This paper provides a synopsis of discussions related to biomedical engineering core curricula that occurred at the Fourth BME Education Summit held at Case Western Reserve University in Cleveland, Ohio in May 2019. This summit was organized by the Council of Chairs of Bioengineering and Biomedical Engineering, and participants included over 300 faculty members from 100+ accredited undergraduate programs. This discussion focused on six key questions: QI: Is there a core curriculum, and if so, what are its components? QII: How does our purported core curriculum prepare students for careers, particularly in industry? QIII: How does design distinguish BME/BIOE graduates from other engineers? QIV: What is the state of engineering analysis and systems-level modeling in BME/BIOE curricula? QV: What is the role of data science in BME/BIOE undergraduate education? QVI: What core experimental skills are required for BME/BIOE undergrads? s. Indeed, BME/BIOI core curricula exists and has matured to emphasize interdisciplinary topics such as physiology, instrumentation, mechanics, computer programming, and mathematical modeling. Departments demonstrate their own identities by highlighting discipline-specific sub-specialties. In addition to technical competence, Industry partners most highly value our students' capacity for problem solving and communication. As such, BME/BIOE curricula includes open-ended projects that address unmet patient and clinician needs as primary methods to prepare graduates for careers in industry. Culminating senior design experiences distinguish BME/BIOE graduates through their development of client-centered engineering solutions to healthcare problems. Finally, the overall BME/BIOE curriculum is not stagnant-it is clear that data science will become an ever-important element of our students' training and that new methods to enhance student engagement will be of pedagogical importance as we embark on the next decade.

Loners-individuals out of sync with a coordinated majority-occur frequently in nature. Are loners incidental byproducts of large-scale coordination attempts, or are they part of a mosaic of life-history strategies? Here, we provide empirical evidence of naturally occurring heritable variation in loner behavior in the model social amoeba Dictyostelium discoideum. We propose that Dictyostelium loners-cells that do not join the multicellular life stage-arise from a dynamic population-partitioning process, the result of each cell making a stochastic, signal-based decision. We find evidence that this imperfectly synchronized multicellular development is affected by both abiotic (environmental porosity) and biotic (signaling) factors. Finally, we predict theoretically that when a pair of strains differing in their partitioning behavior coaggregate, cross-signaling impacts slime-mold diversity across spatiotemporal scales. Our findings suggest that loners could be critical to understanding collective and social behaviors, multicellular development, and ecological dynamics in D. discoideum. More broadly, across taxa, imperfect coordination of collective behaviors might be adaptive by enabling diversification of life-history strategies.

Molecular interactions at the cellular interface mediate organized assembly of single cells into tissues and, thus, govern the development and physiology of multicellular organisms. Here, we developed a cell-type-specific, spatiotemporally resolved approach to profile cell-surface proteomes in intact tissues. Quantitative profiling of cell-surface proteomes of Drosophila olfactory projection neurons (PNs) in pupae and adults revealed global downregulation of wiring molecules and upregulation of synaptic molecules in the transition from developing to mature PNs. A proteome-instructed in vivo screen identified 20 cell-surface molecules regulating neural circuit assembly, many of which belong to evolutionarily conserved protein families not previously linked to neural development. Genetic analysis further revealed that the lipoprotein receptor LRP1 cell-autonomously controls PN dendrite targeting, contributing to the formation of a precise olfactory map. These findings highlight the power of temporally resolved in situ cell-surface proteomic profiling in discovering regulators of brain wiring.

Nervous systems have evolved to combine environmental information with internal state to select and generate adaptive behavioral sequences. To better understand these computations and their implementation in neural circuits, natural behavior must be carefully measured and quantified. Here, we collect high spatial resolution video of single zebrafish larvae swimming in a naturalistic environment and develop models of their action selection across exploration and hunting. Zebrafish larvae swim in punctuated bouts separated by longer periods of rest called interbout intervals. We take advantage of this structure by categorizing bouts into discrete types and representing their behavior as labeled sequences of bout types emitted over time. We then construct probabilistic models—specifically, marked renewal processes—to evaluate how bout types and interbout intervals are selected by the fish as a function of its internal hunger state, behavioral history, and the locations and properties of nearby prey. Finally, we evaluate the models by their predictive likelihood and their ability to generate realistic trajectories of virtual fish swimming through simulated environments. Our simulations capture multiple timescales of structure in larval zebrafish behavior and expose many ways in which hunger state influences their action selection to promote food seeking during hunger and safety during satiety.

Recent work has highlighted that many types of variables are represented in each neocortical area. How can these many neural representations be organized together without interference, and coherently maintained/updated through time? We recorded from large neural populations in posterior cortices as mice performed a complex, dynamic task involving multiple interrelated variables. The neural encoding implied that correlated task variables were represented by uncorrelated modes in an information-coding subspace. We show via theory that this can enable optimal decoding directions to be insensitive to neural noise levels. Across posterior cortex, principles of efficient coding thus applied to task-specific information, with neural-population modes as the encoding unit. Remarkably, this encoding function was multiplexed with rapidly changing, sequential neural dynamics, yet reliably followed slow changes in task-variable correlations through time. We can explain this as due to a mathematical property of high-dimensional spaces that the brain might exploit as a temporal scaffold.

Our understanding of the mechanisms of neural circuit assembly is far from complete. Identification of wiring molecules with novel mechanisms of action will provide insights into how complex and heterogeneous neural circuits assemble during development. In the olfactory system, 50 classes of olfactory receptor neurons (ORNs) make precise synaptic connections with 50 classes of partner projection neurons (PNs). Here, we performed an RNA interference screen for cell surface molecules and identified the leucine-rich repeat-containing transmembrane protein known as Fish-lips (Fili) as a novel wiring molecule in the assembly of the olfactory circuit. Fili contributes to the precise axon and dendrite targeting of a small subset of ORN and PN classes, respectively. Cell-type-specific expression and genetic analyses suggest that Fili sends a transsynaptic repulsive signal to neurites of nonpartner classes that prevents their targeting to inappropriate glomeruli in the antennal lobe.

Fiber-optic epifluorescence imaging with one-photon excitation benefits from its ease of use, cheap light sources, and full-frame acquisition, which enables it for favorable temporal resolution of image acquisition. However, it suffers from a lack of robustness against autofluorescence and light scattering. Moreover, it cannot easily eliminate the out-of-focus background, which generally results in low-contrast images. In order to overcome these limitations, we have implemented fast out-of-phase imaging after optical modulation (Speed OPIOM) for dynamic contrast in fluorescence endomicroscopy. Using a simple and cheap optical-fiber bundle-based endomicroscope integrating modulatable light sources, we first showed that Speed OPIOM provides intrinsic optical sectioning, which restricts the observation of fluorescent labels at targeted positions within a sample. We also demonstrated that this imaging protocol efficiently eliminates the interference of autofluorescence arising from both the fiber bundle and the specimen in several biological samples. Finally, we could perform multiplexed observations of two spectrally similar fluorophores differing by their photoswitching dynamics. Such attractive features of Speed OPIOM in fluorescence endomicroscopy should find applications in bioprocessing, clinical diagnostics, plant observation, and surface imaging.

Neuromodulation plays a critical role in brain function in both health and disease, and new tools that capture neuromodulation with high spatial and temporal resolution are needed. Here, we introduce a synthetic catecholamine nanosensor with fluorescent emission in the near infrared range (1000–1300 nm), near infrared catecholamine nanosensor (nIRCat). We demonstrate that nIRCats can be used to measure electrically and optogenetically evoked dopamine release in brain tissue, revealing hotspots with a median size of 2 µm. We also demonstrated that nIRCats are compatible with dopamine pharmacology and show D2 autoreceptor modulation of evoked dopamine release, which varied as a function of initial release magnitude at different hotspots. Together, our data demonstrate that nIRCats and other nanosensors of this class can serve as versatile synthetic optical tools to monitor neuromodulatory neurotransmitter release with high spatial resolution.

Interactions between proteins play an essential role in metabolic and signaling pathways, cellular processes and organismal systems. We report the development of splitFAST, a fluorescence complementation system for the visualization of transient protein-protein interactions in living cells. Engineered from the fluorogenic reporter FAST (Fluorescence-Activating and absorption-Shifting Tag), which specifically and reversibly binds fluorogenic hydroxybenzylidene rhodanine (HBR) analogs, splitFAST displays rapid and reversible complementation, allowing the real-time visualization of both the formation and the dissociation of a protein assembly.