Multi-utility Learning: Structured-output Learning with Multiple Annotation-specific Loss Functions

Structured-output learning is a challenging problem; particularly so because of the difficulty in obtaining large datasets of fully labelled instances for training. In this paper we try to overcome this difficulty by presenting a multi-utility learning framework for structured prediction that can learn from training instances with different forms of supervision. We propose a unified technique for inferring the loss functions most suitable for quantifying the consistency of solutions with the given weak annotation. We demonstrate the effectiveness of our framework on the challenging semantic image segmentation problem for which a wide variety of annotations can be used. For instance, the popular training datasets for semantic segmentation are composed of images with hard-to-generate full pixel labellings, as well as images with easy-to-obtain weak annotations, such as bounding boxes around objects, or image-level labels that specify which object categories are present in an image. Experimental evaluation shows that the use of annotation-specific loss functions dramatically improves segmentation accuracy compared to the baseline system where only one type of weak annotation is used

Metatranscriptomics reveal differences in in situ energy and nitrogen metabolism among hydrothermal vent snail symbionts

Despite the ubiquity of chemoautotrophic symbioses at hydrothermal vents, our understanding of the influence of environmental chemistry on symbiont metabolism is limited. Transcriptomic analyses are useful for linking physiological poise to environmental conditions, but recovering samples from the deep sea is challenging, as the long recovery times can change expression profiles before preservation. Here, we present a novel, in situ RNA sampling and preservation device, which we used to compare the symbiont metatranscriptomes associated with Alviniconcha, a genus of vent snail, in which specific host–symbiont combinations are predictably distributed across a regional geochemical gradient. Metatranscriptomes of these symbionts reveal key differences in energy and nitrogen metabolism relating to both environmental chemistry (that is, the relative expression of genes) and symbiont phylogeny (that is, the specific pathways employed). Unexpectedly, dramatic differences in expression of transposases and flagellar genes suggest that different symbiont types may also have distinct life histories. These data further our understanding of these symbionts’ metabolic capabilities and their expression in situ, and suggest an important role for symbionts in mediating their hosts’ interaction with regional-scale differences in geochemistry.National Science Foundation (U.S.) (OCE-0732369)National Science Foundation (U.S.) (GRF grant no. DGE-1144152)Gordon and Betty Moore Foundation (Investigator)Agouron Institut

A Preliminary Note on Some Nutritional Requirements for Reproduction in Female Aedes Aegypti

Author Institution: Department of Zoology and Entomology, The Ohio State University, Columbus 1

Nuclear Export of the Oncoprotein v-ErbA Is Mediated by Acquisition of a Viral Nuclear Export Sequence

v-ErbA, an oncogenic derivative of the thyroid hormone receptor α (TRα) carried by the avian erythroblastosis virus, contains several alterations including fusion of a portion of avian erythroblastosis virus Gag to its N terminus, N- and C-terminal deletions, and 13 amino acid substitutions. Nuclear export of v-ErbA occurs through a CRM1-mediated pathway. In contrast, nuclear export of TRα and another isoform, TRβ, is CRM1-independent. To determine which amino acid changes in v-ErbA confer CRM1-dependent nuclear export, we expressed a panel of green and yellow fluorescent protein-tagged mutant and chimeric proteins in mammalian cells. The sensitivity of subcellular trafficking of these mutants to leptomycin B (LMB), a specific inhibitor of CRM1, was assessed by fluorescence microscopy. Our data showed that a nuclear export sequence resides within a 70-amino acid domain in the C-terminal portion of the p10 region of Gag, and in vitro binding assays demonstrated that Gag interacts directly with CRM1. However, a panel of ligand-binding domain mutants of v-ErbA lacking the Gag sequence exhibited greater nuclear localization in the presence of LMB, suggesting that the various amino acid substitutions/deletions may cause a conformation shift, unmasking an additional CRM1-dependent nuclear export sequence. In contrast, the altered DNA-binding domain of the oncoprotein did not contribute to CRM1-dependent nuclear export. Heterokaryon experiments revealed that v-ErbA did not undergo nucleocytoplasmic shuttling when the CRM1 export pathway was blocked by LMB treatment, suggesting that the ability to follow the export pathway used by TRα has been lost by the oncoprotein during its evolution. Our findings thus point to the intriguing possibility that acquisition of altered nuclear export capabilities contributes to the oncogenic properties of v-ErbA

Community transcriptomics reveals universal patterns of protein sequence conservation in natural microbial communities

Background Combined metagenomic and metatranscriptomic datasets make it possible to study the molecular evolution of diverse microbial species recovered from their native habitats. The link between gene expression level and sequence conservation was examined using shotgun pyrosequencing of microbial community DNA and RNA from diverse marine environments, and from forest soil. Results Across all samples, expressed genes with transcripts in the RNA sample were significantly more conserved than non-expressed gene sets relative to best matches in reference databases. This discrepancy, observed for many diverse individual genomes and across entire communities, coincided with a shift in amino acid usage between these gene fractions. Expressed genes trended toward GC-enriched amino acids, consistent with a hypothesis of higher levels of functional constraint in this gene pool. Highly expressed genes were significantly more likely to fall within an orthologous gene set shared between closely related taxa (core genes). However, non-core genes, when expressed above the level of detection, were, on average, significantly more highly expressed than core genes based on transcript abundance normalized to gene abundance. Finally, expressed genes showed broad similarities in function across samples, being relatively enriched in genes of energy metabolism and underrepresented by genes of cell growth. Conclusions These patterns support the hypothesis, predicated on studies of model organisms, that gene expression level is a primary correlate of evolutionary rate across diverse microbial taxa from natural environments. Despite their complexity, meta-omic datasets can reveal broad evolutionary patterns across taxonomically, functionally, and environmentally diverse communities.Gordon and Betty Moore FoundationAgouron InstituteNational Science Foundation (U.S.)Center for Microbial Oceanography: Research and Educatio

Individual phenotypic variation reduces interaction strengths in a consumer–resource system

Natural populations often show variation in traits that can affect the strength of interspecific interactions. Interaction strengths in turn influence the fate of pairwise interacting populations and the stability of food webs. Understanding the mechanisms relating individual phenotypic variation to interaction strengths is thus central to assess how trait variation affects population and community dynamics. We incorporated nonheritable variation in attack rates and handling times into a classical consumer–resource model to investigate how variation may alter interaction strengths, population dynamics, species persistence, and invasiveness. We found that individual variation influences species persistence through its effect on interaction strengths. In many scenarios, interaction strengths decrease with variation, which in turn affects species coexistence and stability. Because environmental change alters the direction and strength of selection acting upon phenotypic traits, our results have implications for species coexistence in a context of habitat fragmentation, climate change, and the arrival of exotic species to native ecosystems

Diverse syntrophic partnerships from deep-sea methane vents revealed by direct cell capture and metagenomics

Microorganisms play a fundamental role in the cycling of nutrients and energy on our planet. A common strategy for many microorganisms mediating biogeochemical cycles in anoxic environments is syntrophy, frequently necessitating close spatial proximity between microbial partners. We are only now beginning to fully appreciate the diversity and pervasiveness of microbial partnerships in nature, the majority of which cannot be replicated in the laboratory. One notable example of such cooperation is the interspecies association between anaerobic methane oxidizing archaea (ANME) and sulfate-reducing bacteria. These consortia are globally distributed in the environment and provide a significant sink for methane by substantially reducing the export of this potent greenhouse gas into the atmosphere. The interdependence of these currently uncultured microbes renders them difficult to study, and our knowledge of their physiological capabilities in nature is limited. Here, we have developed a method to capture select microorganisms directly from the environment, using combined fluorescence in situ hybridization and immunomagnetic cell capture. We used this method to purify syntrophic anaerobic methane oxidizing ANME-2c archaea and physically associated microorganisms directly from deep-sea marine sediment. Metagenomics, PCR, and microscopy of these purified consortia revealed unexpected diversity of associated bacteria, including Betaproteobacteria and a second sulfate-reducing Deltaproteobacterial partner. The detection of nitrogenase genes within the metagenome and subsequent demonstration of 15N2 incorporation in the biomass of these methane-oxidizing consortia suggest a possible role in new nitrogen inputs by these syntrophic assemblages

Improving Global Multi-target Tracking with Local Updates

Conference dates: September 6-7 & 12, 2014We propose a scheme to explicitly detect and resolve ambiguous situations in multiple target tracking. During periods of uncertainty, our method applies multiple local single target trackers to hypothesise short term tracks. These tracks are combined with the tracks obtained by a global multi-target tracker, if they result in a reduction in the global cost function. Since tracking failures typically arise when targets become occluded, we propose a local data association scheme to maintain the target identities in these situations. We demonstrate a reduction of up to 50% in the global cost function, which in turn leads to superior performance on several challenging benchmark sequences. Additionally, we show tracking results in sports videos where poor video quality and frequent and severe occlusions between multiple players pose difficulties for state-of-the-art trackers.Anton Milan, Rikke Gade, Anthony Dick, Thomas B. Moeslund, and Ian Rei

The combined effects of reactant kinetics and enzyme stability explain the temperature dependence of metabolic rates

A mechanistic understanding of the response of metabolic rate to temperature is essential for understanding thermal ecology and metabolic adaptation. Although the Arrhenius equation has been used to describe the effects of temperature on reaction rates and metabolic traits, it does not adequately describe two aspects of the thermal performance curve (TPC) for metabolic rate—that metabolic rate is a unimodal function of temperature often with maximal values in the biologically relevant temperature range and that activation energies are temperature dependent. We show that the temperature dependence of metabolic rate in ectotherms is well described by an enzyme-assisted Arrhenius (EAAR) model that accounts for the temperature-dependent contribution of enzymes to decreasing the activation energy required for reactions to occur. The model is mechanistically derived using the thermodynamic rules that govern protein stability. We contrast our model with other unimodal functions that also can be used to describe the temperature dependence of metabolic rate to show how the EAAR model provides an important advance over previous work. We fit the EAAR model to metabolic rate data for a variety of taxa to demonstrate the model’s utility in describing metabolic rate TPCs while revealing significant differences in thermodynamic properties across species and acclimation temperatures. Our model advances our ability to understand the metabolic and ecological consequences of increases in the mean and variance of temperature associated with global climate change. In addition, the model suggests avenues by which organisms can acclimate and adapt to changing thermal environments. Furthermore, the parameters in the EAAR model generate links between organismal level performance and underlying molecular processes that can be tested for in future work