Interacting forces of predation and fishing affect species’ maturation size

1. Fishing is a strong selective force and is supposed to select for earlier maturation at smaller body size. However, the extent to which fishing‐induced evolution is shaping ecosystems remains debated. This is in part because it is challenging to disentangle fishing from other selective forces (e.g., size‐structured predation and cannibalism) in complex ecosystems undergoing rapid change.
2. Changes in maturation size from fishing and predation have previously been explored with multi‐species physiologically structured models but assumed separation of ecological and evolutionary timescales. To assess the eco‐evolutionary impact of fishing and predation at the same timescale, we developed a stochastic physiologically size‐structured food‐web model, where new phenotypes are introduced randomly through time enabling dynamic simulation of species'' relative maturation sizes under different types of selection pressures.
3. Using the model, we carried out a fully factorial in silico experiment to assess how maturation size would change in the absence and presence of both fishing and predation (including cannibalism). We carried out ten replicate stochastic simulations exposed to all combinations of fishing and predation in a model community of nine interacting fish species ranging in their maximum sizes from 10 g to 100 kg. We visualized and statistically analyzed the results using linear models.
4. The effects of fishing on maturation size depended on whether or not predation was enabled and differed substantially across species. Fishing consistently reduced the maturation sizes of two largest species whether or not predation was enabled and this decrease was seen even at low fishing intensities (F = 0.2 per year). In contrast, the maturation sizes of the three smallest species evolved to become smaller through time but this happened regardless of the levels of predation or fishing. For the four medium‐size species, the effect of fishing was highly variable with more species showing significant and larger fishing effects in the presence of predation.
5. Ultimately our results suggest that the interactive effects of predation and fishing can have marked effects on species'' maturation sizes, but that, at least for the largest species, predation does not counterbalance the evolutionary effect of fishing. Our model also produced relative maturation sizes that are broadly consistent with empirical estimates for many fish species.

     

Mysterious bio-duck sound attributed to the Antarctic minke whale (Balaenoptera bonaerensis)

For decades, the bio-duck sound has been recorded in the Southern Ocean, but the animal producing it has remained a mystery. Heard mainly during austral winter in the Southern Ocean, this ubiquitous sound has been recorded in Antarctic waters and contemporaneously off the Australian west coast. Here, we present conclusive evidence that the bio-duck sound is produced by Antarctic minke whales (Balaenoptera bonaerensis). We analysed data from multi-sensor acoustic recording tags that included intense bio-duck sounds as well as singular downsweeps that have previously been attributed to this species. This finding allows the interpretation of a wealth of long-term acoustic recordings for this previously acoustically concealed species, which will improve our understanding of the distribution, abundance and behaviour of Antarctic minke whales. This is critical information for a species that inhabits a difficult to access sea-ice environment that is changing rapidly in some regions and has been the subject of contentious lethal sampling efforts and ongoing international legal action.     

The distribution of carbohydrate side chains along the polypeptide chain of glucoamylase

Glucoamylase is a starch-hydrolyzing enzyme with a glycoprotein structure, used industrially for the conversion of starch to glucose, citric acid, corn syrups, and high-fructose sweeteners. This enzyme possesses an unusual type of structure in which many carbohydrate side chains are linked O-glycosidically to serine and threonine residues of the polypeptide chain. The carbohydrate side chains may be single monosaccharide residues or oligosaccharides of mannose, glucose, galactose, and in some cases N-acetylglucosamine. New data from experiments on the CNBr fragmentation of glucoamylase followed by chemical and immunological characterization of the fragments show that the carbohydrate side chains are distributed randomly along the polypeptide chain. Such a structure is appropriately termed a random model reprensentation for the glucoamylase molecule.     

Biological and structural properties of MIP-1 alpha expressed in yeast.

The murine macrophage inflammatory proteins-1 alpha (MIP-1 alpha) and MIP-1 beta are distinct but closely related cytokines. Partially purified mixtures of the two proteins affect neutrophil function and cause local inflammation and fever. The particular properties of MIP-1 alpha have not been well studied, although it has been identified as being identical to an inhibitor of haemopoietic stem cell growth. We have expressed MIP-1 alpha in yeast cells and purified it to sequence homogeneity. Structural analysis of this biologically active material by circular dichroism and fluorescence spectroscopy confirms that MIP-1 alpha has a very similar secondary and tertiary structure to platelet factor 4 and interleukin 8 with which it shares limited sequence homology. The in-vitro stem cell inhibitory properties have been confirmed using a range of murine progenitor cells including purified bone marrow progenitor cells (FACS-1), the FDCP-mix A4 cell line, and spleen colony forming unit (CFU-S) populations. Plateau levels of inhibition of stem cell growth were achieved using concentrations of 0.15 micrograms/ml MIP-1 alpha. We have also demonstrated that MIP-1 alpha is active in vivo: 5 micrograms of MIP-1 alpha per mouse given as a bolus injection, protects stem cells from subsequent in-vitro killing by tritiated thymidine. MIP-1 alpha was also shown to enhance the proliferation of more committed progenitor granulocyte macrophage-colony forming cells (GM-CFC) in response to granulocyte macrophage-colony stimulating factor (GM-CSF).     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.