Engineering topics

Wu, Siqi

Publications and source records attributed to Wu, Siqi.

3 records

DOE OSTI2019

Retractile lysyl-tRNA synthetase-AIMP2 assembly in the human multi-aminoacyl-tRNA synthetase complex

Multi-aminoacyl-tRNA synthetase complex (MSC) is the second largest machinery for protein synthesis in human cells and also regulates multiple nontranslational functions through its components. Prior studies have shown that the MSC can respond to external signals by releasing its components to function outside it. The internal assembly is fundamental to MSC regulation. Here, using crystal structural analyses (at 1.88 Å resolution) along with molecular modeling, gel-filtration chromatography, and co-immunoprecipitation, we report that human lysyl-tRNA synthetase (LysRS) forms a tighter assembly with the scaffold protein aminoacyl-tRNA synthetase complex-interacting multifunctional protein 2 (AIMP2) than previously observed. Wefound that two AIMP2 N-terminal peptides form an antiparallel scaffold and hold two LysRS dimers through four binding motifs and additional interactions. Of note, the four catalytic subunits of LysRS in the tightly assembled complex were all accessible for tRNA recognition. We further noted that two recently reported human disease-associated mutations conflict with this tighter assembly, cause LysRS release from the MSC, and inactivate the enzyme. These findings reveal a previously unknown dimension of MSC subcomplex assembly and suggest that the retractility of this complex may be critical for its physiological functions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set of Drosophila early embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identified 21 principal patterns (PP). Providing a compact yet biologically interpretable representation of Drosophila expression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. In conclusion, the performance of PP with the Drosophila data suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

Spatial expression of transcription factors in Drosophila embryonic organ development

Background: Site-specific transcription factors (TFs) bind DNA regulatory elements to control expression of target genes, forming the core of gene regulatory networks. Despite decades of research, most studies focus on only a small number of TFs and the roles of many remain unknown. Results: We present a systematic characterization of spatiotemporal gene expression patterns for all known or predicted Drosophila TFs throughout embryogenesis, the first such comprehensive study for any metazoan animal. We generated RNA expression patterns for all 708 TFs by in situ hybridization, annotated the patterns using an anatomical controlled vocabulary, and analyzed TF expression in the context of organ system development. Nearly all TFs are expressed during embryogenesis and more than half are specifically expressed in the central nervous system. Compared to other genes, TFs are enriched early in the development of most organ systems, and throughout the development of the nervous system. Of the 535 TFs with spatially restricted expression, 79% are dynamically expressed in multiple organ systems while 21% show single-organ specificity. Of those expressed in multiple organ systems, 77 TFs are restricted to a single organ system either early or late in development. Expression patterns for 354 TFs are characterized for the first time in this study. Conclusions: We produced a reference TF dataset for the investigation of gene regulatory networks in embryogenesis, and gained insight into the expression dynamics of the full complement of TFs controlling the development of each organ system.

59 BASIC BIOLOGICAL SCIENCES↗