The collaboratory for MS3D: a new cyberinfrastructure for the structural elucidation of biological macromolecules and their assemblies using mass spectrometry-based approaches

Modern biomedical research is evolving with the rapid growth of diverse data types, biophysical characterization methods, computational tools and extensive collaboration among researchers spanning various communities and having complementary backgrounds and expertise. Collaborating researchers are increasingly dependent on shared data and tools made available by other investigators with common interests, thus forming communities that transcend the traditional boundaries of the single research laboratory or institution. Barriers, however, remain to the formation of these virtual communities, usually due to the steep learning curve associated with becoming familiar with new tools, or with the difficulties associated with transferring data between tools. Recognizing the need for shared reference data and analysis tools, we are developing an integrated knowledge environment that supports productive interactions among researchers. Here we report on our current collaborative environment, which focuses on bringing together structural biologists working in the area of mass spectrometric based methods for the analysis of tertiary and quaternary macromolecular structures (MS3D) called the Collaboratory for MS3D (C-MS3D). C-MS3D is a Web-portal designed to provide collaborators with a shared work environment that integrates data storage and management with data analysis tools. Files are stored and archived along with pertinent meta data in such a way as to allow file handling to be tracked (data provenance) and data files to be searched using keywords and modification dates. While at this time the portal is designed around a specific application, the shared work environment is a general approach to building collaborative work groups. The goal of this is to not only provide a common data sharing and archiving system, but also to assist in the building of new collaborations and to spur the development of new tools and technologies.     

Vector NTI, a balanced all-in-one sequence analysis suite

Vector NTI is a well-balanced desktop application integrated for molecular sequence analysis and biological data management. It has a centralised database and five application modules: Vector NTI, AlignX, BioAnnotator, ContigExpress and GenomBench. In this review, the features and functions available in this software are examined. These include database management, primer design, virtual cloning, alignments, sequence assembly, 3D molecular viewer and internet tools. Some problems encountered when using this software are also discussed. It is hoped that this review will introduce this software to more molecular biologists so they can make better-informed decisions when choosing computational tools to facilitate their everyday laboratory work. This tool can save time and enhance analysis but it requires some learning on the user's part and there are some issues that need to be addressed by the developer.     

Mobile learning applications to improve invertebrate zoology online teaching

The use of new technologies including personal mobile devices has become an indispensable tool in our daily lives, and thus its presence in education is becoming ever more ubiquitous. In the current scenario imposed by the COVID‐19 pandemic, in which in‐person presence in classrooms has been enormously reduced at all educational levels, the use of mobile learning and cutting‐edge methods can greatly improve the way students learn and enhance their online‐learning experience. Mobile applications, combined with extended reality technologies such as virtual reality (VR) and augmented reality (AR), are powerful tools that connect real and virtual environments and allow higher interaction for the user. We have leveraged the advantages of mobile learning and extended reality technologies to develop a series of mobile applications and associated educational activities for university‐level courses involving invertebrate zoology field work. In particular, we have developed (a) a VR SCUBA diving video to explore the diversity of a marine protected area; (b) an AR mobile app to visualize 3D models of marine invertebrates; and (c) a mobile‐based catalogue to explore the terrestrial biodiversity of one of the most diverse regions of Spain. Here we provide detailed information describing the design and creation of these tools, as well as their application in class, to facilitate and encourage their use in higher education. Despite the relatively recent application of these technologies in education, they have an enormous potential: they improve student motivation and learning, can be adapted to different learning styles, reduce social inequalities, and facilitate inclusiveness and diversity practices in the classroom.     

Virtual laboratories in science education: students’ motivation and experiences in two tertiary biology courses

Potential benefits of simulations and virtual laboratory exercises in natural sciences have been both theorised and studied recently. This study reports findings from a pilot study on student attitude, motivation and self-efficacy when using the virtual laboratory programme Labster. The programme allows interactive learning about the workflows and procedures of biological and biochemical experiments, the operation of relevant apparatuses, including the ability to adjust parameters, and the production of results. The programme was used as supplement to mandatory laboratory exercises in two undergraduate courses (i. microbiology and ii. pharmaceutical toxicology) at the University of Southern Denmark. With a theoretical basis in motivational theories, students’ (n = 73) motivation and attitude towards the virtual exercises were evaluated. After completing virtual laboratory cases, the students felt significantly more confident and comfortable operating laboratory equipment, but they did not feel more motivated to engage in virtual laboratories compared to real laboratories. Teachers observed that students were able to participate in discussions at higher levels than in previous years where the programme was not used. The study concludes that virtual laboratories have the potential to improve students’ pre-laboratory preparation.     

Lectinomics I. Relevance of exogenous plant lectins in biomedical diagnostics

This review focuses on utilization of plant lectins as medical diagnostic reagents and tools. The lectin-related diagnostic is aimed at detection of several diseases connected to alteration of the glycosylation profiles of cells and at identification of microbial and viral agents in clinical microbiology. Certain lectins, proposed for or used as diagnostic tools could even recognize those cellular determinants, which are not detected by available antibodies. Broad information is presented on the lectinomics field, illustrating that lectin diagnostics might become practical alternative to antibody-based diagnostic products. In addition, the rising trend of lectin utilization in biomedical diagnostics might initiate a development of innovative methods based on better analytical technologies. Lectin microarray, a rapid and simple methodology, can be viewed as an example for such initiative. This technology could provide simple and efficient screening tools for analysis of glycosylation patterns in biological samples (cellular extracts, tissues and the whole cells), allowing thus personalized detection of changes associated with carbohydrate-related diseases.     

Performance and scaling behavior of bioinformatic applications in virtualization environments to create awareness for the efficient use of compute resources

The large amount of biological data available in the current times, makes it necessary to use tools and applications based on sophisticated and efficient algorithms, developed in the area of bioinformatics. Further, access to high performance computing resources is necessary, to achieve results in reasonable time. To speed up applications and utilize available compute resources as efficient as possible, software developers make use of parallelization mechanisms, like multithreading. Many of the available tools in bioinformatics offer multithreading capabilities, but more compute power is not always helpful. In this study we investigated the behavior of well-known applications in bioinformatics, regarding their performance in the terms of scaling, different virtual environments and different datasets with our benchmarking tool suite BOOTABLE. The tool suite includes the tools BBMap, Bowtie2, BWA, Velvet, IDBA, SPAdes, Clustal Omega, MAFFT, SINA and GROMACS. In addition we added an application using the machine learning framework TensorFlow. Machine learning is not directly part of bioinformatics but applied to many biological problems, especially in the context of medical images (X-ray photographs). The mentioned tools have been analyzed in two different virtual environments, a virtual machine environment based on the OpenStack cloud software and in a Docker environment. The gained performance values were compared to a bare-metal setup and among each other. The study reveals, that the used virtual environments produce an overhead in the range of seven to twenty-five percent compared to the bare-metal environment. The scaling measurements showed, that some of the analyzed tools do not benefit from using larger amounts of computing resources, whereas others showed an almost linear scaling behavior. The findings of this study have been generalized as far as possible and should help users to find the best amount of resources for their analysis. Further, the results provide valuable information for resource providers to handle their resources as efficiently as possible and raise the user community’s awareness of the efficient usage of computing resources.     

Time Development in the Early History of Social Networks: Link Stabilization,Group Dynamics,and Segregation

Studies of the time development of empirical networks usually investigate late stages where lasting connections have already stabilized. Empirical data on early network history are rare but needed for a better understanding of how social network topology develops in real life. Studying students who are beginning their studies at a university with no or few prior connections to each other offers a unique opportunity to investigate the formation and early development of link patterns and community structure in social networks. During a nine week introductory physics course, first year physics students were asked to identify those with whom they communicated about problem solving in physics during the preceding week. We use these students'' self reports to produce time dependent student interaction networks. We investigate these networks to elucidate possible effects of different student attributes in early network formation. Changes in the weekly number of links show that while roughly half of all links change from week to week, students also reestablish a growing number of links as they progress through their first weeks of study. Using the Infomap community detection algorithm, we show that the networks exhibit community structure, and we use non-network student attributes, such as gender and end-of-course grade to characterize communities during their formation. Specifically, we develop a segregation measure and show that students structure themselves according to gender and pre-organized sections (in which students engage in problem solving and laboratory work), but not according to end-of-coure grade. Alluvial diagrams of consecutive weeks'' communities show that while student movement between groups are erratic in the beginnning of their studies, they stabilize somewhat towards the end of the course. Taken together, the analyses imply that student interaction networks stabilize quickly and that students establish collaborations based on who is immediately available to them and on observable personal characteristics.     

Optimizing genetic circuits by global sensitivity analysis

Artificial genetic circuits are becoming important tools for controlling cellular behavior and studying molecular biosystems. To genetically optimize the properties of complex circuits in a practically feasible fashion, it is necessary to identify the best genes and/or their regulatory components as mutation targets to avoid the mutation experiments being wasted on ineffective regions, but this goal is generally not achievable by current methods. The Random Sampling-High Dimensional Model Representation (RS-HDMR) algorithm is employed in this work as a global sensitivity analysis technique to estimate the sensitivities of the circuit properties with respect to the circuit model parameters, such as rate constants, without knowing the precise parameter values. The sensitivity information can then guide the selection of the optimal mutation targets and thereby reduce the laboratory effort. As a proof of principle, the in vivo effects of 16 pairwise mutations on the properties of a genetic inverter were compared against the RS-HDMR predictions, and the algorithm not only showed good consistency with laboratory results but also revealed useful information, such as different optimal mutation targets for optimizing different circuit properties, not available from previous experiments and modeling.     

Grid computing in image analysis

Diagnostic surgical pathology or tissue–based diagnosis still remains the most reliable and specific diagnostic medical procedure. The development of whole slide scanners permits the creation of virtual slides and to work on so-called virtual microscopes. In addition to interactive work on virtual slides approaches have been reported that introduce automated virtual microscopy, which is composed of several tools focusing on quite different tasks. These include evaluation of image quality and image standardization, analysis of potential useful thresholds for object detection and identification (segmentation), dynamic segmentation procedures, adjustable magnification to optimize feature extraction, and texture analysis including image transformation and evaluation of elementary primitives. Grid technology seems to possess all features to efficiently target and control the specific tasks of image information and detection in order to obtain a detailed and accurate diagnosis. Grid technology is based upon so-called nodes that are linked together and share certain communication rules in using open standards. Their number and functionality can vary according to the needs of a specific user at a given point in time. When implementing automated virtual microscopy with Grid technology, all of the five different Grid functions have to be taken into account, namely 1) computation services, 2) data services, 3) application services, 4) information services, and 5) knowledge services. Although all mandatory tools of automated virtual microscopy can be implemented in a closed or standardized open system, Grid technology offers a new dimension to acquire, detect, classify, and distribute medical image information, and to assure quality in tissue–based diagnosis.     

Assessing student learning

Biology education research has now reached a level of maturity where the expectation is that researchers will assess the effectiveness of their innovation on student learning. This may include an examination of affective outcomes, such as student attitudes and beliefs, as well as student understanding of discipline-based content. A variety of tools are available to generate assessment data, each with certain advantages and disadvantages. They include not only quantitative measures, which lend themselves to familiar statistical analyses, but also qualitative techniques that can provide a rich understanding of complex outcomes. This article describes some of the most commonly used assessment techniques, their advantages and disadvantages, and typical ways such information is reported.     

Realities of illusion: tracing an anthropology of the unreal from Torres Strait to virtual reality

This article examines how perceptual illusions become reliable markers of truth in the context of experimental psychology. As laboratory tools, illusions travel across time, place, and media: from the Torres Strait expedition at the close of the nineteenth century to a contemporary psychology lab that utilizes virtual reality. In this historical and ethnographic study, something that might otherwise be considered misleading (illusion) becomes an epistemological guide. Illusion takes on a reality and in so doing raises questions about what ought and ought not to be considered real. This research thus joins other anthropologies that expand what counts as ‘the real’. These anthropologies of the unreal are proliferating of late and breathe hope back into human and nonhuman futures by reconsidering what constitutes being in the world. The reality of illusion highlights a phenomenological position in which reality is the world as perceptually experienced. Further, as this investigation unfolds in the laboratory, it becomes clear that the unreal is not set apart from but incorporated into knowledge systems.     

The positive impact of team-based virtual microscopy on student learning in physiology and histology

Team-based virtual microscopy and on-line learning were used to transform the first-year Physiology/Histology course at The Johns Hopkins School of Medicine into a student-centered learning environment. Prior to each laboratory session, students were required to view prelaboratory virtual lectures and examine digital slides that had been enhanced with annotations and 2-min microlectures. The laboratory classroom was then used for team-based learning exercises including student presentations and small-group discussions designed to integrate histology and physiology. The results of quantitative assessments indicated an 8- to 14-point increase over the identical final exams given over the past 5 yr. Means (+/-SD) of percent correct answers on the final exam were found to be 75.2% (11.1%), 72.5% (12.6%), 70.5% (12.6%), 73.6% (11.3%), 73.1% (12.2%), and 84.1% (9.1%) for years 2001-2006, respectively. The mean test scores for all other years were statistically lower compared with 2006, as determined by the Bonferroni post hoc multiple-comparison test (P < 0.001 for all years).     

Omiga™: A PC-based sequence analysis tool

Computer-based sequence analysis, notation, and manipulation are a necessity for all molecular biologists working with any but the most simple DNA sequences. As sequence data become increasingly available, tools that can be used to manipulate and annotate individual sequences and sequence elements will become an even more vital implement in the molecular biologist's arsenal. The Omiga DNA and Protein Sequence Analysis Software tool, version 2.0 provides an effective and comprehensive tool for the analysis of both nucleic acid and protein sequences that runs on a standard PC available in every molecular biology laboratory. Omiga allows the import of sequences in several common formats. Upon importing sequences and assigning them to various projects, Omiga allows the user to produce, analyze, and edit sequence alignments. Sequences may also be queried for the presence of restriction sites, sequence motifs, and other sequence features, all of which can be added into the notations accompanying each sequence. This newest version of Omiga also allows for sequencing and polymerase chain reaction (PCR) primer prediction, a functionality missing in earlier versions. Finally, Omiga allows rapid searches for putative coding regions, and Basic Local Alignment Search Tool (BLAST) queries against public databases at the National Center for Biotechnology Information (NCBI).     

Enhancing the learning of evolutionary anthropology skills by combining student‐active teaching with actual and virtual immersion of Master's students in fieldwork,laboratory practice,and dissemination

Higher education in evolutionary anthropology involves providing students with in‐depth knowledge of biological and cultural heritage sites and collections that are frequently inaccessible. Indeed, most sites, fossils, and archaeological remains can be visited or manipulated only rarely and solely by specialists with extensive experience. Owing to the development of 3D and medical imaging techniques, this fragile heritage is now more widely accessible, and in a dynamic way. However, exclusive adoption of virtual teaching and learning has a negative impact on student engagement and, naturally, on exchanges with instructors, and thus cannot be used without some reservations. In the ITAP (Immersion dans les Terrains de l’Anthropologie biologique et de la Préhistoire) project of the higher education STEP (Soutien à la Transformation et à l’Expérimentation Pédagogiques) transformation program at the University of Bordeaux, we combine student‐active teaching with Master''s students fully immersed in ongoing fieldwork, laboratory study, and dissemination of research results in order to develop more individually shaped learning curricula and to foster both professional and new interdisciplinary skills. Here, we present examples of experiments conducted in the ITAP project using both authentic and virtual collections of archaeological, experimental, and reference materials that help to break down the barriers between research activities and higher education, as well as providing a more general appraisal of the appropriate use of virtual tools in higher education by combining them with real‐life situations.     

Testing the effectiveness of two natural selection simulations in the context of a large-enrollment undergraduate laboratory class

Background

Simulations can be an active and engaging way for students to learn about natural selection, and many have been developed, including both physical and virtual simulations. In this study we assessed the student experience of, and learning from, two natural selection simulations, one physical and one virtual, in a large enrollment introductory biology lab course. We assigned students to treatments (the physical or virtual simulation activity) by section and assessed their understanding of natural selection using a multiple-choice pre-/post-test and short-answer responses on a post-lab assignment. We assessed student experience of the activities through structured observations and an affective survey.

Results

Students in both treatments showed increased understanding of natural selection after completing the simulation activity, but there were no differences between treatments in learning gains on the pre-/post-test, or in the prevalence of concepts and misconceptions in written answers. On a survey of self-reported enjoyment they rated the physical activity significantly higher than the virtual activity. In classroom observations of student behavior, we found significant differences in the distribution of behaviors between treatments, including a higher frequency of off-task behavior during the physical activity.

Conclusions

Our results suggest that both simulations are valuable active learning tools to aid students’ understanding of natural selection, so decisions about which simulation to use in a given class, and how to best implement it, can be motivated by contextual factors.

     

Molecular approaches to the study of evolution and phylogeny of the Nemertina

Molecular biological tools currently available to us are revolutionizing the way in which we can address questions in evolutionary biology. The purpose of this article is to provide an overview of molecular techniques and applications available to biologists who are interested in evolutionary studies but who have little acquaintance with molecular biology. In evolutionary biology, techniques designed to determine degree of nucleic acid similarity are in common use and will be dealt with first. Another approach, namely gene expression studies, has strong implications for evolutionary biology but generally requires substantial familiarity with molecular biological tools. Expression studies provide powerful tools for discerning processes of speciation, as in the selection of genetic variants, as well as discerning lineages, e.g., expression of specific homeobox genes during segment formation. For investigations where either nucleic acid identity or gene expression are the ultimate goal, detailed information, protocols and appropriate controls are beyond the scope of this work but, where possible, recent review articles are cited.