Directed Evolution of a Selective and Sensitive Serotonin Biosensor Via Machine Learning

Unger, Elizabeth K.; Keller, Jacob P.; Altermatt, Michael; Liang, Ruqiang; Yao, Zi; Sun, Junqing; Matsui, Aya; Dong, Chunyang; Jaffe, David A.; Hartanto, Samantha; Mizuno, Grace O.; Borden, Phillip M.; Shivange, Amol V.; Sinning, Steffen; Underhill, Suzanne M.; Carlin, J. W.; Banala, Sambashiva; Cameron, Lindsay P.; Olson, David E.; Amara, Susan G.; Lang, Duncan Temple; Rudnick, Gary; Marvin, Jonathan S.; Lavis, Luke D.; Lester, Henry A.; Alvarez, Veronica A.; Fisher, A.J.; Prescher, Jennifer A.; Yarov‐Yarovoy, Vladimir; Gradinaru, Viviana; Looger, Loren L.; Tian, Lin

doi:10.2139/ssrn.3498571

Cited by 30 publications

(16 citation statements)

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“…In addition to serving as an excellent sensor in its own right, iAChSnFR also provides a promising scaffold for developing additional sensors through targeted mutagenesis. We have developed iAChSnFR into a sensor specific for serotonin by machine learning-guided protein redesign and directed evolution 86 . In parallel with development of iAChSnFR, we also mutated OpuBC to recognize nicotine or the smoking-cessation drug varenicline 36 (PDB 6EFR).…”

Section: Discussionmentioning

confidence: 99%

A fast genetically encoded fluorescent sensor for faithful in vivo acetylcholine detection in mice, fish, worms and flies

Zhang

Shivange

et al. 2020

Preprint

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138

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Here we design and optimize a genetically encoded fluorescent indicator, iAChSnFR, for the ubiquitous neurotransmitter acetylcholine, based on a bacterial periplasmic binding protein. iAChSnFR shows large fluorescence changes, rapid rise and decay kinetics, and insensitivity to most cholinergic drugs. iAChSnFR revealed large transients in a variety of slice and in vivo preparations in mouse, fish, fly and worm. iAChSnFR will be useful for the study of acetylcholine in all animals. IntroductionAcetylcholine (ACh) is a critical neurotransmitter in all animals. Among invertebrates, it is the most prevalent excitatory transmitter in the brain, sensory ganglia, and frequently the neuromuscular junction (NMJ). Among vertebrates, only a minority of neurons release ACh, but these signals play varying key roles. For instance, ACh signals at the NMJ, in the autonomic nervous system, and in subsets of the central nervous system, particularly projections arising from the brainstem and basal forebrain. Other cholinergic neuron populations in the brain include striatal interneurons, the stria vascularis-medial habenula-interpeduncular nucleus pathway, and sparse, incompletely characterized cell types such as intrinsic cholinergic interneurons in cortex 1 and hippocampus 2 . ACh helps to regulate attention 3 and wakefulness 4 , and participates in memory formation and consolidation 5 . ACh is also an important transmitter in glia, and between the nervous and immune systems 6 .Acetylcholine is synthesized pre-synaptically from choline and acetyl-CoA by choline acetyltransferase (ChAT), then packaged into synaptic vesicles by the vesicular acetylcholine transporter (VAChT). A key, partially understood aspect of cholinergic signaling is co-release with other neurotransmitters, including GABA, ATP, and glutamate 7,8 . To understand the role of co-release, one must measure ACh release alongside emerging measurements of other neurotransmitters.Acetylcholine receptors are among the most diverse neurotransmitter receptor families. Humans possess five muscarinic G protein-coupled receptors (GPCRs) for ACh (mAChRs) with diverse expression in the brain and smooth, cardiac, and skeletal muscle. Vertebrate nicotinic ACh receptors (nAChRs) are pentameric ligand-gated cation channels. Humans have a total of 17 nAChR subunit genes, in five classes: 10 a, 4 b, and one each of g, d, and e. nAChRs occur with many subunit combinations 9 , and others may be undiscovered. Invertebrates also have AChgated chloride channels. On neurons, receptors can be localized pre-, post-, and extrasynaptically, often with different isoforms in each place 10

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Section: Discussionmentioning

confidence: 99%

A fast genetically encoded fluorescent sensor for faithful in vivo acetylcholine detection in mice, fish, worms and flies

Zhang

Shivange

et al. 2020

Preprint

Self Cite

138

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“…There are both GPCR and PBP-based genetically encoded sensors for serotonin (5-hydroxytryptamine or 5HT) (Table 1) [34,35]. GPCR-based GRAB 5HT0.5 and GRAB 5HT1.0 effectively detected serotonergic signals in populations of cells [34].…”

Section: Genetically Encoded Neuromodulatory Transmitter Sensorsmentioning

confidence: 99%

“…GRAB 5HT0.5 performed better in assessing endogenous single-cell serotonergic signals and could serve as a viable tool for dissecting transmission properties of serotonergic modulation, due presumably to its kinetics and affinity matching more closely to the dynamics and concentration of endogenously released 5HT [32,34]. The PBP-based iSeroSnFR reported prominent endogenous serotonergic signals in populations of cells [35]. However, given its relatively lower sensitivity (compared to GRAB 5HT ) [34,35], it waits to see whether the sensor can detect single-cell and subcellular serotonergic signals.…”

Section: Genetically Encoded Neuromodulatory Transmitter Sensorsmentioning

confidence: 99%

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Genetically encoded sensors enable micro- and nano-scopic decoding of transmission in healthy and diseased brains

et al. 2020

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Neural communication orchestrates a variety of behaviors, yet despite impressive effort, delineating transmission properties of neuromodulatory communication remains a daunting task due to limitations of available monitoring tools. Recently developed genetically encoded neurotransmitter sensors, when combined with superresolution and deconvolution microscopic techniques, enable the first micro- and nano-scopic visualization of neuromodulatory transmission. Here we introduce this image analysis method by presenting its biophysical foundation, practical solutions, biological validation, and broad applicability. The presentation illustrates how the method resolves fundamental synaptic properties of neuromodulatory transmission, and the new data unveil unexpected fine control and precision of rodent and human neuromodulation. The findings raise the prospect of rapid advances in the understanding of neuromodulatory transmission essential for resolving the physiology or pathogenesis of various behaviors and diseases.

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“…Fiber photometry is a tool that allows for the recording of bulk fluorescent signals from a growing number of sensors including those for detecting levels of cellular activity, such as GCaMP6 (Chen et al, 2013), jGCaMP7 (Dana et al, 2019), jRCAMP1a,b or jRGECO1a (Dana et al, 2016). In addition, a number of sensors have recently been developed for detecting the binding of specific neurotransmitters, such as glutamate via iGluSnFr (Marvin et al, 2018), GABA via iGABASnFr (Marvin et al, 2019), acetylcholine via iAChSnFr (Borden et al, 2020), serotonin via iSeroSnFr (Unger et al, 2019), dopamine via dLight (Patriarchi et al, 2018) or GRAB DA (Sun et al, 2018), and norepinephrine via GRAB NE (Feng et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

pMAT: An Open-Source, Modular Software Suite for the Analysis of Fiber Photometry Calcium Imaging

Bruno

O’Brien

Bryant

et al. 2020

Preprint

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The combined development of new technologies for neuronal recordings and the development of novel sensors for recording both cellular activity and neurotransmitter binding has ushered in a new era for the field of neuroscience. Among these new technologies is fiber photometry, a technique wherein an implanted fiber optic is used to record signals from genetically encoded fluorescent sensors in bulk tissue. Fiber photometry has been widely adapted due to its cost-effectiveness, ability to examine the activity of neurons with specific anatomical or genetic identities, and the ability to use these highly modular systems to record from one or more sensors or brain sites in both superficial and deep-brain structures. Despite these many benefits, one major hurdle for laboratories adopting this technique is the steep learning curve associated with the analysis of fiber photometry data. This has been further complicated by a lack of standardization in analysis pipelines. In the present communication, we present pMAT, a ‘photometry modular analysis tool’ that allows users to accomplish common analysis routines through the use of a graphical user interface. This tool can be deployed in MATLAB and edited by more advanced users, but is also available as an independently deployable, open-source application.

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Directed Evolution of a Selective and Sensitive Serotonin Biosensor Via Machine Learning

Cited by 30 publications

References 0 publications

A fast genetically encoded fluorescent sensor for faithful in vivo acetylcholine detection in mice, fish, worms and flies

A fast genetically encoded fluorescent sensor for faithful in vivo acetylcholine detection in mice, fish, worms and flies

Genetically encoded sensors enable micro- and nano-scopic decoding of transmission in healthy and diseased brains

pMAT: An Open-Source, Modular Software Suite for the Analysis of Fiber Photometry Calcium Imaging

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