Engineering topics

Kihara, Daisuke

Publications and source records attributed to Kihara, Daisuke.

4 records

DOE OSTI2023

Amino Acids Essential for the Assembly of Cellulose Synthase Complexes

Over 40 years ago, Andrew Staehelin's group showed that plant cellulose microfibrils are synthesized by protein complexes arranged in hexagonal arrays called 'particle rosettes'. Plant cellulose synthases (CESAs) differ from their bacterial ancestral forms by insertion of three unique sequences responsible for the assembly into compact multimeric units that aggregate further into rosettes. We used site-directed mutagenesis to replace amino acids within these sequences predicted to be essential for assembly and developed an in vivo method to determine the ability of mutated CesA1 transgenes to complement an Arabidopsis temperature-sensitive root-swelling1 (rsw1) mutant. Replacement of a Cys residue in the Class-Specific Region (CSR) or Pro417 and Arg453 of the Plant-Conserved Region (P-CR) rendered an AtCesA1 transgene unable to complement the rsw1 mutation. Despite an expected role for Arg457 in the trimerization of CESA proteins, AtCesA1 transgenes with Arg457Ala mutations were able to fully restore the wild-type phenotype in rsw1. Staehelin observed a third order of assembly in Micrasterias dendiculata, where hundreds of rosettes form large hexagonal arrays during the synthesis of secondary wall cellulose macrofibrils. We found by SEM of cytosolic faces of Micrasterias cell fragments that these arrays are associated with fields of regularly spaced slime secretion pore complexes.

arabidopsis↗

DOE OSTI2022

Protein folds vs. protein folding: Differing questions, different challenges

We report protein fold prediction using deep-learning artificial intelligence (AI) has transformed the field of protein structure prediction. By combining physical and geometric constraints—and especially patterns extracted from the Protein Data Bank —these machine learning algorithms can predict protein structures at or near atomic resolution and do so in seconds. Today, these computational methods have now solved more than 200 million protein structures, which are accessible from the AlphaFold Protein Structure Database. This accomplishment seems all the more remarkable because few thought it possible or saw it coming. Deservedly, deep-learning AI was named Science magazine’s 2021 “breakthrough of the year”. Clearly, deep-learning AI represents a major advance in protein fold prediction.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Essential amino acids in the Plant-Conserved and Class-Specific Regions of cellulose synthases

The Plant-Conserved Region (P-CR) and the Class-Specific Region (CSR) are two plant-unique sequences in the catalytic core of cellulose synthases (CESAs) for which specific functions have not been established. Here, we used site-directed mutagenesis to replace amino acids and motifs within these sequences predicted to be essential for assembly and function of CESAs. We developed an in vivo method to determine the ability of mutated CesA1 transgenes to complement an Arabidopsis (Arabidopsis thaliana) temperature-sensitive root-swelling1 (rsw1) mutant. Replacement of a Cys residue in the CSR, which blocks dimerization in vitro, rendered the AtCesA1 transgene unable to complement the rsw1 mutation. Examination of the CSR sequences from 33 diverse angiosperm species showed domains of high-sequence conservation in a class-specific manner but with variation in the degrees of disorder, indicating a nonredundant role of the CSR structures in different CESA isoform classes. The Cys residue essential for dimerization was not always located in domains of intrinsic disorder. Expression of AtCesA1 transgene constructs, in which Pro417 and Arg453 were substituted for Ala or Lys in the coiled-coil of the P-CR, were also unable to complement the rsw1 mutation. Despite an expected role for Arg457 in trimerization of CESA proteins, AtCesA1 transgenes with Arg457Ala mutations were able to fully restore the wild-type phenotype in rsw1. Our data support that Cys662 within the CSR and Pro417 and Arg453 within the P-CR of Arabidopsis CESA1 are essential residues for functional synthase complex formation, but our data do not support a specific role for Arg457 in trimerization in native CESA complexes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

CryoFold: Determining protein structures and data-guided ensembles from cryo-EM density maps

Cryoelectron microscopy requires molecular modeling for refinement of structures. Ensemble models arrive at low free-energy molecular structures, but are computationally expensive and limited to resolving only small proteins. Here, we introduce CryoFold, a pipeline of molecular dynamics simulations that determines ensembles of protein structures by integrating density data of varying sparsity at 3–5 Å resolution with sequence information and coarse-grained topological knowledge of the protein folds. We present six examples, folding proteins between 72 and 2,000 residues, including large membrane and multi-domain systems, and results from two Electron Microscopy Data Bank (EMDB) competitions. Driven by data from a single state, CryoFold discovers ensembles of common low-energy models together with rare low-probability structures that capture the equilibrium distribution of proteins constrained by the density maps. Many of these conformations are experimentally validated and functionally relevant. We arrive at a set of best practices for data-guided protein folding that are controlled using a Python graphical user interface (GUI).

59 BASIC BIOLOGICAL SCIENCES↗