The interaction between LC8 and LCA5 reveals a novel oligomerization function of LC8 in the ciliary-centrosome system

Dynein light chain LC8 is a small dimeric hub protein that recognizes its partners through short linear motifs and is commonly assumed to drive their dimerization. It has more than 100 known binding partners involved in a wide range of cellular processes. Recent large-scale interaction studies suggested that LC8 could also play a role in the ciliary/centrosome system. However, the cellular function of LC8 in this system remains elusive. In this work, we characterized the interaction of LC8 with the centrosomal protein lebercilin (LCA5), which is associated with a specific form of ciliopathy. We showed that LCA5 binds LC8 through two linear motifs. In contrast to the commonly accepted model, LCA5 forms dimers through extensive coiled coil formation in a LC8-independent manner. However, LC8 enhances the oligomerization ability of LCA5 that requires a finely balanced interplay of coiled coil segments and both binding motifs. Based on our results, we propose that LC8 acts as an oligomerization engine that is responsible for the higher order oligomer formation of LCA5. As LCA5 shares several common features with other centrosomal proteins, the presented LC8 driven oligomerization could be widespread among centrosomal proteins, highlighting an important novel cellular function of LC8

Interactions between two regulatory proteins of microtubule dynamics, HDAC6, TPPP/p25, and the hub protein, DYNLL/LC8

Degradation of unwanted proteins is important in protein quality control cooperating with the dynein/dynactin-mediated trafficking along the acetylated microtubule (MT) network. Proteins associated directly/indirectly with tubulin/MTs play crucial roles in both physiological and pathological processes. Our studies focus on the interrelationship of the tubulin deacetylase HDAC6, the MT-associated TPPP/p25 with its deacetylase inhibitory potency and the hub dynein light chain DYNLL/LC8, constituent of dynein and numerous other protein complexes. In this paper, evidence is provided for the direct interaction of DYNLL/LC8 with TPPP/p25 and HDAC6 and their assembly into binary/ternary complexes with functional potency. The in vitro binding data was obtained with recombinant proteins and used for mathematical modelling. These data and visualization of their localizations by bimolecular fluorescence complementation technology and immunofluorescence microscopy in HeLa cells revealed the promoting effect of TPPP/p25 on the interaction of DYNLL/LC8 with both tubulin and HDAC6.Localization of the LC8-2-TPPP/p25 complex was observed on the MT network in contrast to the LC8-2-HDAC6 complex, which was partly translocated to the nucleus. LC8-2 did not influence directly the acetylation of the MT network. However, the binding of TPPP/p25 to a new binding site of DYNLL/LC8, outside the canonical binding groove, counteracted the TPPP/p25-derived hyperacetylation of the MT network. Our data suggest that multiple associations of the regulatory proteins of the MT network could ensure fine tuning in the regulation of the intracellular trafficking process either by the complexation of DYNLL/LC8 with new partners or indirectly by the modulation of the acetylation level of the MT network

Neuronal-specific septin-3 binds Atg8/LC3B, accumulates and localizes to autophagosomes during induced autophagy

In synapses that show signs of local apoptosis and mitochondrial stress and undergo neuro-immunological synapse pruning, an increase in the levels of the presynaptic protein, neuronal-specific septin-3 can be observed. Septin-3 is a member of the septin GTPase family with the ability to form multimers and contribute to the cytoskeleton. However, the function of septin-3 remains elusive. Here, we provide evidence that septin-3 is capable of binding the most-studied autophagy protein Atg8 homolog microtubule-associated protein 1 light chain 3B (LC3B), besides another homolog, GABA receptor-associated protein-like 2 (GABARAPL2). Moreover, we demonstrate that colocalization of septin-3 and LC3B increases upon chemical autophagy induction in primary neuronal cells. Septin-3 is accumulated in primary neurons upon autophagy enhancement or blockade, similar to autophagy proteins. Using electron microscopy, we also show that septin-3 localizes to LC3B positive membranes and can be found at mitochondria. However, colocalization results of septin-3 and the early mitophagy marker PTEN-induced kinase 1 (PINK1) do not support that binding of septin-3 to mitochondria is mitophagy related. We conclude that septin-3 correlates with synaptic/neuronal autophagy, binds Atg8 and localizes to autophagic membranes that can be enhanced with chemical autophagy induction. Based on our results, elevated septin-3 levels might indicate enhanced or impeded autophagy in neurons

Development and In-Depth Characterization of Bacteria Repellent and Bacteria Adhesive Antibody-Coated Surfaces Using Optical Waveguide Biosensing

Bacteria repellent surfaces and antibody-based coatings for bacterial assays have shown a growing demand in the field of biosensors, and have crucial importance in the design of biomedical devices. However, in-depth investigations and comparisons of possible solutions are still missing. The optical waveguide lightmode spectroscopy (OWLS) technique offers label-free, non-invasive, in situ characterization of protein and bacterial adsorption. Moreover, it has excellent flexibility for testing various surface coatings. Here, we describe an OWLS-based method supporting the development of bacteria repellent surfaces and characterize the layer structures and affinities of different antibody-based coatings for bacterial assays. In order to test nonspecific binding blocking agents against bacteria, OWLS chips were coated with bovine serum albumin (BSA), I-block, PAcrAM-g-(PMOXA, NH(2), Si), (PAcrAM-P) and PLL-g-PEG (PP) (with different coating temperatures), and subsequent Escherichia coli adhesion was monitored. We found that the best performing blocking agents could inhibit bacterial adhesion from samples with bacteria concentrations of up to 10(7) cells/mL. Various immobilization methods were applied to graft a wide range of selected antibodies onto the biosensor’s surface. Simple physisorption, Mix&Go (AnteoBind) (MG) films, covalently immobilized protein A and avidin–biotin based surface chemistries were all fabricated and tested. The surface adsorbed mass densities of deposited antibodies were determined, and the biosensor;s kinetic data were evaluated to divine the possible orientations of the bacteria-capturing antibodies and determine the rate constants and footprints of the binding events. The development of affinity layers was supported by enzyme-linked immunosorbent assay (ELISA) measurements in order to test the bacteria binding capabilities of the antibodies. The best performance in the biosensor measurements was achieved by employing a polyclonal antibody in combination with protein A-based immobilization and PAcrAM-P blocking of nonspecific binding. Using this setting, a surface sensitivity of 70 cells/mm(2) was demonstrated

DisProt: intrinsic protein disorder annotation in 2020

The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the ‘dark’ proteome

Critical assessment of protein intrinsic disorder prediction

Abstract: Intrinsically disordered proteins, defying the traditional protein structure–function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in prediction of intrinsically disordered regions and the subset of residues involved in binding. A total of 43 methods were evaluated on a dataset of 646 proteins from DisProt. The best methods use deep learning techniques and notably outperform physicochemical methods. The top disorder predictor has Fmax = 0.483 on the full dataset and Fmax = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with Fmax = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude