foxQ2 marks fast-acting brain interneurons including a subset of dopaminergic neurons innervating mushroom bodies and central complex in the beetle Tribolium castaneum
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eLife Assessment
This valuable descriptive study describes the expression of a developmentally relevant transcription factor in the adult Tribolium brain. The evidence supporting the claims is convincing and based on a very detailed and rigorous analysis of light microscopy data, which, however, lacks single-cell resolution. This neuroanatomical study is of interest to the field of insect neural development and neuroscience.
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Abstract
The brain is one of the most complex animal organs but the development of the many different neuron types remains enigmatic. A set of brain-specific transcription factors is known to be involved in brain patterning but their specific contributions remain to be elucidated in most cases, including foxQ2II. This transcription factor is known to be conserved in anterior neuroectodermal patterning of most animals while it has been lost from vertebrates. However, the contribution of foxQ2II-positive neurons to the adult brain has remained enigmatic. Here, we use an enhancer trap, immunostainings and our newly established beetle brainbow system to categorize Tc-foxQ2II-positive neurons into nine clusters with different projection patterns. All clusters contain neurons with the fast activating neurotransmitters acetylcholine and glutamate while no Tc-foxQ2II positive neuron is GABA-ergic or serotonin-positive. Interestingly, we found that many dopaminergic neurons were Tc-foxQ2II positive and we homologize them with dopaminergic neurons of the PPL2c, PPM1 and PPL1 cluster described in the Drosophila brain. Our results show that Tc-foxQ2II marks subsets of fast-acting interneurons contributing to the higher order brain centers mushroom bodies and central complex. Taken together, our work expands the known functional range of foxQ2 genes from sensory and neurosecretory cell specification to interneurons involved in the function of higher order brain centers.
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eLife Assessment
This valuable descriptive study describes the expression of a developmentally relevant transcription factor in the adult Tribolium brain. The evidence supporting the claims is convincing and based on a very detailed and rigorous analysis of light microscopy data, which, however, lacks single-cell resolution. This neuroanatomical study is of interest to the field of insect neural development and neuroscience.
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Reviewer #1 (Public review):
Summary:
Pang et al. investigated the expression pattern of the transcription factor foxQ2II in an adult beetle brain. They find nine distinct clusters, with many neurons expressing Glut/ChaT and dopamine. Some of the dopamine neurons resemble cell types described in Drosophila. Several neurons seem to project to prominent higher brain regions such as the MB and CX, and might even connect to both.
Strengths:
The authors use state-of-the-art labeling techniques for the analysis of individual cell types, such as beetle brainbow, to investigate the until now unknown expression of the transcription factor in the adult beetle brain.
Rigorous cell reconstruction and image analysis revealed a better understanding of the anatomy of the labeled cells.
Weaknesses:
The brainbow labeling seems to include all cells …
Reviewer #1 (Public review):
Summary:
Pang et al. investigated the expression pattern of the transcription factor foxQ2II in an adult beetle brain. They find nine distinct clusters, with many neurons expressing Glut/ChaT and dopamine. Some of the dopamine neurons resemble cell types described in Drosophila. Several neurons seem to project to prominent higher brain regions such as the MB and CX, and might even connect to both.
Strengths:
The authors use state-of-the-art labeling techniques for the analysis of individual cell types, such as beetle brainbow, to investigate the until now unknown expression of the transcription factor in the adult beetle brain.
Rigorous cell reconstruction and image analysis revealed a better understanding of the anatomy of the labeled cells.
Weaknesses:
The brainbow labeling seems to include all cells labeled by the enhancer trap line, as well as the ones not expressing foxQ2II. Thus, it is unclear how useful this data is to compare individual cells to other insects.
The functional relevance of this transcription factor in the adult brain cell is still unknown. It is therefore unclear if the described neurons have any specific function and if they require this transcription factor for normal function.
Overall, the neural reconstructions are missing single-neuron details; it is difficult to compare the shown cell types to specific cell types in Drosophila based on the presented data, and this finding remains speculative.
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Reviewer #2 (Public review):
Summary:
The authors provide the first thorough profiling of neurons in Tribolium characterized by the expression of the transcription factor foxQ2, which will be useful for developmental neurobiology. They use state-of-the-art methods convincingly to not only identify the neurons, but also to further characterize them anatomically and neurochemically.
Strengths:
Thorough and meticulous application of state-of-the-art anatomical methods in a non-standard laboratory organism.
Weaknesses:
No weaknesses were identified by this reviewer.
Comments:
I don't really have any major suggestions at all. Loved the work.
There is only one tiny nitpicking aspect:
P21: "Biogenic amines are involved in learning and memory and setting arousal threshholds (Davis, 2023), which are functions performed by the mushroom bodies and …
Reviewer #2 (Public review):
Summary:
The authors provide the first thorough profiling of neurons in Tribolium characterized by the expression of the transcription factor foxQ2, which will be useful for developmental neurobiology. They use state-of-the-art methods convincingly to not only identify the neurons, but also to further characterize them anatomically and neurochemically.
Strengths:
Thorough and meticulous application of state-of-the-art anatomical methods in a non-standard laboratory organism.
Weaknesses:
No weaknesses were identified by this reviewer.
Comments:
I don't really have any major suggestions at all. Loved the work.
There is only one tiny nitpicking aspect:
P21: "Biogenic amines are involved in learning and memory and setting arousal threshholds (Davis, 2023), which are functions performed by the mushroom bodies and related to the function of the central complex in goal directed navigation, respectively."
MBs mainly process olfactory memory. At least in Drosophila, most other kinds of memories are being supported elsewhere.
https://pubmed.ncbi.nlm.nih.gov/10454381/
such as, e.g., visual pattern learning in the CX
https://pubmed.ncbi.nlm.nih.gov/16452971/
or motor learning in motor neurons
https://pubmed.ncbi.nlm.nih.gov/38779314/
or ventral ganglion, antennal lobes, and median bundle for place learning:
https://pubmed.ncbi.nlm.nih.gov/10706599/
If the authors focus on MBs, this sentence ought to reflect the fact that the function of the MBs is much narrower than the current sentence appears to suggest.
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Author response:
We thank the editors and reviewers for their thoughtful and constructive assessment of Toothy, and for recognizing it as a potentially valuable resource for standardizing dentate spike (DS) analysis across labs. We are especially glad that the reviewers found the manuscript clear and easy to follow, judged the detection and classification algorithms to be appropriate and well-validated, and appreciated the tool's graphical user interface (GUI) based, pip-installable design for lowering the barrier to entry for DS analysis.
We also understand the concerns raised. Most importantly, we will resolve the data-ingestion and classification errors that reviewers encountered and release an updated version of Toothy that we have verified end-to-end across input formats and datasets. Alongside this, we will provide downloadable …
Author response:
We thank the editors and reviewers for their thoughtful and constructive assessment of Toothy, and for recognizing it as a potentially valuable resource for standardizing dentate spike (DS) analysis across labs. We are especially glad that the reviewers found the manuscript clear and easy to follow, judged the detection and classification algorithms to be appropriate and well-validated, and appreciated the tool's graphical user interface (GUI) based, pip-installable design for lowering the barrier to entry for DS analysis.
We also understand the concerns raised. Most importantly, we will resolve the data-ingestion and classification errors that reviewers encountered and release an updated version of Toothy that we have verified end-to-end across input formats and datasets. Alongside this, we will provide downloadable demo dataset(s) spanning multiple file formats, probe types, and recording conditions, so that users can confirm a correct installation and see how these cases differ.
To make the pipeline more transparent, we will add a section describing what Toothy does between user steps, including the rationale for decisions users cannot change, such as detection from a single representative channel. We will also expand the documentation of parameter choices with supporting citations and alternatives, and surface this guidance within Toothy where feasible, consistent with our aim that the tool not function as a black box.
We will clarify Toothy's scope and current limitations. Recordings with irregular spatial sampling (e.g., tetrodes) are supported for detection but not for CSD-based DS-type classification, which requires a laminar probe spanning approximately the hippocampal fissure to the hilus; we will state this explicitly and evaluate adding an optional waveform-based classification mode (Santiago et al., 2024) to extend type classification to such recordings. We will also add data-quality checks (including sampling rate and inter-electrode spacing) that warn users when a recording may not support reliable results.
Finally, we will situate Toothy among existing open-source toolboxes, describing how it differs, extends beyond, and interoperates with them, and we will add a comparison of Toothy's outputs to previously published analyses while being explicit about the limits of such comparisons. We will of course also address the remaining technical clarifications and figure edits raised by the reviewers.
We are confident that addressing these points will make Toothy clearer and more useful to the hippocampal community.
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