Intermediate gray matter interneurons in the lumbar spinal cord play a critical and necessary role in coordinated locomotion

  1. Naëmi Kuehn
  2. Andreas Schwarz
  3. Carlo Antonio Beretta
  4. Yvonne Schwarte
  5. Francesca Schmitt
  6. Melanie Motsch
  7. Norbert Weidner
  8. Radhika Puttagunta

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Abstract

Locomotion is a complex task involving excitatory and inhibitory circuitry in spinal gray matter. While genetic knockouts examine the function of individual spinal interneuron (SpIN) subtypes, the phenotype of combined SpIN loss remains to be explored. We modified a kainic acid lesion to damage intermediate gray matter (laminae V-VIII) in the lumbar spinal enlargement (spinal L2-L4) in female rats. A thorough, tailored behavioral evaluation revealed deficits in gross hindlimb function, skilled walking, coordination, balance and gait two weeks post-injury. Using a Random Forest algorithm, we combined these behavioral assessments into a highly predictive binary classification system that strongly correlated with structural deficits in the rostro-caudal axis. Machine-learning quantification confirmed interneuronal damage to laminae V-VIII in spinal L2-L4 correlates with hindlimb dysfunction. White matter alterations and lower motoneuron loss were not observed with this KA lesion. Animals did not regain lost sensorimotor function three months after injury, indicating that natural recovery mechanisms of the spinal cord cannot compensate for loss of laminae V-VIII neurons. As gray matter damage accounts for neurological/walking dysfunction in instances of spinal cord injury affecting the cervical or lumbar enlargement, this research lays the groundwork for new neuroregenerative therapies to replace these lost neuronal pools vital to sensorimotor function.

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  1. Version published to 10.1371/journal.pone.0291740
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    Reply to the reviewers

    The work presented here examined the combined contribution of intermediate gray matter spinal interneurons of the spinal lumbar enlargement (L2-L4) to locomotion in rats. By targeting this region with kainic acid, we were able to produce a specific locomotor signature that was not compensated for over time, indicating the need for cellular replacement therapies in the treatment of such spinal cord injuries leading to the loss of spinal enlargement intermediate gray matter. Further, the newly developed techniques of a combinatorial behavioral assessment using Random Forest classification and a machine learning intermediate gray matter neuronal loss assessment established in this work add an unbiased, in-depth approach that we are making available to others.

    The reviewers have critically evaluated our work and highlighted points of weakness either in the research itself or in connecting with our audience. Below is our detailed response to all the comments as well as our revision plan for submission. We believe we have been able to sufficiently address the concerns that were voiced to strengthen our manuscript and express our gratitude for the feedback.

    Reviewer #1 (Evidence, reproducibility and clarity (Required)): __ In this paper, Kuehn and colleagues report on the analysis of functional impairments following intermediate gray matter lesion with kainic acid. The image convincingly show that mostly purely grey matter lesion can be achieved throughout the paper. The authors took care to do a battery of well-designed behavioral tests and sophisticated analysis in order to access functional impairment. They then correlate their behavioral assessment to lesion size, the number of NeuN positive cells in layers V-VII epicenters as well motoneuron numbers and the percentage of white matter. Overall, the manuscript is well written, nicely framed in the existing literature, very clear and the experiments are simple but well designed. The behavioral testing and evaluations including random forest ranking are well performed. The methodology is complete and would allow reproducing the experiments. Statistics are used appropriately. We have however some reserves and comments on some of the results and interpretations. Addressing these comments would not involve new experiments but new re-analysis of the existing datasets.

    Major comments:__

    __ While the claims that grey matter lesions trigger major behavioral impairments is convincing in particular with the refine behavioral experiments performed, the key claim that only interneuron loss in layer V-VII mediates those deficits is currently not supported by the presented data. In particular, we would suggest that the lesions performed, in contrast to the claims, are not purely and selectively impacting layer V-VII but might also impact layers VIII-IX. We think that presenting neuronal counts based on NeuN staining separately for layer I-IV, V-VII, VIII-IX and comparing control vs KA is necessary. Only with these data can conclusions be supported either in the direction suggested by the authors or otherwise.__

    • Although primarily targeting laminae V-VII, we realize this is not exclusively doing so with our lesion model. We understand the value of what you request and are retraining our computer models to be able to do the additional neuronal quantification in laminae I-IV, VIII, IX. We will then combine lamina VIII with laminae V-VII to make up the intermediate gray matter NeuN counts. Completion of all manually validated new analysis is ongoing and will be finished shortly. We plan on adding this additional analysis to the paper, which means much of Figure 6 and Supplementary Figure 3 will be altered and partially for Figure 7, but we won’t know exactly how until we finish the analysis. Tracked changes are shown in the updated manuscript PDF and highlighted text may change depending on results of this analysis.

    Another claim relative to the lack of involvement of motoneurons in the related behavioral deficits is also difficult to resolve with the current data. Motoneurons have been identified based on NeuN staining and size. While this is not the state of the art (ChAT staining would have been preferable), it remains acceptable. However, the data presented figures 7 and 8 show a very wide range in the motoneuron count (15 to 50) indicating either motoneuron loss or a count performed at different lumbar levels in the animals. This raises questions on the model (is it really involving only layers V-VII?) or on the interpretation of the data. Therefore we believe that motoneurons counts need to be presented separately (see above) in control vs KA groups and data need to be discussed in this perspective. Authors should also tone down the specificity of the model and involvement of motoneurons accordingly (page 20 for example).

    • Although we agree with the reviewers that ChAT staining would have been preferable, we had a limited amount of tissue available. Our unbiased, machine-learning-based analysis of neuronal loss by NeuN required much of the existing tissue. However, neuronal staining has been previously established to identify motoneurons based on size inclusion (Hadi et al., 2000; Wen et al., 2015), as we have used here. Additionally, we will be including total neuronal analysis from lamina IX as requested (please see answer to previous comment).

    • By including the Controls along with the KA rats, we postulate that the wide range of motoneuron numbers is due to natural individual variation as well as due to variation at each spinal level, and not due to the KA lesion, as the KA animals have a range of motoneuron counts, sometimes even greater than the controls (Figure 7 and 8). However, as requested, we have split L2, L3 and L4 (graphs below) and still do not see a correlation with behavioral performance (BBB and inclined beam). The variation due to spinal level may partially be explained by the fact that there are different numbers of motoneurons at each spinal level, dependent upon the number of muscles each spinal level is responsible for and the number of motor columns at a given level (Mohan et al., 2015; Nicolopoulos-Stournaras & Iles, 1983). These counts are taken from a given section and not the entirety of the spinal level, adding further possible variation. Moreover, we have removed the controls as suggested (graphed below) for motoneuron analysis and still do not see a correlation between the number of motoneurons and behavioral performance (BBB and inclined beam). We do not find this the correct way to graphically represent the data as it does not allow the reader to see the natural number of motoneurons that exist at each spinal level and variation within as well as knowing that this is not due to injury correlating with behavioral differences, and therefore we would like to keep these graphs with controls in the manuscript.

    We have toned down the specificity of the model and involvement of motoneurons as requested on pages 20-21.

    Most of the conclusions rely on correlations that include control animals (injected with saline hence with no lesions and no behavioral deficits; Fig 6 and 7). This artificially skews the correlations as those animals show no lesions and good performance in the behavioral tests. These correlations need to be performed only with KA injected animals to determine the respective involvements of interneurons and motoneurons.

    • To address your concern, we first did as you asked and removed the controls and performed the correlation analysis for Figure 6, shown below. There are no significant correlations between neurons at each spinal level and behavior. We would further argue that unlike a contusion injury where control animals only receive a laminectomy, our control animals have very minor neuronal loss due to the saline injection itself and therefore do have a minor lesion. An example of this is seen in Figure 6 for the control animal at spinal level L2 where the pipette track is visible. Therefore, to show that the observed behavioral deficits are from the kainic acid and not the injection itself, we would argue that it is important that the control animals remain in the correlation analysis.

    The long-term study (Fig 8) is performed with very few animals and hence, drawing conclusions from these animal numbers is difficult. All correlations are performed including control animals which is even more of a problem here as in Figure 6 and 7 due to the low number of animals. The authors should either add animals or remove the figure. When control animals (injected with saline) are removed (as they do not show any lesion and perform accurately in the behavior), one would actually see a correlation between the number of motoneurons and the behavioral performance (Fig. 8E,F) but not with the lesion size (Fig.8C,D).

    • The long-term study was planned with more animals, but due to exclusion criteria by lesion length, the numbers remain low. We had discussed extensively whether to include this data in the manuscript or not. We decided for several reasons to include it in the manuscript within the main figures. First, it demonstrates that once these interneurons are lost, there are no compensatory mechanisms that restore function, which is quite striking given that the ones that lose weight support by 2 weeks do not regain it over a 3-month observational period. Further indicating that loss of lumbar gray matter interneurons is essential to locomotor function of hindlimbs and should be targeted in SCI replacement therapeutics. However, we do not agree with removing controls to examine the motoneuron number as there is motoneuron number variation within the lesion area and the motoneuron number from the KA animals is within the Control motoneuron range, which can be seen with the graph including the Controls. We can provide the individual spinal lesion level correlations, but this does not provide the entire picture as one level alone has not been found to be essential to the behavioral deficits. We are currently processing these animals to also provide NeuN numbers from laminae I-IV, V-VIII and IX.

    Minor comments:

    __ Figure 1A: if lesions are bilateral, it would be nice to illustrate this on the schematic.__

    • This has been fixed. Figure 1B-D: scale bars are missing

    • This has been fixed. Figure 3H: What represents the y-axis? % of completion or number of completion?

    • This has been fixed. Figure 4 Table: Please specific what the acronym stands for: pLDA.

    • This has been clarified in the figure legend. Figure 6 A: scale bars are missing

    • This will be fixed when the data for the analysis is finished and the figure is redone. Figure 6B/C/D: please add the spinal level analyzed directly on the graphs. This will ease the comprehension.

    • This has been adjusted. Figure 7 and Figure 8: While it is quite convincing that the model is purely a grey matter injury (panel C and D), the data are very much spread out for the number of motoneurons per mice (see major comments above). We would suggest to plot those data to present the number of neurons (interneurons in layer I-IV, V-VII and motoneurons) control vs KA.

    • Thank you for the suggestion. We will plan on presenting the additional neuronal quantification data mentioned above by comparing Controls and KA animals.

    Dots are missing on those figures (probably superimposed on top of each other). This should be changed to see all data points

    • Thank you for the observation. They were superimposed but we have fixed this. Figure 8E,F: the number of motoneurons is very low also in controls. How is this explained?
    • Depending on where the section was taken at each spinal level, there is variation in the number of motoneuron columns innervating targeted muscles (Mohan et al., 2015), Figure 6). Therefore, it is not surprising to see a range of motoneurons. In addition, we would like to clarify that these motoneuron counts are taken from only three sections across the lesion (from the three lesion injection epicenters), not the whole lumbar section. Often the motoneuron number in the KA group was equal to or greater than the Control group, indicating more often variation than motoneuron loss. Regardless motoneuron numbers do not correlate with the observed behavioral deficits.

    __Reviewer #1 (Significance (Required)):

    This paper by Kuehn and colleagues reports on the functional impairments that follow intermediate gray matter lesions using kainic acid. This work is largely confirmatory of previous studies (Magnuson et al., 1999; Hadi et al., 2000) with modern behavioral evaluation. After revision, it would provide a description of the functional impairments following those specific lesions. The paper would be informative for a specific audience in particular scientists in the field of spinal cord injury and spinal interneuron. Our field of expertise is spinal cord injury, inflammation, behavior and axon outgrowth.__

    __Reviewer #2 (Evidence, reproducibility and clarity (Required)):

    This manuscript reports on a pair of well-designed and well-carried out studies investigating a Kainic Acid (KA)-mediated gray matter lesion in the lumbar enlargement of adult female SD rats. The investigators demonstrate, using NeuN immunohistochemistry, that the KA lesion reduces NeuN positive cells along the length of the lumbar spinal cord from rostral to L2 to slightly caudal to L4 following 6 separate injections made on the right and left sides of the spinal cord at L2, L3 and L4. The investigators made significant efforts to avoid depleting neurons in the dorsal and ventral horns, and the evidence provided suggests they were successful. The methodology described is sound and sufficient details are provided to allow the reader to fully understand the studies. It is outstanding that the study was done while following all of the PREPARE and ARRIVE guidelines. A second major component of the work is the use of multiple outcome measures and efforts (using a Forest analysis) to develop a relatively quick, accurate and efficient system to screen or classify the injuries in individual animals within 2 weeks of the injury so that subsequent treatments could be done on animals which received injuries of sufficient severity (within a relatively narrow range) and with balanced experimental and groups. Again, with this effort the investigators were largely successful. The KA lesion results in persistent locomotor and sensorimotor deficits, that plateau early without substantial sensory dysfunction.__

    Major Comments:

    __ Introduction: Overall, the rationale presented and the review of the pertinent literature is solid, with the following exception: The authors state that their model should allow them to thoroughly investigate the behavioral readout of premotor IN loss. It is generally accepted that the designation of premotor interneurons refer to those directly connected to motor neurons, and while the chosen KA lesion certainly targets some premotor neurons, it also targets many other interneurons that do not directly contact motoneurons. Please revise how the lesions are referred to. In the very next paragraph the targets are defined somewhat differently as "INs and propriospinal INs in laminae V-VII in spinal levels L2-L4".__

    • We agree that our wording does cause confusion to the reader and to avoid this we have now made the change from premotor INs to SpINs (pages 3-5).

    • On a side note, we would like to state these are adult female Fischer rats and not adult female SD rats, also described in the methods.

    Spared white matter. In many (but not all) labs, spared white matter at the epicenter is an important measurement because it presumably represents all the spared axons, such that any/all rostrocaudal communication is represented. Thus, it is the single point (or section, in this case) that has the smallest number of axons represented as stained white matter. So, to indicate that you assessed "three epicenters per spinal cord" doesn't make sense in this context, Even if you are referring to three separate KA injection sites (L2, L3 and L4). Thus, averaging three sections also doesn't really make sense because the actual epicenter should be represented by the single cross section that has the smallest area of stained white matter. Also related to spared white matter, in many labs they calculate %SWM based on a section from a control animal, and this should reduce variability because some cords shrink (injured gray matter) more than others after the injury, whether it be a contusion or mild excitotoxic injury. Please either re-calculate your SWM or provide additional justification for your current method.

    • We agree with the reviewer that normally only the epicenter of the lesion needs to be examined for white matter damage as once the connection is severed it does not matter what is rostral or caudal to this site. However, in our case we do not find any significant differences in white matter between the Controls and the KA groups. To be certain we looked at all three lesion epicenters where the damage occurred. If you examine the graphs below, you will notice that in fact the KA animals have a higher % white matter of the CSA than the Controls. Given how this analysis is done we are looking at % white matter of the cross sectional area (CSA). In the KA animals the loss of gray matter causes a collapse that makes it appear as though the white matter covers more of the CSA area than it normally does. Even if we were to normalize to the Controls you would see the same as what you already observe in these graphs.

    For this reason, we have compared the average area of white matter at the three lesion epicenters between the Control and KA groups and did not find significant differences (new Figure 7C). We also evaluated average area of white matter at the individual spinal levels (L2-L4) and did not find significant differences between the two groups and therefore averaged them. This indicates that we are not seeing any white matter alterations with our lesion model.

    Results: Within the results (and elsewhere) there are a number of un-supported statements that should be removed, softened or supported. For example, on page 18 the authors talk about how the CatWalk "further investigates the role of propriospinal INs connecting the cervical and lumbar enlargements" and no reference is provided.

    • The requested references have now been added.

    It is important to note that two animals were not included overall because they were unable to perform the CatWalk assessment. Additional information about these animals might be helpful to further characterize the KA lesions, for example, when they are too large.

    • Yes, we have looked into this. Lesion size appears to play a role (Figure 2C) but does not appear to be the only determining factor as two animals (KA#6, KA#7) with and without weight support had the same lesion length (10,325um). We predict this is due to the amount of neuronal loss; KA#7 had greater neuronal loss in all three levels compared to KA#6.

    Figure 6 brings up a number of questions including how the three "epicenters" were determined and how some KA lesioned spinal cords appear to have more than 100% the number of neurons in the control spinal cords. Yes, there is variability in normal animals, but still this seems unlikely. Is it possible that the KA injection sites were not accurate in these animals? I know it is unlikely, however, the large number of neurons in some animals at L2 is bothersome. Did the investigators always inject L2, L3 and L4 in that order? Pipettes tend to wick up liquid thus diluting the drug/cells/whatever at the tip.

    • We understand your concern of being greater than 100%, therefore we have changed the normalization to the greatest control value vs the average of controls (except for lesion size which is done to largest lesion size overall, new Supplemental Figure 3 and Figures 6 and 7 will be altered once our new analysis is finished).

    • Animal KA #1 that you are referring to could have been a technical error due to injections but it is hard to say at this point as we have found nothing from our surgery records that indicate why this animal would be different from others. Yes, bilateral injections were always performed in the same order (L2, L3, L4). However, we think it is unlikely that this created a significant drug dilution problem as we see animals with more damage in L4 than L3 or L2 (KA #3, #6 and #7 in new Supplemental Figure 3). But clearly L2 in animal KA 1 is not significantly damaged.

    Also for Figure 6, I am not convinced that the color coding is really very useful here. I think what might be more useful would be some higher magnification images of the intermediate gray matter. This figure also appears to show pipette tracks in some sections suggesting that the KA was leaking up the track either during injection or when the pipette was withdrawn. This is not a serious issue, but might be worth mentioning as a confound.

    • First, we would like to clarify that Figure 6 is already a higher magnification image of only laminae V-VII not the entire gray matter (please see figure legend). Figure 1 is a lower magnification but here in Figure 6 we wanted to highlight the region of interest that was analyzed for neuronal loss. Pipette tracks were also observed in the Controls and not thought to be due to KA leakage, as we don’t see neuronal damage beyond the injection tracts in the dorsal horns. With the new figure we will see if the color coding will be added or not dependent on the space available.

    Finally, for Figure 6, the correlations shown are quite poor, and would be even worse of control animals were not included. Too much strength is given to these findings.

    These issues with Figure 6 become even more serious as we move to Figure 7. Here, looking at the correlation to loss of MNs is weak because this reviewer is not convinced that looking at the "three epicenters" is a valid approach. Were the epicenters identified by particular criteria? Also, I think images showing how MNs were identified and counted would be important, in particular since you did not use ChAT staining but relied on NeuN and size.

    • These epicenters were chosen after reviewing all coronal sections in a 1:7 series of the lumbar cord (T12-L5). The three epicenters were the three coronal slices with the greatest neuronal loss (methods, page 12). This is supported by the inflammatory response in these sections (not shown).

    • Please see the schematic below that explains the motoneuron analysis that is also performed in our work which is detailed in the methods. Briefly, the cell soma area of NeuN+ cells in lamina IX were measured in Image J. NeuN+ cells with an area greater than 916µm2 were used for the motoneuron analysis (Wen et al, 2015).

    • We agree that in Figure 6 the correlations for each spinal level although significant are moderate but this is due to the fact that one given spinal level was not found to be responsible for the behavioral deficits. This is supported by our work on correlation with lesion length, the lesion must span multiple levels to produce the behavioral deficit. Finally, the correlations may change when we add in lamina VIII, but we won’t know until the analysis is finished.

    • As for Figure 7, we agree that we do not see correlations and our argument is that motoneuron and white matter area are not responsible for the behavioral deficits we observe (new Figure 7). Therefore, you are reading those correctly, these are not significant correlations.

    Discussion Yes, interneurons in the intermediate gray matter throughout the lumbar enlargement "regulate lower motoneurons" but they also do other things, most notably communicating both intra and intersegmentally (short and long propriospinals). Please adjust this statement.

    • We appreciate this detailed feedback, we have adjusted this statement to the following:

    “Damage to this area, which includes regulation of lower motoneurons leads not only to gross motor deficits (BBB score), but rhythmic and skilled walking (even and uneven horizontal ladders), coordination (BBB subscore), balance (inclined beam) and gait deficits (CatWalk), as well.” (page 25)

    On page 25, you talk again about premotor SpINs. I understand that you are using this term/nomenclature to distinguish these INs from motoneurons, but this is problematic because many if not most of your readers will assume the premotor SpINs synapse directly onto MNs, which of course many of the INs that are eliminated by KA do not. Calling them simply SpINs would be sufficient and still distinguish them from MNs.

    • We have adjusted this to the term “SpIN and premotor circuitry” on pages 26 and 27.

    On page 27 you talk about the RI, and while there is a statistically significant drop in RI, it must be admitted that the RI remains above 90% (0.9) which means that 9 out of 10 steps use a normal sequence. Thus, I think it is misleading to indicate that this indicates a difference for the KA animals. In fact, I think it is more important to consider how these animals were able to maintain an RI in excess of 90% despite the loss of substantial numbers of INs.

    • Thank you for the comment, we have adjusted this in the discussion:

    “In addition to gait rhythm changes, we also saw significant differences in pattern generation. The regularity index (RI) measures correctly sequenced footsteps and is used to analyze recovery in mild to moderate injuries and coordination (Koopmans et al., 2005; Kuerzi et al., 2010; Shepard et al., 2021). While KA-animals have a significantly lower RI in comparison to the controls, the RI remains above 90% which is still relatively high given the amount of neuronal loss. However, we would argue that a single parameter is not the defining factor of gait/coordination, but a combination of parameters and tests provides a more comprehensive picture, as we have seen with our pLDA analysis and Random Forest classification approaches.” (Pages 28-29)

    The rationale for determining classification prior to histological analysis is somewhat weak, and I think it would be worthwhile strengthening this rationale at the beginning of this paragraph...it becomes more obvious later why this classification is important. Is the variability of the KA model greater than an NYU or IH contusion model? If so, why? The early functional plateau is key to this argument.

    • We postulate that less severe SCIs and our milder KA lesion tend to have more variability than more severe SCI models. In the contusion models this is due to the delayed natural compensatory functional recovery plateau that can last up to 5-6 weeks. However with the KA model, variability arises from titrating down KA and adding multiple injection sites increasing variable success rate per injection. In the KA model, the early functional plateau at two weeks allows for correctly excluding or classifying animals into equally lesioned groups prior to treatment with our Random Forest Eco model. We agree that we need to clarify this reasoning in the results and have now done so on page 22. “To test the efficacy of experimental SCI therapies, it is important to effectively evaluate recovery performance through the combination of behavioral tests. In addition to carefully classifying groups at the end of the study, there is a need to provide exclusion criteria and equal sorting of variability between groups prior to treatment (after deficits have stabilized at two weeks).” (page 22)

    Minor Comments:

    __ Heatmap Analysis: The term "lesion size" is insufficiently accurate to be used in this context. Do you mean lesion length?__

    • This term has now been adjusted to lesion length throughout the manuscript and figures.

    Kainic Acid injuries are known to be accompanied by cell division and neurogenesis in the brain, and if that kind of thing is happening in the presented model, it could be an interesting confound/addition to the alluded to cellular replacement __therapies.____

    __

    • KA has been shown to be accompanied by cell division and neurogenesis in the brain, however from our own work and previous work with KA in the spinal cord if this occurs it is not at a level that is relevant to functional recovery as evidenced in our long-term study. A previous study by Magnuson et al compared E14 cerebral rat precursor cell transplantation 40 minutes and 4 weeks post-KA injury and did not find significant differences in cell survival/division (Magnuson et al., 2001). Therefore, we do not believe this would hamper or confound our future work with cellular replacement therapies. In addition, cell transplantation would take place 2 weeks post-KA injury when KA would no longer be able to hamper the transplanted cells.

    __Reviewer #2 (Significance (Required)):

    __

    __ Overall, this is a well-designed and performed set of studies that takes the KA lesion model into new territory, well set-up to perform delayed (sub-acute or early chronic) neuron replacement studies. The work characterizes a multi-segment but mild KA injury model that demonstrates persistent dysfunction that plateaus early, and a rapid and efficient system to classify the injury with a high predictability of long-term dysfunction by 2 weeks post-injury.

    This model should be of interest because it focuses on gray-matter specific tissue loss and functional deficits that should be amenable to neuron replacement strategies without the complications of white-matter dependent functional losses.

    My expertise: I have been using a variety of spinal cord injury models, in rats, for many years including contusions, lacerations and excitotoxic (KA) lesions. I have a lot of experience with locomotor, motor and sensory outcome measures. However, I have very limited experience with the Random Forest analysis employed and am not an expert in statistics.__

    __References: __

    Hadi, B., Zhang, Y. P., Burke, D. A., Shields, C. B., & Magnuson, D. S. (2000). Lasting paraplegia caused by loss of lumbar spinal cord interneurons in rats: no direct correlation with motor neuron loss. J Neurosurg,* 93*(2 Suppl), 266-275. https://doi.org/10.3171/spi.2000.93.2.0266

    Koopmans, G. C., Deumens, R., Honig, W. M., Hamers, F. P., Steinbusch, H. W., & Joosten, E. A. (2005). The assessment of locomotor function in spinal cord injured rats: the importance of objective analysis of coordination. J Neurotrauma,* 22*(2), 214-225. https://doi.org/10.1089/neu.2005.22.214

    Kuerzi, J., Brown, E. H., Shum-Siu, A., Siu, A., Burke, D., Morehouse, J., Smith, R. R., & Magnuson, D. S. (2010). Task-specificity vs. ceiling effect: step-training in shallow water after spinal cord injury. Exp Neurol,* 224*(1), 178-187. https://doi.org/10.1016/j.expneurol.2010.03.008

    Mohan, R., Tosolini, A. P., & Morris, R. (2015). Segmental Distribution of the Motor Neuron Columns That Supply the Rat Hindlimb: A Muscle/Motor Neuron Tract-Tracing Analysis Targeting the Motor End Plates. Neuroscience,* 307*, 98-108. https://doi.org/10.1016/j.neuroscience.2015.08.030

    Nicolopoulos-Stournaras, S., & Iles, J. F. (1983). Motor neuron columns in the lumbar spinal cord of the rat. J Comp Neurol,* 217*(1), 75-85. https://doi.org/10.1002/cne.902170107

    Pitzer, C., Kurpiers, B., & Eltokhi, A. (2021). Gait performance of adolescent mice assessed by the CatWalk XT depends on age, strain and sex and correlates with speed and body weight. Sci Rep,* 11*(1), 21372. https://doi.org/10.1038/s41598-021-00625-8

    Shepard, C. T., Pocratsky, A. M., Brown, B. L., Van Rijswijck, M. A., Zalla, R. M., Burke, D. A., Morehouse, J. R., Riegler, A. S., Whittemore, S. R., & Magnuson, D. S. (2021). Silencing long ascending propriospinal neurons after spinal cord injury improves hindlimb stepping in the adult rat. Elife,* 10*. https://doi.org/10.7554/eLife.70058

    Wen, J., Sun, D., Tan, J., & Young, W. (2015). A consistent, quantifiable, and graded rat lumbosacral spinal cord injury model. J Neurotrauma,* 32*(12), 875-892. https://doi.org/10.1089/neu.2013.3321

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    Referee #2

    Evidence, reproducibility and clarity

    This manuscript reports on a pair of well-designed and well-carried out studies investigating a Kainic Acid (KA)-mediated gray matter lesion in the lumbar enlargement of adult female SD rats. The investigators demonstrate, using NeuN immunohistochemistry, that the KA lesion reduces NeuN positive cells along the length of the lumbar spinal cord from rostral to L2 to slightly caudal to L4 following 6 separate injections made on the right and left sides of the spinal cord at L2, L3 and L4. The investigators made significant efforts to avoid depleting neurons in the dorsal and ventral horns, and the evidence provided suggests they were successful. The methodology described is sound and sufficient details are provided to allow the reader to fully understand the studies. It is outstanding that the study was done while following all of the PREPARE and ARRIVE guidelines. A second major component of the work is the use of multiple outcome measures and efforts (using a Forest analysis) to develop a relatively quick, accurate and efficient system to screen or classify the injuries in individual animals within 2 weeks of the injury so that subsequent treatments could be done on animals which received injuries of sufficient severity (within a relatively narrow range) and with balanced experimental and groups. Again, with this effort the investigators were largely successful. The KA lesion results in persistent locomotor and sensorimotor deficits, that plateau early without substantial sensory dysfunction.

    Major Comments:

    Introduction: Overall, the rationale presented and the review of the pertinent literature is solid, with the following exception: The authors state that their model should allow them to thoroughly investigate the behavioral readout of premotor IN loss. It is generally accepted that the designation of premotor interneurons refer to those directly connected to motor neurons, and while the chosen KA lesion certainly targets some premotor neurons, it also targets many other interneurons that do not directly contact motoneurons. Please revise how the lesions are referred to. In the very next paragraph the targets are defined somewhat differently as "INs and propriospinal INs in laminae V-VII in spinal levels L2-L4".

    Spared white matter. In many (but not all) labs, spared white matter at the epicenter is an important measurement because it presumably represents all the spared axons, such that any/all rostrocaudal communication is represented. Thus, it is the single point (or section, in this case) that has the smallest number of axons represented as stained white matter. So, to indicate that you assessed "three epicenters per spinal cord" doesn't make sense in this context, Even if you are referring to three separate KA injection sites (L2, L3 and L4). Thus, averaging three sections also doesn't really make sense because the actual epicenter should be represented by the single cross section that has the smallest area of stained white matter. Also related to spared white matter, in many labs they calculate %SWM based on a section from a control animal, and this should reduce variability because some cords shrink (injured gray matter) more than others after the injury, whether it be a contusion or mild excitotoxic injury. Please either re-calculate your SWM or provide additional justification for your current method.

    Results: Within the results (and elsewhere) there are a number of un-supported statements that should be removed, softened or supported. For example, on page 18 the authors talk about how the CatWalk "further investigates the role of propriospinal INs connecting the cervical and lumbar enlargements" and no reference is provided.

    It is important to note that two animals were not included overall because they were unable to perform the CatWalk assessment. Additional information about these animals might be helpful to further characterize the KA lesions, for example, when they are too large.

    Figure 6 brings up a number of questions including how the three "epicenters" were determined and how some KA lesioned spinal cords appear to have more than 100% the number of neurons in the control spinal cords. Yes, there is variability in normal animals, but still this seems unlikely. Is it possible that the KA injection sites were not accurate in these animals? I know it is unlikely, however, the large number of neurons in some animals at L2 is bothersome. Did the investigators always inject L2, L3 and L4 in that order? Pipettes tend to wick up liquid thus diluting the drug/cells/whatever at the tip.

    Also for Figure 6, I am not convinced that the color coding is really very useful here. I think what might be more useful would be some higher magnification images of the intermediate gray matter. This figure also appears to show pipette tracks in some sections suggesting that the KA was leaking up the track either during injection or when the pipette was withdrawn. This is not a serious issue, but might be worth mentioning as a confound.

    Finally, for Figure 6, the correlations shown are quite poor, and would be even worse of control animals were not included. Too much strength is given to these findings.

    These issues with Figure 6 become even more serious as we move to Figure 7. Here, looking at the correlation to loss of MNs is weak because this reviewer is not convinced that looking at the "three epicenters" is a valid approach. Were the epicenters identified by particular criteria? Also, I think images showing how MNs were identified and counted would be important, in particular since you did not use ChAT staining but relied on NeuN and size.

    Discussion Yes, interneurons in the intermediate gray matter throughout the lumbar enlargement "regulate lower motoneurons" but they also do other things, most notably communicating both intra and intersegmentally (short and long propriospinals). Please adjust this statement.

    On page 25, you talk again about premotor SpINs. I understand that you are using this term/nomenclature to distinguish these INs from motoneurons, but this is problematic because many if not most of your readers will assume the premotor SpINs synapse directly onto MNs, which of course many of the INs that are eliminated by KA do not. Calling them simply SpINs would be sufficient and still distinguish them from MNs.

    On page 27 you talk about the RI, and while there is a statistically significant drop in RI, it must be admitted that the RI remains above 90% (0.9) which means that 9 out of 10 steps use a normal sequence. Thus, I think it is misleading to indicate that this indicates a difference for the KA animals. In fact, I think it is more important to consider how these animals were able to maintain an RI in excess of 90% despite the loss of substantial numbers of INs.

    The rationale for determining classification prior to histological analysis is somewhat weak, and I think it would be worthwhile strengthening this rationale at the beginning of this paragraph...it becomes more obvious later why this classification is important. Is the variability of the KA model greater than an NYU or IH contusion model? If so, why? The early functional plateau is key to this argument.

    Minor Comments:

    Heatmap Analysis: The term "lesion size" is insufficiently accurate to be used in this context. Do you mean lesion length?

    Kainic Acid injuries are known to be accompanied by cell division and neurogenesis in the brain, and if that kind of thing is happening in the presented model, it could be an interesting confound/addition to the alluded to cellular replacement therapies.

    Significance

    Overall, this is a well-designed and performed set of studies that takes the KA lesion model into new territory, well set-up to perform delayed (sub-acute or early chronic) neuron replacement studies. The work characterizes a multi-segment but mild KA injury model that demonstrates persistent dysfunction that plateaus early, and a rapid and efficient system to classify the injury with a high predictability of long-term dysfunction by 2 weeks post-injury.

    This model should be of interest because it focuses on gray-matter specific tissue loss and functional deficits that should be amenable to neuron replacement strategies without the complications of white-matter dependent functional losses.

    My expertise: I have been using a variety of spinal cord injury models, in rats, for many years including contusions, lacerations and excitotoxic (KA) lesions. I have a lot of experience with locomotor, motor and sensory outcome measures. However, I have very limited experience with the Random Forest analysis employed and am not an expert in statistics.

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    Referee #1

    Evidence, reproducibility and clarity

    In this paper, Kuehn and colleagues report on the analysis of functional impairments following intermediate gray matter lesion with kainic acid. The image convincingly show that mostly purely grey matter lesion can be achieved throughout the paper. The authors took care to do a battery of well-designed behavioral tests and sophisticated analysis in order to access functional impairment. They then correlate their behavioral assessment to lesion size, the number of NeuN positive cells in layers V-VII epicenters as well motoneuron numbers and the percentage of white matter. Overall, the manuscript is well written, nicely framed in the existing literature, very clear and the experiments are simple but well designed. The behavioral testing and evaluations including random forest ranking are well performed. The methodology is complete and would allow reproducing the experiments. Statistics are used appropriately. We have however some reserves and comments on some of the results and interpretations. Addressing these comments would not involve new experiments but new re-analysis of the existing datasets.

    Major comments:

    While the claims that grey matter lesions trigger major behavioral impairments is convincing in particular with the refine behavioral experiments performed, the key claim that only interneuron loss in layer V-VII mediates those deficits is currently not supported by the presented data. In particular, we would suggest that the lesions performed, in contrast to the claims, are not purely and selectively impacting layer V-VII but might also impact layers VIII-IX. We think that presenting neuronal counts based on NeuN staining separately for layer I-IV, V-VII, VIII-IX and comparing control vs KA is necessary. Only with these data can conclusions be supported either in the direction suggested by the authors or otherwise.. Another claim relative to the lack of involvement of motoneurons in the related behavioral deficits is also difficult to resolve with the current data. Motoneurons have been identified based on NeuN staining and size. While this is not the state of the art (ChAT staining would have been preferable), it remains acceptable. However, the data presented figures 7 and 8 show a very wide range in the motoneuron count (15 to 50) indicating either motoneuron loss or a count performed at different lumbar levels in the animals. This raises questions on the model (is it really involving only layers V-VII?) or on the interpretation of the data. Therefore we believe that motoneurons counts need to be presented separately (see above) in control vs KA groups and data need to be discussed in this perspective. Authors should also tone down the specificity of the model and involvement of motoneurons accordingly (page 20 for example). Most of the conclusions rely on correlations that include control animals (injected with saline hence with no lesions and no behavioral deficits; Fig 6 and 7). This artificially skews the correlations as those animals show no lesions and good performance in the behavioral tests. These correlations need to be performed only with KA injected animals to determine the respective involvements of interneurons and motoneurons.
    The long-term study (Fig 8) is performed with very few animals and hence, drawing conclusions from these animal numbers is difficult. All correlations are performed including control animals which is even more of a problem here as in Figure 6 and 7 due to the low number of animals. The authors should either add animals or remove the figure. When control animals (injected with saline) are removed (as they do not show any lesion and perform accurately in the behavior), one would actually see a correlation between the number of motoneurons and the behavioral performance (Fig. 8E,F) but not with the lesion size (Fig.8C,D).

    Minor comments:

    Figure 1A: if lesions are bilateral, it would be nice to illustrate this on the schematic.

    Figure 1B-D: scale bars are missing

    Figure 3H: What represents the y-axis? % of completion or number of completion?

    Figure 4 Table: Please specific what the acronym stands for: pLDA.

    Figure 6 A: scale bars are missing

    Figure 6B/C/D: please add the spinal level analyzed directly on the graphs. This will ease the comprehension.

    Figure 7 and Figure 8: While it is quite convincing that the model is purely a grey matter injury (panel C and D), the data are very much spread out for the number of motoneurons per mice (see major comments above). We would suggest to plot those data to present the number of neurons (interneurons in layer I-IV, V-VII and motoneurons) control vs KA.

    Dots are missing on those figures (probably superimposed on top of each other). This should be changed to see all data points

    Figure 8E,F: the number of motoneurons is very low also in controls. How is this explained?

    Significance

    This paper by Kuehn and colleagues reports on the functional impairments that follow intermediate gray matter lesions using kainic acid. This work is largely confirmatory of previous studies (Magnuson et al., 1999; Hadi et al., 2000) with modern behavioral evaluation. After revision, it would provide a description of the functional impairments following those specific lesions. The paper would be informative for a specific audience in particular scientists in the field of spinal cord injury and spinal interneuron.

    Our field of expertise is spinal cord injury, inflammation, behavior and axon outgrowth.

  8. Version published to 10.1101/2022.10.31.514612v1 on bioRxiv