Cell Biology & Molecular Genetics Research Works
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Item Maryland Biology Expectations Survey (MBEX) for characterizing student epistemology in biology courses(2024) Hall, Kristi L.; Chatzikyriakidou, Kyriaki; Redish, Edward F.; Cooke, Todd J.The Maryland Biology Expectations Survey (MBEX) is a pre-post survey instrument that was designed by Hall (2013) to evaluate the changes of student epistemology occurring in an introductory biology course (Cooke et al., 2023). The MBEX addresses four epistemic themes: principles vs. facts, independence vs. authority, interdisciplinary reasoning vs. siloed thinking, and connection (= relevance) vs. isolation (Hall, 2013). The major difference between MBEX-1 statements and MBEX-2 statements resides in the interdisciplinary reasoning cluster. MBEX-1 incorporates more chemistry-related statements, whereas MBEX-2 focuses almost exclusively on math and physics. It turns out that biology students showed very favorable attitudes toward chemistry in their pre-course MBEX-1 responses, which reduced the ability of that survey to reveal any post-course changes in student attitudes toward interdisciplinary reasoning. This website includes the following files: • MBEX-1 survey • MBEX-2 survey • Cluster assignments, polarization, and correspondence of MBEX-1 and MBEX-2 statements. For further information, email either Kyriaki Chatzikyriakidou (kchatzikyriak@gmail.com) or Todd Cooke (tjcooke@umd.edu). References Cooke, T. J., Jensen, J. S., Carleton, K. L., Hall, K. L., Jardine, H. E., Kent, B. W., Redish, E.F., and Shultz, J. W. (2023). Group active engagements for facilitating principles-based learning in introductory organismal biology. American Biology Teacher 85 (6): 317–326. https://doi.org/10.1525/abt.2023.85.6.317 Hall, K. L. (2013). Examining the effects of students’ classroom expectations on undergraduate biology course reform. Ph.D. Dissertation in Digital Resources at the University of Maryland. https://drum.lib.umd.edu/items/91d250d1-0890-4adc-a040-6b9c9b5eff40Item Evaluation of AlphaFold antibody–antigen modeling with implications for improving predictive accuracy(Wiley, 2023-12-10) Yin, Rui; Pierce, Brian G.High resolution antibody–antigen structures provide critical insights into immune recognition and can inform therapeutic design. The challenges of experimental structural determination and the diversity of the immune repertoire underscore the necessity of accurate computational tools for modeling antibody–antigen complexes. Initial benchmarking showed that despite overall success in modeling protein–protein complexes, AlphaFold and AlphaFold-Multimer have limited success in modeling antibody–antigen interactions. In this study, we performed a thorough analysis of AlphaFold's antibody–antigen modeling performance on 427 nonredundant antibody–antigen complex structures, identifying useful confidence metrics for predicting model quality, and features of complexes associated with improved modeling success. Notably, we found that the latest version of AlphaFold improves near-native modeling success to over 30%, versus approximately 20% for a previous version, while increased AlphaFold sampling gives approximately 50% success. With this improved success, AlphaFold can generate accurate antibody–antigen models in many cases, while additional training or other optimization may further improve performance.Item Critical assessment of methods of protein structure prediction (CASP)—Round XV(Wiley, 2023-11-02) Kryshtafovych, Andriy; Schwede, Torsten; Topf, Maya; Fidelis, Krzysztof; Moult, JohnComputing protein structure from amino acid sequence information has been a long-standing grand challenge. Critical assessment of structure prediction (CASP) conducts community experiments aimed at advancing solutions to this and related problems. Experiments are conducted every 2 years. The 2020 experiment (CASP14) saw major progress, with the second generation of deep learning methods delivering accuracy comparable with experiment for many single proteins. There is an expectation that these methods will have much wider application in computational structural biology. Here we summarize results from the most recent experiment, CASP15, in 2022, with an emphasis on new deep learning-driven progress. Other papers in this special issue of proteins provide more detailed analysis. For single protein structures, the AlphaFold2 deep learning method is still superior to other approaches, but there are two points of note. First, although AlphaFold2 was the core of all the most successful methods, there was a wide variety of implementation and combination with other methods. Second, using the standard AlphaFold2 protocol and default parameters only produces the highest quality result for about two thirds of the targets, and more extensive sampling is required for the others. The major advance in this CASP is the enormous increase in the accuracy of computed protein complexes, achieved by the use of deep learning methods, although overall these do not fully match the performance for single proteins. Here too, AlphaFold2 based method perform best, and again more extensive sampling than the defaults is often required. Also of note are the encouraging early results on the use of deep learning to compute ensembles of macromolecular structures. Critically for the usability of computed structures, for both single proteins and protein complexes, deep learning derived estimates of both local and global accuracy are of high quality, however the estimates in interface regions are slightly less reliable. CASP15 also included computation of RNA structures for the first time. Here, the classical approaches produced better agreement with experiment than the new deep learning ones, and accuracy is limited. Also, for the first time, CASP included the computation of protein–ligand complexes, an area of special interest for drug design. Here too, classical methods were still superior to deep learning ones. Many new approaches were discussed at the CASP conference, and it is clear methods will continue to advance.Item Breaking the conformational ensemble barrier: Ensemble structure modeling challenges in CASP15(Wiley, 2023-10-23) Kryshtafovych, Andriy; Montelione, Gaetano T.; Rigden, Daniel J.; Mesdaghi, Shahram; Karaca, Ezgi; Moult, Johnor the first time, the 2022 CASP (Critical Assessment of Structure Prediction) community experiment included a section on computing multiple conformations for protein and RNA structures. There was full or partial success in reproducing the ensembles for four of the nine targets, an encouraging result. For protein structures, enhanced sampling with variations of the AlphaFold2 deep learning method was by far the most effective approach. One substantial conformational change caused by a single mutation across a complex interface was accurately reproduced. In two other assembly modeling cases, methods succeeded in sampling conformations near to the experimental ones even though environmental factors were not included in the calculations. An experimentally derived flexibility ensemble allowed a single accurate RNA structure model to be identified. Difficulties included how to handle sparse or low-resolution experimental data and the current lack of effective methods for modeling RNA/protein complexes. However, these and other obstacles appear addressable.Item Prospects for developing an Hepatitis C virus E1E2-based nanoparticle vaccine(Wiley, 2023-08-11) Toth, Eric A.; Andrianov, Alexander K.; Fuerst, Thomas R.Globally, more than 58 million people are chronically infected with Hepatitis C virus (HCV) with 1.5 million new infections occurring each year. An effective vaccine for HCV is therefore a major unmet medical and public health need. Since HCV rapidly accumulates mutations, vaccines must elicit the production of broadly neutralising antibodies (bnAbs) in a reproducible fashion. Decades of research have generated a number of HCV vaccine candidates. Based on the available data and research through clinical development, a vaccine antigen based on the E1E2 glycoprotein complex appears to be the best choice, but robust induction of humoral and cellular responses leading to virus neutralisation has not yet been achieved. One issue that has arisen in developing an HCV vaccine (and many other vaccines as well) is the platform used for antigen delivery. The majority of viral vaccine trials have employed subunit vaccines. However, subunit vaccines often have limited immunogenicity, as seen for HCV, and thus multiple formats must be examined in order to elicit a robust anti-HCV immune response. Nanoparticle vaccines are gaining prominence in the field due to their ability to facilitate a controlled multivalent presentation and trafficking to lymph nodes, where they can interact with both arms of the immune system. This review discusses the potential for development of a nanoparticle-based HCV E1E2 vaccine, with an emphasis on the potential benefits of such an approach along with the major challenges facing the incorporation of E1E2 into nanoparticulate delivery systems and how those challenges can be addressed.Item Rosaceae fruit transcriptome database (ROFT)—a useful genomic resource for comparing fruits of apple, peach, strawberry, and raspberry(Wiley, 2023-11-14) Li, Muzi; Mount, Stephen M.; Liu, ZhongchiRosaceae is a large plant family consisting of many economically important fruit crops including peach, apple, pear, strawberry, raspberry, plum, and others. Investigations into their growth and development will promote both basic understanding and progress toward increasing fruit yield and quality. With the ever-increasing high-throughput sequencing data of Rosaceae, comparative studies are hindered by inconsistency of sample collection with regard to tissue, stage, growth conditions, and by vastly different handling of the data. Therefore, databases that enable easy access and effective utilization of directly comparable transcript data are highly desirable. Here, we describe a database for comparative analysis, ROsaceae Fruit Transcriptome database (ROFT), based on RNA-seq data generated from the same laboratory using similarly dissected and staged fruit tissues of four important Rosaceae fruit crops: apple, peach, strawberry, and red raspberry. Hence, the database is unique in allowing easy and robust comparisons among fruit gene expression across the four species. ROFT enables researchers to query orthologous genes and their expression patterns during different fruit developmental stages in the four species, identify tissue-specific and tissue-/stage-specific genes, visualize and compare ortholog expression in different fruit types, explore consensus co-expression networks, and download different data types. The database provides users access to vast amounts of RNA-seq data across the four economically important fruits, enables investigations of fruit type specification and evolution, and facilitates the selection of genes with critical roles in fruit development for further studies.Item Genomic diversity of Vibrio spp. and metagenomic analysis of pathogens in Florida Gulf coastal waters following Hurricane Ian(American Society for Microbiology, 2023-10) Brumfield, Kyle D.; Usmani, Moiz; Santiago, Sanneri; Singh, Komalpreet; Gangwar, Mayank; Hasan, Nur A.; Netherland, Michael Jr.; Deliz, Katherine; Angelini, Christine; Beatty, Norman L.; Huq, Anwar; Jutla, Antarpreet S.; Colwell, Rita R.Changing climatic conditions influence parameters associated with the growth of pathogenic Vibrio spp. in the environment and, hence, are linked to increased incidence of vibriosis. Between 1992 and 2022, a long-term increase in Vibrio spp. infections was reported in Florida, USA. Furthermore, a spike in Vibrio spp. infections was reported post Hurricane Ian, a category five storm that made landfall in Florida on 28 September 2022. During October 2022, water and oyster samples were collected from three stations in Lee County in an area significantly impacted by Ian. Vibrio spp. were isolated, and whole-genome sequencing and phylogenetic analysis were done, with a focus on Vibrio parahaemolyticus and Vibrio vulnificus to provide genetic insight into pathogenic strains circulating in the environment. Metagenomic analysis of water samples provided insight with respect to human health-related factors, notably the detection of approximately 12 pathogenic Vibrio spp., virulence and antibiotic resistance genes, and mobile genetic elements, including the SXT/R391 family of integrative conjugative elements. Environmental parameters were monitored as part of a long-term time series analysis done using satellite remote sensing. In addition to anomalous rainfall and storm surge, changes in sea surface temperature and chlorophyll concentration during and after Ian favored the growth of Vibrio spp. In conclusion, genetic analysis coupled with environmental data and remote sensing provides useful public health information and, hence, constitute a valuable tool to proactively detect and characterize environmental pathogens, notably vibrios. These data can aid the development of early warning systems by yielding a larger source of information for public health during climate change.Item simpleaf: a simple, flexible, and scalable framework for single-cell data processing using alevin-fry(OUP Bioinformatics, 2023-10-06) He, Dongze; Patro, Rob; Patro, RobThe alevin-fry ecosystem provides a robust and growing suite of programs for single-cell data processing. However, as new single-cell technologies are introduced, as the community continues to adjust best practices for data processing, and as the alevin-fry ecosystem itself expands and grows, it is becoming increasingly important to manage the complexity of alevin-fry’s single-cell preprocessing workflows while retaining the performance and flexibility that make these tools enticing. We introduce simpleaf, a program that simplifies the processing of single-cell data using tools from the alevin-fry ecosystem, and adds new functionality and capabilities, while retaining the flexibility and performance of the underlying tools. Simpleaf is written in Rust and released under a BSD 3-Clause license. It is freely available from its GitHub repository https://github.com/COMBINE-lab/simpleaf, and via bioconda. Documentation for simpleaf is available at https://simpleaf.readthedocs.io/en/latest/ and tutorials for simpleaf that have been developed can be accessed at https://combine-lab.github.io/alevin-fry-tutorials.Item The Sialoside-Binding Pocket of SARS-CoV-2 Spike Glycoprotein Structurally Resembles MERS-CoV(MDPI, 2020-08-19) Awasthi, Mayanka; Gulati, Sahil; Sarkar, Debi P.; Tiwari, Swasti; Kateriya, Suneel; Ranjan, Peeyush; Verma, Santosh KumarCOVID-19 novel coronavirus (CoV) disease caused by severe acquired respiratory syndrome (SARS)-CoV-2 manifests severe lethal respiratory illness in humans and has recently developed into a worldwide pandemic. The lack of effective treatment strategy and vaccines against the SARS-CoV-2 poses a threat to human health. An extremely high infection rate and multi-organ secondary infection within a short period of time makes this virus more deadly and challenging for therapeutic interventions. Despite high sequence similarity and utilization of common host-cell receptor, human angiotensin-converting enzyme-2 (ACE2) for virus entry, SARS-CoV-2 is much more infectious than SARS-CoV. Structure-based sequence comparison of the N-terminal domain (NTD) of the spike protein of Middle East respiratory syndrome (MERS)-CoV, SARS-CoV, and SARS-CoV-2 illustrate three divergent loop regions in SARS-CoV-2, which is reminiscent of MERS-CoV sialoside binding pockets. Comparative binding analysis with host sialosides revealed conformational flexibility of SARS-CoV-2 divergent loop regions to accommodate diverse glycan-rich sialosides. These key differences with SARS-CoV and similarity with MERS-CoV suggest an evolutionary adaptation of SARS-CoV-2 spike glycoprotein reciprocal interaction with host surface sialosides to infect host cells with wide tissue tropism.Item Extraction of Membrane Components from Neisseria gonorrhoeae Using Catanionic Surfactant Vesicles: A New Approach for the Study of Bacterial Surface Molecules(MDPI, 2020-08-20) Stein, Daniel C.; Stocker, Lenea H.; Powell, Abigail E.; Kebede, Salsawi; Watts, David; Williams, Emma; Soto, Nicholas; Dhabaria, Avantika; Fenselau, Catherine; Ganapati, Shweta; DeShong, PhilipIdentification of antigens is important for vaccine production. We tested extraction protocols using cetyltrimethylammonium tosylate (CTAT) and sodium dodecylbenzenesulfonate (SDBS) to formulate surfactant vesicles (SVs) containing components from Neisseria gonorrhoeae. Carbohydrate and protein assays demonstrated that protein and carbohydrates were incorporated into the vesicle leaflet. Depending on the extraction protocol utilized, 100–400 µg of protein/mL of SVs solution was obtained. Gel electrophoresis followed by silver staining demonstrated that SV extracts contained lipooligosaccharide and a subset of bacterial proteins and lipoproteins. Western blotting and mass spectral analysis indicated that the majority of the proteins were derived from the outer membrane. Mass spectrometric and bioinformatics analysis of SVs identified 29 membrane proteins, including porin and opacity-associated protein. Proteins embedded in the SVs leaflet could be degraded by the addition of trypsin or proteinase K. Our data showed that the incorporation of CTAT and SDBS into vesicles eliminated their toxicity as measured by a THP-1 killing assay. Incorporation of gonococcal cell surface components into SVs reduced toxicity as compared to the whole cell extracts, as measured by cytokine induction, while retaining the immunogenicity. This process constitutes a general method for extracting bacterial surface components and identification of antigens that might be included in vaccines.