Quaternary organization of the human eEF1B complex reveals unique multi-GEF domain assembly

DeepGenomeScan of 15 Worldwide Bovine Populations Detects Spatially Varying Positive Selection Signals

Identifying genomic regions under selection is essential for understanding the genetic mechanisms driving species evolution and adaptation. Traditional methods often fall short in detecting complex, spatially varying selection signals. Recent advances in deep learning, however, present promising new approaches for uncovering subtle selection signals that traditional methods might miss. In this study, we utilized the deep learning framework DeepGenomeScan to detect spatially varying selection signatures across 15 bovine populations worldwide. Our analysis uncovered novel insights into selective sweep hotspots within the bovine genome, revealing key genes associated with physiological and adaptive traits that were previously undetected. We identified significant quantitative trait loci linked to milk protein and fat percentages. By comparing the selection signatures identified in this study with those reported in the Bovine Genome Variation Database, we discovered 38 novel genes under selection that were not identified through traditional methods. These genes are primarily associated with milk and meat yield and quality. Our findings enhance our understanding of spatially varying selection's impact on bovine genomic diversity, laying a foundation for future research in genetic improvement and conservation. This is the first deep learning-based study of selection signatures in cattle, offering new insights for evolutionary and livestock genomics research.

EEF1B2 regulates bone marrow-derived mesenchymal stem cells bone-fat balance via Wnt/β-catenin signaling

The pathological advancement of osteoporosis is caused by the uneven development of bone marrow-derived mesenchymal stem cells (BMSCs) in terms of osteogenesis and adipogenesis. While the role of EEF1B2 in intellectual disability and tumorigenesis is well established, its function in the bone-fat switch of BMSCs is still largely unexplored. During the process of osteogenic differentiation, we observed an increase in the expression of EEF1B2, while a decrease in its expression was noted during adipogenesis. Suppression of EEF1B2 hindered the process of osteogenic differentiation and mineralization while promoting adipogenic differentiation. On the contrary, overexpression of EEF1B2 enhanced osteogenesis and strongly inhibited adipogenesis. Furthermore, the excessive expression of EEF1B2 in the tibias has the potential to mitigate bone loss and decrease marrow adiposity in mice with osteoporosis. In terms of mechanism, the suppression of β-catenin activity occurred when EEF1B2 function was suppressed during osteogenesis. Our collective findings indicate that EEF1B2 functions as a regulator, influencing the differentiation of BMSCs and maintaining a balance between bone and fat. Our finding highlights its potential as a therapeutic target for diseases related to bone metabolism.

Autosomal recessive intellectual disability caused by compound heterozygous variants of the EEF1D gene in a Chinese family

BACKGROUND

Intellectual disability is a prevalent neurodevelopmental disorder, with the majority of affected children exhibiting global developmental delay before the age of 5 years. In recent years, certain children have been found to carry homozygous variations of the EEF1D gene, leading to autosomal recessive intellectual disability. However, the pathogenicity of compound heterozygous variations in this gene remains largely unknown.

METHODS

Trio whole-exome sequencing and copy number variation sequencing were done for the genetic etiological diagnosis of a 3-year and 11-month-old Chinese boy who presented with brachycephaly, severe to profound global developmental delay, and hypotonia in the lower limbs.

RESULTS

In this case, compound heterozygous variants of the EEF1D gene were found in the child through trio whole-exome sequencing; one was a splice variant (NM_032378.6:c.1905+1G>A) inherited from his father, and the other was a nonsense variant (NM_032378.6:c.676C>T) inherited from his mother. The nonsense variant leads to the production of a premature termination (p.Gln226*). These variations have the ability to explain the clinical phenotypes of the child.

CONCLUSIONS

Our study expands the variation spectrum and provides compelling evidence for EEF1D as a candidate gene for autosomal recessive intellectual disability. However, due to the deficient number of reported cases, researchers need to further study EEF1D and supplement the clinical phenotypes and treatment measures.

Hidden Glutathione Transferases in the Human Genome

With the development of accurate protein structure prediction algorithms, artificial intelligence (AI) has emerged as a powerful tool in the field of structural biology. AI-based algorithms have been used to analyze large amounts of protein sequence data including the human proteome, complementing experimental structure data found in resources such as the Protein Data Bank. The EBI AlphaFold Protein Structure Database (for example) contains over 230 million structures. In this study, these data have been analyzed to find all human proteins containing (or predicted to contain) the cytosolic glutathione transferase (cGST) fold. A total of 39 proteins were found, including the alpha-, mu-, pi-, sigma-, zeta- and omega-class GSTs, intracellular chloride channels, metaxins, multisynthetase complex components, elongation factor 1 complex components and others. Three broad themes emerge: cGST domains as enzymes, as chloride ion channels and as protein-protein interaction mediators. As the majority of cGSTs are dimers, the AI-based structure prediction algorithm AlphaFold-multimer was used to predict structures of all pairwise combinations of these cGST domains. Potential homo- and heterodimers are described. Experimental biochemical and structure data is used to highlight the strengths and limitations of AI-predicted structures.

Reconstitution of Multi-Protein Complexes through Ribozyme-Assisted Polycistronic Co-Expression

In living cells, proteins often exert their functions by interacting with other proteins forming protein complexes. Obtaining homogeneous samples of protein complexes with correct fold and stoichiometry is critical for its biochemical and biophysical characterization as well as functional investigation. Here, we developed a Ribozyme-Assisted Polycistronic co-expression system (pRAP) for heterologous co-production and in vivo assembly of multi-subunit complexes. In the pRAP system, a polycistronic mRNA transcript is co-transcriptionally converted into individual mono-cistrons in vivo. Each cistron can initiate translation with comparable efficiency, resulting in balanced production for all subunits, thus permitting faithful protein complex assembly. With pRAP polycistronic co-expression, we have successfully reconstituted large functional multi-subunit complexes involved in mammalian translation initiation. Our invention provides a valuable tool for studying the molecular mechanisms of biological processes.

The eEF1 family of mammalian translation elongation factors

The eEF1 family of mammalian translation elongation factors is comprised of the two variants of eEF1A (eEF1A1 and eEF1A2), and the eEF1B complex. The latter consists of eEF1Bα, eEF1Bβ, and eEF1Bγ subunits. The two eEF1A variants have similar translation activity but may differ with respect to their secondary, "moonlighting" functions. This variability is underlined by the difference in the spatial organization of eEF1A1 and eEF1A2, and also possibly by the differences in their post-translational modifications. Here, we review the data on the spatial organization and post-translation modifications of eEF1A1 and eEF1A2, and provide examples of their involvement in various processes in addition to translation. We also describe the structural models of eEF1B subunits, their organization in the subcomplexes, and the trimeric model of the entire eEF1B complex. We discuss the functional consequences of such an assembly into a complex as well as the involvement of individual subunits in non-translational processes.