases

Studying neuroanatomy using MRI

The study of neuroanatomy using imaging enables key insights into how our brains function, are shaped by genes and environment, and change with development, aging, and disease. Developments in MRI acquisition, image processing, and data modelling have been key to these advances. However, MRI provides an indirect measurement of the biological signals we aim to investigate. Thus, artifacts and key questions of correct interpretation can confound the readouts provided by anatomical MRI. In this review we provide an overview of the methods for measuring macro- and mesoscopic structure and inferring microstructural properties; we also describe key artefacts and confounds that can lead to incorrect conclusions. Ultimately, we believe that, though methods need to improve and caution is required in its interpretation, structural MRI continues to have great promise in furthering our understanding of how the brain works