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1. Designing a Compact, Low-Cost FRET Microscopy Platform for the Undergraduate Classroom

   https://doi.org/10.35459/tbp.2019.000117  

   Rupel, John W.; Sdao, Sophia M.; Johnston, Kadina E.; Nethery, Ethan T.; Gabardi, Kaitlyn A.; Ratliff, Benjamin A.; Simmons, Zach J.; Postlewaite, Jack T.; Kita, Angela M.; Rogers, Jeremy D.; et al (June 2020, The Biophysicist)

   null (Ed.)

   ABSTRACT Advances in fluorescent biosensors allow researchers to spatiotemporally monitor a diversity of biochemical reactions and secondary messengers. However, commercial microscopes for the specific application of Förster Resonance Energy Transfer (FRET) are prohibitively expensive to implement in the undergraduate classroom, owing primarily to the dynamic range required and need for ratiometric emission imaging. The purpose of this article is to provide a workflow to design a low-cost, FRET-enabled microscope and to equip the reader with sufficient knowledge to compare commercial light sources, optics, and cameras to modify the device for a specific application. We used this approach to construct a microscope that was assembled by undergraduate students with no prior microscopy experience that is suitable for most single-cell cyan and yellow fluorescent protein FRET applications. The utility of this design was demonstrated by measuring small metabolic oscillations by using a lactate FRET sensor expressed in primary mouse pancreatic islets, highlighting the biologically suitable signal-to-noise ratio and dynamic range of our compact microscope. The instructions in this article provide an effective teaching tool for undergraduate educators and students interested in implementing FRET in a cost-effective manner. 

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2. Enabling materials informatics for 29Si solid-state NMR of crystalline materials

   https://doi.org/10.1038/s41524-020-0328-3  

   Sun, He; Dwaraknath, Shyam; Ling, Handong; Qu, Xiaohui; Huck, Patrick; Persson, Kristin A.; Hayes, Sophia E. (May 2020, npj Computational Materials)

   Abstract Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for obtaining precise information about the local bonding of materials, but difficult to interpret without a well-vetted dataset of reference spectra. The ability to predict NMR parameters and connect them to three-dimensional local environments is critical for understanding more complex, long-range interactions. New computational methods have revealed structural information available from²⁹Si solid-state NMR by generating computed reference spectra for solids. Such predictions are useful for the identification of new silicon-containing compounds, and serve as a starting point for determination of the local environments present in amorphous structures. In this study, we have used 42 silicon sites as a benchmarking set to compare experimentally reported²⁹Si solid-state NMR spectra with those computed by CASTEP-NMR and Vienna Ab Initio Simulation Program (VASP). Data-driven approaches enable us to identify the source of discrepancies across a range of experimental and computational results. The information from NMR (in the form of an NMR tensor) has been validated, and in some cases corrected, in an effort to catalog these for the local spectroscopy database infrastructure (LSDI), where over 10,000²⁹Si NMR tensors for crystalline materials have been computed. Knowledge of specific tensor values can serve as the basis for executing NMR experiments with precision, optimizing conditions to capture the elements accurately. The ability to predict and compare experimental observables from a wide range of structures can aid researchers in their chemical assignments and structure determination, since the computed values enables the extension beyond tables of typical chemical shift (or shielding) ranges. 

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3. True FRET‐Based Sensing of pH via Separation of FRET and Photon Reabsorption

   https://doi.org/10.1002/adom.202200242  

   Corbella_Bagot, Conrad; Rappeport, Eric; Das, Ananda; Ba_Tis, Taleb; Park, Wounjhang (May 2022, Advanced Optical Materials)

   Abstract Förster resonance energy transfer (FRET)‐based devices have been extensively researched as potential biosensors due to their highly localized responsivity. In particular, dye‐conjugated upconverting nanoparticles (UCNPs) are among the most promising FRET‐based sensor candidates. UCNPs have a multi‐modal emission profile that allows for ratiometric sensing, and by conjugating a biosensitive dye to their surface, this profile can be used to measure localized variations in biological parameters. However, the complex nature of the UCNP energy profile as well as reabsorption of emitted photons must be taken into account in order to properly sense the target parameters. To the authors’ knowledge, no proposed UCNP‐based sensor has accurately taken care of these intricacies. In this article, the authors account for these complexities by creating a FRET‐based sensor that measures pH. This sensor utilizes Thulium (Tm³⁺)‐doped UCNPs and the fluorescent dye fluorescein isothiocyanate (FITC). It is first demonstrated that photon reabsorption is a serious issue for the 475 nm Tm³⁺emission, thereby limiting its use in FRET‐based sensing. It is then shown that by taking the ratio of the 646 and 800 nm emissions rather than the more popular 475 nm one, it is possible to measure pH exclusively through FRET. 

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4. An orthogonalized PYR1-based CID module with reprogrammable ligand-binding specificity

   https://doi.org/10.1038/s41589-023-01447-7  

   Park, Sang-Youl; Qiu, Jingde; Wei, Shuang; Peterson, Francis C.; Beltrán, Jesús; Medina-Cucurella, Angélica V.; Vaidya, Aditya S.; Xing, Zenan; Volkman, Brian F.; Nusinow, Dmitri A.; et al (October 2023, Nature Chemical Biology)

   Abstract Plants sense abscisic acid (ABA) using chemical-induced dimerization (CID) modules, including the receptor PYR1 and HAB1, a phosphatase inhibited by ligand-activated PYR1. This system is unique because of the relative ease with which ligand recognition can be reprogrammed. To expand the PYR1 system, we designed an orthogonal ‘*’ module, which harbors a dimer interface salt bridge; X-ray crystallographic, biochemical and in vivo analyses confirm its orthogonality. We used this module to create PYR1*^MANDI/HAB1* and PYR1*^AZIN/HAB1*, which possess nanomolar sensitivities to their activating ligands mandipropamid and azinphos-ethyl. Experiments inArabidopsis thalianaandSaccharomyces cerevisiaedemonstrate the sensitive detection of banned organophosphate contaminants using living biosensors and the construction of multi-input/output genetic circuits. Our new modules enable ligand-programmable multi-channel CID systems for plant and eukaryotic synthetic biology that can empower new plant-based and microbe-based sensing modalities. 

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5. Liquid Metal‐Based Biosensors: Fundamentals and Applications

   https://doi.org/10.1002/adfm.202308173  

   Jamalzadegan, Sina; Kim, Sooyoung; Mohammad, Noor; Koduri, Harshita; Hetzler, Zach; Lee, Giwon; Dickey, Michael_D; Wei, Qingshan (January 2024, Advanced Functional Materials)

   Abstract Biosensors are analytical tools for monitoring various parameters related to living organisms, such as humans and plants. Liquid metals (LMs) have emerged as a promising new material for biosensing applications in recent years. LMs have attractive physical and chemical properties such as deformability, high thermal and electrical conductivity, low volatility, and low viscosity. LM‐based biosensors represent a new strategy in biosensing particularly for wearable and real‐time sensing. While early demonstrations of LM biosensors focus on monitoring physical parameters such as strain, motion, and temperature, recent examples show LM can be an excellent sensing material for biochemical and biomolecular detection as well. In this review, the recent progress of LM‐based biosensors for personalized healthcare and disease monitoring via both physical and biochemical signaling is survey. It is started with a brief introduction of the fundamentals of biosensors and LMs, followed by a discussion of different mechanisms by which LM can transduce biological or physiological signals. Next, it is reviewed example LM‐based biosensors that have been used in real biological systems, ranging from real‐time on‐skin physiological monitoring to target‐specific biochemical detection. Finally, the challenges and future directions of LM‐integrated biosensor platforms is discussed. 

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