Mice have a transcribed L-threonine aldolase/GLY1 gene, but the human GLY1 gene is a non-processed pseudogene

BACKGROUND: There are three pathways of L-threonine catabolism. The enzyme L-threonine aldolase (TA) has been shown to catalyse the conversion of L-threonine to yield glycine and acetaldehyde in bacteria, fungi and plants. Low levels of TA enzymatic activity have been found in vertebrates. It has been suggested that any detectable activity is due to serine hydroxymethyltransferase and that mammals lack a genuine threonine aldolase. RESULTS: The 7-exon murine L-threonine aldolase gene (GLY1) is located on chromosome 11, spanning 5.6 kb. The cDNA encodes a 400-residue protein. The protein has 81% similarity with the bacterium Thermotoga maritima TA. Almost all known functional residues are conserved between the two proteins including Lys242 that forms a Schiff-base with the cofactor, pyridoxal-5'-phosphate. The human TA gene is located at 17q25. It contains two single nucleotide deletions, in exons 4 and 7, which cause frame-shifts and a premature in-frame stop codon towards the carboxy-terminal. Expression of human TA mRNA was undetectable by RT-PCR. In mice, TA mRNA was found at low levels in a range of adult tissues, being highest in prostate, heart and liver. In contrast, serine/threonine dehydratase, another enzyme that catabolises L-threonine, is expressed very highly only in the liver. Serine dehydratase-like 1, also was most abundant in the liver. In whole mouse embryos TA mRNA expression was low prior to E-15 increasing more than four-fold by E-17. CONCLUSION: Mice, the western-clawed frog and the zebrafish have transcribed threonine aldolase/GLY1 genes, but the human homolog is a non-transcribed pseudogene. Serine dehydratase-like 1 is a putative L-threonine catabolising enzyme

Enhancement of toxin- and virus-neutralizing capacity of single-domain antibody fragments by N-glycosylation

Single-domain antibody fragments (VHHs) have several beneficial properties as compared to conventional antibody fragments. However, their small size complicates their toxin- and virus-neutralizing capacity. We isolated 27 VHHs binding Escherichia coli heat-labile toxin and expressed these in Saccharomyces cerevisiae. The most potent neutralizing VHH (LT109) was N-glycosylated, resulting in a large increase in molecular mass. This suggests that N-glycosylation of LT109 improves its neutralizing capacity. Indeed, deglycosylation of LT109 decreased its neutralizing capacity three- to fivefold. We also studied the effect of glycosylation of two previously isolated VHHs on their ability to neutralize foot-and-mouth disease virus. For this purpose, these VHHs that lacked potential N-glycosylation sites were genetically fused to another VHH that was known to be glycosylated. The resulting fusion proteins were also N-glycosylated. They neutralized the virus at at least fourfold-lower VHH concentrations as compared to the single, non-glycosylated VHHs and at at least 50-fold-lower VHH concentrations as compared to their deglycosylated counterparts. Thus, we have shown that N-glycosylation of VHHs contributes to toxin- and virus-neutralizing capacity

Large-Scale Discovery and Characterization of Protein Regulatory Motifs in Eukaryotes

The increasing ability to generate large-scale, quantitative proteomic data has brought with it the challenge of analyzing such data to discover the sequence elements that underlie systems-level protein behavior. Here we show that short, linear protein motifs can be efficiently recovered from proteome-scale datasets such as sub-cellular localization, molecular function, half-life, and protein abundance data using an information theoretic approach. Using this approach, we have identified many known protein motifs, such as phosphorylation sites and localization signals, and discovered a large number of candidate elements. We estimate that ∼80% of these are novel predictions in that they do not match a known motif in both sequence and biological context, suggesting that post-translational regulation of protein behavior is still largely unexplored. These predicted motifs, many of which display preferential association with specific biological pathways and non-random positioning in the linear protein sequence, provide focused hypotheses for experimental validation

Glycosylation site prediction using ensembles of Support Vector Machine classifiers

Article discussing the performance of different computational methods for prediction of glycosylation sites from amino acid sequences

Unfolding of the Amyloid β-Peptide Central Helix: Mechanistic Insights from Molecular Dynamics Simulations

Alzheimer's disease (AD) pathogenesis is associated with formation of amyloid fibrils caused by polymerization of the amyloid β-peptide (Aβ), which is a process that requires unfolding of the native helical structure of Aβ. According to recent experimental studies, stabilization of the Aβ central helix is effective in preventing Aβ polymerization into toxic assemblies. To uncover the fundamental mechanism of unfolding of the Aβ central helix, we performed molecular dynamics simulations for wild-type (WT), V18A/F19A/F20A mutant (MA), and V18L/F19L/F20L mutant (ML) models of the Aβ central helix. It was quantitatively demonstrated that the stability of the α-helical conformation of both MA and ML is higher than that of WT, indicating that the α-helical propensity of the three nonpolar residues (18, 19, and 20) is the main factor for the stability of the whole Aβ central helix and that their hydrophobicity plays a secondary role. WT was found to completely unfold by a three-step mechanism: 1) loss of α-helical backbone hydrogen bonds, 2) strong interactions between nonpolar sidechains, and 3) strong interactions between polar sidechains. WT did not completely unfold in cases when any of the three steps was omitted. MA and ML did not completely unfold mainly due to the lack of the first step. This suggests that disturbances in any of the three steps would be effective in inhibiting the unfolding of the Aβ central helix. Our findings would pave the way for design of new drugs to prevent or retard AD

Integrative Identification of Arabidopsis Mitochondrial Proteome and Its Function Exploitation through Protein Interaction Network

Mitochondria are major players on the production of energy, and host several key reactions involved in basic metabolism and biosynthesis of essential molecules. Currently, the majority of nucleus-encoded mitochondrial proteins are unknown even for model plant Arabidopsis. We reported a computational framework for predicting Arabidopsis mitochondrial proteins based on a probabilistic model, called Naive Bayesian Network, which integrates disparate genomic data generated from eight bioinformatics tools, multiple orthologous mappings, protein domain properties and co-expression patterns using 1,027 microarray profiles. Through this approach, we predicted 2,311 candidate mitochondrial proteins with 84.67% accuracy and 2.53% FPR performances. Together with those experimental confirmed proteins, 2,585 mitochondria proteins (named CoreMitoP) were identified, we explored those proteins with unknown functions based on protein-protein interaction network (PIN) and annotated novel functions for 26.65% CoreMitoP proteins. Moreover, we found newly predicted mitochondrial proteins embedded in particular subnetworks of the PIN, mainly functioning in response to diverse environmental stresses, like salt, draught, cold, and wound etc. Candidate mitochondrial proteins involved in those physiological acitivites provide useful targets for further investigation. Assigned functions also provide comprehensive information for Arabidopsis mitochondrial proteome

Gaia Early Data Release 3: The celestial reference frame (Gaia-CRF3)

Context. Gaia-CRF3 is the celestial reference frame for positions and proper motions in the third release of data from the Gaia mission, Gaia DR3 (and for the early third release, Gaia EDR3, which contains identical astrometric results). The reference frame is defined by the positions and proper motions at epoch 2016.0 for a specific set of extragalactic sources in the (E)DR3 catalogue. Aims. We describe the construction of Gaia-CRF3 and its properties in terms of the distributions in magnitude, colour, and astrometric quality. Methods. Compact extragalactic sources in Gaia DR3 were identified by positional cross-matching with 17 external catalogues of quasi-stellar objects (QSO) and active galactic nuclei (AGN), followed by astrometric filtering designed to remove stellar contaminants. Selecting a clean sample was favoured over including a higher number of extragalactic sources. For the final sample, the random and systematic errors in the proper motions are analysed, as well as the radio-optical offsets in position for sources in the third realisation of the International Celestial Reference Frame (ICRF3). Results. Gaia-CRF3 comprises about 1.6 million QSO-like sources, of which 1.2 million have five-parameter astrometric solutions in Gaia DR3 and 0.4 million have six-parameter solutions. The sources span the magnitude range G = 13-21 with a peak density at 20.6 mag, at which the typical positional uncertainty is about 1 mas. The proper motions show systematic errors on the level of 12 μas yr-1 on angular scales greater than 15 deg. For the 3142 optical counterparts of ICRF3 sources in the S/X frequency bands, the median offset from the radio positions is about 0.5 mas, but it exceeds 4 mas in either coordinate for 127 sources. We outline the future of Gaia-CRF in the next Gaia data releases. Appendices give further details on the external catalogues used, how to extract information about the Gaia-CRF3 sources, potential (Galactic) confusion sources, and the estimation of the spin and orientation of an astrometric solution

Pulsations in main sequence OBAF-type stars

CONTEXT: The third Gaia data release provides photometric time series covering 34 months for about 10 million stars. For many of those stars, a characterisation in Fourier space and their variability classification are also provided. This paper focuses on intermediate- to high-mass (IHM) main sequence pulsators (M ≥  1.3 M⊙) of spectral types O, B, A, or F, known as β Cep, slowly pulsating B (SPB), δ Sct, and γ Dor stars. These stars are often multi-periodic and display low amplitudes, making them challenging targets to analyse with sparse time series. AIMS: We investigate the extent to which the sparse Gaia DR3 data can be used to detect OBAF-type pulsators and discriminate them from other types of variables. We aim to probe the empirical instability strips and compare them with theoretical predictions. The most populated variability class is that of the δ Sct variables. For these stars, we aim to confirm their empirical period-luminosity (PL) relation, and verify the relation between their oscillation amplitude and rotation. METHODS: All datasets used in this analysis are part of the Gaia DR3 data release. The photometric time series were used to perform a Fourier analysis, while the global astrophysical parameters necessary for the empirical instability strips were taken from the Gaia DR3 gspphot tables, and the v sin i data were taken from the Gaia DR3 esphs tables. The δ Sct PL relation was derived using the same photometric parallax method as the one recently used to establish the PL relation for classical Cepheids using Gaia data. RESULTS: We show that for nearby OBAF-type pulsators, the Gaia DR3 data are precise and accurate enough to pinpoint them in the Hertzsprung-Russell (HR) diagram. We find empirical instability strips covering broader regions than theoretically predicted. In particular, our study reveals the presence of fast rotating gravity-mode pulsators outside the strips, as well as the co-existence of rotationally modulated variables inside the strips as reported before in the literature. We derive an extensive period–luminosity relation for δ Sct stars and provide evidence that the relation features different regimes depending on the oscillation period. We demonstrate how stellar rotation attenuates the amplitude of the dominant oscillation mode of δ Sct stars. CONCLUSIONS: The Gaia DR3 time-series photometry already allows for the detection of the dominant (non-)radial oscillation mode in about 100 000 intermediate- and high-mass dwarfs across the entire sky. This detection capability will increase as the time series becomes longer, allowing the additional delivery of frequencies and amplitudes of secondary pulsation modes