Leucokinin and Associated Neuropeptides Regulate Multiple Aspects of Physiology and Behavior in Drosophila

Corticotropin-releasing factor-like diuretic hormone 44 and five corresponding GPCRs in Drosophila suzukii: Structural and functional characterization

Diuretic hormones (DHs) activate corresponding G protein-coupled receptors (GPCRs), mediating the water and ion homeostasis in arthropods. There are two different DHs known to be expressed in insects, calcitonin (CT)-like DH31 and corticotropin-releasing factor (CRF)-like DH44. In this study, we identified and characterized a DH44 and five GPCR variants, DH44-R1 and DH44-R2a/b/c/d, in Drosophila suzukii (spotted-wing drosophila), causing detrimental damage to fresh and soft-skinned fruits. Among the five DH44 receptors, DH44-R1 was the longest GPCR and most strongly responded to DH44, and the other DH44-R2 splicing variants were relatively shorter and over 90 % similar to each other. Some DH44-Rs including DH44-R1 utilized both cAMP and Ca2+ as second messengers. Interestingly, DH44-R1 was dominantly expressed in the brain, whereas DH44-R2 variants were dominant in the digestive organs, particularly the Malpighian tubules (MTs) by their gene expressions. The results suggest that DH44 may have multiple physiological functions, including the regulation of the sleep-wake cycle and diuretic activity. Injection of DH44 stimulated fluid secretion in adults, and the rate of the excretion increased in a dose-dependent manner. Moreover, when the flies were injected with a mixture of DH31 and DH44, a high mortality rate was observed. Here, we demonstrate the gene structures, expressions, characterization of DH44 and five GPCRs, their second messengers, and the effects of DH peptides on the fly. These investigations offer molecular insights into the physiological roles of the DH system and may assist in the fundamental aspects of developing D. suzukii management in the field.

A fluorescently-tagged tick kinin neuropeptide triggers peristalsis and labels tick midgut muscles

Ticks are blood-feeding arthropods that require heme for their successful reproduction. During feeding they also acquire pathogens that are subsequently transmitted to humans, wildlife and/or livestock. Understanding the regulation of tick midgut is important for blood meal digestion, heme and nutrient absorption processes and for aspects of pathogen biology in the host. We previously demonstrated the activity of tick kinins on the cognate G protein-coupled receptor. Herein we uncovered the physiological role of the kinin receptor in the tick midgut. A fluorescently-labeled kinin peptide with the endogenous kinin 8 sequence (TMR-RK8), identical in the ticks Rhipicephalus microplus and R. sanguineus, activated and labeled the recombinant R. microplus receptor expressed in CHO-K1 cells. When applied to the live midgut the TMR-RK8 labeled the kinin receptor in muscles while the labeled peptide with the scrambled-sequence of kinin 8 (TMR-Scrambled) did not. The unlabeled kinin 8 peptide competed TMR-RK8, decreasing confocal microscopy signal intensity, indicating TMR-RK8 specificity to muscles. TMR-RK8 was active, inducing significant midgut peristalsis that was video-recorded and evaluated with video tracking software. The TMR-Scrambled peptide used as a negative control did not elicit peristalsis. The myotropic function of kinins in eliciting tick midgut peristalsis was established.

Neurotransmitter classification from electron microscopy images at synaptic sites in Drosophila melanogaster

High-resolution electron microscopy of nervous systems has enabled the reconstruction of synaptic connectomes. However, we do not know the synaptic sign for each connection (i.e., whether a connection is excitatory or inhibitory), which is implied by the released transmitter. We demonstrate that artificial neural networks can predict transmitter types for presynapses from electron micrographs: a network trained to predict six transmitters (acetylcholine, glutamate, GABA, serotonin, dopamine, octopamine) achieves an accuracy of 87% for individual synapses, 94% for neurons, and 91% for known cell types across a D. melanogaster whole brain. We visualize the ultrastructural features used for prediction, discovering subtle but significant differences between transmitter phenotypes. We also analyze transmitter distributions across the brain and find that neurons that develop together largely express only one fast-acting transmitter (acetylcholine, glutamate, or GABA). We hope that our publicly available predictions act as an accelerant for neuroscientific hypothesis generation for the fly.

AI protein structure prediction-based modeling and mutagenesis of a protostome receptor and peptide ligands reveal key residues for their interaction

The protostome leucokinin (LK) signaling system, including LK peptides and their G protein-coupled receptors, has been characterized in several species. Despite progress in this area, molecular mechanisms governing LK peptide-receptor interactions remain to be elucidated. Previously, we identified a precursor protein for Aplysia leucokinin-like peptides (ALKs) that contains the greatest number of amidated peptides among LK precursors in all species identified so far. Here, we identified the first ALK receptor from Aplysia, ALKR. We used cell-based IP1 activation assays to demonstrate that the two ALK peptides with the most copies, ALK1 and ALK2, activated ALKR with high potencies. Other endogenous ALK-derived peptides bearing the FXXWX-amide motif also activated ALKR to various degrees. Our examination of cross-species activity of ALKs with the Anopheles LKR was consistent with a critical role for the FXXWX-amide motif in receptor activity. Furthermore, we showed, through alanine substitution of ALK1, the highly conserved phenylalanine (F), tryptophan (W), and C-terminal amidation were each essential for receptor activation. Finally, we used an AI-based protein structure prediction server (Robetta) and Autodock Vina to predict the ligand-bound conformation of ALKR. Our model predicted several interactions (i.e., hydrophobic interactions, hydrogen bonds, and amide-pi stacking) between ALK peptides and ALKR, and several of our substitution and mutagenesis experiments were consistent with the predicted model. In conclusion, our results provide important information defining the possible interactions between ALK peptides and their receptors. The workflow utilized here may be useful for studying other ligand-receptor interactions for a neuropeptide signaling system, particularly in protostomes.

Descending control of nociception in insects?

Modulation of nociception allows animals to optimize chances of survival by adapting their behaviour in different contexts. In mammals, this is executed by neurons from the brain and is referred to as the descending control of nociception. Whether insects have such control, or the neural circuits allowing it, has rarely been explored. Based on behavioural, neuroscientific and molecular evidence, we argue that insects probably have descending controls for nociception. Behavioural work shows that insects can modulate nocifensive behaviour. Such modulation is at least in part controlled by the central nervous system since the information mediating such prioritization is processed by the brain. Central nervous system control of nociception is further supported by neuroanatomical and neurobiological evidence showing that the insect brain can facilitate or suppress nocifensive behaviour, and by molecular studies revealing pathways involved in the inhibition of nocifensive behaviour both peripherally and centrally. Insects lack the endogenous opioid peptides and their receptors that contribute to mammalian descending nociception controls, so we discuss likely alternative molecular mechanisms for the insect descending nociception controls. We discuss what the existence of descending control of nociception in insects may reveal about pain perception in insects and finally consider the ethical implications of these novel findings.

Endocrine cybernetics: neuropeptides as molecular switches in behavioural decisions

Plasticity in animal behaviour relies on the ability to integrate external and internal cues from the changing environment and hence modulate activity in synaptic circuits of the brain. This context-dependent neuromodulation is largely based on non-synaptic signalling with neuropeptides. Here, we describe select peptidergic systems in the Drosophila brain that act at different levels of a hierarchy to modulate behaviour and associated physiology. These systems modulate circuits in brain regions, such as the central complex and the mushroom bodies, which supervise specific behaviours. At the top level of the hierarchy there are small numbers of large peptidergic neurons that arborize widely in multiple areas of the brain to orchestrate or modulate global activity in a state and context-dependent manner. At the bottom level local peptidergic neurons provide executive neuromodulation of sensory gain and intrinsically in restricted parts of specific neuronal circuits. The orchestrating neurons receive interoceptive signals that mediate energy and sleep homeostasis, metabolic state and circadian timing, as well as external cues that affect food search, aggression or mating. Some of these cues can be triggers of conflicting behaviours such as mating versus aggression, or sleep versus feeding, and peptidergic neurons participate in circuits, enabling behaviour choices and switches.

An evolutionary genomics view on neuropeptide genes in Hydrozoa and Endocnidozoa (Myxozoa)

BACKGROUND

The animal phylum Cnidaria consists of six classes or subphyla: Hydrozoa, Scyphozoa, Cubozoa, Staurozoa, Anthozoa, and Endocnidozoa. Cnidarians have an early evolutionary origin, diverging before the emergence of the Bilateria. Extant members from this phylum, therefore, are important resources for understanding the evolution of the nervous system. Cnidarian nervous systems are strongly peptidergic. Using genomics, we have recently shown that three neuropeptide families (the X1PRX2amides, GRFamides, and GLWamides) are wide-spread in four (Scyphozoa, Cubozoa, Staurozoa, Anthozoa) out of six cnidarian classes or subphyla, suggesting that these three neuropeptide families emerged in the common cnidarian ancestor. In the current paper, we analyze the remaining cnidarian class, Hydrozoa, and the subphylum Endocnidozoa, to make firm conclusions about the evolution of neuropeptide genes in Cnidaria.

RESULTS

We analyzed sixteen hydrozoan species with a sequenced genome or transcriptome, using a recently developed software program for discovering neuropeptide genes. These species belonged to various hydrozoan subclasses and orders, among them the laboratory models Hydra, Hydractinia, and Clytia. We found that each species contained three to five neuropeptide families. A common feature for all hydrozoans was that they contained genes coding for (i) X1PRX2amide peptides, (ii) GRFamide peptides, and (iii) GLWamide peptides. These results support our previous conclusions that these three neuropeptide families evolved early in evolution. In addition to these three neuropeptide families, hydrozoans expressed up to two other neuropeptide gene families, which, however, were only occurring in certain animal groups. Endocnidozoa (Myxozoa) are microscopically small endoparasites, which are strongly reduced. For long, it was unknown to which phylum these parasites belonged, but recently they have been associated with cnidarians. We analyzed nine endocnidozoan species and found that two of them (Polypodium hydriforme and Buddenbrockia plumatellae) expressed neuropeptide genes. These genes coded for neuropeptides belonging to the GRFamide and GLWamide families with structures closely resembling them from hydrozoans.

CONCLUSIONS

We found X1PRX2amide, GRFamide, and GLWamide peptides in all species belonging to the Hydrozoa, confirming that these peptides originated in the common cnidarian ancestor. In addition, we discovered GRFamide and GLWamide peptide genes in some members of the Endocnidozoa, thereby linking these parasites to Hydrozoa.

Insects as a New Complex Model in Hormonal Basis of Obesity

Nowadays, one of the biggest problems in healthcare is an obesity epidemic. Consumption of cheap and low-quality energy-rich diets, low physical activity, and sedentary work favor an increase in the number of obesity cases within many populations/nations. This is a burden on society, public health, and the economy with many deleterious consequences. Thus, studies concerning this disorder are extremely needed, including searching for new, effective, and fitting models. Obesity may be related, among other factors, to disrupting adipocytes activity, disturbance of metabolic homeostasis, dysregulation of hormonal balance, cardiovascular problems, or disorders in nutrition which may lead to death. Because of the high complexity of obesity, it is not easy to find an ideal model for its studies which will be suitable for genetic and physiological analysis including specification of different compounds’ (hormones, neuropeptides) functions, as well as for signaling pathways analysis. In recent times, in search of new models for human diseases there has been more and more attention paid to insects, especially in neuro-endocrine regulation. It seems that this group of animals might also be a new model for human obesity. There are many arguments that insects are a good, multidirectional, and complex model for this disease. For example, insect models can have similar conservative signaling pathways (e.g., JAK-STAT signaling pathway), the presence of similar hormonal axis (e.g., brain–gut axis), or occurrence of structural and functional homologues between neuropeptides (e.g., neuropeptide F and human neuropeptide Y, insulin-like peptides, and human insulin) compared to humans. Here we give a hint to use insects as a model for obesity that can be used in multiple ways: as a source of genetic and peptidomic data about etiology and development correlated with obesity occurrence as well as a model for novel hormonal-based drug activity and their impact on mechanism of disease occurrence.