Elaborate behaviours are produced by tightly controlled flexor-extensor motor neuron activation patterns. Motor neurons are regulated by a network of interneurons within the spinal cord, but the computational processes involved in motor control are not fully understood. The neuroanatomical arrangement of motor and premotor neurons into topographic patterns related to their controlled muscles is thought to facilitate how information is processed by spinal circuits. Rabies retrograde monosynaptic tracing has been used to label premotor interneurons innervating specific motor neuron pools, with previous studies reporting topographic mediolateral positional biases in flexor and extensor premotor interneurons. To more precisely define how premotor interneurons contacting specific motor pools are organized, we used multiple complementary viral-tracing approaches in mice to minimize systematic biases associated with each method. Contrary to expectations, we found that premotor interneurons contacting motor pools controlling flexion and extension of the ankle are highly intermingled rather than segregated into specific domains like motor neurons. Thus, premotor spinal neurons controlling different muscles process motor instructions in the absence of clear spatial patterns among the flexor-extensor circuit components. . Within these networks are interneurons that project to motor neurons, which innervate different types of muscle to contract: flexors (such as the biceps), which bend, or ‘flex’, the body’s joints, and extensors (such as the triceps), which lead to joint extension. These motor signals must be carefully coordinated to allow precise and stable control of the body’s movements.The spinal cord contains circuits of nerve cells that control how the body movesPrevious studies suggest that where interneurons are placed in the spinal cord depends on whether they activate the motor neurons responsible for flexion or extension. To test if these findings were reproducible, Ronzano, Skarlatou, Barriga, Bannatyne, Bhumbra et al. studied interneurons which flex and extend the ankle joint in mice. In collaboration with several laboratories, the team used a combination of techniques to trace how interneurons and motor neurons were connected in the mouse spinal cord. This revealed that regardless of the method used or the laboratory in which the experiments were performed, the distribution of interneurons associated with flexion and extension overlapped one another.This finding contradicts previously published results and suggests that interneurons in the spinal cord are not segregated based on their outputs. Instead, they may be positioned based on the signals they receive, similar to motor neurons.Understanding where interneurons in the spinal cord are placed will provide new insights on how movement is controlled and how it is impacted by injuries and disease. In the future, this knowledge could benefit work on how neural circuits in the spinal cord are formed and how they can be regenerated. Precise regulation in the timing and pattern of activation of muscle groups across a joint is at the basis of motor control. In limbed vertebrates, the activity of flexor and extensor muscles is directed by dedicated pools of motor neurons that receive inputs from different subtypes of excitatory and inhibitory interneurons. Several of these classes of interneurons have been described in electrophysiological, anatomical, and genetic studies ; howeverViral trans-synaptic tracing techniques have been used for several decades to map motor circuits . Given tThe introduction of RabV monosynaptic tracing provided a high-throughput method for mapping presynaptic connectivity of selected neuronal populations . MonosynShortly after its introduction, monosynaptic rabies tracing was applied to the study of premotor interneurons in the spinal cord. To obtain selective complementation of G and subsequent rabies monosynaptic transfer from a single motor neuron pool, an elegant approach based on intramuscular co-injection of an AAV expressing G (AAV-G) and ΔG-RabV, both of which can infect motor neurons retrogradely, was described . Thus, sCre/+Chat mice was used to target G expression to cholinergic neurons, with restriction of starter cells to a motor pool achieved by ΔG-RabV muscle injection. These experiments also showed medio-lateral segregation in the distribution of flexor and extensor premotor interneurons  2 and L5 sections 8–9 days after injection revealed two main clusters of premotor interneurons located in the dorsal ipsilateral and ventral contralateral spinal cord  and LG  muscles of postnatal day (P) 1–2 nal cord . Next, wCre/+; Rosa26RΦGTChat mice: TA and LG, LG, and MG  and TA and PL . We started by analysing the results from the antagonist pairs, LG (n=11) and TA (n=7), pooling experiments from single and double injections  medial motor neurons that send recurrent axon collaterals to lateral motor neurons. In fact, while collaterals from lateral or medial motor neurons have not been traced outside their respective columns, the dendritic arborization from medial and lateral motor neuron columns extends to each other and labelling of lateral motor neurons following rabies injection of medial column innervating muscles has been observed , indicatCre/+; Rosa26RΦGTChat mice (9 I.U./ml) to reduce its infection efficiency (see 9 I.U./ml). Once again, we did not observe segregation in the medio-lateral distribution of LG and TA premotor interneurons , the median value of the medio-lateral positions in each experiment were very similar  in ΦGT mice  as in thency see . In low rneurons , nor alorneurons . The pairneurons . While tR2=0.48), in agreement with published brain datasets , while for ventral interneurons were 395 μm for LG and 437 μm for TA . between all individual experiments underscored the conserved positional organization of LG and TA premotor interneurons. These data indicate that there is no significant difference in the distribution of GlyT2off and GlyT2on premotor interneurons controlling the activity of flexor and extensor muscles.We monitored the GlyT2 status of cells while performing transsynaptic labelling from LG and TA motor neurons. First, we compared the distribution of premotor GlyT2rneurons  and thenrons . In contrast, ventral ipsilateral GlyT2on were more abundant than GlyT2off for both LG . Overall, the data show a clear segregation in the distributions of GlyT2off and GlyT2on premotor interneurons in the ventral half of the spinal cord: GlyT2on interneurons are almost exclusively found in the ipsilateral side while GlyT2off interneurons also present a prominent peak in the contralateral side (off and GlyT2on premotor interneurons for both LG and TA premotor interneurons (r≤0.4).Finally, we compared the distributions of GlyT2scle, LG  and TA  that have prominent projections to motor neurons  and the low values of hierarchical bootstraps of the Hedges’ G coefficients across muscles and Cre/+Olig2 and Cre/+Chat injections  and Cre/+Olig2 (295 μm for GS and 310 μm for TA) animals injected in the same muscle  using the ig2Cre/+  instead e/+ line . This lie/+ line . We rease/+ mice . There we/+ mice –12 as wee/+ mice , with mejections . In addiIn contrast to previous findings using AAV-G , we founCre/+Chat mice (1 μl of a 3:1 AAV-flex-oG: ΔG-RabV mix), a strategy that was previously used to show segregation of flexor and extensor premotor circuits  for the GS pairs and –0.14  for the TA pairs. In addition, there was an excess of medially located infected neurons, in both GS and TA experiments, when the expression of G was not restricted to motor neurons. The dorsoventral and mediolateral differences in the distributions observed in AAV-G and AAV-oG-Flex experiments were substantial for both GS and TA, thus indicating that when G could be expressed by sensory neurons (AAV-G muscle injection), the average position of labelled cells extended more dorsally and medially compared to experiments in which G could only be expressed in motor neurons (AAV-oG-Flex). The observed mediodorsal shift is compatible with a contribution of anterograde tracing from sensory neurons , which iFinally, we studied organization of premotor circuits using a different viral tracing method. Pseudorabies virus (PRV) is a neurotropic virus that travels transsynaptically in the retrograde direction. It has previously been used to resolve the connectivity order in polysynaptic circuits  using tiWe finally pooled together all the results obtained with different methods. In all cases, the correlations between flexor and extensor muscles labelled with the same methods were very high . The lowSpinal circuits are responsible for integrating descending commands and sensory information to ensure precise control and coordination of movement. In order to understand how these circuits organise movement, it is necessary to first identify and then study the roles and contributions of spinal interneurons that control the activity of different muscles. Previous work  exploiteRΦGTRosa26 mice; Cre/+Chat or Cre/+Olig2 lines , it is unlikely that many, if any, double jumps would have occurred in this time window. We cannot exclude that at least some of the labelled interneurons were generated by second-order transfers, but arguably these are rare events and unlikely to be the source of the different results obtained in AAV vs mouse genetic experiments.Nonetheless, to further explore the possibility of disynaptic pathways via cholinergic spinal interneurons, we examined the organization of flexor and extensor premotor circuits in experiments conducted with the rneurons . We did transfer . The earCre/+Chat mice was used  promoter to drive G expression , we usedThe identity and number of starter cells are the main determinants of reproducibility in rabies tracing experiments and thus represent key parameters for comparing different approaches. For experiments using ΔG-RabV, starter cells are those that are both primarily infected with RabV and express G. In general, for both the AAV and mouse genetics methods discussed here, it is difficult to precisely determine these factors, as neither approach employs expression of a reporter gene to mark G-expressing cells. Moreover, RabV is known to be toxic to neurons and some primary infected motor neurons are likely to die before analysis . BecauseRestriction of starter ‘status’ to motor neurons connected to a single muscle is determined by two aspects: the specificity of rabies virus injection and the availability of sufficient levels of G protein in the same cells . All theIn the short term, the introduction of a reporter system to label G-expressing neurons, as routinely done in many rabies experiments, combined with the use of non-toxic rabies variants that would prevent motor neuron death  will helWhile it has been proposed that spatial segregation of premotor interneurons provides an anatomical substrate for labelled line inputs from proprioceptive afferents to motor neurons , our datIn conclusion, despite using five different methods, we have not been able to find evidence that spinal premotor interneurons innervating flexor vs extensor motor neurons are segregated. It is important to stress that none of the methods discussed here is completely exempt from potential problems . HoweverCre/+Olig2 mice were performed and analysed at the Max Delbrück Center (MDC), with locally produced RabV. The injections of AAV-G and AAV-G-Flex in wild type and Cre/+Chat mice respectively were performed and analysed at the Salk Institute. The AAV-G construct was produced from Applied Viromics, while the AAV-G-Flex was produced at the Salk GT3 Core and the RabV was obtained from Janelia Farm. Experiments with PRV-Bartha rabies strain were performed and analysed at the Salk Institute. PRV-Bartha was obtained from NIH CNNV.The experiments were performed and analysed across 4 different laboratories. The injections labelled as UoG (University of Glasgow) were performed in the Beato lab at UCL (three different operators) and processed in Glasgow (Maxwell and Todd labs) using RabV produced in the Beato lab. The injections labelled as UCL were performed in the Brownstone lab (two different operators) using RabV produced in the Brownstone lab and the tissue was processed at UCL (Brownstone lab). The injections in All experiments at UCL were carried out according to the Animals (Scientific Procedures) Act UK (1986) and were approved by the UCL AWERB committee under project licence number 70/9098. All experiments performed at the MDC were carried out in compliance with the German Animal Welfare Act and approved by the Regional Office for Health and Social Affairs Berlin (LAGeSo). All experiments performed at the Salk Institute were conducted in accordance with IACUC and AAALAC guidelines of the Salk Institute for Biological Studies. Experimental design followed the ARRIVE guidelines.Cre/CreChat mice , to generate Cre/+; Rosa26RΦGTChat or Cre/+; Rosa26RΦGTOlig2 mice  mice (13 sections from 3 mice), and found tdTom expression in cholinergic motor neurons and interneurons as expected, as well as in some non-cholinergic neurons distributed in intermediate  and dorsal  laminae, with the remaining 35 located ventrally  multiplicity of infection. Three RΦGTRosa26 heterozygous mice were injected in the lateral gastrocnemius muscle at P1 and fixed 9 days post injections. The tissue was cut as described below, but along the horizontal plane in 60 μm sections, in order to isolate the dorsal motor column. Following immunoreaction for eGFP, in each of the three cords, we found a maximum of three labelled motor neurons  but no interneurons labelled, indicating some leakage in the expression of the TVA-IRES-glycoprotein cassette from the RΦGTRosa26 mice, but insufficient G expression to support transsynaptic jumps . The cell lines were not used as an experimental system, but only for virus production. The cells were then inoculated at 0.2–0.3 multiplicity of infection with either the ΔG-RabV-eGFP or the ΔG-RabV-mCherry . Cells were incubated for 6 hr at 35 °C and 3% CO2 and then split 1–4 into 20 dishes (10 ml) with 10% FBS medium and kept at 37 °C and 5% CO2 for 12–24 hr, until ~70% confluent and medium was then replaced with 2% FBS medium and cells incubated at 35 °C and 3% CO2 for virus production. The supernatant was collected after ~3 days, new medium was added for another round of production and supernatant was filtered (0.45 μm filter) and centrifuged for 2 hr at 19,400 rpm (SW28 Beckman rotor). The pellets were suspended in phosphate buffer saline (PBS), dispersed and collected in a single tube and further centrifuged for 4 hr at 21,000 rpm in a 20% sucrose gradient (SW55 Beckman rotor). The resulting pellet was suspended in 100 μl PBS and the virus was aliquoted (5–10 μl) and stored in a –80° freezer. The viral titre of each round of production was measured by serial 10-fold dilution of three different aliquots using standard protocols (13 GC/mL) was generated at Applied Viriomics, while AAV6-CAG-Flex-oG was generated at the GT3 core at the Salk Institute. For retrograde PRV-Bartha experiments, PRV-152 (GFP) and PRV-614 (mRFP) were obtained from the Center for Neuroanatomy with Neurotropic Viruses (CNNV).Rabies virus used in experiments performed at UCL, was obtained from in house stocks of a variant of the SAD-B19 rabies strain where the sequence coding for the glycoprotein was replaced by the sequence for either eGFP or mCherry . Virus wrotocols . As a merotocols . For theNeonatal pups (P1-P2) were anaesthetized using isoflurane inhalation and an incision was made on the skin to expose the belly of the targeted muscle, either lateral or medial gastrocnemius , tibialis anterior (TA) or peroneus longus . The virus was injected intramuscularly using a 5 μl Hamilton syringe (model 7652–01) fixed to a manual Narishige micromanipulator (M-3333) and loaded with a bevelled glass pipette of inner diameter 50–70 μm. The volume injected was 1 μl, compatible with the estimated volume of the muscles at this age (~2 μl), in order to minimize the risk of leaks to adjacent muscles. Viral batches of similar titres were slowly (>1 min) injected, the skin incision was sutured with Vicryl 8–0  and the pups received a subcutaneous injection of carprofen (10%) for pain management. Mice were closely monitored for the next 24 hr for signs of movement impairment and were perfused under terminal general anaesthesia 8–9 days after injection.Cre/+; Rosa26RΦGTChat or Cre/+; Rosa26RΦGTGlyT2-eGFP;Chat mice.In order to compare directly the distributions of flexor and extensor associated premotor interneurons and avoid confounding factors in the coordinate representations of these interneurons across different spinal cords, we performed double injections of ΔG-RabV in the same animal, using ΔG-Rab-eGFP and ΔG-Rab-mCherry injected in pairs of antagonist muscles, lateral gastrocnemius and tibialis anterior. For comparison, we also performed double injections in pairs of synergist muscles: LG and MG or TA and PL. Due to the close proximity of these pairs of muscles, before cutting the spinal tissue for immunohistochemistry, we dissected the injected leg and confirmed that there was no contamination of virus across the injected muscles or in adjacent muscles below or above the knee. To exclude confounding factors in our observed premotor interneuron distributions due to systematic viral interference , in a suCre/+; Rosa26RΦGTin Olig2 mice using a glass capillary. Animals were perfused at P10, 6 days after injection in order to minimize the chance of disynaptic transfer.For experiments performed at MDC, intramuscular injections were done as previously described . BrieflyCre/+Chat experiments, a 3:1 mixture of AAV-CAG-Flex-oG (Addgene #74292) and ΔG-Rab-GFP was injected into either the GS or TA muscles of P1-P2 pups. Anaesthesia, injection volume, and syringe used were the same as above. Animals were fixed by perfusion under terminal general anaesthesia, as described below, 7 days post-injection. Hindlimbs were visualized under a stereoscope to confirm correct targeting of muscles.For wild type ΔG-RabV premotor labelling experiments performed at the Salk Institute, P2 pups were anesthetised on ice and 1 μl of a 3:1 mixture of AAV-Ef1a-B19G and ΔG-Rab-GFP or ΔG-Rab-mCherry was injected through the skin into the GS or TA muscles of the same animal, using a 10 μl Hamilton syringe with 30-gauge metal needle. Animals were fixed by perfusion under terminal general anaesthesia, as described below, 10 days post injection. For For PRV experiments, intramuscular injections of PRV were performed in P11 pups under 2–3% isoflurane anaesthesia. Briefly, a small incision was made in the skin to expose the TA and GS and 0.5 μl of PRV-152 or PRV-614 was delivered to either muscle, in the same animal, using a glass needle and picospritzer. Animals were perfused 48 hr post injection. Hindlimbs were visualized under a stereoscope and sectioned to confirmed correct targeting of muscles.Under ketamine/xylazine terminal anaesthesia (i.p. 80 mg/kg and 10 mg/kg respectively), mice were intracardially perfused with phosphate buffer solution (0.1 M PBS), followed by 4% paraformaldehyde in PBS. The spinal cords were dissected and post-fixed for 2 hr at 4 °C, cryoprotected overnight at 4 °C in 30% PBS sucrose solution and embedded in OCT  compound.For UCL experiments, injections were all conducted at UCL, whereas the immunohistochemistry and imaging were conducted on different animals independently in two different laboratories (Maxwell at Glasgow University and Beato/Brownstone at UCL). For tissue processing performed at UCL, lumbar spinal cords were cut (30 μm thickness) in series in the transverse plane with a cryostat  mounted onto charged glass slides , and stored at –20 °C. Sections were incubated for 36 hours at 4 °C with primary antibodies and overnight at 4 °C with secondary antibodies in PBS containing 0.3 M NaCl, 0.2% Triton 100 X , 7% donkey normal serum . The primary antibodies used were: guinea pig anti-Isl1 , goat anti choline acetyl transferase , rabbit anti-GFP , chicken anti-mCherry . The secondary antibodies were: donkey anti-guinea pig Alexa 647 , donkey anti-goat preabsorbed Alexa 405 , donkey anti-rabbit Alexa 488 , and donkey anti-chicken Cy3 . The slides were mounted in Mowiol  and cover-slipped  for imaging.At Glasgow University, the spinal cords were sectioned using a Leica VT1000 vibratome (thickness 60 μm) and incubated in 50% ethanol for 30 min. Primary antibodies used were: chicken anti-GFP , rabbit anti-mCherry  and goat anti-ChAT . The secondary antibodies were: donkey anti-chicken A488 , and donkey anti-rabbit Rhodamine red . Sections were mounted in Vectashield  and coverslipped.AB_2750952) followed by 1 hr incubation at room temperature with secondary antibody . Slides were mounted in Vectashield.For the experiments performed at MDC, spinal cords were processed as previously described . BrieflyFor PRV and ΔG-RabV experiments performed at the Salk Institute, animals were transcardially perfused with ice cold 1 x PBS followed by ice cold 4% PFA . Spinal cords were dissected and post-fixed in 4% PFA for 2 hr at 4 °C. After the post-fixation, samples were washed with 1 x PBS for 10 min followed by a 1–3 day incubation in 30% sucrose for cryoprotection (4 °C). The lumbar spinal cord was then embedded in Tissue-Tek OCT (Sakura 4583) for cryosectioning onto glass slides (Fisherbrand Superfrost slides 12-550-15) in the transverse plane. The section thickness was 60 μm for delta-G-RabV experiments and 30 μm for PRV experiments. Immunohistochemistry was performed by incubating tissue with primary antibodies overnight at 4 °C and secondary antibodies for 2 hr at room temperature, in a 0.3% Triton-X and 20% donkey serum blocking buffer. After staining slides were mounted with a glass coverslip and Fluoromount-G (00-49-58-02). The antibodies used for this portion of the study were: goat anti-GFP , rabbit anti RFP , donkey anti-goat Alexa 488 , donkey anti-rabbit-Alexa 555 .For UCL experiments, confocal images were acquired using a Zeiss LSM800 confocal microscope with a 20 x (0.8 NA) air objective and tile advanced set up function of ZEN Blue 2.3 software for imaging of the entire slice. The tiles were stitched using ZEN Blue software and cell detection was performed using Imaris  software. Cell counts were manually performed on every other section, in order to minimize the risk of counting the same cell twice in two consecutive sections.For experiments performed at Glasgow University, the images were acquired using a Zeiss LSM710, with a 20 x (0.8 NA) air objective and cells were counted manually using Neurolucida. Only a subset of sections was analysed (1 in every 8 consecutive sections), thus accounting for approximately 2 sections for every spinal segment.For experiments performed at the MDC, confocal images were acquired using a Zeiss LSM800 confocal microscope. Regions of interest corresponding to each section and consisting of 8 tiles were imaged with a 10 x (0.3 NA) air objective. The tiles were subsequently stitched using ZEN 2.3 Software. Acquisition and processing were performed immediately after immunohistochemistry where possible, to obtain the best possible signal. The resulting images were used for three-dimensional positional analysis as previously described .th section. Both samples were analyzed in MATLAB using a custom script for cell detection.For experiments performed at the Salk Institute, fluorescent images were acquire using an Olympus VS-120 virtual slide scanner microscope with a 10 x objective (0.3 NA). For ΔG-RabV experiments cells counts were performed on every section. For PRV experiments cell counts were performed on every 8A consistent system of coordinates was established using the central canal as origin of the x-y plane. The y-axis was defined as parallel to the dorso-ventral axis, with positive values towards the dorsal side and the x-axis was determined by the mediolateral direction, with positive values on the side of injection. For UCL and University of Glasgow experiments the L4-L5 border in the z direction was determined during the slicing procedure and its location was confirmed post-processing by identifying the slices with the widest mediolateral width. For MDC and Salk Institute experiments, the border between T13 and L1 was chosen as the starting point for slicing. The z coordinates obtained in different labs were subsequently aligned using the widest section as a point of reference for the border between L4 and L5 segments. For both Neurolucida and Imaris data files, in order to account for the different shapes of sections throughout the lumbar cord and deformation of individual sections, normalization of coordinates was performed independently for each quadrant using as reference points those indicated in n for each experiment n and evaluating the correlation coefficient nmr between experiments n and m using the formulaGaussian convolutions were calculated splitting the transverse, normalized, spinal cord profile into ipsi- and contra-lateral, and dorsal and ventral halves, with the corresponding distributions shown surrounding the transverse spinal cord maps. Areas under the top-bottom or left-right distributions of each label sum to 1. Correlations across individual experiments were calculated from the x-y coordinates projected along the rostrocaudal axis by computing a density matrix ρ–4) p-values for distributions whose medians where only a few μm apart. Since the spatial resolution of our cell location procedure is no higher than the diameter of the infected cells, such results cannot be considered meaningful. Second, our data have an intrinsically nested structure, therefore, hypothesis testing on pooled experiments would lead to an error caused by ignoring the hierarchical nature of our data. Therefore, when comparing different methods of injections where distributions from multiple animals were analysed, we first performed a hierarchical bootstrap procedure  feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: (i) Decision letter after peer review:eLife. Your article has been reviewed by 3 peer reviewers, including Jeffrey C Smith as Reviewing Editor and Reviewer #1, and the evaluation has been overseen by John Huguenard as the Senior Editor.Thank you for submitting your article "Spinal premotor interneurons controlling antagonistic muscles are spatially intermingled" for consideration by The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential revisions:1) The connections and spatial distributions of lumbar spinal premotoneurons were studied here in neonatal mice. This is a current limitation of the technique. Most other labs have also used neonatal animals for their studies. This is potentially a significant limitation and should be carefully discussed since it limits interpretation because there is still significant ongoing synaptogenesis and refinement of connections at this age. We understand that other similar studies have similar limitations but, with the emphasis on technical issues in the paper, this limitation should be discussed.2) The authors should comment on the large variability between experiments and possible sources. Examination of the number of motoneurons labeled in these experiments provided in Table 1 and Figure 12 supplements show high variability.3) Figure 3—figure supplement 1 illustrates data from segments lumbar 1 to 6 in which all segments are identical in size and shape due to the normalization procedure used. To avoid confusion, the authors could show the actual sizes before normalization, and then the normalized outlines and distributions. At least make sure the main text explains these are normalized representations .4) Currently it is unclear which experiments were analyzed throughout the whole lumbar enlargement and which did not. It would be beneficial to state in the Table the segments analyzed  in each experiment. Supplemental Figure 12 depicts only L4 and L5 sections. See Reviewer #2 for related comments.5) There are questions about the authors' interpretation of ectopic motoneurons outside of expected motor pools. Please see Reviewer #2: Ectopic motoneurons.6) When using a motoneuron-specific AAV-flex-G in ChAT-Cre mice, there are many more interneurons labeled in these experiments compared to experiments using transgenesis for introducing G in motoneurons. This requires some explanation because the main argument of using transgenic animals to express G is that it would increase and normalize the number of starter motoneurons reducing variability due to the probabilistic nature of co-infections with two viruses.7) The peaks of the contours in Figure 8C are indiscernible . Since this is a key replication experiment, the results should be clear for comparison. Using darker shades of the colors for contrast may be enough.8) The leak in Cre expression indicated by Cre/tdTomato labeling in Figure 13 is extensive with 25% of TdTomato labeled neurons being ChAT negative. This is a significant number of interneurons that could initiate second trans-synaptic jumps, which should be pointed out more clearly. If the leaky Cre of the ChAT mouse marks V2 and V3 neurons, this would explain the similar results between the mice. The experiment in the RΦGT mouse without Cre  Extending the spatial analyses to consider the locations of excitatory and inhibitory interneurons is an important component of these studies, although there are questions about the authors' identification/nomenclature of excitatory and inhibitory interneurons. Based on previous anatomical studies suggesting co-expression of GABA and glycine in spinal interneurons, the authors interpret GlyT2-off neurons as excitatory. As argued by Reviewer #2, the statement that all GABAergic spinal neurons should be GlyT2-on may be inaccurate. It is recommended that the authors be more conservative in their interpretation, for instance, by just naming these cells as non-glycinergic, and not making assumptions on these GlyT2-off neurons are excitatory interneurons without direct evidence. Please see the questions by Reviewer #2.10) The argument (lines 264-266) that interneurons presynaptic to V0c neurons are located in superficial laminae and that most labeling shown in here is more ventral is weak. Reviewer #2, for the reasons outlined in the review, recommends that the authors do not discard possible contributions of disynaptic jumps that might not be revealed by the current analyses. This should be discussed.11) In the Discussion the authors propose that intracellular delivery of DNA for G and TVA followed by EnvA-coated RV could increase specificity and allow tracing from single functionally defined motoneurons. The transsynaptic jump and expression of these genes takes days and therefore in vivo experiments allowing for enough survival time are necessary. Is motoneuron patch-clamping with in vivo experiments followed by a survival period possible? Are the authors proposing a feasible approach?12) Although the authors made several attempts to provide explanations for the discrepancies with the previously published mapping results, the question remains – how did two groups who published independent studies using different strategies demonstrate flexor and extensor separation in the dorsal horn, when this study, using several strategies in multiple labs, show that the premotor neurons are in complete overlap? Additional small differences in methodologies could be identified which are not discussed and may provide potential explanations. There are small differences that are not discussed and could provide potential explanations for discrepancies within single techniques, but none will resolve the conflict since they each apply only to a single strategy. For example, the AAV promoters are different (Efa1 here and CMV in the Arber lab papers) and the ratio of Rab to G complement is different (3:1 here and 1:1 in the prior). These could fit well into the section of the Discussion (lines 449-454) because, where they could differentially affect the transmission in the co-injection to muscle experiments, they do not provide answers for discrepancies with other techniques, including the conditional virus experiments.Reviewer #1 (Recommendations for the authors):All the experimental approaches and data analyses are technically elegant, well designed and executed, and clearly presented with due consideration in the manuscript for any technical limitations. Overall, the experiments are rigorously performed with a design that attempts to reduce biases associated with the various RabV-based circuit tracing methods. The data, although very extensive with numerous data source files and supplemental illustrations (which is justified given the scientific problem and controversy requiring data transparency), are clearly presented. I do not have major concerns.Reviewer #2 (Recommendations for the authors):I congratulate the authors for a comprehensive set of thorough analyses with a large number of experiments and experimental variables tested to shed some light into the important problem of the organization of premotor interneurons in the spinal cord. As I mentioned in the public review, I believe this is a very useful study. However, there are some important details that need to be clarified such that confusion is not introduced for potential future users of this complex methodology to map premotor interneurons in the spinal cord.1) Figure 3-figures supplement 1 illustrates data from segments lumbar 1 to 6. All segments are identical in size and shape because the normalization procedure used by the authors and explained in methods. This is misleading to most readers which will be largely of unaware of spinal cord anatomy. I recommend showing the actual realistic sizes, before normalization, and then the normalized outlines and distributions. Also, please make sure the main text explains these are normalized representations . I believe this normalization was not done in Tripodi et al., who seem to have just added all cells in 2D projections with the original positional values  independent of lumbar segments. Tripodi argues that medio-lateral differences are more apparent rostrally, which makes sense because the narrower lateral extension of L1 compared to L4/L5. Figure 2C only shows TA and LG interneurons distributions overlapping in L4 and L5, but in the supplemental figure it looks there are many more TA interneurons in L1 compared to LG. Is it possible to illustrate the distribution of these interneurons in an horizonal projection of all lumbar segments as in 2C? Are TA interneurons indeed more abundant in L1 and because of this they bias more medially when all segments are added together without normalization? Is the normalization obscuring one further explanation for the differences among the studies? On a related noted I was not sure which experiments were analyzed throughout the whole lumbar enlargement and which did not. It will be good to state in the Table the segments analyzed  in each experiment. Supplemental Figure 12 depicts only L4 and L5 sections.2) Lines 122-124. I do not understand why the authors argue that lack of identification of G complementation prevents identification of starter neurons. With the transgenic approaches they are using, all motoneurons should express G and precise identification of starter cells thus only depends on how many motoneurons are infected. Of course, this is difficult to estimate because progressive cell death, as indicated in the manuscript. I recommend deleting lines 122 and 123 and just state that it is difficult to identify all starter motoneurons unambiguously because the possibility of cell death.3) Variability in cell numbers: Close examination of the number of motoneurons labeled in these experiments provided in table 1 and figures 12 supplements show high variability. For example, LG muscle injections in Chat-cre with high titer virus at UCL or UoG vary from 8 motoneurons to 110 (even when taking away differences in counting methods and section sampling), with more motoneurons in experiments labeled as UCL compared to UoG. Similar variability occurs in recovered interneurons (356 to 2574). MDC experiments in Olig2-cre mice seem to be in between. It is remarkable that the dorso-ventral and medio-lateral distribution are the same despite such wide variations in interneurons labeled. This strengthens the conclusions, but I would suggest the authors comment on the large variability between experiments and possible sources. Moreover, from Materials and methods it was unclear whether in injections of UoG were also done that UCL and then processed at Glasgow. It seems this was the case but it could be made clearer, given that in the table they are labeled as a different institution.4) Ectopic motoneurons. The authors argue that ectopic motoneurons outside the expected motor pools are caused mainly by motoneuron-to-motoneuron connections and transynaptic transfer, this might be for some, however in Figure 2C and Figure 12 supplements some are in the medial motor column. As far as I know there are no reports of recurrent motor axon collaterals between LMC and MMC motoneurons and therefore the authors need to consider alternative explanations. In addition, many of the motoneurons ventral to LG and TA motor pools could well belong to biceps motor pools. By difference to the statement made by the authors, the lower part of the biceps covers anatomically the LG in rodents and it is located in the same limb compartment. In such small animals it might be difficult to avoid virus spread, even with 1 microliter injections. The authors indicate that they confirm muscle injection specificity post-hoc after euthanizing the animals, but this is not shown. Was there any small spread to overlaying biceps? At least the authors should modify their statement to reflect the possibility of some leakage at the injection site to nearby muscles. Moreover, suggesting that all motor pools ventral to LG and TA innervate muscle compartments above the knee is not accurate. Entertaining the possibility of some, quite likely, injection leakage should not affect the main conclusions of the study if estimates suggest they occur in low numbers. They also have a nice control with the injections at different titers. In other words, I do not see the need to try to explain ectopic motoneurons based only on motoneuron-to-motoneuron connections. This is a relatively weak given the data.5) Definition of excitatory and inhibitory interneurons. To compare the distribution of excitatory and inhibitory interneurons they introduced the GlyT2-GFP allele in Chat-cre animals. Based on anatomical studies from Andrew Todd's group suggesting extensive localization between GABAergic and glycinergic interneurons, they interpret GlyT2-off neurons as excitatory. However, the papers cited  focus on Lamina I to III inhibitory neurons and similar detailed analyses have not yet been performed in lower laminae or in the ventral horn. Moreover, one of these papers was based on the assumption that gephyrin is a marker of glycinergic synapses only, and we now know this is not the case. Therefore, the statement that all GABAergic spinal cord neurons should be GlyT2-on might be inexact. For example, ventrally projecting presynaptic GAD65 interneurons that reside in the medial dorsal horn are not GlyT2 positive and although they are labeled "presynaptic to Ia afferents" because this is one of the major functions, they also synapse on postsynaptic motoneurons (sometimes on the soma) in triadic arrangements that have been well known and reported in the electron microscopy literature for decades. Another possibility are the large GABAergic neurons from LVIII projecting contralaterally and that have been shown previously to reach lamina IX. However, the data presented here shows that contralaterally projecting neurons are almost exclusively GlyT2-off. Is there evidence of contralateral monosynaptic inputs onto motoneurons being predominantly excitatory? Can this population be explained solely by V3s? I suggest to the authors to be more conservative in their interpretation and just name these cells as non-glycinergic, not making assumptions on the excitatory nature of GlyT2-off neurons without direct evidence. For example, why not use in a similar approach the VGLUT2-Chr2-YFP transgene developed by Ole Kiehn?6) Lines 264-266. The argument that interneurons presynaptic to V0c neurons are located in superficial laminae and that most labeling shown in here is more ventral is weak. Analysis of the Figures in Zampieri et al. suggest that interneurons presynaptic to V0c distribute throughout the spinal cord and that the strong labeling in superficial laminae contains a dense staining that appears mainly axonal and probably derived from the TrkA nociceptive DRG neurons that were also abundantly transynapticaly stained from the V0c population. In addition, Figure 13 shows a more extensive distribution of Chat-cre genetic interneuronal labeling in this animal beyond pitx2 cells. The comparison with Olig2-cre is a much better approach than this explanation which might be based on partially wrong premises: distribution of interneurons presynaptic to V0c are mainly superficial laminae and interneurons targeted in Chat-cre animals are mainly pitx2 interneurons. Therefore, I do not see the need for lines 264-266 that might introduce confusion. It is unfortunate that neither Olig2 or Chat are fully restricted to motoneurons. Nevertheless, together reinforce the conclusion that the distribution of flexor vs extensor coupled interneurons do not differ in location despite the likely presence of some contamination from disynaptic jumps. I see nothing wrong accepting that there is currently no animal model for uniquely targeting motoneurons with a single gene. I recommend the authors do not discard possible contributions of disynaptic jumps because if these occur in interneurons that are so intermingled in the spinal cord, they might not be revealed by the current analyses.7) Tracing with AAV complementation methods. These experiments confirm the thesis of this manuscript, but I was surprised by the fact that even when using a motoneuron specific AAV-flex-G in Chat-cre mice there are thousands more interneurons labeled in these experiments compared to experiments using transgenesis for introducing G in motoneurons . This requires some explanation because the main argument of using transgenic animals to express G is that it would increase and normalize the number of starter motoneurons reducing variability due to the probabilistic nature of co-infections with two viruses. On the contrary, according to the data presented, co-injection of AAV-G and RV was similar or more efficient. Unfortunately, in these experiments the starter motoneurons and specificity of muscle injections were not analyzed and therefore it is difficult to compare whether motoneuron and pool specificity was comparable with the experiments using RITVA mice to introduce G in motoneurons. I agree with the authors in that "The identity and number of starter cells are the main determinants of reproducibility in rabies tracing experiments".8) In the discussion the authors propose that intracellular delivery of DNA for G and TVA followed by EnvA-coated RV could increase specificity and allow tracing from single functionally defined motoneurons. But I wonder how this experiment will work. The transsynaptic jump and expression of these genes takes days and therefore in vivo experiments allowing for enough survival time are necessary. Is motoneuron patch-clamping with in vivo experiments followed by a survival period possible? Are the authors proposing a feasible approach?9) The study is based on two muscles. Using LG or G as a model extensor and TA as a flexor. However, in reality LG is bifunctional by inserting in the femur and therefore also contributing flexion at the knee. I understand that current literature using genetic approaches routinely make these useful simplifications, but that does not make them true. It could be helpful to introduce the concept that these studies analyze the distribution of interneurons controlling two specific muscles with different roles at the ankle, and move away from strict extensor/flexors dichotomies that might not be exact.10) The important issue of how representative are the connections revealed at P1/P2 to the spinal cord in mature animals remains. This is a very significant limitation of the technique and affects all conclusions and should be carefully discussed.Reviewer #3 (Recommendations for the authors):– There are small differences which are not discussed that could provide potential explanations for discrepancies within single techniques but none will resolve the conflict since they each apply only to a single strategy. For example, the AAV promoters are different (Efa1 here and CMV in the Arber lab papers) and the ratio of Rab to G complement are different (3:1 here and 1:1 in the prior). These could fit well into the section of the Discussion (lines 449-454) because, where they could differentially affect the transmission in the co-injection to muscle experiments, they do not provide answers for discrepancies with other techniques, including the conditional virus experiments. – Restriction of cre-dependent G to ChAT or Olig neurons in the genetic strategy is not directly shown, for good reasons, but the leak in expression of Cre/tdTomato in the indirect experiment  is quite extensive and concerning. 25% of TdTomato neurons are ChAT-. Whether it be due to developmental downregulation of ChAT or ectopic cre expression, this is a significant number of interneurons that could initiate second transsynaptic jumps. The Olig2cre experiments are nice but not really helpful with this. If the leaky cre of the ChAT mouse marks V2 and V3 neurons, this would explain the similar results between the mice. The experiment in the RΦGT mouse without cre  is necessary because it shows that the RΦGT mouse likely contributes little, if at all, to the issue but this does not get at the potential problem of the leaky cre. There should be a few lines devoted to this, given the results with the tomato reporter. However, again, this provides a potential confound or reason for a discrepancy in results which only applies to some of the experiments (those using the cre-dependent strategies), and the results and conclusions drawn from these cre-dependent strategies are consistent with the other non-genetic strategies used.– The peaks of the contours in Figure 8C are indiscernible . Since this is a key replication experiment, the results should be clear for comparison. Using darker shades of the colors for contrast may be enough.– Only ankle flexor/extensors tested. The wording throughout the text reflects this, except for the Abstract. The sentence in line 8-10 could include "motor pools controlling flexion and extension of the ankle". Essential revisions:1) The connections and spatial distributions of lumbar spinal premotoneurons were studied here in neonatal mice. This is a current limitation of the technique. Most other labs have also used neonatal animals for their studies. This is potentially a significant limitation and should be carefully discussed since it limits interpretation because there is still significant ongoing synaptogenesis and refinement of connections at this age. We understand that other similar studies have similar limitations but, with the emphasis on technical issues in the paper, this limitation should be discussed.See response to Reviewer #2, comment number 102) The authors should comment on the large variability between experiments and possible sources. Examination of the number of motoneurons labeled in these experiments provided in Table 1 and Figure 12 supplements show high variability.See response to Reviewer #2, comment number 33) Figure 3—figure supplement 1 illustrates data from segments lumbar 1 to 6 in which all segments are identical in size and shape due to the normalization procedure used. To avoid confusion, the authors could show the actual sizes before normalization, and then the normalized outlines and distributions. At least make sure the main text explains these are normalized representations .See response to Reviewer #2, comment number 1, first part4) Currently it is unclear which experiments were analyzed throughout the whole lumbar enlargement and which did not. It would be beneficial to state in the Table the segments analyzed  in each experiment. Supplemental Figure 12 depicts only L4 and L5 sections. See Reviewer #2 for related comments.See response to Reviewer #2, comment number 1, second and third part5) There are questions about the authors' interpretation of ectopic motoneurons outside of expected motor pools. Please see Reviewer #2: Ectopic motoneurons.See response to Reviewer #2, comment number 46) When using a motoneuron-specific AAV-flex-G in ChAT-Cre mice, there are many more interneurons labeled in these experiments compared to experiments using transgenesis for introducing G in motoneurons. This requires some explanation because the main argument of using transgenic animals to express G is that it would increase and normalize the number of starter motoneurons reducing variability due to the probabilistic nature of co-infections with two viruses.See response to Reviewer #2, comment number 77) The peaks of the contours in Figure 8C are indiscernible . Since this is a key replication experiment, the results should be clear for comparison. Using darker shades of the colors for contrast may be enough.See response to Reviewer #3, comment number 38) The leak in Cre expression indicated by Cre/tdTomato labeling in Figure 13 is extensive with 25% of TdTomato labeled neurons being ChAT negative. This is a significant number of interneurons that could initiate second trans-synaptic jumps, which should be pointed out more clearly. If the leaky Cre of the ChAT mouse marks V2 and V3 neurons, this would explain the similar results between the mice. The experiment in the RΦGT mouse without Cre  Extending the spatial analyses to consider the locations of excitatory and inhibitory interneurons is an important component of these studies, although there are questions about the authors' identification/nomenclature of excitatory and inhibitory interneurons. Based on previous anatomical studies suggesting co-expression of GABA and glycine in spinal interneurons, the authors interpret GlyT2-off neurons as excitatory. As argued by Reviewer #2, the statement that all GABAergic spinal neurons should be GlyT2-on may be inaccurate. It is recommended that the authors be more conservative in their interpretation, for instance, by just naming these cells as non-glycinergic, and not making assumptions on these GlyT2-off neurons are excitatory interneurons without direct evidence. Please see the questions by Reviewer #2.See response to Reviewer #2, comment number 510) The argument (lines 264-266) that interneurons presynaptic to V0c neurons are located in superficial laminae and that most labeling shown in here is more ventral is weak. Reviewer #2, for the reasons outlined in the review, recommends that the authors do not discard possible contributions of disynaptic jumps that might not be revealed by the current analyses. This should be discussed.See response to Reviewer #2, comment number 611) In the Discussion the authors propose that intracellular delivery of DNA for G and TVA followed by EnvA-coated RV could increase specificity and allow tracing from single functionally defined motoneurons. The transsynaptic jump and expression of these genes takes days and therefore in vivo experiments allowing for enough survival time are necessary. Is motoneuron patch-clamping with in vivo experiments followed by a survival period possible? Are the authors proposing a feasible approach?See response to Reviewer #2, comment number 812) Although the authors made several attempts to provide explanations for the discrepancies with the previously published mapping results, the question remains – how did two groups who published independent studies using different strategies demonstrate flexor and extensor separation in the dorsal horn, when this study, using several strategies in multiple labs, show that the premotor neurons are in complete overlap? Additional small differences in methodologies could be identified which are not discussed and may provide potential explanations. There are small differences that are not discussed and could provide potential explanations for discrepancies within single techniques, but none will resolve the conflict since they each apply only to a single strategy. For example, the AAV promoters are different (Efa1 here and CMV in the Arber lab papers) and the ratio of Rab to G complement is different (3:1 here and 1:1 in the prior). These could fit well into the section of the Discussion (lines 449-454) because, where they could differentially affect the transmission in the co-injection to muscle experiments, they do not provide answers for discrepancies with other techniques, including the conditional virus experiments.See response to Reviewer #3, comment number 1Reviewer #1 (Recommendations for the authors):All the experimental approaches and data analyses are technically elegant, well designed and executed, and clearly presented with due consideration in the manuscript for any technical limitations. Overall, the experiments are rigorously performed with a design that attempts to reduce biases associated with the various RabV-based circuit tracing methods. The data, although very extensive with numerous data source files and supplemental illustrations (which is justified given the scientific problem and controversy requiring data transparency), are clearly presented. I do not have major concerns.We thank Reviewer #1 for their detailed and supportive comments. We are delighted that the reviewer finds that our data are clearly presented, because a lot of effort went into combining them in a coherent and consistent way. We hope we are adding further clarity and transparency, by making all the data available and providing a fully executable version of the manuscript in Matlab and R format.Reviewer #2 (Recommendations for the authors):I congratulate the authors for a comprehensive set of thorough analyses with a large number of experiments and experimental variables tested to shed some light into the important problem of the organization of premotor interneurons in the spinal cord. As I mentioned in the public review, I believe this is a very useful study. However, there are some important details that need to be clarified such that confusion is not introduced for potential future users of this complex methodology to map premotor interneurons in the spinal cord.1) Figure 3-figures supplement 1 illustrates data from segments lumbar 1 to 6. All segments are identical in size and shape because the normalization procedure used by the authors and explained in methods. This is misleading to most readers which will be largely of unaware of spinal cord anatomy. I recommend showing the actual realistic sizes, before normalization, and then the normalized outlines and distributions. Also, please make sure the main text explains these are normalized representations . I believe this normalization was not done in Tripodi et al., who seem to have just added all cells in 2D projections with the original positional values  independent of lumbar segments.We have added another supplementary figure  showing the pooled data from all the high titre LG and TA injections split across segments before normalization. The size of the idealized spinal cord profiles has been scaled using the six normalization points described in the methods. While the area occupied by premotor interneurons is obviously narrower in the rostral segments, the distributions are still overlapping at all segmental levels, confirming that the normalization procedure does not skew the distributions. In order to keep the text lighter, we have chosen to specify that the data have been scaled to the dimension of individual sections in all the legends of the figures where interneurons distributions are shown , but if preferred by the reviewer, we can transfer this note to the text body. It is difficult to perform a direct comparison of the Tripodi data, because we have not been given access (despite numerous requests) to the raw data and their methods section fails to specify whether their data were normalized , since they only mention that the position of labelled neurons were reconstructed using the “reference axes” plug-in run in the processing suite “Qu”, none of which have been made available.Tripodi argues that medio-lateral differences are more apparent rostrally, which makes sense because the narrower lateral extension of L1 compared to L4/L5. Figure 2C only shows TA and LG interneurons distributions overlapping in L4 and L5, but in the supplemental figure it looks there are many more TA interneurons in L1 compared to LG. Is it possible to illustrate the distribution of these interneurons in an horizonal projection of all lumbar segments as in 2C? Are TA interneurons indeed more abundant in L1 and because of this they bias more medially when all segments are added together without normalization? Is the normalization obscuring one further explanation for the differences among the studies?ChAT::Cre; RϕGT and Olig2::Cre; RϕGT injections we were only showing the transverse projection  in order to keep a compact figure layout. However, we agree with the referee that this does not give a direct visual representation of the pooled experiments and still leaves the possibility of different relative abundance of LG or TA interneurons in different segments. In order to clarify this, we have added the longitudinal pooled representation of the data as a supplement to the figures where only the transverse sections were shown . Scrolling through the new figures, it is clear that there is no rostrocaudal bias in the density of premotor interneurons belonging to flexors and extensor muscles. Therefore, the mediolateral segregation cannot have originated from differences in the density of premotor interneurons along the rostrocaudal axis. The new supplementary figures are now called in the text at the appropriate points .In the original version of the paper we have chosen to show the full rostrocaudal projections only for individual experiments  in the main text, but we added supplementary figures and data for all the experiments in which rostrocaudal distributions are shown. In the figures describing pooled experiments for On a related noted I was not sure which experiments were analyzed throughout the whole lumbar enlargement and which did not. It will be good to state in the Table the segments analyzed  in each experiment. Supplemental Figure 12 depicts only L4 and L5 sections.Depending on the exact position of the starting level for sectioning, the representations along the rostrocaudal axis do not encompass exactly the same range across labs . The whole set of supplementary figures to Figure 12 represent the data in their entirety and therefore already contain the information requested by the reviewer. We would leave it as an editorial choice whether to repeat this information also in the summary table, which is already quite extensivemas this would require some changes in format and probably font size.2) Lines 122-124. I do not understand why the authors argue that lack of identification of G complementation prevents identification of starter neurons. With the transgenic approaches they are using, all motoneurons should express G and precise identification of starter cells thus only depends on how many motoneurons are infected. Of course, this is difficult to estimate because progressive cell death, as indicated in the manuscript. I recommend deleting lines 122 and 123 and just state that it is difficult to identify all starter motoneurons unambiguously because the possibility of cell death.This observation is correct. Our statement is valid only when referring to methods requiring the use of a helper virus in order to express G , but not when genetic tools are used . We have removed the sentence as suggested by the reviewer.3) Variability in cell numbers: Close examination of the number of motoneurons labeled in these experiments provided in table 1 and figures 12 supplements show high variability. For example, LG muscle injections in Chat-cre with high titer virus at UCL or UoG vary from 8 motoneurons to 110 (even when taking away differences in counting methods and section sampling), with more motoneurons in experiments labeled as UCL compared to UoG. Similar variability occurs in recovered interneurons (356 to 2574). MDC experiments in Olig2-cre mice seem to be in between. It is remarkable that the dorso-ventral and medio-lateral distribution are the same despite such wide variations in interneurons labeled. This strengthens the conclusions, but I would suggest the authors comment on the large variability between experiments and possible sources.We agree that the efficiency of rabies infection exhibits large variability, both at the level of primary and secondary infected neurons. This is an important point that deserves to be highlighted. We have added an in-depth analysis of this issue and an extra supplementary figure, following the methods described in Tran-Van-Minh et al., BioRxiv 2022 (doi: https://doi.org/10.1101/2022.06.08.494952). The new text is now at lines 204-219, describing Figure 4—figure supplement 3. Briefly, we observe that the number of interneurons vs number of putative starter cells follows a power law, similar to what has been shown in the brain by combining data from many different groups, summarized in the paper cited above. We have no explanation for the large difference in the number of starter neurons, other than subtle differences in the site of injection. However, we observed that reduced titre invariably leads to a reduced number of starter cells (~5 against ~ 35 on average between low and high titre experiments), while the relation between interneurons and primary infected neurons follows a predictable pattern.Moreover, from Materials and methods it was unclear whether in injections of UoG were also done that UCL and then processed at Glasgow. It seems this was the case but it could be made clearer, given that in the table they are labeled as a different institution.We have changed the initial sentence in the methods section (now on lines 575-579) to make it clearer where the injections were performed and the tissue analysed. The injections labelled as UoG were performed in the Beato Lab at UCL and the tissue was processed at Glasgow University (Todd and Maxwell labs). The injections labelled as UCL were performed independently and 1-2 years later in the Brownstone lab (again at UCL) where the tissue was processed.4) Ectopic motoneurons. The authors argue that ectopic motoneurons outside the expected motor pools are caused mainly by motoneuron-to-motoneuron connections and transynaptic transfer, this might be for some, however in Figure 2C and Figure 12 supplements some are in the medial motor column. As far as I know there are no reports of recurrent motor axon collaterals between LMC and MMC motoneurons and therefore the authors need to consider alternative explanations.We were equally surprised by the observation of some motoneurons labelled in the medial motor column. This has happened in a subset of experiments: 170427n2 (n=3), 1578 (n=2), 170125n3 (n=6), 170508n7 (n=4), 1579 (n=2), 170125n7 (n=5), 170125n8 (n=1), that is 7 injections out of the 53 in which motoneurons were identified, and 23 putative medial motoneurons out of a total of 1174 labelled motoneurons. While these numbers are negligible, we agree with the reviewer that the finding is nonetheless interesting. These findings could best be explained in two different ways:10.1016/j.neuron.2014.11.024). It would be wonderful if we could see their data in their entirety for a more careful analysis.1) There are genuine synaptic contacts between the medial and lateral motor column. The statement that axons from MMCs invading LMCs have not been described does not prove that they do not exist. A current work in progress in the Beato lab is focussed on motoneuron-motoneuron connections  and it is revealing somewhat surprising rules of connectivity. While we haven’t (yet) directly looked at MMC-LMC connections, the appearance of a few no longer surprises us. Interestingly, published images from the Arber lab clearly demonstrate the converse: that LMC motoneurons are presynaptic to MMC neurons  The large cells labelled in the medial motor column are perhaps not motoneurons. In our study, we have defined motoneurons as ChAT positive cells infected by rabies, and have excluded the ones that can be clearly seen as cholinergic interneurons, such as the population of cholinergic partition neurons (V0c) located around the central canal. These neurons are known to be premotor and are labelled by rabies tracing . Therefore, it is possible that at least some of the cells that were labelled in the medial motor column were cholinergic interneurons pre-synaptic to the infected nucleus. We have inserted this caveat at lines 144-153.In addition, many of the motoneurons ventral to LG and TA motor pools could well belong to biceps motor pools. By difference to the statement made by the authors, the lower part of the biceps covers anatomically the LG in rodents and it is located in the same limb compartment. In such small animals it might be difficult to avoid virus spread, even with 1 microliter injections. The authors indicate that they confirm muscle injection specificity post-hoc after euthanizing the animals, but this is not shown. Was there any small spread to overlaying biceps? At least the authors should modify their statement to reflect the possibility of some leakage at the injection site to nearby muscles. Moreover, suggesting that all motor pools ventral to LG and TA innervate muscle compartments above the knee is not accurate. Entertaining the possibility of some, quite likely, injection leakage should not affect the main conclusions of the study if estimates suggest they occur in low numbers. They also have a nice control with the injections at different titers. In other words, I do not see the need to try to explain ectopic motoneurons based only on motoneuron-to-motoneuron connections. This is a relatively weak given the data.We have added a discussion of potential leak in the biceps muscle  at lines 156-162 and included this as a possibility. We have however kept the alternative explanation of trans-synaptic jumps between motoneurons because we have abundant functional evidence  of synaptic connectivity between motoneurons belonging to different nuclei, including those innervating the antagonist muscles studied in the present manuscript (paper in preparation). Overall, we agree with the reviewer that the exact reason behind the presence of ectopic motoneurons is less important than the fact that they are a minority and their presence is unlikely to affect the overall distribution of premotor interneurons.5) Definition of excitatory and inhibitory interneurons. To compare the distribution of excitatory and inhibitory interneurons they introduced the GlyT2-GFP allele in Chat-cre animals. Based on anatomical studies from Andrew Todd's group suggesting extensive localization between GABAergic and glycinergic interneurons, they interpret GlyT2-off neurons as excitatory. However, the papers cited  focus on Lamina I to III inhibitory neurons and similar detailed analyses have not yet been performed in lower laminae or in the ventral horn. Moreover, one of these papers was based on the assumption that gephyrin is a marker of glycinergic synapses only, and we now know this is not the case. Therefore, the statement that all GABAergic spinal cord neurons should be GlyT2-on might be inexact. For example, ventrally projecting presynaptic GAD65 interneurons that reside in the medial dorsal horn are not GlyT2 positive and although they are labeled "presynaptic to Ia afferents" because this is one of the major functions, they also synapse on postsynaptic motoneurons (sometimes on the soma) in triadic arrangements that have been well known and reported in the electron microscopy literature for decades. Another possibility are the large GABAergic neurons from LVIII projecting contralaterally and that have been shown previously to reach lamina IX. However, the data presented here shows that contralaterally projecting neurons are almost exclusively GlyT2-off. Is there evidence of contralateral monosynaptic inputs onto motoneurons being predominantly excitatory? Can this population be explained solely by V3s? I suggest to the authors to be more conservative in their interpretation and just name these cells as non-glycinergic, not making assumptions on the excitatory nature of GlyT2-off neurons without direct evidence. For example, why not use in a similar approach the VGLUT2-Chr2-YFP transgene developed by Ole Kiehn?We agree with the caution suggested by the referee. The neurons were correctly labelled as GlyT2_on or _off in the figure, but the wrong reference to excitatory and inhibitory was maintained in the text. We have now removed all instances of excitatory and inhibitory and toned down any conclusion based on the wrong identification of Glyt2_off cells as an exclusive excitatory population (entire paragraph starting at line 245).6) Lines 264-266. The argument that interneurons presynaptic to V0c neurons are located in superficial laminae and that most labeling shown in here is more ventral is weak. Analysis of the Figures in Zampieri et al. suggest that interneurons presynaptic to V0c distribute throughout the spinal cord and that the strong labeling in superficial laminae contains a dense staining that appears mainly axonal and probably derived from the TrkA nociceptive DRG neurons that were also abundantly transynapticaly stained from the V0c population. In addition, Figure 13 shows a more extensive distribution of Chat-cre genetic interneuronal labeling in this animal beyond pitx2 cells. The comparison with Olig2-cre is a much better approach than this explanation which might be based on partially wrong premises: distribution of interneurons presynaptic to V0c are mainly superficial laminae and interneurons targeted in Chat-cre animals are mainly pitx2 interneurons. Therefore, I do not see the need for lines 264-266 that might introduce confusion. It is unfortunate that neither Olig2 or Chat are fully restricted to motoneurons. Nevertheless, together reinforce the conclusion that the distribution of flexor vs extensor coupled interneurons do not differ in location despite the likely presence of some contamination from disynaptic jumps. I see nothing wrong accepting that there is currently no animal model for uniquely targeting motoneurons with a single gene. I recommend the authors do not discard possible contributions of disynaptic jumps because if these occur in interneurons that are so intermingled in the spinal cord, they might not be revealed by the current analyses.The reviewer highlights the limitation of the genetic approach for the expression of the rabies glycoprotein, that is, a single specific molecular marker for motor neurons does not exist. We have corrected our initial, wrong (as correctly pointed out by the referee) statement that ‘V0c presynaptic partners … comprise mostly interneurons located in the dorsal laminae of the spinal cord’, replacing ‘mostly’ with ‘many’ (line 295). The argument that double jumps from V0c interneurons are unlikely still holds, because if that was the case, we should see at least some of those ‘many’ interneurons – or axons, as the reviewer points out – pre-synaptic to V0c.We still think that double jumps are a rare event and, as stressed by the reviewer, this is proved by the near perfect overlap of distributions from ChAT and Olig2 mice, in which the contribution of double jumps, if any, would arise from entirely different populations of premotor interneurons, making our observations unlikely in the extreme. A substantial contribution of double jumps is further ruled out by the experiments with AAV trans-complementation of the glycoprotein, where the occurrence of double jumps is impossible. Following the reviewer’s recommendation, we have toned down the parts of the text where we discuss the possibility of double jumps, but still cite our arguments against them (see lines 445-447).7) Tracing with AAV complementation methods. These experiments confirm the thesis of this manuscript, but I was surprised by the fact that even when using a motoneuron specific AAV-flex-G in Chat-cre mice there are thousands more interneurons labeled in these experiments compared to experiments using transgenesis for introducing G in motoneurons . This requires some explanation because the main argument of using transgenic animals to express G is that it would increase and normalize the number of starter motoneurons reducing variability due to the probabilistic nature of co-infections with two viruses. On the contrary, according to the data presented, co-injection of AAV-G and RV was similar or more efficient. Unfortunately, in these experiments the starter motoneurons and specificity of muscle injections were not analyzed and therefore it is difficult to compare whether motoneuron and pool specificity was comparable with the experiments using RITVA mice to introduce G in motoneurons. I agree with the authors in that "The identity and number of starter cells are the main determinants of reproducibility in rabies tracing experiments".10.1016/j.celrep.2016.03.067). Furthermore, in the set of experiments using AAV-G, we think that the distribution observed resulted from both retrograde and anterograde tracing. This seems to have dramatically increased the number of spinal INs labelled with substantial labelling of the dorsal horn originating from transsynaptic anterograde transfer from sensory afferents in addition to the retrograde infection of premotor INs.We agree with the reviewer that the number of labelled interneurons in some of the AAV experiments is exceptionally high, but once the section sampling is taken into account, it is still in the range (5000-10000) of the most efficient among the experiments using the generic trans-complementation strategy . Knowledge of the number of motoneurons would have allowed to test whether the ratio of secondary to primary infections obeys the power law described in Figure 4—figure supplement 2 also in this set of experiments. It is known that one important determinant of efficiency is the quality of the AAV-G, and it is possible that in these sets of experiment the expression of G was particularly efficient. We do not have any direct means of comparison from muscle injections, because none of the published papers using this technique  report the raw number of infected cells, but judging by their figures it is possible that some of their experiments labelled neurons in the thousands, so not far from what we are typically seeing in our dataset. It is also worth noting that the AAV-FLEX injections were done with the enhanced glycoprotein (oG) that in the Callaway lab has been shown to increase the efficiency of trans-synaptic jumps (DOI: 8) In the discussion the authors propose that intracellular delivery of DNA for G and TVA followed by EnvA-coated RV could increase specificity and allow tracing from single functionally defined motoneurons. But I wonder how this experiment will work. The transsynaptic jump and expression of these genes takes days and therefore in vivo experiments allowing for enough survival time are necessary. Is motoneuron patch-clamping with in vivo experiments followed by a survival period possible? Are the authors proposing a feasible approach?We added a note in the discussion (lines 526-534) to specify that with the currently available techniques, this is only a gedanken experiment, one that is theoretically possible, but has never been attempted. It is mentioned here because it has been successfully performed in the brain , but the main limitation is that to our knowledge nobody has ever patched motoneurons in vivo, and sharp recordings (that are instead relatively straightforward) would not be ideal for the transfer of viral material and in all likelihood would not result in the survival of the recorded motoneurons.9) The study is based on two muscles. Using LG or G as a model extensor and TA as a flexor. However, in reality LG is bifunctional by inserting in the femur and therefore also contributing flexion at the knee. I understand that current literature using genetic approaches routinely make these useful simplifications, but that does not make them true. It could be helpful to introduce the concept that these studies analyze the distribution of interneurons controlling two specific muscles with different roles at the ankle, and move away from strict extensor/flexors dichotomies that might not be exact.We agree that the generic term ‘extensor’ is inappropriate for GS, that also contributes to knee flexion. We have now added the term ‘ankle extensor’ to the methods. We find that replacing all occurrences of ‘extensor’ with ‘ankle extensor’ would damage the flow of the text, but if required, we can do it on a second revision.10) The important issue of how representative are the connections revealed at P1/P2 to the spinal cord in mature animals remains. This is a very significant limitation of the technique and affects all conclusions and should be carefully discussed.See point 1: We agree that our map of premotor interneurons is a snapshot of the state of connectivity during the first 4-5 days following injection, when most of the jumps presumably occur and this does not necessarily reflect the actual connectivity in any given adult animal. This neonatal state in fact reflects the starting point used by spinal circuits, on which there are undoubtedly changes as mice develop, adapt to their environments, and learn new motor behaviours. As such, we have no evidence to support the idea that similar distributions of premotor interneurons would be observed at a more mature stage. We have now mentioned explicitly this caveat at the end of discussion (lines 553-561). Nonetheless, when it comes to methods comparisons and contrast with previously published results, the issue of age is not relevant, since all the rabies experiments are performed at similar ages in this study and the original study we are comparing our data to.Reviewer #3 (Recommendations for the authors):– There are small differences which are not discussed that could provide potential explanations for discrepancies within single techniques but none will resolve the conflict since they each apply only to a single strategy. For example, the AAV promoters are different (Efa1 here and CMV in the Arber lab papers) and the ratio of Rab to G complement are different (3:1 here and 1:1 in the prior). These could fit well into the section of the Discussion (lines 449-454) because, where they could differentially affect the transmission in the co-injection to muscle experiments, they do not provide answers for discrepancies with other techniques, including the conditional virus experiments. 1) We thank the reviewer for noticing two further differences in the experiments. This has now been highlighted in the discussion (lines 482-489) in the suggested paragraph, but we agree that multiple lines of evidence indicate that this is not sufficient to explain the results. The normalization issue has been raised also by reviewer #2. In answer to their comment we have added an extra figure sowing the data before normalization (see comment number 1 to reviewer #2 above). We also wish to add that it is difficult to envisage a normalization issue that differentially affects injections from one muscle and not the other. Furthermore, many of our experiments were performed with double injections in the same animals  and in these cases the lack of segregation could clearly not be due to normalization issues.– Restriction of cre-dependent G to ChAT or Olig neurons in the genetic strategy is not directly shown, for good reasons, but the leak in expression of Cre/tdTomato in the indirect experiment  is quite extensive and concerning. 25% of TdTomato neurons are ChAT-. Whether it be due to developmental downregulation of ChAT or ectopic cre expression, this is a significant number of interneurons that could initiate second transsynaptic jumps. The Olig2cre experiments are nice but not really helpful with this. If the leaky cre of the ChAT mouse marks V2 and V3 neurons, this would explain the similar results between the mice. The experiment in the RΦGT mouse without cre  is necessary because it shows that the RΦGT mouse likely contributes little, if at all, to the issue but this does not get at the potential problem of the leaky cre. There should be a few lines devoted to this, given the results with the tomato reporter. However, again, this provides a potential confound or reason for a discrepancy in results which only applies to some of the experiments (those using the cre-dependent strategies), and the results and conclusions drawn from these cre-dependent strategies are consistent with the other non-genetic strategies used.ON ChATOFF cells around the central canal in Fig13 that certainly depict either autonomic NOS+ motoneurons or V0c commissural INs that are known to express ChAT. Thus, the 25% should be considered as an upper limit, since some of the ChATOFF neurons were likely just below the threshold for detection. Furthermore, a large majority of the ChAT OFF and TdTomato ON neurons are located in the superficial laminae, where they could not contribute to di-synaptic jumps, since this area is devoid of projections from intermediate spinal interneurons. Hence the potential contribution of leaky Cre is limited, but we have now further acknowledged this issue when we describe the results of Figure 13 (lines 607-609). The observation of Cre leak is also what prompted us to use also alternative strategies (the two different AAVs and the PRV). The overlap of the distributions regardless of the methods used is evidence  that while all methods have their associated error, the magnitude of such errors is not sufficient to significantly alter any of the observed distributions.2) We agree that 25% of TdTomato neurons that are ChAT negative is concerning. However, the immunoreaction for ChAT is notoriously very delicate and heterogeneous between the very high expression in motor neurons and lower expression in other spinal IN populations that are known to express ChAT. This is notably shown by the high number of TdTomato– The peaks of the contours in Figure 8C are indiscernible . Since this is a key replication experiment, the results should be clear for comparison. Using darker shades of the colors for contrast may be enough.3) We have re-plotted this dataset using different settings for the contours in order to make the representation clearer. The paper is now also available in executable form, so that any reader can alter the settings of the contour plots.– Only ankle flexor/extensors tested. The wording throughout the text reflects this, except for the Abstract. The sentence in line 8-10 could include "motor pools controlling flexion and extension of the ankle".This has been now corrected.


In vivo and invitro analysis of key genes and the trace of interaction pathway is crucial to better understand the unique outcomes from the novel genes, forming the basis to understand the pathway that ends up causing T2DM. Afterwards, docking was executed enabling recognition of interacting residues involved in inhibition. The complex CCL5-265 and CD8A-40585 thus docked showed best results as is evident from its PCA analysis and MMGBSA calculation. There is now scope for deriving candidate drugs that could possibly detect personalized therapies for T2DM.There is a rapid rise in cases of Type-2-diabetes mellitus (T2DM) globally, irrespective of the geography, ethnicity or any other variable factors. The molecular mechanisms that could cause the condition of T2DM need to be more thoroughly analysed to understand the clinical manifestations and to derive better therapeutic regimes. Tools in bioinformatics are used to trace out key gene elements and to identify the key causative gene elements and their possible therapeutic agents. Microarray datasets were retrieved from the Gene expression omnibus database and studied using R to derive different expressed gene (DEG) elements. With the comparison of the expressed genes with disease specific genes in DisGeNET, the final annotated genes were taken for analysis. Gene Ontology studies, Protein–protein interaction (PPI), Co-expression analysis, Gene-drug interactions were performed to scale down the hub genes and to identify the novelty across the genes analysed so far.  Blood glucose is the primary source of energy and accumulates in the blood from dietary intake. Insulin, a hormone made by the pancreas, helps blood glucose to enter cells to be used up as energy . DiabeteThe discovery of biomarkers which can potentially subside the pathophysiology of the disorder can be a good motive that could inspiringly lead to the discovery of more effective therapeutic options in future . PotentiThe Medicinal plants possess secondary metabolites that are valuable sources for the treatment of many disorders and diseases . These hThere is not much substantiation that is currently available to validate the existence of disease-causing genes, and their elemental contribution to the incidence, prevalence or pathogenicity of T2DM. Integrative bioinformatic approaches were explored and understood to trace out the pathogenetically functional genes as derivative negotiators that could turn down the progression of T2DM. Differential Gene Analysis (DEG) is performed with Gene ontology analysis (Gene ontology and reactome). Pathways in a reactome are placed in a hierarchy, so as to group up details of pathways for translation, protein folding and post-translational modification into larger domains of biological function like protein metabolism. This arrangement enables Gene Ontology (GO) which is nothing but a biological process hierarchy .Protein-Protein Interactions (PPI) is used to list out the hub genes that could be causing the condition and co-expression network was used to validate the listed genes by a heat map considering the co-regulation scores of these genes . NonetheIn this study, T2DM targeting genes were analyzed for Gene Ontology studies, Protein–protein interaction (PPI), Co-expression analysis and Gene-drug interactions. It was subsequently followed by exploring interaction pathway study. The screened the top-ranked complex CCL5-265 and CD8A-40585 after docking  was furt2The approaches and steps used in the study are briefly outlined in 2.1https://www.ncbi.nlm.nih.gov/geoprofiles/) contains gene expression datasets , which is an interactive tool to analyze and compare the data of two or more sample groups under the similar experimental conditions  were identified as DEGs. Genes that portray the features of up-regulation or down-regulation in T2DM were strategically identified by an online Venn diagram tool called Venny 2.1 (http://bioinfogp.cnb.csic.es/tools/venny/).Differential gene expression is crucial for biological depiction of conditional differences between a healthy and a diseased status of the body . Differenditions . Genes t2.3https://reactome.org/). Tri-level functional prediction analysis was performed on the DEGs using the Reactome tool to understand biological process (BP) functions. Generation of heat maps for the BP pathway was calculated by - log10  and a clustered bar chart of top 15 pathways were constructed.Functional enrichment analysis is used to determine classes of genes or proteins that are over-represented in a large group of genes or proteins and may have relations with disease phenotypes. Enrichment analysis of Gene Ontology (GO) was done  to predi2.4https://string-db.org/) for those with interaction scores greater than 0.5. The network analysis was performed by the visualization of the PPI network and further understood by the tool Cytoscape 3.8.2 (A protein–protein interaction (PPI) network systematically identifies disease-related genes from the connection between those genes with similar functions. The interactive networks of the well-known DEGs among all datasets were constructed using a web-based interactive search tool called STRING  [29]. The drugs that are used are also drugs that are approved by the Food and Drug Administration (FDA) with DrugBank sourcing.A discovery of a drug-gene interaction does not necessarily indicate efficacy of any decided treatment regime with any drugs . Drugs w2.7Molecular docking and simulation studies were employed on the two selected unique targets such as CCL5 and CD8A. For this purpose, structure of CCL5 with PDB ID:6AEZ was retrieved from protein data bank database. Structure of CD8A was predicted through phyre2 protein fold recognition tool. A comprehensive library of 12,000 phytochemicals was docked with these two protein structures and top five compounds were banked on the basis of root mean square deviation (RMSD), energy function score (S_Score) and hydrogen bonding interaction (H-bond accepter or H-bond donor). MOE software was used to perform molecular docking. Before molecular docking, both the protein structures were minimized in a Molecular operating environment (MOE) by selecting the MMFF94x force field.+ Cl- salt ions. Protein ligand complex was further minimized using the steepest method of maestro with LBFGS algorithms. For both protein ligand complexes MD simulation was carried at 100 ns to check the stability of the complexes.Furthermore, to validate the molecular docking results, molecular dynamics simulation of the one best compound for each protein was performed through Desmond (version 3.6 package). The solvent model “TIP3P” with orthorhombic boundary box was used. To neutralize the protein ligand complex system, OPLS-2005 force field was used by adding the Na33.1The microarray datasets taken from NCBI - GEO were analyzed using GEO2R. The parameters were set to default and the analysis was performed with p-value < 0.05 and the Benjamini & Hochberg for decreasing false discovery rate (FDR). Quantile normalization was performed, creating a volcano plot for the condition of disease vs normal. This analysis yielded 3220 and 1395 on GSE25724 and GSE101931 datasets after annotation respectively. Out of these, 287 genes intersect in both datasets . This da3.2The datasets GSE25724 and GSE101931 had 3220 and 1395 differentially expressed genes respectively. This data was compared against the set of disease conditions in the DisGeNET database. Out of the 8296 genes found from the DisGeNET database, 67 genes were located to be expressed in the differentially expressed dataset. These 67 genes were curated and a final list of 61 genes for the comparison and identification of hub genes were used. The other 6 genes were synonymous to the list and were considered a duplicate. The associations of the above 3 datasets are explained using a Venn diagram below A.Fig. 3. The top 15 pathways had -log10 ranging from 2.56 to 3.57. The list of the pathways and its associated -log10 are provided in the clustered bar chart below  G. The mo4. The gene expression profiles from GEO database to identify the molecular mechanisms and also the key hub genes contributing to synovial inflammation with existing conditions of rheumatoid arthritis were also studied  is a protein coding gene. The CCL5 (C-C Motif Chemokine Ligand 5) gene is one of the several chemokine genes clustered on the q-arm of chromosome 17 and is a protein coding gene. Many studies suggest that an increase in serum levels of CCL5 occurs in T2DM and are closely related to postprandial hyperglycemia .In spite of the fact that docking studies have been effectively utilized in computing the limiting postures of ligands for some proteins, they refrained in evaluating ligand potential to binding. The protein rigidity in consideration overlook the conformational modification in the course of docking of certain ligands . The modWith substantial proliferation of computational biology and utilizing bioinformatics tools have forced stringent compliance in drug designing, thus helps reduction in the expenses and turn over time needed for in vivo screening and experimentations prerequisite for successful drug development . These aRecently, computational skills determined the probability of linking various molecules before their development and estimation in experimental setup. Thus, the top-ranked compounds further chosen for MD simulation which demonstrated outcomes within the acceptable range of parameters proposes the interaction results are reliable in conformation. Nonetheless, investigative efforts on drug-gene interactions in our work, potentially inspire the research activities to identify therapeutic drug candidates for T2DM.5In the current work, a new mechanism was proposed which explains the progression in pathogenesis of T2DM that might be due to the genes that disturb the pathways leading to the disease condition. The shortlisted hub genes, CD8A and CCL5 were not found in the interaction, proving it to be a unique target gene for understanding the mechanism of T2DM, hence these genes might act as potential biomarkers for diagnosis of T2DM at an early stage. The docking and simulation done proposes the candidate complex to be compact and stable. The hub genes cause disruption in cellular pathways which deeply worsens the disease condition. Experimental models may be effectively designed to aid the detection of pathogenesis, evaluation of risk, and in determining the targeted therapies with reference to the hub genes.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.