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  1. Evaluation Summary:

    Berryer et al. report on an automated and quantitative platform to study the number of synaptic inputs formed in networks of human excitatory neurons and astrocytes in vitro. The authors tested the utility of the platform by screening a large collection of small molecules and identified several modulators of synapse density, which were validated in follow-up experiments. The automated platform substantially extends what is currently available, particularly with respect to the automation of the initial analysis steps. The positive hits identified here, the inhibitors of bromodomain and extraterminal (BET) family of gene expression regulators, are important, and will likely contribute to the understanding of the mechanisms of human synapse assembly.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 and Reviewer #3 agreed to share their name with the authors.)

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  2. Reviewer #1 (Public Review):

    A high-throughput synaptic phenotyping platform targeting human synapses is highly valuable. The validity of the present system is supported by a small molecule inhibitor screen that has identified targets, including the BET family proteins, whose role in brain function has been previously demonstrated. The authors have gone one step further to analyze the gene expression programs impacted by the BET Inhibitors, and the observations that synaptic genes encoding proteins such as neurexin-3 and homer 1 are altered is reassuring. In addition, demonstrating that the presence of astrocytes crucially impacts the density of presynaptic marker protein is of relevance for the design of similar platforms. The general utility of the present platform in identifying synaptic changes, however, needs to be further substantiated by additional synaptic markers.

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  3. Reviewer #2 (Public Review):

    In this manuscript, Berryer et al describe a fully automated, scalable approach to quantify the number of synaptic inputs formed onto human iPSC-derived neurons (hNs) in 2D culture. They validate the sensitivity of their approach by synapsin1 knock-down and test almost 400 small molecules for their effect on synapses, and the role of astrocytes. They identify BET inhibitors as strong modifiers of synapse numbers in hNs and performed follow-up experiments to confirm the finding, characterize the effect further and demonstrate the critical role of astrocytes.

    Every step of the protocol is automated to achieve high reproducibility and homogeneity throughout the experiments. This automated approach has great potential for scaling up drug screening, genetic perturbations, and disease modeling experiments related to synapses.

    The authors successfully identified, in two independent hNs lines, three small-molecule inhibitors of transcription modifiers of the BET family as the strongest positive modifiers of synaptic inputs. The initial study performed with immunofluorescence was then validated by Western blot analysis and mRNA-seq analysis, which showed an increase in the expression of trans-synaptic signaling genes.
    While accessing the molecular mechanisms of BET inhibitors, the authors observed that the increased synaptic inputs occurred only in cocultures of astrocytes and neurons, and not in hNs monoculture. Finally, the authors report that the presence of astrocytes alone is a major driving force to promote synaptic inputs.

    Overall, the experiments are well conducted, and the conclusions are supported by the data. The new approach reaches beyond the current state of the field, especially in the first steps of automation and the identified modulators (BET inhibitors) are interesting and novel, and the subsequent validation is convincing.

    On the other hand, the manuscript does not yet define the exact resolution and power of the new methods, and does not convincingly show that the observed synapsin-puncta are synapses and that the data of the validation experiments can be improved.

    Major points:

    1. Although the manuscript contains a lot of quantitative data on variance, the current manuscript stops short of an exact definition of the resolution of the assay and its statistical power. With the real (measured) variance of the assay, the power to detect certain effects can be computed. To be relevant for other applications than the current (e.g. genetic perturbations and disease modelling), it is relevant to define this for smaller effects too: can this assay detect a 25% effect with reasonable numbers of observations? Such assessments can also provide important recommendations on when it makes sense to add more repeated measures of the same specimens (wells, ROIs) and when more independent inductions are required (and how much this adds to overall power). The manuscript would also benefit from a short discussion on how to optimize future study designs (repeated measures, independent inductions, number of subjects).

    2. It is widely recognized that synapses formed in networks of NGN2-induced excitatory neurons only, may not model synapses in the real human brain very well (yet), especially not at DIV21. First, the authors can be more open/precise about this, e.g., in line 156 the authors indicate they use hNs at DIV21 because they are "electrophysiologically active" based on three references. However, (a) these references indicate that hNs cultures start to mature from DIV21 onwards but are not really mature yet, and (b) being "electrophysiologically active" seems not the most relevant criterion. Synaptic parameters like initial release probability, rise/decay time, and synchronicity are more relevant (none of which indicate synapses are mature at DIV21). Second, especially in the light of the claims the authors make regarding the effects of compounds on "synaptic connectivity" it seems essential to test, at least in a set of validation experiments, the distribution of postsynaptic markers. Synapsin-positive puncta may not be accompanied by a postsynaptic specialization and rather represent (mobile) vesicle clusters and/or release sites without postsynaptic partners. In addition, the authors claim synapsin1 is a pan-neuronal synapse marker. This is not yet validated for human neurons. A few control stainings with synaptic vesicle and active zone markers will secure this claim.

    3. The analysis of the transcriptional effects of BET inhibitors is rather basic, especially given the rather strong claim: "BET inhibitors enhance synaptic gene expression programs". Which programs? Differentially expressed transcripts can at least be analysed further in terms of subcellular localization (pre/post) or synaptic functions, e.g. using SYNGO, also to address point 2 above.

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  4. Reviewer #3 (Public Review):

    In this paper Berryer et al. developed an efficient automated and quantitative high-content synaptic phenotyping platform to be used for human neurons and astrocytes derived from iPSCs. With this quantitative platform, the authors screened the effects of 376 small molecules on presynaptic density, neurite outgrowth, and cell viability. Interestingly six small molecules were identified that specifically enhanced human presynaptic density in vitro and the presence of astrocytes in culture was essential for mediating the effects of the six molecules. Among these molecules, the bromodomain and extraterminal (BET) inhibitors were the most effective in increasing the presynaptic clusters and in upregulating synaptic gene expression programs. Thus this paper provides strong evidence for the possibility to use a reproducible and automated screening platform for the identification of synaptic modulators in human neurons.

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