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.     

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.     

Molecular basis for expression of common and rare fragile sites

Fragile sites are specific loci that form gaps, constrictions, and breaks on chromosomes exposed to partial replication stress and are rearranged in tumors. Fragile sites are classified as rare or common, depending on their induction and frequency within the population. The molecular basis of rare fragile sites is associated with expanded repeats capable of adopting unusual non-B DNA structures that can perturb DNA replication. The molecular basis of common fragile sites was unknown. Fragile sites from R-bands are enriched in flexible sequences relative to nonfragile regions from the same chromosomal bands. Here we cloned FRA7E, a common fragile site mapped to a G-band, and revealed a significant difference between its flexibility and that of nonfragile regions mapped to G-bands, similar to the pattern found in R-bands. Thus, in the entire genome, flexible sequences might play a role in the mechanism of fragility. The flexible sequences are composed of interrupted runs of AT-dinucleotides, which have the potential to form secondary structures and hence can affect replication. These sequences show similarity to the AT-rich minisatellite repeats that underlie the fragility of the rare fragile sites FRA16B and FRA10B. We further demonstrate that the normal alleles of FRA16B and FRA10B span the same genomic regions as the common fragile sites FRA16C and FRA10E. Our results suggest that a shared molecular basis, conferred by sequences with a potential to form secondary structures that can perturb replication, may underlie the fragility of rare fragile sites harboring AT-rich minisatellite repeats and aphidicolin-induced common fragile sites.     

Integrated Microfluidics for Protein Modification Discovery

Protein post-translational modifications mediate dynamic cellular processes with broad implications in human disease pathogenesis. There is a large demand for high-throughput technologies supporting post-translational modifications research, and both mass spectrometry and protein arrays have been successfully utilized for this purpose. Protein arrays override the major limitation of target protein abundance inherently associated with MS analysis. This technology, however, is typically restricted to pre-purified proteins spotted in a fixed composition on chips with limited life-time and functionality. In addition, the chips are expensive and designed for a single use, making complex experiments cost-prohibitive. Combining microfluidics with in situ protein expression from a cDNA microarray addressed these limitations. Based on this approach, we introduce a modular integrated microfluidic platform for multiple post-translational modifications analysis of freshly synthesized protein arrays (IMPA). The system''s potency, specificity and flexibility are demonstrated for tyrosine phosphorylation and ubiquitination in quasicellular environments. Unlimited by design and protein composition, and relying on minute amounts of biological material and cost-effective technology, this unique approach is applicable for a broad range of basic, biomedical and biomarker research.Protein post-translational modifications (PTMs)¹ vastly diversify eukaryotic proteomes and are integrated in essentially all cellular processes (1). Proteomic approaches, such as mass spectrometry (MS), have been instrumental in monitoring global molecular dynamics for research and clinical applications (2–5). However, even in this modern era, large-scale analyses of PTMs by MS is challenging because of the limited number of modified peptides derived from proteins that, by themselves, may not be abundant. Moreover, comprehensive PTM analysis by MS often requires significant amounts of biological material that may not be available. PTM analysis using protein arrays can overcome these limitations because of the equimolar amount of the arrayed proteins (6, 7). Large-scale protein arrays have been successfully integrated into PTM research (8, 9). However, this technology relies on pre-purified proteins that are arrayed on a surface and thus, incompatible with biochemically challenging proteins, let alone insoluble proteins. Moreover, the production of recombinant protein arrays is impractical in-house. Therefore, such arrays cannot be used fresh, and they are inherently limited to certain designs, protein compositions, and model organisms of high commercial value. To overcome the abovementioned limitations, we designed a modular integrated microfluidic platform for PTM analysis (IMPA).