Rapid and precise genome engineering in a naturally short-lived vertebrate.

The African turquoise killifish is a powerful vertebrate system to study complex phenotypes at scale, including aging and age-related disease. Here, we develop a rapid and precise CRISPR/Cas9-mediated knock-in approach in the killifish. We show its efficient application to precisely insert fluorescent reporters of different sizes at various genomic loci in order to drive cell-type- and tissue-specific expression. This knock-in method should allow the establishment of humanized disease models and the development of cell-type-specific molecular probes for studying complex vertebrate biology.

Life Span Assessment in the African Turquoise Killifish Nothobranchius furzeri.

The African turquoise killifish (Nothobranchius furzeri) is the shortest-lived vertebrate bred in captivity, with a median life span of 4-6 mo. Within its short life span, the killifish recapitulates critical aspects of human aging, including neurodegeneration and increased frailty. Developing standardized protocols for life span assessment in killifish is critical for identifying environmental and genetic factors that impact vertebrate life span. A standardized life span protocol should have low variability and high reproducibility, and it should enable comparison of life spans between laboratories. Here, we report our standardized protocol for measuring life span in the African turquoise killifish.

Husbandry of the African Turquoise Killifish Nothobranchius furzeri.

The African turquoise killifish (Nothobranchius furzeri) is an extremely short-lived vertebrate that has emerged as a powerful model organism for several research areas, including aging and embryonic diapause, which is the temporary suspension of embryonic development. The killifish research community is expanding and developing new solutions to improve the tractability of the killifish as a model system. Starting a killifish colony from scratch can present numerous challenges. In this protocol, we aim to highlight critical elements in building and maintaining a killifish colony. This protocol should help laboratories start a killifish colony and standardize aspects of killifish husbandry.

An automated feeding system for the African killifish reveals the impact of diet on lifespan and allows scalable assessment of associative learning.

The African turquoise killifish is an exciting new vertebrate model for aging studies. A significant challenge for any model organism is the control over its diet in space and time. To address this challenge, we created an automated and networked fish feeding system. Our automated feeder is designed to be open-source, easily transferable, and built from widely available components. Compared to manual feeding, our automated system is highly precise and flexible. As a proof of concept for the feeding flexibility of these automated feeders, we define a favorable regimen for growth and fertility for the African killifish and a dietary restriction regimen where both feeding time and quantity are reduced. We show that this dietary restriction regimen extends lifespan in males (but not in females) and impacts the transcriptomes of killifish livers in a sex-specific manner. Moreover, combining our automated feeding system with a video camera, we establish a quantitative associative learning assay to provide an integrative measure of cognitive performance for the killifish. The ability to precisely control food delivery in the killifish opens new areas to assess lifespan and cognitive behavior dynamics and to screen for dietary interventions and drugs in a scalable manner previously impossible with traditional vertebrate model organisms.

Machine learning-guided channelrhodopsin engineering enables minimally invasive optogenetics.

We engineered light-gated channelrhodopsins (ChRs) whose current strength and light sensitivity enable minimally invasive neuronal circuit interrogation. Current ChR tools applied to the mammalian brain require intracranial surgery for transgene delivery and implantation of fiber-optic cables to produce light-dependent activation of a small volume of tissue. To facilitate expansive optogenetics without the need for invasive implants, our engineering approach leverages the substantial literature of ChR variants to train statistical models for the design of high-performance ChRs. With Gaussian process models trained on a limited experimental set of 102 functionally characterized ChRs, we designed high-photocurrent ChRs with high light sensitivity. Three of these, ChRger1-3, enable optogenetic activation of the nervous system via systemic transgene delivery. ChRger2 enables light-induced neuronal excitation without fiber-optic implantation; that is, this opsin enables transcranial optogenetics.

Viral Strategies for Targeting the Central and Peripheral Nervous Systems.

Recombinant viruses allow for targeted transgene expression in specific cell populations throughout the nervous system. The adeno-associated virus (AAV) is among the most commonly used viruses for neuroscience research. Recombinant AAVs (rAAVs) are highly versatile and can package most cargo composed of desired genes within the capsid's ∼5-kb carrying capacity. Numerous regulatory elements and intersectional strategies have been validated in rAAVs to enable cell type-specific expression. rAAVs can be delivered to specific neuronal populations or globally throughout the animal. The AAV capsids have natural cell type or tissue tropism and trafficking that can be modified for increased specificity. Here, we describe recently engineered AAV capsids and associated cargo that have extended the utility of AAVs in targeting molecularly defined neurons throughout the nervous system, which will further facilitate neuronal circuit interrogation and discovery.

Learned protein embeddings for machine learning.

Motivation: Machine-learning models trained on protein sequences and their measured functions can infer biological properties of unseen sequences without requiring an understanding of the underlying physical or biological mechanisms. Such models enable the prediction and discovery of sequences with optimal properties. Machine-learning models generally require that their inputs be vectors, and the conversion from a protein sequence to a vector representation affects the model's ability to learn. We propose to learn embedded representations of protein sequences that take advantage of the vast quantity of unmeasured protein sequence data available. These embeddings are low-dimensional and can greatly simplify downstream modeling. Results: The predictive power of Gaussian process models trained using embeddings is comparable to those trained on existing representations, which suggests that embeddings enable accurate predictions despite having orders of magnitude fewer dimensions. Moreover, embeddings are simpler to obtain because they do not require alignments, structural data, or selection of informative amino-acid properties. Visualizing the embedding vectors shows meaningful relationships between the embedded proteins are captured. Availability and implementation: The embedding vectors and code to reproduce the results are available at https://github.com/fhalab/embeddings_reproduction/. Supplementary information: Supplementary data are available at Bioinformatics online.

Machine learning to design integral membrane channelrhodopsins for efficient eukaryotic expression and plasma membrane localization.

There is growing interest in studying and engineering integral membrane proteins (MPs) that play key roles in sensing and regulating cellular response to diverse external signals. A MP must be expressed, correctly inserted and folded in a lipid bilayer, and trafficked to the proper cellular location in order to function. The sequence and structural determinants of these processes are complex and highly constrained. Here we describe a predictive, machine-learning approach that captures this complexity to facilitate successful MP engineering and design. Machine learning on carefully-chosen training sequences made by structure-guided SCHEMA recombination has enabled us to accurately predict the rare sequences in a diverse library of channelrhodopsins (ChRs) that express and localize to the plasma membrane of mammalian cells. These light-gated channel proteins of microbial origin are of interest for neuroscience applications, where expression and localization to the plasma membrane is a prerequisite for function. We trained Gaussian process (GP) classification and regression models with expression and localization data from 218 ChR chimeras chosen from a 118,098-variant library designed by SCHEMA recombination of three parent ChRs. We use these GP models to identify ChRs that express and localize well and show that our models can elucidate sequence and structure elements important for these processes. We also used the predictive models to convert a naturally occurring ChR incapable of mammalian localization into one that localizes well.

The Jellyfish Cassiopea Exhibits a Sleep-like State.

Do all animals sleep? Sleep has been observed in many vertebrates, and there is a growing body of evidence for sleep-like states in arthropods and nematodes [1-5]. Here we show that sleep is also present in Cnidaria [6-8], an earlier-branching metazoan lineage. Cnidaria and Ctenophora are the first metazoan phyla to evolve tissue-level organization and differentiated cell types, such as neurons and muscle [9-15]. In Cnidaria, neurons are organized into a non-centralized radially symmetric nerve net [11, 13, 15-17] that nevertheless shares fundamental properties with the vertebrate nervous system: action potentials, synaptic transmission, neuropeptides, and neurotransmitters [15-20]. It was reported that cnidarian soft corals [21] and box jellyfish [22, 23] exhibit periods of quiescence, a pre-requisite for sleep-like states, prompting us to ask whether sleep is present in Cnidaria. Within Cnidaria, the upside-down jellyfish Cassiopea spp. displays a quantifiable pulsing behavior, allowing us to perform long-term behavioral tracking. Monitoring of Cassiopea pulsing activity for consecutive days and nights revealed behavioral quiescence at night that is rapidly reversible, as well as a delayed response to stimulation in the quiescent state. When deprived of nighttime quiescence, Cassiopea exhibited decreased activity and reduced responsiveness to a sensory stimulus during the subsequent day, consistent with homeostatic regulation of the quiescent state. Together, these results indicate that Cassiopea has a sleep-like state, supporting the hypothesis that sleep arose early in the metazoan lineage, prior to the emergence of a centralized nervous system.

Directed Evolution of a Bright Near-Infrared Fluorescent Rhodopsin Using a Synthetic Chromophore.

By engineering a microbial rhodopsin, Archaerhodopsin-3 (Arch), to bind a synthetic chromophore, merocyanine retinal, in place of the natural chromophore all-trans-retinal (ATR), we generated a protein with exceptionally bright and unprecedentedly red-shifted near-infrared (NIR) fluorescence. We show that chromophore substitution generates a fluorescent Arch complex with a 200-nm bathochromic excitation shift relative to ATR-bound wild-type Arch and an emission maximum at 772 nm. Directed evolution of this complex produced variants with pH-sensitive NIR fluorescence and molecular brightness 8.5-fold greater than the brightest ATR-bound Arch variant. The resulting proteins are well suited to bacterial imaging; expression and stability have not been optimized for mammalian cell imaging. By targeting both the protein and its chromophore, we overcome inherent challenges associated with engineering bright NIR fluorescence into Archaerhodopsin. This work demonstrates an efficient strategy for engineering non-natural, tailored properties into microbial opsins, properties relevant for imaging and interrogating biological systems.

Structure-guided SCHEMA recombination generates diverse chimeric channelrhodopsins.

Integral membrane proteins (MPs) are key engineering targets due to their critical roles in regulating cell function. In engineering MPs, it can be extremely challenging to retain membrane localization capability while changing other desired properties. We have used structure-guided SCHEMA recombination to create a large set of functionally diverse chimeras from three sequence-diverse channelrhodopsins (ChRs). We chose 218 ChR chimeras from two SCHEMA libraries and assayed them for expression and plasma membrane localization in human embryonic kidney cells. The majority of the chimeras express, with 89% of the tested chimeras outperforming the lowest-expressing parent; 12% of the tested chimeras express at even higher levels than any of the parents. A significant fraction (23%) also localize to the membrane better than the lowest-performing parent ChR. Most (93%) of these well-localizing chimeras are also functional light-gated channels. Many chimeras have stronger light-activated inward currents than the three parents, and some have unique off-kinetics and spectral properties relative to the parents. An effective method for generating protein sequence and functional diversity, SCHEMA recombination can be used to gain insights into sequence-function relationships in MPs.

Genetically Encoded Spy Peptide Fusion System to Detect Plasma Membrane-Localized Proteins In Vivo.

Membrane proteins are the main gatekeepers of cellular state, especially in neurons, serving either to maintain homeostasis or instruct response to synaptic input or other external signals. Visualization of membrane protein localization and trafficking in live cells facilitates understanding the molecular basis of cellular dynamics. We describe here a method for specifically labeling the plasma membrane-localized fraction of heterologous membrane protein expression using channelrhodopsins as a case study. We show that the genetically encoded, covalent binding SpyTag and SpyCatcher pair from the Streptococcus pyogenes fibronectin-binding protein FbaB can selectively label membrane-localized proteins in living cells in culture and in vivo in Caenorhabditis elegans. The SpyTag/SpyCatcher covalent labeling method is highly specific, modular, and stable in living cells. We have used the binding pair to develop a channelrhodopsin membrane localization assay that is amenable to high-throughput screening for opsin discovery and engineering.

Recent advances in engineering microbial rhodopsins for optogenetics.

Protein engineering of microbial rhodopsins has been successful in generating variants with improved properties for applications in optogenetics. Members of this membrane protein family can act as both actuators and sensors of neuronal activity. Chimeragenesis, structure-guided mutagenesis, and directed evolution have proven effective strategies for tuning absorption wavelength, altering ion specificity and increasing fluorescence. These approaches facilitate the development of useful optogenetic tools and, in some cases, have yielded insights into rhodopsin structure-function relationships.

Archaerhodopsin variants with enhanced voltage-sensitive fluorescence in mammalian and Caenorhabditis elegans neurons.

Probing the neural circuit dynamics underlying behaviour would benefit greatly from improved genetically encoded voltage indicators. The proton pump Archaerhodopsin-3 (Arch), an optogenetic tool commonly used for neuronal inhibition, has been shown to emit voltage-sensitive fluorescence. Here we report two Arch variants with enhanced radiance (Archers) that in response to 655 nm light have 3-5 times increased fluorescence and 55-99 times reduced photocurrents compared with Arch WT. The most fluorescent variant, Archer1, has 25-40% fluorescence change in response to action potentials while using 9 times lower light intensity compared with other Arch-based voltage sensors. Archer1 is capable of wavelength-specific functionality as a voltage sensor under red light and as an inhibitory actuator under green light. As a proof-of-concept for the application of Arch-based sensors in vivo, we show fluorescence voltage sensing in behaving Caenorhabditis elegans. Archer1's characteristics contribute to the goal of all-optical detection and modulation of activity in neuronal networks in vivo.

Hypocrea jecorina cellobiohydrolase I stabilizing mutations identified using noncontiguous recombination.

Noncontiguous recombination (NCR) is a method to identify pieces of structure that can be swapped among homologous proteins to create new, chimeric proteins. These "blocks" are encoded by elements of sequence that are not necessarily contiguous along the polypeptide chain. We used NCR to design a library in which blocks of structure from Hypocrea jecorina cellobiohydrolase I (Cel7A) and its two thermostable homologues from Talaromyces emersonii and Chaetomium thermophilum are shuffled to create 531,438 possible chimeric enzymes. We constructed a maximally informative subset of 35 chimeras to analyze this library and found that the blocks contribute additively to the stability of a chimera. Within two highly stabilizing blocks, we uncovered six single amino acid substitutions that each improve the stability of H. jecorina cellobiohydrolase I by 1-3 °C. The small number of measurements required to find these mutations demonstrates that noncontiguous recombination is an efficient strategy for identifying stabilizing mutations.

Competitive sorption kinetics of inhibited endo- and exoglucanases on a model cellulose substrate.

For the first time, the competitive adsorption of inhibited cellobiohydrolase I (Cel7A, an exoglucanase) and endoglucanase I (Cel7B) from T. longibrachiatum is studied on cellulose. Using quartz crystal microgravimetry (QCM), sorption histories are measured for individual types of cellulases and their mixtures adsorbing to and desorbing from a model cellulose surface. We find that Cel7A has a higher adsorptive affinity for cellulose than does Cel7B. The adsorption of both cellulases becomes irreversible on time scales of 30-60 min, which are much shorter than those typically used for industrial cellulose hydrolysis. A multicomponent Langmuir kinetic model including first-order irreversible binding is proposed. Although adsorption and desorption rate constants differ between the two enzymes, the rate at which each surface enzyme irreversibly binds is identical. Because of the higher affinity of Cel7A for the cellulose surface, when Cel7A and Cel7B compete for surface sites, a significantly higher bulk concentration of Cel7B is required to achieve comparable surface enzyme concentrations. Because cellulose deconstruction benefits significantly from the cooperative activity of endoglucanases and cellobiohydrolases on the cellulose surface, accounting for competitive adsorption is crucial to developing effective cellulase mixtures.