Enhanced mating efficiency at 28 °C is an intriguing observation; however, the current experimental design doesn’t distinguish between two plausible explanations: (1) increased secretion of gametolysins, MMPs, and related factors at 28 °C directly enhances mating competence, or (2) broader physiological changes associated with acclimation to 28 °C (e.g., altered membrane properties, flagellar remodeling) are the primary drivers, with changes in the secretome being correlative rather than causal.

To disentangle these possibilities, have you considered a reciprocal autolysin transfer experiment, similar to the approach described in the Bio-protocol publication by Findinier 2023 (DOI:10.21769/BioProtoc.4705)? In this design, autolysin preparations from cells grown at 18 °C and 28 °C would be cross-applied to gametes conditioned at each temperature, generating four conditions: (i) 18 °C autolysin + 18 °C gametes; (ii) 28 °C autolysin + 28 °C gametes; (iii) 18 °C autolysin + 28 °C gametes; and (iv) 28 °C autolysin + 18 °C gametes.

If the secreted proteome is the primary determinant of enhanced mating efficiency, then 28 °C-derived autolysin should increase mating efficiency regardless of the temperature at which the recipient gametes were produced. In contrast, if physiological acclimation is dominant, mating efficiency should track with the growth temperature of the gametes rather than the source of the autolysin. This framework would also allow assessment of potential synergy between these factors, with the strongest increase in mating efficiency observed in the matched 28 °C condition relative to either of the reciprocal treatments.

I see the appeal of identifying evolutionarily agnostic regulatory activity and appreciate the effort to tackle this goal. I was hoping you could speak toward the magnitude of the effects observed in the initial screens.

In the plant and human screens, the largest log fold changes reported appear relatively modest. Do you think this reflects limitations of the screening platforms themselves, the size or composition of the candidate CR library (e.g., that stronger regulators may not have been captured), or might it suggest that CRs lose some regulatory potency when moved outside of their native evolutionary or chromatin context?

The seed-coat is T0 maternal tissue, so how would this be helpful to determine segregation of the transgene in the T1 seeds?

Earlier in the paragraph you suggest that T-DNA molecules are undergoing concatemerization prior to chromosomal integration, rather than multiple independent partial T-DNA insertions. However, if this was the case, then the mutlple transgene copies would be linked and segregation would occur as if there was a single insertion event.

Based on your segregation data, is it possible to determine if the RUBY observed in the seeds is being expressed in the T1 seeds, or if it is being expressed in T0 maternal floral tissue and being transferred/leaked into the seed?

Since editing continues through T0 generation development, which developmental stage did you use for checking T0 CRISPR editing efficiency? How soon is too soon, and is there a recommended tissue and/or developmental time point to perform the T0 screening?

It's exciting to see that Cas9 can be linked to RUBY using P2A, and I can see multiple benefits. Not just for selection, but it also helps reduce the size of the binary vector for plant transformation. With that in mind, since ZmUbi1 promoter is used for GIF1 and Cas9-RUBY, is there a reason for the current design over ZmUbi1::GRF-GIF1-P2A-CAS9-P2A-RUBY?

I’m excited to see the development of a commercial V. natriegens for the community to try out. I had a few questions arise when reading your paper.

First, in the introduction section you mention “This can be scaled from small culture tubes in the laboratory (to generate microgram quantities of DNA), to large-scale industrial bioreactors (to generate kilograms of DNA for vaccine production).” I am wondering where you envision the biggest benefit occurring? Would it be mostly for commercial DNA manufacturing? For general cloning in a research lab, I’m not sure how much I’ve ever worried about E.coli’s slower doubling time for my typical cloning workflow, since I often start cultures in the evening and let them grow overnight. With this system, I’m envisioning you would more likely to be starting cultures in the morning and harvesting in the afternoon. It would be nice to see a figure demonstrating what some hypothetical cloning workflows (with timelines) would look like to have a better understanding of how much time could be saved.

Second, I am wondering if you tested transformation of any larger plasmids. Most plasmids you tested ranged from ~3kb to 6kb. However, some of the larger plasmids seem like they may have a growth penalty (Figure 6) and a decrease in transformation efficiency (Fig 9). Would these possible phenotypes be more pronounced if you are transforming a plasmid that is 20-25kb, which is about the max that E.coli can support?