Structural Analysis of the Caenorhabditis elegans Dauer Larval Anterior Sensilla by Focused Ion Beam-Scanning Electron Microscopy

Serial Lift-Out: sampling the molecular anatomy of whole organisms

Cryo-focused ion beam milling of frozen-hydrated cells and subsequent cryo-electron tomography (cryo-ET) has enabled the structural elucidation of macromolecular complexes directly inside cells. Application of the technique to multicellular organisms and tissues, however, is still limited by sample preparation. While high-pressure freezing enables the vitrification of thicker samples, it prolongs subsequent preparation due to increased thinning times and the need for extraction procedures. Additionally, thinning removes large portions of the specimen, restricting the imageable volume to the thickness of the final lamella, typically <300 nm. Here we introduce Serial Lift-Out, an enhanced lift-out technique that increases throughput and obtainable contextual information by preparing multiple sections from single transfers. We apply Serial Lift-Out to Caenorhabditis elegans L1 larvae, yielding a cryo-ET dataset sampling the worm's anterior-posterior axis, and resolve its ribosome structure to 7 Å and a subregion of the 11-protofilament microtubule to 13 Å, illustrating how Serial Lift-Out enables the study of multicellular molecular anatomy.

Dendrite morphogenesis in Caenorhabditis elegans

Since the days of Ramón y Cajal, the vast diversity of neuronal and particularly dendrite morphology has been used to catalog neurons into different classes. Dendrite morphology varies greatly and reflects the different functions performed by different types of neurons. Significant progress has been made in our understanding of how dendrites form and the molecular factors and forces that shape these often elaborately sculpted structures. Here, we review work in the nematode Caenorhabditis elegans that has shed light on the developmental mechanisms that mediate dendrite morphogenesis with a focus on studies investigating ciliated sensory neurons and the highly elaborated dendritic trees of somatosensory neurons. These studies, which combine time-lapse imaging, genetics, and biochemistry, reveal an intricate network of factors that function both intrinsically in dendrites and extrinsically from surrounding tissues. Therefore, dendrite morphogenesis is the result of multiple tissue interactions, which ultimately determine the shape of dendritic arbors.

Comparative connectomics of dauer reveals developmental plasticity

A fundamental question in neurodevelopmental biology is how flexibly the nervous system changes during development. To address this, we reconstructed the chemical connectome of dauer, an alternative developmental stage of nematodes with distinct behavioral characteristics, by volumetric reconstruction and automated synapse detection using deep learning. With the basic architecture of the nervous system preserved, structural changes in neurons, large or small, were closely associated with connectivity changes, which in turn evoked dauer-specific behaviors such as nictation. Graph theoretical analyses revealed significant dauer-specific rewiring of sensory neuron connectivity and increased clustering within motor neurons in the dauer connectome. We suggest that the nervous system in the nematode has evolved to respond to harsh environments by developing a quantitatively and qualitatively differentiated connectome.

mEMbrain: an interactive deep learning MATLAB tool for connectomic segmentation on commodity desktops

Connectomics is fundamental in propelling our understanding of the nervous system's organization, unearthing cells and wiring diagrams reconstructed from volume electron microscopy (EM) datasets. Such reconstructions, on the one hand, have benefited from ever more precise automatic segmentation methods, which leverage sophisticated deep learning architectures and advanced machine learning algorithms. On the other hand, the field of neuroscience at large, and of image processing in particular, has manifested a need for user-friendly and open source tools which enable the community to carry out advanced analyses. In line with this second vein, here we propose mEMbrain, an interactive MATLAB-based software which wraps algorithms and functions that enable labeling and segmentation of electron microscopy datasets in a user-friendly user interface compatible with Linux and Windows. Through its integration as an API to the volume annotation and segmentation tool VAST, mEMbrain encompasses functions for ground truth generation, image preprocessing, training of deep neural networks, and on-the-fly predictions for proofreading and evaluation. The final goals of our tool are to expedite manual labeling efforts and to harness MATLAB users with an array of semi-automatic approaches for instance segmentation. We tested our tool on a variety of datasets that span different species at various scales, regions of the nervous system and developmental stages. To further expedite research in connectomics, we provide an EM resource of ground truth annotation from four different animals and five datasets, amounting to around 180 h of expert annotations, yielding more than 1.2 GB of annotated EM images. In addition, we provide a set of four pre-trained networks for said datasets. All tools are available from https://lichtman.rc.fas.harvard.edu/mEMbrain/. With our software, our hope is to provide a solution for lab-based neural reconstructions which does not require coding by the user, thus paving the way to affordable connectomics.

mEMbrain: an interactive deep learning MATLAB tool for connectomic segmentation on commodity desktops

Connectomics is fundamental in propelling our understanding of the nervous system’s organization, unearthing cells and wiring diagrams reconstructed from volume electron microscopy (EM) datasets. Such reconstructions, on the one hand, have benefited from ever more precise automatic segmentation methods, which leverage sophisticated deep learning architectures and advanced machine learning algorithms. On the other hand, the field of neuroscience at large, and of image processing in particular, has manifested a need for user-friendly and open source tools which enable the community to carry out advanced analyses. In line with this second vein, here we propose mEMbrain, an interactive MATLAB-based software which wraps algorithms and functions that enable labeling and segmentation of electron microscopy datasets in a user-friendly user interface compatible with Linux and Windows. Through its integration as an API to the volume annotation and segmentation tool VAST, mEMbrain encompasses functions for ground truth generation, image preprocessing, training of deep neural networks, and on-the-fly predictions for proofreading and evaluation. The final goals of our tool are to expedite manual labeling efforts and to harness MATLAB users with an array of semi-automatic approaches for instance segmentation. We tested our tool on a variety of datasets that span different species at various scales, regions of the nervous system and developmental stages. To further expedite research in connectomics, we provide an EM resource of ground truth annotation from 4 different animals and 5 datasets, amounting to around 180 hours of expert annotations, yielding more than 1.2 GB of annotated EM images. In addition, we provide a set of 4 pre-trained networks for said datasets. All tools are available from https://lichtman.rc.fas.harvard.edu/mEMbrain/ . With our software, our hope is to provide a solution for lab-based neural reconstructions which does not require coding by the user, thus paving the way to affordable connectomics.

Synaptogenesis: unmasking molecular mechanisms using Caenorhabditis elegans

The nematode Caenorhabditis elegans is a research model organism particularly suited to the mechanistic understanding of synapse genesis in the nervous system. Armed with powerful genetics, knowledge of complete connectomics, and modern genomics, studies using C. elegans have unveiled multiple key regulators in the formation of a functional synapse. Importantly, many signaling networks display remarkable conservation throughout animals, underscoring the contributions of C. elegans research to advance the understanding of our brain. In this chapter, we will review up-to-date information of the contribution of C. elegans to the understanding of chemical synapses, from structure to molecules and to synaptic remodeling.

Long-term imaging reveals behavioral plasticity during C. elegans dauer exit

BACKGROUND

During their lifetime, animals must adapt their behavior to survive in changing environments. This ability requires the nervous system to undergo adjustments at distinct temporal scales, from short-term dynamic changes in expression of neurotransmitters and receptors to longer-term growth, spatial and connectivity reorganization, while integrating external stimuli. The nematode Caenorhabditis elegans provides a model of nervous system plasticity, in particular its dauer exit decision. Under unfavorable conditions, larvae will enter the non-feeding and non-reproductive stress-resistant dauer stage and adapt their behavior to cope with the harsh new environment, with active reversal under improved conditions leading to resumption of reproductive development. However, how different environmental stimuli regulate the exit decision mechanism and thereby drive the larva's behavioral change is unknown. To fill this gap and provide insights on behavioral changes over extended periods of time, we developed a new open hardware method for long-term imaging (12h) of C. elegans larvae.

RESULTS

Our WormObserver platform comprises open hardware and software components for video acquisition, automated processing of large image data (> 80k images/experiment) and data analysis. We identified dauer-specific behavioral motifs and characterized the behavioral trajectory of dauer exit in different environments and genetic backgrounds to identify key decision points and stimuli promoting dauer exit. Combining long-term behavioral imaging with transcriptomics data, we find that bacterial ingestion triggers a change in neuropeptide gene expression to establish post-dauer behavior.

CONCLUSIONS

Taken together, we show how a developing nervous system can robustly integrate environmental changes activate a developmental switch and adapt the organism's behavior to a new environment. WormObserver is generally applicable to other research questions within and beyond the C. elegans field, having a modular and customizable character and allowing assessment of behavioral plasticity over longer periods.

Developmental history modulates adult olfactory behavioral preferences via regulation of chemoreceptor expression in Caenorhabditiselegans

Developmental experiences play critical roles in shaping adult physiology and behavior. We and others previously showed that adult Caenorhabditiselegans which transiently experienced dauer arrest during development (postdauer) exhibit distinct gene expression profiles as compared to control adults which bypassed the dauer stage. In particular, the expression patterns of subsets of chemoreceptor genes are markedly altered in postdauer adults. Whether altered chemoreceptor levels drive behavioral plasticity in postdauer adults is unknown. Here, we show that postdauer adults exhibit enhanced attraction to a panel of food-related attractive volatile odorants including the bacterially produced chemical diacetyl. Diacetyl-evoked responses in the AWA olfactory neuron pair are increased in both dauer larvae and postdauer adults, and we find that these increased responses are correlated with upregulation of the diacetyl receptor ODR-10 in AWA likely via both transcriptional and posttranscriptional mechanisms. We show that transcriptional upregulation of odr-10 expression in dauer larvae is in part mediated by the DAF-16 FOXO transcription factor. Via transcriptional profiling of sorted populations of AWA neurons from control and postdauer animals, we further show that the expression of a subset of additional chemoreceptor genes in AWA is regulated similarly to odr-10 in postdauer animals. Our results suggest that developmental experiences may be encoded at the level of olfactory receptor regulation, and provide a simple mechanism by which C. elegans is able to precisely modulate its behavioral preferences as a function of its current and past experiences.

Three-dimensional SEM, TEM, and STEM for analysis of large-scale biological systems

A major aim in structural cell biology is to analyze intact cells in three dimensions, visualize subcellular structures, and even localize proteins at the best possible resolution in three dimensions. Though recently developed electron microscopy tools such as electron tomography, or three-dimensional (3D) scanning electron microscopy, offer great resolution in three dimensions, the challenge is that, the better the resolution, usually the smaller the volume under investigation. Several different approaches to overcome this challenge were presented at the Microscopy Conference in Vienna in 2021. These tools include array tomography, batch tomography, or scanning transmission electron tomography, all of which can nowadays be extended toward correlative light and electron tomography, with greatly increased 3D information. Here, we review these tools, describe the underlying procedures, and discuss their advantages and limits.