Visualizing the Invisible: A Guide to Designing, Printing, and Incorporating Dynamic 3D Molecular Models to Teach Structure–Function Relationships

Understanding the intricate relationship between macromolecular structure and function represents a central goal of undergraduate biology education (1–3). In teaching complex three-dimensional (3D) concepts, instructors typically depend on static two-dimensional (2D) textbook images or computer-based visualization software, which can lead to unintended misconceptions (4–6). While chemical and molecular kits exist, these models cannot handle the size and detail of macromolecules. Consequently, students may graduate in the life sciences without understanding how structure underlies function or acquiring skills to translate between 2D and 3D molecular models (5, 7). Building on recent technological advances, 3D printing (3DP) potentiates an era in which students learn through direct interaction with dynamic 3D structural models. With 3DP, instructors have the opportunity to use tailor-made models of virtually any size molecule. For example, protein models can be designed to relate enzyme active site structures to kinetic activity. Furthermore, instructors can use diverse printing materials and accessories to demonstrate molecular properties, dynamics, and interactions (Fig. 1). In this article and supplemental guide, we present an example of how to incorporate a 3D model-based lesson on DNA supercoiling in an undergraduate biochemistry classroom and best practices for designing and printing 3D models

Student Understanding of DNA Structure–Function Relationships Improves from Using 3D Learning Modules with Dynamic 3D Printed Models

Understanding the relationship between molecular structure and function represents an important goal of undergraduate life sciences. Although evidence suggests that handling physical models supports gains in student understanding of structure–function relationships, such models have not been widely implemented in biochemistry classrooms. Three-dimensional (3D) printing represents an emerging cost-effective means of producing molecular models to help students investigate structure–function concepts. We developed three interactive learning modules with dynamic 3D printed models to help biochemistry students visualize biomolecular structures and address particular misconceptions. These modules targeted specific learning objectives related to DNA and RNA structure, transcription factor-DNA interactions, and DNA supercoiling dynamics. We also designed accompanying assessments to gauge student learning. Students responded favorably to the modules and showed normalized learning gains of 49% with respect to their ability to understand and relate molecular structures to biochemical functions. By incorporating accurate 3D printed structures, these modules represent a novel advance in instructional design for biomolecular visualization. We provide instructors with the materials necessary to incorporate each module in the classroom, including instructions for acquiring and distributing the models, activities, and assessments. 9 supplemental files attached (below

Subjective versus objective risk in genetic counseling for hereditary breast and/or ovarian cancers

Background. Despite the fact that genetic counseling in oncology provides information regarding objective risks, it can be found a contrast between the subjective and objective risk. The aims of this study were to evaluate the accuracy of the perceived risk compared to the objective risk estimated by the BRCApro computer model and to evaluate any associations between medical, demographic and psychological variables and the accuracy of risk perception. Methods. 130 subjects were given medical-demographic file, Cancer and Genetic Risk Perception, Hospital Anxiety-Depression Scale. It was also computed an objective evaluation of the risk by the BRCApro model. Results. The subjective risk was significantly higher than objective risk. The risk of tumour was overestimated by 56%, and the genetic risk by 67%. The subjects with less cancer affected relatives significantly overestimated their risk of being mutation carriers and made a more innacurate estimation than high risk subjects. Conclusion. The description of this sample shows: general overestimation of the risk, inaccurate perception compared to BRCApro calculation and a more accurate estimation in those subjects with more cancer affected relatives (high risk subjects). No correlation was found between the levels of perception of risk and anxiety and depression. Based on our findings, it is worth pursuing improved communication strategies about the actual cancer and genetic risk, especially for subjects at "intermediate and slightly increased risk" of developing an hereditary breast and/or ovarian cancer or of being mutation carrier

Predicted Benign and Synonymous Variants in CYP11A1 Cause Primary Adrenal Insufficiency Through Missplicing.

Primary adrenal insufficiency (PAI) is a potentially life-threatening condition that can present with nonspecific features and can be difficult to diagnose. We undertook next generation sequencing in a cohort of children and young adults with PAI of unknown etiology from around the world and identified a heterozygous missense variant (rs6161, c.940G>A, p.Glu314Lys) in CYP11A1 in 19 individuals from 13 different families (allele frequency within undiagnosed PAI in our cohort, 0.102 vs 0.0026 in the Genome Aggregation Database; P A, Thr330 = ; c.1173C>T, Ser391 =). Although p.Glu314Lys is predicted to be benign and showed no loss-of-function in an Escherichia coli assay system, in silico and in vitro studies revealed that the rs6161/c.940G>A variant, plus the c.990G>A and c.1173C>T changes, affected splicing and that p.Glu314Lys produces a nonfunctional protein in mammalian cells. Taken together, these findings show that compound heterozygosity involving a relatively common and predicted "benign" variant in CYP11A1 is a major contributor to PAI of unknown etiology, especially in European populations. These observations have implications for personalized management and demonstrate how variants that might be overlooked in standard analyses can be pathogenic when combined with other very rare disruptive changes.Medical Research Council UK Project (grant MR/K020455/1 to L.A.M.).J.C.A. is a Wellcome Trust Senior Research Fellow in Clinical Science (grants 098513/Z/12/Z and 209328/Z/17/Z) with research support from Great Ormond Street Hospital Children’s Charity (grant V2518) and the National Institute for Health Research, Great Ormond Street Hospital Biomedical Research Centre (grant IS-BRC-1215-20012).Funding also included support from The Mater Medical Research Institute (to M.H.) and National Institutes of Health (grant R01GM086596 to R.J.A.)

Visualizing the Invisible: A Guide to Designing, Printing, and Incorporating Dynamic 3D Molecular Models to Teach Structure–Function Relationships

Understanding the intricate relationship between macromolecular structure and function represents a central goal of undergraduate biology education (1–3). In teaching complex three-dimensional (3D) concepts, instructors typically depend on static two-dimensional (2D) textbook images or computer-based visualization software, which can lead to unintended misconceptions (4–6). While chemical and molecular kits exist, these models cannot handle the size and detail of macromolecules. Consequently, students may graduate in the life sciences without understanding how structure underlies function or acquiring skills to translate between 2D and 3D molecular models (5, 7). Building on recent technological advances, 3D printing (3DP) potentiates an era in which students learn through direct interaction with dynamic 3D structural models. With 3DP, instructors have the opportunity to use tailor-made models of virtually any size molecule. For example, protein models can be designed to relate enzyme active site structures to kinetic activity. Furthermore, instructors can use diverse printing materials and accessories to demonstrate molecular properties, dynamics, and interactions (Fig. 1). In this article and supplemental guide, we present an example of how to incorporate a 3D model-based lesson on DNA supercoiling in an undergraduate biochemistry classroom and best practices for designing and printing 3D models

Student Understanding of DNA Structure–Function Relationships Improves from Using 3D Learning Modules with Dynamic 3D Printed Models

Understanding the relationship between molecular structure and function represents an important goal of undergraduate life sciences. Although evidence suggests that handling physical models supports gains in student understanding of structure–function relationships, such models have not been widely implemented in biochemistry classrooms. Three-dimensional (3D) printing represents an emerging cost-effective means of producing molecular models to help students investigate structure–function concepts. We developed three interactive learning modules with dynamic 3D printed models to help biochemistry students visualize biomolecular structures and address particular misconceptions. These modules targeted specific learning objectives related to DNA and RNA structure, transcription factor-DNA interactions, and DNA supercoiling dynamics. We also designed accompanying assessments to gauge student learning. Students responded favorably to the modules and showed normalized learning gains of 49% with respect to their ability to understand and relate molecular structures to biochemical functions. By incorporating accurate 3D printed structures, these modules represent a novel advance in instructional design for biomolecular visualization. We provide instructors with the materials necessary to incorporate each module in the classroom, including instructions for acquiring and distributing the models, activities, and assessments. 9 supplemental files attached (below

Teaching Metabolism in Upper-Division Undergraduate Biochemistry Courses using Online Computational Systems and Dynamical Models Improves Student Performance

Understanding metabolic function requires knowledge of the dynamics, interdependence, and regulation of metabolic networks. However, multiple professional societies have recognized that most undergraduate biochemistry students acquire only a surface-level understanding of metabolism. We hypothesized that guiding students through interactive computer simulations of metabolic systems would increase their ability to recognize how individual interactions between components affect the behavior of a system under different conditions. The computer simulations were designed with an interactive activity (i.e., module) that used the predict–observe–explain model of instruction to guide students through a process in which they iteratively predict outcomes, test their predictions, modify the interactions of the system, and then retest the outcomes. We found that biochemistry students using modules performed better on metabolism questions compared with students who did not use the modules. The average learning gain was 8% with modules and 0% without modules, a small to medium effect size. We also confirmed that the modules did not create or reinforce a gender bias. Our modules provide instructors with a dynamic, systems-driven approach to help students learn about metabolic regulation and equip students with important cognitive skills, such as interpreting and analyzing simulation results, and technical skills, such as building and simulating computer-based models