Stability-based Selection Research Articles

Highly active enzymes produced by directed evolution with stability-based selection

In a directed evolution aimed at improving enzymatic activity, a situation occurs where highly active variants can no longer be obtained from a template protein because the template is already located at a peak (local maximum) in the fitness landscape of activity for the sequence space. To overcome this situation, the template needs to descend the mountain (lose activity) once and climb another higher mountain. However, there is no solid guideline of how the template should go down. Here, we propose a stability index. Previous studies have shown that protein evolution is potentially governed by stability, and that proteins with low activity but high stability are more favorable templates for producing highly active variants. In our earlier works on conventional directed evolution by random mutagenesis of an esterase from Sulfolobus tokodaii, we identified variants with 3-fold higher activity than the wild-type as the highest activity variants. In this work, as a first step, stability-keeping variants were selected by five rounds of random mutagenesis and screening based on halo formation assay using the substrate tributyrin at 70 °C after heat treatment for 30 min at 90 °C. These variants are likely to be scattered at the feet of various mountains in the fitness landscape. Next, these variants were pooled and used as parental proteins for a conventional experiment with activity-based selection, where the activity of variants was assayed using their cell-free extracts on the substrate p-nitrophenyl butyrate at 75 °C. After two rounds of random mutagenesis, we successfully obtained a variant with 9-fold higher activity than the wild-type. These results indicate that the two-step selection by stability and activity enables us more easily to produce markedly activity-improving variants.

3D-VAR for parameterized partial differential equations: a certified reduced basis approach

In this paper, we propose a reduced order approach for 3D variational data assimilation governed by parameterized partial differential equations. In contrast to the classical 3D-VAR formulation that penalizes the measurement error directly, we present a modified formulation that penalizes the experimentally observable misfit in the measurement space. Furthermore, we include a model correction term that allows to obtain an improved state estimate. We begin by discussing the influence of the measurement space on the amplification of noise and prove a necessary and sufficient condition for the identification of a “good” measurement space. We then propose a certified reduced basis (RB) method for the estimation of the model correction, the state prediction, the adjoint solution, and the observable misfit with respect to the true state for real-time and many-query applications. A posteriori bounds are proposed for the error in each of these approximations. Finally, we introduce different approaches for the generation of the reduced basis spaces and the stability-based selection of measurement functionals. The 3D-VAR method and the associated certified reduced basis approximation are tested in a parameter and state estimation problem for a steady-state thermal conduction problem with unknown parameters and unknown Neumann boundary conditions.

Assessment of Stability and Discrimination Capacity of Radiomic Features on Apparent Diffusion Coefficient Images

The objectives of the study are to develop a new way to assess stability and discrimination capacity of radiomic features without the need of test-retest or multiple delineations and to use information obtained to perform a preliminary feature selection. Apparent diffusion coefficient (ADC) maps were computed from diffusion-weighted magnetic resonance images (DW-MRI) of two groups of patients: 18 with soft tissue sarcomas (STS) and 18 with oropharyngeal cancers (OPC). Sixty-nine radiomic features were computed, using three different histogram discretizations (16, 32, and 64 bins). Geometrical transformations (translations) of increasing entity were applied to the regions of interest (ROIs), and the intra-class correlation coefficient (ICC) was used to compare the features computed on the original and modified ROIs. The distribution of ICC values for minimal and maximal entity translations (ICC10 and ICC100, respectively) was used to adjust thresholds of ICC (ICCmin and ICCmax) used to discriminate between good, unstable (ICC10 < ICCmin), and non-discriminative features (ICC100 > ICCmax). Fifty-four and 59 radiomic features passed the stability-based selection for all the three histogram discretizations for the OPC and STS datasets, respectively. The excluded features were similar across the different histogram discretizations (Jaccard’s index 0.77 ± 0.13 and 0.9 ± 0.1 for OPC and STS, respectively) but different between datasets (Jaccard’s index 0.19 ± 0.02). The results suggest that the observed radiomic features are mainly stable and discriminative, but the stability depends on the region of the body under observation. The method provides a way to assess stability without the need of test-retest or multiple delineations.

Performance of variable selection methods using stability-based selection

BackgroundVariable selection is frequently carried out during the analysis of many types of high-dimensional data, including those in metabolomics. This study compared the predictive performance of four variable selection methods using stability-based selection, a new secondary selection method that is implemented in the R package BioMark. Two of these methods were evaluated using the more well-known false discovery rate (FDR) as well.ResultsSimulation studies varied factors relevant to biological data studies, with results based on the median values of 200 partial area under the receiver operating characteristic curve. There was no single top performing method across all factor settings, but the student t test based on stability selection or with FDR adjustment and the variable importance in projection (VIP) scores from partial least squares regression models obtained using a stability-based approach tended to perform well in most settings. Similar results were found with a real spiked-in metabolomics dataset. Group sample size, group effect size, number of significant variables and correlation structure were the most important factors whereas the percentage of significant variables was the least important.ConclusionsResearchers can improve prediction scores for their study data by choosing VIP scores based on stability variable selection over the other approaches when the number of variables is small to modest and by increasing the number of samples even moderately. When the number of variables is high and there is block correlation amongst the significant variables (i.e., true biomarkers), the FDR-adjusted student t test performed best. The R package BioMark is an easy-to-use open-source program for variable selection that had excellent performance characteristics for the purposes of this study.

Stability-based selection of cutting parameters to increase material removal rate in high-speed machining process

The reasonable selection of cutting parameters is of great significance to improve the productivity in high-speed machining process. In this article, a stability-based selection method of cutting parameters is proposed to increase material removal rate in high-speed machining process. First, the coupled dynamics of the high-speed spindle system and machining process is modeled. Then, the interaction mechanism between the spindle-tool system and the cutting process is investigated. Based on the process stability and surface quality of workpiece, a cutting parameter selection method is proposed from the perspective of machining stability. In order to select reasonable spindle speed and depth of cut, the lower bound of chatter stability lobe diagram and surface finish are taken as constraints, and the maximum material removal rate is set as the target. The proposed method is applied to the machining of the front face of a gearbox cover, which is made of Aluminum-7050. The axial depth of cut and spindle speed are chosen reasonably with the increase in machining efficiency by about 133%.

A Model for Protein Sequence Evolution Based on Selective Pressure for Protein Stability: Application to Hemoglobins

Negative selection against protein instability is a central influence on evolution of proteins. Protein stability is maintained over evolution despite changes in underlying sequences. An empirical all-site stability-based model of evolution was developed to focus on the selection of residues arising from their contributions to protein stability. In this model, site rates could vary. A structure-based method was used to predict stationary frequencies of hemoglobin residues based on their propensity to promote protein stability at a site. Sites with destabilizing residues were shown to change more rapidly in hemoglobins than sites with stabilizing residues. For diverse proteins the results were consistent with stability-based selection. Maximum likelihood studies with hemoglobins supported the stability-based model over simple Poisson-based methods. These observations are consistent with suggestions that purifying selection to maintain protein structural stability plays a dominant role in protein evolution.

Core-directed protein design. II. Rescue of a multiply mutated and destabilized variant of ubiquitin.

We have applied the method described in the preceding paper [Finucane, M. D., et al. (1999) Biochemistry 38, 11604-11612], namely, stability-based selection using phage display, to explore the sequence requirements for packing in the hydrophobic core of ubiquitin. In contrast to the parent protein, which was a structurally compromised mutant, the selected variants could be overexpressed and purified in yields for structural studies. In particular, CD and NMR measurements showed that the selectants folded correctly to stable native-like structures. These points demonstrate the utility of our core-directed method for stabilizing and redesigning proteins. In addition and in contrast to foregoing studies on other proteins, which suggest that hydrophobic cores permit substitutions provided that hydrophobicity and core volumes are generally conserved, we find that the core of ubiquitin is surprisingly intolerant of amino acid substitutions; variants that survived our selection showed a clear consensus for the wild-type sequence. It is probable that our results differed from those from other groups for two reasons. First, ubiquitin may be unusual in that it has strict sequence requirements for its structure and stability. We discuss this result in light of sequence conservation in the eukaryotic ubiquitins and proteins of the ubiquitin structural superfamily. Second, our mutants were selected solely on the basis of stability, in contrast to the other studies that rely on function-based selection. The latter may lead to proteins that are more plastic and tolerant of substitutions.