Linking the 'why' and 'how' of ageing: evidence for somatotropic control of long-term memory function in the pond snail Lymnaea stagnalis

Transcriptome analysis provides genome annotation and expression profiles in the central nervous system of Lymnaea stagnalis at different ages

BACKGROUND

The pond snail, Lymnaea stagnalis (L. stagnalis), has served as a valuable model organism for neurobiology studies due to its simple and easily accessible central nervous system (CNS). L. stagnalis has been widely used to study neuronal networks and recently gained popularity for study of aging and neurodegenerative diseases. However, previous transcriptome studies of L. stagnalis CNS have been exclusively carried out on adult L. stagnalis only. As part of our ongoing effort studying L. stagnalis neuronal growth and connectivity at various developmental stages, we provide the first age-specific transcriptome analysis and gene annotation of young (3 months), adult (6 months), and old (18 months) L. stagnalis CNS.

RESULTS

Using the above three age cohorts, our study generated 55-69 millions of 150 bp paired-end RNA sequencing reads using the Illumina NovaSeq 6000 platform. Of these reads, ~ 74% were successfully mapped to the reference genome of L. stagnalis. Our reference-based transcriptome assembly predicted 42,478 gene loci, of which 37,661 genes encode coding sequences (CDS) of at least 100 codons. In addition, we provide gene annotations using Blast2GO and functional annotations using Pfam for ~ 95% of these sequences, contributing to the largest number of annotated genes in L. stagnalis CNS so far. Moreover, among 242 previously cloned L. stagnalis genes, we were able to match ~ 87% of them in our transcriptome assembly, indicating a high percentage of gene coverage. The expressional differences for innexins, FMRFamide, and molluscan insulin peptide genes were validated by real-time qPCR. Lastly, our transcriptomic analyses revealed distinct, age-specific gene clusters, differentially expressed genes, and enriched pathways in young, adult, and old CNS. More specifically, our data show significant changes in expression of critical genes involved in transcription factors, metabolisms (e.g. cytochrome P450), extracellular matrix constituent, and signaling receptor and transduction (e.g. receptors for acetylcholine, N-Methyl-D-aspartic acid, and serotonin), as well as stress- and disease-related genes in young compared to either adult or old snails.

CONCLUSIONS

Together, these datasets are the largest and most updated L. stagnalis CNS transcriptomes, which will serve as a resource for future molecular studies and functional annotation of transcripts and genes in L. stagnalis.

The unlimited potential of the great pond snail, Lymnaea stagnalis

Only a limited number of animal species lend themselves to becoming model organisms in multiple biological disciplines: one of these is the great pond snail, Lymnaea stagnalis. Extensively used since the 1970s to study fundamental mechanisms in neurobiology, the value of this freshwater snail has been also recognised in fields as diverse as host-parasite interactions, ecotoxicology, evolution, genome editing and 'omics', and human disease modelling. While there is knowledge about the natural history of this species, what is currently lacking is an integration of findings from the laboratory and the field. With this in mind, this article aims to summarise the applicability of L. stagnalis and points out that this multipurpose model organism is an excellent, contemporary choice for addressing a large range of different biological questions, problems and phenomena.

Aging and disease-relevant gene products in the neuronal transcriptome of the great pond snail (Lymnaea stagnalis): a potential model of aging, age-related memory loss, and neurodegenerative diseases

Modelling of human aging, age-related memory loss, and neurodegenerative diseases has developed into a progressive area in invertebrate neuroscience. Gold standard molluscan neuroscience models such as the sea hare (Aplysia californica) and the great pond snail (Lymnaea stagnalis) have proven to be attractive alternatives for studying these processes. Until now, A. californica has been the workhorse due to the enormous set of publicly available transcriptome and genome data. However, with growing sequence data, L. stagnalis has started to catch up with A. californica in this respect. To contribute to this and inspire researchers to use molluscan species for modelling normal biological aging and/or neurodegenerative diseases, we sequenced the whole transcriptome of the central nervous system of L. stagnalis and screened for the evolutionary conserved homolog sequences involved in aging and neurodegenerative/other diseases. Several relevant molecules were identified, including for example gelsolin, presenilin, huntingtin, Parkinson disease protein 7/Protein deglycase DJ-1, and amyloid precursor protein, thus providing a stable genetic background for L. stagnalis in this field. Our study supports the notion that molluscan species are highly suitable for studying molecular, cellular, and circuit mechanisms of the mentioned neurophysiological and neuropathological processes.

Monoamines, Insulin and the Roles They Play in Associative Learning in Pond Snails

Molluscan gastropods have long been used for studying the cellular and molecular mechanisms underlying learning and memory. One such gastropod, the pond snail Lymnaea stagnalis, exhibits long-term memory (LTM) following both classical and operant conditioning. Using Lymnaea, we have successfully elucidated cellular mechanisms of learning and memory utilizing an aversive classical conditioning procedure, conditioned taste aversion (CTA). Here, we present the behavioral changes following CTA training and show that the memory score depends on the duration of food deprivation. Then, we describe the relationship between the memory scores and the monoamine contents of the central nervous system (CNS). A comparison of learning capability in two different strains of Lymnaea, as well as the filial 1 (F1) cross from the two strains, presents how the memory scores are correlated in these populations with monoamine contents. Overall, when the memory scores are better, the monoamine contents of the CNS are lower. We also found that as the insulin content of the CNS decreases so does the monoamine contents which are correlated with higher memory scores. The present review deepens the relationship between monoamine and insulin contents with the memory score.