Main Menu (Mobile)- Block

Main Menu - Block

janelia7_blocks-janelia7_fake_breadcrumb | block
Koyama Lab / Publications
custom | custom


facetapi-Q2b17qCsTdECvJIqZJgYMaGsr8vANl1n | block

Associated Lab

facetapi-W9JlIB1X0bjs93n1Alu3wHJQTTgDCBGe | block
facetapi-PV5lg7xuz68EAY8eakJzrcmwtdGEnxR0 | block
facetapi-021SKYQnqXW6ODq5W5dPAFEDBaEJubhN | block
general_search_page-panel_pane_1 | views_panes

3552 Publications

Showing 51-60 of 3552 results
09/02/22 | Tracing and Manipulating Drosophila Cell Lineages Based on CRISPR: CaSSA and CLADES.
Garcia-Marques J, Lee T
Methods in Molecular Biology. 2022 Sep 02;2540:201-217. doi: 10.1007/978-1-0716-2541-5_9

Cell lineage defines the mitotic connection between cells that make up an organism. Mapping these connections in relation to cell identity offers an extraordinary insight into the mechanisms underlying normal and pathological development. The analysis of molecular determinants involved in the acquisition of cell identity requires gaining experimental access to precise parts of cell lineages. Recently, we have developed CaSSA and CLADES, a new technology based on CRISPR that allows targeting and labeling specific lineage branches. Here we discuss how to better exploit this technology for lineage studies in Drosophila, with an emphasis on neuronal specification.

View Publication Page
09/01/22 | Leveraging the model-experiment loop: Examples from cellular slime mold chemotaxis.
Zhu X, Hager ER, Huyan C, Sgro AE
Exp Cell Res. 09/2022;418(1):113218. doi: 10.1016/j.yexcr.2022.113218

Interplay between models and experimental data advances discovery and understanding in biology, particularly when models generate predictions that allow well-designed experiments to distinguish between alternative mechanisms. To illustrate how this feedback between models and experiments can lead to key insights into biological mechanisms, we explore three examples from cellular slime mold chemotaxis. These examples include studies that identified chemotaxis as the primary mechanism behind slime mold aggregation, discovered that cells likely measure chemoattractant gradients by sensing concentration differences across cell length, and tested the role of cell-associated chemoattractant degradation in shaping chemotactic fields. Although each study used a different model class appropriate to their hypotheses - qualitative, mathematical, or simulation-based - these examples all highlight the utility of modeling to formalize assumptions and generate testable predictions. A central element of this framework is the iterative use of models and experiments, specifically: matching experimental designs to the models, revising models based on mismatches with experimental data, and validating critical model assumptions and predictions with experiments. We advocate for continued use of this interplay between models and experiments to advance biological discovery.

View Publication Page
09/01/22 | A serotonergic axon-cilium synapse drives nuclear signaling to maintain chromatin accessibility
Shu-Hsien Sheu , Srigokul Upadhyayula , Vincent Dupuy , Song Pang , Andrew L. Lemire , Deepika Walpita , H. Amalia Pasolli , Fei Deng , Jinxia Wan , Lihua Wang , Justin Houser , Silvia Sanchez-Martinez , Sebastian E. Brauchi , Sambashiva Banala , Melanie Freeman , C. Shan Xu , Tom Kirchhausen , Harald F. Hess , Luke Lavis , Yu-Long Li , Séverine Chaumont-Dubel , David E. Clapham
Cell. 2022 Sep 01;185(18):3390-3407. doi: 10.1016/j.cell.2022.07.026

Chemical synapses between axons and dendrites mediate much of the brain’s intercellular communication. Here we describe a new kind of synapse – the axo-ciliary synapse - between axons and primary cilia. By employing enhanced focused ion beam – scanning electron microscopy on samples with optimally preserved ultrastructure, we discovered synapses between the serotonergic axons arising from the brainstem, and the primary cilia of hippocampal CA1 pyramidal neurons. Functionally, these cilia are enriched in a ciliary-restricted serotonin receptor, 5-hydroxytryptamine receptor 6 (HTR6), whose mutation is associated with learning and memory defects. Using a newly developed cilia-targeted serotonin sensor, we show that optogenetic stimulation of serotonergic axons results in serotonin release onto cilia. Ciliary HTR6 stimulation activates a non-canonical Gαq/11-RhoA pathway. Ablation of this pathway results in nuclear actin and chromatin accessibility changes in CA1 pyramidal neurons. Axo-ciliary synapses serve as a distinct mechanism for neuromodulators to program neuron transcription through privileged access to the nuclear compartment.

View Publication Page
08/25/22 | In situ single particle classification reveals distinct 60S maturation intermediates in cells.
Bronwyn A. Lucas , Kexin Zhang , Sarah Loerch , Nikolaus Grigorieff
eLife. 2022 Aug 25:. doi: 10.7554/eLife.79272

Electron cryo-microscopy (cryo-EM) can generate high-resolution views of cells with faithful preservation of molecular structure. In situ cryo-EM, therefore, has enormous potential to reveal the atomic details of biological processes in their native context. However, in practice, the utility of in situ cryo-EM is limited by the difficulty of reliably locating and confidently identifying molecular targets (particles) and their conformational states in the crowded cellular environment. We recently showed that 2DTM, a fine-grained template-based search applied to cryo-EM micrographs, can localize particles in two-dimensional views of cells with high precision. Here we demonstrate that the signal-to-noise ratio (SNR) observed with 2DTM can be used to differentiate related complexes in focused ion beam (FIB)-milled cell sections. We apply this method in two contexts to locate and classify related intermediate states of 60S ribosome biogenesis in the Saccharomyces cerevisiae cell nucleus. In the first, we separate the nuclear pre-60S population from the cytoplasmic mature 60S population, using the subcellular localization to validate assignment. In the second, we show that relative 2DTM SNRs can be used to separate mixed populations of nuclear pre-60S that are not visually separable. We use a maximum likelihood approach to define the probability of each particle belonging to each class, thereby establishing a statistic to describe the confidence of our classification. Without the need to generate 3D reconstructions, 2DTM can be applied even when only a few target particles exist in a cell.

View Publication Page
08/24/22 | A single-cell transcriptomic atlas of complete insect nervous systems across multiple life stages.
Corrales M, Cocanougher BT, Kohn AB, Wittenbach JD, Long XS, Lemire A, Cardona A, Singer RH, Moroz LL, Zlatic M
Neural Development. 2022 Aug 24;17(1):8. doi: 10.1186/s13064-022-00164-6

Molecular profiles of neurons influence neural development and function but bridging the gap between genes, circuits, and behavior has been very difficult. Here we used single cell RNAseq to generate a complete gene expression atlas of the Drosophila larval central nervous system composed of 131,077 single cells across three developmental stages (1 h, 24 h and 48 h after hatching). We identify 67 distinct cell clusters based on the patterns of gene expression. These include 31 functional mature larval neuron clusters, 1 ring gland cluster, 8 glial clusters, 6 neural precursor clusters, and 13 developing immature adult neuron clusters. Some clusters are present across all stages of larval development, while others are stage specific (such as developing adult neurons). We identify genes that are differentially expressed in each cluster, as well as genes that are differentially expressed at distinct stages of larval life. These differentially expressed genes provide promising candidates for regulating the function of specific neuronal and glial types in the larval nervous system, or the specification and differentiation of adult neurons. The cell transcriptome Atlas of the Drosophila larval nervous system is a valuable resource for developmental biology and systems neuroscience and provides a basis for elucidating how genes regulate neural development and function.

View Publication Page
08/23/22 | Transverse endoplasmic reticulum expansion in hereditary spastic paraplegia corticospinal axons.
Zhu P, Hung H, Batchenkova N, Nixon-Abell J, Henderson J, Zheng P, Renvoisé B, Pang S, Xu CS, Saalfeld S, Funke J, Xie Y, Svara F, Hess HF, Blackstone C
Human Molecular Genetics. 2022 Aug 23;31(16):2779-2795. doi: 10.1093/hmg/ddac072

Hereditary spastic paraplegias (HSPs) comprise a large group of inherited neurologic disorders affecting the longest corticospinal axons (SPG1-86 plus others), with shared manifestations of lower extremity spasticity and gait impairment. Common autosomal dominant HSPs are caused by mutations in genes encoding the microtubule-severing ATPase spastin (SPAST; SPG4), the membrane-bound GTPase atlastin-1 (ATL1; SPG3A) and the reticulon-like, microtubule-binding protein REEP1 (REEP1; SPG31). These proteins bind one another and function in shaping the tubular endoplasmic reticulum (ER) network. Typically, mouse models of HSPs have mild, later onset phenotypes, possibly reflecting far shorter lengths of their corticospinal axons relative to humans. Here, we have generated a robust, double mutant mouse model of HSP in which atlastin-1 is genetically modified with a K80A knock-in (KI) missense change that abolishes its GTPase activity, whereas its binding partner Reep1 is knocked out. Atl1KI/KI/Reep1-/- mice exhibit early onset and rapidly progressive declines in several motor function tests. Also, ER in mutant corticospinal axons dramatically expands transversely and periodically in a mutation dosage-dependent manner to create a ladder-like appearance, on the basis of reconstructions of focused ion beam-scanning electron microscopy datasets using machine learning-based auto-segmentation. In lockstep with changes in ER morphology, axonal mitochondria are fragmented and proportions of hypophosphorylated neurofilament H and M subunits are dramatically increased in Atl1KI/KI/Reep1-/- spinal cord. Co-occurrence of these findings links ER morphology changes to alterations in mitochondrial morphology and cytoskeletal organization. Atl1KI/KI/Reep1-/- mice represent an early onset rodent HSP model with robust behavioral and cellular readouts for testing novel therapies.

View Publication Page
08/22/22 | Visual projection neuron convergence and compensation in developing sensorimotor circuits in the Drosophila optic glomeruli
Brennan W. McFarland , HyoJong Jang , Natalie Smolin , Tanja A. Godenschwege , Aljoscha Nern , Yerbol Z. Kurmangaliyev , Catherine R. von Reyn

Visual features detected by the early visual system must be combined into higher order representations to guide behavioral decision. Although key developmental mechanisms that enable the separation of visual feature channels in early visual circuits have been discovered, relatively little is known about the mechanisms that underlie their convergence in later stages of visual processing. Here we explore the development of a functionally well-characterized sensorimotor circuit in Drosophila melanogaster, the convergence of visual projection neurons (VPNs) onto the dendrites of a large descending neuron called the giant fiber (GF). We find two VPNs encoding different visual features that target the same giant fiber dendrite establish their territories on the dendrite, in part, through sequential axon arrival during development prior to synaptogenesis. Physical occupancy is important to maintain territories, as we find the ablation of one VPN results in expanded dendrite territory of the remaining VPN, and that this compensation enables the GF to remain responsive to ethologically relevant visual stimuli. Our data highlight temporal mechanisms for visual feature convergence and promote the GF circuit, and the Drosophila optic glomeruli where VPN to GF connectivity resides, as an ideal developmental model for investigating complex wiring programs and plasticity in visual feature convergence.

View Publication Page
08/19/22 | Flexible control of behavioral variability mediated by an internal representation of head direction
Chuntao Dan , Brad K. Hulse , Vivek Jayaraman , Ann M. Hermundstad
bioRxiv. 2022 Aug 19:. doi: 10.1101/2021.08.18.456004

Internal representations are thought to support the generation of flexible, long-timescale behavioral patterns in both animals and artificial agents. Here, we present a novel conceptual framework for how Drosophila use their internal representation of head direction to maintain preferred headings in their surroundings, and how they learn to modify these preferences in the presence of selective thermal reinforcement. To develop the framework, we analyzed flies’ behavior in a classical operant visual learning paradigm and found that they use stochastically generated fixations and directed turns to express their heading preferences. Symmetries in the visual scene used in the paradigm allowed us to expose how flies’ probabilistic behavior in this setting is tethered to their head direction representation. We describe how flies’ ability to quickly adapt their behavior to the rules of their environment may rest on a behavioral policy whose parameters are flexible but whose form is genetically encoded in the structure of their circuits. Many of the mechanisms we outline may also be relevant for rapidly adaptive behavior driven by internal representations in other animals, including mammals.

View Publication Page
08/17/22 | Homeodomain proteins hierarchically specify neuronal diversity and synaptic connectivity
Chundi Xu , Tyler B. Ramos , Ed M. Rogers , Michael B. Reiser , Chris Q. Doe
bioRxiv. 2022 Aug 17:. doi: 10.1101/2021.10.01.462699

The brain generates diverse neuron types which express unique homeodomain transcription factors (TFs) and assemble into precise neural circuits. Yet a mechanistic framework is lacking for how homeodomain TFs specify both neuronal fate and synaptic connectivity. We use Drosophila lamina neurons (L1-L5) to show the homeodomain TF Brain-specific homeobox (Bsh) is initiated in lamina precursor cells (LPCs) where it specifies L4/L5 fate and suppresses homeodomain TF Zfh1 to prevent L1/L3 fate. Subsequently, Bsh activates the homeodomain TF Apterous (Ap) in L4 in a feedforward loop to express the synapse recognition molecule DIP-β, in part by Bsh direct binding a DIP-β intron. Thus, homeodomain TFs function hierarchically: primary homeodomain TF (Bsh) first specifies neuronal fate, and subsequently acts with secondary homeodomain TF (Ap) to activate DIP-β, thereby generating precise synaptic connectivity. We speculate that hierarchical homeodomain TF function may represent a general principle for coordinating neuronal fate specification and circuit assembly.

View Publication Page
08/13/22 | A vast space of compact strategies for highly efficient decisions
Tzuhsuan Ma , Ann M Hermundstad
bioRxiv. 2022 Aug 13:. doi: 10.1101/2022.08.10.503471

When foraging in dynamic and uncertain environments, animals can benefit from basing their decisions on smart inferences about hidden properties of the world. Typical theoretical approaches to understand the strategies that animals use in such settings combine Bayesian inference and value iteration to derive optimal behavioral policies that maximize total reward given changing beliefs about the environment. However, specifying these beliefs requires infinite numerical precision; with limited resources, this problem can no longer be separated into optimizing inference and optimizing action selections. To understand the space of behavioral policies in this constrained setting, we enumerate and evaluate all possible behavioral programs that can be constructed from just a handful of states. We show that only a small fraction of the top-performing programs can be constructed by approximating Bayesian inference; the remaining programs are structurally or even functionally distinct from Bayesian. To assess structural and functional relationships among all programs, we developed novel tree embedding algorithms; these embeddings, which are capable of extracting different relational structures within the program space, reveal that nearly all good programs are closely connected through single algorithmic “mutations”. We demonstrate how one can use such relational structures to efficiently search for good solutions via an evolutionary algorithm. Moreover, these embeddings reveal that the diversity of non-Bayesian behaviors originates from a handful of key mutations that broaden the functional repertoire within the space of good programs. The fact that this diversity of behaviors does not significantly compromise performance suggests a novel approach for studying how these strategies generalize across tasks.

View Publication Page