An Insertion Peptide in Yeast Glycyl-tRNA Synthetase Facilitates both Productive Docking and Catalysis of Cognate tRNAs

The yeast Saccharomyces cerevisiae possesses two distinct glycyl-tRNA synthetase (GlyRS) genes: GRS1 and GRS2. GRS1 is dually functional, encoding both cytoplasmic and mitochondrial activities, while GRS2 is dysfunctional and not required for growth. The protein products of these two genes, GlyRS1 and GlyRS2, are much alike but are distinguished by an insertion peptide of GlyRS1, which is absent from GlyRS2 and other eukaryotic homologues. We show that deletion or mutation of the insertion peptide modestly impaired the enzyme''s catalytic efficiency in vitro (with a 2- to 3-fold increase in K_m and a 5- to 8-fold decrease in k_cat). Consistently, GRS2 can be conveniently converted to a functional gene via codon optimization, and the insertion peptide is dispensable for protein stability and the rescue activity of GRS1 at 30°C in vivo. A phylogenetic analysis further showed that GRS1 and GRS2 are paralogues that arose from a gene duplication event relatively recently, with GRS1 being the predecessor. These results indicate that GlyRS2 is an active enzyme essentially resembling the insertion peptide-deleted form of GlyRS1. Our study suggests that the insertion peptide represents a novel auxiliary domain, which facilitates both productive docking and catalysis of cognate tRNAs.     

Hypophysiotrophic thyrotropin releasing hormone (TRH) synthesizing neurons. Ultrastructure, adrenergic innervation and putative transmitter action

The neuropeptide thyrotropin releasing hormone (TRH) is capable of influencing both neuronal mechanisms in the brain and the activity of the pituitary-thyroid endocrine axis. By the use of immunocytochemical techniques, first the ultrastructural features of TRH-immunoreactive (IR) perikarya and neuronal processes were studied, and then the relationship between TRH-IR neuronal elements and dopamine-beta-hydroxylase (DBH) or phenylethanolamine-N-methyltransferase (PNMT)-IR catecholaminergic axons was analyzed in the parvocellular subnuclei of the hypothalamic paraventricular nucleus (PVN). In control animals, only TRH-IR axons were detected and some of them seemed to follow the contour of immunonegative neurons. Colchicine treatment resulted in the appearance of TRH-IR material in parvocellular neurons of the PVN. At the ultrastructural level, immunolabel was associated with rough endoplasmic reticulum, free ribosomes and neurosecretory granules. Non-labelled axons formed synaptic specializations with both dendrites and perikarya of the TRH-synthesizing neurons. TRH-IR axons located in the parvocellular units of the PVN exhibited numerous intensely labelled dense-core and fewer small electron lucent vesicles. These axons were frequently observed to terminate on parvocellular neurons, forming both bouton- and en passant-type connections. The simultaneous light microscopic localization of DBH or PNMT-IR axons and TRH-synthesizing neurons demonstrated that catecholaminergic fibers established contacts with the dendrites and cell bodies of TRH-IR neurons. Ultrastructural analysis revealed the formation of asymmetric axo-somatic and axo-dendritic synaptic specializations between PNMT-immunopositive, adrenergic axons and TRH-IR neurons in the periventricular and medial parvocellular subnuclei of the PVN. These morphological data indicate that the hypophysiotrophic, thyrotropin releasing hormone synthesizing neurons of the PVN are directly influenced by the central epinephrine system and that TRH may act as a neurotransmitter or neuromodulator upon other paraventricular neurons.     

Rapid determination of substrate specificity of Clostridium histolyticum beta-collagenase using an immobilized peptide library.

The molecular basis of the substrate specificity of Clostridium histolyticum beta-collagenase was investigated using a combinatorial method. An immobilized positional peptide library, which contains 24,000 sequences, was constructed with a 7-hydroxycoumarin-4-propanoyl (Cop) fluorescent group attached at the N terminus of each sequence. This immobilized peptide library was incubated with C. histolyticum beta-collagenase, releasing fluorogenic fragments in the solution phase. The relative substrate specificity (k(cat)/K(m)) for each member of the library was determined by measuring fluorescence intensity in the solution phase. Edman sequencing was used to assign structure to subsites of active substrate mixtures. Collectively, the substrate preference for subsites (P(3)-P(4)') of C. histolyticum beta-collagenase was determined. The last position on the C-terminal side in which the identity of the amino acids affects the activity of the enzyme is P(4)', and an aromatic side chain is preferred in this position. The optimal P(1)'-P(3)' extended substrate sequence is P(1)'-Gly/Ala, P(2)'-Pro/Xaa, and P(3)'-Lys/Arg/Pro/Thr/Ser. The Cop group in either the P(2) or P(3) position is required for a high substrate activity with C. histolyticum beta-collagenase. S(2) and S(3) sites of the protease play a dominant role in fixing the substrate specificity. The immobilized peptide library proved to be a powerful approach for assessing the substrate specificity of C. histolyticum beta-collagenase, so it may be applied to the study of other proteases of interest.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.