A diffusion barrier impeding membrane molecule motion between the axon and the somatodendritic compartment develops as neurons mature and the axon initial segment (AIS) is enriched in specific molecules. Albrecht et al. analyze the mobility of lipid-anchored molecules in the AIS using single-particle tracking time course experiments and propose a new mechanistic model for the AIS diffusion barrier.

The axon initial segment (AIS) is enriched in specific adaptor, cytoskeletal and transmembrane molecules. During AIS establishment, a membrane diffusion barrier is formed between the axon and the somatodendritic domain.Recently, an axonal periodic pattern of actin, spectrin and ankyrin forming 190 nm distanced, ring-like structures has been discovered. However, whether this structure is related to the diffusion barrier function is unclear.Here, we performed single particle tracking timecourse experiments on hippocampal neurons during AIS development. We analyzed the mobility of lipid-anchored molecules by high-speed single particle tracking and correlated positions of membrane molecules with the nanoscopic organization of the AIS cytoskeleton.We observe a strong reduction in mobility early in AIS development.Membrane protein motion in the AIS plasma membrane is confined to a repetitive pattern of ~190 nm spaced segments along the AIS axis as early as DIV4 and this pattern alternates with actin rings. Our data provide a new model for the mechanism of the AIS diffusion barrier.3

We consider the problem of delivering m messages between specified source-target pairs in a weighted undirected graph, by k mobile agents initially located at distinct nodes of the graph. Each agent consumes energy proportional to the distance it travels in the graph and we are interested in optimizing the total energy consumption for the team of agents. Unlike previous related work, we consider heterogeneous agents with different rates of energy consumption (weights w i ). To solve the delivery problem, agents face three major challenges: Collaboration (how to work together on each message), Planning (which route to take) and Coordination (how to assign agents to messages).We first show that the delivery problem can be 2-approximated without collaborating and that this is best possible, i.e., we show that the benefit of collaboration is 2 in general. We also show that the benefit of collaboration for a single message is 1/ ln 2 ≈ 1.44. Planning turns out to be NP-hard to approximate even for a single agent, but can be 2-approximated in polynomial time if agents have unit capacities and do not collaborate. We further show that coordination is NPhard even for agents with unit capacity, but can be efficiently solved exactly if they have uniform weights. Finally, we give a polynomial-time (4 max wi wj )-approximation for message delivery with unit capacities.

BackgroundGiven a peptide as a string of amino acids, the masses of all its prefixes and suffixes can be found by a trivial linear scan through the amino acid masses. The inverse problem is the ideal de novo peptide sequencing problem: Given all prefix and suffix masses, determine the string of amino acids. In biological reality, the given masses are measured in a lab experiment, and measurements by necessity are noisy. The (real, noisy) de novo peptide sequencing problem therefore has a noisy input: a few of the prefix and suffix masses of the peptide are missing and a few other masses are given in addition. For this setting, we ask for an amino acid string that explains the given masses as accurately as possible.ResultsPast approaches interpreted accuracy by searching for a string that explains as many masses as possible. We feel, however, that it is not only bad to not explain a mass that appears, but also to explain a mass that does not appear. We propose to minimize the symmetric difference between the set of given masses and the set of masses that the string explains. For this new optimization problem, we propose an efficient algorithm that computes both the best and the k best solutions. Proof-of-concept experiments on measurements of synthesized peptides show that our approach leads to better results compared to finding a string that explains as many given masses as possible.ConclusionsWe conclude that considering the symmetric difference as optimization goal can improve the identification rates for de novo peptide sequencing. A preliminary version of this work has been presented at WABI 2016.Electronic supplementary materialThe online version of this article (doi:10.1186/s13015-017-0104-1) contains supplementary material, which is available to authorized users.