Confidence Sharing: An Economic Strategy for Efficient Information Flows in Animal Groups

Social animals may share information to obtain a more complete and accurate picture of their surroundings. However, physical constraints on communication limit the flow of information between interacting individuals in a way that can cause an accumulation of errors and deteriorated collective behaviors. Here, we theoretically study a general model of information sharing within animal groups. We take an algorithmic perspective to identify efficient communication schemes that are, nevertheless, economic in terms of communication, memory and individual internal computation. We present a simple and natural algorithm in which each agent compresses all information it has gathered into a single parameter that represents its confidence in its behavior. Confidence is communicated between agents by means of active signaling. We motivate this model by novel and existing empirical evidences for confidence sharing in animal groups. We rigorously show that this algorithm competes extremely well with the best possible algorithm that operates without any computational constraints. We also show that this algorithm is minimal, in the sense that further reduction in communication may significantly reduce performances. Our proofs rely on the Cramér-Rao bound and on our definition of a Fisher Channel Capacity. We use these concepts to quantify information flows within the group which are then used to obtain lower bounds on collective performance. The abstract nature of our model makes it rigorously solvable and its conclusions highly general. Indeed, our results suggest confidence sharing as a central notion in the context of animal communication.     

Hepatic lipase: a member of a family of structurally related lipases

Partial amino acid sequence of rat hepatic lipase was obtained by gas-phase microsequence analysis of proteolytic fragments. Sequence comparison to bovine lipoprotein lipase and porcine pancreatic lipase reveals a highly conserved region existing among these three physiologically distinct lipolytic enzymes. In a stretch of 36 amino acid residues previously reported for pancreatic lipase (De Caro, J., Boudouard, M., Bonicel, J., Guidoni, A., Desnuelle, P. and Rovery, M. (1981) Biochim. Biophys. Acta 671, 129-138), nineteen residues are identical for all three enzymes, whereas 27 of 36 are identical in rat hepatic lipase and bovine lipoprotein lipase. The fact that this primary structural conservation extends to three different animal species emphasizes the conclusion that these lipolytic enzymes comprise a protein family originating from a common ancestral gene.     

A Shared Endoplasmic Reticulum-associated Degradation Pathway Involving the EDEM1 Protein for Glycosylated and Nonglycosylated Proteins

Studies of misfolded protein targeting to endoplasmic reticulum-associated degradation (ERAD) have largely focused on glycoproteins, which include the bulk of the secretory proteins. Mechanisms of targeting of nonglycosylated proteins are less clear. Here, we studied three nonglycosylated proteins and analyzed their use of known glycoprotein quality control and ERAD components. Similar to an established glycosylated ERAD substrate, the uncleaved precursor of asialoglycoprotein receptor H2a, its nonglycosylated mutant, makes use of calnexin, EDEM1, and HRD1, but only glycosylated H2a is a substrate for the cytosolic SCF^Fbs2 E3 ubiquitin ligase with lectin activity. Two nonglycosylated BiP substrates, NS-1κ light chain and truncated Igγ heavy chain, interact with the ERAD complex lectins OS-9 and XTP3-B and require EDEM1 for degradation. EDEM1 associates through a region outside of its mannosidase-like domain with the nonglycosylated proteins. Similar to glycosylated substrates, proteasomal inhibition induced accumulation of the nonglycosylated proteins and ERAD machinery in the endoplasmic reticulum-derived quality control compartment. Our results suggest a shared ERAD pathway for glycosylated and nonglycosylated proteins composed of luminal lectin machinery components also capable of protein-protein interactions.     

Enhanced generation of intraluminal vesicles in neuronal late endosomes in the brain of a Down syndrome mouse model with endosomal dysfunction

Down syndrome (DS) is a human genetic disease caused by trisomy of chromosome 21 and characterized by early developmental brain abnormalities. Dysfunctional endosomal pathway in neurons is an early event of DS and Alzheimer's disease. Recently, we have demonstrated that exosome secretion is upregulated in human DS postmortem brains, in the brain of the trisomic mouse model Ts[Rb(12.17¹⁶)]2Cje (Ts2) and by DS fibroblasts as compared with disomic controls. High levels of the tetraspanin CD63, a regulator of exosome biogenesis, were observed in DS brains. Partially blocking exosome secretion by DS fibroblasts exacerbated a pre‐existing early endosomal pathology. We thus hypothesized that enhanced CD63 expression induces generation of intraluminal vesicles (ILVs) in late endosomes/multivesicular bodies (MVBs), increasing exosome release as an endogenous mechanism to mitigate endosomal abnormalities in DS. Herein, we show a high‐resolution electron microscopy analysis of MVBs in neurons of the frontal cortex of 12‐month‐old Ts2 mice and littermate diploid controls. Our quantitative analysis revealed that Ts2 MVBs are larger, more abundant, and contain a higher number of ILVs per neuron compared to controls. These findings were further corroborated biochemically by Western blot analysis of purified endosomal fractions showing higher levels of ILVs proteins in the same fractions containing endosomal markers in the brain of Ts2 mice compared to controls. These data suggest that upregulation of ILVs production may be a key homeostatic mechanism to alleviate endosomal dysregulation via the endosomal–exosomal pathway.     

Geometric algorithms for the analysis of 2D-electrophoresis gels.

In proteomics, two-dimensional gel electrophoresis (2-DE) is a separation technique for proteins. The resulting protein spots can be identified either by using picking robots and subsequent mass spectrometry or by visual cross inspection of a new gel image with an already analyzed master gel. Difficulties especially arise from inherent noise and irregular geometric distortions in 2-DE images. Aiming at the automated analysis of large series of 2-DE images, or at the even more difficult interlaboratory gel comparisons, the bottleneck is to solve the two most basic algorithmic problems with high quality: Identifying protein spots and computing a matching between two images. For the development of the analysis software CAROl at Freie Universit?t Berlin, we have reconsidered these two problems and obtained new solutions which rely on methods from computational geometry. Their novelties are: 1. Spot detection is also possible for complex regions formed by several "merged" (usually saturated) spots; 2. User-defined landmarks are not necessary for the matching. Furthermore, images for comparison are allowed to represent different parts of the entire protein pattern, which only partially "overlap." The implementation is done in a client server architecture to allow queries via the internet. We also discuss and point at related theoretical questions in computational geometry.     

On the interaction of colicin E3 with the ribosome

Colicin E3 is a protein that kills Escherichia coli cells by a process that involves binding to a surface receptor, entering the cell and inactivating its protein biosynthetic machinery. Colicin E3 kills cells by a catalytic mechanism of a specific ribonucleolytic cleavage in 16S rRNA at the ribosomal decoding A-site between A1493 and G1494 (E. coli numbering system). The breaking of this single phosphodiester bond results in a complete cessation of protein biosynthesis and cell death. The inactive E517Q mutant of the catalytic domain of colicin E3 binds to 30S ribosomal subunits of Thermus thermophilus, as demonstrated by an immunoblotting assay. A model structure of the complex of the ribosomal subunit 30S and colicin E3, obtained via docking, explains the role of the catalytic residues, suggests a catalytic mechanism and provides insight into the specificity of the reaction. Furthermore, the model structure suggests that the inhibitory action of bound immunity is due to charge repulsion of this acidic protein by the negatively charged rRNA backbone     

Prediction of the structure of the complex between the 30S ribosomal subunit and colicin E3 via weighted-geometric docking

Colicin E3 kills Escherichia coli cells by ribonucleolytic cleavage in the 16S rRNA. The cleavage occurs at the ribosomal decoding A-site between nucleotides A1493 and G1494. The breaking of this single phosphodiester bond results in a complete termination of protein biosynthesis leading to cell death. A model structure of the complex of the ribosomal subunit 30S and colicin E3 was constructed by means of a new weighted-geometric docking algorithm, in which interactions involving specified parts of the molecular surface can be up-weighted, allowing incorporation of experimental data in the docking search. Our model, together with available experimental data, predicts the role of the catalytic residues of colicin E3. In addition, it suggests that bound acidic immunity protein inhibits the enzymatic activity of colicin E3 by electrostatic repulsion of the negatively charged substrate.