Biology subjects

Kemenes, I.

Publications and source records attributed to Kemenes, I..

3 recordsLinked to original sources

bioRxiv2021

Histone acetyltransferase activity of CREB-binding protein is essential for synaptic plasticity in Lymnaea

In eukaryotes, CREB-binding protein (CBP), a coactivator of CREB, functions both as a platform for recruiting other components of the transcriptional machinery and as a histone acetyltransferase (HAT) that alters chromatin structure. We previously showed that the transcriptional activity of cAMP-responsive element binding protein (CREB) plays a crucial role in neuronal plasticity in the pond snail Lymnaea stagnalis. However, there is no information on the role CBP plays in CREB-initiated plastic changes in Lymnaea. In this study, we characterized the Lymnaea CBP (LymCBP) gene and investigated the roles it plays in synaptic plasticity involved in regulating feeding behaviors. Similar to CBPs of other species, LymCBP possesses functional domains, such as KIX domain, which is essential for interaction with CREB and was shown to regulate long-term memory (LTM). In situ hybridization showed that the staining patterns of LymCBP mRNA in the central nervous system were very similar to those of Lymnaea CREB1 (LymCREB1). A particularly strong LymCBP mRNA signal was observed in the Cerebral Giant Cell (CGC), an identified extrinsic modulatory interneuron of the feeding circuit, key to both appetitive and aversive LTM for taste. Biochemical experiments using the recombinant protein of LymCBP HAT domain showed that its enzymatic activity was blocked by classical HAT inhibitors such as curcumin, anacardic acid and garcinol. Preincubation of Lymnaea CNSs with these HAT inhibitors blocked cAMP-induced long-term potentiation between the CGC and the follower B1 motoneuron. We therefore suggest that HAT activity of LymCBP in the CGCs is a key factor in synaptic plasticity contributing to LTM after classical conditioning.

neuroscience↗

bioRxiv2021

A proteomics database for CNS proteins of the great pond snail Lymnaea stagnalis

Applications of key technologies in biomedical research, such as qRT-PCR or LC-MS based proteomics, are generating large biological (-omics) data sets which are useful for the identification and quantification of biomarkers involved in molecular mechanisms of any research area of interest. Genome, transcriptome and proteome databases are already available for a number of model organisms including vertebrates and invertebrates. However, there is insufficient information available for protein sequences of certain invertebrates, such as the great pond snail Lymnaea stagnalis, a model organism that has been used highly successfully in elucidating evolutionarily conserved mechanisms of learning and memory, ageing and age-related as well as amyloid-{beta} induced memory decline. In this investigation, we used a bioinformatics approach to designing and benchmarking a comprehensive CNS proteomics database (LymCNS-PDB) for the identification of proteins from the Central Nervous System (CNS) of Lymnaea stagnalis by LC-MS based proteomics. LymCNS-PDB was created by using the Trinity TransDecoder bioinformatics tool to translate amino acid sequences from mRNA transcript assemblies obtained from an existing published Lymnaea stagnalis transcriptomics database. The blast-style MMSeq2 software was used to match all translated sequences to sequences for molluscan proteins (including Lymnaea stagnalis and other molluscs) available from UniProtKB. LymCNS-PDB, which contains 9,628 identified matched proteins, was then benchmarked by performing LC-MS based proteomics analysis with proteins isolated from the CNS of Lymnaea stagnalis. MS/MS analysis using the LymCNS-PDB database led to the identification of 3,810 proteins while only 982 proteins were identified by using a non-specific Molluscan database. LymCNS-PDB provides a valuable tool that will enable us to perform quantitative proteomics analysis to identify a plethora of protein interactomes involved in several CNS functions in Lymnaea stagnalis including learning and memory, aging-related memory decline and others.

bioinformatics↗

bioRxiv2020

Interneuronal mechanisms underlying a learning-induced switch in a sensory response that anticipates changes in behavioural outcomes

How an animal responds to a particular sensory stimulus will to a great extent depend on prior experience associated with that stimulus. For instance, aversive associative learning may lead to a change in the predicted outcomes, which suppresses the behavioural response to an otherwise rewarding stimulus. However, the neuronal mechanisms of how aversive learning can result in the suppression of even a vitally important innate behaviour is not well understood. Here we used the model system of Lymnaea stagnalis to address the question of how an anticipated aversive outcome can alter the behavioural response to a previously effective feeding stimulus. We found that aversive classical conditioning with sucrose as the CS (conditioned stimulus) and strong touch as the aversive US (unconditioned stimulus) reverses the decision so that the same salient feeding stimulus inhibits feeding, rather than activating it. Key to the understanding of the neural mechanism underlying this switch in the behavioural response is the PlB (pleural buccal) extrinsic interneuron of the feeding network whose modulatory effects on the feeding circuit inhibit feeding. After associative aversive training, PlB is excited by sucrose to reverse its effects on the feeding response. Aversive associative learning induces a persistent change in the electrical properties of PlB that is both sufficient and necessary for the switch in the behavioural output. In addition, the strong touch used as the US during the associative training protocol can also serve as a sensitizing stimulus to lead to an enhanced defensive withdrawal response to a mild touch stimulus. This non-associative effect of the strong touch is probably based on the facilitated excitatory output of a key identified interneuron of the defensive withdrawal network, PeD12.

neuroscience↗