The Caenorhabditis elegans Kinesin-3 motor UNC-104/KIF1A is degraded upon loss of specific binding to cargo

UNC-104/KIF1A is a Kinesin-3 motor that transports synaptic vesicles from the cell body towards the synapse by binding to PI(4,5)P(2) through its PH domain. The fate of the motor upon reaching the synapse is not known. We found that wild-type UNC-104 is degraded at synaptic regions through the ubiquitin pathway and is not retrogradely transported back to the cell body. As a possible means to regulate the motor, we tested the effect of cargo binding on UNC-104 levels. The unc-104(e1265) allele carries a point mutation (D1497N) in the PI(4,5)P(2) binding pocket of the PH domain, resulting in greatly reduced preferential binding to PI(4,5)P(2)in vitro and presence of very few motors on pre-synaptic vesicles in vivo. unc-104(e1265) animals have poor locomotion irrespective of in vivo PI(4,5)P(2) levels due to reduced anterograde transport. Moreover, they show highly reduced levels of UNC-104 in vivo. To confirm that loss of cargo binding specificity reduces motor levels, we isolated two intragenic suppressors with compensatory mutations within the PH domain. These show partial restoration of in vitro preferential PI(4,5)P(2) binding and presence of more motors on pre-synaptic vesicles in vivo. These animals show improved locomotion dependent on in vivo PI(4,5)P(2) levels, increased anterograde transport, and partial restoration of UNC-104 protein levels in vivo. For further proof, we mutated a conserved residue in one suppressor background. The PH domain in this triple mutant lacked in vitro PI(4,5)P(2) binding specificity, and the animals again showed locomotory defects and reduced motor levels. All allelic variants show increased UNC-104 levels upon blocking the ubiquitin pathway. These data show that inability to bind cargo can target motors for degradation. In view of the observed degradation of the motor in synaptic regions, this further suggests that UNC-104 may get degraded at synapses upon release of cargo.     

Cathepsin S controls angiogenesis and tumor growth via matrix-derived angiogenic factors

The cysteine protease cathepsin S is highly expressed in malignant tissues. By using a mouse model of multistage murine pancreatic islet cell carcinogenesis in which cysteine cathepsin activity has been functionally implicated, we demonstrated that selective cathepsin S deficiency impaired angiogenesis and tumor cell proliferation, thereby impairing angiogenic islet formation and the growth of solid tumors, whereas the absence of its endogenous inhibitor cystatin C resulted in opposite phenotypes. Although mitogenic vascular endothelial growth factor, transforming growth factor-beta1, and the anti-angiogenic endostatin levels in either serum or carcinoma tissue extracts did not change in cathepsin S- or cystatin C-null mice, tumor tissue basic fibroblast growth factor and serum type 1 insulin growth factor levels were higher in cystatin C-null mice, and serum type 1 insulin growth factor levels were also increased in cathepsin S-null mice. Furthermore, cathepsin S affected the production of type IV collagen-derived anti-angiogenic peptides and the generation of bioactive pro-angiogenic gamma2 fragments from laminin-5, revealing a functional role for cathepsin S in angiogenesis and neoplastic progression.     

Deciphering common recognition principles of nucleoside mono/di and tri‐phosphates binding in diverse proteins via structural matching of their binding sites

Nucleoside triphosphate (NTP) ligands are of high biological importance and are essential for all life forms. A pre‐requisite for them to participate in diverse biochemical processes is their recognition by diverse proteins. It is thus of great interest to understand the basis for such recognition in different proteins. Towards this, we have used a structural bioinformatics approach and analyze structures of 4677 NTP complexes available in Protein Data Bank (PDB). Binding sites were extracted and compared exhaustively using PocketMatch, a sensitive in‐house site comparison algorithm, which resulted in grouping the entire dataset into 27 site‐types. Each of these site‐types represent a structural motif comprised of two or more residue conservations, derived using another in‐house tool for superposing binding sites, PocketAlign. The 27 site‐types could be grouped further into 9 super‐types by considering partial similarities in the sites, which indicated that the individual site‐types comprise different combinations of one or more site features. A scan across PDB using the 27 structural motifs determined the motifs to be specific to NTP binding sites, and a computational alanine mutagenesis indicated that residues identified to be highly conserved in the motifs are also most contributing to binding. Alternate orientations of the ligand in several site‐types were observed and rationalized, indicating the possibility of some residues serving as anchors for NTP recognition. The presence of multiple site‐types and the grouping of multiple folds into each site‐type is strongly suggestive of convergent evolution. Knowledge of determinants obtained from this study will be useful for detecting function in unknown proteins. Proteins 2017; 85:1699–1712. © 2017 Wiley Periodicals, Inc.     

MAP3K4 Controls the Chromatin Modifier HDAC6 during Trophoblast Stem Cell Epithelial-to-Mesenchymal Transition

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LR8 expression in fibroblasts of healthy and fibrotic human tissues

LR8 gene was first reported in a subpopulation of cultured human lung fibroblasts expressing the receptor for C1q-globular domain, and it was not detectable in cultured endothelial cells and smooth muscle cells. LR8 mRNA levels were higher in fibrotic lungs. In this study we assessed LR8 production in human tissues and determined if the distribution of fibroblasts producing LR8 is affected in fibrosis. Normal and fibrotic tissue sections from human liver, lung and kidneys were immunostained with antibodies to LR8 and examined for the presence of fibroblasts staining positively and negatively. The cells were also examined for co-expression of α-smooth muscle actin (SMA), a marker for myofibroblasts. The results showed that LR8 was expressed by fibroblasts, smooth muscle cells, endothelial cells, bile duct cells, pulmonary alveolar cells and distal and proximal kidney tubule cells. Connective tissues of normal and fibrotic tissues contained fibroblasts staining positively and negatively with anti- LR8 antibody. The number of LR8-positive cells was higher in fibrotic tissues, but differences were not statistically significant. Fibroblasts producing both LR8 and SMA were present in higher numbers in fibrotic tissues as compared to normal tissues and the differences were statistically significant (p<0.05). Our results show that fibroblast subtypes differing in LR8 expression are present in human tissues, and that in fibrotic tissues cells co-expressing LR8 and SMA are present. Our results indicate that LR8 expressing cells may participate in the early stages of fibrotic diseases and that fibroblasts expressing LR8, not LR8 negative cells, have potential to become myofibroblasts in fibrotic tissues.     

Emerging nanoproteomics approaches for disease biomarker detection: a current perspective

Availability of genome sequence of human and different pathogens has advanced proteomics research for various clinical applications. One of the prime goals of proteomics is identification and characterization of biomarkers for cancer and other fatal human diseases to aid an early diagnosis and monitor disease progression. However, rapid detection of low abundance biomarkers from the complex biological samples under clinically relevant conditions is extremely difficult, and it requires the development of ultrasensitive, robust and high-throughput technological platform. In order to overcome several technical limitations associated with sensitivity, dynamic range, detection time and multiplexing, proteomics has started integrating several emerging disciplines such as nanotechnology, which has led to the development of a novel analytical platform known as 'nanoproteomics'. Among the diverse classes of nanomaterials, the quantum dots, gold nanoparticles, carbon nanotubes and silicon nanowires are the most promising candidates for diagnostic applications. Nanoproteomics offers several advantages such as ultralow detection, short assay time, high-throughput capability and low sample consumption. In this article, we have discussed the application of nanoproteomics for biomarker discovery in various diseases with special emphasis on various types of cancer. Furthermore, we have discussed the prospects, merits and limitations of nanoproteomics.