Estimating the Postmortem Interval of Carcasses in the Water Using the Carrion Insect, Brain Tissue RNA, Bacterial Biofilm, and Algae

The accurate estimation of postmortem interval (PMI) is crucial in the investigation of homicide cases. Unlike carcasses on land, various biological and abiotic factors affect the decomposition of carcasses in water. In addition, the insect evidence (e.g., blow flies) that is commonly used to estimate the PMI are unavailable before the carcasses float on water. Therefore, it is difficult to estimate the PMI of a carcass in water. This study aimed to explore an effective way of estimating the PMI of a carcass in water. Carrion insects, brain tissue RNA, bacterial biofilm on the skin surface, and algae in water with PMI were studied using 45 rat carcasses in a small river. The results showed that carrion insects might not be suitable for the estimation of PMI of a carcass in water since they do not have a regular succession pattern as a carcass on land, and the flies only colonized six of the carcasses. The target genes (β-actin, GAPDH, and 18S) in the brain tissue were associated with the PMI in a time-dependent manner within 1 week after death. A polynomial regression analysis was used to assess the relationship between the gene expression profiles and PMI. The correlation coefficient R2 of each regression equation was ≥ 0.924. A third-generation sequencing analysis showed that the bacteria on the skin surface of the carcass and the algae in the water samples around the carcass had a regular succession pattern, where Cryptomonas and Placoneis incased and decreased, respectively, within first 9 days. The results of this study provide a promising way to use the brain tissue RNA, bacterial biofilm, and algae to estimate the PMI of a carcass in water.

Molecular Rationale of Insect-Microbes Symbiosis—From Insect Behaviour to Mechanism

Insects nurture a panoply of microbial populations that are often obligatory and exist mutually with their hosts. Symbionts not only impact their host fitness but also shape the trajectory of their phenotype. This co-constructed niche successfully evolved long in the past to mark advanced ecological specialization. The resident microbes regulate insect nutrition by controlling their host plant specialization and immunity. It enhances the host fitness and performance by detoxifying toxins secreted by the predators and abstains them. The profound effect of a microbial population on insect physiology and behaviour is exploited to understand the host–microbial system in diverse taxa. Emergent research of insect-associated microbes has revealed their potential to modulate insect brain functions and, ultimately, control their behaviours, including social interactions. The revelation of the gut microbiota–brain axis has now unravelled insects as a cost-effective potential model to study neurodegenerative disorders and behavioural dysfunctions in humans. This article reviewed our knowledge about the insect–microbial system, an exquisite network of interactions operating between insects and microbes, its mechanistic insight that holds intricate multi-organismal systems in harmony, and its future perspectives. The demystification of molecular networks governing insect–microbial symbiosis will reveal the perplexing behaviours of insects that could be utilized in managing insect pests.

Circuits for integrating learned and innate valences in the insect brain

Animal behavior is shaped both by evolution and by individual experience. Parallel brain pathways encode innate and learned valences of cues, but the way in which they are integrated during action-selection is not well understood. We used electron microscopy to comprehensively map with synaptic resolution all neurons downstream of all Mushroom Body output neurons (encoding learned valences) and characterized their patterns of interaction with Lateral Horn neurons (encoding innate valences) in Drosophila larva. The connectome revealed multiple convergence neuron types that receive convergent Mushroom Body and Lateral Horn inputs. A subset of these receives excitatory input from positive-valence MB and LH pathways and inhibitory input from negative-valence MB pathways. We confirmed functional connectivity from LH and MB pathways and behavioral roles of two of these neurons. These neurons encode integrated odor value and bidirectionally regulate turning. Based on this we speculate that learning could potentially skew the balance of excitation and inhibition onto these neurons and thereby modulate turning. Together, our study provides insights into the circuits that integrate learned and innate to modify behavior.

Interspecific variation of antennal lobe composition among four hornet species

Olfaction is a crucial sensory modality underlying foraging, social and mating behaviors in many insects. Since the olfactory system is at the interface between the animal and its environment, it receives strong evolutionary pressures that promote neuronal adaptations and phenotypic variations across species. Hornets are large eusocial predatory wasps with a highly developed olfactory system, critical for foraging and intra-specific communication. In their natural range, hornet species display contrasting ecologies and olfactory-based behaviors, which might match to adaptive shifts in their olfactory system. The first olfactory processing center of the insect brain, the antennal lobe, is made of morphological and functional units called glomeruli. Using fluorescent staining, confocal microscopy and 3D reconstructions, we compared antennal lobe structure, glomerular numbers and volumes in four hornet species (Vespa crabro, Vespa velutina, Vespa mandarinia and Vespa orientalis) with marked differences in nesting site preferences and predatory behaviors. Despite a conserved organization of their antennal lobe compartments, glomeruli numbers varied strongly between species, including in a subsystem thought to process intraspecific cuticular signals. Moreover, specific adaptations involving enlarged glomeruli appeared in two species, V. crabro and V. mandarinia, but not in the others. We discuss the possible function of these adaptations based on species-specific behavioral differences.

Honeybee Brain Oscillations Are Generated by Microtubules. The Concept of a Brain Central Oscillator

Microtubules (MTs) are important structures of the cytoskeleton in neurons. Mammalian brain MTs act as biomolecular transistors that generate highly synchronous electrical oscillations. However, their role in brain function is largely unknown. To gain insight into the MT electrical oscillatory activity of the brain, we turned to the honeybee (Apis mellifera) as a useful model to isolate brains and MTs. The patch clamp technique was applied to MT sheets of purified honeybee brain MTs. High resistance seal patches showed electrical oscillations that linearly depended on the holding potential between ± 200 mV and had an average conductance in the order of ~9 nS. To place these oscillations in the context of the brain, we also explored local field potential (LFP) recordings from the Triton X-permeabilized whole honeybee brain unmasking spontaneous oscillations after but not before tissue permeabilization. Frequency domain spectral analysis of time records indicated at least two major peaks at approximately ~38 Hz and ~93 Hz in both preparations. The present data provide evidence that MT electrical oscillations are a novel signaling mechanism implicated in brain wave activity observed in the insect brain.

Appetitive olfactory learning suffers in ants when octopamine or dopamine receptors are blocked

Associative learning relies on the detection of coincidence between a stimulus and a reward or punishment. In the insect brain, this process is carried out in the mushroom bodies under control of octopaminergic and dopaminergic neurons. It was assumed that appetitive learning is governed by octopaminergic neurons, while dopamine is required for aversive learning. This view has been recently challenged: Both neurotransmitters are involved in both types of learning in bees and flies. Here, we test which neurotransmitters are required for appetitive learning in ants. We trained Lasius niger workers to discriminate two mixtures of linear hydrocarbons and to associate one of them with a sucrose reward. We analysed the walking paths of the ants using machine learning and found that the ants spent more time near the rewarded odour than the other, a preference that was stable for at least 24 hours. We then treated the ants before learning with either epinastine, an octopamine receptor blocker, or with flupentixol, a dopamine receptor blocker. Ants with blocked octopamine receptors did not prefer the rewarded odour. Octopamine signalling is thus necessary for appetitive learning of olfactory cues, likely because it signals information about odours or reward to the mushroom body. In contrast, ants with blocked dopamine receptors initially learned the rewarded odour but failed to retrieve this memory 24 hours later. Dopamine is thus likely required for long-term memory consolidation, independent of short-term memory formation. Our results show that appetitive olfactory learning depends on both octopamine and dopamine signalling in ants.

A micro-CT-based standard brain atlas of the bumblebee

In recent years, bumblebees have become a prominent insect model organism for a variety of biological disciplines, particularly to investigate learning behaviors as well as visual performance. Understanding these behaviors and their underlying neurobiological principles requires a clear understanding of brain anatomy. Furthermore, to be able to compare neuronal branching patterns across individuals, a common framework is required, which has led to the development of 3D standard brain atlases in most of the neurobiological insect model species. Yet, no bumblebee 3D standard brain atlas has been generated. Here we present a brain atlas for the buff-tailed bumblebee Bombus terrestris using micro-computed tomography (micro-CT) scans as a source for the raw data sets, rather than traditional confocal microscopy, to produce the first ever micro-CT-based insect brain atlas. We illustrate the advantages of the micro-CT technique, namely, identical native resolution in the three cardinal planes and 3D structure being better preserved. Our Bombus terrestris brain atlas consists of 30 neuropils reconstructed from ten individual worker bees, with micro-CT allowing us to segment neuropils completely intact, including the lamina, which is a tissue structure often damaged when dissecting for immunolabeling. Our brain atlas can serve as a platform to facilitate future neuroscience studies in bumblebees and illustrates the advantages of micro-CT for specific applications in insect neuroanatomy.

Developmental plasticity in male courtship in Bicyclus anynana butterflies is driven by hormone regulation of the yellow gene

The organizational role for hormones in the regulation of sexual behavior is currently poorly explored. Previous work showed that seasonal variation in levels of the steroid hormone 20-hydroxyecdysone (20E) during pupal development regulates plasticity in male courtship behavior in Bicyclus anynana butterflies. Wet season (WS) males, reared at high temperature, have high levels of 20-hydroxyecdysone (20E) during pupation and become active courters. Dry season (DS) males, reared at low temperatures, have lower levels of 20E and lower courtship rates. Rescue of WS courtship rates can be achieved via injection of 20E into DS male pupae, but it is still unknown whether 20E alters gene expression in the pupal brain, and if so, the identity of those targets. Using transcriptomics, qPCR, and behavioral assays with a transgenic knockout, we show that higher expression levels of the yellow gene in DS male pupal brains, relative to WS brains, represses courtship in DS males. Furthermore, injecting DS males with 20E downregulates yellow to WS levels 4 hours post-injection, revealing a hormone sensitive window that determines courtship behavior. These findings are in striking contrast to Drosophila, where yellow is required for active male courtship behavior. We conclude that 20E plays an organizational role during pupal brain development by regulating the expression of yellow, which is a repressor of the neural circuity for male courtship behavior in B. anynana. This work shows that similar to vertebrates, hormones can also play an organizational role in insect brains, leading to permanent changes in adult sexual behavior.Significance StatementBehavioral plasticity in adult insects is known to be regulated by hormones, which activate neural circuits in response to environmental cues. Here, we show that hormones can also regulate adult behavioral plasticity by altering gene expression during brain development, adjusting the insect’s behavior to predictable seasonal environmental variation. We show that seasonal changes in the hormone 20E alters expression of the yellow gene in the developing pupal brain of Bicyclus anynana butterflies, which leads to differences in male courtship behavior between the dry and wet seasonal forms. This work provides one of the first examples of the organizational role of hormones in altering gene expression and adult sexual behavior in the developing insect brain.

Appetitive learning relies on octopamine and dopamine in ants

Associative learning relies on the detection of coincidence between a stimulus and a reward or punishment. In the insect brain, this process is thought to be carried out in the mushroom bodies under control of octopaminergic and dopaminergic neurons. It was assumed that appetitive learning is governed by octopaminergic neurons, while dopamine is required for aversive learning. This view has been recently challenged: Both neurotransmitters seem to be involved in both types of memory in bees and flies. Here, we test which neurotransmitters are required for appetitive learning in ants. We trained Lasius niger ant workers to discriminate two mixtures of linear hydrocarbons and associate one of them with a sucrose reward. We analysed the behaviour of the trained ants using machine learning and found that they preferred the rewarded odour over the other, a preference that was stable for at least 24 hours. We then treated the ants before learning with either epinastine, an octopamine receptor blocker, or with flupentixol, a dopamine receptor blocker. Ants with blocked octopamine receptors did not remember the rewarded odour. Octopamine signalling is thus necessary for the formation of appetitive memory. In contrast, ants with blocked dopamine receptors initially learned the rewarded odour but failed to retrieve this memory 24 hours later. Dopamine is thus required for long-term memory consolidation during appetitive conditioning, independent of short-term memory formation. Our results show that appetitive learning depends on both octopamine and dopamine signalling in ants.

Elucidating the complex organization of neural micro-domains in the locust Schistocerca gregaria using dMRI

To understand brain function it is necessary to characterize both the underlying structural connectivity between neurons and the physiological integrity of these connections. Previous research exploring insect brain connectivity has typically used electron microscopy techniques, but this methodology cannot be applied to living animals and so cannot be used to understand dynamic physiological processes. The relatively large brain of the desert locust, Schistercera gregaria (Forksȧl) is ideal for exploring a novel methodology; micro diffusion magnetic resonance imaging (micro-dMRI) for the characterization of neuronal connectivity in an insect brain. The diffusion-weighted imaging (DWI) data were acquired on a preclinical system using a customised multi-shell diffusion MRI scheme optimized to image the locust brain. Endogenous imaging contrasts from the averaged DWIs and Diffusion Kurtosis Imaging (DKI) scheme were applied to classify various anatomical features and diffusion patterns in neuropils, respectively. The application of micro-dMRI modelling to the locust brain provides a novel means of identifying anatomical regions and inferring connectivity of large tracts in an insect brain. Furthermore, quantitative imaging indices derived from the kurtosis model that include fractional anisotropy (FA), mean diffusivity (MD) and kurtosis anisotropy (KA) can be extracted. These metrics could, in future, be used to quantify longitudinal structural changes in the nervous system of the locust brain that occur due to environmental stressors or ageing.