Wedged between bottom-up and top-down processes: aphids on tansy

Abstract. 1. Many species of aphids exploit a single host‐plant species and have to cope with changing environmental conditions. They often vary greatly in abundance even when feeding on the same host. In a field experiment, the bottom‐up (plant quality/patch type frequency) and top‐down (ant attendance/predation) effects on the abundance of four species of aphids feeding on tansy (Tanacetum vulgare) were tested using a full factorial design. In addition, a model was used to examine these patch characteristics for their relative effects on the population dynamics and abundance of different aphid species. 2. Aphid numbers changed significantly depending on the quality of the host plant and the presence/absence of attending ants. The obligate myrmecophile, Metopeurum fuscoviride, was abundant on high‐quality plants, while on poor quality plants or on plants without attending ants these aphids did not survive until the end of the experiment. The facultative myrmecophiles, Aphis fabae and Brachycaudus cardui, and the unattended aphid species, Macrosiphoniella tanacetaria, all reached similar peak population densities, but M. tanacetaria did best in poor quality patches. 3. Natural enemies reduced aphid numbers, but those species feeding on high‐quality plants survived longer than those on poor‐quality plants, which existed only for a short period of time, especially when associated with ants. Losses due to migration of winged morphs and mortality caused by parasitoids were insignificant. 4. Varying the frequency of different patch types in a model indicates that different degrees of associations with ants are favoured in different environments. If the proportion of high‐quality patches in a habitat is large, obligate myrmecophiles do best. On increasing the number of poor‐quality patches, unattended species become more abundant. 5. The results suggest that, in spite of large species specific differences in growth rates, degree of myrmecophily or life cycle features, the temporal and spatial variability in top‐down and bottom‐up forces differentially affects aphid species and allows the simultaneous exploitation of a shared host‐plant species.     

Biological Markers of Auditory Gap Detection in Young,Middle-Aged,and Older Adults

The capability of processing rapid fluctuations in the temporal envelope of sound declines with age and this contributes to older adults'' difficulties in understanding speech. Although, changes in central auditory processing during aging have been proposed as cause for communication deficits, an open question remains which stage of processing is mostly affected by age related changes. We investigated auditory temporal resolution in young, middle-aged, and older listeners with neuromagnetic evoked responses to gap stimuli with different leading marker and gap durations. Signal components specific for processing the physical details of sound stimuli as well as the auditory objects as a whole were derived from the evoked activity and served as biological markers for temporal processing at different cortical levels. Early oscillatory 40-Hz responses were elicited by the onsets of leading and lagging markers and indicated central registration of the gap with similar amplitude in all three age groups. High-gamma responses were predominantly related to the duration of no-gap stimuli or to the duration of gaps when present, and decreased in amplitude and phase locking with increasing age. Correspondingly, low-frequency activity around 200 ms and later was reduced in middle aged and older participants. High-gamma band, and long-latency low-frequency responses were interpreted as reflecting higher order processes related to the grouping of sound items into auditory objects and updating of memory for these objects. The observed effects indicate that age-related changes in auditory acuity have more to do with higher-order brain functions than previously thought.     

Oryctes rhinoceros populations and behavior influenced by a baculovirus

Oryctes rhinoceros adults stopped feeding and flew less frequently, and the males mated less often after they became infected with the baculovirus of Oryctes. Monitoring the larval and adult population in Western Samoa over several years gave evidence that the incidence of the virus is dependent on the density of the O. rhinoceros population. Male beetles were more frequently infected than female bettles. Adding more virus-infected beetles to the O. rhinoceros populations of Nukunonu Atoll, where the virus had become established 5 years earlier, reduced the population significantly. The data indicated that the reduction was caused mainly by a decrease in the number of eggs deposited.     

Metabolic systems biology

The first full genome sequences were established in the mid-1990s. Shortly thereafter, genome-scale metabolic network reconstructions appeared. Since that time, we have witnessed an exponential growth in their number and uses. Here I discuss, from a personal point of view, four topics: (1) the placement of metabolic systems biology in the context of broader scientific developments, (2) its foundational concepts, (3) some of its current uses, and (4) some of the expected future developments in the field.     

Tamoxifen and raloxifene modulate gap junction coupling during early phases of retinoic acid-dependent neuronal differentiation of NTera2/D1 cells

Gap junctions (GJ) represent a cellular communication system known to influence neuronal differentiation and survival. To assess a putative role of this system for neural effects of tamoxifen (TAM) and raloxifene (RAL), we used the human teratocarcinoma cell line NTera2/D1, retinoic acid (RA)-dependent neuronal differentiation of which is regulated by gap junctions formed of connexin43 (Cx43). As demonstrated by Western blot analysis, concentrations above 1 μmol/l for TAM, and 0.1 μmol/l for RAL lead to a temporary time- and concentration-dependent increase in Cx43 immunoreactivity, which reached a peak for TAM after 1 day and for RAL after 2 days. Immunocytochemical stainings revealed the increase in Cx43 immunoreactivity to result from an accumulation in intracellular compartments such as the Golgi apparatus or lysosomes. In addition, TAM and RAL were able to prevent the RA-dependent decrease of Cx43 immunoreactivity in NTera2/D1 cells, normally observed during neuronal differentiation. This suggested a suppression of neuronal differentiation to result from these substances. According to this, treatment of NTera2/D1 cells with 10 μmol/l TAM or RAL during weeks 1 and 2 of a 6 weeks RA-driven differentiation schedule impaired, whereas treatment during weeks 5 and 6 did not impair, neuronal differentiation of these cells. Modulation of GJ coupling between NTera2/D1 cells by TAM and RAL seems therefore to perturb early neuronal differentiation, whereas differentiated neurons in the mature brain seem to be not affected. These effects could be of importance for actions of TAM and RAL on early embryonic steps of nervous system formation.     

PhysioSpace: Relating Gene Expression Experiments from Heterogeneous Sources Using Shared Physiological Processes

Relating expression signatures from different sources such as cell lines, in vitro cultures from primary cells and biopsy material is an important task in drug development and translational medicine as well as for tracking of cell fate and disease progression. Especially the comparison of large scale gene expression changes to tissue or cell type specific signatures is of high interest for the tracking of cell fate in (trans-) differentiation experiments and for cancer research, which increasingly focuses on shared processes and the involvement of the microenvironment. These signature relation approaches require robust statistical methods to account for the high biological heterogeneity in clinical data and must cope with small sample sizes in lab experiments and common patterns of co-expression in ubiquitous cellular processes. We describe a novel method, called PhysioSpace, to position dynamics of time series data derived from cellular differentiation and disease progression in a genome-wide expression space. The PhysioSpace is defined by a compendium of publicly available gene expression signatures representing a large set of biological phenotypes. The mapping of gene expression changes onto the PhysioSpace leads to a robust ranking of physiologically relevant signatures, as rigorously evaluated via sample-label permutations. A spherical transformation of the data improves the performance, leading to stable results even in case of small sample sizes. Using PhysioSpace with clinical cancer datasets reveals that such data exhibits large heterogeneity in the number of significant signature associations. This behavior was closely associated with the classification endpoint and cancer type under consideration, indicating shared biological functionalities in disease associated processes. Even though the time series data of cell line differentiation exhibited responses in larger clusters covering several biologically related patterns, top scoring patterns were highly consistent with a priory known biological information and separated from the rest of response patterns.     

A Systems Approach to Predict Oncometabolites via Context-Specific Genome-Scale Metabolic Networks

Altered metabolism in cancer cells has been viewed as a passive response required for a malignant transformation. However, this view has changed through the recently described metabolic oncogenic factors: mutated isocitrate dehydrogenases (IDH), succinate dehydrogenase (SDH), and fumarate hydratase (FH) that produce oncometabolites that competitively inhibit epigenetic regulation. In this study, we demonstrate in silico predictions of oncometabolites that have the potential to dysregulate epigenetic controls in nine types of cancer by incorporating massive scale genetic mutation information (collected from more than 1,700 cancer genomes), expression profiling data, and deploying Recon 2 to reconstruct context-specific genome-scale metabolic models. Our analysis predicted 15 compounds and 24 substructures of potential oncometabolites that could result from the loss-of-function and gain-of-function mutations of metabolic enzymes, respectively. These results suggest a substantial potential for discovering unidentified oncometabolites in various forms of cancers.     

Spatial autocorrelation patterns of stream invertebrates: exogenous and endogenous factors

Aim To investigate spatial autocorrelation of taxonomic stream invertebrate groups (richness and composition) at a large geographical scale and to analyse the importance of exogenous and endogenous factors. Location The Mediterranean Basin. Methods For exogenous factors, we used large‐scale factors related to climate, geology and river zonation; for endogenous factors, we used the dispersal mode of each taxonomic group. After describing and analysing spatial patterns of genus richness and genus composition of stream invertebrate groups in the Mediterranean Basin, we computed Moran’s I before and after accounting for the exogenous factors and related it to the endogenous factors. Results In relation to genus richness, most of the taxonomic groups did not show significant spatial autocorrelation, suggesting that no main large‐scale exogenous or endogenous factors were important and that local‐scale factors were probably controlling taxonomic richness. In contrast, for genus composition, all taxonomic groups except Odonata had significant spatial autocorrelation before accounting for the environment. After accounting for the environment, most taxonomic groups still had a significant spatial autocorrelation, but it decreased with their increasing dispersal ability (from Crustacea to Coleoptera). Thus, spatial taxonomic composition of groups with the strongest dispersal potential is mainly related to exogenous factors, whereas that of groups with weaker dispersal potential is related to a combination of exogenous and endogenous factors. Main conclusions Our results illustrate the importance of dispersal as an endogenous factor causing spatial autocorrelation and suggest that ignoring endogenous factors can lead to misunderstandings when explaining large‐scale community patterns.