This study was to meet a practical need to design a simple tool to identify TB patients who may potentially be facing catastrophic costs while seeking TB care in the public sector. Such a tool may help prevent and address catastrophic costs among individual patients.We used data from the national TB patient cost survey in the Philippines. We randomly allocated TB patients to either the derivation or validation sample. Using adjusted odds ratios (ORs) and β coefficients of logistic regression, we developed four scoring systems to identify TB patients who may be facing catastrophic costs from the derivation sample. We validated each scoring system in the validation sample.We identified a total of 12 factors as predictive indicators associated with catastrophic costs. Using all 12 factors, the β coefficients-based scoring system  had a high validity. Even with seven selected factors with OR > 2.0, the validity remained in the acceptable range .The β coefficients-based scoring systems in this analysis can be used to identify those at high risk of facing catastrophic costs due to TB in the Philippines. Operational feasibility needs to be investigated further to implement this in routine TB surveillance. Therefore, progress towards zero catastrophic costs after the first TB-PCS is unknown. This delay may be due to a lack of planning, as implementing a national survey requires substantial time and resources. Even if countries conduct the survey every 5 years as recommended by the WHO, it does not allow national TB programmes (NTPs) to monitor the situation on a more routine and frequent basis, nor identify areas or populations that need interventions to address or prevent catastrophic costs.The WHO recommended that countries conduct a first national TB patient cost survey (TB-PCS) by 2020. The survey aims at establishing the baseline towards eliminating catastrophic costs due to TB. The WHO also suggested that governments repeat the surveys every 5 years to monitor progress.In response to such practical needs of the programme in the Philippines, this study aimed to develop a risk scoring system as a tool to identify TB patients who are currently or potentially at risk of incurring catastrophic costs. Therefore, the main objective of this study was to identify potential predictors associated with catastrophic costs due to TB using the TB-PCS data in the Philippines. Another aim was to develop and validate four risk scoring systems. The programme may use a risk scoring system as a proxy assessment tool for TB-PCS in routine TB services and surveillance to identify TB patients who may be facing catastrophic costs.10 A total of 1,912 TB patients participated in the survey. The overall proportion of the households facing catastrophic costs was 42.4%.10 The sample size calculation and results are detailed elsewhere.10This study was a secondary analysis using anonymised TB patient data collected during the Philippines’ TB-PCS. This study was conducted by the Philippines NTP and the University of the Philippines in 2016–2017.We used a split-sample comparison method to identify predictive factors, and develop and validate the scoring systems. Half of the total survey participants were randomly selected and allocated to a population group to develop the scoring systems (the derivation sample). The rest was assigned to another group to assess the validity of each scoring system .P < 0.05, and all of the statistical analyses and data visualisations were performed using R v4.0.3 .We used descriptive statistics such as median and interquartile ranges (IQRs), mean and standard deviation (SD) for continuous variables, and frequencies and percentages for categorical variables to characterise the derivation and validation samples. Logistic regression was used to identify predictive factors and develop the scoring systems from the derivation sample. Statistical significance was defined at This study did not consider the weight adjustment for drug-susceptible TB (DS-TB) and drug-resistant TB (DR-TB) because obtaining the nationally representative results was not the purpose of this study. Besides, we aimed to keep the analysis as simple as possible.P-value were removed.We first carried out univariate logistic regression analysis using the derivation sample to identify demographic, clinical and economic factors associated with households facing catastrophic costs due to TB, including coping mechanisms and perceived financial impact. We then performed a stepwise analysis with ‘forward selection’ to build the final multivariate model, in which factors with correlations or with a large 12 In Scoring System 1, an integer score ranging from 0 to 6 based on OR was assigned to each predictive factor  and β coefficients of multivariate logistic regression were used in this analysis to build scoring systems. First, we used categorical values derived from ORs based on a scoring algorithm. (Scoring System 1).We assessed the validity of both Scoring Systems 1 and 2 using only selected factors with a relatively high OR (OR > 2.0 in multivariate logistic regression) , as well as that with all the identified predictive factors . We did this to minimise operational workload for healthcare workers providing TB services.14 Finally, the overall accuracy of each scoring system was evaluated based on the receiver-operating characteristics (ROC) curve and its area under the curve (AUC).15Total scores with each scoring system were calculated for each TB patient in the validation sample. We then assessed sensitivity, specificity and positive predictive value (PPV) at different thresholds (cut-off points) in each scoring system, and the optimal cut-off point was defined based on the point at which the Youden Index (sensitivity + specificity – 1) was maximised.10 As the data were already anonymised before conducting this study, we did not use any personal identifying information throughout the analysis.Ethics clearance was not required as we used secondary data from the TB-PCS in the Philippines, which the Philippines NTP conducted in 2016–2017.n = 1,912) to the derivation sample (n = 956) and validation sample (n = 956), the unweighted proportion of TB patients incurring catastrophic costs was 47.0% in the derivation sample and 45.1% in the validation sample  and monthly household income during TB treatment (P = 0.013).No significant difference was observed in demographic, clinical, economic factors between the two sample populations except for the proportion of patients who were household breadwinners , monthly household income <US$160 , relapse or retreatment cases , household size <7 , patient was breadwinner , unemployed during TB treatment , taking TB treatment with treatment partner , ever hospitalised during TB treatment , taking loans , interrupted schooling , food insecurity , perceived financial impact   .Using all 12 factors mentioned above, the possible total score ranged from 0 to 60 in the full scale of Scoring System 1 and ranged from 0 to 109 in the full scale of Scoring System 2. For the short scale of scoring systems, seven factors with OR more than 2.0 were used. As a result, the possible total score in the short scale was from 0 to 42 in Scoring System 1 and from 0 to 86 in Scoring System 2, respectively .The AUC demonstrated that Scoring System 2 derived from β coefficients had higher validity than Scoring System 1. Scoring System 1 yielded an AUC of 0.764 (95% CI 0.735–0.794) in full scale and 0.756 (95% CI 0.726–0.787) in the short scale, while Scoring System 2 had an AUC of 0.783 (95% CI 0.754–0.812) in full scale and 0.767 (95% CI 0.737–0.798) in the short scale, showing the acceptable level of validity even in short scales .In this study, we have developed risk scoring systems for predicting catastrophic costs due to TB using data from TB-PCS conducted in the Philippines. The survey had the largest sample size among all the TB patient cost surveys conducted to date. It allowed us to perform a derivation and validation process within the nationally representative sample of TB patients. A total of 12 sociodemographic and clinical characteristics were associated with facing catastrophic costs in the derivation sample.12 For example, having both DR-TB as type of TB status and relapse/retreatment as the treatment group received the same score of 6, whereas the OR of DR-TB (OR 5.2) was two times higher than that of relapse/retreatment (OR 2.6). Also, in this study, scoring systems that used fewer risk factors showed an acceptable level of validity compared to the scoring systems with all 12 risk factors . This implies that TB patients who faced catastrophic costs might share common risk factors with high ORs, such as having DR-TB, being hospitalised and being unemployed.We found that the β coefficients-based scoring systems had a high validity to predict the occurrence of catastrophic costs in the validation sample . In OR-based scoring systems, a score of 6 was given to all the risk factors that had OR of more than 2.0. This might result in ignoring the differences in the level of effect among the risk factors that were highly associated with facing catastrophic costs.6 A monitoring method for catastrophic costs has not been set yet since the target was newly set in 2013, and the implementation of TB-PCS was just started since 2015.7 This study is the first to develop a tool to be used in routine TB services/surveillance to identify patients with TB likely to face catastrophic costs.Given the global burden of TB disease, the End TB strategy has ambitious targets of ending the global TB epidemic by 2030. One of the targets is to achieve zero catastrophic costs for TB-affected households.10 Although more than two-thirds of the households were already in poverty even before having TB, the proportion receiving a conditional cash transfer programme for the poor, the ‘Pantawid Pamilyang Pilipino Program (4Ps)’, was only 1.3% in the survey.10 This suggests that the 4Ps implemented by the Filipino Department of Social Welfare and Development (DSWD) may not have reached the TB-affected households in poverty despite their eligibility. A recent qualitative study conducted in South Africa found that even though TB patients were eligible for a disability grant, healthcare workers unintentionally or intentionally acted as gatekeepers to the grant.16 Also, the study in South Africa reported that the application process for the disability grant was time-consuming for TB patients and required extra costs, which resulted in limited access to the grant for TB patients.16 A similar issue was reported for a national disability grant for formal employers in TB-PCS in Lao People’s Democratic Republic,17 which found that a lengthy administrative process to access the grant might be a barrier for the low proportion of TB patients receiving the grant.17 It is necessary to better understand the reasons for the low proportion of 4Ps recipients among TB patients in the Filipino context. In any case, strengthening multisectoral cooperation/coordination between NTP and DSWD would certainly save TB-affected households from financial catastrophe.The first TB-PCS in the Philippines revealed that 42.4% of TB-affected households incurred catastrophic costs.18 Health workers can create scores based on interviews with patients, or patients can self-assess and provide the necessary information to create the scores. These scores can serve as a proxy indicator for the patients facing catastrophic costs and alert the health worker for those at risk while suggesting possible interventions. The scores will also feed into an algorithm for further refining the accuracy of predictions of patients who will experience catastrophic costs. The trends produced by these assessments and resulting scores will be monitored regularly by the NTP as a part of TB surveillance. Findings will periodically be shared with the multisectoral National Coordinating Committee for TB, including the DSWD, to advocate for enhanced social protection for TB patients.A scoring system in our study  will be implemented as a questionnaire in an existing mobile application (‘Care TB’) in the Philippines.19 For example, while data on HIV status were routinely collected in other TB patient cost surveys, it was not collected in the Philippines TB-PCS due to the confidentiality of HIV status in the Philippines. Patients with TB-HIV coinfection usually incur a heavier financial burden due to comorbidity and the greater frequency of facility visits.20 In such contexts, HIV status may need to be a component of scoring systems. Second, It is important to note that while risk prediction models are valuable tools, they should be applied to populations or groups with available sociodemographic and clinical data rather than being used to assess individual patients.21 Hence, the scores obtained from our TB scoring system should not be used as a sole indicator to classify each TB patient with regards to catastrophic costs. Rather, it should be used in conjunction with other clinical assessments and considerations.Our analysis had two limitations. First, identified risk factors and the scoring systems developed are specifically for Filipino settings and those who receive TB treatment in the NTP-engaged facilities. The proportion of catastrophic costs and their risk factors vary widely depending on the country context. Our scoring systems may therefore be specific to patients in the Philippines who undergo TB treatment in non-NTP-engaged facilities; however, the analytical methods used in this study can be applied to other countries.The scoring systems developed in this analysis, which are based on β coefficients, can be valuable in identifying individuals who may potentially face catastrophic costs due to TB in the Philippines. These systems may serve as a practical tool to monitor progress towards the goal of zero catastrophic costs. Further investigation is required to assess the operational feasibility of implementing and using this as a tool in routine TB surveillance systems.


CYCLIND6;1  to promote the formation of new cell layers. In the peripheral zone, auxin accumulates at sites of lateral organ primordia initiation and activates SHR expression via the auxin response factor MONOPTEROS (MP) and auxin response elements in the SHR promoter. In the central zone, the SHR-target SCL23 physically interacts with the key stem cell regulator WUSCHEL (WUS) to promote stem cell fate. Both SCL23 and WUS expression are subject to negative feedback regulation from stem cells through the CLAVATA signaling pathway. Together, our findings illustrate how SHR-dependent transcription factor complexes act in different domains of the shoot meristem to mediate cell division and auxin dependent organ initiation in the peripheral zone, and coordinate this activity with stem cell maintenance in the central zone of the SAM.Plants produce new organs post-embryonically throughout their entire life cycle. This is due to stem cells present in the shoot and root apical meristems, the SAM and RAM, respectively. In the SAM, stem cells are located in the central zone where they divide slowly. Stem cell daughters are displaced laterally and enter the peripheral zone, where their mitotic activity increases and lateral organ primordia are formed. How the spatial arrangement of these different domains is initiated and controlled during SAM growth and development, and how sites of lateral organ primordia are determined in the peripheral zone is not yet completely understood. We found that the SHORTROOT (SHR) transcription factor together with its target transcription factors SCARECROW (SCR), SCARECROW-LIKE23 (SCL23) and JACKDAW (JKD), promotes formation of lateral organs and controls shoot meristem size. SHR, SCR, SCL23, and JKD are expressed in distinct, but partially overlapping patterns in the SAM. They can physically interact and activate expression of key cell cycle regulators such as  In multicellular organisms, stem cells are the source of all tissues and organs. In contrast to animals where organs are formed during embryogenesis, plants form organs postembryonically, and they can continuously produce new organs throughout their life span. This process depends on the activity of pluripotent stem cells embedded in their shoot and root apical meristems .CYCLIND6;1  to instruct development of distinct endodermis and cortex cell layers  in stem cells (WUS expression to the organizing center via a system of receptor-like kinases and co-receptors: CLAVATA1 (CLV1), CLAVATA2 (CLV2), CORYNE (CRN) and BARELY ANY MERISTEM1-3 (BAM1-3) , a plant-specific transcription factor that plays a key role in flower primordia initiation and in primordium fate specification  . WUS traem cells . In turn(BAM1-3) . The res(BAM1-3) . Recentl(BAM1-3) . Formati(BAM1-3) , which i(BAM1-3) . The tra(BAM1-3) . ARFs bi(BAM1-3) . An incr(BAM1-3) . Auxin-d(BAM1-3) . MP playnce stem . MP direfication .CYCD6;1. We find that mutants in the SHR gene regulatory network show reduced meristem sizes and delayed cell cycle progression due to an extended G1 phase. We demonstrate that auxin via MP promotes expression of SHR and SCR in the peripheral zone, where SHR acts upstream of LFY to promote flower primordia formation. In the meristem center, members of the SHR network directly interact with the WUS-CLV circuit. Together, our study shows how mobile TFs of the SHR network establish a balance between stem cell maintenance and lateral organ initiation, by controlling cell division rates and cell fate in different domains within the SAM in an auxin dependent manner.Here, we started to unravel how organ initiation at the periphery is coordinated with stem cell behavior in the center of the SAM. We show that SHR, SCR, SCL23, and JKD act in the SAM in different expression domains with complementary and overlapping patterns, and together, they cover all the functional domains of the SAM. Interestingly, the overlapping region of the four TFs coincides with the expression domain of SHR and SCR in shoot meristem development, we analyzed the phenotypes of shr-2, scr-3, and scr-4 mutants. All mutants displayed a small rosette, dwarfed shoot phenotype and initiated fewer flowers compared to wild type  compared to WT, indicating a significant delay in lateral organ primordia initiation  in SAM development. SAMs of l number . The trahenotype  showed trimordia . Expressrimordia , indicatrimordia .JKD expression correlates with sepal identity. To address this, we used the strong lfy-12 mutant, which generates mostly sepal-like organs in the flowers   . Only CY the SAM . CYCD1;1rimordia , while Crimordia . pCYCD6; the SAM . Importa and JKD . In shr-imordia, .shr-2 mutant lateral organ primordia compared to WT  core motifs (TGTCTC) . The mock control SAMs expressing pPIN1:PIN1-GFP showed a wide distribution of PIN1-GFP, which relocated into a ring shaped domain in deeper regions of the meristem 3d after treatment with 100 µM NPA  , which c(TGTCTC) . Treatmereatment , but the0 µM NPA . Concomin domain . Similarreatment . NPA tre complex . TogetheMP, SHR, and SCR partially overlapped in lateral organ primordia . Treatment of these plants with dexamethasone (DEX) allows the nuclear entry of MP-GR. Within 4 hr of DEX treatment, ubiquitously expressed MP resulted in increased expression levels of pSHR:SHR-YFP and pSHR:ntdTOMATO while SHR retained its WT expression domain  in the SHR promoter can control expression of the reporter genes mVenus or Luciferase upon Agrobacterium-mediated transient expression in Nicotiana benthamiana leaves. pSHR(WT):mVenus was co-infiltrated with p35S:MP, or with p35S:GUS as a negative control. We observed strong mVenus expression from the WT-SHR promoter in the presence of p35S:MP, which was about sixfold higher than upon coexpression of p35S:GUS  , which is directly activated by MP . Since Mrimordia , and we ed to WT . We furtY::GLFY) . In WT, to WTand . This in mutants , and we  defects . We concSCL23 in the SAM using the transcriptional reporter pSCL23:H2B-YFP, and the functional translational reporter line pSCL23:SCL23-YFP  or pRPS5A (pRPS5A:SCL23-mVenus) promoter. Both UBIQ10 and RPS5A promoters drive high-level and widespread expression of the fused reporter gene. However, we observed SCL23-mVenus fluorescence confined to the lateral organ primordia and not in the meristem center, where endogenous SCL23 is normally expressed (SHR or SCR in the SAM (The closest homologue of SCR is the GRAS-family TF SCARECROW-LIKE23 (SCL23). We investigated the expression pattern of CL23-YFP . pSCL23:rimordia . The trareporter , suggest the SAM . We thenrimordia . Some cem center , indicat/scl23-2 . Using t the SAM . Genetic stature . To furtxpressed . We foun the SAM , implyin the SAM . We prop the SAM , and thaGRAS family transcription factors HAM1 and HAM2 were shown to physically interact with WUS to promote shoot stem cell proliferation and repress CLV3 expression in the organizing center  is crucial for unraveling the complexities of SAM development and organ formation. In this study, we investigated the role of the  the SAM . We foun the SAM . Additioral zone . These fral zone . IntriguSAM size , suggestin roots . NotablySHR, SCR, SCL23, and JKD are expressed across all functional domains of the SAM, and mutant analyses emphasized an important role of the SHR network in SAM stem cell homeostasis and organogenesis. We found that both SHR and SCL23 proteins are mobile in the SAM, with SCL23 exhibiting hypermobility, similar to its behavior in the RAM , and not in the organizing center itself (where miRNA171 levels are low and WUS interacts with HAMs)  . Unlike g center . Thus, tSHR would serve as a central integrator, which perceives input from auxin signaling, regulates the expression level and locality of other network components such as SCR, SCL23 and JKD, and controls, at least in one instance via CYCD6;1, local cell division patterns and growth. The SHR regulatory network has been reused in evolutionary times for generating and specifying new cell layers in the RAM, and for maintenance of the quiescent center; the SHR network is also in part responsible for coordination of cell fate decisions in the developing vascular system. Although the individual wiring diagrams might differ, the key interactions within this versatile network appear highly conserved  conditions (16 hr light / 8 hr dark) at 21 °C. Most plants used in this study were in the Columbia (Col-0) background, except for: scr-4 (WS) (wus-7 (Landsberg erecta (L.er.) background .r-4 (WS)  and wus-)  plants were transformed with Agrobacterium tumefaciens (strain GV3101 pMP90 pSoup) containing the respective destination vectors using the floral dipping method (Nicotiana benthamiana plants were grown 4–5 weeks in the greenhouse and subsequently used for transient leaf epidermis cell transformation.The entry plasmids in this study (Table 5) were generated by gDNA or cDNA sequences that were amplified with Phusion High-Fidelity PCR polymerase using primers described in g method . TransgeAgrobacterium tumefaciens strains (strain GV3101 pMP90 pSoup) harbouring relevant reporter constructs were cultured overnight with shaking at 28 °C in 5 ml dYT  with appropriate antibiotics. Cell cultures were adjusted to an optical density (OD600) of 0.3 and then harvested by centrifugation at 4000xg for 10 min. The pellet was resuspended in infiltration buffer  and incubated for 2 h at 4 °C. For coexpression of two transgenes, the corresponding transformed A. tumefaciens were mixed equally. The resuspensions were infiltrated into the abaxial leaf surface of the 3–4 weeks old N. benthamiana using a needle-less syringe. Plants transformed with constructs under the control of the 35 S promotor were used for analyses 4 days after infiltration.pSHR:SHR-YFP, pSCR:SCR-YFP and pCYCD6;1:GFP expression analysis following auxin and auxin transport inhibitor treatment were performed by dipping 30-day-old plants inflorescence once in 10 µM  once or with 100 µM NPA twice (at 0 hr and 7 hr). For Dexamethasone treatment pUBIQ1:MP-GR inflorescence meristems were treated with 10 μM DEX only once and were imaged 5 hr after treatment.For hormone and dexamethasone treatments, plants were grown in soil. For RNA isolation experiments, N. benthamiana leaves were co-transformed with different pSHR:mVenus-NLS and the effector plasmids p35S:GUS or p35S:MP (Table 6). Four days after infiltration, the leaves were processed for further analysis using imaging with a Zeiss LSM780 using the same settings for all conditions.SHR promoter (Table 7) were co-infiltrated into N. benthamiana leaves together with the effector plasmids p35S:GUS or p35S:MP (Table 6). Luciferase activities were measured four days after infiltration with the NightOwl luminescence system (Berthold). As substrate for the luciferase reaction, 5 mM D-Luciferin potassium salt solution was used.The different reporter constructs with firefly luciferase reporter (FLUC) under the control of the different versions of All confocal images were obtained by using a Zeiss LSM780 confocal microscope . For time series analysis, settings were established in the beginning on mock samples and were kept standard during the experiment. Shoot meristems were manually dissected by cutting of the stem, removing the flowers, and were stained with 1 mg/ml DAPI or 5 mM propidium iodide (PI). Individual populations of 2–20 plants were analyzed.Green fluorescence was excited with an argon laser at 488 nm and emission was detected at 490–530 nm, yellow was excited with an argon laser at 514 nm and emission was detected at 520–550 nm, and red was excited with Diode-pumped solid state (DPSS) lasers at 514 nm and detected at 570–650 nm. PI was excited at 561 nm by DPSS lasers and detected by PMTs at 590–650 nm. DAPI was excited at 405 nm with a laser diode and detected at 410–480 nm.N. benthamiana leaf epidermal cells were examined using a Zeiss LSM780 confocal microscope . FRET was measured via mVenus fluorescence intensity increase after photobleaching of the acceptor mCherry (FRET = (EFRET = (mVenusafter – mVenusbefore)/mVenusafter x 100). All photobleaching experiments were performed in the nucleus. The displayed data were obtained from at least three independent experiments. mCherry . The perIn vivo FRET-FLIM experiments were measured using a Zeiss LSM780 confocal microscope  equipped with a single-photon counting device (PicoQuant HydraHarp400) and a linear polarized diode laser (LDH-D-C-485).YFP donor fluorophores was excited with a 485 nm  pulsed polarized diode laser. Excitation power was adjusted to 1,5μW. Emitted light was separated by a polarizing beam splitter and detected with a band-pass filter (520/35 AHF) by Tau-SPADs (PicoQuant).Images were acquired with a resolution of 256x256 pixel, zoom 8, a pixel size of 0.1 μm and a dwell time of 12.6μs. For each measurement, 100 frames were taken and the intensity-weighted mean lifetimes τ (ns) were calculated using PicoQuant SymPhoTime64 software applying a bi-exponential fit. The displayed data were obtained from at least 5 independent experiments.For qRT-PCR, RNA was isolated from dissected inflorescence meristems using RNeasyMini kit (Qiagen). First strand cDNA was synthesized with 1 μg of RNA cDNA using the Superscript III Kit (Invitrogen). Quantitative real-time PCR was performed with 10-fold diluted cDNA using The SsoAdvancedTM Universal SYBR Green Supermix (Bio-Rad). The mean and standard error were determined using three biological replicates with three technical replicates each. Expression levels were normalized to the references genes TIP41-like (At4g34270) and SAND-domain protein (AT2G28390) . PrimersRosettes and plants were analyzed by taking photographs using Canon EOS400D camera with an EF-S 60 mm Canon ZOOM lens of plants growing on soil. Inflorescences were analyzed by taking pictures using stereo microscope (Nikon SMZ25). The inflorescence plastochron was obtained by calculating the average time separating the emergence of 2 successive flower above stage 15 emerging after plant bolting. For SAM area measurement, 30DAG plants growing under LD conditions were used. The primary inflorescence was dissected and imaged using LSM780. The SAM area measurement was done by Fiji.Arabidopsis Information Resource (TAIR), (http://www.arabidopsis.org/). Indigo was used for the luciferase assay imaging. Statistical analyses and box plots were realized with GraphPad Prism v 8. For visualization. Using the open-source software MorphoGraphX (MGX) software (https://morphographx.org/)   the surfhx.org/) . The vishx.org/)  was donehx.org/) . All Sta This is a valuable study of Arabidopsis shoot apical meristem maintenance and organ initiation, with a focus on how SHR, SCR, JKD, and SCL23, four transcription factors initially characterized in root meristems, are deployed in a different context. The imaging, genetics and FRET-FLIM evidence supporting the claims of the authors is compelling. The work will be of interest and importance for plant developmental biologists. public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) 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, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Jürgen Kleine-Vehn as the Senior Editor. The reviewers have opted to remain anonymous.Thank you for submitting your article "The Arabidopsis SHORTROOT network coordinates shoot apical meristem development with auxin dependent lateral organ initiation" 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) Although the amount of data included is impressive, the current length and organization of the manuscript obscure the story. Making clearer connections between sections, defining a clear message, streamlining (removing) peripheral information and reducing unnecessary background information are required. Specific suggestions about how to cut or combine material made by individual reviewers are excellent guidelines. .2) As this is a highly dense study, the overview figure, collecting the results and situating them in a broader perspective is needed. However, the model figure (13) was not very helpful in understanding the regulator relationships among the GRAS factors and the differences/commonalities between the RAM and SAM. One potential solution would be to place the diagram of RAM factors  beside the SAM diagram and to discuss what is and isn't the same and if the differences map on to different things the meristems do, or to the presence of a unique TF. Additional detail should be added. For example, the expression pattern of SCR and SCL23 seems not to overlap and yet these proteins are drawn in the same complex. The inclusion of SCL23 in the core complex with SHR and SCR is also inconsistent with LOF phenotypes reported as being additive (line 460). Indicating which interactions are experimentally validated in the SAM and which are putative interactions, would avoid ambiguous interpretation. The authors could also add different shades for the domains where the protein moves so the reader can easily distinguish between transcriptional and translational expression.3) Several issues need to be resolved with the JKD model. One reviewer notes that the SHR-SCR interaction seems to happen in different cells than the SCR-JKD interaction. Are representative images and/ or protein-protein imaging data that could support the conclusion of the authors that SHR-SCR-JKD are localized in the same cell type and that is where they interact? A second reviewer was not clear on the model for JKD influencing the SCR and SHR dimers and activities in the meristem. PlaCCI expression appears to be measured in epidermis, but JKD isn't there, so is the presumed longer G1 phase indirect and due to the proposed sequestering of SHR-SCR? Given the lower levels of JKD relative to SHR and SCR, is this a reasonable hypothesis? Also starting on line 276, it was not clear how the data for JKD-SCR indicate the behavior with SHR-SCR. Lifetime measurements seem to go down the same about for FRET data in 6H and 4E. It was not clear how this assay could distinguish between binary and ternary complexes of SHR-SCR-JKD.4) In general, the conclusion statements at the end of the paragraphs oversimplify and overstate the evidence. For example, line 165-7 "We conclude that SHR and SCR promote cell cycle progression in the meristem by controlling the G1 phase, which could account for the observed reduction in SAM size and delay in organ initiation in the PZ of shr and scr mutants." Or line 375-6 "We conclude that MP acts through SHR to promote lateral organ initiation". More experimental evidence would be required to make these firm conclusions, but an alternative would be substituting the phrase "our data are consistent with a model that" for "we conclude".5) Some conclusions are not supported by data. For example, the authors conclude that SHR and cofactors drive cell proliferation through CYCD6, but their evidence is that "We found that the number of cell layers in the L3 of lateral organ primordia is strongly reduced in shr-2 mutants compared to WT." It would be essential to examine the SAM of the cycd6;1 mutant to make this conclusion.Reviewer #1 (Recommendations for the authors):This long manuscript contains many well done experiments, but the overall story seems underwhelming relative to the data, and could use some streamlining in the text as well as better set up of expectations for when SAM and RAM would be expected to use the same factors in the same way vs. when it would be surprising if they did. It felt like a missed opportunity to highlight how analysis of the GRAS TF network in another tissue extends our understanding of the regulatory logic of these factors and/or plants.1) The authors say "In the root meristem, CYCD6;1 specifically controls periclinal cell divisions and the formation of new tissue layers . We found that the number of cell layers in the L3 of lateral organ primordia is strongly reduced in shr-2 mutants compared to WT." Yet the authors didn't examine the SAM of the cycd6;1 mutant. I think it would be essential to do so to make this conclusion. My own observation is that the cycd6;1 phenotype is too mild for it to be placed at the center of the root response, and there has been some over interpretation of CYCD6 function; it may just be a very handy expression marker.2) In general, the conclusion statements at the end of the paragraphs oversimplify and overstate the evidence. For example, line 165-7 "We conclude that SHR and SCR promote cell cycle progression in the meristem by controlling the G1 phase, which could account for the observed reduction in SAM size and delay in organ initiation in the PZ of shr and scr mutants." Or line 375-6 "We conclude that MP acts through SHR to promote lateral organ initiation". More experimental evidence would be required to make these firm conclusions, but an alternative would be substituting the phrase "our data are consistent with a model that" for "we conclude".3) Figure 10. The figure shows that AREs are necessary for SHR expression, but I think the point that MP could bind these would be made better if some of the data from Figure S8B and S9B were included in this main figure.4) I did not find the model figure (13) very helpful in understanding the regulator relationships among the GRAS factors and the differences/commonalities between the RAM and SAM. One potential solution would be to place the diagram of RAM factors  beside the SAM diagram and to discuss what is and isn't the same and if the differences map on to different things the meristems do, or to the presence of a unique TF. I was also confused by the inclusion of SCL23 in the core complex with SHR and SCR because the LOF phenotypes were reported as being additive (line 460).5) I was confused by some of the explanations of the JKD experiments and results. It was not clear to me what the model is for JKD influencing the SCR and SHR dimers and activities in the meristem. PlaCCI expression appears to be measured in epidermis, but JKD isn't there, so I guess the presumed longer G1 phase must be indirect and potentially due to the proposed sequestering of SHR-SCR. But given the lower levels of JKD relative to SHR and SCR, is this a reasonable hypothesis? Also starting on line 276, it was not clear to me how the data for JKD-SCR indicate the behavior with SHR-SCR. Lifetime measurements seem to go down the same about for FRET data in 6H and 4E. I could not see how this assay could distinguish between binary and ternary complexes of SHR-SCR-JKD.Reviewer #2 (Recommendations for the authors):1. Whereas SHR and SCR mutants have strong shoot development phenotypes, shoot development in mutants of JKD and SCL23 are relatively normal. Can the authors use a dominant-negative version of SCL23, such as fusing with EAR to test the roles of scl23 in the CZ?2. Why SHR and SCR mutants have much smaller SAM (than SCL23 mutants), although they do not express in the SAM (as SCL23)?Reviewer #3 (Recommendations for the authors):Even though the authors explained the results carefully and critically, the manuscript would benefit from shortening and restructuring of the results. For example, the first two result sections as well as figure 1 and 2 can be merged, auxin-related results can be moved together, and the LFY results would fit better if they were condensed and moved to the "MONOPTEROS regulates SHR and SCR expression in the SAM" section, possibly after line 372 as an example of MP -mediated regulation of organ initiation.The authors use a very systematic approach, where they show that SHR and SCR expression overlaps and the SAM is reduced in the mutant due to fewer cells. They show that SHR and SCR are interacting, which seems to localize at P1. Given the known role of JKD in the root, the authors continue to look into JKD and show the interaction between SCR-JKD. However, the reviewer is questioning whether JKD and SHR interact in the SAM. The SHR-SCR interaction seems to happen in different cells than the SCR-JKD interaction. Are representative images and/ or protein-protein imaging data that could support the conclusion of the authors that SHR-SCR-JKD are localized in the same cell type and that is where they interact?As this is a highly dense study, the overview figure, collecting the results and situating them in a broader perspective is needed. However, the presented overview figure 13 would greatly improve if additional detail can be added. For example, the expression pattern of SCR and SCL23 seems not to overlap and yet these proteins are drawn in the same complex. Thus, indicating which interactions are experimentally validated in the SAM and which are putative interactions, would avoid ambiguous interpretation. The authors could also add different shades for the domains where the protein moves so the reader can easily distinguish between transcriptional and translational expression.The authors state that SCR does not homodimerize in the root, however, specifically in the QC SCR does form dimers as shown by Clark et al. 2020. Please rephrase this statement in the results or elaborate on the sensitivity of FRET-FLIM, which could miss the yet shown 5% SCR-SCR dimer formation. Essential revisions:1) Although the amount of data included is impressive, the current length and organization of the manuscript obscure the story. Making clearer connections between sections, defining a clear message, streamlining (removing) peripheral information and reducing unnecessary background information are required. Specific suggestions about how to cut or combine material made by individual reviewers are excellent guidelines. .We greatly appreciate all the suggestions provided. We have incorporated them into the manuscript, leading us to restructure both the figures and the results and Discussion sections. The manuscript has also been shortened, and although new data were added, we reduced the total number of figures. We hope that we thereby addressed all the reviewers and editors concerns, and submit here a vastly improved version.2) As this is a highly dense study, the overview figure, collecting the results and situating them in a broader perspective is needed. However, the model figure (13) was not very helpful in understanding the regulator relationships among the GRAS factors and the differences/commonalities between the RAM and SAM. One potential solution would be to place the diagram of RAM factors  beside the SAM diagram and to discuss what is and isn't the same and if the differences map on to different things the meristems do, or to the presence of a unique TF.We have changed the model based on your suggestions, and present a new summary figure that gives a better overview of the results. It also highlights the relationships and interactions between GRAS factors and their partners, and displays commonalities and important differences RAM and SAM.Additional detail should be added. For example, the expression pattern of SCR and SCL23 seems not to overlap and yet these proteins are drawn in the same complex.Regarding the expression patterns of SCR and SCL23, it's important to note that their expression does overlap in the primordia. This can be seen in Figure 5C-D' and Figure 5-FigSuppl1D, indicated by the arrowheads. In addition, we conclude that SCL23 protein is very mobile, which was already noted earlier by others when studying SCL23 function in the root system. We also found that while SCL23 promoter activity is confined to the organising centre of the SAM, the SCL23 fusion proteins are found in a much larger domain. We deduce from this observation (described in the text) that SCL23 protein can serve to communicate cell fate decisions between CZ and PZ.The inclusion of SCL23 in the core complex with SHR and SCR is also inconsistent with LOF phenotypes reported as being additive (line 460).. In our manuscript, we have also taken into account the functional aspects of this complex. Our results indicate that SHR plays a pivotal role as the core component in this signaling pathway. This conclusion is supported by our demonstration that shr mutants exhibit epistatic effects over scl23 mutants in double mutant combinations, as shown in Figure 5-FigSuppl2A-H'. This observation aligns with similar findings presented by Yoon et al., 2016. We hope this clarifies this point!We appreciate the opportunity to clarify these points. In our study, we have presented evidence for the interaction between SHR and SCR in the SAM. Because SHR, SCR and SCL23 proteins are all found in specific regions of the PZ, we deduce that protein complexes comprising SHR, SCR and SCL23 can form there. This is illustrated in Figure 5C-D' and Figure 5-FigSuppl1D (arrowheads). It has been shown previously that in RAM, SHR, SCR and SCL23 proteins can interact Indicating which interactions are experimentally validated in the SAM and which are putative interactions, would avoid ambiguous interpretation. The authors could also add different shades for the domains where the protein moves so the reader can easily distinguish between transcriptional and translational expression.We have incorporated distinct labeling to allow readers to easily differentiate between transcriptional and translational reporter lines, and therefore gene expression and presence of the (mobile) protein .3) Several issues need to be resolved with the JKD model. One reviewer notes that the SHR-SCR interaction seems to happen in different cells than the SCR-JKD interaction. Are representative images and/ or protein-protein imaging data that could support the conclusion of the authors that SHR-SCR-JKD are localized in the same cell type and that is where they interact? A second reviewer was not clear on the model for JKD influencing the SCR and SHR dimers and activities in the meristem.SHR, SCR, and JKD proteins are all present within the same overlapping domain, specifically in the lateral organ primordia, which is now illustrated better in Figures 3H and 3I. In this domain, JKD interacts with SCR , and in the same domain, SHR also interacts with SCR .PlaCCI expression appears to be measured in epidermis, but JKD isn't there, so is the presumed longer G1 phase indirect and due to the proposed sequestering of SHR-SCR?It is possible that JKD operates in a manner similar to its role in the root, exerting control over SHR mobility and prompting additional ectopic cell divisions. Addressing the cell cycle reporter aspect, we examined the expression of pCDT1a:CDT1a-eCFP, pHTR13:pHTR13-mCherry, and pCYCB1;1:NCYCB1;1-YFP in cells across the entire meristem excluding lateral organ primordia. To achieve this, we employed nucleus segmentation through Imaris, as detailed in the material and methods section. Figure 1-FigSuppl1P shows a visual representation of our measurements.Given the lower levels of JKD relative to SHR and SCR, is this a reasonable hypothesis? Also starting on line 276, it was not clear how the data for JKD-SCR indicate the behavior with SHR-SCR. Lifetime measurements seem to go down the same about for FRET data in 6H and 4E. It was not clear how this assay could distinguish between binary and ternary complexes of SHR-SCR-JKD.Our FRET assays can only resolve binary interactions, and not the formation of putative ternary complexes. However, our results demonstrate JKD's interaction with SCR within the same cells where SHR interacts with SCR. Based on these findings, we have inferred that JKD likely forms a complex in conjunction with both SCR and SHR. This assumption is based also on the consistency of our observations and the results published by Long et al., 2017.4) In general, the conclusion statements at the end of the paragraphs oversimplify and overstate the evidence. For example, line 165-7 "We conclude that SHR and SCR promote cell cycle progression in the meristem by controlling the G1 phase, which could account for the observed reduction in SAM size and delay in organ initiation in the PZ of shr and scr mutants." Or line 375-6 "We conclude that MP acts through SHR to promote lateral organ initiation". More experimental evidence would be required to make these firm conclusions, but an alternative would be substituting the phrase "our data are consistent with a model that" for "we conclude".We have revised the conclusion statements throughout the manuscript and have made the necessary modifications.5) Some conclusions are not supported by data. For example, the authors conclude that SHR and cofactors drive cell proliferation through CYCD6, but their evidence is that "We found that the number of cell layers in the L3 of lateral organ primordia is strongly reduced in shr-2 mutants compared to WT." It would be essential to examine the SAM of the cycd6;1 mutant to make this conclusion.shr-2 mutant. This decrease in expression corresponds with the reduction in the number of cell layers within the L3 of the lateral organ primordia in shr-2 mutants, compared to wild-type. To further support this conclusion, we have added new data by analyzing the meristem of the cycd6;1 mutant. Our findings reveal a small, but significant reduction in both meristem size and the number of cell layers in the L3, relative to the wild type, as depicted in Figure 4-FigSuppl2 7I-N. Collectively, these findings underscore our assertion that the SHR regulatory network plays a role in activating CYCD6;1 expression, thereby promoting cell division within the lateral organ primordia.We concluded that SHR and cofactors drive cell proliferation through CYCD6;1, substantiated by the significant reduction in pCYCD6;1-GFP expression within the lateral organ primordia of the Reviewer #1 (Recommendations for the authors):This long manuscript contains many well done experiments, but the overall story seems underwhelming relative to the data, and could use some streamlining in the text as well as better set up of expectations for when SAM and RAM would be expected to use the same factors in the same way vs. when it would be surprising if they did. It felt like a missed opportunity to highlight how analysis of the GRAS TF network in another tissue extends our understanding of the regulatory logic of these factors and/or plants.We have streamlined the text and placed more emphasis on establishing clear expectations for the usage of common factors between SAM and RAM, addressing similarities and differences.1) The authors say "In the root meristem, CYCD6;1 specifically controls periclinal cell divisions and the formation of new tissue layers . We found that the number of cell layers in the L3 of lateral organ primordia is strongly reduced in shr-2 mutants compared to WT." Yet the authors didn't examine the SAM of the cycd6;1 mutant. I think it would be essential to do so to make this conclusion. My own observation is that the cycd6;1 phenotype is too mild for it to be placed at the center of the root response, and there has been some over interpretation of CYCD6 function; it may just be a very handy expression marker.see response above.2) In general, the conclusion statements at the end of the paragraphs oversimplify and overstate the evidence. For example, line 165-7 "We conclude that SHR and SCR promote cell cycle progression in the meristem by controlling the G1 phase, which could account for the observed reduction in SAM size and delay in organ initiation in the PZ of shr and scr mutants." Or line 375-6 "We conclude that MP acts through SHR to promote lateral organ initiation". More experimental evidence would be required to make these firm conclusions, but an alternative would be substituting the phrase "our data are consistent with a model that" for "we conclude".We have reviewed the highlighted sections and have made necessary adjustments to ensure that our conclusions accurately reflect the level of evidence presented.3) Figure 10. The figure shows that AREs are necessary for SHR expression, but I think the point that MP could bind these would be made better if some of the data from Figure S8B and S9B were included in this main figure.We appreciate your suggestion regarding Figure 10. While we acknowledge that including data from Figure S8B and S9B could enhance the point about MP potentially binding to AREs, we opted not to make this modification in order to maintain clarity and avoid overcrowding the main figures. Our intention was to create a balance between providing comprehensive information and ensuring figure legibility. However, we've made sure that the relevant data and information from Figure S8B and S9B are well-referenced in the text, allowing readers to easily access and understand the supporting evidence.4) I did not find the model figure (13) very helpful in understanding the regulator relationships among the GRAS factors and the differences/commonalities between the RAM and SAM. One potential solution would be to place the diagram of RAM factors  beside the SAM diagram and to discuss what is and isn't the same and if the differences map on to different things the meristems do, or to the presence of a unique TF.We have changed the model based on your suggestions, and present a new summary figure that gives a better overview of the results. It also highlights the relationships and interactions between GRAS factors and their partners, and displays commonalities and important differences RAM and SAM.I was also confused by the inclusion of SCL23 in the core complex with SHR and SCR because the LOF phenotypes were reported as being additive (line 460).shr mutant provides further support for its involvement in the same pathway, acting downstream of SHR. With this in mind, the additive phenotype indicates that complexes between SCL23, SHR and SCR also comprise other partners, with partially redundant functions.Our study establishes that SHR and SCR interact in the SAM, where the overlapping expression patterns of SHR, SCR, and SCL23 are observed, as depicted in Figure 5C-D' and Figure 5-FigSuppl1D (arrowheads). Integration of SCL23 in a complex with SHR and SCR has been experimentally validated in vivo by Long et al., 2015a. Additionally, the downregulation of SCL23 expression in the 5) I was confused by some of the explanations of the JKD experiments and results. It was not clear to me what the model is for JKD influencing the SCR and SHR dimers and activities in the meristem. PlaCCI expression appears to be measured in epidermis, but JKD isn't there, so I guess the presumed longer G1 phase must be indirect and potentially due to the proposed sequestering of SHR-SCR. But given the lower levels of JKD relative to SHR and SCR, is this a reasonable hypothesis? Also starting on line 276, it was not clear to me how the data for JKD-SCR indicate the behavior with SHR-SCR. Lifetime measurements seem to go down the same about for FRET data in 6H and 4E. I could not see how this assay could distinguish between binary and ternary complexes of SHR-SCR-JKD.It is important to note that SHR, SCR, and JKD are all expressed within the same overlapping domain, as illustrated in Figure 3H and I.shr and scr mutants, but not in jkd mutants, so we cannot speculate on a general role of JKD in cell cycle regulation beyond CYCD6;1.Addressing the cell cycle reporter aspect, we examined PlaCCI expression  in cells across the entire meristem, not only in the epidermis. To achieve this, we employed nucleus segmentation through Imaris, as detailed in the material and methods section. See Figure 1-FigSuppl1P for a visual representation of our measurements. PlaCCI was studied in wildtype, Turning to the complex formation involving SHR, SCR, and JKD, we assayed FRET-FLIM within the shared domain of these factors. Such FRET assays do not allow to distinguish between binary and tertiary complexes, so the exact composition and stoichiometry of the complexes is not known. Nevertheless, we found that JKD interacts with SCR within the same cellular context where SHR also engages with SCR, as depicted in Figure 2H and 3N, .Reviewer #2 (Recommendations for the authors):1. Whereas SHR and SCR mutants have strong shoot development phenotypes, shoot development in mutants of JKD and SCL23 are relatively normal. Can the authors use a dominant-negative version of SCL23, such as fusing with EAR to test the roles of scl23 in the CZ?jkd and scl23 mutants in the manuscript: SAM sizes of jkd-4 mutants are increased compared to the wild type (WT), indicating a significant impact on shoot development. We observed decreased SAM sizes in scl23 mutants compared to WT, underlining the role of SCL23 in shoot development.We have described distinct phenotypes associated with both 2. Why SHR and SCR mutants have much smaller SAM (than SCL23 mutants), although they do not express in the SAM (as SCL23)?The differences in SAM sizes between SHR, SCR, and SCL23 mutants can be attributed to their distinct expression patterns and potential roles in the meristem. SCR is expressed in the peripheral zone, in the L1 layer in the center of the meristem and in lateral organ primordia, while SHR is primarily expressed in the lateral organ primordia but absent from the meristem's center. On the other hand, SCL23 is expressed in both the center of the meristem and lateral organ primordia. We propose that these genes are interconnected within the same signaling system. The expression of genes in the lateral organ primordia and those in the center of the meristem suggests a coordinated communication mechanism. This interaction contributes to the coordination of primordia initiation at the meristem's periphery with cell proliferation in the meristem's center. While the exact mechanisms need further investigation, our observations suggest that these genes play roles in regulating different aspects of meristem development that collectively impact SAM size.Reviewer #3 (Recommendations for the authors):Even though the authors explained the results carefully and critically, the manuscript would benefit from shortening and restructuring of the results. For example, the first two result sections as well as figure 1 and 2 can be merged, auxin-related results can be moved together, and the LFY results would fit better if they were condensed and moved to the "MONOPTEROS regulates SHR and SCR expression in the SAM" section, possibly after line 372 as an example of MP -mediated regulation of organ initiation.We shortened and restructured the manuscript.The authors use a very systematic approach, where they show that SHR and SCR expression overlaps and the SAM is reduced in the mutant due to fewer cells. They show that SHR and SCR are interacting, which seems to localize at P1. Given the known role of JKD in the root, the authors continue to look into JKD and show the interaction between SCR-JKD. However, the reviewer is questioning whether JKD and SHR interact in the SAM. The SHR-SCR interaction seems to happen in different cells than the SCR-JKD interaction. Are representative images and/ or protein-protein imaging data that could support the conclusion of the authors that SHR-SCR-JKD are localized in the same cell type and that is where they interact?Note that the overall expression patterns of SHR, SCR, and JKD are different, but they are also expressed within an overlapping domain, see for example Fig3H,I; here, the three proteins  can interact in multimeric complexes. We measured FRET-FLIM in this domain, and found that they interact.As this is a highly dense study, the overview figure, collecting the results and situating them in a broader perspective is needed. However, the presented overview figure 13 would greatly improve if additional detail can be added. For example, the expression pattern of SCR and SCL23 seems not to overlap and yet these proteins are drawn in the same complex. Thus, indicating which interactions are experimentally validated in the SAM and which are putative interactions, would avoid ambiguous interpretation. The authors could also add different shades for the domains where the protein moves so the reader can easily distinguish between transcriptional and translational expression.We have taken this comment and similar comments by the other reviewers into account and redesigned the figure.The authors state that SCR does not homodimerize in the root, however, specifically in the QC SCR does form dimers as shown by Clark et al. 2020. Please rephrase this statement in the results or elaborate on the sensitivity of FRET-FLIM, which could miss the yet shown 5% SCR-SCR dimer formation.The sensitivity of our FRET experiments would not allow to detect a minor fraction of homodimers in vivo, we have therefore changed the text accordingly.