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Since the Force Concept Inventory in 1992, many concept inventories have been developed to cover classical scientific fields. However, there is a lack of concept inventories for interdisciplinary fields, such as biophysics. We introduce a Biophysics Concept Inventory Survey (BCIS), a 20-question, multiple-choice survey to measure student gains in biophysical concepts. The BCIS contains 5 question classifications: remember, understand, apply, analyze, and create, as well as question concepts divided into primarily physics or primarily biology questions. We administered the BCIS to 3 cohorts of students over 4 years. Each cohort participated in a 10-week summer Research Experience for Undergraduates (REU) in biophysics. We compared the presurvey (before REU) and postsurvey (after REU) scores to determine the fraction of the maximum possible gain or loss realized. Our analysis of the results suggests that the BCIS shows no biases based on sex or ethnicity. Further, we used the BCIS to show that 69% of the REU participants showed gains in biophysics concepts, with most of the total participant mean of gain occurring at higher levels of Bloom’s taxonomy: create and analyze. Overall, participants obtain slightly higher scores in physics (8% increase) than biology (5% increase) when comparing the pre- and postscores. The coronavirus disease 2019 pandemic allows a splitting of prepandemic and postpandemic cohorts, with the postpandemic cohort showing significantly larger gains than the prepandemic students. These results show that the BCIS, with question classifications and concepts, probes the students’ ability to apply knowledge to various biophysical science topics without underlying biases and enables instructors to obtain answers to important questions about the effectiveness of the educational programs. The BCIS fills a gap for interdisciplinary concept inventories. 

Transcription factors (TFs) regulate gene expression by binding to specific DNA sequences and gating access to genes. Even when the binding of TFs and their cofactors to DNA is reversible, indicating a reversible control of gene expression, there is little knowledge about the molecular effect DNA has on TFs. Using single-molecule multiparameter fluorescence spectroscopy, molecular dynamics simulations, and biochemical assays, we find that the monomeric form of the forkhead (FKH) domain of the human FoxP1 behaves as a disordered protein and increases its folded population when it dimerizes. Notably, DNA binding promotes a disordered FKH dimer bound to DNA, negatively controlling the stability of the dimeric FoxP1:DNA complex. The DNA-mediated reversible regulation on FKH dimers suggests that FoxP1-dependent gene suppression is unstable, and it must require the presence of other dimerization domains or cofactors to revert the negative impact exerted by the DNA. 

Transcription factors are multidomain proteins with specific DNA binding and regulatory domains. In the human FoxP subfamily (FoxP1, FoxP2, FoxP3, and FoxP4) of transcription factors, a 90 residue-long disordered region links a Leucine Zipper (ZIP)—known to form coiled-coil dimers—and a Forkhead (FKH) domain—known to form domain swapping dimers. We used replica exchange discrete molecular dynamics simulations, single-molecule fluorescence experiments, and other biophysical tools to understand how domain tethering in FoxP1 impacts dimerization at ZIP and FKH domains and how DNA binding allosterically regulates their dimerization. We found that domain tethering promotes FoxP1 dimerization but inhibits a FKH domain-swapped structure. Furthermore, our findings indicate that the linker mediates the mutual organization and dynamics of ZIP and FKH domains, forming closed and open states with and without interdomain contacts, thus highlighting the role of the linkers in multidomain proteins. Finally, we found that DNA allosterically promotes structural changes that decrease the dimerization propensity of FoxP1. We postulate that, upon DNA binding, the interdomain linker plays a crucial role in the gene regulatory function of FoxP1. 

Transcription factors regulate gene expression by binding to DNA. They have disordered regions and specific DNA-binding domains. Binding to DNA causes structural changes, including folding and interactions with other molecules. The FoxP subfamily of transcription factors in humans is unique because they can form heterotypic interactions without DNA. However, it is unclear how they form heterodimers and how DNA binding affects their function. We used computational and experimental methods to study the structural changes in FoxP1's DNA-binding domain when it forms a heterodimer with FoxP2. We found that FoxP1 has complex and diverse conformational dynamics, transitioning between compact and extended states. Surprisingly, DNA binding increases the flexibility of FoxP1, contrary to the typical folding-upon-binding mechanism. In addition, we observed a 3-fold increase in the rate of heterodimerization after FoxP1 binds to DNA. These findings emphasize the importance of structural flexibility in promoting heterodimerization to form transcriptional complexes. 

Single-molecule Förster Resonance Energy Transfer (smFRET) experiments are ideally suited to resolve the structural dynamics of biomolecules. A significant challenge to date is capturing and quantifying the exchange between multiple conformational states, mainly when these dynamics occur on the sub-millisecond timescale. Many methods for quantitative analysis are challenged if more than two states are involved, and the appropriate choice of the number of states in the kinetic network is difficult. An additional complication arises if dynamically active molecules coexist with pseudo-static molecules in similar conformational states with undistinguishable Förster Resonance Energy Transfer (FRET) efficiencies. To address these problems, we developed a quantitative integrative analysis framework that combines the information from FRET-lines that relate average fluorescence lifetimes and intensities in two-dimensional burst frequency histograms, fluorescence decays obtained by time-correlated single-photon-counting, photon distribution analysis of the intensities, and fluorescence correlation spectroscopy. Individually, these methodologies provide ambiguous results for the characterization of dynamics in complex kinetic networks. However, the global analysis approach enables accurate determination of the number of states, their kinetic connectivity, the transition rate constants, and species fractions. To challenge the potential of smFRET experiments for studying multi-state kinetic networks, we apply our integrative framework using a set of synthetic data for three-state systems with different kinetic connectivity and exchange rates. Our methodology paves the way toward an integrated analysis of multiparameter smFRET experiments that spans all dimensions of the experimental data. Finally, we propose a workflow for the analysis and show examples that demonstrate the usefulness of this toolkit for dynamic structural biology.