Biology subjects

Sprecher, S.

Publications and source records attributed to Sprecher, S..

7 recordsLinked to original sources

bioRxiv2022

Genome assembly of the acoel flatworm Symsagittifera roscoffensis, a model for research on photosymbiosis

Symsagittifera roscoffensis is a well-known member of the order Acoela that lives in symbiosis with the algae Tetraselmis convolutae during its adult stage. Its natural habitat is the eastern coast of the Atlantic, where at specific locations thousands of individuals can be found lying in large pools on the surface of sand at low tide and in the sandy interstitial web at high tide. As a member of the Acoela it has been used as a proxy for early bilaterian animals; however, its phylogenetic position remains debated. In order to understand the basic structural characteristics of the acoel genome, we sequenced and assembled the genome of aposymbiotic S. roscoffensis. The size of S. roscoffensis genome was measured to be in range 910 - 940 Mb. Sequencing of the genome was performed using PacBio Hi-Fi technology. Hi-C and RNA-seq data were also generated to scaffold and annotate the genome. The resulting assembly is 1.1 Gb large (covering 118% of the estimated genome size) and highly continuous, with N50 scaffold size of 1.04 Mb. The repetitive fraction of the genome is 61%, of which 85% (half of the genome) are LTR retrotransposons. Genome-guided transcriptome assembly identified 34,493 genes, of which 29,351 are protein coding (BUSCO score 97.6%), and 30.2% of genes are spliced leader (SL) trans-spliced. The completeness of this genome suggests that it can be used extensively to characterize gene families and conduct accurate phylogenomic reconstructions. SignificanceSymsagittifera is a representative of the phylum Acoela, the first offshoot of bilaterian animals. This key phylogenetic position adds an extra value to the knowledge of its genome, since it will inform us on how the genome of a bilaterian ancestor might have looked like. Moreover, Symsagittifera roscoffensis is a model organism used in symbiogenesis research. Host and algae can be cultured independently and, after mixing, the symbiosis can be followed. Symbiogenesis was established early on during the evolution of Metazoa. In spite of its biological relevance, very little is known on the molecular mechanisms that control it. Here the genome of the acoel host should provide us with insights on the first adaptations to symbiogenesis occurring in bilateral animals.

genomics↗

bioRxiv2022

Neuromodulation by Monoamines is a Bilaterian Innovation

Monoamines like serotonin, dopamine, and adrenaline/noradrenaline (epinephrine/ norepinephrine) act as neuromodulators that tune the response of the nervous system to the environment with predictable advantages for fitness. For instance, monoamines influence action selection depending on the internal state of the organism, contribute to higher cognitive functions like learning and memory formation and modulate fundamental homeostatic needs such as sleep or feeding. Despite their significance and the extensive research in model organisms, the evolutionary origin of the monoaminergic system is uncertain. Here using a phylogenomic approach we study the evolution of the majority of genes involved in the production, modulation, and detection of monoamines. Our analyses suggest that most of the genes of the monoaminergic system originated in the common ancestor of bilaterians. These findings suggest that the monoaminergic synaptic pathway is a bilaterian innovation. We hypothesise that monoaminergic neuromodulation contributed to the diversification and complexification of behaviour and forms found in Bilateria.

evolutionary biology↗

bioRxiv2019

Predictive olfactory learning in Drosophila

Olfactory learning and conditioning in the fruit fly is typically modelled by correlation-based associative synaptic plasticity. It was shown that the conditioning of an odor-evoked response by a shock depends on the connections from Kenyon cells (KC) to mushroom body output neurons (MBONs). Although on the behavioral level conditioning is recognized to be predictive, it remains unclear how MBONs form predictions of aversive or appetitive values (valences) of odors on the circuit level. We present behavioral experiments that are not well explained by associative plasticity between conditioned and unconditioned stimuli, and we suggest two alternative models for how predictions can be formed. In error-driven predictive plasticity, dopaminergic neurons (DANs) represent the error between the predictive odor value and the shock strength. In target-driven predictive plasticity, the DANs represent the target for the predictive MBON activity. Predictive plasticity in KC-to-MBON synapses can also explain trace-conditioning, the valence-dependent sign switch in plasticity, and the observed novelty-familiarity representation. The model offers a framework to dissect MBON circuits and interpret DAN activity during olfactory learning.

neuroscience↗

bioRxiv2019

Multilevel regulation of the glass locus during Drosophila eye development

Development of eye tissue is initiated by a conserved set of transcripton factors termed retinal determination network (RDN). In the fruit fly Drosophila melanogaster, the zinc-finger transcription factor Glass acts directly downstream of the RDN to control idendity of photoreceptor as well as non-photoreceptors cells. Tight control of spatial and temporal gene expression is a critical feature during development, cell-fate determination as well as maintainance of differentiated tissues. The molecular mechanisms that control expression of glass, however remain largely unknown. We here identify complex regulatory mechanisms controlling expression of the glass locus. All information to recapitulate glass expression are contained in a compact 5.2 kb cis-acting genomic element by combining different cell-type specific and general enhancers with repressor elements. Moreover, the immature RNA of the locus contains an alterantive small open reading frame (smORF) upstream of the actual glass translation start, resulting in a small peptide instead of the three possible glass protein isoforms. CRISPR/Cas9-based mutagenesis shows that the smORF is not required for the formation of functioning photoreceptors, but to attenuate effects of glass misexpression. Furthermore, editing the genome to generate glass loci eliminating either one or two isoforms shows that only one of the three proteins is critical for formation of functioning photoreceptors, while removing the two other isoforms did not cause defects in developmental or photoreceptor function. Our results show that eye development and function is surprisingly robust and appears buffered to targeted manipulations of critical features of the glass transcript, suggesting a strong selection pressure to allow the formation of a functioning eye.

developmental biology↗

bioRxiv2018

Mathematical modeling of navigational decisions based on intensity versus directionality in Drosophila larval phototaxis

Organisms use environmental cues for directed navigation. Depending on the sensory modality and complexity of the involved sensory organs, different types of information may be processed. Understanding the basic logic behind navigational decisions critically depends on the complexity of the nervous system. Due to the comparably simple organization of the nervous system of the fruit fly larva, it stands as a powerful model to study decision-making processes that underlie directed navigation. Here, we formulate a stochastic method based on biased Markov chains to model the behavioral basis of negative phototaxis. We have quantitatively measured phototaxis in response to defined sensory inputs. We find that larvae make navigational decisions by taking into account both light intensities and its spatial gradients, and our model allows us to quantify how larvae minimize their exposure to light intensity and at the same time maximize their distance to the source of light. The response to the light field is a non-linear response and saturates above an intensity threshold. Our mathematical model simulates and predicts larval behavioral dynamics only using light intensity and directionality as input parameters. Moreover, it allows us to evaluate the relative importance of these two factors governing visual navigation. The model has been validated with experimental biological data yielding insight into the strategy that larvae use to achieve their goal with respect to the navigational cue of light, paving the way for future work to study the role of the different neuronal components in this mechanism.\n\nAuthor SummaryNavigational decision-making is a complex process during which the nervous system is able to decipher external input through molecular and cellular mechanisms to produce a spatially-coordinated behavioral output. Drosophila larvae provide an excellent model to understand these decision-making mechanisms as we can measure the behavioral output (larval navigation) in response to quantifiable external input (different light conditions). We have performed experiments to quantify larval light avoidance in order to subsequently design a mathematical model that quantitatively reproduces larval behavior. Our results allow us to characterize the relative importance of light intensity and directionality and yield insight into the neural algorithms used in the decision-making mechanism of larval phototaxis.

neuroscience↗

bioRxiv2017

Mushroom body-specific profiling of gene expression identifies regulators of long-term memory in Drosophila

Memory formation is achieved by genetically tightly controlled molecular pathways that result in a change of synaptic strength and synapse organization. While for short-term memory traces rapidly acting biochemical pathways are in place, the formation of long-lasting memories requires changes in the transcriptional program of a cell. Although many genes involved in learning and memory formation have been identified, little is known about the genetic mechanisms required for changing the transcriptional program during different phases of long-term memory formation. With Drosophila melanogaster as a model system we profiled transcriptomic changes in the mushroom body, a memory center in the fly brain, at distinct time intervals during long-term memory formation using the targeted DamID technique. We describe the gene expression profiles during these phases and tested 33 selected candidate genes for deficits in long-term memory formation using RNAi knockdown. We identified 10 genes that enhance or decrease memory when knocked-down in the mushroom body. For vajk-1 and hacd1, the two strongest hits, we gained further support for their crucial role in learning and forgetting. These findings show that profiling gene expression changes in specific cell-types harboring memory traces provides a powerful entry point to identify new genes involved in learning and memory. The presented transcriptomic data may further be used as resource to study genes acting at different memory phases.

neuroscience↗

bioRxiv2017

Organization Of The Drosophila Larval Visual Circuit

Visual systems transduce, process and transmit light-dependent environmental cues. Computation of visual features depends on the types of photoreceptor neurons (PR) present, the organization of the eye and the wiring of the underlying neural circuit. Here, we describe the circuit architecture of the visual system of Drosophila larvae by mapping the synaptic wiring diagram and neurotransmitters. By contacting different targets, the two larval PR-subtypes create parallel circuits potentially underlying the computation of absolute light intensity and temporal light changes already within this first visual processing center. Locally processed visual information then signals via dedicated projection interneurons to higher brain areas including the lateral horn and mushroom body. The stratified structure of the LON suggests common organizational principles with the adult fly and vertebrate visual systems. The complete synaptic wiring diagram of the LON paves the way to understanding how circuits with reduced numerical complexity control wide ranges of behaviors.

neuroscience↗