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Carbon dioxide (CO2) is a critical biological signal that is noxious to many animals at high concentrations. The earthwormDendrobaena venetalives in subterranean burrows containing high levels of CO2and respires through its skin. Despite the ecological and agricultural importance of earthworms, relatively little is known about how they make decisions in their environment, including their response to elevated levels of CO2. To examine CO2detection in this species, we designed the exudate assay, in which we placed an earthworm in a sealed container, exposed it to varying concentrations of CO2for one minute, and recorded the amount of exudate secreted. Because earthworms excrete exudate in response to noxious stimuli, we hypothesized that the amount of exudate produced was proportional to the amount of irritation. We repeated these experiments after treatment with several blockers for molecules with potential involvement in CO2detection, including carbonic anhydrases, guanylate cyclase, TRPA1 channels, ASICs, and OTOP channels. We also confirmed the presence of homologous transcripts for each of these gene families in an epithelial transcriptome forD. veneta.Additionally, since organisms often detect CO2levels indirectly by monitoring the conversion to carbonic acid (a weak acid), we used the exudate assay to evaluate aversion to additional weak acids (formic acid, acetic acid, and propionic acid). Earthworms excreted significantly more exudate in response to CO2in a dosage-dependent manner, and this response was muted by the general carbonic anhydrase inhibitor acetazolamide, the carbonic anhydrase IX/XII inhibitor indisulam, the calcium channel blocker ruthenium red, the sodium channel blocker amiloride, and the acid-sensing ion channel blocker diminazene aceturate. These data provide evidence of the role of carbonic anhydrase and ENaCs in earthworm CO2detection and contribute to our understanding of the mechanisms used by earthworms to detect and react to weak acids in their environment.Contribution to the field statement:Carbon dioxide (CO2) is a major byproduct of cellular respiration and an important biological signal. The metabolism of animals living underground in burrows can cause the concentration of CO2to increase above atmospheric CO2. Most animals have multiple molecular mechanisms that detect CO2and find high concentrations aversive or noxious; some subterranean animals have adaptations that make them more tolerant of concentrated CO2. Earthworms live in burrows, are a keystone species for subterranean ecosystems, and in their lightless environment must rely primarily on tactile and chemical signals. Despite the profound importance of earthworms to the ecosystems, few if any of the molecular mechanisms they use to detect these signals have been characterized. Here we use RNA sequencing to develop a list of candidate mechanisms that the European nightcrawler may use to respond to CO2. We also have developed an assay for comparing how noxious different concentrations of volatile compounds are to earthworms. In the present study, we utilize that assay with inhibitors to further narrow the possible multiple molecular mechanisms responsible for the detection of CO2. We suspect that our study is among the first attempts to combine RNA-sequencing technology and pharmacology to describe earthworm sensory biology.

We, the participants of the First Organoid Intelligence Workshop - "Forming an OI Community" (22-24 February 2022), call on the international scientific community to explore the potential of human brain-based organoid cell cultures to advance our understanding of the brain and unleash new forms of biocomputing while recognizing and addressing the associated ethical implications. The term "organoid intelligence" (OI) has been coined to describe this research and development approach (1) in a manner consistent with the term "artificial intelligence" (AI) - used to describe the enablement of computers to perform tasks normally requiring human intelligence. OI has the potential for diverse and far-reaching applications that could benefit humankind and our planet, and which urge the strategic development of OI as a collaborative scientific discipline. OI holds promise to elucidate the physiology of human cognitive functions such as memory and learning. It presents game-changing opportunities in biological and hybrid computing that could overcome significant limitations in silicon-based computing. It offers the prospect of unparalleled advances in interfaces between brains and machines. Finally, OI could allow breakthroughs in modeling and treating dementias and other neurogenerative disorders that cause an immense and growing disease burden globally. Realizing the world-changing potential of OI will require scientific breakthroughs. We need advances in human stem cell technology and bioengineering to recreate brain architectures and to model their potential for pseudo-cognitive capabilities. We need interface breakthroughs to allow us to deliver input signals to organoids, measure output signals, and employ feedback mechanisms to model learning processes. We also need novel machine learning, big data, and AI technologies to allow us to understand brain organoids.

Continual learning without catastrophic forgetting is a challenge for artificial systems but it is done naturally across a range of biological systems, including in insects. A recurrent circuit has been identified in the fruit fly mushroom body to consolidate long term memories (LTM), but there is not currently an algorithmic understanding of this LTM formation. We hypothesize that generative replay is occurring to consolidate memories in this recurrent circuit, and find anatomical evidence in synapse-level connectivity that supports this hypothesis. Next, we introduce a computational model which combines an initial experience phase and LTM phase to perform generative replay based continual learning. When evaluated on a CIFAR-100 class-incremental continual learning task, the modeled LTM phase increases classification performance by 20% and approaches within 2% of the performance for a non-incremental upper bound baseline. Unique elements of the proposed generative replay model include: 1) coupling high dimensional sparse activation patterns with generative replay and 2) sampling and reconstructing higher level representations for training generative replay (as opposed to reconstructing sensory-level or processed sensory-level representations). Additionally, we make the experimentally testable prediction that a specific set of synapses would need to undergo experience-dependent plasticity during LTM formation to support our generative replay based model.

The healthy human brain has long been considered a sterile environment, with the blood brain barrier preventing the formation of a bacterial brain microbiome. Recent electron microscopy (EM) imaging of brain tissue has, however, provided the first preliminary evidence of bacteria in otherwise healthy brain slices. Whether due to contamination, disease, or a previously unknown relationship of bacteria to healthy brain tissue, novel tools are needed to detect and search for bacteria in nanoscale, volumetric EM images. While computer vision tools are widely used in cell segmentation and object detection problems in EM imaging, no bacteria detection tool or dataset exists. Overcoming the rarity of training data, this work presents the first pipeline for training a bacteria detection network for EM images, leveraging existing deep networks for object detection. A deployment and proofreading pipeline is presented, along with characterization of deployment to public EM image datasets. While bacteria in healthy brain tissue were not discovered in this work, this tool presents an opportunity for large scale bacteria search in EM imaging for both scientific discovery and experimental quality control, and serves more generally as a framework for sparse object detection in large imagery datasets.

Neuroscientists now have the opportunity to analyze synaptic resolution connectomes that are larger than the memory on single consumer workstations. As dataset size and tissue diversity have grown, there is increasing interest in conducting comparative connectomics research, including rapidly querying and searching for recurring patterns of connectivity across brain regions and species. There is also a demand for algorithm reuse — applying methods developed for one dataset to another volume. A key technological hurdle is enabling researchers to efficiently and effectively query these diverse datasets, especially as the raw image volumes grow beyond terabyte sizes. Existing community tools can perform such queries and analysis on smaller scale datasets, which can fit locally in memory, but the path to scaling remains unclear. Existing solutions such as neuPrint or FlyBrainLab enable these queries for specific datasets, but there remains a need to generalize algorithms and standards across datasets. To overcome this challenge, we present a software framework for comparative connectomics and graph discovery to make connectomes easy to analyze, even when larger-than-RAM, and even when stored in disparate datastores. This software suite includes visualization tools, a web portal, a connectivity and annotation query engine, and the ability to interface with a variety of data sources and community tools from the neuroscience community. These tools include MossDB (an immutable datastore for metadata and rich annotations); Grand (for prototyping larger-than-RAM graphs); GrandIso-Cloud (for querying existing graphs that exceed the capabilities of a single work-station); and Motif Studio (for enabling the public to query across connectomes). These tools interface with existing frameworks such as neuPrint, graph databases such as Neo4j, and standard data analysis tools such as Pandas or NetworkX. Together, these tools enable tool and algorithm reuse, standardization, and neuroscience discovery.

While many instances of GPCR dimerization have been reported for vertebrate receptors, invertebrate GPCR dimerization remains poorly investigated, with few invertebrate GPCRs having been shown to assemble as dimers. To date, no Drosophila GPCRs have been shown to assemble as dimers. To explore the evolutionary conservation of GPCR dimerization, we employed an acceptor-photobleaching FRET methodology to evaluate whether multiple subclasses of Drosophila GPCRs assembled as homodimers when heterologously expressed in HEK-293 T cells. We C-terminally tagged multiple Drosophila neuropeptide GPCRs that exhibited structural homology with a vertebrate GPCR family member previously shown to assemble as a dimer with CFP and YFP fluorophores and visualized these receptors through confocal microscopy. FRET responses were determined based on the increase in CFP emission intensity following YFP photobleaching for each receptor pair tested. A significant FRET response was observed for each receptor expressed as a homodimer pair, while non-significant FRET responses were displayed by both cytosolic CFP and YFP expressed alone, and a heterodimeric pair of receptors from unrelated families. These findings suggest that receptors exhibiting positive FRET responses assemble as homodimers at the plasma membrane and are the first to suggest that Drosophila GPCRs assemble as homodimeric complexes. We propose that GPCR dimerization arose early in metazoan evolution and likely plays an important and underappreciated role in the cellular signaling of all animals.

In insects, Adipokinetic hormone is the primary hormone responsible for the mobilization of stored energy. While a growing body of evidence has solidified role of Adipokinetic hormone (AKH) in modulating the physiological and behavioral responses to metabolic stress, little is known about the upstream endocrine circuit that directly regulates AKH release. We evaluated the AKH-producing cell (APC) transcriptome to identify potential regulatory elements controlling APC activity, and found that a number of receptors show consistent expression levels, including all known dopamine receptors and the Pigment Dispersing Factor receptor (PDFR). We tested the consequences of targeted genetic knockdown and found that AKH expression of RNAi elements corresponding to each dopamine receptor caused a significant reduction in survival under starvation. In contrast, PDFR knockdown significantly extended lifespan under starvation whereas expression of a tethered PDF in APCs resulted in a significantly shorter lifespan. These manipulations caused various changes in locomotor activity under starvation. We used live-cell imaging to evaluate the acute effects of the ligands for these receptors on APC activation. Dopamine application led to a transient increase in intracellular calcium in a sugar-dependent manner. Furthermore, co-application of dopamine and ecdysone led to a complete loss of this response, suggesting that these two hormones act antagonistically. We also found that PDF application led to an increase in cAMP in APCs, and that this response was dependent on expression of the PDFR in APCs. Together these results suggest a complex circuit in which multiple hormones act on APCs to modulate metabolic state.

In insects, adipokinetic hormone is the primary hormone responsible for the mobilization of stored energy. While a growing body of evidence has solidified the role of adipokinetic hormone (AKH) in modulating the physiological and behavioral responses to metabolic stress, little is known about the upstream endocrine circuit that directly regulates AKH release. We evaluated the AKH-producing cell (APC) transcriptome to identify potential regulatory elements controlling APC activity and found that a number of receptors showed consistent expression levels, including all known dopamine receptors and the pigment dispersing factor receptor (PDFR). We tested the consequences of targeted genetic knockdown and found that APC limited expression of RNAi elements corresponding to each dopamine receptor and caused a significant reduction in survival under starvation. In contrast, PDFR knockdown significantly extended lifespan under starvation, whereas expression of a tethered PDF in APCs resulted in significantly shorter lifespans. These manipulations caused various changes in locomotor activity under starvation. We used live-cell imaging to evaluate the acute effects of the ligands for these receptors on APC activation. Dopamine application led to a transient increase in intracellular calcium in a trehalose-dependent manner. Furthermore, coapplication of dopamine and ecdysone led to a complete loss of this response, suggesting that these two hormones act antagonistically. We also found that PDF application led to an increase in cAMP in APCs and that this response was dependent on expression of the PDFR in APCs. Together, these results suggest a complex circuit in which multiple hormones act on APCs to modulate metabolic state.

Neuroscientists can leverage technological advances to image neural tissue across a range of different scales, potentially forming the basis for the next generation of brain atlases and circuit reconstructions at submicron resolution, using Electron Microscopy and X-ray Microtomography modalities. However, there is variability in data collection, annotation, and storage approaches, which limits effective comparative and secondary analysis. There has been great progress in standardizing interfaces for large-scale spatial image data, but more work is needed to standardize annotations, especially metadata associated with neuroanatomical entities. Standardization will enable validation, sharing, and replication, greatly amplifying investment throughout the connectomics community. We share key design considerations and a usecase developed for metadata for a recent large-scale dataset.

All organisms confront the challenges of maintaining metabolic homeostasis in light of both variabilities in nutrient supplies and energetic costs of different physiologies and behaviors. While all cells are nutrient sensitive, only relative few cells within Metazoans are nutrient sensing cells. Nutrient sensing cells organize systemic behavioral and physiological responses to changing metabolic states. One group of cells present in the arthropods, is the adipokinetic hormone producing cells (APCs). APCs possess intrinsic nutrient sensors and receive contextual information regarding metabolic state through other endocrine connections. APCs express receptors for different hormones which modulate APC physiology and the secretion of the adipokinetic hormone (AKH). APCs are functionally similar to alpha cells in the mammalian pancreas and display a similar physiological organization. AKH release results in both hypertrehalosemia and hyperlipidemia through high affinity binding to the AKH receptor (AKHR). Another hallmark of AKH signaling is heightened locomotor activity, which accompanies starvation and is thought to enhance foraging. In this review, we discuss mechanisms of nutrient sensing and modulation of AKH release. Additionally, we compare the organization of AKH/AKHR signaling in different taxa. Lastly, we consider the signals that APCs integrate as well as recent experimental results that have expanded the functional repertoire of AKH signaling, further establishing this as both a metabolic and stress hormone.

Rigorous comparisons of human and machine learning algorithm performance on the same task help to support accurate claims about algorithm success rates and advances understanding of their performance relative to that of human performers. In turn, these comparisons are critical for supporting advances in artificial intelligence. However, the machine learning community has lacked a standardized, consensus framework for performing the evaluations of human performance necessary for comparison. We demonstrate common pitfalls in a designing the human performance evaluation and propose a framework for the evaluation of human performance, illustrating guiding principles for a successful comparison. These principles are first, to design the human evaluation with an understanding of the differences between human and algorithm cognition; second, to match trials between human participants and the algorithm evaluation, and third, to employ best practices for psychology research studies, such as the collection and analysis of supplementary and subjective data and adhering to ethical review protocols. We demonstrate our framework's utility for designing a study to evaluate human performance on a one-shot learning task. Adoption of this common framework may provide a standard approach to evaluate algorithm performance and aid in the reproducibility of comparisons between human and machine learning algorithm performance.

Adipokinetic Hormone (AKH) is the primary insect hormone that mobilizes stored energy and is functional equivalent to mammalian glucagon. While most studies have focused on exploring the functional roles of AKH, relatively little is known about how AKH secretion is regulated. We assessed the AKH cell transcriptome and mined the data set for specific insight into the identities of different ion channels expressed in this cell lineage. We found reliable expression of multiple ion channel genes with multiple members for each ionic species. Specifically, we found significant signals for 39 of the either known or suspected ion channel genes within the Drosophila genome. We next performed a targeted RNAi screen aimed to identify the functional contribution of these different ion channels that may participate in excitation-secretion coupling in AKH producing cells (APCs). We assessed starvation survival, because changes in AKH signaling have previously been shown to impact starvation sensitivity. Genetic knockdown of three genes (Ca-Beta, Sur, and sei), in AKH producing cells caused highly significant changes (P < 0.001) in both male and female lifespan, and knockdown of six other genes (Shaw, cac, Ih, NaCP60E, stj, and TASK6) caused significant changes (P < 0.05) in only female lifespan. Specifically, the genetic knockdown of Ca-Beta and Sur led to increases in starvation lifespan, whereas the knockdown of sei decreased starvation survivorship. Focusing on these three strongest candidates from the behavioral screen, we assessed other AKH-dependent phenotypes. The AKH hormone is required for starvation-induced hyperactivity, and we found that these three ion channel gene knockdowns changed activity profiles and further suggest a modulatory role of these channels in AKH release. We eliminated the possibility that these genetic elements caused AKH cell lethality, and using independent methods, we verified expression of these genes in AKH cells. Collectively, these results suggest a model of AKH-cell excitability and establish an experimental framework for evaluating intrinsic mechanisms of AKH release.

In insects, Adipokinetic hormone is the primary hormone responsible for the mobilization of stored energy. While a growing body of evidence has solidified AKH’s role in modulating the physiological and behavioral responses to metabolic stress, little is known about the upstream endocrine circuit that directly regulates AKH release. We evaluated the AKH-expressing cell transcriptome to identify potential regulatory elements controlling AKH cell activity, and found that a number of receptors show consistent expression levels, including all known dopamine receptors, dopamine ecdysone receptor (DopEcR), Dopamine 2-like receptor (D2R), Dopamine 1-like receptor 2 (DopR2), DopR, and the Pigment Dispersing Factor (PDFR). We tested the consequences of targeted genetic knockdown and found that RNAi elements targeting each dopamine receptor caused a significant reduction in survival under starvation. In contrast, PDFR knockdown significantly extended lifespan under starvation whereas expression of a tethered PDF in AKH cells resulted in a significantly shorter lifespan during starvation. These manipulations also caused various changes in locomotor activity under starvation. Specifically, there were higher amounts of locomotor activity in dopamine receptor knockdowns, in both replete and starved states. PDFR knockdown resulted in increased locomotion during replete conditions and locomotion levels that were comparable to wild-type during starvation. Expression of a membrane-tethered PDF led to decreased locomotion under baseline and starvation. Next, we used live-cell imaging to evaluate the acute effects of the ligands for these receptors (dopamine, ecdysone, and Pigment Dispersing Factor) on AKH cell activation. Dopamine application led to a transient increase in intracellular calcium in a sugar-dependent manner. Furthermore, we found that co-application of dopamine and ecdysone led to a complete loss of this response, suggesting that these two hormones are acting antagonistically. We also found that PDF application directly led to an increase in cAMP in AKH cells, and that this response was dependent on expression of the PDFR in AKH cells. Together these results suggest a complex circuit in which multiple hormones act on AKH cells to modulate metabolic state.

G protein-coupled receptors are the largest superfamily of cell surface receptors in the Metazoa and play critical roles in transducing extracellular signals into intracellular responses. This action is mediated through conformational changes in the receptor following ligand binding. A number of conserved motifs have critical roles in GPCR function, and here we focus on a highly conserved motif (WxFG) in extracellular loop one (EL1). A phylogenetic analysis documents the presence of the WxFG motif in ∼90% of Class A GPCRs and the motif is represented in 17 of the 19 Class A GPCR subfamilies. Using site-directed mutagenesis, we mutagenized the conserved tryptophan residue in eight receptors which are members of disparate class A GPCR subfamilies from different taxa. The modification of the Drosophila leucokinin receptor shows that substitution of any non-aromatic amino acid for the tryptophan leads to a loss of receptor function. Additionally, leucine substitutions at this position caused similar signaling defects in the follicle-stimulating hormone receptor (FSHR), Galanin receptor (GALR1), AKH receptor (AKHR), corazonin receptor (CRZR), and muscarinic acetylcholine receptor (mACHR1). Visualization of modified receptors through the incorporation of a fluorescent tag revealed a severe reduction in plasma membrane expression, indicating aberrant trafficking of these modified receptors. Taken together, these results suggest a novel role for the WxFG motif in GPCR trafficking and receptor function.