An Avida-ED digital evolution curriculum for undergraduate biology

We present an inquiry-based curriculum based on the digital evolution platform Avida-ED (http://avida-ed.msu.edu). We designed an instructional sequence and lab book consisting of an introduction to Avida-ED and a set of three lessons focused on specific evolutionary concepts. These served to familiarize students with experimental evolution and Avida-ED. Students then developed independent Avida-ED research projects to test their own questions. Curriculum design and implementation occurred over the course or two semesters, with a pilot implementation in the first semester, followed by curriculum revision and full implementation in the second semester. The curriculum was implemented in an undergraduate Introductory Cell and Molecular Biology course at a major research university. Full implementation of the curriculum in semester two involved the use of Avida-ED mainly in the teaching lab in parallel with a bacterial antibiotic resistance experimental research stream, allowing students to draw connections between Avidian digital evolution and the evolution of antibiotic resistance in microbial populations. After carrying out the introductory exercises, students developed independent Avida-ED projects to test their own research questions, and presented their data to researchers in the NSF-funded BEACON Center for the Study of Evolution in Action. Preliminary results of our studies to assess the impacts of an Avida-ED curriculum indicate a positive effect on student learning of evolutionary concepts, particularly in increasing the level of complexity of student explanations about the random nature of mutation.     

An examination of the OMIM database for associating mutation to a consensus reference sequence

Gene mutation (e.g. substitution, insertion and deletion) and related phenotype information are important biomedical knowledge. Many biomedical databases (e.g. OMIM) incorporate such data. However, few studies have examined the quality of this data. In the current study, we examined the quality of protein single-point mutations in the OMIM and identified whether the corresponding reference sequences align with the mutation positions. Our results show that close to 20% of mutation data cannot be mapped to a single reference sequence. The failed mappings are caused by position conflict, site shifting (peptide, N-terminal methionine) and other types of data error. We propose a preliminary model to resolve such inconsistency in the OMIM database.     

The use of small groups in a large lecture microbiology course

In the fall of 1997, we started using small groups in our large (100–200 students) junior level introductory microbiology course. Students form five-person groups early in the semester, and work on projects within these groups throughout the semester. These projects involve exploration of concepts such as metabolism, protein synthesis, and viral reproduction strategies and the submission of a poster describing a disease of their choice at the end of the semester. We have refined the use of the small groups during the last three semesters, and student acceptance and performance have improved steadily. In the fall semester of 1998, a comprehensive assessment of the effectiveness of these group projects was performed. Students were chosen at random to participate in student consultation groups to discuss group projects. Furthermore, we utilized a master teacher-in-residence from the Rocky Mountain Teachers Education Collaborative (RMTEC). This teacher-in-residence attended our classes, spoke with students, helped with student consultation groups, and provided observations of student responses to group work activities. RMTEC also provided funds to hire a research assistant to conduct student consultation groups, analyze student evaluations of our course, and compare evaluations from before and after the implementation of group examinations. Additionally, the Center for Teaching and Learning at Colorado State University assisted with mid-semester evaluations in each subsequent semester. The results of our analysis show that small groups in large lectures can be an effective learning tool provided students are given well-designed activities with clearly defined, obtainable goals and clearly articulated guidelines. Our experience also shows that the manner in which the instructor presents the process to students affects students' willingness to participate in the process. It must be clearly articulated to students why he has incorporated active learning strategies into the course, what he hopes students will gain from the experience, and how he expects students to participate in these activities. We recognize the increase in workload on ourselves as instructors, but the benefits seem worth the additional time and effort. This paper describes the group process that we use and provides an evaluation of the effort. Journal of Industrial Microbiology & Biotechnology (2000) 25, 121–126. Received 24 March 1999/ Accepted in revised form 23 November 1999     

Medical students' attitudes toward genetic testing of minors

The purpose of this study was to examine attitudes of medical students at a single university toward genetic testing in minors, defining attitudes as willingness to offer testing, and reasons for offering or not offering testing. A survey was distributed to all University of Arizona medical students (n = 428) during the 2003-2004 academic year. The survey consisted of three clinical vignettes concerning genetic testing for Huntington's disease (HD), BRCA1 breast cancer predisposition mutation, and cystic fibrosis (CF) carrier status. For each vignette, students responded to whether they would provide testing for a 7-year-old, a 17-year-old, and their reasons for each age and condition. One hundred thirty-five students (31.5%) responded to the survey. Medical students were significantly more likely to test a 7-year-old for CF carrier status (57%), than they were for a BRCA1 mutation (47%), and an HD mutation (40%). Students were significantly more likely to test a 17-year-old than a 7-year-old in each clinical scenario. Students who had completed a genetics course in medical school were significantly less likely to test a 7-year-old for a BRCA1 mutation than those who had not completed a formal course. Medical students' willingness to perform genetic testing in a minor is influenced by the type of condition, the age of the minor being tested, and the amount of genetics education received in medical school.     

Learning how scientists work: experiential research projects to promote cell biology learning and scientific process skills

Facilitating not only the mastery of sophisticated subject matter, but also the development of process skills is an ongoing challenge in teaching any introductory undergraduate course. To accomplish this goal in a sophomore-level introductory cell biology course, I require students to work in groups and complete several mock experiential research projects that imitate the professional activities of the scientific community. I designed these projects as a way to promote process skill development within content-rich pedagogy and to connect text-based and laboratory-based learning with the world of contemporary research. First, students become familiar with one primary article from a leading peer-reviewed journal, which they discuss by means of PowerPoint-based journal clubs and journalism reports highlighting public relevance. Second, relying mostly on primary articles, they investigate the molecular basis of a disease, compose reviews for an in-house journal, and present seminars in a public symposium. Last, students author primary articles detailing investigative experiments conducted in the lab. This curriculum has been successful in both quarter-based and semester-based institutions. Student attitudes toward their learning were assessed quantitatively with course surveys. Students consistently reported that these projects significantly lowered barriers to primary literature, improved research-associated skills, strengthened traditional pedagogy, and helped accomplish course objectives. Such approaches are widely suited for instructors seeking to integrate process with content in their courses.     

Compensated Pathogenic Deviations: Analysis of Structural Effects

Pathogenic deviations (PDs) in humans are disease-causing missense mutations. However, in some cases, these disease-associated residues occur as the wild-type residues in functionally equivalent proteins in other species and these cases are termed ‘compensated pathogenic deviations’ (CPDs). The lack of pathogenicity in a non-human protein is presumed to be explained in most cases by the presence of compensatory mutations, most commonly within the same protein. Identification of structural features of CPDs and detection of specific compensatory events will help us to understand traversal along fitness landscape valleys in protein evolution.We divided mutations listed in the OMIM (Online Mendelian Inheritance in Man) database into PD and CPD data sets and performed two independent analyses: (i) We searched for potential compensatory mutations spatially close to the CPDs and, (ii) using our SAAPdb database, we examined likely structural effects to try to explain why mutations are pathogenic, comparing PDs and CPDs. Our data sets were obtained from a set of 245 human proteins of known structure and contained a total of 2328 mutations of which 453 (from 85 structures) were seen to be compensated in at least one functionally equivalent protein in another (non-human) species.Structural analysis results confirm previous findings that CPDs are, on average, ‘milder’ in their likely structural effects than uncompensated PDs and tend to be on the protein surface. We also showed that the residues surrounding the CPD residue in the folded protein are more often mutated than the residues surrounding an uncompensated mutation, supporting the hypothesis that compensation is largely a result of structurally local mutations.     

Isolation and characterization of Saccharomyces cerevisiae mutants defective in chromosome transmission in an undergraduate genetics research course

An upper-level genetics research course was developed to expose undergraduates to investigative science. Students are immersed in a research project with the ultimate goal of identifying proteins important for chromosome transmission in mitosis. After mutagenizing yeast Saccharomyces cerevisiae cells, students implement a genetic screen that allows for visual detection of mutants with an increased loss of an ADE2-marked yeast artificial chromosome (YAC). Students then genetically characterize the mutants and begin efforts to identify the defective genes in these mutants. While engaged in this research project, students practice a variety of technical skills in both classical and molecular genetics. Furthermore, students learn to collaborate and gain experience in sharing scientific findings with others in the form of written papers, poster presentations, and oral presentations. Previous students indicated that, relative to a traditional laboratory course, this research course improved their understanding of scientific concepts and technical skills and helped them make connections between concepts. Moreover, this course allowed students to experience scientific inquiry and was influential for students as they considered future endeavors.     

Facilities that make the PDB data collection more powerful

We describe a series of databases and tools that directly or indirectly support biomedical research on macromolecules, with focus on their applicability in protein structure bioinformatics research. DSSP, that determines secondary structures of proteins, has been updated to work well with extremely large structures in multiple formats. The PDBREPORT database that lists anomalies in protein structures has been remade to remove many small problems. These reports are now available as PDF‐formatted files with a computer‐readable summary. The VASE software has been added to analyze and visualize HSSP multiple sequence alignments for protein structures. The Lists collection of databases has been extended with a series of databases, most noticeably with a database that gives each protein structure a grade for usefulness in protein structure bioinformatics projects. The PDB‐REDO collection of reanalyzed and re‐refined protein structures that were solved by X‐ray crystallography has been improved by dealing better with sugar residues and with hydrogen bonds, and adding many missing surface loops. All academic software underlying these protein structure bioinformatics applications and databases are now publicly accessible, either directly from the authors or from the GitHub software repository.     

Motif mining: an assessment and perspective for amyloid fibril prediction tool

Amyloid fibril forming regions in protein sequences are associated with a number of diseases. Experimental evidences compel in favor of the hypothesis that short motif regions are responsible for its amyloidogenic behavior. Thus, identifying these short peptides is critical in understanding the cause of diseases associated with aggregation of proteins and developing sequencetargeted anti-aggregation drugs. Owing to the constraints of wet lab molecular techniques for the identification of amyloid fibril forming targets, computational methods are implemented to offer better and affordable in silico predictions. The present study takes into consideration an assessment and perspective of the recent tools available for predicting a peptide status: amyloidogenic or non-amyloidogenic. To the best of our knowledge, the existing review articles on amyloidogenic prediction tools have not touched upon their effectiveness in terms of true positive rates or false positive rates. In this work, we compare few tools such as Aggrescan, Amylpred and FoldAmyloid to evaluate the performance of their predictability based on the experimentally proved data in terms of specificity, sensitivity, Matthews Correlation Coefficient and Balanced accuracy. As evident from the results, a significant reduction of sensitivity associated with a gain in specificity is noted in all the tools considered under the present study.     

Functional and evolutionary analysis of viral proteins containing a Rossmann‐like fold

Viruses are the most abundant life form and infect practically all organisms. Consequently, these obligate parasites are a major cause of human suffering and economic loss. Rossmann‐like fold is the most populated fold among α/β‐folds in the Protein Data Bank and proteins containing Rossmann‐like fold constitute 22% of all known proteins 3D structures. Thus, analysis of viral proteins containing Rossmann‐like domains could provide an understanding of viral biology and evolution as well as could propose possible targets for antiviral therapy. We provide functional and evolutionary analysis of viral proteins containing a Rossmann‐like fold found in the evolutionary classification of protein domains (ECOD) database developed in our lab. We identified 81 protein families of bacterial, archeal, and eukaryotic viruses in light of their evolution‐based ECOD classification and Pfam taxonomy. We defined their functional significance using enzymatic EC number assignments as well as domain‐level family annotations.     

DR-GAS: A database of functional genetic variants and their phosphorylation states in human DNA repair systems

We present DR-GAS¹, a unique, consolidated and comprehensive DNA repair genetic association studies database of human DNA repair system. It presents information on repair genes, assorted mechanisms of DNA repair, linkage disequilibrium, haplotype blocks, nsSNPs, phosphorylation sites, associated diseases, and pathways involved in repair systems. DNA repair is an intricate process which plays an essential role in maintaining the integrity of the genome by eradicating the damaging effect of internal and external changes in the genome. Hence, it is crucial to extensively understand the intact process of DNA repair, genes involved, non-synonymous SNPs which perhaps affect the function, phosphorylated residues and other related genetic parameters. All the corresponding entries for DNA repair genes, such as proteins, OMIM IDs, literature references and pathways are cross-referenced to their respective primary databases. DNA repair genes and their associated parameters are either represented in tabular or in graphical form through images elucidated by computational and statistical analyses. It is believed that the database will assist molecular biologists, biotechnologists, therapeutic developers and other scientific community to encounter biologically meaningful information, and meticulous contribution of genetic level information towards treacherous diseases in human DNA repair systems. DR-GAS is freely available for academic and research purposes at: http://www.bioinfoindia.org/drgas.     

Rapid Annotation of Anonymous Sequences from Genome Projects Using Semantic Similarities and a Weighting Scheme in Gene Ontology

Background

Large-scale sequencing projects have now become routine lab practice and this has led to the development of a new generation of tools involving function prediction methods, bringing the latter back to the fore. The advent of Gene Ontology, with its structured vocabulary and paradigm, has provided computational biologists with an appropriate means for this task.

Methodology

We present here a novel method called ARGOT (Annotation Retrieval of Gene Ontology Terms) that is able to process quickly thousands of sequences for functional inference. The tool exploits for the first time an integrated approach which combines clustering of GO terms, based on their semantic similarities, with a weighting scheme which assesses retrieved hits sharing a certain number of biological features with the sequence to be annotated. These hits may be obtained by different methods and in this work we have based ARGOT processing on BLAST results.

Conclusions

The extensive benchmark involved 10,000 protein sequences, the complete S. cerevisiae genome and a small subset of proteins for purposes of comparison with other available tools. The algorithm was proven to outperform existing methods and to be suitable for function prediction of single proteins due to its high degree of sensitivity, specificity and coverage.     

Founder mutations in hypertrophic cardiomyopathy patients in the Netherlands

In this part of a series on cardiogenetic founder mutations in the Netherlands, we review the Dutch founder mutations in hypertrophic cardiomyopathy (HCM) patients. HCM is a common autosomal dominant genetic disease affecting at least one in 500 persons in the general population. Worldwide, most mutations in HCM patients are identified in genes encoding sarcomeric proteins, mainly in the myosin-binding protein C gene (MYBPC3, OMIM #600958) and the beta myosin heavy chain gene (MYH7, OMIM #160760). In the Netherlands, the great majority of mutations occur in the MYBPC3, involving mainly three Dutch founder mutations in the MYBPC3 gene, the c.2373_2374insG, the c.2864_2865delCT and the c.2827C>T mutation. In this review, we describe the genetics of HCM, the genotype-phenotype relation of Dutch founder MYBPC3 gene mutations, the prevalence and the geographic distribution of the Dutch founder mutations, and the consequences for genetic counselling and testing. (Neth Heart J 2010;18:248-54.)     

Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders

Online Mendelian Inheritance in Man (OMIM™) is a comprehensive, authoritative and timely knowledgebase of human genes and genetic disorders compiled to support research and education in human genomics and the practice of clinical genetics. Started by Dr Victor A. McKusick as the definitive reference Mendelian Inheritance in Man, OMIM (www.ncbi.nlm.nih.gov/omim) is now distributed electronically by the National Center for Biotechnology Information (NCBI), where it is integrated with the Entrez suite of databases. Derived from the biomedical literature, OMIM is written and edited at Johns Hopkins University with input from scientists and physicians around the world. Each OMIM entry has a full-text summary of a genetically determined phenotype and/or gene and has numerous links to other genetic databases such as DNA and protein sequence, PubMed references, general and locus-specific mutation databases, approved gene nomenclature, and the highly detailed mapviewer, as well as patient support groups and many others. OMIM is an easy and straightforward portal to the burgeoning information in human genetics.     

Meta-omic evaluation of bacterial microbial community structure and activity for the environmental assessment of soils: overcoming protein extraction pitfalls

Microorganisms play unique, essential and integral roles in the biosphere. This work aims to assess the utility of soil's metaomics for environmental diagnosis. Doñana National Park (DNP) was selected as a natural lab since it contains a strictly protected core that is surrounded by numerous threats of pollution. Culture-independent high-throughput molecular tools were used to evaluate the alterations of the global structure and metabolic activities of the microbiome. 16S rRNA sequencing shows lower bacterial abundance and diversity in areas historically exposed to contamination that surround DNP. For metaproteomics, an innovative post-alkaline protein extraction protocol was developed. After NaOH treatment, successive washing with Tris–HCl buffer supplemented with glycerol was essential to eliminate interferences. Starting from soils with different physicochemical characteristics, the method renders proteins with a remarkable resolution on SDS-PAGE gels. The proteins extracted were analysed by using an in-house database constructed from the rRNA data. LC–MS/MS analysis identified 2182 non-redundant proteins with 135 showing significant differences in relative abundance in the soils around DNP. Relevant global biological processes were altered in response to the environmental changes, such as protective and antioxidant mechanisms, translation, folding and homeostasis of proteins, membrane transport and aerobic respiratory metabolism.     

Carrying BioMath Education in a Leaky Bucket

In this paper, we describe a project-based mathematical lab implemented in our Applied Mathematics in Biology course. The Leaky Bucket Lab allows students to parameterize and test Torricelli's law and develop and compare their own alternative models to describe the dynamics of water draining from perforated containers. In the context of this lab students build facility in a variety of applied biomathematical tools and gain confidence in applying these tools in data-driven environments. We survey analytic approaches developed by students to illustrate the creativity this encourages as well as prepare other instructors to scaffold the student learning experience. Pedagogical results based on classroom videography support the notion that the Biology-Applied Math Instructional Model, the teaching framework encompassing the lab, is effective in encouraging and maintaining high-level cognition among students. Research-based pedagogical approaches that support the lab are discussed.     

Combining experimental and predicted datasets for determination of the subcellular location of proteins in Arabidopsis

Substantial experimental datasets defining the subcellular location of Arabidopsis (Arabidopsis thaliana) proteins have been reported in the literature in the form of organelle proteomes built from mass spectrometry data (approximately 2,500 proteins). Subcellular location for specific proteins has also been published based on imaging of chimeric fluorescent fusion proteins in intact cells (approximately 900 proteins). Further, the more diverse history of biochemical determination of subcellular location is stored in the entries of the Swiss-Prot database for the products of many Arabidopsis genes (approximately 1,800 proteins). Combined with the range of bioinformatic targeting prediction tools and comparative genomic analysis, these experimental datasets provide a powerful basis for defining the final location of proteins within the wide variety of subcellular structures present inside Arabidopsis cells. We have analyzed these published experimental and prediction data to answer a range of substantial questions facing researchers about the veracity of these approaches to determining protein location and their interrelatedness. We have merged these data to form the subcellular location database for Arabidopsis proteins (SUBA), providing an integrated understanding of protein location, encompassing the plastid, mitochondrion, peroxisome, nucleus, plasma membrane, endoplasmic reticulum, vacuole, Golgi, cytoskeleton structures, and cytosol (www.suba.bcs.uwa.edu.au). This includes data on more than 4,400 nonredundant Arabidopsis protein sequences. We also provide researchers with an online resource that may be used to query protein sets or protein families and determine whether predicted or experimental location data exist; to analyze the nature of contamination between published proteome sets; and/or for building theoretical subcellular proteomes in Arabidopsis using the latest experimental data.     

The Nuclear Protein Database (NPD): sub-nuclear localisation and functional annotation of the nuclear proteome

The Nuclear Protein Database (NPD) is a curated database that contains information on more than 1300 vertebrate proteins that are thought, or are known, to localise to the cell nucleus. Each entry is annotated with information on predicted protein size and isoelectric point, as well as any repeats, motifs or domains within the protein sequence. In addition, information on the sub-nuclear localisation of each protein is provided and the biological and molecular functions are described using Gene Ontology (GO) terms. The database is searchable by keyword, protein name, sub-nuclear compartment and protein domain/motif. Links to other databases are provided (e.g. Entrez, SWISS-PROT, OMIM, PubMed, PubMed Central). Thus, NPD provides a gateway through which the nuclear proteome may be explored. The database can be accessed at http://npd.hgu.mrc.ac.uk and is updated monthly.     

Testing for Starch,Respiring Tissues,and Vascular Bundles: Inquiry-Based Seed and Stem Anatomy Labs

In this article, the authors present lab exercises in which students use the microscope to study cells. After learning how to recognize the parts of a cell, differentiate between types of cells, and identify the nucleus, the students study blood samples from both familiar and “unknown” animals. The activities allow students to work independently and to become more proficient at microscope use. Students also gain a deeper understanding of the more “invisible” world of science.