We report the cloning and characterization of a Drosophila proteasome 11 S REG␥ (PA28) homolog. The 28-kDa protein shows 47% identity to the human REG␥ and strongly enhances the trypsin-like activities of both Drosophila and mammalian 20 S proteasomes. Surprisingly, the Drosophila REG was found to inhibit the proteasome's chymotrypsin-like activity against the fluorogenic peptide succinyl-LLVY-7-amino-4-methylcoumarin. Immunocytological analysis reveals that the Drosophila REG is localized to the nucleus but is distributed throughout the cell when nuclear envelope breakdown occurs during mitosis. Through site-directed mutagenesis studies, we have identified a functional nuclear localization signal present in the homolog-specific insert region. The Drosophila PA28 NLS is similar to the oncogene c-Myc nuclear localization motif. Comparison between uninduced and innate immune induced Drosophila cells suggests that the REG␥ proteasome activator has a role independent of the invertebrate immune system. Our results support the idea that ␥ class proteasome activators have an ancient conserved function within metazoans and were present prior to the emergence of the ␣ and ␤ REG classes.

Aminoacyl tRNA synthetases (aaRSs) have long been viewed as mere housekeeping proteins and have therefore often been overlooked in drug discovery. However, recent findings have revealed that many aaRSs have non-canonical functions and several of the aaRSs have been linked to autoimmune diseases, cancer and neurological disorders. Deciphering these roles has been challenging due to a lack of tools to enable their study. To help solve this problem, we have generated recombinant high-affinity antibodies for a collection of thirteen cytoplasmic and one mitochondrial aaRSs. Selected domains of these proteins were produced recombinantly in Escherichia coli and used as antigens in phage display selections using a synthetic human single-chain fragment variable (scFv) library. All targets yielded large sets of antibody candidates that were validated through a panel of binding assays against the purified antigen. Furthermore, the top performing binders were tested in immunoprecipitation followed by mass spectrometry (IP-MS) for their ability to capture the endogenous protein from mammalian cell lysates. For antibodies targeting individual members of the multi-tRNA synthetase complex (MSC), we were able to detect all members of the complex, co-immunoprecipitating with the target, in several cell types. The functionality of a sub-set of binders for each target was also confirmed using immunofluorescence. The sequences of these proteins have been deposited in publicly available databases and repositories. We anticipate this open source resource, in the form of high quality recombinant proteins and antibodies, will accelerate and empower future research of the role of aaRSs in health and disease.

In this paper, we report an experimental setup and mathematical algorithm for determination of relative protein abundance from directly labeled native protein samples applied to an array of antibodies. The application of the proposed experimental system compensates internally at each array element for a number of deficiencies in array experiments such as differential labeling efficiency in dual color assay systems, differential solubility of protein molecules in dual color assay systems, and differential affinity of capture reagents toward proteins labeled with two different fluorescent dyes. This system offers full compensation for variable amounts of capture reagents on separate array structures, as well as limited compensation for nonspecific interactions between capture reagents and analytes. The proposed experimental strategy enables the use of a large number of capture reagents to develop a true multiplex analysis system that will yield complete relative protein abundance information in two biological systems.

Abstract-Compressed sensing (CS) is a universal technique for the compression of sparse signals. CS has been widely used in sensing platforms where portable, autonomous devices have to operate for long periods of time with limited energy resources. Therefore, an ultra-low-power (ULP) CS implementation is vital for these kind of energy-limited systems. Sub-threshold (sub-VT) operation is commonly used for ULP computing, and can also be combined with CS. However, most established CS implementations can achieve either no or very limited benefit from sub-VT operation. Therefore, we propose a sub-VT application-specific instruction-set processor (ASIP), exploiting the specific operations of CS. Our results show that the proposed ASIP accomplishes 62x speed-up and 11.6x power savings with respect to an established CS implementation running on the baseline low-power processor.